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Research

The Department of Biostatistics maintains an active research program both in the development of new statistical methodology and in the collaboration on important research projects in public health and the biomedical area. Since 1995 the faculty in the Department have co-authored more than 600 publications in a variety of research areas. This includes papers in statistical methodology, as well as collaborative research papers in the areas of cancer treatment and prevention, cardiovascular disease, transplantation, AIDS, childhood disease, health services and outcomes research, evaluation of diagnostic imaging systems and evaluation of treatment for psychiatric problems. Currently members of the Department are responsible for the statistical analysis of more than 100 million dollars of funding to conduct research in the public health and biomedical areas.

The Department of Biostatistics is nationally and internationally recognized for its contributions to the investigation of public health concerns associated with urban and industrial environments. These efforts are exemplified by the department's research into the evaluation of disease risk among workers exposed to potentially toxic substances. To date, large-scale follow-up studies have evaluated the health risks of more than 250,000 workers in a wide variety of industries including steel, coal mining, automobile manufacturing, chemical, fiberglass, nickel, and pharmaceutical. The methodologic approaches developed in these studies have served as models for national and international investigations involving large-scale occupational cohorts. Biostatistics faculty have also contributed to environmental quantitative risk assessment, emphasizing the use of statistical models to quantify cancer risks and the development of methodologies to facilitate the use of epidemiologic data for setting environmental standards. Statistical models developed by faculty members within the department include improved models for carcinogenesis, models to estimate reproductive risk and models to predict carcinogenicity of chemicals. Faculty members have developed a software package, the Occupational Cohort Mortality Analysis Program (OCMAP), that is used as a primary analytic tool for statistical/epidemiological research by over 300 institutions in the US and abroad. They also developed a large data base repository and retrieval system for detailed mortality data provided by the National Center for Health Statistics and the U.S. Census Bureau, called the Mortality and Population Data System (MPDS). MPDS is used regularly by the Department and outside researchers as a unique source of standard population data for comparative mortality analyses with OCMAP or other software.

Departmental faculty collaborate closely with the faculty in other GSPH departments as well as with various departments within the School of Medicine, the Pittsburgh Cancer Institute, and the VA Pittsburgh Healthcare System. Since 1975 faculty from the Department have directed the Biostatistical Center and provided biostatistical expertise for the National Surgical Adjuvant Breast and Bowel Project (NSABP). The NSABP is an internationally recognized, multidisciplinary, clinical trial research organization. The physicians and their support personnel are affiliated with major medical centers, community hospitals, and physician groups in 49 states and in 6 Canadian provinces. Since 1971, the NSABP has enrolled more than 100,000 participants in over 50 large-scale, community-based randomized clinical trials that are designed to assess treatments for breast and colorectal cancers. The Biostatistical Center is the statistical and data management coordinating center for all the NSABP treatment trials. The Center is responsible for the statistical aspects of protocol design and implementation, centralized randomization, data collection and management of patient treatment and follow-up information, and analysis of study results. The NSABP Biostatistical Center is also the statistical and data management coordinating center for the Breast Cancer Prevention Trial, a randomized double-blinded trial of 13,000 women at increased risk of breast cancer. The primary aim of this trial was to test the worth of the oral drug, tamoxifen, as a preventive for breast cancer. The trial demonstrated that tamoxifen resulted in a 50% reduction in breast cancer incidence. Recently the NSABP completed accrual of over 19,000 women into the STAR Trial which randomized women at high risk for breast cancer to receive either tamoxifen or raloxifene as chemotherapy to reduce their risk of developing breast cancer. The goal of this study is to determine if raloxifene will be as effective as tamoxifen in reducing breast cancer risk with the additional benefit of having fewer side effects than tamoxifen. It is anticipated that the final results of this trial will be available by the Spring of 2006.

Additional collaborative research in which the department supplies the quantitative component include evaluation of diagnostic imaging systems, evaluation of the etiology and treatment of ear disease in children, evaluation of treatment and survival of patients with organ transplants, development of learning tools to study tumor growth and evaluation of treatment for psychiatric patients. In addition to collaborative research the department is active in the development of new statistical methodology. The current faculty has more than 150 publications related to the development of new statistical methodology or innovative improvements in the design of biomedical studies. Active areas of methodological research include survey research, exploratory data analysis, survival analysis, missing data analysis, copulas, ROC analysis, sequential analysis and designs, case cohort studies and statistical genetics. More information on specific types of research areas in which the department is involved can be found under the categories listed below.  Select a category or scroll through this document.

NSABP Breast Cancer Treatment Trials
NSABP Colo-Rectal Cancer Treatment Trials
NSABP Prevention Trials
Statistical Methodology
Health Outcomes/Health Services Research
Statistical Genetic Research
Environmental & Occupational Epidemiology
OCMAP/MPDS Sofware Package
Radiological Imaging Systems
Otolaryngology
Psychiatric Research
Oncology Thinking Cap
Biostatistics Facility of the University of Pittsburgh Cancer Institute


NSABP - Breast Cancer Treatment

The Biostatistics Department began collaboration with the National Surgical Adjuvant Breast and Bowel Project (NSABP) in 1974. Since that time there have been more than 50,000 breast cancer patients randomized to one of more than 40 clinical trials to evaluate various treatment modalities for women with Stage I and Stage II breast cancer. Treatment modalities evaluated in these trials include chemotherapy, radiation, immunotherapy and hormonal therapy, as well as differing surgical procedures. The NSABP is internationally recognized as one of the premier clinical trials groups in the evaluation of new treatments for women with operable breast cancer. Notable accomplishments by the NSABP and in which members of the Biostatistics Department provided the primary statistical analysis include being one of the first two groups to demonstrate the efficacy of chemotherapy in the treatment of women with Stage II breast cancer (Protocol B-05), one of the first groups to demonstrate the equivalence in terms of survival of patients receiving more conservative surgery to those receiving more aggressive surgery (Protocols B-04, B-06), the first group to demonstrate the efficacy of tamoxifen in addition to chemotherapy for patients with Stage II breast cancer (Protocol B-09), and among the first groups to demonstrate the efficacy of chemotherapy for Stage I breast cancer patients with negative nodes who are estrogen receptor negative (Protocol B-13) and the efficacy of tamoxifen alone for Stage I breast cancer patients with positive nodes who are estrogen receptor positive (Protocol B-14). The observation in Protocol B-14 that tamoxifen reduced the incidence of cancer recurrence in the opposite breast was one of the major factors leading to the evaluation and subsequent demonstration of efficacy of tamoxifen as a prophylactic for breast cancer treatment.

The finding that even negative node patients benefit from more aggressive treatment and animal experiments suggesting that surgery may accelerate metastasis led NSABP to consider protocols where chemotherapy was given prior to surgery. Protocol B-18 demonstrated that preoperative chemotherapy results in the same survival as postoperative chemotherapy but often results in more conservative surgery.

Selected Publications:

Swain SM, Wilson JW, Mamounas EP, Bryant J, Wickerham DL, Fisher B, Paik S, Wolmark N. Estrogen receptor status of the primary breast cancer is predictive of estrogen receptor status of contralateral breast cancer. Journal of the National Cancer Institute, 96:516-523, 2004.

Bear HD, Anderson S, Brown A, Smith R, Mamounas EP, Fisher B, Margolese R, Theoret H, Soran A, Wickerham DL and Wolmark N. The Effect on Tumor Response of Adding Sequential Preoperative Docetaxel (Taxotere) to Preoperative Doxorubicin and Cyclophosphamide (AC): Preliminary Results from National Surgical Adjuvant Breast and Bowel Project (NSABP) Protocol B-27. Journal of Clinical Oncology, 21:4165-4174, 2003.

Jeong J, Jung S, Wieand S. A parametric model for long-term follow-up data from phase III breast cancer clinical trials. Statist Med, 22:339-352, 2003.

Smith RE, Bryant J, DeCillis A, and Anderson S. Acute myeloid leukemia and myelodysplastic syndrome following doxorubicin-cyclophosphamide adjuvant therapy for operable breast cancer: The NSABP experience. Journal of Clinical Oncology, 21(7), 1195-1204, 2003.

Fisher B, Bryant J, Dignam JJ, Wickerham DL, Mamounas EP, Fisher ER, Margolese RG, Wolmark N. Tamoxifen, Radiation Therapy or Both for Prevention of Ipsliateral Breast Tumor Recurrence After Lumpectomy in Women with Invasive Breast Cancers of Less Than or Equal 1 cm. Journal of Clinical Oncology, 20:4141-4149, 2002.

Fisher ER, Wang J, Bryant J, Fisher B, Mamounas E, Wolmark N. Pathobiology of preoperative chemotherapy: findings from the National Surgical Adjuvant Breast and Bowel Project (NSABP) Protocol B-18. Cancer, 95:681-695, 2002.

Costantino JP. The impact of Hormonal treatment on quality of life of patients with metastatic breast cancer. Clin Therapeutics 24; Suppl C:26-42, 2002.

Smith RE, Anderson SJ, Brown A, Scholnik AP, Desai AM, Kardinal CG, Lembersky BC, and Mamounas EP. Phase II trial of a doxorubicin, docetaxel, and cyclophosphamide triplet for locally advanced and metastatic breast cancer: results from NSABP trial BP-58. Clinical Breast Cancer, 3(5), 333-340, 2002

Fisher B, Anderson S, Bryant J, Margolese RG, Deutsch J, Fisher ER, Jeong JH and Wolmark N. Twenty-year follow-up of a randomized trial comparing total mastectomy, lumpectomy, and lumpectomy followed by irradiation for the treatment of invasive breast cancer. The New England Journal of Medicine, 347(16), 1233-1241, 2002.

Fisher B, Jeong JH, Anderson S, Bryant J, Fisher ER and Wolmark N. Twenty-five-year follow-up of a randomized trial comparing radical mastectomy, and total mastectomy followed by irradiation. The New England Journal of Medicine, 347(8), 567-575, 2002.

Paik S, Bryant J, Tan-Chiu E, Romond E, Park K, Browm A, Yother G, Anderson S, Smith R, Wickerham DL, Wolmark N. Real World Performance of HER2 Testing - National Surgical Adjuvant Breast and Bowel Project Experience. J Natl Cancer Inst, (94):852-854, 2002.

Singletary SE, Allred C, Ashley P, Bassett LW, Berry D, Bland KI, Borgen PI, Clark G, Edge SB, Hayes DF, Hughes LL, Hutter RVP, Morrow M, Page DL, Recht A, Theriault RL, Thor A, Weaver DL, Wieand HS, Greene FL. Revision of the American Joint Committee on Cancer Staging System for Breast Cancer. J Clin Oncol, 20:3628-3636, 2002.
Fisher, ER, Anderson, S, Tan-Chiu, E, Fisher, B, Eaton, L and Wolmark, N Fifteen year prognostic discriminants for invasive breast cancer: NSABP Protocol B-06. Cancer, 91(8): 1679-1687, 2001.

Fisher, B, Anderson, S, Tan-Chiu, E., Wolmark, N, et al. Tamoxifen and chemotherapy for axillary node negative, estrogen receptor-negative breast cancer: findings from the National Surgical Breast and Bowel Project B-23. Journal of Clinical Oncology, 93(4): 931-942, 2001.

Fisher, B, Anderson, S, Decillis, D, Dimitrov, N, et al. Further evaluation of intensified and increased total dose of cyclophosphamide for the treatment of primary breast cancer: findings from National Surgical Adjuvant Breast and Bowel Project B-25. Journal of Clinical Oncology, 17(5): 3374-3388, 1999.

Bryant J, Fisher B, Gunduz N, Costantino JP, Emir B. S-Phase Fraction Combined with Other Patient and Tumor Characteristics for the Prognosis of Node-Negative, Estrogen-Receptor Positive Breast Cancer. Breast Cancer Research and Treatment, 51: 239-253, 1998.

Dignam J, Bryant J, Wieand HS, Fisher B, Wolmark N. Early Stopping of a Clinical Trial When There Is Evidence That the Treatment will Ultimately Not Prove Beneficial: Protocol B-14 of the National Surgical Adjuvant Breast and Bowel Project. Controlled Clinical Trials, 19: 575-588, 1998.

Paik S, Bryant J, Park C, Fisher B, et al. ErbB-2 and Response to Doxorubicin in Patients with Axially Lymph Node Positive, Hormone Receptor Negative Breast Cancer. Journal of the National Cancer Institute, 90(18): 1361-70, 1998.

Fisher B, Bryant J, Wolmark N, Mamounas E, Brown A, Fisher E, Wickerham DL, Begovic M, DeCillis A, Robidoux A, Margolese R, Cruz A, Hoehn J, Lees A, Dimitrov N, Bear H. The Effect of Preoperative Chemotherapy on the Outcome of Women with Operable Breast Cancer. Journal of Clinical Oncology,16(8): 2672-2685, 1998.

Dignam JJ, Redmond CK, Fisher B, Costantino JP, Edwards BK. Prognosis among black women and white women with node-negative breast cancer: findings from two randomized clinical trials of the national surgical adjuvant breast and bowel project (NSABP). Cancer 80(1): 80-90, 1997.

Fisher, B, Anderson, S, Wickerham, DL, Decillis, A, et al. Increased intensification and increased total dose of cyclophosphamide in a doxorubicin-cyclophosphomide regimen for the treatment of primary breast cancer: findings from NSABP B-22. Journal of Clinical Oncology, 15(5): 1858-1869, 1997.

Fisher B, Anderson S, Redmond CK, Wolmark N, Wickerham DL, Cronin WM: Reanalysis and results after 12 years of follow-up in a randomized clinical trial comparing total mastectomy with lumpectomy with or without irradiation in the treatment of breast cancer. NEJM 333:1456-61, 1995.

Fisher ER, Anderson S, Redmond CK et al: Pathologic findings from the National Surgical Adjuvant Breast Project Protocol B-06: 10-year pathologic and clinical prognostic discriminants. Cancer 71:2507-2514, 1993.

Fisher ER, Anderson S, Redmond CK and Fisher B: Ipsilateral breast tumor recurrence and survival following lumpectomy and irradiation: Pathologic findings from NSABP Protocol B-06. Seminars in Surgical Oncology 8:161-166, 1992.

Fisher ER, Costantino JP, Fisher B, Redmond CK et al: Pathologic findings from the National Surgical Adjuvant Breast Project (Protocol 4): Discriminants for 15-year survival. Cancer 71:2142-2150, 1992.

Fisher B, Anderson S, Redmond CK, Wickerham DL, Wolmark N, Mamounas EP, Deutsch M and Margolese R: Significance of ipsilateral breast tumor recurrence after lumpectomy. Lancet 338:327-331, 1991.

Fisher ER, Leeming R, Anderson S, Redmond CK, Fisher B and collaborating NSABP investigators: Conservative management of intraductal carcinoma (DCIS) of the breast. Journal of Surgical Oncology 47:139-147, 1991.

Fisher B, Redmond CK, Dimitrov NV, Bowman D, Legault-Poisson S, Wickerham DL, Wolmark N, Fisher ER, Margolese R, Sutherland C, Glass A, Foster R, Caplan R and Others: A randomized clinical trial evaluating sequential methotrexate and fluorouracil in the treatment of patients with node-negative breast cancer who have estrogen-receptor-negative tumors. New England Journal of Medicine 320(8):473-478, 1989.

Fisher B, Costantino JP, Redmond CK, Poisson R, Bowman D, Couture J, Dimitrov NV, Wolmark DL, Wickerham DL, Fisher ER, Margolese R, Robidoux A, Shibata H, Terz J, Paterson AHG, Feldman MI, Farrar W, Evans J, Lickley HL, Ketner M and Others: A randomized clinical trial evaluating tamoxifen in the treatment of patients with node-negative breast cancer who have estrogen-receptor-positive tumors. New England Journal of Medicine 320(8):479-484, 1989.

