美国《临床肿瘤学杂志》：在社区开展乳腺癌21基因检测——理想很丰满，现实很骨感！

纳兰烙烙

Genomic Health公司是美国癌症分子诊断第二大厂，所研发的安可待（Oncotype DX）是乳癌肿瘤基因分子检测项目，检测乳癌肿瘤组织中的21个差异基因。Oncotype DX检测除了提供预后信息，还对治疗效果有预测能力，它实际上可预测患者对化疗的应答情况。

——《壹篇》按

美国《临床肿瘤学杂志》2018年1月8日在线先发

在社区医疗中基因表达谱检测的成本效益

目的

基因表达谱（GEP）检测可以为雌激素受体阳性、人表皮生长因子2阴性的早期乳腺癌患者的化疗决策提供支撑。安可待（Oncotype DX，美国加州雷德伍德城Genomic Health公司产品）是一种基因表达谱（GEP）检测产品，本研究评估了这项基因表达谱（GEP）检测在社区医疗中针对年龄在40至79岁之间、符合条件患的者成本效益。

方法

一个仿真模型对2005年至2012年社区使用Oncotype DX检测所带来的25年社会增量成本和质量调整生命年（QALYs）对比实施Oncotype DX检测前时段（2000-2004）常规治疗的25年社会增量成本和质量调整生命年（QALYs）进行了比较。输入的数据包括Oncotype DX数据和化疗数据，这些数据来自一个医疗综合保健系统数据、美国全国数据和已发表数据，数据涵盖Oncotype DX准确性、化疗效果、实用性、生存和复发情况、医疗保险和病人花费。对不同的个体患者参数进行了敏感性分析，还估算了理想条件下的结果（如100%检测、100%依从建议检测下进行治疗、准确无误的检测精度、考虑了检测对患者宽心或担忧的影响、成本最低）。

结果

有24%的符合检测条件的患者做了Oncotype DX检测。年轻患者和肿瘤Ⅰ期（对比IIA期）患者检测率较高，分别有75.3%的复发风险评分高的患者和10.2%的复发风险评分低的患者接受了化疗。检测的成本效益比（对比常规治疗）为每质量调整生命年（QALYs）188125美元。考虑检测对担忧对比宽心的影响，成本效益比下降到每质量调整生命年58431美元。检测精度准确无误，则成本效益比为28947美元/质量调整生命年，理想条件下，则为是39496美元/质量调整生命年。

结论

基于社区医疗模式下开展基因表达谱（GEP）检测，成本效益比可能会较高，但假定一些关键因素实际上会有变化，基因表达谱（GEP）检测的成本效益比就会在所受到的其它干预因素下有波动。当评价这种新技术时，在社区条件对比理想条件下的基础上，成本效益比的这种差异突显了实际实施的重要性。

来源：《桓兴医讯》孙晓莹

Cost Effectiveness of Gene Expression Profile Testing in Community Practice

https://doi.org/10.1200/JCO.2017.74.5034

Purpose

Gene expression profile (GEP) testing can support chemotherapy decision making for patients with early-stage, estrogen receptor–positive, human epidermal growth factor 2–negative breast cancers. This study evaluated the cost effectiveness of one GEP test, Oncotype DX (Genomic Health, Redwood City, CA), in community practice with test-eligible patients age 40 to 79 years.

Methods

A simulation model compared 25-year societal incremental costs and quality-adjusted life-years (QALYs) of community Oncotype DX use from 2005 to 2012 versus usual care in the pretesting era (2000 to 2004). Inputs included Oncotype DX and chemotherapy data from an integrated health care system and national and published data on Oncotype DX accuracy, chemotherapy effectiveness, utilities, survival and recurrence, and Medicare and patient costs. Sensitivity analyses varied individual parameters; results were also estimated for ideal conditions (ie, 100% testing and adherence to test-suggested treatment, perfect test accuracy, considering test effects on reassurance or worry, and lowest costs).

Results

Twenty-four percent of test-eligible patients had Oncotype DX testing. Testing was higher in younger patients and patients with stage I disease (v stage IIA), and 75.3% and 10.2% of patients with high and low recurrence risk scores received chemotherapy, respectively. The cost-effectiveness ratio for testing (v usual care) was $188,125 per QALY. Considering test effects on worry versus reassurance decreased the cost-effectiveness ratio to $58,431 per QALY. With perfect test accuracy, the cost-effectiveness ratio was $28,947 per QALY, and under ideal conditions, it was $39,496 per QALY.

Conclusion

GEP testing is likely to have a high cost-effectiveness ratio on the basis of community practice patterns. However, realistic variations in assumptions about key variables could result in GEP testing having cost-effectiveness ratios in the range of other accepted interventions. The differences in cost-effectiveness ratios on the basis of community versus ideal conditions underscore the importance of considering real-world implementation when assessing the new technology.