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Influence of incomplete death information on cumulative risk estimates in US claims data. | LitMetric

AI Article Synopsis

  • Administrative claims databases often lack accurate records of death, leading researchers to mistakenly treat death as just another reason for study withdrawal instead of a critical competing event.
  • A study analyzed nearly 35,000 patients over 1, 3, and 5 years, comparing cardiovascular risks between those taking telmisartan and ramipril, finding significant differences in risk estimates affected by how death is treated in the analysis.
  • Results showed that as the follow-up time increased and patients' age rose, the disparities between cause-specific and subdistribution cumulative risks grew, emphasizing the need for researchers to consider baseline mortality risk when using incomplete databases.

Article Abstract

Administrative claims databases often do not capture date or fact of death, so studies using these data may inappropriately treat death as a censoring event-equivalent to other withdrawal reasons-rather than a competing event. We examined 1-, 3-, and 5-year inverse-probability-of-treatment weighted cumulative risks of a composite cardiovascular outcome among 34 527 initiators of telmisartan (exposure) and ramipril (referent), who were aged ≥55 years, in Optum (United States) claims data from 2003 to 2020. Differences in cumulative risks of the cardiovascular endpoint due to censoring of death (cause-specific), as compared with treating death as a competing event (subdistribution), increased with greater follow-up time and older age, where event and mortality risks were higher. Among ramipril users, 5-year cause-specific and subdistribution cumulative risk estimates per 100, respectively, were 16.4 (95% CI, 15.3-17.5) and 16.2 (95% CI, 15.1-17.3) among ages 55-64 (difference = 0.2) and were 43.2 (95% CI, 41.3-45.2) and 39.7 (95% CI, 37.9-41.4) among ages ≥75 (difference = 3.6). Plasmode simulation results demonstrated the differences in cause-specific versus subdistribution cumulative risks to increase with increasing mortality rate. We suggest researchers consider the cohort's baseline mortality risk when deciding whether real-world data with incomplete death information can be used without concern. This article is part of a Special Collection on Pharmacoepidemiology.

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Source
http://dx.doi.org/10.1093/aje/kwae034DOI Listing

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