L. Leung , J.M. Kirkwood , S. Srinivasan , M. Dyer , A. Qian , M.-M. Pourrahmat , E. Kasireddy , J.R. May , A. Moshyk , M. Kurt
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Validity and predictive performance of WLR were assessed using leave-one-out cross-validation. Sensitivity analyses evaluated impact of RCTs violating proportional hazards assumption, publication year, treatments’ mechanism of action, and cancer stage.</div></div><div><h3>Results</h3><div>Across 30 RCTs, treatments included interferon-α (<em>n</em> = 17), other immunotherapy-containing regimens (<em>n</em> = 10), immune checkpoint inhibitors (<em>n</em> = 3), and targeted therapies (<em>n</em> = 2). BRMA (0.68, 95% CI 0.45-0.82) and WLR (0.71, 95% CI 0.42-0.87) estimated moderate correlation between HR<sub>RFS</sub> and HR<sub>OS</sub>. Surrogate threshold effect was 0.66/0.68 for studies with 800/1000 patients. Slope coefficients were statistically significant in both models (95% CI 0.09-0.61 BRMA; 95% CI 0.41-0.92 WLR). The 95% prediction intervals around the HR<sub>OS</sub> predicted by WLR accurately contained 29/31 (93.5%) of observed HR<sub>OS</sub>. Across sensitivity analyses correlations ranged between 0.69 and 0.84 (BRMA) and 0.55 and 0.77 (WLR).</div></div><div><h3>Conclusions</h3><div>Statistically meaningful correlation between HR<sub>RFS</sub> and HR<sub>OS</sub> can assist earlier predictions of OS benefit from improvements in RFS for RCTs in resected stage II/III melanoma and provide insights for the earlier evaluation of emerging therapies. 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Sensitivity analyses evaluated impact of RCTs violating proportional hazards assumption, publication year, treatments’ mechanism of action, and cancer stage.</div></div><div><h3>Results</h3><div>Across 30 RCTs, treatments included interferon-α (<em>n</em> = 17), other immunotherapy-containing regimens (<em>n</em> = 10), immune checkpoint inhibitors (<em>n</em> = 3), and targeted therapies (<em>n</em> = 2). BRMA (0.68, 95% CI 0.45-0.82) and WLR (0.71, 95% CI 0.42-0.87) estimated moderate correlation between HR<sub>RFS</sub> and HR<sub>OS</sub>. Surrogate threshold effect was 0.66/0.68 for studies with 800/1000 patients. Slope coefficients were statistically significant in both models (95% CI 0.09-0.61 BRMA; 95% CI 0.41-0.92 WLR). The 95% prediction intervals around the HR<sub>OS</sub> predicted by WLR accurately contained 29/31 (93.5%) of observed HR<sub>OS</sub>. 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引用次数: 0
摘要
在研究切除II/III期黑色素瘤的随机对照试验（rct）中，我们评估了治疗效果与无复发生存期（RFS）和总生存期（OS）之间的关系。方法通过文献查阅获得RFS和OS的风险比（hr）。双变量随机效应荟萃分析（BRMA）和加权线性回归（WLR）模型估计了HRRFS和HROS之间的相关性[95%置信区间（CI）]。估计了代理方程的斜率和截距。不同样本量的WLR导出了代理阈值效应。采用留一交叉验证评估WLR的效度和预测性能。敏感性分析评估了违反比例风险假设、发表年份、治疗作用机制和癌症分期的随机对照试验的影响。结果在30项随机对照试验中，治疗包括干扰素-α (n = 17)、其他含有免疫疗法的方案（n = 10）、免疫检查点抑制剂（n = 3）和靶向治疗（n = 2）。BRMA （0.68, 95% CI 0.45-0.82）和WLR （0.71, 95% CI 0.42-0.87）估计HRRFS和HROS之间存在中度相关性。在800/1000患者的研究中，替代阈值效应为0.66/0.68。两种模型的斜率系数均具有统计学意义(95% CI 0.09-0.61 BRMA；95% ci 0.41-0.92 wlr)。WLR预测的HROS周围95%预测区间准确包含29/31（93.5%）的观测HROS。在整个敏感性分析中，相关性在0.69 - 0.84 （BRMA）和0.55 - 0.77 （WLR）之间。结论HRRFS和HROS之间具有统计学意义的相关性，可以帮助在切除II/III期黑色素瘤的rct中早期预测OS受益于RFS的改善，并为早期评估新兴疗法提供见解。初步模型预测应谨慎处理，因为近一半的证据基础包括干扰素-α试验。
Challenges and opportunities of predicting overall survival benefit from improvements to recurrence-free survival in stage II/III melanoma: a correlation meta-analysis
Background
We evaluated the association between treatment effects on recurrence-free survival (RFS) and overall survival (OS) in randomized controlled trials (RCTs) studying resected stage II/III melanoma.
Methods
Hazard ratios (HRs) of RFS and OS were obtained from a literature review. Bivariate random-effects meta-analysis (BRMA) and weighted linear regression (WLR) models estimated correlations [95% confidence interval (CI)] between HRRFS and HROS. Slopes and intercepts of surrogacy equations were estimated. Surrogate threshold effect was derived from WLR for various sample sizes. Validity and predictive performance of WLR were assessed using leave-one-out cross-validation. Sensitivity analyses evaluated impact of RCTs violating proportional hazards assumption, publication year, treatments’ mechanism of action, and cancer stage.
Results
Across 30 RCTs, treatments included interferon-α (n = 17), other immunotherapy-containing regimens (n = 10), immune checkpoint inhibitors (n = 3), and targeted therapies (n = 2). BRMA (0.68, 95% CI 0.45-0.82) and WLR (0.71, 95% CI 0.42-0.87) estimated moderate correlation between HRRFS and HROS. Surrogate threshold effect was 0.66/0.68 for studies with 800/1000 patients. Slope coefficients were statistically significant in both models (95% CI 0.09-0.61 BRMA; 95% CI 0.41-0.92 WLR). The 95% prediction intervals around the HROS predicted by WLR accurately contained 29/31 (93.5%) of observed HROS. Across sensitivity analyses correlations ranged between 0.69 and 0.84 (BRMA) and 0.55 and 0.77 (WLR).
Conclusions
Statistically meaningful correlation between HRRFS and HROS can assist earlier predictions of OS benefit from improvements in RFS for RCTs in resected stage II/III melanoma and provide insights for the earlier evaluation of emerging therapies. Primary model predictions should be approached with caution as nearly half of the evidence base comprised interferon-α trials.
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