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. 2024 Feb 28:16:97-109.
doi: 10.2147/CEOR.S448975. eCollection 2024.

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

Sukhvinder Johal  1 , Lance Brannman  2 , Victor Genestier  3 , Hélène Cawston  4
Affiliations

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

Sukhvinder Johal et al. Clinicoecon Outcomes Res. .

Abstract

Objective: The study aimed to explore methods and highlight the challenges of extrapolating the overall survival (OS) of immunotherapy-based treatment in first-line extensive stage small-cell lung cancer (ES-SCLC).

Methods: Standard parametric survival models, spline models, landmark models, mixture and non-mixture cure models, and Markov models were fitted to 2-year data of the CASPIAN Phase 3 randomised trial of PD-L1 inhibitor durvalumab added to platinum-based chemotherapy (NCT03043872). Extrapolations were compared with updated 3-year data from the same trial and the plausibility of long-term estimates assessed.

Results: All models used provided a reasonable fit to the observed Kaplan-Meier (K-M) survival data. The model which provided the best fit to the updated CASPIAN data was the mixture cure model. In contrast, the landmark analysis provided the least accurate fit to model survival. Estimated mean OS differed substantially across models and ranged from (in years) 1.41 (landmark model) to 4.81 (mixture cure model) for durvalumab plus etoposide and platinum and from 1.01 (landmark model) to 2.00 (mixture cure model) for etoposide and platinum.

Conclusion: 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.

Keywords: cure models; extensive stage small-cell lung cancer; landmark model; parametric extrapolation; spline model; survival analysis.

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Conflict of interest statement

Victor Genestier and Hélène Cawston are employees of Amaris. Sukhvinder Johal is an employee of AstraZeneca and reports stock ownership in AstraZeneca. Lance Brannman is a former employee of AstraZeneca and reports stock ownership in AstraZeneca. He is now affiliated with the University of Utah, College of Pharmacy, Pharmacotherapy Outcomes Research Center, Salt Lake City, UT, USA. The authors report no other conflicts of interest in this work.

Figures

Figure 1
Figure 1
Hazard plots for proposed approaches. (A) Durvalumab plus etoposide and platinum; (B) etoposide and platinum.
Figure 2
Figure 2
Best distribution for each approach. (A) Durvalumab plus etoposide and platinum overall survival and (B) etoposide and platinum overall survival.
See this image and copyright information in PMC

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