The role of the Biostatistics Core is to support the investigators of the SPORE in Prostate Cancer in their research efforts, including laboratory experiments and the design and analysis of clinical trials. In preclinical studies, core members will assist in the formulation of the experimental design and in the analysis and interpretation of the data at the conclusion of the study. In the clinical trial design phase, a core member will conduct a protocol review with the principal investigator. Based on this review, a statistical section for the protocol will be provided, outlining major scientific objectives, population to be studied, primary and secondary endpoints, experimental design, a randomization procedure if necessary, analysis plans, and a targeted sample size justified in probabilistic terms. At the conclusion of the trial, data analyses will be performed to assess outcomes of the primary and secondary endpoints stated in the protocol.
The specific aims of the Biostatistics Core are to:
Aim 1 : Contribute to the design and analysis of laboratory-based prostate cancer research Aim 2: Contribute to the design and analysis of clinical studies in prostate cancer Aim 3: Develop statistical methodology that will assist in the advancement of prostate cancer research
The Biostatistics Core assists the research efforts of the MSKCC SPORE in Prostate Cancer investigators, contributing to the design and analysis of clinical and laboratory research and the development of valid conclusions. The core provides statistical analysis and consultancy as well as ongoing quality assurance. The core has also established a data quality working group to improve the quality of SPORE data.
|Loeb, Stacy; Lilja, Hans; Vickers, Andrew (2016) Beyond prostate-specific antigen: utilizing novel strategies to screen men for prostate cancer. Curr Opin Urol 26:459-65|
|Fleshner, Katherine; Assel, Melissa; Benfante, Nicole et al. (2016) Clinical Findings and Treatment Outcomes in Patients with Extraprostatic Extension Identified on Prostate Biopsy. J Urol 196:703-8|
|Carlsson, Sigrid V; de Carvalho, Tiago M; Roobol, Monique J et al. (2016) Estimating the harms and benefits of prostate cancer screening as used in common practice versus recommended good practice: A microsimulation screening analysis. Cancer 122:3386-3393|
|Zelefsky, Michael J; Poon, Bing Ying; Eastham, James et al. (2016) Longitudinal assessment of quality of life after surgery, conformal brachytherapy, and intensity-modulated radiation therapy for prostate cancer. Radiother Oncol 118:85-91|
|Kent, Matthew; Penson, David F; Albertsen, Peter C et al. (2016) Successful external validation of a model to predict other cause mortality in localized prostate cancer. BMC Med 14:25|
|Scher, Howard I; Lu, David; Schreiber, Nicole A et al. (2016) Association of AR-V7 on Circulating Tumor Cells as a Treatment-Specific Biomarker With Outcomes and Survival in Castration-Resistant Prostate Cancer. JAMA Oncol 2:1441-1449|
|Sood, Anup; Miller, Alexandra M; Brogi, Edi et al. (2016) Multiplexed immunofluorescence delineates proteomic cancer cell states associated with metabolism. JCI Insight 1:|
|Danila, Daniel C; Samoila, Aliaksandra; Patel, Chintan et al. (2016) Clinical Validity of Detecting Circulating Tumor Cells by AdnaTest Assay Compared With Direct Detection of Tumor mRNA in Stabilized Whole Blood, as a Biomarker Predicting Overall Survival for Metastatic Castration-Resistant Prostate Cancer Patients. Cancer J 22:315-320|
|Braun, Katharina; Sjoberg, Daniel D; Vickers, Andrew J et al. (2016) A Four-kallikrein Panel Predicts High-grade Cancer on Biopsy: Independent Validation in a Community Cohort. Eur Urol 69:505-11|
|Preston, Mark A; Batista, Julie L; Wilson, Kathryn M et al. (2016) Baseline Prostate-Specific Antigen Levels in Midlife Predict Lethal Prostate Cancer. J Clin Oncol 34:2705-11|
Showing the most recent 10 out of 424 publications