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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:sec>
<jats:title>Background</jats:title>
<jats:p>Health-related quality of life (HRQL) has become an important outcome parameter in cardiology. The MOS 36-ltem Short-Form Health Survey (SF-36) and the PROMIS-29 are two widely used generic measures providing composite HRQL scores. The domains of the SF-36, a well-established instrument utilized for several decades, can be aggregated to physical (PCS) and mental (MCS) component summary scores. Alternative scoring algorithms for correlated component scores (PCS<jats:sub>c</jats:sub> and MCS<jats:sub>c</jats:sub>) have also been suggested. The PROMIS-29 is a newer but increasingly used HRQL measure. Analogous to the SF-36, physical and mental health summary scores can be derived from PROMIS-29 domain scores, based on a correlated factor solution. So far, scores from the PROMIS-29 are not directly comparable to SF-36 results, complicating the aggregation of research findings. Thus, our aim was to provide algorithms to convert PROMIS-29 data to well-established SF-36 component summary scores.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>Data from <jats:italic>n</jats:italic> = 662 participants of the Berlin Long-term Observation of Vascular Events (BeLOVE) study were used to estimate linear regression models with either PROMIS-29 domain scores or aggregated PROMIS-29 physical/mental health summary scores as predictors and SF-36 physical/mental component summary scores as outcomes. Data from a subsequent assessment point (<jats:italic>n</jats:italic> = 259) were used to evaluate the agreement between empirical and predicted SF-36 scores.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>PROMIS-29 domain scores as well as PROMIS-29 health summary scores showed high predictive value for PCS, PCS<jats:sub>c</jats:sub>, and MCS<jats:sub>c</jats:sub> (R<jats:sup>2</jats:sup> ≥ 70%), and moderate predictive value for MCS (R<jats:sup>2</jats:sup> = 57% and R<jats:sup>2</jats:sup> = 40%, respectively). After applying the regression coefficients to new data, empirical and predicted SF-36 component summary scores were highly correlated (<jats:italic>r</jats:italic> > 0.8) for most models. Mean differences between empirical and predicted scores were negligible (|SMD|<0.1).</jats:p>
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<jats:title>Conclusions</jats:title>
<jats:p>This study provides easy-to-apply algorithms to convert PROMIS-29 data to well-established SF-36 physical and mental component summary scores in a cardiovascular population. Applied to new data, the agreement between empirical and predicted SF-36 scores was high. However, for SF-36 mental component summary scores, considerably better predictions were found under the correlated (MCS<jats:sub>c</jats:sub>) than under the original factor model (MCS). Additionally, as a pertinent byproduct, our study confirmed construct validity of the relatively new PROMIS-29 health summary scores in cardiology patients.</jats:p>
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Hinweis
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DeepGreen-ID: b57e506a96da4b9b850356ad14000183 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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