Impact of Tumor Assessment Frequency on Statistical Power in Randomized Cancer Clinical Trials Evaluating Progression-Free Survival

Therapeutic Innovation & Regulatory Science(2021)

引用 1|浏览7
暂无评分
摘要
Background Progression-free survival (PFS) is frequently used as a primary endpoint in late-phase clinical trials for anti-metastatic cancer agents. Previous studies have indicated that the frequency of tumor assessment affects the statistical power for PFS because progression dates are inaccurate; however, this finding may be difficult to generalize because of its unrealistic assumptions. Therefore, we re-examined this issue under realistic assumptions and various scenarios that approximate actual clinical trials. Methods Randomized clinical trials comparing two interventions against a solid tumor were simulated under conditions where progressive disease (PD)-dominant PFS or a non-negligible number of deaths (death-competitive PFS) contributed to PFS events, which are conditions that resemble clinical trials of first-line therapy and later-line therapy, respectively. We assessed the impact of tumor assessment frequency on the statistical power. Results Under the PD-dominant PFS condition, even in extreme scenarios, statistical power loss was only approximately 3%. Under the death-competitive PFS condition, tumor assessment frequency affected the statistical power of PFS if the effect of the treatment on overall survival was lower than that on time to progression. In this case, loss of statistical power was often more than 10% in some realistic scenarios. Conclusion In trials investigating first-line treatments (PD-dominant PFS), tumor assessment frequency has a negligible impact on statistical power, whereas in trials investigating late-line therapies (death-competitive PFS), the potential impact of tumor assessment frequency on statistical power should be carefully evaluated at the design stage.
更多
查看译文
关键词
Log-rank test, Progression-free survival, Randomized clinical trial, Survival analysis, Statistical power
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要