Statistical issues in survival analysis (Nature article 3556)
April 10, 2024 The authors aimed to assess overall survival rates for colorectal cancer (CRC) at 3 years and also identify the associated prognostic factors amongst patients in Morocco using a machine learning approach, a random survival forest (RSF). CRC has...
Statistical issues in survival analysis (Part XVVV)
March 27, 2024 In this article, the authors described their Schemper-Henderson measure to account for explained variation for survival outcomes, extended to allow for competing risks. They defied explained variation as the relative gain in predictive accuracy when...
Statistical issues in survival analysis (Part XVVIV)
March 13, 2024 New immunotherapies for cancer have shown to have different treatment effects often with delay compared to other cytotoxic treatments and, therefore, this has called for different ways of modeling the survival curves. The usual log-rank test has relied...
Statistical issues in survival analysis (Part XVVIII)
February 26, 2024 TABLE 1. Summary of the available methods for survival regression with competing risks (CR). Model Type Proportional hazards (PH) High dimensions (�) Missing data Approaches based on a cause-specific hazard specification Cox proportional CS hazard...
Statistical issues in general (Part IV)
In an article in Biometrical Journal, Heinze et al discussed phases of methodological research in biostatistics. The authors of this publication are all members of an international STRATOS (STRengthening Analytical Thinking for Observational Studies) Intiative, whose...
Statistical issues in survival analysis (Part XVVII)
January 31, 2024 In an article that appeared in Biometrical Journal, Hu described a new random-intercept accelerated failure time model with Bayesian additive regression trees (riAFT-BART), which can be used to draw causal inferences on population treatment effectts...
Statistical issues in survival analysis (Part XVVI)
January 17, 2023 In an article that appeared in Biometrical Journal, Hoogland et al (2023) had aimed to combine the benefits of flexible parametric survival modeling and regularization in order to improve risk prediction modeling in the context of time-to-event data....
Statistical issues in general (Part III)
January 3, 2023 In an article that appeared in Biometrical Journal, Le Bourdonnec et al (2023) discussed a method to address unmeasured confounding in cohort studies by an instrumental varible (IV) method for a time fixed expousre on an outcome trajectory, repeatedly...
Statistical issues in survival analysis (Part XVV)
December 20, 2023 In article that appeared in Statistics in Medicine, Denz et al explored different methods for modeling of adjusted survival curves especially in observational studies, which tend to have issues with confounding. The authors also brought in...
Statistical issues in survival analysis (Part XVIV)
December 6, 2023 In article that appeared in Biostatistics, Wu et al describe a joint modeling approach of longitduinal data like quality of life and survival data on a retrospective time scale and handling of informative censoring issues in a two arm clinical trial...