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Updated: Aug 25, 2025

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Risk Model Development and Validation in Clinical Oncology: Lessons Learned
Gary H Lyman1, Pavlos Msaouel2, Nicole M Kuderer3
1Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Abstract:
Reliable risk models can greatly facilitate patient-centered inferences and decisions. Herein we summarize key considerations related to risk modeling in clinical oncology. Often overlooked challenges include data quality, missing data, effective sample size estimation, and selecting the variables to be included in the risk model. The stability and quality of the model should be carefully interrogated with particular emphasis on rigorous internal validation.
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