Challenges and Opportunities in Interdisciplinary Research and Real-World Data for Treatment Sequences in Health Technology Assessments.

With an ever-increasing number of treatment options, the assessment of treatment sequences has become crucial in health technology assessment (HTA). This review systematically explores the multifaceted challenges inherent in evaluating sequences, delving into their interplay and nuances that go beyond economic model structures. We synthesised a 'roadmap' of literature from key methodological studies, highlighting the evolution of recent advances and emerging research themes. These insights were compared against HTA guidelines to identify potential avenues for future research. Our findings reveal a spectrum of challenges in sequence evaluation, encompassing selecting appropriate decision-analytic modelling approaches and comparators, deriving appropriate clinical effectiveness evidence in the face of data scarcity, scrutinising effectiveness assumptions and statistical adjustments, considering treatment displacement, and optimising model computations. Integrating methodologies from diverse disciplines-statistics, epidemiology, causal inference, operational research and computer science-has demonstrated promise in addressing these challenges. An updated review of application studies is warranted to provide detailed insights into the extent and manner in which these methodologies have been implemented. Data scarcity on the effectiveness of treatment sequences emerged as a dominant concern, especially because treatment sequences are rarely compared in clinical trials. Real-world data (RWD) provide an alternative means for capturing evidence on effectiveness and future research should prioritise harnessing causal inference methods, particularly Target Trial Emulation, to evaluate treatment sequence effectiveness using RWD. This approach is also adaptable for analysing trials harbouring sequencing information and adjusting indirect comparisons when collating evidence from heterogeneous sources. Such investigative efforts could lend support to reviews of HTA recommendations and contribute to synthesising external control arms involving treatment sequences.

Beyond 10-year lead-times in EQ-5D-5L: leveraging alternative lead-times in willingness-to-accept questions to capture preferences for worse-than-dead states and their implication.

BACKGROUND: A fixed 10-year lead-time in composite time-trade-off (C-TTO) tasks might compromise the precision of utility values below - 1. This study explored how alternative lead-times (ALTs) influence EQ-5D-5L value sets and their implications in economic evaluations. METHODS: Leveraging data from Taiwan's EQ-5D-5L valuation and capitalizing on its exploratory willingness-to-accept question, we explored participants' quantification of "worse-than-dead (WTD)" health states with ALTs up to 50 years. We then derived alternative value sets incorporating these ALTs through interval regression and compared them against those from conventional models. To evaluate their impact on health change valuation, we simulated utility differences for all possible EQ-5D-5L health-state-pairs using each value set. RESULTS: With a salient floor effect observed in the C-TTO values, the model with ALT led to a wider range of predicted utilities ( - 2.3897 ~ 1), compared with those of conventional models (generalized least squares (GLS): - 0.7773 ~ 1; Tobit-GLS: - 0.9583 ~ 1). Compared to the Tobit-GLS model, the model with ALT increased the numerical distance in 80% of health-state-pairs, with 11% decreasing and 9% altering direction (e.g., positive to negative) in utility differences. CONCLUSIONS: While ALTs offer insights into patient preferences, their integration into economic evaluations might require rescaling. Future research should prioritize advanced rescaling methods or enhanced elicitation strategies for populations with substantial censoring. This is pivotal for improving the elicitation of extreme WTD states and accurately discerning the relative distances between health states. Countries developing EQ-5D-5L value sets should consider pilot studies and incorporating region-specific questions on social determinants, especially where pronounced floor effects are suspected.