Maximizing value: The critical role of health-related quality of life data collection in pivotal trials

Health-related quality of life (HRQoL) refers to the impact a medical condition and/or therapy has on a patient’s daily life, physical, psychological and social functioning and well-being. HRQoL can be measured using patient-reported outcome (PRO) measures, which are often self-administered questionnaires with pre-specified response formats. Some generic HRQoL instruments are designed to be applicable across a wide range of populations and interventions, whereas others are disease-specific tools. 

HRQoL is increasingly being measured in clinical trials alongside other outcome measures to evaluate the full range of effects of an intervention from the patients’ perspective. However, some pharmaceutical and biotech companies still question the necessity of collecting such data, citing perceived limited added value, the risk of not meeting all pre-specified endpoints, and the potential administrative burden on patients. Here, we discuss how drug manufacturers could and likely should collect HRQoL data in their pivotal trials for two potential objectives.

1.    Clinical benefit assessment

Drug manufacturers could consider collecting HRQoL data when their aim is to demonstrate that their investigational drug can improve or slow down the deterioration of patients' HRQoL in a statistically significant and clinically meaningful way. Such information can be used in clinical (risk-)benefit assessments and may be valuable to multiple stakeholders:¹ 

• Regulators: HRQoL data may influence licensing decisions and support labelling claims
• HTA agencies: Health Technology Assessment (HTA) agencies may use this data to inform reimbursement decisions, especially in countries where the focus primarily lies on clinical and patient-relevant benefits
• Policy decision-makers: HRQoL data may be considered when evaluating comparative effectiveness
• Patients and treating physicians: This data can inform discussions around treatment options and prescribing decisions

The importance of HRQoL to HTA decision-making is very clear in Germany, for example. The outcome of benefit assessments carried out by the local HTA agency (Gemeinsamer Bundesausschuss; G-BA) has a major impact on subsequent price and reimbursement negotiations between the manufacturer and the statutory health insurance. According to the Act on the Reform of the Market for Medicinal Products (AMNOG) introduced in 2011, the added benefit of an intervention versus a relevant comparator can only be claimed based on patient-relevant endpoints which include mortality, morbidity, safety and HRQoL. As the G-BA prefers to judge the overall effect of new treatments on all dimensions, not capturing HRQoL in a pivotal trial is regularly criticized and can have a negative impact on the outcome of the benefit assessment, particularly in those instances where the primary endpoint does not clearly demonstrate added benefit versus all relevant comparators, or if there is a high degree of uncertainty in the added benefit.² HRQoL data are particularly relevant in oncology, where morbidity endpoints like progression-free survival are frequently not considered to be patient-relevant by the G-BA. The demonstration of a substantial improvement in HRQoL versus the appropriate comparative therapy, with morbidity and mortality being equal, can be sufficient to obtain a major added benefit rating.³  

In most other countries, HTA bodies generally consider HRQoL data as supportive evidence during evaluation of the overall clinical benefit profile.⁴  Yet there is growing recognition that the patient voice needs to be heard in HTA processes, as evidenced by the inclusion of PROs in guidance for the EU’s Joint Clinical Assessments (JCA).⁵  The impact and importance of PROs in the JCA evaluation process is yet to be determined, with the initial evaluation reports due for publication in early 2026. Currently, the impact and adoption of these reports by HTA bodies in the member states, and the weighting of PROs in local decision-making is unknown. 

The recommended approach for manufacturers includes using a relevant and validated disease-specific instrument to collect HRQoL data for use in benefit assessments, as such an instrument should be sensitive enough to pick up differences in the assessment of the most important facets of the specific condition. Although it would theoretically be possible to include such an HRQoL measure as (co-)primary endpoint, it would typically be included as a pre-specified secondary endpoint in pivotal trials.

2.    Economic assessment

Drug manufacturers should consider collecting HRQoL data with the aim of deriving utility values to be used in (quality-adjusted life year calculations in) health economic evaluations. Certain PROs measure the patient’s health status and allow the derivation of utility values that represent the strength of individuals’ preferences for different health states. Health state utility value estimates are typically among the most important and uncertain data inputs in cost-utility models that inform pricing and reimbursement decisions in many different countries (including major markets such as the UK, Nordics, Canada, Australia). 

Clinical trials and open-label extension studies represent an important opportunity and an efficient manner for the prospective collection of such data. The incremental cost of adding a utility measure to a regulatory trial is expected to be substantially less than the cost of performing a separate utility study.⁶ HTA agencies generally prefer utility values from relevant clinical studies. They consider other sources if the clinical trial population does not represent patients in their country.⁷ 

The EQ-5D, HUI, and SF-6D are three multi-attribute utility instruments that are most commonly recommended by HTA agencies. These generic, non-disease-specific instruments are not very sensitive and may not necessarily capture all important HRQoL facets of all medical conditions. Such measures can, however, be included as secondary, exploratory or (health) economic endpoints in clinical trials. There is also no formal requirement from HTA agencies for these measures to demonstrate statistically significant differences between HRQoL outcomes across trial arms, although it could be beneficial. HRQoL data is actually often pooled across trial arms to improve the precision of utility estimates representing specific health states (e.g., at baseline, upon disease progression, after experiencing a specific clinical event). An economic analysis combining these (potentially pooled) health state utility values with clear clinical benefits demonstrated on efficacy endpoints may be sufficient to provide payers with compelling evidence of a health economic benefit.

