While patient input to health technology assessment (HTA) has traditionally been of a qualitative nature, there is increasing interest to integrate quantitative evidence from patient preference studies into HTA decision making. Preference data can be used to generate disease-specific health utility data. We generated a health utility score for patients with chronic obstructive pulmonary disease (COPD) and consider its use within HTAs.

Based on qualitative research, six symptoms were identified as important to COPD patients: shortness of breath, exacerbations, chronic cough, mucus secretion, sleep disturbance, and urinary incontinence. We employed a discrete choice experiment (DCE) and the random parameter logistic regression technique to estimate utility scores for all COPD health states. The relationship between patients’ COPD health utility scores, self-perceived COPD severity, and EQ-5D-3L utility scores was analyzed, with data stratified according to disease severity and comorbidity subgroups.

The COPD health utility score had face validity, with utility scores negatively correlated with patients’ self-perceived COPD severity. The correlation between the COPD health utility scores and EQ-5D-3L values was only moderate. While patient EQ-5D-3L scores were impacted by comorbidities, the COPD health utility score was less impacted by comorbid conditions.

Our COPD utility measure, derived from a DCE, provides a patient-centered health utility score and is more sensitive to the COPD health of the individual and less sensitive to other comorbidities. This disease-specific instrument should be considered alongside generic health-related quality of life instruments when valuing new COPD therapies in submissions to licensing and reimbursement agencies.

Previous qualitative research analyzing social media and online community discussions highlighted the symptomatic burden of cough and mucus (sputum), alongside shortness of breath, in patients with chronic obstructive pulmonary disease (COPD). The objective of this study was to determine the relative importance of these symptoms and their consequences (for example, disturbed sleep) to COPD patients, compared with conventional COPD endpoints (lung function and exacerbations).

A total of 1,050 patients (at least 40 years of age) with moderate to severe COPD or chronic bronchitis, and regular symptoms of cough and excess mucus production, are to be recruited through patient advocacy groups (PAGs) from five countries (Australia, France, Japan, the United Kingdom, and the United States; 150 to 400 patients per country). A discrete choice experiment was designed with input from clinical experts and the PAGs, plus scientific advice from the National Institute for Health and Care Excellence (NICE) in the United Kingdom. Patients’ preferences for the conditional relative importance of symptoms and impact of COPD will be quantified based on trade-offs they are willing to make among hypothetical COPD disease state profiles, described by differing attributes and levels. Hierarchical Bayesian analysis with effect-coding parameterization will be undertaken on the choice data to estimate (using Gibbs sampling) the relative value each respondent places on an attribute level.

The feedback from NICE informed the selection of screening criteria and the statistical analysis plan, as well as the inclusion of a health status measure, the EQ-5D-3L. Qualitative patient interviews and pilot testing of the attributes and levels grid have been completed, informing finalization of the online survey design.

Patient preference studies evaluating the relative importance of symptom burden through assessment of disease state preference values are an important new form of patient-based evidence for informing value-based decision making in HTA. The present study should facilitate a more patient-centered approach to developing new treatments for and improving the care of patients with COPD.