Grant Number:	5R00CA248335-05 Interpret this number
Primary Investigator:	Dickerman, Barbra
Organization:	Harvard School Of Public Health
Project Title:	Identifying Optimal Dynamic Strategies for Prostate Cancer Control
Fiscal Year:	2024

PROJECT SUMMARY/ABSTRACT Big Data has the potential to revolutionize cancer research and care, but extracting the information it holds on the optimal strategies for cancer control will require cutting-edge tools in data science. The optimal strategies for cancer control will be dynamic strategies that adapt clinical decisions over time to a patient’s evolving clinical history. Unfortunately, conventional statistical methods cannot appropriately compare dynamic strategies, so we need methods specifically designed for this task: g-methods. G-methods have helped to shape clinical care in many areas, but they have not been systematically applied to cancer research. Further, while g-methods let us validly estimate the effect of pre-specified strategies, these may not be the optimal strategies. My overarching goal is to apply and further develop analytic methods to learn the optimal strategies for cancer control from complex longitudinal data and generate user-friendly, publicly-available software to make these methods available to the cancer research community. I will apply these methods to answer key clinical questions across the prostate cancer control continuum: 1) the optimal dietary and lifestyle strategies to prevent aggressive prostate cancer, 2) the optimal screening strategy following a baseline PSA test to maximize detection of aggressive disease while minimizing detection of indolent tumors, and 3) the optimal statin therapy strategy to maximize survival among men with nonmetastatic prostate cancer. This project will leverage data from a large prospective cohort study and a novel platform of electronic health records linked with genetic data. I will first apply g-methods to estimate the effects of recommended strategies for cancer control that a randomized trial would have limited feasibility to evaluate. I will then investigate whether novel methods that learn the optimal strategies from the data may lead to improved, targeted recommendations that get the right interventions to the right people at the right time. This innovative project will advance comparative effectiveness research for cancer care at the cutting edge of data science. I am optimally positioned to undertake this research based on my 1) expertise in cancer, epidemiology, and causal inference; 2) exceptional multidisciplinary mentoring team comprised of global leaders in their respective fields; and 3) unparalleled research environment to support my career development. Through this work, I will expand my expertise in new areas, including machine learning. The proposed research and training will help me achieve my long-term career goal to become an independent investigator and lead a transdisciplinary research program that integrates causal inference and machine learning to identify optimal strategies for cancer control. Leveraging rich, existing data, this proposal represents a significant opportunity to develop, apply, and disseminate powerful methods for big clinical data to accelerate progress in cancer research and care.




Neighborhood greenness and long-term physical and psychosocial quality of life among prostate cancer survivors in the Health Professionals Follow-up Study.
Authors: Chen N. , Hu C.R. , Iyer H.S. , James P. , Dickerman B.A. , Mucci L.A. , Nethery R.C. .
Source: Environmental Research, 2024-08-24 00:00:00.0; 262(Pt 1), p. 119847.
EPub date: 2024-08-24 00:00:00.0.
PMID: 39187150
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Prostate-Specific Antigen Screening and Prostate Cancer Mortality: An Emulation of Target Trials in US Medicare.
Authors: García-Albéniz X. , Hsu J. , Etzioni R. , Chan J.M. , Shi J. , Dickerman B. , Hernán M.A. .
Source: Jco Clinical Cancer Informatics, 2024 Aug; 8, p. e2400094.
PMID: 39159422
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Social integration and long-term physical and psychosocial quality of life among prostate cancer survivors in the Health Professionals Follow-up Study.
Authors: Chen N. , McGrath C.B. , Stopsack K.H. , Morgans A.K. , Nethery R.C. , Dickerman B.A. , Mucci L.A. .
Source: Journal Of Cancer Survivorship : Research And Practice, 2024-07-01 00:00:00.0; , .
EPub date: 2024-07-01 00:00:00.0.
PMID: 38951371
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Comparison of the Test-negative Design and Cohort Design With Explicit Target Trial Emulation for Evaluating COVID-19 Vaccine Effectiveness.
Authors: Li G. , Gerlovin H. , Figueroa Muñiz M.J. , Wise J.K. , Madenci A.L. , Robins J.M. , Aslan M. , Cho K. , Gaziano J.M. , Lipsitch M. , et al. .
Source: Epidemiology (cambridge, Mass.), 2024-03-01 00:00:00.0; 35(2), p. 137-149.
EPub date: 2023-12-18 00:00:00.0.
PMID: 38109485
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Prostate Cancer Screening in African American Men: A Review of the Evidence.
Authors: Kensler K.H. , Johnson R. , Morley F. , Albrair M. , Dickerman B.A. , Gulati R. , Holt S.K. , Iyer H.S. , Kibel A.S. , Lee J.R. , et al. .
Source: Journal Of The National Cancer Institute, 2023-09-15 00:00:00.0; , .
EPub date: 2023-09-15 00:00:00.0.
PMID: 37713266
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Development of the TrAnsparent ReportinG of observational studies Emulating a Target trial (TARGET) guideline.
