2-040 Li Ka Shing Centre for Health Research Innovation, School of Public Health, University of Alberta, Edmonton, AB, T6G 2E1, Canada.
Alberta PROMs and EQ-5D Research and Support Unit (APERSU), University of Alberta, Edmonton, AB, Canada.
Eur J Health Econ. 2021 Dec;22(9):1441-1451. doi: 10.1007/s10198-021-01324-x. Epub 2021 Jun 5.
We propose a modified quality-adjusted life year (QALY) calculation that aims to be consistent with guidance for interpreting change in patient-reported outcomes. This calculation incorporates the minimally important difference (MID) in generic preference-based health-related quality of life (HRQL) change scores to reflect what might be considered meaningful HRQL improvement/deterioration. In doing so, we review common issues in QALY calculations such as adjustment for baseline scores and standardizing for between-group differences.
Using EQ-5D-5L outcome data from the Alberta TEAMCare-Primary Care Network trial in the management of depression for patients with type 2 diabetes (n = 98), this study compared results from different QALY calculation methods to investigate the impact of (i) adjusting for baseline HRQL score, (ii) standardizing between-group differences at baseline, and (iii) adjusting for 'meaningful' HRQL changes. The following QALY calculation methods are examined: area under curve (QALY-AUC), change from baseline (QALY-CFB), regression modelling (QALY-R), and incorporating an MID for HRQL changes from baseline (QALY-MID).
The incremental QALY-AUC estimate favoured the Collaborative Care group (0.031) while the incremental QALY-CFB (-0.028) estimate favoured Enhanced Care. Adjusting for meaningful HRQL changes resulted in a crude incremental QALY-MID of -0.023; however, after adjusting for between-group differences at baseline, QALY-R and adjusted incremental QALY-MID estimates were -0.007 and -0.001, respectively. In addition, recursive regression analyses showed that very low baseline HRQL scores impact incremental QALY estimates.
Uncertainty in incremental QALY estimates reflects uncertainty in the value of small within-individual change as well as the impact of small differences between groups at baseline. Applying a responder-definition approach yielded crude and adjusted QALY-MID estimates that were more in favour of Collaborative Care than QALY-CFB and QALY-R estimates, respectively, suggesting that ambiguous small changes in HRQL scores have the potential to influence QALY outcomes used in economic or non-economic applications.
我们提出了一种改良的质量调整生命年(QALY)计算方法,旨在与解释患者报告结局变化的指南保持一致。这种计算方法纳入了通用偏好健康相关生活质量(HRQL)变化评分的最小重要差异(MID),以反映可能被认为是有意义的 HRQL 改善/恶化。为此,我们回顾了 QALY 计算中的常见问题,例如对基线评分的调整和对组间差异的标准化。
使用阿尔伯塔省 TEAMCare-初级保健网络试验中治疗 2 型糖尿病患者抑郁症的 EQ-5D-5L 结局数据(n=98),本研究比较了不同 QALY 计算方法的结果,以调查以下因素的影响:(i)调整基线 HRQL 评分,(ii)标准化基线时的组间差异,以及(iii)调整基线时的“有意义”HRQL 变化。研究考察了以下 QALY 计算方法:曲线下面积(QALY-AUC)、从基线变化(QALY-CFB)、回归建模(QALY-R)和纳入基线 HRQL 变化的 MID(QALY-MID)。
增量 QALY-AUC 估计值有利于协作护理组(0.031),而增量 QALY-CFB(-0.028)估计值有利于强化护理。调整有意义的 HRQL 变化导致原始增量 QALY-MID 为-0.023;然而,在调整基线时的组间差异后,QALY-R 和调整后的增量 QALY-MID 估计值分别为-0.007 和-0.001。此外,递归回归分析表明,基线 HRQL 得分非常低会影响增量 QALY 估计值。
增量 QALY 估计值的不确定性反映了个体内小变化的价值不确定性以及基线时组间差异的影响。应用应答者定义方法得出了原始和调整后的 QALY-MID 估计值,分别更有利于协作护理,而不是 QALY-CFB 和 QALY-R 估计值,这表明 HRQL 得分的模糊小变化有可能影响经济或非经济应用中的 QALY 结果。