Fisher B, Bauer M, Poisson R, Margolese R, Redmond C, et al: Five-Year results of a randomized clinical trial comparing total mastectomy and segmental mastectomy with or without radiation in the treatment of breast cancer. New England Journal of Medicine 312:665-673, 1985.

Fisher B, Redmond CK, Fisher ER, et al: Ten year results of a randomized clinical trial comparing radical mastectomy and total mastectomy with or without radiation. New England Journal of Medicine 312:674-681, 1985.

Redmond CK, Fisher B, Wieand HS. The methodologic dilemma in retrospectively correlating the amount of chemotherapy received in adjuvant therapy protocols with disease free survival: A commentary. Cancer Treatment Reports 67: 519-526, 1983.

Rockette HE, Redmond CK, Fisher B, and participating NSABP investigators. Impact of randomized clinical trials on therapy of primary breast cancer: The NSABP overview. Controlled Clinical Trials 3:209-225, 1982.

Fisher B, Redmond C, et al. The treatment of primary breast cancer with chemotherapy and tamoxifen. N Engl J Med 305:1-6, 1981.

Fisher B, Redmond CK, Fisher ER, and Participating NSABP Investigators. The contribution of recent NSABP clinical trials of primary breast cancer therapy to an understanding of tumor biology - an overview of findings. Cancer 46:1009-1025, 1980.

Fisher B, Sherman B, Rockette H, Redmond CK et al. Phenylalanine mustard (L-PAM) in the management of premenopausal patients with primary breast cancer: Lack of association of disease-free survival with depression of ovarian function. Cancer 44:847-857, 1979.

Fisher B, Carbone P, Economou SG, Frelick R, Glass A, Lerner H, Redmond CK, Zelen M, Band P, Katrych DL, Wolmark N, Fisher ER: L-phenylalanine mustard (L-Pam) in the management of primary breast cancer. A report of early findings. N Engl J Med 292:227-22, 1975.

Fisher ER, Gregorio R, Redmond CK, Vellios F, Sommers SC, Fisher B: Pathologic findings from the National Surgical Adjuvant Breast Project (Protocol No. 4) I. Observations concerning the multicentricity of mammary cancer. Cancer 35:247-54, 1975.

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NSABP - Colorectal Cancer Treatment Trials

The National Surgical Breast and Bowel Project (NSABP) began accrual into colo-rectal cancer trials in 1977. Since the initiation of these trials, faculty in the Biostatistics Department have been responsible for the data management and analysis and have participated in the interpretation and publication of results for these clinical trials. To date more than 12,000 patients have been randomized to eight colon cancer trials and four rectal cancer trials. The primary aim of the majority of these studies was to improve the disease free survival and survival for colorectal cancer patients undergoing a potentially curable resection of the colon or rectum. Treatment modalities evaluated included systemic chemotherapy, portal vein infusion, immunotherapy and radiation. The NSABP was one of the first groups to demonstrate that adjuvant chemotherapy could improve disease free survival and survival for patients with operable colorectal cancer, and one of the first groups to demonstrate the efficacy of leucovorin-5 FU as an effective adjuvant therapy. Leucovoren 5FU remains one of the more effective chemotherapeutic regimens for the treatment of operable colorectal cancer. The NSABP has also demonstrated in numerous trials of rectal cancer that radiation as an adjuvant to surgery controls local disease but does not improve survival.

Selected Publications:

Fisher E, Colangelo L, Wieand S, Fisher B, Wolmark N. Lack of influence of cytokeratin-positive nimi micrometastases in "negative node" patients with colorectal cancer: findings from the NSABP protocols R-01 and C-01. Diseases of the Colon and Rectum, 46:1021-1025, 2003.

Allegra CJ, Paik S, Colangelo LH, Parr AL, Kirsch I, Kim G, Klein P, Johnston PG, Wolmark N, Wieand S. Prognostic value of thymidylate synthase, Ki-67 and p53 in patients with Dukes' B and C colon cancer: an NCI-NSABP collaborative study. J Clin Oncol, 21: 241-250, 2003.

Dignam JJ, Ye Y, Colangelo L, Smith R, Mamounas E, Wieand S, Wolmark N. Prognosis after rectal cancer in Blacks and Whites participating in adjuvant therapy randomized trials. J Clin Oncol, 21:413-420, 2003.

Wolmark N, Rockette H, Mamounas E, Jones J, Wieand S, Wickerham L, Bear HD, Atkins JN, Dimitrov NV, Glass AG, Fisher ER, Fisher B: A clinical trial to assess the relative efficacy of 5-FU + leucovorin, 5-FU + Levamisole, and 5-FU + Leucovorin + Levamisole in patients with dukes B and C carcinoma of the colon: Results from NSABP C-04. J Clin Oncol 17:(11) 3553-3559, Nov 1999.

Wolmark, N., Bryant, J., Smith, R., et al. Adjuvant 5-Flourouracil and Leucovorin With or Without Interferon A 1 fa-2a In Colon Carcinoma: NSABP Protocol C-05. Journal Natl Cancer Inst 90:1810-1816, 1998.

Hyams DM, Mamounas EP, Petrelli N, Rockette HE, Jones J, Wieand HS, Deutsch M, Wickerham DL, Fisher B, Wolmark N: A clinical trial to evaluate the worth of preoperative multimodality therapy in patients with operable carcinoma of the rectum: A progress report of NSABP protocol R-03. Diseases of the Colon and Rectum 40(2): 131-139,1997.

Mayberry RM, Coates RJ, Hill HA, Click LA, Chen VW, Astin DF, Redmond CK, et al.: Determinants of Black/White Differences in Colon Cancer Survival. JNCI, 87(22), 1686-1693, 1995.

Johnston PG, Fisher ER, Rockette HE, Fisher B, Wolmark N, Drake JC, Chabner BA and Allegra CJ: The role of thymidylate synthase expression in prognosis and outcome of adjuvant chemotherapy in patients with rectal cancer. Journal of Clinical Oncology, Vol. 12, No. 12: 2640-2647, 1994.

Wolmark N, Rockette HE, Fisher B, Wickerham DL, Redmond CK, Fisher ER, Jones J, Eleftherios PM, Ore L et al: The benefit of leucovorin-modulated 5-FU as postoperative adjuvant therapy for primary colon cancer: Results from NSABP protocol C-03. Journal of Clinical Oncology, Vol. 11, No. 10: 1879-1887, 1993.

Wolmark N, Rockette HE, Wickerham DL, Fisher B, Redmond CK, Fisher ER, Potvin M, Darres RJ, Jones J, Robidoux A, Wexler M, Gordon P, Cruz AB, Horsley S, Nims TA, Thurwell M, Phillips WA, Prager D, Stern HS, Lerner HJ, Frazier TG: Adjuvant therapy of dukes' A, B and C adenocarcinoma of the colon with portal vein 5- FU hepatic infusion: preliminary results of NSABP protocol C0-2. J Clin Oncol Vol 8, No 9, 1466-1475, Sept. 1990.

Fisher ER, Park SM, Rockette H, Jones J, Caplan R, and Fisher B: Prognostic Significance of Eosinophils and Most Cells in Rectal Cancer: Findings From the National Surgical Adjuvant Breast and Bowel Project (Protocol R-01). Hum Path 20: 159-163, 1989.

Fisher B, Wolmark N, Rockette H, Redmond C, Deutsch M, Wickerham D, Fisher E, Caplan R, Lerner H, Gordon P, Feldman M, Cruz A, Legault-Poisson S, and Other NSABP Investigators: Postoperative adjuvant chemotherapy or radiation therapy for rectal cancer: results from NSABP Protocol R-01. J Nat Cancer Inst. Vol 80, March 2, :21-29, 1988.

Wolmark N, Fisher B, Rockette H, Redmond C, Wickerham D, Fisher E, Jones J, Lerner H, Lawrence W, Prager D, Wexler M, Evans R, and Other NSABP Investigators: Postoperative adjuvant chemotherapy or BCG for colon cancer: Results from NSABP Protocol C-01. Journal of the National Cancer Institute, 80, 30-36, March 2, 1988.

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NSABP - Prevention Trials

In 1992 the National Surgical Adjuvant Breast and Bowel Project initiated the Breast Cancer Prevention Trial (BCPT). The specific aim of this large-scale, randomized clinical trial was to test the hypothesis that long-term treatment with tamoxifen is effective in preventing invasive breast cancer. Breast cancer risk profiles were generated for more than 98,000 women of whom more than 57,000 met the eligibility criteria for the trial. Ultimately, more than 13,000 women at high risk from breast cancer were randomized to receive either tamoxifen or a placebo. Faculty in the Biostatistics Department had a major role in the design, conduct and analysis of this clinical trial. Since participants at the time of entry into the study are healthy and do not have disease, there is a need to have a more refined method of risk assessment than is required in most treatment trials. The results of the trial indicated almost a 50% reduction in the incidence of invasive breast cancer in the groups randomized to tamoxifen when compared to the group randomized to placebo. Not only did the findings from BCPT provide an additional option for women at high risk from breast cancer, but it contributed to the improvement of the methodology related to the assessment and implementation of prevention trials where there is the potential that risk of treatment may out weigh the benefit of treatment for some subgroups of patients.

Recently the NSABP completed accrual of over 19,000 women into the STAR Trial which randomized women at high risk from breast cancer to receive either tamoxifen or raloxifene as chemotherapy to reduce their risk of developing breast cancer. The goal of this study is to determine if raloxifene will be as effective as tamoxifen in reducing breast cancer risk with the additional benefit of having fewer side effects than tamoxifen. It is anticipated that the final results of this trial will be available by the Spring of 2006. In addition, in mid 2004, the NSABP initiated a trial to evaluate Celebrex as a therapy to prevent colon cancer by reducing the incidence of colon polyps.

Selected Publications:

Wang J, Costantino JP, Tan-Chiu E, Wickerham DL, Paik S, Wolmark N. Lower-category benign breast disease and the risk of invasive breast cancer. J National Cancer Institute, 96:616-629, 2004.

Wickerham DL, Costantino JP. Breast cancer prevention: the U.S.A. viewpoint. In: Breast Cancer Management: Application of Evidence to Patient Care, 2nd Ed. Lippincott Williams & Wilkins, Philadelphia, PA p.535-547, 2003.

Tan-Chiu E, Wang J, Costantino JP, Paik S, Butch C, Wickerham DL, Wolmark N. The effect of tamoxifen on benign breast disease in women at high risk for breast cancer: Findings from the National Surgical Adjuvant Breast and Bowel Project's Breast Cancer Prevention Trial (BCPT). J Natl Cancer Inst 95:302-7, 2003.

Vogel VG, Costantino JP, Wickerham DL, Cronin WM. NSABP update: prevention trials and endocrine therapy for DCIS. Clin Cancer Res 9:495s-501s, 2003.

Cushman M, Costantino JP, Bovill EG, Wickerham DL, Buckley L, Roberts JD, Krag DN. Effect of tamoxifen on venous thrombosis risk factors in women without cancer: The breast cancer prevention trial. Brit. J. Haematol 120:109-116, 2003.

Vogel VG, Costantino JP, Wickerham DL, Cronin WM. Tamoxifen for the prevention of breast cancer: report of the National Surgical Adjuvant Breast and Bowel Project P-1Study. J Natl Cancer Inst 94(19):1504, 2002.

Vogel VG, Costantino JP, Wickerham DL, Cronin WM, and Wolmark N. The study of tamoxifen and raloxifene: Preliminary enrollment data from a randomized breast cancer risk reduction trial. Clin Breast Cancer 3(2):153-159, 2002.

Cushman M, Costantino JP, Tracy RP, Song K, Buckley L, Roberts JD, Krag DN. Tamoxifen and cardiac risk factors in healthy women: suggestion of an anti-inflammatory effect. Arterioscler, Thromb and Vasc Biol 2001; 21:255-261.

Costantino, JP, Vogel VG. Results and Implications of the Royal Marsden and Other Trials Tamoxifen chemoprevention trials: An Alternative view. Clinical Breast Cancer 2(1):41-46, 2001.

Costantino, JP. Benefit/Risk assessment. In: Biostatistics in Clinical Trials Redmond, C., Colton, T., Ed Wiley, pg. 18-25, 2001

Gail, M., Costantino, JP. Validating and improving models for projecting the absolute risk of breast cancer. J National Cancer Institute 93:334-335, 2001.

Cushman, M., Costantino, JP, Tracey R.P., Song, K., Buckey, L., et al. Tamoxifen and novel cardiac risk factors in healthy women: evidence for an anti-inflammatory effect. Arterosder Thromb and Vasc Bio 21:255-261, 2001.

Reis, S.E., Costantino, JP, Wickerham, D.L., Tan-Chiu, E., Wang, J., et al. Cardiovascular effects of tamoxifen in women with and without heart disease. J National Cancer Institute 93:16-21, 2001.

Gail MH, Costantino JP, Bryant J, Croyle R, Freedman L, Helzlsouer and Vogel V. Weighing the risks and benefits of tamoxifen for preventing breast cancer. J Natl Cancer Inst 91:1829-46, 1999.

Costantino JP, Gail MH, Pee D, Anderson S, Redmond CK, Benichou J. Validation studies for models to project the risk of invasive and total breast cancer incidence. J Natl Cancer Inst 91:1541-48, 1999.

Day R, Ganz PA, Costantino JP, Cronin WM, Wickerham DL, Fisher B. Health-related quality of life and tamoxifen in breast cancer prevention: A report from the National Surgical Adjuvant breast and bowel project P-1 study. J Clin Oncol 17:2659-2669, 1999.

Fisher, B., Costantino, J., Wickerham, D.L., et al. Tamoxifen for Prevention of Breast Cancer: Report of the National Adjucant Breast and Bowel Project Pl Study. Journal National Cancer Inst. 90:1371-1388, 1998.

Ganz, P.A., Day, R., Costantino, J., Compliance with Quality of Life Data Collection in the National Surgical Adjuvant Breast and Bowel Project Breast Cancer Prevention Trial. Statistics In Medicine 17:613-622, 1998.

Fisher B, Costantino J. Highlights of the NSABP Breast Cancer Prevention Trial. Cancer Control 4:78-86, 1997.

Redmond CK, Costantino JP. Design and Current Status of NSABP Breast Cancer Prevention Trial. Recent Results Cancer Research, 140:309-317, 1996.

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Statistical Methododology

The Department of Biostatistics has been active in the development of new statistical procedures for use in the public health and medical areas. The current faculty has more than one hundred publications in peer reviewed statistical journals. This number does not include the more than fifty additional methodological papers appearing in medical journals and book chapters written to familiarize various disciplines with statistical concepts and procedures. General methodological areas of interest include survival analysis, multivariate methods, sequential methods, missing data analysis, ROC curve analysis and regression diagnostics. Often the methodological research has developed from applied research in which the faculty is participating . This is particularly true in the area of clinical trials and occupational and environmental biostatistics.

Parametric survival models have related mostly to the lognormal (1) and Weibull models (2-5). Considerable work has also been done on more general approaches such as the log rank test (6), the proportional hazards model (7-11), and extensions to multivariate failure time data (12) or nonproportional hazards models (13-14). In some cases methodological work in survival analysis was motivated by the collaborative research in which the faculty participates (15-17).

Developmental work has also been done on sequential methods as they relate both to Phase II (18, 19) and Phase III clinical trials (20-23). Additional related work includes the design of a Phase II trial within a Phase III trial (24), two stage designs for both binary outcomes (25) and survival (26-27). Members of the Department have also been active in the development of methods useful in the design of experiments. These include the previously mentioned sequential methods and two stage designs as well as methods for multiple comparisons (28-30) and sample size estimation (31-32).

