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Updated: Apr 23, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Analyzing overall survival in randomized controlled trials with crossover and implications for economic evaluation

Linus Jönsson1, Rickard Sandin2, Mattias Ekman1

  • 1OptumInsight AB, Klarabergsviadukten, Stockholm, Sweden.

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
|September 20, 2014
PubMed
Summary

Correcting for treatment crossover in oncology trials is crucial for accurate survival and cost-effectiveness analysis. Choosing appropriate statistical methods, like inverse probability of censoring weighting or rank-preserving structural failure time models, minimizes bias and ensures optimal drug reimbursement decisions.

Keywords:
cost effectivenesscrossoveroncologysunitinibsurviva

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