Artikel
Health-related quality of life in multiple myeloma and mapping algorithms to derive health-state utility values: an overview
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Autoren
Veröffentlicht: | 20. März 2019 |
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Gliederung
Text
Background/research question: Health-related quality of life (HRQoL) and health-state utility values (HSUVs) are measured with different methods and instruments. Deriving HSUVs from generic preference-based instruments (e.g., EQ-5D, SF-6D, HUI) is recommended by academic institutions, HTA agencies and reimbursement authorities. In clinical trials of patients with multiple myeloma (MM), condition-specific instruments are most frequently used to measure HRQoL. When HSUVs are not available, “mapping” can be applied to link outcomes from different measures of HRQoL to HSUVs. Therefore, our aim is to give an overview on published HRQoL data in MM patients and to assess if the identified data could be applied to derive HSUVs with already published mapping techniques.
Methods: We performed a systematic literature search in PubMed/MEDLINE, Cochrane, Tufts CEA Registry, Web of Science, EQ-5D and EORTC databases to identify studies reporting on HRQoL data and/or HSUVs in patients diagnosed and treated for MM, derived from EQ-5D and/or EORTC (QLQ-C30 or QLQ-MY20). We used evidence tables to systematically extract and summarize HRQoL data, HSUVs and study characteristics. To assess if published mapping algorithms could be used to derive HSUVs from the extracted HRQoL data, we compared population characteristics, treatments and functional scores reported.
Results: From the overall 847 identified studies, we included 31 studies for analysis based on our inclusion criteria. All included studies reported data from the QLQ-C30 for MM patients, five studies reported HSUVs derived from the EQ-5D and 18 studies showed HRQoL data derived from the QLQ-MY20. Treatment combinations included bortezomib, thalidomide, lenalidomide, carfilzomib, pamidronate melphalan, prednisone, dexamethasone, and stem cell transplantation. Only 16 studies explained the complete range of functional scores from the QLQ-C30 or QLQ-MY20 and could be used to calculate HSUVs applying the mapping algorithms [1], [2], [3].
Conclusions: We identified studies reporting on HRQoL data in patients with MM from the QLQ-C30 or QLQ-MY20 that could be used in mapping estimations to derive HSUVs for MM. Several studies did not report full functional scores of the questionnaire as needed for the mapping algorithms, thus limiting their applicability for mapping to derive HSUVs.
References
- 1.
- Kharroubi SA, Edlin R, Meads D, Browne C, Brown J, McCabe C. Use of Bayesian Markov chain Monte Carlo methods to estimate EQ-5D utility scores from EORTC QLQ data in myeloma for use in cost-effectiveness analysis. Med Decis Making. 2015;35(3):351-60.
- 2.
- McKenzie L, van der Pol M. Mapping the EORTC QLQ C-30 onto the EQ-5D instrument: the potential to estimate QALYs without generic preference data. Value Health. 2009;12(1):167-71.
- 3.
- Proskorovsky I, Lewis P, Williams CD, Jordan K, Kyriakou C, Ishak J, et al. Mapping EORTC QLQ-C30 and QLQ-MY20 to EQ-5D in patients with multiple myeloma. Health Qual Life Outcomes. 2014;12:35.