Improving Interpretation of Evidence Relating to Quality of Life in Health Technology Assessments of Rare Disease Treatments.
Elena NicodAndrew J LloydThomas MorelMichela MeregagliaSheela UpadhyayaAmanda WhittalKaren M FaceyMichael F DrummondPublished in: The patient (2022)
Rare diseases are often severe, debilitating, life-limiting conditions, many of which occur in childhood. These complex conditions have a wide range of clinical manifestations that have a substantial impact on the lives of patients, carers and families and often produce heterogeneous clinical outcomes. Therefore, the evaluation of quality-of-life (QoL) impacts is important. In health technology assessment (HTA), patient-reported outcome measures (PROMs) and/or health state utility values (HSUVs) are used to determine QoL impacts of new treatments, but their use in rare diseases is challenging due to small and heterogeneous populations and limited disease knowledge. This paper describes challenges associated with the use of patient-reported outcomes (PROs)/HSUVs to evaluate QoL in HTA of rare disease treatments (RDTs) and identifies five recommendations to ensure appropriate interpretation of QoL impacts. These were derived from mixed methods research (literature reviews, appraisal document analyses, appraisal committee observations and interviews) examining the use of PROs/HSUVs in HTA of RDTs. They highlight that HTAs of RDTs must (1) understand the QoL impacts of the disease and of treatments; (2) critically assess PRO data, recognising the nuances in development and administration of PROMs/HSUVs, considering what is feasible and what matters most to the patient population; (3) recognise that lack of significant effect on a PRO does not imply no QoL benefit; (4) use different forms of evidence to understand QoL impacts, such as patient input; and (5) provide methodological guidance to capture QoL impacts on patients/carers.
Keyphrases
- patient reported outcomes
- healthcare
- end stage renal disease
- patient reported
- public health
- ejection fraction
- mental health
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- health information
- prognostic factors
- clinical trial
- machine learning
- electronic health record
- dna methylation
- risk assessment
- health promotion
- climate change
- early life
- artificial intelligence
- young adults
- childhood cancer