Meta-analysis of health state utility values measured by EuroQol 5-dimensions (EQ5D) questionnaire in Chinese women with breast cancer

Background To synthesise EQ5D health state utility values in Chinese women with breast cancer for parameterising a cost utility model. Methods Eligible studies had to report health state utility values measured by EQ-5D in Chinese women diagnosed with breast cancer. Risk of bias was assessed using the Newcastle Ottawa Scale (NOS). Data from single arm studies was pooled using meta-analysis of single proportions to provide overall point estimates and 95% confidence intervals for fixed and random effects models using the inverse variance and Der Simonian-Laird methods respectively. Heterogeneity was evaluated using the I2 statistic and sensitivity analysis and meta-regression were conducted. Results Five papers were included, when all studies were combined (n = 4,100) the mean utility (95% confidence interval) for random effects model was 0.83 (0.78, 0.89); for TNM 0-1 0.85 (0.75, 0.95); for TNM II 0.85 (0.78, 0.93); for TNM III 0.83 (0.77, 0.90) and for TNM IV 0.73 (0.63, 0.82).The utility of patients in State P (first year after primary breast cancer) 0.84 (0.80, 0.88); in State R (first year after recurrence) 0.73 (0.69, 0.76), in State S (second and following years after primary breast cancer or recurrence) 0.88 (0.83, 0.92); and in State M (metastatic disease) 0.78 (0.74, 0.82). Mean utility for duration since diagnosis 13 to 36 months was 0.88 (0.80, 0.96, I2 =95%); for 37 to 60 months 0.89 (0.82, 0.96, I2 =90%); for more than 60 months 0.86 (0.76, 0.96, I2 =90%). Mean utility for chemotherapy was 0.86 (0.79, 0.92, I2 =97%); for radiotherapy 0.83 (0.69, 0.96, I2 =97%); surgery 0.80 (0.69, 0.91, I2 =98%); concurrent chemo-radiation 0.70 (0.60, 0.81, I2 =86%) and endocrine therapy 0.90 (0.83, 0.97, I2 =91%). Conclusion: This study synthesises the evidence for health state utility values for Chinese women with breast cancer which is useful to inform cost utility models.

Exploring Structural Uncertainty and Impact of Health State Utility Values on Lifetime Outcomes in Diabetes Economic Simulation Models: Findings from the Ninth Mount Hood Diabetes Quality-of-Life Challenge

Background Structural uncertainty can affect model-based economic simulation estimates and study conclusions. Unfortunately, unlike parameter uncertainty, relatively little is known about its magnitude of impact on life-years (LYs) and quality-adjusted life-years (QALYs) in modeling of diabetes. We leveraged the Mount Hood Diabetes Challenge Network, a biennial conference attended by international diabetes modeling groups, to assess structural uncertainty in simulating QALYs in type 2 diabetes simulation models. Methods Eleven type 2 diabetes simulation modeling groups participated in the 9th Mount Hood Diabetes Challenge. Modeling groups simulated 5 diabetes-related intervention profiles using predefined baseline characteristics and a standard utility value set for diabetes-related complications. LYs and QALYs were reported. Simulations were repeated using lower and upper limits of the 95% confidence intervals of utility inputs. Changes in LYs and QALYs from tested interventions were compared across models. Additional analyses were conducted postchallenge to investigate drivers of cross-model differences. Results Substantial cross-model variability in incremental LYs and QALYs was observed, particularly for HbA1c and body mass index (BMI) intervention profiles. For a 0.5%-point permanent HbA1c reduction, LY gains ranged from 0.050 to 0.750. For a 1-unit permanent BMI reduction, incremental QALYs varied from a small decrease in QALYs (−0.024) to an increase of 0.203. Changes in utility values of health states had a much smaller impact (to the hundredth of a decimal place) on incremental QALYs. Microsimulation models were found to generate a mean of 3.41 more LYs than cohort simulation models ( P = 0.049). Conclusions Variations in utility values contribute to a lesser extent than uncertainty captured as structural uncertainty. These findings reinforce the importance of assessing structural uncertainty thoroughly because the choice of model (or models) can influence study results, which can serve as evidence for resource allocation decisions. Highlights The findings indicate substantial cross-model variability in QALY predictions for a standardized set of simulation scenarios and is considerably larger than within model variability to alternative health state utility values (e.g., lower and upper limits of the 95% confidence intervals of utility inputs). There is a need to understand and assess structural uncertainty, as the choice of model to inform resource allocation decisions can matter more than the choice of health state utility values.

Validation of the predictive accuracy of health-state utility values based on the Lloyd model for metastatic or recurrent breast cancer in Japan

IntroductionAlthough there is a lack of data on health-state utility values (HSUVs) for calculating quality-adjusted life-years in Japan, cost–utility analysis has been introduced by the Japanese government to inform decision making in the medical field since 2016.ObjectivesThis study aimed to determine whether the Lloyd model which was a predictive model of HSUVs for metastatic breast cancer (MBC) patients in the UK can accurately predict actual HSUVs for Japanese patients with MBC.DesignThe prospective observational study followed by the validation study of the clinical predictive model.Setting and participantsForty-four Japanese patients with MBC were studied at 336 survey points.MethodsThis study consisted of two phases. In the first phase, we constructed a database of clinical data prospectively and HSUVs for Japanese patients with MBC to evaluate the predictive accuracy of HSUVs calculated using the Lloyd model. In the second phase, Bland-Altman analysis was used to determine how accurately predicted HSUVs (based on the Lloyd model) correlated with actual HSUVs obtained using the EuroQol 5-Dimension 5-Level questionnaire, a preference-based measure of HSUVs in patients with MBC.ResultsIn the Bland-Altman analysis, the mean difference between HSUVs estimated by the Lloyd model and actual HSUVs, or systematic error, was −0.106. The precision was 0.165. The 95% limits of agreement ranged from −0.436 to 0.225. The t value was 4.6972, which was greater than the t value with 2 degrees of freedom at the 5% significance level (p=0.425).ConclusionsThere were acceptable degrees of fixed and proportional errors associated with the prediction of HSUVs based on the Lloyd model for Japanese patients with MBC. We recommend that sensitivity analysis be performed when conducting cost-effectiveness analyses with HSUVs calculated using the Lloyd model.

Changes in Health State Utility Values in Japanese Patients with End-Stage Breast Cancer

We aimed to determine the dynamic trends in health state utility values (HSUVs) in patients with end-stage breast cancer. We selected 181 patients comprising 137 with primary breast cancer (PBC) and 44 with metastatic breast cancer (MBC) (28 survivors and 16 patients with MBC death). HSUVs were 0.90 and 0.89 in patients with PBC and 0.83 and 0.80 in those with MBC (survivors) at 6 and 3 months, respectively, before the end of the observation period; these values were 0.73 and 0.66, respectively, in those with MBC (deceased) during the aforementioned period. The root-mean-squared error (RMSE) for the decrease in HSUVs over 3 months was 0.10, 0.096, and 0.175 for patients with PBC, MBC (survivors), and MBC (deceased), respectively. One-way analysis of variance for differences in absolute error among the groups was significant (p = 0.0102). Multiple comparisons indicated a difference of 0.068 in absolute error between patients with PBC and those with MBC (deceased) (p = 0.0082). Patients with end-stage breast cancer had well-controlled HSUVs 3 months before death, with a sharp decline in HSUVs in the 3 months leading up to death.