Reflection on modern methods: trial emulation in the presence of immortal-time bias. Assessing the benefit of major surgery for elderly lung cancer patients using observational data
| Autor: | Aurélien Belot, Bernard Rachet, Camille Maringe, Matthew Smith, Aimilia Exarchakou, Sara Benitez Majano, Clemence Leyrat |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Observational data Epidemiology Education Corner elderly 03 medical and health sciences 0302 clinical medicine Covariate medicine AcademicSubjects/MED00860 030212 general & internal medicine Lung cancer Survival analysis business.industry Confounding Contrast (statistics) inverse-probability-of-censoring weighting General Medicine trial emulation medicine.disease Surgery lung cancer immortal-time bias 030220 oncology & carcinogenesis Censoring (clinical trials) Cohort Observational study business |
| Zdroj: | International Journal of Epidemiology |
| ISSN: | 0300-5771 |
| Popis: | Acquiring real-world evidence is crucial to support health policy, but observational studies are prone to serious biases. An approach was recently proposed to overcome confounding and immortal-time biases within the emulated trial framework. This tutorial provides a step-by-step description of the design and analysis of emulated trials, as well as R and Stata code, to facilitate its use in practice. The steps consist in: (i) specifying the target trial and inclusion criteria; (ii) cloning patients; (iii) defining censoring and survival times; (iv) estimating the weights to account for informative censoring introduced by design; and (v) analysing these data. These steps are illustrated with observational data to assess the benefit of surgery among 70–89-year-old patients diagnosed with early-stage lung cancer. Because of the severe unbalance of the patient characteristics between treatment arms (surgery yes/no), a naïve Kaplan-Meier survival analysis of the initial cohort severely overestimated the benefit of surgery on 1-year survival (22% difference), as did a survival analysis of the cloned dataset when informative censoring was ignored (17% difference). By contrast, the estimated weights adequately removed the covariate imbalance. The weighted analysis still showed evidence of a benefit, though smaller (11% difference), of surgery among older lung cancer patients on 1-year survival. Complementing the CERBOT tool, this tutorial explains how to proceed to conduct emulated trials using observational data in the presence of immortal-time bias. The strength of this approach is its transparency and its principles that are easily understandable by non-specialists. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|