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Comparing Approaches to Link SF-36 PF-10 Scores to PROMIS Physical Function: A Validation Study in Three Clinical
Audrey Yuki Brinker1, Sandra Nolte2,3, Felix H Fischer4
1Center for Patient-Centered Outcomes Research (CPCOR), Department of Psychosomatic Medicine, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, and Berlin Institute of Health, Berlin, Germany. Audrey-Yuki.Brinker@Charite.de.
Linking methods reliably translate SF-36 PF-10 scores to PROMIS-PF T-scores in clinical populations. Cross-walk tables offer a practical approach for score conversion without complex statistical modeling.
Area of Science:
- Health Outcomes Research
- Psychometrics
- Clinical Measurement
Background:
- Physical function (PF) is a key patient-reported outcome (PRO) across various conditions.
- Disparate PRO measures (PROMs) hinder score comparability and interpretability.
- The Patient-Reported Outcomes Measurement Information System (PROMIS®) developed a standardized T-score metric using item response theory (IRT) to address this.
- Linking algorithms enable conversion of scores from different PROMs to the PROMIS-PF metric for harmonization.
Purpose of the Study:
- To validate and compare two established linking methods for translating SF-36 PF-10 scores to the PROMIS-PF metric.
- To assess the reliability of these methods in diverse clinical populations.
Main Methods:
- Two linking approaches were evaluated: item-level linking and cross-walk tables.
- PROMIS-PF T-scores derived from SF-36 PF-10 scores were compared against directly observed PROMIS-PF20a T-scores.
- The study included patients from cardiology, rheumatology, and psychosomatic medicine.
Main Results:
- All linking methods showed high correlation with observed PROMIS-PF20a T-scores (Pearson correlation ≥ 0.84).
- Negligible practical differences were observed at the group level (standardized mean difference < 0.2).
Conclusions:
- Established linking methods reliably translate SF-36 PF-10 scores to PROMIS-PF T-scores across clinical samples.
- This eliminates the need for re-estimating models for new datasets.
- Cross-walk tables are recommended as a practical method for score conversion, avoiding complex statistical modeling.
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