The range of interest in methodological problems has varied over time as well as over individual faculty members. Thus, there are publications on more classical areas such as estimation theory (7, 8, 33-36), nonparametric statistics (37-41), multivariate methods (42-65) and linear models (46-48) as well as more recently developed areas such as frailty models (49-50), smoothing splines (51-53), missing data analysis (54-56), semiparametric models (56-57), computer intensive methods (58-60), microarrays (61-62), machine learning (63), copulas (64), and neural networks (65).

Additional areas of activity include regression diagnostics, ROC curve analysis and meta analysis. Regression diagnostics include methods to assess multicollinearity (66, 67, 69) influence diagnostics for various models (2, 10, 68) and residual analysis (70). Several recent papers apply to regression diagnostics for the Cox model (69, 71, 72). ROC curve methodology is being increasingly applied to the evaluation of diagnostic imagining systems and the predictive capability of a statistical model in the clinical setting. There are several papers related to various aspects of these problems (73-78). Meta analysis is a set of procedures and methods which can be used to combine multiple studies. Members of the department have been active in addressing some of the methodological and conceptual issues in meta analysis (79, 80) as well as applying it to a variety of areas of research (81-84).

References

1. Schneider H, and Weissfeld A. Interval Estimation for Accelerated Life Tests Based on the Lognormal Model. Journal of Quality Technology, 21(1):24-31, 1989.
2. Weissfeld LA, and Schneider H. Influence Diagnostics for the Normal Linear Model with Censored Data. Statistics and Probability Letters, 9:67-73, 1990.
3. Schneider H, and Weissfeld LA. Interval Estimation Based on Censored Samples for the Weibull Distribution. Journal of Quality Technology, 21(3):19-186, 1989.
4. Rockette HE, Antle CE, Klimko LA. Maximum likelihood estimation with the Weibull model. J Amer Stat Assn, 1974.
5. Klimko LA, Rockette HE, Antle CE, Rademaker FA. Upper bounds for the power of invariant tests for the exponential distribution with Weibull alternatives. Technometrics, 1975.
6. Jeong J. Efficiency of log-rank test under dependent censorship. Communications in Statistics: Theory and Methods, 32:1197-1211, 2003.
7. Jeong J, and Oakes D. On the asymptotic relative efficiency of estimates from Cox’s model. Sankhya, 65:411-421, 2003.
8. Jeong J, and Oakes D. Effects of different hazards ratios on asymptotic relative efficiency of estimates from Cox’s model. Communications in Statistics - Theory and Methods, in press.
9. Liu K, Mazumdar S, Stone R, Dew MA, Houck PR, and Reynolds CF. Accounting for covariate measurement error in a Cox model and analysis of recurrence depression. Journal of Psychiatric Research, 35:177-185, 2001.
10. Weissfeld LA. Influence Diagnostics for the Proportional Hazards Model. Statistics and Probability Letters, 10:411-417, 1990.
11. Liu K, Stone RA, Mazumdar S, Houck PR, Reynolds CF. Covariate measurement error in the Cox model: a simulation study. Communications in Statistics, in press.
12. Wei LJ, Lin DY, and Weissfeld LA. Regression Analysis of Multivariate Incomplete Failure Time Data by Modeling Marginal Distributions. Journal of the American Statistical Association, 84:1065-1073, 1989.
13. Lee EC, and Weissfeld LA. Assessment of Covariate Effects in Aalen’s Additive Hazard Model. Statistics in Medicine, 17:983-998, 1998.
14. Valenta Z, and Weissfeld LA. Estimation of the Survival Function for Gray’s Piecewise-Constant Time-Varying Coefficients Models. Statistics in Medicine, 21:717-727, 2002.
15. Jeong J, Jung S, Wieand S. A parametric model for long-term follow-up data from phase III breast cancer clinical trials. Statist Med, 22:339-352, 2003.
16. Mazumdar S, Berhane Z, Weissfeld L, Begley A, Dew MA, Houck PR, and Reynolds CF. Survival models with time-varying coefficients: A flexible approach to the analysis of psychiatric survival data. Psychopharmacology Bulletin, 36(4):84-91, 2002.
17. Roberts MS, Angus DC, Bryce CL, Valenta Z, Weissfeld L. Survival after liver transplantation in the United States. A disease-specific analysis of the UNOS database. To appear in Liver Transplantation.
18. Chang MN, Therneau TM, Wieand HS, Cha SS. Designs for group sequential phase II clinical trials. Biometrics, 43:865-874, 1987.
19. Chang MN, Wieand HS, and Chang VT. The bias of the sample proportion following a group sequential phase II clinical trial. Statist in Med, 8:563-570, 1989.
20. Therneau TM, Wieand HS, Chang MN. Optimal designs for a grouped sequential binomial trial. Biometrics, 46:771-781, 1990.
21. Wieand HS, Schroeder G, O’Fallon JR. Stopping when the experimental regimen does not appear to help. Statist in Med, 13:1453-1458, 1994.
22. Dignam J, Bryant J, Wieand S, Fisher B, Wolmark N. Early stopping of a clinical trial when there is evidence of no treatment benefit: Protocol B-14 of the National Surgical Adjuvant Breast and Bowel Project. Controlled Clinical Trials, 19:575-588, 1998.
23. Mor MK, and Anderson S. A Bayesian Group Sequential approach for multiple endpoints. To appear in The Sequential Analysis Journal, 2004.
24. Schaid DJ, Ingle JN, Wieand HS, Ahmann DL. A design for phase II testing of anti-cancer agents within a phase III clinical trial. Controlled Clinical Trials 9:107-118, 1988.
25. Wieand HS, Therneau T. A two-stage design for randomized trials with binary outcomes. Controlled Clinical Trials 8:20-28, 1987.
26. Schaid DJ, Wieand HS, Therneau TM. Optimal two-stage screening designs for survival comparisons. Biometrika, 77:507-513, 1990.
27. Wahed A and Tsiatis AA. Optimal estimator for the survival distribution and related quantities for treatment policies in two-stage randomization designs in clinical trials. Biometrics, Vol. 60, No. 1, pp 124-133, 2004.
28. Bryant J, Fox G. Some Comments on a Class of Simultaneous Inference Procedures in ANCOVA. Communications in Statistics, 14:2511-2530, 1985.
29. Bryant J, Bruvold N. Multiple Comparison Procedures in the Analysis of Covariance. Journal of the American Statistical Association, 75:874-880, 1980.
30. Bryant J, Paulson A. An Extension of Tukey’s Method of Multiple Comparisons to Experimental Designs with Random Concomitant Variables. Biometrika, 63:631-638, 1976.
31. Ahnn S, and Anderson SJ. Sample size determination in complex clinical trials comparing more than two groups for survival endpoints. Statistics in Medicine, 17:2525-2534, 1998.
32. Ahnn S, and Anderson SJ. Sample size calculations for comparing k survival distributions. Statistics in Medicine, 14:2273-2282, 1995.
33. Sinha BK, Wieand HS. Admissibility and minimaxity of a MVUE when the parameter space is restricted to integers. Calcutta Statist Assoc Bulletin, 25:165-168, 1975.
34. Wieand HS. On a condition under which the Pitman and Bahadur approaches to efficiency coincide. Ann Statist, 4:1003-1011, 1976.
35. Sinha BK, Wieand HS. Admissibility and inadmissability of the MLE when the parameter space is restricted to integers. Calcutta Statist Assoc Bulletin, 26:113-116, 1977.
36. Ghosh JK, Sinha BK, Wieand HS. Second order efficiency of the MLE with respect to any bounded, bowl-shaped loss function. Ann Statist, 8:506-521, 1980.
37. Sinha BK, Wieand HS. Multivariate nonparametric tests for independence. J Multi Anal, 7:572-583, 1977.
38. Sinha BK, Wieand HS. Bounds on the efficiencies of four commonly used nonparametric tests of location. Sankhya, Ser B, 39:121-129, 1977.
39. Bush JR, Wieand HS. An asymptomatically optimal nonparametric statistic optimal for testing equality of two normal population means and variables. Communications in Statist A, 11:1-12, 1982.
40. Weissfeld L, Wieand HS. Bounds on the efficiencies of some commonly used nonparametric tests. Communications in Statist A, 13:1741-1758, 1984.
41. Wieand HS, Gail MH, James B, James K. Nonparametric procedures for comparing diagnostic tests with paired or unpaired data. Biometrika, 76:585-592, 1989.
42. Miller B, Mazumdar S. Estimation of parameters of a polynomial model under intra class correlation structure for incomplete longitudinal data. Communications in Statistics, Theory and Methods, 15(5):1549-1559, 1986. [Errata (1987), 16, 1541].
43. Sinha BK, Wieand HS. Union-intersection test fo the mean vector when the covariance matrix is totally reducible. J Am Statist Assoc, 74:340-343, 1977.
44. Tate RL, Bryant JL. Parameter Sensitivity for Discriminant Analysis. Multivariate Behavioral Research, 21:411-427, 1986.
45. Tian W, and Anderson SJ. Markov chain models fo multivariate repeated binary data analysis. Communications in Statistics, Simulation and Computation, 29(4), 2000.
46. Schneider H, and Weissfeld LA. Estimation in Linear Models with Censored Data. Biometrika, 73:741-745, 1986.
47. Weissfeld LA, and Schneider H. Inferences Based on the Buckley-James Procedure. Communications in Statistics - Theory Methods, 16(6):1773-1788, 1987.
48. Mazumdar S, Li CC, Bryce GR. Correspondence between a Linear Restriction and a Generalized Inverse in Linear Model Analysis. American Statistician, 34(2):103-105, 1980.
49. Day R, Bryant J, Lefkopoulou M. Adapting Bivariate Frailty Models for Prediction with Application to Biological Markers as Prognostic Indicators. Biometrika, 84:45-56, 1997.
50. Oakes D, and Jeong J. Frailty models and rank tests. Lifetime Data Analysis, 4:209-228, 1998.
51. Berhane K, and Weissfeld LA. Inference in spline based models fo the multiple time-to-event data: with applications to a breast cancer prevention trial. To appear in Biometrics, 2003.
52. Anderson SJ, and Jones RH. Smoothing splines for longitudinal data. Statistics in Medicine, 14:1235-1248, 1995.
53. Anderson SJ, Jones RH, and Swanson GD. Smoothing polynomial splines for bivariate data. SIAM Journal of Scientific and Statistical Computing, 11(4), 1990.
54. Tang G, Little RJA, and Raghunathan TE. Analysis of Multivariate Missing Data with Nonignorable Nonresponse. Biometrika, 90(4):747-764, 2003.
55. Mazumdar S, Liu K, Houck PR, and Reynolds CF. Intent-to-treat analysis for longitudinal clinical trials: coping with the challenge of missing values. Journal of Psychiatric Research, 33:87-95, 1999.
56. Zhang Z, Rockette HE. On maximum likelihood estimation in parametric regression with missing covariates. Journal of Statistical Planning and Inference, (in press) 2004.
57. Kong L, Jianwen C and Sen PK. Weighted estimating equations for semiparametric transformation models with censored data from a case-cohort design. Biometrika, 2004, in press.
58. Sussman NB, Arena VC, Yu S, Mazumdar S, Thampatty BP. Decision tree SAR models for developmental toxicity based on an FDA/TERIS database. SAR and QSAR in Environmental Research, 14(2):83-96, 2003.
59. Arena VC, Sussman NB, Mazumdar S, Yu S, Macina OT. The utility of structure-activity relationship (SAR) models for prediction and covariate selection in developmental toxicity: comparative analysis of logistic regression and decision tree models. SAR and QSAR in Environmental Research, 15(1):1-18, 2004.
60. Tseng GC, and Wong WH. Tight Clustering: A Resampling-based Approach for Identifying Stable and Tight Patterns in Data. Biometrics, 2004 (in press).
61. Tseng GC, Oh M-K, Rohlin L, Liao JC, and Wong WH. Issues in cDNA microarray analysis : quality filtering, channel normalization, modes of variations and assessment of gene effects. Nucleic Acids Research, 29:2549-2557, 2001.
62. Hwang J-J, Allen PD, Tseng GC, Lam C-W, Fananapazir L, Dzau VJ, and Liew C-C. Microarray gene expression profiles in dilated and hypertrophic cardiomyopathic end-stage heart failure. Physiological Genomics, 10:31-44, 2002.
63. Shen X, Tseng GC, Zhang X, and Wong WH. On psi-Learning. Journal of American Statistical Association, 98:724-734, 2003.
64. Phelps A, and Weissfeld LA. AA Comparison of Dependence Estimators in Bivariate Copula Models. Communications in Statistics - Simulation and Computation, 26(4): 1583-1598, 1997.
65. Landsittel D, Singh H, Arena VC and Anderson SJ. Null distribution of the likelihood ratio statistic for feed-forward neural networks. The Journal of Modern Applied Statistical Methods, 1(2):333-342, 2002.
66. Weissfeld LA. A Multicollinearity Diagnostic for Models Fit to Censored Data. American Statistical Association, 18:2073-2085, 1989.
67. Weissfeld LA, and Sereika S. A Multicollinearity Diagnostic for Discrete Response Models. Communications in Statistics, 20(4):1183-1198, 1991.
68. Weissfeld LA, and Schneider H. Influence Diagnostics for the Normal Linear Model with Censored Data. Australian Journal of Statistics, 32:11-20, 1990.
69. Lee KY, and Weissfeld LA. A Collinearity Diagnostic for the Cox Proportional Hazards Model with Time Dependent Covariate. Communications in Statistics - Simulation and Computation, 25(1): 41-59, 1996.
70. Weissfeld LA, and Schneider H. Residual Analysis for Parametric Models Fit to Censored Data. Communications in Statistics - Theory and Methods, 23(8):2283-2298, 1994.
71. Jung S, Wieand HS. Analysis of goodness-of-fit test for Cox regression model. Statistics and Probability Letters, 41:379-382, 1999.
72. Chang CC, and Weissfeld LA. Normal Approximation Diagnostics for the Cox Model. Biometrics, 55(4):1114-1119, 1999.
73. Beam CA and Wieand HS. A statistical method for the comparison of a discrete diagnostic test with several continuous diagnostic tests. Biometrics, 47:907-919, 1991.
74. Jung SH, Wieand HS, Cha SS. A statistic for comparing two correlated markers which are prognostic for time to an event. Statist in Med, 14:2217-2225, 1995.
75. Emir B, Wieand S, Su J, Cha S. Analysis of Repeated Markers Used to Predict Progression of Cancer. Statist in Med, 17:2563-2578, 1998.
76. Emir B, Wieand S, Jung S, Ying Z. Comparison of diagnostic markers with repeated measurements: a non-parametric approach. Statist in Med, 19:511-523, 2000.
77. Obuchowski NA, Rockette HE. Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: An ANOVA approach with dependent observations. Commun Statistics, 24(2):285-308, 1995.
78. Rockette HE, Li W, Brown ML, Britton CA, Towers JT, Gur D. A statistical test to assess rank order ROC imaging studies. Academic Radiology, 8(1):24-30, 2001.
79. Sankey SS, Weissfeld LA, Fine MJ, Kapoor WN. An Assessment of the Continuity Correction for Sparse Data in Meta-Analysis. Communications in Statistics - Simulation and Computation, 25(4): 1031-1056, 1996.
80. Rockette HE, Redmond CK. Issues related to combining data from multiple randomized clinical trials. Presented at “Medical Statistics: Design and Analysis of Clinical Trials”, Institute of Mathematics, Oberwolfach, Germany, February 1987. Published in Recent Results Cancer Research, 99-104, 1988.
81. Miles PG, Vig PS, Weyant RJ, Forrest TD, and Rockette HE. Craniofacial structure and obstructive sleep apnea syndrome - a qualitative analysis and meta-analysis of the literature. Orthod Dentofac Orthop, 109:163-172, 1996.
82. Rockette HE, Gur D, Campbell WL, Thaete FL. Utilization of meta analysis in the evaluation of imaging systems. Academic Radiology, 1:63-69, 1994.
83. Fine MJ, Smith MA, Carson CA, Meffe F, Sankey SS, Weissfeld LA, Detsky AS, Kapoor WN. Efficacy of Pneumococcal Vaccination in Adults: A Meta-Analysis of Randomized Controlled Trials. Archives of Internal Medicine, 154(23):2666-2677, 1994.
84. Nowell PD, Mazumdar S, Buysse DJ, Dew MA, Reynolds CF, and Kupfer DJ. Benzodiazepines and Zolpidem for Chronic Insomnia: A Meta-Analysis of Treatment Efficacy. Journal of the American Medical Association, 278(24):2170-2177, 1997.
85. Starr TB, Gause CK, Youk AO, Stone RA, Marsh GM, Collins JJ. A risk assessment for occupational acrylonitrile exposure using epidemiology data. Risk Analysis 2004;24:587-601.
86. Youk AO, Stone RA, Marsh GM. A method for imputing missing data in longitudinal studies. Annals of Epidemiology 2004;14:354-361.

