Dataset Information

Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

ABSTRACT: BACKGROUND:Measuring patient-reported outcomes (PROs) is becoming an integral component of quality improvement initiatives, clinical care, and research studies in cancer, including comparative effectiveness research. However, the number of PROs limits comparability across studies. Herein, the authors attempted to link the Functional Assessment of Cancer Therapy-General Physical Well-Being (FACT-G PWB) subscale with the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) calibrated item bank. The also sought to augment a subset of the conceptually most similar FACT-G PWB items with PROMIS PF items to improve the linking. METHODS:Baseline data from 5506 participants in the Measuring Your Health (MY-Health) study were used to identify the optimal items for linking FACT-G PWB with PROMIS PF. A mixed methods approach identified the optimal items for creating the 5-item FACT/PROMIS-PF5 scale. Both the linked and augmented relationships were cross-validated using the follow-up MY-Health data. RESULTS:A 5-item FACT-G PWB item subset was found to be optimal for linking with PROMIS PF. In addition, a 2-item subset, including only items that were conceptually very similar to the PROMIS item bank content, were augmented with 3 PROMIS PF items. This new FACT/PROMIS-PF5 provided superior score recovery. CONCLUSIONS:The PROMIS PF metric allows for the evaluation of the extent to which similar questionnaires can be linked and therefore expressed on the same metric. These results allow for the aggregation of existing data and provide an optimal measure for future studies wishing to use the FACT yet also report on the PROMIS PF metric. Cancer 2018;124:153-60. © 2017 American Cancer Society.

SUBMITTER: Kaat AJ

PROVIDER: S-EPMC5734956 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature

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Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

Kaat Aaron J AJ Schalet Benjamin D BD Rutsohn Joshua J Jensen Roxanne E RE Cella David D

Cancer 20170908 1

<h4>Background</h4>Measuring patient-reported outcomes (PROs) is becoming an integral component of quality improvement initiatives, clinical care, and research studies in cancer, including comparative effectiveness research. However, the number of PROs limits comparability across studies. Herein, the authors attempted to link the Functional Assessment of Cancer Therapy-General Physical Well-Being (FACT-G PWB) subscale with the Patient-Reported Outcomes Measurement Information System (PROMIS) Phy ...[more]

PMID: 28885707

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Project description:BackgroundLimitations in physical functioning are a big concern especially for patients with chronic or musculoskeletal diseases. Therefore, physical functioning is often used as a core outcome of treatments. The generic patient-reported outcomes information system (PROMIS) physical function (PF) item bank has shown potential to measure PF with better precision, interpretability and lower respondent burden compared with traditional patient-reported outcome measures. This study provides an overview of the current evidence on the quality of the measurement properties of the translated Dutch-Flemish PROMIS-PF item bank and its subdomains, and their derived short forms and computer adaptive tests (CATs).MethodsPubMed was searched up to June 17th 2020 for validation studies of Dutch-Flemish PROMIS-PF in Dutch and Flemish adults. Quality assessment of the included studies was conducted using the COSMIN Risk of bias checklist. The COSMIN criteria for good measurement properties were used to judge the results of the studies, which were adjusted and added to where needed for this review, in the context of IRT instruments and item banks. The quality of evidence was summarized for each measurement property based on the Grading of Recommendation Assessment, Development, and Evaluation (GRADE) approach.ResultsEleven studies were included, evaluating the PROMIS-PF item bank, the Upper Extremity (UE) subdomain, and/or their derived short forms and CATs in different clinical populations. There is evidence for sufficient structural validity, measurement precision, construct validity, and cross-cultural validity of the Dutch-Flemish PROMIS-PF item bank. The upper extremity subdomain item bank shows high quality evidence for structural validity and measurement precision. Content validity of these item banks has not been thoroughly demonstrated in a Dutch-Flemish population. Furthermore, the derived instruments have far less robust evidence: there are fewer validation studies available and none examined their performance as stand-alone administered instruments.ConclusionsThe first studies into the Dutch-Flemish PROMIS-PF item bank and the UE subdomain show promising results, with especially high quality evidence for sufficient structural validity and measurement precision. However, more studies, and with higher methodological quality, are needed to study the instruments derived from these item banks. These studies should also evaluate content validity, reliability and responsiveness.

Project description:Background and objectiveThe Patient-Reported Outcomes Measurement Information System (PROMIS-29) is gaining popularity as healthcare system funders increasingly seek value-based care. However, it is limited in its ability to estimate utilities and thus inform economic evaluations. This study develops the first mapping algorithm for estimating EuroQol 5-Dimension 5-Level (EQ-5D-5L) utilities from PROMIS-29 responses using a large dataset and through extensive comparisons between econometric models.MethodsAn online survey was conducted to collect responses to PROMIS-29 and EQ-5D-5L from the general Australian population (N = 3013). Direct and indirect mapping methods were explored, including linear regression, Tobit, generalised linear model, censored regression model, beta regression (Betamix), the adjusted limited dependent variable mixture model (ALDVMM) and generalised ordered logit. The most robust model was selected by assessing the performance based on average ten-fold cross-validation geometric mean absolute error and geometric mean squared error, the predicted mean, maximum and minimum utilities, as well as the fitting across the entire distribution.ResultsThe direct approach using ALDVMM was considered the preferred model based on lowest geometric mean absolute error and geometric mean squared error in cross-validation (0.0882, 0.0299) and its superiority in predicting the actual observed mean, full health states and lower utility extremes. The robustness and precision in prediction across the entire distribution of utilities with ALDVMM suggest it is an accurate and valid mapping algorithm. Moreover, the suggested mapping algorithm outperformed previously published algorithms using Australian data, indicating the validity of this model for economic evaluations.ConclusionsThis study developed a robust algorithm to estimate EQ-5D-5L utilities from PROMIS-29. Consistent with the recent literature, the ALDVMM outperformed all other econometric models considered in this study, suggesting that the mixture models have relatively better performance and are an ideal candidate model for mapping.

Dataset Information

Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

Publications

Physical function metric over measure: An illustration with the Patient-Reported Outcomes Measurement Information System (PROMIS) and the Functional Assessment of Cancer Therapy (FACT).

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