Damiano CerasuoloMany clinical studies evaluate the benefit of a treatment based on both survival and other continuous/ordinal clinical outcomes, such as quality of life scores. In these studies, when subjects die before the follow-up assessment, the clinical outcomes become undefined and are truncated by death. Treating outcomes as “missing” or “censored” due to death can be misleading for treatment effect evaluation.
Interesting reading: Kernel Cox partially linear regression.
Building kernel Cox proportional hazards semi-parametric model and regularized garrotized kernel machine (RegGKM) method to account wide heterogeneity in cancer patients’ survival due to molecular profiles. #stats #StatisticsInMedicine #statsodon
Résumé: "Much of the art of applied statistics and the skills of a trained statistician or epidemiologist involve factors that lie outside the data and, hence, cannot be captured by data-driven AI algorithms alone." #AI #Stats #Statistics #Medicine #StatisticsInMedicine https://www.nejm.org/doi/full/10.1056/NEJMra2212850