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Grant Details

Grant Number: 5R01CA234538-05 Interpret this number
Primary Investigator: Ward, Kevin
Organization: Emory University
Project Title: Registering Cancer Recurrences in the Georgia Cancer Registry
Fiscal Year: 2023


There are 15 million US cancer survivors, most diagnosed with early-stage disease, so at risk for a cancer recurrence. There is no population-based information about the risk of cancer recurrence. For decades, mortality has been the only outcome available to monitor progress in cancer care. As cancer care has improved, however, the correspondence between recurrence and mortality has diminished. A recent commentary in the Journal of the National Cancer Institute emphasized that the lack of surveillance data on recurrence is a barrier to comparative effectiveness research in the realm of cancer care and to research on cancer quality-of-care. In the clinical setting, the lack of even basic recurrence risk data by cancer type and stage is a barrier to informed patient-physician decision-making and risk stratification. A high-quality registry of cancer recurrences would fill these gaps, open new avenues for cancer research, and enable improvements in clinical care tied directly to the most salient and immediate outcome for all early-stage cancer patients. Georgia provides an ideal setting for the first-ever registry of cancer recurrences. The population of about 10 million is diverse with respect to all major demographic characteristics. The large population ensures that adequate data on recurrences will accumulate rapidly. The diverse population assures that heterogeneity of recurrence risk by demographic characteristics will be adequately characterized. The Georgia Cancer Registry has been a long-term member of the National Cancer Institute’s Surveillance Epidemiology and End Results program, the National Program for Cancer Registries established by the Centers for Disease Control and Prevention, and the North American Association of Central Cancer Registries. Thus, Georgia has the right population and the Georgia Cancer Registry has the right infrastructure to accomplish the following two aims: Aim #1: Use six data streams to signal potential recurrences occuring among Georgia cancer survivors diagnosed with one of four cancer types (breast, prostate, colorectal, or lymphoma), review medical records to validate true recurrences, and implement constant learning processes to improve accuracy, efficiency, and sustainability of the registration process. Aim #2: For these four cancer types, which represent 43% of incident cases and 58% of prevalent survivors in the US, generate the first-ever descriptive data on the risks and rates of recurrence over ten years of follow-up and evaluate how these vary by demographic characteristics. By achieving these aims, we will fill an important gap in the knowledge base regarding cancer outcomes and provide a foundation for innovative research on patterns and predictors of recurrence. The recurrence data will be available to other researchers through existing mechanisms, so resource sharing will be enabled from the outset. Furthermore, as the infrastructure solidifies and the methods are optimized, the recurrence registration protocols will be transportable to cancer registries with similar infrastructure and legal authority .


A Design and Analytical Strategy for Monitoring Disease Positivity and Biomarker Levels in Accessible Closed Populations.
Authors: Lyles R.H. , Zhang Y. , Ge L. , Waller L.A. .
Source: American journal of epidemiology, 2024-01-08; 193(1), p. 193-202.
PMID: 37625449
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Tailoring capture-recapture methods to estimate registry-based case counts based on error-prone diagnostic signals.
Authors: Ge L. , Zhang Y. , Ward K.C. , Lash T.L. , Waller L.A. , Lyles R.H. .
Source: Statistics in medicine, 2023-07-30; 42(17), p. 2928-2943.
EPub date: 2023-05-09.
PMID: 37158167
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Validation of LexisNexis Accurint in the Georgia Cancer Registry's Cancer Recurrence and Information Surveillance Program.
Authors: Woolpert K.M. , Ward K.C. , England C.V. , Lash T.L. .
Source: Epidemiology (Cambridge, Mass.), 2021-05-01; 32(3), p. 434-438.
PMID: 33591053
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Adaptive Validation Design: A Bayesian Approach to Validation Substudy Design With Prospective Data Collection.
Authors: Collin L.J. , MacLehose R.F. , Ahern T.P. , Nash R. , Getahun D. , Roblin D. , Silverberg M.J. , Goodman M. , Lash T.L. .
Source: Epidemiology (Cambridge, Mass.), 2020 Jul; 31(4), p. 509-516.
PMID: 32483065
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Application of the Adaptive Validation Substudy Design to Colorectal Cancer Recurrence.
Authors: Collin L.J. , Riis A.H. , MacLehose R.F. , Ahern T.P. , Erichsen R. , Thorlacius-Ussing O. , Lash T.L. .
Source: Clinical epidemiology, 2020; 12, p. 113-121.
EPub date: 2020-02-03.
PMID: 32099477
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