The impact of different censoring methods for analyzing survival using real-world data with linked mortality information: a simulation study

Researchers should consider the completeness of linked external mortality information when choosing how to censor the analysis of overall survival using RWD. Substantial bias in median survival estimates can occur if an inappropriate censoring scheme is selected. We advocate for RWD providers to perform validation studies of their mortality data and publish their findings to inform methodological decisions better.

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Publication Details

Journal
BMC Medical Research Methodology
Published
2024-09-13
DOI
https://doi.org/10.1186/s12874-024-02313-3
Citations
7
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
11.95
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article

The impact of different censoring methods for analyzing survival using real-world data with linked mortality information: a simulation study

Craig S. Parzynski, Aaron Crowley, Wei‐Chun Hsu
7 citations
BMC Medical Research Methodology
Insurance, Mortality, Demography, Risk Management
11.95
article

The impact of different censoring methods for analyzing survival using real-world data with linked mortality information: a simulation study

Craig S. Parzynski, Aaron Crowley, Wei‐Chun Hsu
article en
7 citations

Abstract

Researchers should consider the completeness of linked external mortality information when choosing how to censor the analysis of overall survival using RWD. Substantial bias in median survival estimates can occur if an inappropriate censoring scheme is selected. We advocate for RWD providers to perform validation studies of their mortality data and publish their findings to inform methodological decisions better.

BMC Medical Research MethodologyVol. 24(1)
Stevens Institute of Technology (US), Genesis Research Institute (JP)
Openalex Percentile: Top 2%
Insurance, Mortality, Demography, Risk Management
11.95
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