Safonov Anton, Wang Shiyi, Gross Cary P, Agarwal Divyansh, Bianchini Giampaolo, Pusztai Lajos, Hatzis Christos
Yale School of Medicine, New Haven, USA.
Yale School of Public Health, New Haven, USA.
Breast Cancer Res Treat. 2016 Jan;155(2):223-34. doi: 10.1007/s10549-016-3677-3. Epub 2016 Jan 9.
Evaluation of cost-utility is critical in assessing the medical utility of predictive or prognostic biomarkers. Current methods involve complex state-transition models, requiring comprehensive data inputs. We propose a simplified decision-analytic tool to explore the relative effect of factors contributing to the cost-utility of a biomarker. We derived a cost-utility metric, the "test incremental cost-effectiveness ratio" (TICER) for biomarker-guided treatment compared to no biomarker use. This method uses data inputs readily accessible through clinical literature. We compared our results with traditional cost-effectiveness analysis of predictive biomarkers for established (HER2-guided trastuzumab, ALK-guided crizotinib, OncotypeDX-guided adjuvant chemotherapy) and emerging (ROS1-guided crizotinib) targeted treatments. We conducted sensitivity analysis to determine which factors had the greatest impact on TICER estimates. Base case TICER for HER2 was $149,600/quality-adjusted life year (QALY), for ALK was $22,200/QALY, and for OncotypeDX was $11,600/QALY, consistent with literature-reported estimates ($180,000/QALY, $202,800/QALY, $8900/QALY, respectively). Base case TICER for ROS1-guided crizotinib was $205,900/QALY. Generally, when treatment cost is considerably greater than biomarker testing costs, TICER is driven by clinical outcomes and health-related quality of life, while biomarker prevalence and treatment cost have a lesser effect. Our simplified decision-analytic approach produces values consistent with existing cost-effectiveness analyses. Our results suggest that biomarker value is mostly driven by the clinical efficacy of the targeted agent. A user-friendly web tool for complete TICER analysis has been made available for open use at http://medicine.yale.edu/lab/pusztai/ticer/ .
成本效用评估对于预测或预后生物标志物的医学效用评估至关重要。当前方法涉及复杂的状态转换模型，需要全面的数据输入。我们提出了一种简化的决策分析工具，以探讨影响生物标志物成本效用的因素的相对作用。我们推导了一种成本效用指标，即与不使用生物标志物相比，生物标志物指导治疗的“检测增量成本效益比”（TICER）。该方法使用通过临床文献易于获取的数据输入。我们将我们的结果与已确立的（HER2指导的曲妥珠单抗、ALK指导的克唑替尼、OncotypeDX指导的辅助化疗）和新兴的（ROS1指导的克唑替尼）靶向治疗的预测生物标志物的传统成本效益分析进行了比较。我们进行了敏感性分析，以确定哪些因素对TICER估计值影响最大。HER2的基础病例TICER为149,600美元/质量调整生命年（QALY），ALK为22,200美元/QALY，OncotypeDX为11,600美元/QALY，与文献报道的估计值（分别为180,000美元/QALY、202,800美元/QALY、8900美元/QALY）一致。ROS1指导的克唑替尼的基础病例TICER为205,900美元/QALY。一般来说，当治疗成本远高于生物标志物检测成本时，TICER由临床结果和健康相关生活质量驱动，而生物标志物患病率和治疗成本的影响较小。我们简化的决策分析方法得出的值与现有的成本效益分析一致。我们的结果表明，生物标志物的价值主要由靶向药物的临床疗效驱动。一个用于完整TICER分析的用户友好型网络工具已在http://medicine.yale.edu/lab/pusztai/ticer/ 上开放供公众使用。