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Health Outcomes/Health Services Research

Health outcomes/health services research is a pragmatic, multidisciplinary approach for assessing clinical decision making, access to care, cost containment, resource allocation, quality of care, and patient-centered medical outcomes and patient satisfaction. Health services research also includes observational studies to document the role of patient, provider and site characteristics in delivery of medical care, as well as intervention studies to improve the performance of recommended processes of care. The department currently conducts health services research in diverse settings including the Veteran's Administration (VA) Healthcare System, the UPMC Healthcare System, local health insurance providers, pediatric trauma centers and the manufacturing industry. At the Center for Health Equity Research and Promotion at the Pittsburgh VA , multiple studies are planned or ongoing to improve care for vulnerable populations of veterans. In collaboration with the UPMC Healthcare System and other sites, the Pneumonia Patient Outcomes Research Team study documented current practices and developed a medical practice guideline for patients with community acquired pneumonia (CAP). A series of subsequent studies evaluated interventions to improve the delivery of care, including the admission decision, choice and duration of antibiotics, length of stay, and the discharge decision. The department has been involved in the identification of under- and over-users of health resources in a managed care setting, reliability studies on medical record abstraction, survey methods to characterize health care providers, and assessment of patient satisfaction. Research areas include pediatric trauma and registry development. Identification and evaluation of risk factors and treatment of pediatric trauma; such as developing pediatric trauma scoring systems for survival and disability. Registry development projects include a designing a national trauma registry for children (NTRC) and a project to develop, maintain and analyze an occupational medical claims registry.

Selected Publications:

Aujesky DA, Stone RA, Obrosky DS, Yealy DM, Auble TE, Meehan TP, Graff LG, Fine JM, Fine MJ. How good is the agreement between retrospectively and prospectively collected data comprising the pneumonia severity index? Journal of Clinical Epidemiology (to appear).

Aujesky DA, Auble TE, Yealy DM, Obrosky DS, Stone RA, Fine MJ. Prospective comparison of three validated prediction rules for prognosis in community-acquired pneumonia. Am J Med (to appear).

Yealy DM, Auble TE, Stone RA, Lave JR, Meehan TP, Graff LG, Fine JM, Obrosky DS, Edick SM, Hough LJ, Tuozzo K, Fine MJ. The emergency department community-acquired pneumonia trial: methodology of a quality improvement intervention. Annals of Emergency Medicine 2004; 43(6):1-13.

Fine MJ, Stone RA, Lave JR, Hough LJ, Obrosky DS, Mor MK, Kapoor WN. Implementation of an evidence-based guideline to reduce duration of intravenous antibiotic therapy and length of stay for patients hospitalized with community-acquired pneumonia. American Journal of Medicine 2003; 115:343-351.

Cassidy LD, Marsh GM, Holleran MK, Ruhl LS. Methodology to improve data quality from chart review in the managed care setting. American Journal of Managed Care 2002; 8:787-793.

Lear D, Schall LC, Marsh GM, Liu KS , Yao Y. Identification and case management in an HMO of patients at risk of preterm labor. American Journal of Managed Care 1998; 4:865-871.

Fine MJ, Stone RA, Singer DE, Coley CM, Marrie TJ, Lave JR, Hough LJ, Obrosky DS, Schulz R, Ricci EM, Rogers JC, Kapoor WN. Processes and outcomes of care for patients with community-acquired pneumonia: results from the Pneumonia Patient Outcomes Research Team (PORT) cohort study. Archives of Internal Medicine 1999; 159: 970-980.

Gleason PP, Kapoor WN, Stone RA, Lave JR, Obrosky DS, Schulz R, Singer DE, Coley CM, Marrie TJ, Fine MJ. Medical outcomes and antimicrobial costs with the use of the American Thoracic Society guidelines for outpatients with community-acquired pneumonia. JAMA 1997; 278:32-39.

Fine MJ, Medsger AR, Stone RA, Marrie TJ, Coley CM, Singer DE, Akkad H, Hough LJ, Lang W, Ricci EM, Polenik DM, Kapoor WN. The hospital discharge decision for patients with community-acquired pneumonia. Results from the Pneumonia Patient Outcomes Research Team cohort study. Archives of Internal Medicine 1997; 157:47-56.

Fine MJ, Auble TE, Yealy DM, Hanusa BH, Weissfeld LA, Singer DE, Coley CM, Marrie TJ, Kapoor WN . A prediction rule to identify low-risk patients with community-acquired pneumonia. New England Journal of Medicine 1997;336:243-250

Fine MJ, Hanusa BH, Lave JR, Singer DE, Stone RA, Weissfeld LA, Coley CM, Marrie TJ, Kapoor WN. Comparison of a disease-specific and a generic severity of illness measure for patients with community-acquired pneumonia. Journal of General Internal Medicine 1995; 10:359-368.

Stone RA, Obrosky DS, Singer DE, Kapoor WN, Fine MJ. Propensity score adjustment for pretreatment differences between hospitalized and ambulatory patients with community-acquired pneumonia. Pneumonia Patient Outcomes Research Team (PORT) Investigators. Medical Care 1995; 33(4 Suppl):AS56-66.

Cassidy LD, Potoka DA, Ford HR. “ Development of a Novel Method to Predict Disability Following Head Trauma in Children.” J Ped Surgery. 38(3): 482-485, Mar 2003.

Schall LC, Potoka DA, Ford HR. Journal of Trauma . 52(2):235-41, Feb 2001. “A New Method for Estimating Probability of Survival in Pediatric Patients Using Revised TRISS Methodology Based on Age-Adjusted Weights”.

Potoka DA, Schall LC, Ford HR. "Development of a Novel Age-Specific Pediatric Trauma Score." Journal of Pediatric Surgery . 2000; 36(1):106-112.

Potoka DA, Schall LC, Gardner M, Stafford P, Peitzman AB , Ford HR."Impact of Pediatric Trauma Centers on Mortality in a Statewide System." Journal of Trauma. August 2000.

Potoka DA, Schall LC, Ford HR. “Risk factors for splenectomy in children with blunt splenic trauma”. J. Ped Surgery. 37(3):294-9, Mar 2002.

Potoka DA, Schall LC, Ford HR et al. “Improved Functional Outcome and Decreased Length of Stay for Severely Injured Children Treated at Pediatric Trauma Centers.” Journal of Trauma . 51(5):824-32, Nov 2001

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Statistical Genetic Research

The Department has a long history of research in statistical genetics in collaboration with the Division of Statistical Genetics in the Department of Human Genetics. Focuses include linkage analysis for mapping susceptibility genes in complex diseases (1, 2, 3) and methods for mapping genes for quantitative traits using selected sibships (4, 5). Another recent focus has moved to the rapidly evolving field of bioinformatics. It includes statistical modelling and hypothesis esting for differentially expressed genes (6, 7), gene-gene interaction (8), cluster analysis (9, 10) and machine learning (11) in large scale genomic or proteomic data such as those from microarray, serial analysis of gene expression (SAGE) and mass spectrometry (12) experiments. Related research also includes exploring a mechanism to find gene markers that are associated with survival outcome and applying those in cancer clinical trials (13).

1. Mukhopadhyay N, Finegold DN, Larson MG, Cupples LA, Myers RH, Weeks DE (2003) A genome-wide scan for loci affecting normal adult height in the Framingham Heart Study. Hum Hered 55:191-201.

2. Weeks DE, Conley YP, Tsai HJ, Mah TS, Schmidt S, Postel EA, Agarwal A, Haines JL, Pericak-Vance MA, Rosenfeld PJ, Paul TO, Eller AW, Morse LS, Dailey JP, Ferrell RE, Gorin MB (2004) Age-related maculopathy: A genomewide scan with continued evidence of susceptibility loci within the 1q31, 10q26, and 17q25 regions. Am J Hum Genet 75:174-189.

3. Zondervan KT, Weeks DE, Colman R, Cardon LR, Hadfield R, Schleffler J, Trainor AG, Coe CL, Kemnitz JW, Kennedy SH (2004) Familial aggregation of endometriosis in a large pedigree of rhesus macaques. Hum Reprod 19:448-455.

4. Szatkiewicz JP, Feingold E. A powerful and robust new linkage statistic for discordant sibling pairs. American Journal of Human Genetics, 75:906-909, 2004.

5. Szatkiewicz JP, Feingold E. QTL mapping with discordant and concordant sibling pairs - new statistics and new design strategies. Genetic Epidemiology, in press.

6. George C. Tseng, Min-Kyu Oh, Lars Rohlin, James C. Liao, and Wing Hung Wong. (2001) Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Research. 29: 2549-2557.

7. Lin Y, Reynolds P, Feingold E. An Empirical Bayesian Method for Differential Expression Studies Using One-Channel Microarray Data. Statistical Applications in Genetics and Molecular Biology, 2(1):Article 8, 2003.

8. "Weakest Link Models for Detecting Small Groups of Genes to Predict Lung Cancer Survival, CAMDA'03 (Critical Assessment of Microarray Data Analysis", Richards TJ, Day RS, Kaminski N. Durham, North Carolina, November 2003.

9. George C. Tseng. (2004) A Comparative Review of Gene Clustering in Expression Profile. 8th International Conference on Control, Automation, Robotics and Vision (ICARCV). 1320-1324.

10. George C. Tseng and Wing H. Wong. (2005) Tight Clustering: A Resampling-based Approach for Identifying Stable and Tight Patterns in Data. Biometrics. 61:10-16.

11. Xiaotong Shen, George C. Tseng, Xuegong Zhang, and Wing H. Wong. (2003) On psi-Learning. Journal of American Statistical Association. 98:724-734.

12. Yingying Huang, Joseph M. Triscari, George C. Tseng, Ljiljana Pasa-Tolic, Mary S. Lipton, Richard D. Smith, Vicki H. Wysocki. (2005) Statistical Characterization of Charge State and Residue Dependence of Low Energy CID Peptide Dissociation Patterns. (submitted to Analytical Chemistry).

13. Soonmyung Paik, Steven Shak, Gong Tang, Chungyeul Kim, Joffre Baker, Maureen Cronin, Frederick L. Baehner, Michael G. Walker, Drew Watson, Taesung Park, William Hiller, Edwin R. Fisher, D. Lawrence Wickerham, John Bryant, and Norman Wolmark. New England Journal of Medicine 2004; 351:2817-26.

 

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Occupational & Environmental Epidemiology

The Department of Biostatistics has a long history of conducting studies that investigate the relationship of occupational exposure to elevated risks of cancer. Often such studies entailed the formation of industry-wide cohort studies of occupational groups with the exposures of interest. The Department has conducted more than two dozen occupational cohort studies totaling more than 250,000 workers. Occupational studies conducted include asbestos workers, coal miners, steel workers, aluminum reduction plant workers, chemical workers, man-made vitreous fiber (fiber glass and rock/slag wool) workers, nickel workers, workers in copper smelting and pharmaceutical workers. Faculty members also direct a bladder cancer screening program for workers at high risk of bladder cancer from prior occupational exposure to the potent carcinogen, beta-naphthylamine (BNA).

Previous studies conducted by faculty in the Department of Biostatistics (1) were among the first to demonstrate the relationship of lung cancer to asbestos exposure; (2) characterized the mortality patterns of coal miners; (3) provided the scientific information necessary to set standards for coke oven emissions; (4) characterized the mortality patterns for a wide range of jobs within the steel industry; (5) better delineated the relationship of lung cancer to exposure from arsenic; and (6) characterized the exposure-response relationships for respirable man-made vitreous fibers and malignant and non-malignant respiratory disease, formaldehyde and nasopharyngeal and lung cancer, and acrylonitrile and lung and brain cancer. Often the early studies conducted by the Department in these areas led to improvement in the methods used to conduct, quality control and analyze this type of epidemiological study. Faculty have also been involved in the re-analysis of large scale occupational cohort studies conducted by the National Cancer Institute (NCI) and the National Institute for Occupational Safety and Health (NIOSH).

In addition, Department faculty members have developed software programs and data base systems to facilitate the conduct of these studies. Examples of these tools, the Occupational Cohort Mortality Analysis Program (OCMAP) and the Mortality and Population Data System (MPDS) are described in other sections.

Relating general environmental exposures to excess risk is more difficult than risk assessment in an occupational group since exposures in the general environment are more difficult to characterize. Studies done by faculty in the Department of Biostatistics in the area of environmental epidemiology have related to estimating the effects of air pollution on mortality, identifying cancer risks in communities surrounding industrial plants, development of models to assess reproductive risks in animal studies, and assessment of the excess risk of cardiovascular disease resulting from smoking and alcohol usage. Examples of environmental studies include health effects investigations of communities with potential environmental exposures due to residing near point sources of pollution. These sources include, Arizona copper smelters, chemical plants in the Kanawha River valley of WV, and U.S. Environmental Protection Agency (EPA) PA Superfund sites, such as a PA chemical plant that used BNA.

Faculty in the Biostatistics Department collaborated with the faculty members in the Department of Environmental and Occupational Health in the area of computational toxicology, one of the research areas of the EOH Department. This effort has been mostly in addressing methodological issues, developing methods and related software.

Stone RA, Youk AO, Marsh GM, Buchanich JM, Smith TJ. Historical cohort study of U.S. Man-made vitreous fiber production workers IX: summary of 1992 mortality follow up and analysis of respiratory system cancer among female workers. J Occup Environ Med 2004;46:55-67.

Wei L, Mazumdar S, Arena VC and Sussman N. A resampling approach for adjustment in prediction models for covariate measurement error. Computer Methods and Programs in Biomedicine (in press).

Arena VC, Sussman NB, Mazumdar S, Yu S, Macina OT. The utility of structure-activity relationship (SAR) models for prediction and covariate selection in developmental toxicity: comparative analysis of logistic regression and decision tree models. SAR and QSAR in Environmental Research, 15(1), 1-18, 2004.

Li W, Arena VC, Sussman NB, and Mazumdar S. Model validation software for classification models using repeated partitioning:MVREP. Computer Methods and Programs in Biomedicine, 72 (2003) 81-87.

Sussman NB, Arena VC, S. Yu , Mazumdar S, Thampatty BP. Decision tree SAR models for developmental toxicity based on an FDA/TERIS database . SAR and QSAR in Environmental Research, 2003, 14(2), 83-96.

Marsh GM, Gula MJ, Roggli V, Churg A. The Role of Smoking and Asbestos Exposure in a Questionable Case of Mesothelioma. Industrial Health, 2003 (In Press).

