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Mapping the patient-oriented prostate utility scale from the expanded prostate cancer index composite and the short-form health surveys

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dc.contributor.author Zamora, Victor
dc.contributor.author Garin Boronat, Olatz, 1979-
dc.contributor.author Pardo Cladellas, Yolanda
dc.contributor.author Pont Acuña, Àngels
dc.contributor.author Gutiérrez, Cristina
dc.contributor.author Cabrera Roldán, Patricia
dc.contributor.author Gómez-Veiga, Francisco
dc.contributor.author Pijoán, José Ignacio
dc.contributor.author Litwin, Mark S.
dc.contributor.author Ferrer Forés, Montserrat
dc.contributor.author Multicentric Spanish Group of Clinically Localized Prostate Cancer
dc.date.accessioned 2022-07-14T07:13:00Z
dc.date.issued 2021
dc.identifier.citation Zamora V, Garin O, Pardo Y, Pont À, Gutiérrez C, Cabrera P, et al. Mapping the patient-oriented prostate utility scale from the expanded prostate cancer index composite and the short-form health surveys. Value Health. 2021 Nov; 24(11):1676-85. DOI: 10.1016/j.jval.2021.03.021
dc.identifier.issn 1098-3015
dc.identifier.uri http://hdl.handle.net/10230/53731
dc.description.abstract Objectives: this study aimed to develop mapping algorithms from the Expanded Prostate Cancer Index Composite (EPIC) and the Short-Form (SF) Health Surveys to the Patient-Oriented Prostate Utility Scale (PORPUS), an econometric instrument specifically developed for patients with prostate cancer. Methods: data were drawn from 2 cohorts concurrently administering PORPUS, EPIC-50, and SF-36v2. The development cohort included patients who had received a diagnosis of localized or locally advanced prostate cancer from 2017 to 2019. The validation cohort included men who had received a diagnosis of localized prostate cancer from 2014 to 2016. Linear regression models were constructed with ln(1 - PORPUS utility) as the dependent variable and scores from the original and brief versions of the EPIC and SF as independent variables. The predictive capacity of mapping models constructed with all possible combinations of these 2 instruments was assessed through the proportion of variance explained (R2) and the agreement between predicted and observed values. Validation was based on the comparison between estimated and observed utility values in the validation cohort. Results: models constructed with EPIC-50 with and without SF yielded the highest predictive capacity (R2 = 0.884, 0.871, and 0.842) in comparison with models constructed with EPIC-26 (R2 = 0.844, 0.827, and 0.776). The intraclass correlation coefficient was excellent in the 4 models (>0.9) with EPIC and SF. In the validation cohort, predicted PORPUS utilities were slightly higher than those observed, but differences were not statistically significant. Conclusions: Mapping algorithms from both the original and the abbreviated versions of the EPIC and the SF Health Surveys allow estimating PORPUS utilities for economic evaluations with cost-utility analyses in patients with prostate cancer.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier http://dx.doi.org/10.1016/j.jval.2021.03.021
dc.title Mapping the patient-oriented prostate utility scale from the expanded prostate cancer index composite and the short-form health surveys
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1016/j.jval.2021.03.021
dc.subject.keyword EPIC
dc.subject.keyword PORPUS
dc.subject.keyword Health utility measures
dc.subject.keyword Localized prostate cancer
dc.subject.keyword Mapping
dc.subject.keyword Patient-reported outcomes
dc.rights.accessRights info:eu-repo/semantics/embargoedAccess
dc.type.version info:eu-repo/semantics/acceptedVersion
dc.embargo.liftdate 2022-11-24
dc.date.embargoEnd info:eu-repo/date/embargoEnd/2022-11-24


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