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Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and cohort identification.

ABSTRACT: The Chronic Hepatitis Cohort Study (CHeCS) is a longitudinal observational study of risks and benefits of treatments and care in patients with chronic hepatitis B (HBV) and C (HCV) infection from four US health systems. We hypothesized that comparative effectiveness methods-including a centralized data management system and an adaptive approach for cohort selection-would improve cohort selection while controlling data quality and reducing the cost.Cohort selection and data collection were performed primarily via the electronic health record (EHR); cases were confirmed via chart abstraction. Two parallel sources fed data to a centralized data management system: direct EHR data collection with common data elements, and chart abstraction via electronic data capture. An adaptive Classification and Regression Tree (CART) identified a set of electronic variables to improve case ascertainment accuracy.Over 16 million patient records were collected on 23 case report forms in 2006-2008. The vast majority of data (99.2%) were collected electronically from EHR; only 0.8% was collected via chart abstraction. Initial electronic criteria identified 12,144 chronic hepatitis patients; 10,098 were confirmed via chart abstraction with positive predictive values (PPV) 79 and 83% for HBV and HCV, respectively. CART-optimized models significantly increased PPV to 88 for HBV and 95% for HCV.CHeCS is a comparative effectiveness research project that leverages electronic centralized data collection and adaptive cohort identification approaches to enhance study efficiency. The adaptive CART model significantly improved the positive predictive value of cohort identification methods.

SUBMITTER: Lu M

PROVIDER: S-EPMC5719869 | biostudies-other | 2014 Dec

REPOSITORIES: biostudies-other

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Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and cohort identification.

Lu Mei M Rupp Loralee B LB Moorman Anne C AC Li Jia J Zhang Talan T Lamerato Lois E LE Holmberg Scott D SD Spradling Philip R PR Teshale Eyasu H EH Vijayadeva Vinutha V Boscarino Joseph A JA Schmidt Mark A MA Nerenz David R DR Gordon Stuart C SC

Digestive diseases and sciences 20140717 12

<h4>Background and aims</h4>The Chronic Hepatitis Cohort Study (CHeCS) is a longitudinal observational study of risks and benefits of treatments and care in patients with chronic hepatitis B (HBV) and C (HCV) infection from four US health systems. We hypothesized that comparative effectiveness methods-including a centralized data management system and an adaptive approach for cohort selection-would improve cohort selection while controlling data quality and reducing the cost.<h4>Methods</h4>Coho ...[more]

PMID: 25030940

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Project description:ImportanceResearchers often analyze cancer registry data to assess for differences in survival among cancer treatments. However, the retrospective, nonrandomized design of these analyses raises questions about study validity.ObjectiveTo examine the extent to which comparative effectiveness analyses using observational cancer registry data produce results concordant with those of randomized clinical trials.Design, setting, and participantsIn this comparative effectiveness study, a total of 141 randomized clinical trials referenced in the National Comprehensive Cancer Network Clinical Practice Guidelines for 8 common solid tumor types were identified. Data on participants within the National Cancer Database (NCDB) diagnosed between 2004 and 2014, matching the eligibility criteria of the randomized clinical trial, were obtained. The present study was conducted from August 1, 2017, to September 10, 2019. The trials included 85 118 patients, and the corresponding NCDB analyses included 1 344 536 patients. Three Cox proportional hazards regression models were used to determine hazard ratios (HRs) for overall survival, including univariable, multivariable, and propensity score-adjusted models. Multivariable and propensity score analyses controlled for potential confounders, including demographic, comorbidity, clinical, treatment, and tumor-related variables.Main outcomes and measuresThe main outcome was concordance between the results of randomized clinical trials and observational cancer registry data. Hazard ratios with an NCDB analysis were considered concordant if the NDCB HR fell within the 95% CI of the randomized clinical trial HR. An NCDB analysis was considered concordant if both the NCDB and clinical trial P values for survival were nonsignificant (P ≥ .05) or if they were both significant (P < .05) with survival favoring the same treatment arm in the NCDB and in the randomized clinical trial.ResultsAnalyses using the NCDB-produced HRs for survival were concordant with those of 141 randomized clinical trials in 79 univariable analyses (56%), 98 multivariable analyses (70%), and 90 propensity score models (64%). The NCDB analyses produced P values concordant with randomized clinical trials in 58 univariable analyses (41%), 65 multivariable analyses (46%), and 63 propensity score models (45%). No clinical trial characteristics were associated with concordance between NCDB analyses and randomized clinical trials, including disease site, type of clinical intervention, or severity of cancer.Conclusions and relevanceThe findings of this study suggest that comparative effectiveness research using cancer registry data often produces survival outcomes discordant with those of randomized clinical trial data. These findings may help provide context for clinicians and policy makers interpreting observational comparative effectiveness research in oncology.

Dataset Information

Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and cohort identification.

Publications

Comparative effectiveness research of chronic hepatitis B and C cohort study (CHeCS): improving data collection and cohort identification.

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