Cassidy LD, Youk AO, Marsh GM. The Drake Health Registry Study: Cause-Specific Mortality among Workers with Probable Past Exposure to Beta-naphthylamine. American Journal of Industrial Medicine, 2003 (In Press)

Bloemen LJ, Youk AO, Bradley TD, Bodner KM, Marsh GM, Collins JJ. Lymphohematopietic Cancer among Chemical Workers Exposed to Benzene. Occupational and Environmental Medicine, 2003 (In Press).

Marsh GM, Cassidy LD. The Drake Health Registry Study: Findings from Fifteen Years of Continuous Bladder Cancer Screening. American Journal of Industrial Medicine, 43:142-148, 2003.

Talbott EO, YOUK AO, Pemu-McHugh K, Zoborowski J. Long Term Follow-Up of the Residents of the Three Mile Island Area: 1979-1998. Environmental Health Perspectives, 11(3):341-348, 2003.

Schall LC, Marsh GM, Holleran MK, Ruhl LS. Methodology to Improve Data Quality from Chart Review in the Managed Care Setting. American Journal of Managed Care, 8:787-793, 2002.

Marsh GM, Youk AO, Stone RA, Buchanich JM, Gula MJ, Smith TJ, Churg A, Colby T. Does Fiber Glass Pose a Respiratory Cancer Risk in Man? Findings from the Latest Update of the U.S. Cohort Study of Man-Made Vitreous Fiber Workers. Annals of Occupational Hygiene, 46(Supp.1): 110-114, 2002.

Marsh GM, Gula MJ, Youk AO, Cassidy LD. Bladder Cancer among Chemical Workers Exposed to Nitrogen Products and Other Substances. American Journal of Industrial Medicine, 42:286-295, 2002.

Marsh GM, Youk AO, Stone, RA, Buchanich JM, Gula MJ, Smith TJ, Quinn MM: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. I. 1992 Fiber Glass Cohort Follow-Up- Initial Findings. Journal of Occupational and Environmental Medicine 43:741-756, 2001.

Marsh GM, Youk AO, Collins J: A Reevaluation of Lung Cancer Risk in the NCI/NIOSH Acrylonitrile Cohort Study. Scandinavian Journal of Work, Environment and Health 27:5-13, 2001.

Schall LC, Buchanich, JM, Marsh GM, Bittner G: Utilizing Multiple Vital Status Tracing Services Optimizes Mortality Follow-Up in Large Cohort Studies. Annals of Epidemiology 11:292-296, 2001.

Marsh GM, Gula MJ, Youk AO, Buchanich JM, Churg A, Colby TV: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. II. Mortality from Mesothelioma. Journal of Occupational and Environmental Medicine 43:757-766, 2001.

Youk AO, Marsh GM, Stone RA, Buchanich JM, Smith TJ: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. III. Analysis of Exposure-Weighted Measures of Respirable Fibers and Formaldehyde in the Nested Case-Control Study of Respiratory System Cancer. Journal of Occupational and Environmental Medicine 43:767-778, 2001.

Stone RA, Youk AO, Marsh GM, Buchanich JM, McHenry MB, Smith TJ: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. IV. Quantitative Exposure-Response Analysis of the Nested Case-Control Study of Respiratory System Cancer. Journal of Occupational and Environmental Medicine 43:779-792, 2001.

Buchanich JM, Marsh GM, Youk AO: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. V. Tobacco Smoking Habits. Journal of Occupational and Environmental Medicine 43:793-802, 2001.

Marsh GM, Buchanich JM, Youk AO: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. VI.Respiratory System Cancer SMRs Adjusted for the Confounding Effect of Cigarette Smoking. Journal of Occupational and Environmental Medicine 43:803-808, 2001.

Smith TJ, Quinn MM, Marsh GM, Youk AO, Stone RA, Buchanich JM, Gula MJ: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Production Workers. VII. Overview of the Exposure Assessment. Journal of Occupational and Environmental Medicine 43:809-823, 2001.

Quinn MM, Smith TJ, Youk AO, Marsh GM, Stone, RA, Buchanich JM, Gula MJ: Historical Cohort Study of U.S. Man-Made Vitreous Fiber Glass Production Workers VIII. Exposure-Specific Job Analysis. Journal of Occupational and Environmental Medicine 43:824-834, 2001.

Mazumdar S, XU Y, Mattison DR, Sussman NB, and Arena VC. Statistical Methods For Reproductive Risk assessment. Hand Book of Statistics, Vol. 18. Bio-environmental and Public Heath Statistics. Editors: P. K. Sen and C.R. Rao. 2000 Elsiever Science, PP 649-671.

Arena VC, Costantino JP, Sussman NB, Redmond CK: Issues and Findings in the Evaluation of Occupational Risk in Women: The High Nickel Alloys Cohort. American Journal of Industrial Medicine, 36, 114-121, 1999.

Marsh GM, Gula MJ, Youk AO, Schall LC: Mortality Among Chemical Plant Workers Exposed to Acrylonitrile and Other Substances. American Journal of Industrial Medicine, 36, 423-436, 1999.

Marsh GM, Lucas L, Youk AO, Schall LC: Mortality Patterns Among Workers Exposed to Acrylamide: 1994 Follow-Up. Occupational and Environmental Medicine, 56, 181-190, 1999.

Esmen NA, Hall TA, Stone RA, Marsh GM, Gula MJ, Gause CK: An Investigation of Secondary Exposure Misclassification Effects of Lifelong Occupational History in Exposure Estimation. American Industrial Hygiene Association Journal, 60, 175-181, 1999.

Mazumdar S, Xu Y, Mattison DR, Sussman N, and Arena VC. Reproductive Risk Assessment with Longitudinal data. The Journal of Applied Statistical Sciences IV 59-75, 1999.

Mattison DR, Mazumdar S, XU Y, Sussman N, and Arena VC. Characterizing reproductive risks using biological markers of reproductive toxicity: In Biomarkers: Medical and Workplace Applications. Editors: Mendelsohn ML, Mohr LC and Peeters JP. Joseph Henry Press: A publication of the National Academy of Sciences. Washington D.C. Pages 323-33, 1998.

Arena VC, Sussman NB, Redmond CK, Costantino JP, Trauth JM: Using Alternative Comparison Populations to Assess Occupational Related Mortality Risk: Results for High Nickel Alloys Workers Cohort. Journal of Occupational and Environmental Medicine, 40, 907-916, 1998.

Marsh GM, Youk AO, Stone RA, Sefcik S, Alcorn C: OCMAP-PLUS, A New Program for the Comprehensive Analysis of Occupational Cohort Data. Journal of Occupational and Environmental Health, 40, 351-362, 1998.

Rockette HE: Occupational Biostatistics. Chapter 6 in Environmental and Occupational Medicine, Little, Brown and Company, Boston MA (William N. Rom ed) 3rd edition, 1998.

Marsh GM, Stone RA, Esmen NA, Gula MJ, Gause CK, Petersen NJ, Meaney FJ, Rodney S, Prybylski D. A Case-Control Study of Lung Cancer Mortality in Four Rural Arizona Smelter Towns. Archives of Environmental Health 1998; 53:15-28.

Marsh GM, Stone RA, Esmen NA, Gula MJ, Gause CK, Petersen NJ, Meaney FJ, Rodney S, Prybylski D. A Case-Control Study of Lung Cancer Mortality in Six Gila Basin, Arizona Smelter Towns. Environmental Research 1997; 75:56-72.

Mazumdar SM, Mattison DR and Damaraju CV: Temporal issues in reproductive risk assessment. Inhalation Toxicology, 7, 837-862, 1995.

Mazumdar S, Mattison DR and Damaraju CV. Issues and Approaches for assessing risks from reproductive toxicants: DBCP as a case study. SANKHYA, 57, series B, Pt. 2, 223-236, 1995.

Gitelman JH, Alderman FR, Kurs Lasky M, Rockette HE: Serum and urinary aluminum levels of workers in the aluminum industry. Ann Occup Hyg Vol 39, No 2, PP 181-191, 1995.

Marsh GM, Stone RA, Esmen NA, Henderson VL: Mortality Among Chemical Plant Workers Exposed to Formaldehyde and Other Substances. Journal of the National Cancer Institute, 86, 384-385, 1994.

Redmond CK, Mazumdar S: Design, Analysis and Interpretation of Long-term Mortality Studies of Coke Oven Workers. International Statistical Review, 61, 2, 207-221, 1993.

Rockette HE: What evidence is needed to link lung cancer and second-hand smoke? Chance 1993, Vol. 6, No. 4: 15-18.

Marsh GM, Stone RA, Henderson V: Lung Cancer Mortality among Industrial Workers Exposed to Formaldehyde: A Poison Regression Analysis of the National Cancer Institute Study. American Industrial Hygiene Association Journal, 53, 681-691, 1992.

Zhou SYJ, Mazumdar S, Redmond CK, Dong MH, Costantino JP: Computations of Adjusted Rates and Lifetime Risks from Occupational Cohort Data: A Program Package using FORTRAN and GLIM. Computers and Biomedical Research, 24, 29-46, 1991.

Mazumdar S, Redmond CK, Costantino JP, Patwardhan RN, Zhou SYJ: Recent Developments in the Multistage Modeling of Cohort Data for Carcinogenic Risk Assessment. Environmental Health Perspective, 90, 271-277, 1991.

Marsh GM, Leviton LC, Talbott E, Callahan C, Pavlock D, Hemstreet G, Logue JN, Fox J, Schulte, P: The Drake Chemical Workers Health Registry Study: I. Notification and Medical Surveillance of a Group of Workers at High Risk of Developing Bladder Cancer. American Journal of Industrial Medicine, 19, 291-302, 1991.

Marsh GM, Enterline PE, Stone RA, Henderson VL: Mortality Among a Cohort of US Man-made Mineral Fiber Workers: 1985 Follow-upJournal of Occupational Medicine, 32, 594-604, 1990.

Rao BR, Marsh GM: Simultaneous Statistical Inference Concerning the SMR's of Several Strata in an Epidemiologic Study. Biometrical Journal, 32, 107-123, 1990.

Mazumdar S, Redmond CK, Enterline PE, Marsh GM, Costantino JP, Zhou SYJ, Patwardhan RN: Multistage Modeling of Lung Cancer Mortality Among Arsenic Exposed Copper-Smelter Workers. Risk Analysis, 9, 551-563, 1989.

Rao BR, Marsh GM, Winwood J: Asymptotic Interval Estimation of Some Cause-Specific Mortality Risk Measures in Epidemiologic Studies. Biometrical Journal, 31, 461-475, 1989.

Marsh GM, Co-Chien H, Rao BR, Ehland J: OCMAP: Module 6 - A New Computing Algorithm for Proportional Mortality Analysis. American Statistician, 43, 127-128, 1989.

Dong MH, Redmond CK, Mazumdar S, Costantino JP: A Multistage Approach to the Cohort Analysis of Lifetime Lung Cancer Risk Among Steelworkers Exposed to Coke Oven Emissions. American Journal of Epidemiology, 128, 4, 860-873, 1988.

Marsh GM, Costantino JP, Lyons EE, Logue JN, Fox JM: Health Effects of Exposure to the Drake Chemical Company Superfund Site: Morbidity Patterns Among Former Employees. Journal of Environmental Health, 50-389-394, 1988.

Rockette HE, Arena VC: An Evaluation of the Proportionate Mortality Index in the Presence of Multiple Comparisons. Statistics in Medicine 6(1):71-77, 1987.

Enterline PE, Marsh GM, Henderson V, Callahan C: Mortality Update of a Cohort of U.S. Man-Made Mineral Fiber Workers. The Annals of Occupational Hygiene, 31, 625-656, 1987.

Marsh GM, Winwood J, Rao BR: Prediction of the Standardized Risk Ratio Via Proportional Mortality Analysis. Biometrical Journal, 29, 355-368, 1987.

Marsh GM, Caplan RJ: Evaluating Health Effects of Exposure to Hazardous Waste Sites: A Review of the State-of-the-Art with Recommendations for Future Research. In Health Effects from Hazardous Waste Sites, Editors: J.B. Andelman and D.W. Underhill, Lewis Publishers, Inc., Chelsea, MI, 1987.

Marsh GM, Winwood J, Rao BR: Prediction of the Standardized Risk Ratio Via Proportional Mortality Analysis. Biometrical Journal, 29, 355-368, 1987.

Marsh GM, Caplan RJ: The Feasibility of Conducting Epidemiologic Studies of Populations Residing Near Hazardous Waste Disposal Sites. In Environmental Epidemiology, Editors: F.C. Kopfler and G.F. Craun, Lewis Publishers, Inc., Chelsea, MI, 1986.

Matanoski G, Fishbein L, Redmond C, Rosenkranz H, Wallace L: Contribution of organic particulates to respiratory cancer. Environmental Health Perspectives 70:37-49, 1986.

Rao BR, Marsh GM, Winwood J: Sidak-Type Simultaneous Confidence Intervals for the Measures RSMRi in Proportional Mortality Analyses Involving Competing Risks of Death. Communications in Statistics-Theory and Methods, 15, 515-536, 1986.

Marsh GM, Ehland J, Paik M, Preininger M, Caplan R: OCMAP/PC: A User Oriented Cohort Mortality Analysis Program for the IBM PC. The American Statistician, 40, 308-309, 1986.

Savitz DA, Redmond CK: Screening for geographic heterogeneity of disease rates: application to cancer incidence in Allegheny County, Pennsylvania, 1969-71. Journal of Chronic Diseases 38:145-156, 1985.

Rockette HE: Contributed Chapter 3 to 1985 Report to Surgeon General: Smoking Related Cancer and Chronic Lung Disease in the Workplace: Evaluation of Smoking Related Cancers in the Workplace, PP 97-135.

Fisher B, Rockette HE, Fisher ER, Wickerham DL, Redmond C, Brown A: Leukemia in breast cancer patients following adjuvant chemotherapy or post-operative radiation. The NSABP experience. Journal of Clinical Oncology 3(12):1640-1658, 1985.

Rockette HE, Redmond CK: Selection, followup and analysis in the coke oven study. National Cancer Institute. Monogr 67:89-94, 1985.

Deutscher S, Rockette HE, Krishnaswami V: Evaluation of habitual excessive alcohol consumption on myocardial infarction risk in coronary disease patients. Journal of Chronic Diseases, Vol 37, No. 5, PP 407-415, 1984.

Deutscher S, Rockette HE, Krishnaswami V: Correlations between habitual excessive drinking, cigarette smoking and myocardial infarction. American Heart Journal 108(4) Part 1, 988-995, 1984.

Ellakkani M, Alaire Y, Weyel D, Mazumdar S, Karol M: Pulmonary Reactions to Inhaled Cotton Dust: Animal Model for Byssinosis. Journal of Toxicology and Applied Pharmacology, 74, 267-284, 1984.

Miller B, Mazumdar S: MVSPEC: A User-Oriented Multivariate Spectral Analysis Program. The American Statistician. 88, 4, 319, 1984.

Rockette HE, Arena VC: Mortality studies of aluminum reduction plant workers: Potroom and carbon department. JOM Vol 25, No. 7:549-557, 1983.

Redmond CK: Cancer Mortality Among Coke Oven Workers. Environmental Health Perspectives, 52, 67-73, 1983.

Mazumdar S, Sussman N: Relationships of Air Pollution to Health: Results from the Pittsburgh Study. Archives of Environmental Health, 38, 1, 17-24, 1983.

Mazumdar S, Schimmel H, Higgins I: Relation of Daily Mortality to Air Pollution: Analysis of 14 London Winters. 1958/59 1971/72. Archives of Environmental Health, 37, 4, 213-220, 1982.

Marsh GM: Computerized Approach to Verifying Study Population Data in Occupational Epidemiology. Journal of Occupational Medicine, 24, 596-601, 1982.

