Quality of life assumptions determine which cervical cancer screening strategies are cost-effective.

Abstract

Quality-adjusted life years are used in cost-effectiveness analyses (CEAs). To calculate QALYs, a "utility" (0-1) is used for each health state induced or prevented by the intervention. We aimed to estimate the impact of quality of life (QoL) assumptions (utilities and durations of health states) on CEAs of cervical cancer screening. To do so, 12 alternative sets of utility assumptions were retrieved from published cervical cancer screening CEAs. Two additional sets were based on empirical QoL data that were integrally obtained through two different measures (SF-6D and EQ-5D) from eight groups of women (total n = 3,087), from invitation for screening to diagnosis with cervical cancer. Per utility set we calculated the number of quality-adjusted days lost (QADL) for each relevant health state in cervical cancer screening, by multiplying the study-specific assumed disutilities (i.e., 1-utility) with study-specific durations of the loss in QoL, resulting in 14 "QADL-sets." With microsimulation model MISCAN we calculated cost-effectiveness of 342 alternative screening programs (varying in primary screening test [Human Papillomavirus (HPV) vs. cytology], starting ages, and screening interval) for each of the 14 QADL-sets. Utilities used in CEAs appeared to differ largely. We found that ten QADL-sets from the literature resulted in HPV and two in cytology as preferred primary test. The SF-6D empirical QADL-set resulted in cytology and the EQ-5D one in HPV as preferred primary test. In conclusion, assumed utilities and health state durations determine cost-effectiveness of cervical cancer screening. Also, the measure used to empirically assess utilities can be crucial for CEA conclusions.