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Virtual Pooled Registry-Cancer Linkage System: an improved method for ascertaining cancer diagnoses. | LitMetric

Background: The National Cancer Institute funds many large cohort studies that rely on self-reported cancer data requiring medical record validation. This is labor intensive, costly, and prone to underreporting or misreporting of cancer and disparity-related differential response. US population-based central cancer registries identify incident cancer within their catchment area, yielding all malignant neoplasms and benign brain and central nervous system tumors with standardized data fields. This manuscript describes the development, implementation, and features of a system to facilitate linkage between cohort studies and cancer registries and the release of cancer registry data for matched cohort participants.

Methods: The Virtual Pooled Registry-Cancer Linkage System (VPR-CLS) provides an online system to link cohorts with multiple state cancer registries by 1) securely transmitting a study file to registries, 2) providing an optimized linkage algorithm to generate preliminary match counts, and 3) providing a streamlined process and templated forms for submitting and tracking data requests for cohort participants who matched with registries.

Results: In 2022, the VPR-CLS launched with 45 registries, covering 95% of the US state populations and Puerto Rico. Registries have linked with 15 studies having 14 273-10.9 million participants. Except in 1 study, linkage sensitivity ranged from 87.0% to 99.9%. Numerous registries have adopted the VPR-CLS templated institutional review board-registry application (n = 39), templated data use agreement (n = 25), and central institutional review board (n = 16).

Conclusions: The VPR-CLS markedly improves ascertainment of cancer outcomes and is the preferred approach for determination of outcomes from cohort studies, postmarketing surveillance, and clinical trials.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11300027PMC
http://dx.doi.org/10.1093/jncimonographs/lgae005DOI Listing

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