Othus Megan, Bansal Aasthaa, Koepl Lisel, Wagner Samuel, Ramsey Scott
Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
Value Health. 2017 Apr;20(4):705-709. doi: 10.1016/j.jval.2016.04.011. Epub 2016 Jun 9.
Economic evaluations often measure an intervention effect with mean overall survival (OS). Emerging types of cancer treatments offer the possibility of being "cured" in that patients can become long-term survivors whose risk of death is the same as that of a disease-free person. Describing cured and noncured patients with one shared mean value may provide a biased assessment of a therapy with a cured proportion.
The purpose of this article is to explain how to incorporate the heterogeneity from cured patients into health economic evaluation.
We analyzed clinical trial data from patients with advanced melanoma treated with ipilimumab (Ipi; n = 137) versus glycoprotein 100 (gp100; n = 136) with statistical methodology for mixture cure models. Both cured and noncured patients were subject to background mortality not related to cancer.
When ignoring cured proportions, we found that patients treated with Ipi had an estimated mean OS that was 8 months longer than that of patients treated with gp100. Cure model analysis showed that the cured proportion drove this difference, with 21% cured on Ipi versus 6% cured on gp100. The mean OS among the noncured cohort patients was 10 and 9 months with Ipi and gp100, respectively. The mean OS among cured patients was 26 years on both arms. When ignoring cured proportions, we found that the incremental cost-effectiveness ratio (ICER) when comparing Ipi with gp100 was $324,000/quality-adjusted life-year (QALY) (95% confidence interval $254,000-$600,000). With a mixture cure model, the ICER when comparing Ipi with gp100 was $113,000/QALY (95% confidence interval $101,000-$154,000).
This analysis supports using cure modeling in health economic evaluation in advanced melanoma. When a proportion of patients may be long-term survivors, using cure models may reduce bias in OS estimates and provide more accurate estimates of health economic measures, including QALYs and ICERs.
经济评估通常用平均总生存期(OS)来衡量干预效果。新型癌症治疗方法提供了“治愈”的可能性,即患者可成为长期存活者,其死亡风险与无病者相同。用一个共同的均值来描述治愈和未治愈的患者,可能会对有治愈比例的治疗方法产生有偏差的评估。
本文旨在解释如何将治愈患者的异质性纳入卫生经济评估。
我们采用混合治愈模型的统计方法,分析了接受伊匹单抗(Ipi;n = 137)与糖蛋白100(gp100;n = 136)治疗的晚期黑色素瘤患者的临床试验数据。治愈和未治愈的患者均面临与癌症无关的背景死亡率。
在忽略治愈比例时,我们发现接受Ipi治疗的患者估计平均OS比接受gp100治疗的患者长8个月。治愈模型分析表明,治愈比例导致了这种差异,Ipi治疗组的治愈率为21%,而gp100治疗组为6%。未治愈队列患者中,Ipi和gp100治疗组的平均OS分别为10个月和9个月。两组治愈患者的平均OS均为26年。在忽略治愈比例时,我们发现比较Ipi与gp100时的增量成本效益比(ICER)为324,000美元/质量调整生命年(QALY)(95%置信区间254,000 - 600,000美元)。采用混合治愈模型时,比较Ipi与gp100的ICER为113,000美元/QALY(95%置信区间101,000 - 154,000美元)。
该分析支持在晚期黑色素瘤的卫生经济评估中使用治愈模型。当一部分患者可能成为长期存活者时,使用治愈模型可减少OS估计中的偏差,并能更准确地估计包括QALY和ICER在内的卫生经济指标。