Simões Corrêa Galendi Julia, Vennedey Vera, Kentenich Hannah, Stock Stephanie, Müller Dirk
Institute of Health Economics and Clinical Epidemiology, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Gleueler Str. 174-176, 50923 Cologne, Germany.
Cancers (Basel). 2021 Sep 29;13(19):4879. doi: 10.3390/cancers13194879.
Genetic screen-and-treat strategies for the risk-reduction of breast cancer (BC) and ovarian cancer (OC) are often evaluated by cost-utility analyses (CUAs). This analysis compares data on health preferences (i.e., utility values) in CUAs of targeted genetic testing for BC and OC. Based on utilities applied in fourteen CUAs, data on utility including related assumptions were extracted for the health states: (i) genetic test, (ii) risk-reducing surgeries, (iii) BC/OC and (iv) post cancer. In addition, information about the sources of utility and the impact on the cost-effectiveness was extracted. Utility for CUAs relied on heterogeneous data and assumptions for all health states. The utility values ranged from 0.68 to 0.97 for risk-reducing surgeries, 0.6 to 0.85 for BC and 0.5 to 0.82 for OC. In two out of nine studies, considering the impact of the test result strongly affected the cost-effectiveness ratio. While in general utilities seem not to affect the cost-utility ratio, in future modeling studies the impact of a positive/negative test on utility should be considered mandatory. Women's health preferences, which may have changed as a result of improved oncologic care and genetic counselling, should be re-evaluated.
降低乳腺癌(BC)和卵巢癌(OC)风险的基因筛查与治疗策略通常通过成本效用分析(CUA)进行评估。本分析比较了BC和OC靶向基因检测的CUA中健康偏好数据(即效用值)。基于十四项CUA中应用的效用,提取了以下健康状态的效用数据及相关假设:(i)基因检测,(ii)降低风险的手术,(iii)BC/OC,以及(iv)癌症后。此外,还提取了效用来源及对成本效益影响的信息。CUA的效用依赖于所有健康状态的异质性数据和假设。降低风险手术的效用值范围为0.68至0.97,BC为0.6至0.85,OC为0.5至0.82。在九项研究中的两项中,考虑检测结果的影响对成本效益比有很大影响。虽然总体上效用似乎不影响成本效用比,但在未来的建模研究中,应强制考虑阳性/阴性检测对效用的影响。由于肿瘤治疗和基因咨询的改善,女性的健康偏好可能已经发生变化,应重新评估。