Authors: Hansford H.J. , Cashin A.G. , Jones M.D. , Swanson S.A. , Islam N. , Dahabreh I.J. , Dickerman B.A. , Egger M. , Garcia-Albeniz X. , Golub R.M. , et al. .
Source: Bmj Open, 2023-09-12 00:00:00.0; 13(9), p. e074626.
EPub date: 2023-09-12 00:00:00.0.
PMID: 37699620
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Reporting of Observational Studies Explicitly Aiming to Emulate Randomized Trials: A Systematic Review.
Authors: Hansford H.J. , Cashin A.G. , Jones M.D. , Swanson S.A. , Islam N. , Douglas S.R.G. , Rizzo R.R.N. , Devonshire J.J. , Williams S.A. , Dahabreh I.J. , et al. .
Source: Jama Network Open, 2023-09-05 00:00:00.0; 6(9), p. e2336023.
EPub date: 2023-09-05 00:00:00.0.
PMID: 37755828
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Evaluating Metformin Strategies for Cancer Prevention: A Target Trial Emulation Using Electronic Health Records.
Authors: Dickerman B.A. , García-Albéniz X. , Logan R.W. , Denaxas S. , Hernán M.A. .
Source: Epidemiology (cambridge, Mass.), 2023-09-01 00:00:00.0; 34(5), p. 690-699.
EPub date: 2023-05-23 00:00:00.0.
PMID: 37227368
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Comparative effectiveness of third doses of mRNA-based COVID-19 vaccines in US veterans.
Authors: Dickerman B.A. , Gerlovin H. , Madenci A.L. , Figueroa Muñiz M.J. , Wise J.K. , Adhikari N. , Ferolito B.R. , Kurgansky K.E. , Gagnon D.R. , Cho K. , et al. .
Source: Nature Microbiology, 2023 Jan; 8(1), p. 55-63.
EPub date: 2023-01-02 00:00:00.0.
PMID: 36593297
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Tenofovir disoproxil fumarate and coronavirus disease 2019 outcomes in men with HIV.
Authors: Li G. , Park L.S. , Lodi S. , Logan R.W. , Cartwright E.J. , Aoun-Barakat L. , Casas J.P. , Dickerman B.A. , Rentsch C.T. , Justice A.C. , et al. .
Source: Aids (london, England), 2022-10-01 00:00:00.0; 36(12), p. 1689-1696.
EPub date: 2022-07-15 00:00:00.0.
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Comparative Safety of BNT162b2 and mRNA-1273 Vaccines in a Nationwide Cohort of US Veterans.
Authors: Dickerman B.A. , Madenci A.L. , Gerlovin H. , Kurgansky K.E. , Wise J.K. , Figueroa Muñiz M.J. , Ferolito B.R. , Gagnon D.R. , Gaziano J.M. , Cho K. , et al. .
Source: Jama Internal Medicine, 2022-07-01 00:00:00.0; 182(7), p. 739-746.
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A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses' Health Studies.
Authors: Brantley K.D. , Zeleznik O.A. , Dickerman B.A. , Balasubramanian R. , Clish C.B. , Avila-Pacheco J. , Rosner B. , Tamimi R.M. , Eliassen A.H. .
Source: British Journal Of Cancer, 2022-06-18 00:00:00.0; , .
EPub date: 2022-06-18 00:00:00.0.
PMID: 35717425
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Predicting counterfactual risks under hypothetical treatment strategies: an application to HIV.
Authors: Dickerman B.A. , Dahabreh I.J. , Cantos K.V. , Logan R.W. , Lodi S. , Rentsch C.T. , Justice A.C. , Hernán M.A. .
Source: European Journal Of Epidemiology, 2022-02-22 00:00:00.0; , .
EPub date: 2022-02-22 00:00:00.0.
PMID: 35190946
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Comparative Effectiveness of BNT162b2 and mRNA-1273 Vaccines in U.S. Veterans.
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Source: The New England Journal Of Medicine, 2022-01-13 00:00:00.0; 386(2), p. 105-115.
EPub date: 2021-12-01 00:00:00.0.
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Estimating the effect of nutritional interventions using observational data: the American Heart Association's 2020 Dietary Goals and mortality.
Authors: Chiu Y.H. , Chavarro J.E. , Dickerman B.A. , Manson J.E. , Mukamal K.J. , Rexrode K.M. , Rimm E.B. , Hernán M.A. .
Source: The American Journal Of Clinical Nutrition, 2021-08-02 00:00:00.0; 114(2), p. 690-703.
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Association of pre-diagnostic blood metabolomics with prostate cancer defined by ERG or PTEN molecular subtypes.
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Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2021-02-24 00:00:00.0; , .
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Emulating a target trial in case-control designs: an application to statins and colorectal cancer.
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Source: International Journal Of Epidemiology, 2020-10-01 00:00:00.0; 49(5), p. 1637-1646.
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Counterfactual prediction is not only for causal inference.
Authors: Dickerman B.A. , Hernán M.A. .
Source: European Journal Of Epidemiology, 2020 Jul; 35(7), p. 615-617.
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