Enterline PE, Marsh GM: Cancer Among Workers Exposed to Arsenic and other Substances in a Copper Smelter. American Journal of Epidemiology, 116, 895-911, 1982.

Redmond CK: Sensitive Population Subsets in Relation to Effects of Low Doses. Environmental Health Perspectives, 42, 137-140, 1981.

Marsh GM, Preininger ME: OCMAP: A User-Oriented Occupational Cohort Mortality Analysis Program. American Statistician, 34, 245-246, 1980.

Mazumdar S, Sussman N: Evidence of Possible Acute Health Effects of Ambient Air Pollution: Results Based on Pittsburgh Area Daily Mortality and Morbidity. Proceedings of the Park City Environmental Health Conference: Park City, Utah, April 4-7, 1979.

Rockette HE: Mortality studies of coal miners. Proceedings of Conference on the Health Implications of New Energy Technologies, Park City, Utah, April 1979.

Redmond CK, Emes J, Mazumdar S, Magee PC, Kamon E: Mortality of Steelworkers Employed in Hot Jobs. Journal of Environmental Pathology and Toxicology, 2, 75-96, 1979.

Marsh GM, Enterline PE: A Method for Verifying the Completeness of Cohorts Used in Occupational Mortality Studies. Journal of Occupational Medicine, 21, 665-670, 1979.

Mazumdar S, Redmond C: Evaluating Dose-Response Relationships Using Epidemiological Data on Occupational Groups. Proceedings of a Conference on Environmental Health, Alta, Utah, June 26-30, 1978. Sponsored by SIAM Institute for Mathematics and Society.

Emes J, Mazumdar S, Redmond C, Kamon E: Models for Estimating Worksite WBGT. American Industrial Hygiene Association Journal, 39, 592-597, 1978.

Wong O, Rockette H, Redmond CK, Heid M: Evaluation of Multiple Causes of Death in Occupational Mortality Studies. Journal of Chronic Diseases, 31, 183-193, 1978.

Rockette HE: Cause specific mortality of coal miners covered by the UMW Health and Retirement Funds. J Occup Med Vol 19, No. 12, pp 795-801, December 1977.

Collins J, Redmond CK: The Use of Retirees to Evaluate Occupational Hazards. Journal of Occupational Medicine, 18, 595-602, 1976.

Rockette, H, Redmond CK: Long-term Mortality Experience of Steelworkers, X. Mortality Patterns Among Masons. Journal of Occupational Medicine, 18, 541-545, 1976.

Redmond CK, Breslin PP: Comparison of Methods for Assessing Occupational Hazards. Journal of Occupational Medicine, 17, 313-318, 1975.

Mazumdar S, Redmond C, Sollecito W, Sussman N: An Epidemiological Study of Exposure to Coal Tar Pitch Volatiles Among Coke Oven Workers. Journal of the Air Pollution Control Association, 25, 4, 382-389, 1975.

Mazumdar S, Lerer T, Redmond, C: Long-Term Mortality Study of Steelworkers IX. Mortality Patterns Among Sheet and Tin Mill Workers. Journal of Occupational Medicine, 17,12, 751-755, 1975.

Redmond CK, Ciocco A, Lloyd JW, Rush HW: Long-term Mortality Study of Steelworkers, VI. Mortality from Malignant Neoplasms Among Coke Oven Workers. Journal of Occupational Medicine, 14, 621-629, 1972.

Redmond CK, Smith EM, Lloyd JW, Rush HW: Long-term Mortality Study of Steelworkers, III. Follow-up. Journal of Occupational Medicine, 11, 513-521, 1969.

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Occupational Cohort Mortality Analysis Program (OCMAP)

Faculty members in the Department have also been active in the development of software packages and data base systems for use in the occupational and environmental epidemiology research program. The Occupational Cohort Mortality Analysis Program (OCMAP) began in 1980 as a unified set of FORTRAN programs for the comprehensive editing and analysis of data from the Department's many occupational health related research projects (Marsh and Preininger, 1980). A particular advantage of the original OCMAP was its unique ability, compared with other programs at that time, to relate mortality outcomes to a number and variety of exposure metrics computed directly from detailed work service histories of study subjects. Due to the high demand for such a comprehensive and generalized computing resource, the Department began to distribute and market copies of OCMAP to outside researchers in academia, government and the private sectors. Funds obtained from sales of the program were used for continued research and development.

In the 1980's, OCMAP-PC, the first microcomputer version of OCMAP was created (Marsh et al., 1986), and new analytic modules were developed by Biostatistic's students as part of their Master's thesis requirement (Caplan et al., 19984; Marsh et al., 1989). In the 1990's, OCMAP was redesigned for optimal microcomputer use and extended to include many new computing algorithms (Marsh et al., 1998). The new program, OCMAP-PLUS, offered a comprehensive, flexible and efficient analysis of incidence or mortality rates and standardized measures in relation to multiple and diverse work history and exposure measures. New features included executable code, minimization of memory requirements, disk file storage of person-day arrays, stratified analyses by geographic area, employment status and up to eight exposure variables, a data imputation algorithm for study members with unknown race and enhanced algorithms for constructing several time-dependent exposure measures. New modules create grouped data files for Poisson and logistic regression and risk sets files for use in relative risk regression models.

Currently, faculty members are working on a version of OCMAP-Plus that operates efficiently under the MS Windows ® graphical interface, and plan to release a beta test version in early 2002. While the OCMAP programs were designed primarily for occupational mortality studies, applications generalize easily to studies of other health endpoints such as cancer incidence, and to studies in non-occupational settings. OCMAP is now in use by more than 300 institutions in the United States and abroad. OCMAP has been referenced in more than 180 peer-reviewed journal articles based on a review of the Science Citations Index data base (Institute for Science Information, 1999). Further information about OCMAP can be found in the cited articles or on the dedicated web site: ocmap.biostat.pitt.edu.

Selected Publications (for OCMAP section):

Marsh GM, Youk AO, Stone RA, Sefcik S, Alcorn C. OCMAP-Plus: A program for the comprehensive analysis of occupational cohort data. Journal of Occupational and Environmental Medicine 1998;40:351-362.
Marsh GM, Co-Chien H, Rao BR, Ehland J. OCMAP: Module 6-A new computing algorithm for proportional mortality analysis. American Statistician 1989;43:127-128.
Marsh GM, Ehland J, Paik M, Preininger M, Caplan R. A user oriented cohort mortality analysis program for the IBM PC. American Statistician 1986;40:308-309.
Caplan RJ, Marsh GM, Enterline PE. A generalized effective exposure modeling program for assessing dose-response in epidemiologic investigations. Comput Biomed Res. 1984;16:587-596.
Marsh GM, Preininger ME. OCMAP: A user-oriented occupational cohort mortality analysis program. American Statistician 1980;34: 245-246.

Mortality and Population Data System (MPDS)

Also since 1980, faculty members in the Department of Biostatistics have developed and maintained a data repository and retrieval system for detailed mortality data provided by the National Center for Health Statistics and the U.S. Census Bureau. This Mortality and Population Data System (MPDS) contains the underlying cause of death code (using International Classification of Diseases (ICD) four-digit codes) for all persons who died in the U.S. between 1950 and 1994 (limited to deaths from malignant neoplasms for the 1950-61 period). Individual death records include codes for sex, race, age of death, year of death and geographic location (county and state of residence at time of death).

In MPDS, individual death records are categorized and linked with the corresponding population data to form death rates specific for five-year age groups, five-year time periods, race (white and non-white), sex, geographic location and cause of death. Cause of death can be defined by any individual ICD code or combination of ICD codes. The OCMAP/MPDS web site ocmap.biostat.pitt.edu. provides a listing of the standard 63 cause of death categories that are suitable for most cohort analyses. The listing shows the ICD codes for the sixth through ninth revisions, and indicates which categories can be made comparable to any one revision using comparability ratios (CR) provided by the NCHS. This approach, in which death rates are "adjusted" to a specific base ICD revision, is appropriate for studies that code all deaths to the base revision. MPDS death rates are also available in unadjusted form. Such rates are appropriate for studies that code all deaths to the revision of the ICD in effect at the time of death.

The MPDS standard death rate files can be written to OCMAP-Plus format specifications and input directly as standard population data in comparative mortality analyses. Because of this useful feature, many users of the OCMAP programs also request MPDS rate files for use as standard populations in historical cohort analyses. Funds generated from sales of the MPDS rate files are also used for continued research and development of MPDS and OCMAP. The MPDS data base is updated annually as new NCHS data are released. The MPDS is the most comprehensive and accessible data repository and retrieval system of its kind in use today. Further information about MPDS can be found in the cited articles or on the dedicated web site: ocmap.biostat.pitt.edu.

(at this time there are no publications for this section.)

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Radiological Imaging Systems

The Biostatistics Department has a long standing relationship with the Department of Radiology in studies to compare the accuracy of different diagnostic imaging systems. The biostatistical component usually addresses issues relative to the design, analysis and interpretation of the study. To date, there has been collaboration on five large scale clinical studies involving more than 20 different radiologists and 200,000 different images. These studies have included evaluating the effects of pixel size, resolution, brightness, compression and clinical history on the diagnostic accuracy of different imaging modalities.

In addition to participating in the analysis and interpretation of specific studies, the Biostatistics Department has contributed to the improvement of design, analysis, and interpretation of diagnostic imaging studies. Design issues which have been addressed include the role of subtle cases, the effect of "easy" controls, the role of stratification in imaging studies, methods to estimate sample size, and the advantages of a continuous scoring scale. Contributions to the improvement in the analysis of imaging studies include methods of analyzing studies stratified by subtlety of the case, a method of analyzing studies with multiple readers, and a rank order method to analyze studies with an underlying ordered parameter.

Several faculty members in the Biostatistics Department are collaborating with the PET methodology researchers in the Radiology Department in several studies involving design, analysis and interpretation of results. Special emphasis is given to methodological research for the analysis of neuroimaging data. Graduate students get opportunities to work as graduate student researchers and develop their theses.

Selected Publications:

Meltzer CC, Price JC, Mathis CA, Butters MA, Ziolko SK, Moses-Kolko E, Mazumdar S, Mulsant BH, Houck PR, Lopresti BJ, Weissfeld LA, and Reynolds CF. Serotonin 1A receptor binding and treatment response in late-life depression. Neuropsychopharmacology (in press).

Price JC, Kelley DE, Ryan CM, Meltzer CC, Drevets WC, Mathis CA , Mazumdar S, and Reynolds CF. Evidence of increased serotonin-1A receptor binding in type 2 diabetes: a positron emission tomography study. Brain Research, 2002; 927:97-103.

Price JC, Drevets WC, Ruszkiewicz J, Greer PJ, Villemagne VL, Xu L, Mazumdar S, Cantwell MN, Mathis CA.Sequential H 2 [ 15 O] pet studies in baboons: before and after amphetamine. The Journal of Nuclear Medicine, 43(8): 1090-1100, 2002.

Gur D, Rockette HE, Armfield DR, Blachar A, Bogan JK, Brancatelli G, Britton CA, Brown ML, Davis PL, Ferris JV, Fuhrman CR, Golla S, Katyal S, Lamomis JM, McCook B, Thaete FL, Warfel TE. The Prevalence Effect in a Laboratory Environment. Radiology, 228: 10-14, 2003.

Fuhrman CR, Britton CA, Bender T, Sumkin JH, Brown ML, Holbert JM, Chang TS, Rockette HE, Gur D: Observer Performance Studies: Detection of single vs. multiple abnormalities of the chest. American Journal of Roentgenology, 179(6): 1551-3, 2002.

Rockette HE, Li W, Brown ML, Britton CA, Towers JT, Gur D. A Statistical Test to Assess Rank Order ROC Imaging Studies. Academic Radiology 8(1):24-30, 2001.

Herron JM, Bender T, Campbell WL, Sumkin JH, Rockette HE and Gur D: Effects of luminance and resolution on observer performance. Radiology 215:169-174, 2000.

Good WF, Sumkin JH, Dash N, Johns CM, Zuley ML, Rockette HE, Gur D: Observer sensitivity to small differences: A multipoint rank-order experiment. AJR 173: 275-278,1999.

Rockette HE, Campbell WL, Britton CA, Holbert JM, King JL, Gur D: Empirical assessment of parameters that affect the design of multireader ROC studies. Academic Radiology Vol 6:723-729, 1999.

Rockette HE, King JL, Medina JL, Eisen HB, Brown ML, Gur D: Imaging systems evaluation: Effect of subtle cases on the design and analysis of receiver operating characteristic studies. American Journal of Roentgenology Vol. 165(3), 679-683, 1996.

Oliver JH, Baron RL, Federle MP, Rockette HE: Detecting hepatocellular carcinoma: value of unenhanced or arterial phase CT imaging or both used in conjunction with conventional portal venous phase contrast-enhanced CT imaging. Amer J Roentgenology 167(1):71-77, 1996.

Rockette HE, Gur D, Kurs-Lasky M, King JL: On the generalization of the receiver operating characteristic analysis to the population of readers and cases with the jackknife method: An assessment. Academic Radiology Vol 2, PP 66-69, 1995.

Obuchowski NA, Rockette HE: Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests: An ANOVA approach with dependent observations. Commun Statistics 24(2), 285-308, 1995.

Rockette HE, Gur D, Campell WL, Thaete FL: Utilization of meta analysis in the evaluation of imaging systems. Academic Radiology Vol. 1, PP 63-69, 1994.

Rockette HE: An index for diagnostic accuracy in the multiple disease setting. Academic Radiology Vol 1, PP 283-286, 1994.

Rockette HE, Gur D and Metz CH: The use of continuous and discrete confidence judgments in receiver operating characteristic studies of diagnostic imaging techniques. Investigative Radiology 1992, 27: 169-172.

Gur D, Rockette H, Good WF, Slasky BS, Cooperstein LA, Straub WH, Obuchowski NA and Metz CE: Effect of Observer Instruction on ROC Study of Chest Images. Invest Rad March 1990: Vol. 25, No. 3: 230-234.

Rockette HE, Gur D, Cooperstein LA, Obuchowski NA, King JL, Fuhrman CR, Tabor EK, Metz CE:iEffect of two rating formats in multi-disease ROC study of chest images. Invest Rad March 1990: Vol. 25, No. 3: 225-229.

Good BC, Cooperstein LA, DeMarino GB, Miketic LM, Gennari RC, Rockette HE, Gur D: Does knowledge of the clinical history effect the accuracy of chest radiograph interpretation? AJR: 154, April 1990, pg. 709-711.

Slasky BS, Gur D, Good WF, Costa-Greco MA, Harris KM, Cooperstein LA, Rockette HE: Receiver operating characteristic analysis of chest image interpretation with conventional, laser printed, and high resolution workstation images. Radiology 1990, 174: 775- 780.

Rockette HE, Obuchowski NA, Gur D: Nonparametric estimation of degenerate ROC data sets used for comparison of imaging systems. Invest Radiol 1990, 25: 835-837.

Gur D, King JL, Rockette HE, Britton CA, Thaete FL, Hoy RJ: Practical issues of experimental ROC: Selection of controls. Investigative Radiology June 1990: Vol. 25, 583-586.

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Otolaryngology

Various manifestations of ear disease are the most common reason (other than routine physical examinations) that parents visit a pediatrician. Complications of ear disease include potential hearing loss associated with fluid in the ear which if present over long periods of time may impact on language development. The Department of Biostatistics has a long history of collaboration with the Department of Otolaryngology in studies to better delineate the aetiology and treatment of ear disease (otitis media) in children. This has entailed participation in the design and analysis of more than two dozen studies of over 10,000 children. Studies conducted have included the evaluation of the treatment effect of decongestant and antihistamine and various antibiotics on the short term resolution of otitis media with effusion, the effect of surgery and tube placement for the treatment of chronic otitis media with effusion, and the effect of various antibiotics on the treatment of acute otitis media (ear infection). Additional studies have characterized both the demographic factors related to the incidence of ear disease and the genetic component of the disease.