EQ-5D in focus

Health economists would generally recommend drug manufacturers to collect EQ-5D data in their clinical trials. The EQ-5D is mentioned in 85% of global pharmaco-economic guidelines as either the preferred instrument or as an example of a suitable instrument for the determination of health utilities.⁸  HTA agencies’ preference for EQ-5D is due to its widespread use in studies across a variety of therapeutic areas, enabling consistency and comparability, and the availability of national value sets. There are two versions of the EQ-5D for measuring and valuing health in adults. Whereas the 3-level version of the instrument (EQ-5D-3L) has been used to derive utility values for many years, the 5-level variant (EQ-5D-5L) is increasingly included in clinical studies because it reduces ceiling effects and has greater discriminatory power.⁹  Some manufacturers may nevertheless still prefer to use EQ-5D-3L for practical (e.g., availability of value sets in certain markets) or tactical reasons (eg, anticipated impact on economic outcomes)¹⁰.

Alternative and/or complementary methods for the collection of HRQoL data and utility values for subsequent use in economic analyses include:

• Conducting a comprehensive review of existing estimates available in the published literature. Some HTA agencies even require a systematic review as part of the evidence submission. In the absence of a trial-based estimate to compare to, however, it can always be questioned how representative a utility value collected from literature would be for your specific target population.
• When generic preference-based measures are not available, such data can be estimated by mapping other HRQoL measures or health-related benefits seen in the relevant clinical trials to EQ-5D/utility values. NICE guidelines, however, clarify that mapping should be considered a second-best solution at best and considers it to be a departure from the reference case.²
• In vignette studies, a representative sample of the general population is being asked to rate / value health states based on detailed descriptions (‘vignettes’) provided by patients and/or physicians. This approach has clear limitations and should only be considered where data from validated HRQoL measures is not available or cannot be collected.

These alternative methods are not universally recommended / accepted by all HTA agencies. Utility values derived using these approaches would generally be associated with higher uncertainty (e.g. wider confidence intervals). When they are used in cost-utility analysis, in view of this uncertainty, HTA agencies may consequently not accept incremental cost-effectiveness ratios (ICERs) that lie close to their upper willingness-to-pay threshold. 

To increase the probability that the intervention would be considered cost-effective (based on evaluation of sensitivity analyses and cost-effectiveness acceptability curves), manufacturers might be required to lower their drug price to avoid the risk of rejection or focus on a subpopulation where there is a lower perceived uncertainty or greater benefit.

Conclusion

Manufacturers that do not collect HRQoL data in their pivotal trials may subsequently experience a less-than-ideal reimbursement journey. Costly additional studies may be required, drug prices may need to be lowered, drug appraisals and reimbursement decisions may take longer, could be postponed, or might lead to a rejection. 

We acknowledge that it is not always straightforward or possible to collect robust HRQoL / utility estimates in specific populations (e.g., young children) or indications (e.g. rare diseases, dementia etc.). In most circumstances, we recommend that drug manufacturers collect EQ-5D data in their registrational clinical studies to inform health economic analysis and consider collecting additional HRQoL data using a validated disease-specific instrument should they aim to demonstrate that their investigational drug can provide a HRQoL benefit to patients. 

Our Access Consulting team regularly reviews research protocols and helps pharmaceutical and biotech organizations to design clinical trials with payers and HTA agencies in mind. Get in touch to learn more.
 

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Disclaimer:
Parexel provides the information contained in this document for educational purposes only. The information does not constitute legal or regulatory advice. Readers should not act upon this information without seeking advice from professional advisers. 
 

References

1. Mercieca-Bebber et al. The importance of patient-reported outcomes in clinical trials and strategies for future optimization. Patient Relat Outcome Meas. 2018 Nov 1:9:353-367.
2. Böhme et al. Patient-reported outcomes in the context of the benefit assessment in Germany. arXiv:2107.03249v2
3. Schneider. Relevance of Instruments for Measurements of Quality of Life in the AMNOG Context: An Analysis of the Endpoint Health-Related Quality of Life from Different Perspectives. In: Advances in Pharma Business Management and Research. Schweizer et al., Eds. 2020, Springer Nature Switzerland AG.
4. Wolters et al. Differences in evidentiary requirements for oncology drug effectiveness assessments among six European health technology assessment bodies - can alignment be improved? Expert Rev Pharmacoecon Outcomes Res. 2024;24(2):251-65.
5. EU Directorate-General for Health and Food Safety. Guidance on outcomes for joint clinical assessments. 13 June 2024.
6. Wolowacz et al. Estimating Health-State Utility for Economic Models in Clinical Studies: An ISPOR Good Research Practices Task Force Report. Value Health. 2016;19(6):704-19.
7. ICE health technology evaluations: the manual (PMG36). Published: 31 January 2022
8. Kennedy‑Martin et al. Which multi‑attribute utility instruments are recommended for use in cost‑utility analysis? A review of national health technology assessment (HTA) guidelines. Eur J Health Econ. 2020;21(8):1245-57.
9. Janssen et al. Is EQ-5D-5L better than EQ-5D-3L? A head-to-head comparison of descriptive systems and value sets from seven countries. Pharmacoeconomics. 2018;36(6):675–97.
10. Pennington et al. The impact of moving from EQ-5D-3L to 25L in NICE technology appraisals. Pharmacoeconomics. 2019;37(1):75–84.
     

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