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Abstract:
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In immune checkpoint inhibitor (ICI) trials, long tails and early crossover in survival curves—which violate the Cox proportional hazards (PH) assumption—are commonly observed, making cure or restricted mean survival time models preferable for analysis of ICI survival data. Cox PH analysis, however, still appears in major medical journals, leading to potential misinterpretation of clinical significance of findings. To convert inappropriate Cox hazard ratio (HR) to appropriate PH cure model treatment-effect estimates for more accurate interpretation of published ICI trials, we propose Cox-TEL (Cox PH – Taylor Expansion adjustment for Long-term survival data), a novel adjustment method. The proposed Cox-TEL method requires only two inputs, the reported Cox HRs and Kaplan-Meier-estimated survival probabilities. We present comprehensive simulation studies to show the strength of our new method in terms of power, bias, and type I error rate. Moreover, we illustrate the magnitude of potential difference between reported and adjusted HR using real-world ICI trial results. Our results suggest the need to revisit published ICI survival data analysis to address potential misinterpretation.
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