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Updated: Feb 20, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[Use of prognostic knowledge in the planning and analysis of randomized therapeutic trials]
Abstract:
For most diseases, one observes great variability in clinical course and response to therapy which should be taken into account in the design and the analysis of clinical trials. Eligibility criteria and stratified randomization use prognostic knowledge. A suitable analysis of randomized studies includes: (1) checking treatment effect groups for comparability, (2) adjustment of treatment effect by stratifying or modeling to account for any imbalances in prognostic factors and to increase the precision of the treatment comparison by reducing random variation, (3) looking for treatment-covariate interactions suggesting that response to treatment depends on patients' characteristics. Tests for interaction should be interpreted with caution in light of medical plausibility; multiple comparisons should be taken into account. Recording information on known prognostic factors in clinical trials is important, as is the continuing search for new ones.
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