Analyses of quality of life in cancer drug trials - a review of measurements and analytical choices in post-reimbursement studies.

OBJECTIVES: For drugs reimbursed with limited evidence of patient benefits, confirmatory evidence of overall survival (OS) and quality of life (QoL) benefits is important. For QoL data to serve as valuable input to patients and decision-makers, it must be measured and analyzed using appropriate methods. We aimed to assess the measurement and analyses of post-reimbursement QoL data for cancer drugs introduced in Swedish healthcare with limited evidence at the time of reimbursement. METHODS: We reviewed any published post-reimbursement trial data on QoL for cancer drugs reimbursed in Sweden between 2010 and 2020 with limited evidence of improvement in QoL and OS benefits at the time of reimbursement. We extracted information on the instruments used, frequency of measurement, extent of missing data, statistical approaches, and the use of pre-registration and study protocols. RESULTS: Out of 22 drugs satisfying our inclusion criteria, we identified published QoL data for 12 drugs in 22 studies covering multiple cancer types. The most frequently used QoL instruments were EORTC QLQ-C30 and EQ-5D-3/5L. We identified three areas needing improvement in QoL measurement and analysis: (i) motivation for the frequency of measurements, (ii) handling of the substantial missing data problem, and (iii) inclusion and adherence to QoL analyses in clinical trial pre-registration and study protocols. CONCLUSIONS: Our review shows that the measurements and analysis of QoL data in our sample of cancer trials covering drugs initially reimbursed without any confirmed QoL or OS evidence have significant room for improvement. The increasing use of QoL assessments must be accompanied by a stricter adherence to best-practice guidelines to provide valuable input to patients and decision-makers.

Place or patient as the driver of regional variation in healthcare spending - Discrepancies by category of care.

We study how much regional variation in healthcare spending is driven by place- and patient-specific factors using a random sample of 53,620 regional migrants in Sweden. We find notable differences depending on the category of care, with place-specific factors having a significantly larger impact on specialized outpatient care compared to inpatient and pharmaceutical care. The place effect is estimated to 75% of variation in specialized outpatient care, but 26% or less in variations in inpatient care, and 5% in prescription drug spending. We also find that the empirical estimator has a substantial impact on the estimates of the place-specific effect. The results based on the traditional approach in the literature with two-way fixed effects and event-study models produce much larger estimates of the place-specific effect compared to results based on recently developed heterogeneity-robust models. For total healthcare spending, the traditional two-way fixed effects model estimates a place effect of 78%, while the heterogeneity-robust estimator finds a place effect around 10%. This finding indicates that previous results in this literature, all based on traditional two-way fixed-effects regressions, should be interpreted with care.