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Quality of Life Research

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01-09-2014 | Brief Communication

Comparing PROMIS computer-adaptive tests to the Brief Symptom Inventory in patients with prostate cancer

Auteurs: George Baum, Karen Basen-Engquist, Maria C. Swartz, Patricia A. Parker, Cindy L. Carmack

Gepubliceerd in: Quality of Life Research | Uitgave 7/2014

Abstract

Purpose

This study assessed whether the Patient-Reported Outcomes Measurement Information System (PROMIS) computer-adaptive tests (CATs) provided results similar to those of the Brief Symptom Inventory (BSI) with a low patient burden.

Methods

Secondary data analysis of 136 prostate cancer patients who completed the 53-item BSI and the PROMIS CATs assessing depression, anxiety, and hostility.

Results

The PROMIS CATs and BSI correlated significantly in measures of depression (.85), anxiety (.76), and anger/hostility (.66; p < .001 for all). Using our BSI cutoff points for depression, anxiety, and anger/hostility, ROC analysis yielded areas under the curve of .966 [standard error (SE) = .014, p < .001], .975 (SE = .012, p < .001), and .952 (SE = .027, p < .001), respectively.

Conclusions

PROMIS CATs were highly correlated with the BSI subscales, indicating that the CATs performed well compared with the BSI, a widely used psychosocial measure.

vorige artikel Measuring individual quality of life in patients receiving radiation therapy: the SEIQoL-Questionnaire

volgende artikel Differential item functioning in the Observer Scale of the POSAS for different scar types

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Titel: Comparing PROMIS computer-adaptive tests to the Brief Symptom Inventory in patients with prostate cancer
Auteurs: George Baum
Karen Basen-Engquist
Maria C. Swartz
Patricia A. Parker
Cindy L. Carmack
Publicatiedatum: 01-09-2014
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 7/2014
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-014-0647-2

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Purpose

Methods

Results

Conclusions

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