Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
Academic Breast Cancer Center, Department of Oncologic and Gastro-intestinal Surgery, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Int J Cancer. 2024 Jul 1;155(1):117-127. doi: 10.1002/ijc.34899. Epub 2024 Mar 13.
In breast cancer research, utility assumptions are outdated and inconsistent which may affect the results of quality adjusted life year (QALY) calculations and thereby cost-effectiveness analyses (CEAs). Four hundred sixty four female patients with breast cancer treated at Erasmus MC, the Netherlands, completed EQ-5D-5L questionnaires from diagnosis throughout their treatment. Average utilities were calculated stratified by age and treatment. These utilities were applied in CEAs analysing 920 breast cancer screening policies differing in eligible ages and screening interval simulated by the MISCAN-Breast microsimulation model, using a willingness-to-pay threshold of €20,000. The CEAs included varying sets on normative, breast cancer treatment and screening and follow-up utilities. Efficiency frontiers were compared to assess the impact of the utility sets. The calculated average patient utilities were reduced at breast cancer diagnosis and 6 months after surgery and increased toward normative utilities 12 months after surgery. When using normative utility values of 1 in CEAs, QALYs were overestimated compared to using average gender and age-specific values. Only small differences in QALYs gained were seen when varying treatment utilities in CEAs. The CEAs varying screening and follow-up utilities showed only small changes in QALYs gained and the efficiency frontier. Throughout all variations in utility sets, the optimal strategy remained robust; biennial for ages 40-76 years and occasionally biennial 40-74 years. In sum, we recommend to use gender and age stratified normative utilities in CEAs, and patient-based breast cancer utilities stratified by age and treatment or disease stage. Furthermore, despite varying utilities, the optimal screening scenario seems very robust.
在乳腺癌研究中，效用假设已经过时且不一致，这可能会影响质量调整生命年 (QALY) 的计算结果，并进而影响成本效益分析 (CEA)。464 名在荷兰伊拉斯姆斯医学中心接受治疗的女性乳腺癌患者在确诊后至治疗期间完成了 EQ-5D-5L 问卷。按年龄和治疗分层计算平均效用。这些效用应用于通过 MISCAN-Breast 微观模拟模型模拟的不同年龄和筛查间隔的 920 项乳腺癌筛查政策的 CEA 分析中，使用的意愿支付阈值为 20,000 欧元。CEA 中包含了不同的标准、乳腺癌治疗和筛查以及随访效用集。比较效率前沿以评估效用集的影响。在乳腺癌诊断时和手术后 6 个月计算出的平均患者效用降低，并且在手术后 12 个月朝着标准效用增加。在 CEA 中使用 1 的标准效用值时，与使用平均性别和年龄特定值相比，QALYs 被高估。在 CEA 中改变治疗效用时，仅看到 QALYs 获得的微小差异。在不同的筛查和随访效用的 CEA 中，仅看到 QALYs 获得和效率前沿的微小变化。在所有效用集的变化中，最佳策略仍然保持稳健；40-76 岁的女性每两年筛查一次，偶尔每两年筛查一次 40-74 岁的女性。总之，我们建议在 CEA 中使用性别和年龄分层的标准效用，并根据年龄和治疗或疾病阶段分层患者的乳腺癌效用。此外，尽管效用不同，但最佳的筛查方案似乎非常稳健。
