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Purpose: Cancer of the prostate (CaP) is the leading cancer among men in sub-Saharan Africa (SSA). A substantial proportion of these men with CaP are diagnosed at late (usually incurable) stages, yet little is known about the etiology of CaP in SSA. Methods: We established the Men of African Descent and Carcinoma of the Prostate Network, which includes seven SSA centers partnering with five US centers to study the genetics and epidemiology of CaP in SSA. We developed common data elements and instruments, regulatory infrastructure, and biosample collection, processing, and shipping protocols. We tested this infrastructure by collecting epidemiologic, medical record, and genomic data from a total of 311 patients with CaP and 218 matched controls recruited at the seven SSA centers. We extracted genomic DNA from whole blood, buffy coat, or buccal swabs from 265 participants and shipped it to the Center for Inherited Disease Research (Baltimore, MD) and the Centre for Proteomics and Genomics Research (Cape Town, South Africa), where genotypes were generated using the UK Biobank Axiom Array. Results: We used common instruments for data collection and entered data into the shared database. Double-entered data from pilot participants showed a 95% to 98% concordance rate, suggesting that data can be collected, entered, and stored with a high degree of accuracy. Genotypes were obtained from 95% of tested DNA samples (100% from blood-derived DNA samples) with high concordance across laboratories. Conclusion: We provide approaches that can produce high-quality epidemiologic and genomic data in multicenter studies of cancer in SSA.

Purpose: Health research in low- and middle-income countries can generate novel scientific knowledge and improve clinical care, fostering population health improvements to prevent premature death. Project management is a critical part of the success of this research, applying knowledge, skills, tools, and techniques to accomplish required goals. Here, we describe the development and implementation of tools to support a multifaceted study of prostate cancer in Africa, focusing on building strategic and operational capacity. Methods: Applying a learning organizational framework, we developed and implemented a project management toolkit (PMT) that includes a management process flowchart, a cyclical center-specific schedule of activities, periodic reporting and communication, and center-specific monitoring and evaluation metrics. Results: The PMT was successfully deployed during year one of the project with effective component implementation occurring through periodic cycles of dissemination and feedback to local center project managers. A specific evaluation was conducted 1 year after study initiation to obtain enrollment data, evaluate individual quality control management plans, and undertake risk log assessments and follow-up. Pilot data obtained identified areas in which centers required mentoring, strengthening, and capacity development. Strategies were implemented to improve project goals and operational capacity through local problem solving, conducting quality control checks and following compliancy with study aims. Moving forward, centers will perform quarterly evaluations and initiate strengthening measures as required. Conclusion: The PMT has fostered the development of both strategic and operational capacity across project centers. Investment in project management resources is essential to ensuring high-quality, impactful health research in low- and middle-income countries.

Purpose: Cancer of the prostate (CaP) is the leading cancer among men in sub-Saharan Africa (SSA). A substantial proportion of these men with CaP are diagnosed at late (usually incurable) stages, yet little is known about the etiology of CaP in SSA., Methods: We established the Men of African Descent and Carcinoma of the Prostate Network, which includes seven SSA centers partnering with five US centers to study the genetics and epidemiology of CaP in SSA. We developed common data elements and instruments, regulatory infrastructure, and biosample collection, processing, and shipping protocols. We tested this infrastructure by collecting epidemiologic, medical record, and genomic data from a total of 311 patients with CaP and 218 matched controls recruited at the seven SSA centers. We extracted genomic DNA from whole blood, buffy coat, or buccal swabs from 265 participants and shipped it to the Center for Inherited Disease Research (Baltimore, MD) and the Centre for Proteomics and Genomics Research (Cape Town, South Africa), where genotypes were generated using the UK Biobank Axiom Array., Results: We used common instruments for data collection and entered data into the shared database. Double-entered data from pilot participants showed a 95% to 98% concordance rate, suggesting that data can be collected, entered, and stored with a high degree of accuracy. Genotypes were obtained from 95% of tested DNA samples (100% from blood-derived DNA samples) with high concordance across laboratories., Conclusion: We provide approaches that can produce high-quality epidemiologic and genomic data in multicenter studies of cancer in SSA.