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Challenges with Estimating Long-Term Overall Survival in Extensive Stage Small-Cell Lung Cancer: A Validation-Based Case Study.

Sukhvinder JohalLance BrannmanVictor GenestierHélène Cawston
Published in: ClinicoEconomics and outcomes research : CEOR (2024)
While most models may provide a good fit to K-M data, it is crucial to assess beyond the statistical goodness-of-fit and consider the clinical plausibility of the long-term predictions. The more complex cure models demonstrated the best predictive ability at 3 years, potentially providing a better representation of the underlying method of action of immunotherapy; however, consideration of the models' clinical plausibility and cure assumptions need further research and validation. Our findings underscore the significance of adopting a clinical perspective when selecting the most appropriate approach to model long-term survival, particularly when considering the use of more complex models.
Keyphrases
  • small cell lung cancer
  • machine learning
  • big data
  • deep learning
  • artificial intelligence