The most recent study entailed the follow-up and evaluation of more than 5,000 children during the first two years of life of whom more than 400 children with persistent ear disease were randomized to receive tubes immediately or to delay for a short period to provide further opportunity for clearance of fluid. The group with delayed tube placement had more ear disease over the first three years but required significantly less surgical procedures. Furthermore tests at three years of age indicated no difference in the language development of the two groups.

Some of the collaborative publications resulting from the effort with Children's Hospital are as follows:

Campbell TF, Dollaghan CA, Rockette HE, Paradise JL, Feldman HM, Shruberg LD, Sabo D, Kurs-Lasky M. Risk Factors for Speech Delay in Three Year Old Children. Child Development. Vol. 74 (2): 346-357, March/April 2003.

Mandel EM, Casselbrant ML, Rockette HE, Fireman P, Kurs-Lasky M, Bluestone CD. Systemic Steroid For Chronic Otitis Media with Effusion in Children. Pediatrics, 110(6): 1071-80, 2002

Paradise JL, Feldman HN, Campbell TF, Dollagham CA, Calburen KD, Bernard BS, Rockette HE, Janosky JE, Pitcairn DL, Sabo DL, Kurs-Lasky M, Smith CG: Effect of Early or Delayed Insertion of Tympanostomy Tubes for Persistent Otitis Media on Developmental Outcomes at the Age of Three Years. New England Journal of Medicine 344(16):1179-1187, 2001.

Casselbrandt ML, Mandel EM, Fall PA, Rockette HE, Kurs-Lasky M, Bluestone CD, Ferrell RE: The heritability of otitis media: A twin and triplet study. JAMA 282(22): 2125-2130, Dec 1999.

Paradise JL, Rockette HE, Colborn DK, Bernard BS, Smith CG, Kurs-Lasky M, and Janosky JE: Otitis media in 2253 Pittsburgh-area infants: Prevalence and risk factors during the first two years of life. Pediatrics 99(3):318-333, 1997.

Mandel EM, Casselbrandt ML, Rockette HE, Bluestone CD, Kurs-Lasky M: Efficacy of antimicrobial prophylaxis for recurrent middle ear effusion. Pediatrics Infectious Dis J 15:1074-1082, 1996.

Casselbrandt ML, Mandel EM, Kurs-Lasky M, Rockette HE, Bluestone CD: Otitis Media in a population of Black American and White American infants, 0-2 years of age. International Journal of Pediatric Otorhinolaryngology 33, 1-16, 1995.

Mandel EM, Casselbrandt ML, Rockette HE, Bluestone CD, Kurs-Lasky M: Efficacy of 20- vs 10-day antimicrobial treatment for acute otitis media. Pediatrics 96, 5-13, 1995.

Casselbrant ML, Kaleida PH, Rockette HE, Paradise JL, Bluestone CD, Kurs-Lasky M, Nozza RJ and Wald ER: Efficacy of antimicrobial prophylaxis and of tympanotomy tube insertion for prevention of recurrent acute otitis media: results of a randomized clinical trial. Pediatr Infect Dis J 11:278-286, 1992.

Mandel EM, Rockette HE, Bluestone CD, Paradise JL and Nozza RJ: Efficacy of myringotomy with and without tympanotomy tubes for chronic otitis media with effusion. Pediatr Infect Dis J 11:270-277, 1992.

Mandel EM, Rockette HE, Paradise JL, Bluestone CD and Nozza RJ: Comparative efficacy of erythromycin-sulfisoxazole, cefaclor, amoxicillin or placebo for otitis media with effusion in children. Pediatr Infect Dis J 10:899-906, 1991.

Rosenfeld RM and Rockette HE: Biostatistics in otolaryngology Journals. Arch Otolaryngol Head Neck Surg 117:1172-1176, 1991.

Mandel EM, Rockette HE, Bluestone CD, Paradise JL, Nozza RJ: Efficacy of Amoxicillin with and without Decongestant/Antihistamine for Otitis Media with Effusion in Children: Results of a Double-Blind, Randomized Trial. New England Journal of Medicine 316:432-437, 1987.

Kaleida PH, Bluestone CD, Rockette HE, Bass LW, Wolfson JH, Breck JM, Ubinger EB, Rohn DD: Amoxicillin-Clavulanate Potassium Compared to Cefaclor for Acute Otitis Media in Infants and Children. Pediatr Infect Dis 6:265-271, 1987.

Cantekin EI, Mandel EM, Bluestone CD, Rockette HE, Paradise JL, Stool SE, Fria TJ, Rogers KD: Lack of efficacy of a decongestant-antihistamine combination for otitis media with effusion ("Secretory Otitis Media") in children: Results of a double-blind, randomized trial. N England J of Med 308:297-30l, 1983.

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Psychiatric Research

Department of Biostatistics started a collaboration with the Department of Psychiatry, School of Medicine about ten years ago. Faculty members are involved in psychiatric clinical trials in evaluating different intervention strategies in mood disorders and sleep disorders. The biostatistical component of the collaboration includes issues relative to the design, analysis and interpretation of the studies. There has been participation in the Mental Health Clinical Research Center in Late-life mood Disorders and several NIH funded research protocol in the Departments of Psychiatry and Radiology. Students in the Department of Biostatistics have the opportunity of working as graduate student researchers with psychiatric researchers and develop their thesis from research needs in the psychiatric arena. The statistical methodologies needed in this area are mostly: survival analysis, longitudinal data analysis, factor analysis and structural equations modeling. Recent efforts have started to develop the analysis of fMRI and PET data as they are used in psychiatric clinical trials.

Selected Publications:

Liu K, Stone RA, Mazumdar S , Houck PR, Reynolds CF. Covariate measurement error in the Cox model: a simulation study. Communications in Statististics (in press) .

Houck PR, Mazumdar S , Sengul TK, Tang G, Mulsant BH, Pollock BG, Reynolds CF. Estimating treatment effects from longitudinal clinical trial data with missing values: comparative analyses using different approaches. Psychiatric Research (in press).

Mazumdar S , Dew MA, Houck PR, and Reynolds CF. Assessing intra-individual changes in health related quality of life data in psychiatric clinical trials. ENVIRONMETRICS , 15, 491-499, 2004.

Houck PR, Mazumdar S , Mulsant BH, Pollock BG, Dew MA, and Reynolds CF. An intent to treat method for enhancing analysis of clinical trials with rescue medication: a mixed-model approach. Psychopharmacology Bulletin. 2003-Vol 37(1), 79-89.

Mazumdar S , Houck PR, Liu KS , Mulsant BH, Pollock, BG, Dew MA and Reynolds CF. Intent-to-treat analysis for clinical trials: use of data collected after termination of treatment protocol. Journal of Psychiatric Research , 2002, 36, 153-164.  

Mazumdar S, Berhane Z, Weissfeld L, Begley A, Dew MA, Houck PR and Reynolds CF. Survival models with time-varying coefficients: A flexible approach to the analysis of psychiatric survival data. Psychopharmacology Bulletin. Autumn 2002-Vol 36(4), pp. 84-91.

Kowalski J, Tu XM, Begley A, Houck P, Mazumdar S, Miewald J, Buysse DJ, and Kupfer DJ. Data recycling: a response to the changing technology from the statistical perspective with application to psychiatric sleep. Journal of the Royal Statistical Society, Series C (Applied Statistics), 2001, 28(8):1029-1049..

Kastango KB, Kim Y, Dew MH, Mazumdar S, Mulsant BH, Rosen J, Reynolds CF, Pilkonis PA and Pollock BG. Verification of a scale sub-domain in elderly patients with dementia: a confirmatory factor analytic approach. American Journal of Geriatric Psychiatry, 2002, 10:706-14.

Liu K, Mazumdar S, Stone RA, Dew MA, Houck PR and Reynolds CF. Accounting for covariate measurement error in a Cox model analysis of recurrence depression. Journal of Psychiatric Research, 35: 177-185, 2001.

Mazumdar S, Houck PR and Reynolds CF. Statistics in Psychiatric Research. Hand Book of Statistics, Vol. 18. Bio-environmental and Public Heath Statistics. Editors: P. K. Sen and C.R. Rao. 2000 Elsiever Science, pp 1005-1026.

Pollock BG, Ferrell RE, Mulsant BH, Mazumdar S, Miller M, Sweet RA, Davis S, Kirshner MA, Houck PR, Stack JA, Reynolds CF and Kupfer DJ. Allelic Variation in the Serotonin Transporter Promoter Affects Onset of Paroxetine Treatment Response in Late-Life Depression. Neuropsychopharmacology, 23(5), 587-590, 2000.

Mazumdar S, Liu K, Ahnn S, Houck PR, and Reynolds CF. Transition (Markov) models for the analysis of survival times in clinical psychiatric research. Communications in Statistics-Simulations, 28(1), 165-176, 1999.

Mazumdar S, Liu K, Houck PR, and Reynolds CF. Intent-to-treat analysis for longitudinal clinical trials: coping with the challenge of missing values. Journal of Psychiatric Research, 33, 87-95, 1999.

Mazumdar S, Begley A, Houck PR Yang Y, Reynolds CF and Kupfer DJ. Residual Analysis in Random Regression using SAS and S-PLUS. Computer Methods and Programs in Biomedicine, 58, 281-282, 1999.

Reynolds CF, Frank E, Perel J, Imber SD, Cornes Cleone, Miller MD, Mazumdar S, Houck PR, Dew MA, Stack JA, Pollock BG, Kupfer DJ. Nortriptyline and interpersonal psychotherapy as maintenance therapies for recurrent major depression: a randomized controlled trial in patients older than 59 years. Journal of the American Medical Association, 281(1), 1999.

Rosen J, Bobys PD, Mazumdar S, Mulsant BH, Sweet RA, Yu K, Kollar M, and Pollock BG. OBRA regulations and neuroleptic use: defining agitation using the Pittsburgh Agitation Scale and the Neurobehavioral Rating Scale. Annals of Long-term Care, 7(12) 429-436, 1999.

Reynolds CF, Frank E, Perel JM, Mazumdar S, and Kupfer D. Maintenance Therapies for Late-Life Recurrent Major Depression: Research and Review Circa 1996. In: Geriatric Psychopharmacology (Ed. Nelson, JC). Marcel Dekker, Inc, New York, 1998.

Mulsant BH, Mazumdar S, Pollock BG, Sweet RA, Rosen J and Lo K. Methodological issues in characterizing treatment response in demented patients with behavioral disturbances. International Journal of Geriatric Psychiatry, 12:537-547, 1997.

Nowell PD, Mazumdar S, Buysse DJ, Mary Amanda Dew, Reynolds CF, and Kupfer DJ. Benzodiazepines and Zolpidem for Chronic Insomnia: A Meta-Analysis of Treatment Efficacy. Journal of the American Medical Association, 278 (24), 2170-2177, 1997.

Mazumdar S, Reynolds CF, Houck PR, Frank E, Dew MA, and Kupfer DJ. Quality of Life in elderly patients with recurrent major depression: A Factor Analysis of the General Life Functioning (GLF) Scale. Psychiatry Research, 63, 183-190, 1996.

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Oncology Thinking Cap (OncoTCap)

The Oncology Thinking Cap (OncoTCap) computer program developed by Dr. Roger Day under NCI grant R25-CA63548 represents the behavior of individual cancer cells in heterogeneous tumors and calculates simulations of populations of cancer patients treated with specific regimens. The modeling architecture of the simulation engine supports integration of processes at many scales, including molecular functional networks, micro-environmental interactions, functioning of physiologic systems, measurement processes, patient management plans, patient-doctor relations, and clinical trials design and execution. In its current level of maturity, applications to cancer professional education have been built, deployed and utilized in settings from middle school through medical school, oncology fellowship programs and a national cancer pharmacology workshop.

Currently in development is a comprehensive software-based cancer model development and validation facility, in which the simulation engine is at the core. The purpose requires some explanation. In many areas of controversy in cancer treatment, clinical research is inconclusive. Pre-clinical studies could in principle contribute to clarifying the issues. However, the relevant literature is voluminous and ever-growing, the number of postulated mechanisms is large, and the relevance of pre-clinical information is always suspect. Complicating interpretation further, many observations suggest strong connections between the postulated mechanisms and molecular networks affecting cell cycle regulation, signal transduction, apoptosis, invasiveness, and angiogenesis. Finally, tumor heterogeneity repeatedly appears as a key complication. (In fact cancer mortality generally stems from metastasis, whose essence is spatial heterogeneity). This puts great demands on the intuition and interpretational powers of breast cancer scientists; single tissue samples can mislead when clonal evolution, natural selection prior to diagnosis, and selection by treatment cause spatial and temporal shifts in cancer cell genotype and phenotype. All these factors interfere with making the best use of all available research information.

Given a cancer management problem statement, the new system will support the gathering and assessment of relevant research information, followed by translation of some of this information into model-specification programming statements, translation of others into validation suites of observations with goodness-of-fit criteria. The simulation engine can then generate predictions, the comparisons with observations in the validation suite assessed, and the resulting goodness-of-fit measures assembled into a validation report card. Suitable models would then be selected based on the specific purpose in light of the report card. The ultimate result will be the intelligent planning, design and selection of new treatment regimens to test clinically. A longer term goal would be the design of biologically individualized treatment plans.

Selected Publications:

Hmelo CE, Ramakrishnan, Day RS, Shirey WE, Brufsky A, Johnson C, Baar J, Huang, Q. The Oncology Thinking Cap: Scaffolded use of a simulation to learn clinical trial design. Teaching and Learning Medicine, 13(3), 2001.

Hmelo CE, Nagarajan A, and Day RS. Effects of high and low prior knowledge on construction of a joint problem space. Journal of Experimental Education 69:36-56, 2000.

Hmelo C and Day R. Contextualized questioning to scaffold learning from simulations. Computers & Education 32:151-164, 1999.

Day R, Shirey W, Ramakrishnan S, Huang Q. Tumor biology modeling workbench for prospectively evaluating cancer treatments. Proceedings of the CESA '98 IMACS Multiconference. April 1998.

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Biostatistics Facility of the University of Pittsburgh Cancer Institute

The Biostatistics Facility provides clinical and basic-science investigators in the University of Pittsburgh Cancer Institute (UPCI) with statistical and computer-related expertise in design, execution, analysis, and reporting of cancer-related research studies. These cover basic-science studies; phase I and phase II oncology clinical trials; epidemiologic studies, including those related to cancer prevention and awareness; and investigations of behavioral and health sequelae of cancer treatment. Statisticians serve on UPCI's Clinical Research Oversight Committee, Protocol Review Committee, and Data and Safety Monitoring Committee. They support the training of students, fellows, and cancer researchers in biostatistics, clinical trials, and tumor dynamics. The Facility is also committed to applying statistical and computational methods to improve the manner in which clinical trials and translational research are performed at UPCI, and to developing statistical methodology that aids cancer research. Methodologic research in the Facility has focused on the analysis of biomarkers for prognosis and prediction of response to treatment; quality control in immunologic assay systems; adaptive dose-finding techniques for phase I trials; permutation tests for logistic regression, and for inference from small datasets with many covariates; stochastic modeling of tumor growth and metastasis; weakest-link modeling for studying cause-effect in biological and medical phenomena; meta-analysis; and evaluating quality of life, and behavioral and health outcomes, of patients undergoing cancer treatment.

The Biostatistics Facility is the home of the Educational Resource for Tumor Heterogeneity (ERTH), an NCI-funded project to develop a biomathematical modeling system for oncology: the Oncology Thinking Cap simulator (OncoTCap). This software simulates the evolution of heterogeneous tumors based on mathematical and stochastic modeling of mechanisms arising from molecular biology. The growth, metastasis, and differential response of cancer cells to various treatments can be simulated, thereby providing an assessment of the therapeutic potential of alternative treatment regimens.

The Biostatistics Facility of UPCI is complemented by the Biostatistical Center for the National Surgical Adjuvant Breast and Bowel Project, a cooperative clinical trials group that conducts randomized phase III clinical trials for the prevention and treatment of breast and colorectal cancer.

Selected References

Allegra CJ, Paik S, Colangelo LH, Parr AL, Kirsch I, Kim G, Klein P, Johnston PG, Wolmark N, Wieand S. Prognostic value of thymidylate synthase, Ki-67 and p53 in patients with Dukes' B and C colon cacner: an NCI-NSABP collaborative study. J Clin Oncol, 21:241-250, 2003.

Kunkel M, Reichert TE, Benz P, Lehr HA, Jeong JH, Wieand S, Bartenstein P, Wagner W, Whiteside T. Overexpression of Flut-1 and increased glucose metabolism in the tumor are associated with poor prognosis in oral squamous cell carcinoma. Cancer, 97:1015-1024, 2003.

Grumbach M, Biller B, Braunstein G, Campbell K, Carney J, Godley P, Harris E, Lee J, Oertel Y, Posner M, Schlechte J, Wieand H. Management of the clinically inalpparent adrenal mass ("Incidentaloma"). Annals of Internal Medicine, 138:424-429, 2003.

Zarour HM, Maillere B, Brusic V, Coval K, Willams E, Pouvelle-Moratille S, Castelli F, Land S, Bennouna J, Logan T and Kirkwood JM. NY-ESO-1 119-143 is a promiscuous MHC class II T-helper epitope recognized by Th1 and Th2-type tumor-reactive CD4+ T cells. Cancer Res., Jan 1; 62(1):213-8, 2002.

Muindi JR, Yibing P, Potter DM, Tauch JS, Capozzoli MJ, Egorin MJ, Johnson CD, Trump DL. Pharmacokinetics of High Dose, Oral Calcitriol: Results Obtained During a Phase One Trial of Calcitriol and Paclitaxel. Clinical Pharmacology and Therapeutics, 72:648-659, 2002.

Zamboni WC, Gervais AC, Egorin MJ, Schellens JH, Hamburger DR, Delauter BJ, Grim A, Zuhowski EG, Joseph E, Pluim D, Potter DM, Eisenman JL. Inter- and intratumoral disposition of platinum in solid tumors after administration of cisplatin. Clinical Cancer Research, 8(9):2992-2999, 2002.

Brissette-Storkus CS, Kettel JC, Whitham TF, Giezeman-Smits KM, Villa LA, Potter DM, Chambers WH. Flt-3 ligand (FL) driver differentiation of rat bone marrow-derived dendritic cells expressing OX62 and/or CD161 (NKR-P1). Journal of Leukocyte Biology, 71(6):941-949, 2002.

Kirkwood JM, Richards T, Zarour HM, Sosman J, Ernstoff M, Whiteside T, Ibrahim J, Blum R, Wieand S, Mascari R. Immunomodulatory Effects of High- and Low-dose IFNalpha2b in Patients with High-risk Resected Melanoma: The E2690 Laboratory Corollary of Intergroup Adjuvant Trial E1690. Cancer, 95: 1101-1112, 2002.

Matin K, Egorin MJ, Bellesteros MF, Smith DC, Lembersky B, Day RS, Johnson CS, Trump DL. Phase I and Pharmacokinetic study of vinblastine and high dose megestrol acetate. Cancer Chemotherapy & Pharmacology, 50(3):179-85, 2002.

Rose C, Green M, Webber S, Kingsley L, Day R, Watkins S, Reyes J, Rowe D. Detection of Epstein-Barr virus genomes in peripheral blood B cells from solid organ transplant recipients by fluorescent in situ hybridization. Journal of Clinical Microbiology, 40(7):2533-44, 2002.

Hmelo CE, Nagarajan A, and Day RS. It's harder than we thought it would be: A comparative case study of expert-novice experimentation strategies. Science Education, 219-243, 2003.

Reichert TE, Scheuer C, Day R, Wagner W, Whiteside TL. The number of intratumoral dendritic cells and zeta-chain expression in T cells as prognostic and survival biomarkers in patients with oral carcinoma. Cancer 91(11):2136-2147, 2001.

Zamboni WC, Egorin MJ, Van Echo DA, Day RS, Meisenberg BR, Brooks SE, Doyle LA, Nemieboka NN, Dobson JM, Tait NS, Tkaczuk KH. Pharmacokinetic and pharmacodynamic study of the combination of codetaxel and topotecan in patients with solid tumors. J Clin Oncol 18(18):3288-3294, 2000.
Bahri S, Agarwala S, Cano E, Johnson J, Myers E, Jeong J et al. Phase II study of concurrent carboplatin and paclitaxel with radiation therapy in patients with locally advanced, inoperable squamous cell carcinoma of the head and neck (HNSCC). Proceeding of the American Society of Clinical Oncology (ASCO), 2000.
Ball ED, Wilson J, Phelps V, Neudorf S. Autologous bone marrow transplantation for acute myeloid leukemia in remission or first relapse using monoclonal antibody-purged marrow: results of Phase II studies with long-term follow-up. Bone Marrow Trans 25:823-829, 2000.
Wilson JW, Kim HT. Biostatistics. In Practical Guide to Bone Marrow Transplantation (Ball ED, Lister J, Law, P, eds., WB Saunders Co) 2000.
Faul C, Gerszten K, Edwards R, Land S, D'Angelo G, Kelly III J, Price F. A Phase I/II study of hypofractionated whole abdominal radiation therapy in patients with chemoresistant ovarian carcinoma: impact on quality of life. Int J Radiat Oncol Biol Phys 1:47(3), 749-754, 2000.
Konety BR, Nguyen TT, Brenes G, Sholder A, Lewis N, Bastacky S, Potter DM, Getzenberg RH. Clinical usefulness of the Novel Marker BLCA-4 for the detection of bladder cancer. J Urology 164:634-639, 2000.
Smith DC, Johnson CS, Freeman CC, Muindi J, Wilson JW, Trump DL. A Phase I trial of calcitroil (1,25 Dihydroxycholecalciferol) in patients with advanced malignancy. Clin Cancer Res 5:1339-1345, 1999.
DeMagalhaes-Silverman M, Donnenberg AD, Lister J, Rybka W, Wilson J, Ball E. Factors influencing mobilization and engraftment in patients with metastatic breast cancer undergoing peripheral blood stem cell transplantation. J Hematotherapy 8:167-172, 1999.
Martin JA, Slivka A, Rabinovitz M, Carr BI, Wilson J, Silverman WB. ERCP and stent therapy for progressive jaundice in hepatocellular carcinoma: which patients benefit, which patients don't? Digestive Dis & Sci 44:1298-1302, 1999.
Shpilberg O, Wilson J, Whiteside TL, Herberman RB and the Pittsburgh PTLD study group. Pre-transplant immunological profile and risk factor analysis of post-transplant lymphoproliferative disease development: the results of a nested matched case-control study. Leuk & Lymphoma 36:109-121, 1999.
Hmelo C and Day R. Contextualized questioning to scaffold learning from simulations. Computers & Educ 32:151-164, 1999.
Belani CP, Aisner J, Ramanathan R, Jett J, Greenberger J, Day R, Capazolli MJ, Hiponia D, Engstrom C. Paclitaxel and carboplatin with simultaneous thoracic irradiation in regionally advanced non-small cell lung cancer. Seminars Rad Oncol 7(2):S1-S11-S13-S14, 1999.
Belani CP, Luketich JD, Landreneau RJ, Kim R, Ramanathan RK, Day R, Ferson PF, Keenan RJ, Posner M, Seger J, Lembersky B. Efficacy if cisplatin, 5-fluorouracil, and paclitaxel regimen for carcinoma of the esophagus. Seminars Rad Oncol 1998.
Adedoyin A, Stiff DD, Smith DC, Romkes M, Bahnson RC, Day R, Hofacker J, Branch RA, Trump DL. All-trans-retinoic acid modulation of drug-metabolizing enzyme activities: Investigation with selective metabolic drug probes. Cancer Chemo & Pharm 41:133-139, 1998.
Day R, Shirey W, Ramakrishnan S, Huang Q. Tumor biology modeling workbench for prospectively evaluating cancer treatments. Proc CESA ‘98 IMACS Multiconference, April 1998.
Reichert TE, Day RS, Wagner EM, Whiteside TL. Absent or low expression of the zeta chain in T cells at the tumor site correlates with poor survival in patients with oral carcinoma. Cancer Res 58(23):5344-5347, 1998.
Grandis JR, Melhem MF, Gooding WE, Day R, Holst VA, Wagener MM, Drenning SD, Tweardy DJ. Tumor levels of TGF and EGFR protein predict survival in patients with head and neck squamous call carcinoma. J Natl Cancer Inst 90(11):824-832, 1998.
Pitman KT, Johnson JT, Edington H, Barnes EL, Day R, Wagner RL, Myers EN. Lymphatic mapping with isoulfan blue dye in head and neck squamous cell carcinoma. Arch Ontolaryn Head Neck Surg 124(7):790-793, 1998.
Kirkwood J, Bryant J, Schiller JH, Oken MM, Borden EC, Whiteside TL. Immunomodulatory function of interferon gamma in patients with metastatic melanoma: Results of a Phase IIB trial in subjects with metastatic melanoma: ECOG Study 4987. J Immunotherapy 20(2):146-157, 1997.
DeMagalhaes-Silverman M, Lister J, Rybka W, Wilson J, Ball E. Busulfan and cyclophosphamide (BU/CY2) as preparative regimen for patients with lymphoma. Bone Marrow Trans 19:777-781, 1997.
Kirkwood JM, Wilson JW, Whiteside TL, Donnelly SL, Herberman RB. Phase Ib trial of Picibanil (OK-432) an as immunomodulator in patients with resected high-risk melanoma. Cancer Immun Immunother 44:137-149, 1997.
DeMagalhaes-Silverman M, Bloom E, Lembersky B, Lister J, Pincus S, Rybka W, Voloshin M, Wilson J, Ball E. High dose chemotherapy and autologous stem cell support followed by posttransplant doxorubicin as initial therapy for metastatic breast cancer. Clin Cancer Res 3:193-197, 1997.
Kozii R, Wilson J, Persichetti J, Phelps V, Ball SEB, Ball ED. THY-1 Expression on blast cells from adult patients with acute myeloid leukemia. Leukemia Res 21:381-85, 1997.
Trump DL, Smith DC, Stiff D, Adedoyin A, Day R, Bahnson RR, Hofacker J, Branch RA. A Phase II trial of all-trans-retinoic acid in hormone-refractory prostate cancer: A clinical trial with detailed pharmacokinetic analysis. Cancer Chemo & Pharm 39(4):349-356, 1997.
Belani CP, Luketich JD, Landreneau RJ, Kim R, Ramanathan RK, Day R, Ferson PF, Keenan RJ, Posner M, Seger J, Lembersky B. Efficacy if cisplatin, 5-fluorouracil, and paclitaxel regimen for carcinoma of the esophagus. Seminars Oncol 24(6):S-19-89-S19-92, 1997.
Getzenberg RH, Light BW, Lapco PI, Konety BR, Nangia AK, Acierno JS, Chir R, Shurin Z, Day RS, Trump DL, Johnson CS. Vitamin D inhibition of prostate adenocarcinoma growth and metastasis in the Dunning rat prostate model system. Urology 50(6):999-1006, 1997.
Belani CP, Aisner J, Bahri S, Jett J, Day R, Capazolli MJ, Hiponia D, Engstrom C. Chemotherapy in non-small cell lung cancer: Pacitaxel/carboplatin/radiotherapy in regionally advanced diseases. Seminars Oncol 23(6 Suppl 16):113-116, 1996.
Shpilberg O, Wilson J, Green M, Nalesnik M, Day R, Herberman RB, Whiteside T. The role of immunological effector-cells in the development of post-transplant lymphoproliferative disorders (PTLD). Blood 86(10)[1]:1354, 1995.
Osborn JL, Schwartz GG, Smith DC, Bahnson R, Day R, Trump DL. Phase II trial of oral 1,25-dihydroxyvitamin d (calcitriol) in hormone refractory prostate cancer. Urologic Oncol 1:195-198, 1995.
Nanmark U, Johansson BR, Bryant JL, Unger ML, Hokland ME, Goldfarb RH, Basse PH. Microvessel origin and distribution in pulmonary metastases of the B16 melanoma: Implications for adoptive immunotherapy. Cancer Res 55:4627-4632, 1995.
Appasamy R, Bryant J, Hassanein T, Van Thiel DH, Whiteside TL. Effects of therapy with alpha interferon on peripheral blood lymphocyte subsets and their cytotoxicity in patients with chronic hepatitis C. Clin Immun Immunopath 73(3):350-357, 1994.
Whiteside TL, Letessier E, Hirabayashi H, Vitolo D, Bryant J, Barnes L, Snyderman C, Johnson JT, Myers E, Herberman RB, Rubin J, Vlock DR. Evidence for local and systemic activation of immune cells in the Phase Ib trial of peritumoral injections of interleukin 2 in patients with advanced squamous cell carcinoma of the head and neck. Cancer Res 53:5654-5662, 1993.
Logan TF, Bryant J, Shannon W, Kane P, Wolmark N, Posner M, Kirkwood JM, Ernstoff M, Futrell JW, Dexter-Straw L, Iwatuski E, Bahnson R. Preparation of viable tumor cell vaccine from human solid tumors: Relationship between tumor and cell yield. Melanoma Res 3:451-455, 1993.
Goldberg J, Gryn J, Raza A, Bennet J, Browman G, Bryant J, Grunwald H, Larson R, Vogler R, Preisler H. Mitoxantrone and 5-azacytidine for refractory/relapsed ANLL or CML in blast crisis: A leukemia intergroup study. Amer J Hemat 43:286-290, 1993.
Gollin SM, Bruno MA, Law J, Ferrell RE, Bryant JL, Johnson JT, Myers EN, Barnes EL, Rossie KM. TP53 abnormalities in oral squamous cell carcinoma. Amer J Human Gen 53(3):303, 1993.
Lese CM, Rossie KM, Appel BN, Johnson JT, Myers EN, Bryant JL, Gollin SM. Aneuploidy in oral squamous cell carcinoma. Amer J. Human Gen 53(3):322, 1993.
Kirkwood JM, Wilson J, Whiteside TL, Bryant J, Vlock DR, Straw L, Herberman RG. Antitumor and immunomodulatory effects of intradermal picibanil (OK-432): Results of a Phase IB trial in high risk melanoma. Cancer Invest 10:20-21, 1992.
Larson RA, Day RS, Axarnia N, Bennett JM, Browman G, Goldberg J, Gottlieb A, Grunwald H, Miller K, Raza A, Vogler R, Winto E, Preisler H. The selective use of amsa following high-dose cytarabine in patients with acute myeloid leukaemia in relapse. Brit J Hema 82:337-346, 1992.
Ernstoff MS, Gooding W, Nair S, Bahnson RR, Miketic LM, Banner B, Day R, Whiteside TL, Titus-Ernstoff L, Kirkwood JM. Immunological effects of treatment with sequential administration of recombinant interferon gamma and alpha in patients with metastatic renal cell carcinoma during a phase I trial. Cancer Res 52:91-103, 1992.
Logan T, Kaplan S, Bryant J, Ernstoff M, Krause M, Kirkwood J. Granulocytopenia in cancer patients treated in a Phase I trial with recombinant human tumor necrosis factor (TNF). J Immunotherapy 10:84-95, 1991.
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Dept. of Biostatistics, University of Pittsburgh

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