Dataset Information

Computing PROPr Utility Scores for PROMIS® Profile Instruments.

ABSTRACT:

Objectives

The Patient-Reported Outcomes Measurement Information System® (PROMIS) Profile instruments measure health status on 8 PROMIS domains. The PROMIS-Preference (PROPr) score provides a preference-based summary score for health states defined by 7 PROMIS domains. The Profile and PROPr share 6 domains; PROPr has 1 unique domain (Cognitive Function-Abilities), and the Profile has 2 unique domains (Anxiety and Pain Intensity). We produce an equation for calculating PROPr utility scores with Profile data.

Methods

We used data from 3982 members of US online survey panels who have scores on all 9 PROMIS domains. We used a 70%/30% split for model fit/validation. Using root-mean-square error and mean error on the utility scale, we compared models for predicting the missing Cognitive Function score via (A) the population average; (B) a score representing excellent cognitive function; (C) a score representing poor cognitive function; (D) a score predicted from linear regression of the 8 profile domains; and (E) a score predicted from a Bayesian neural network of the 8 profile domains.

Results

The mean errors in the validation sample on the PROPr scale (which ranges from -0.022 to 1.00) for the models were: (A) 0.025, (B) 0.067, (C) -0.23, (D) 0.018, and (E) 0.018. The root-mean-square errors were: (A) 0.097, (B) 0.12, (C) 0.29, (D) 0.095, and (E) 0.094.

Conclusion

Although the Bayesian neural network had the best root-mean-square error for producing PROPr utility scores from Profile instruments, linear regression performs almost as well and is easier to use. We recommend the linear model for producing PROPr utility scores for PROMIS Profiles.

SUBMITTER: Dewitt B

PROVIDER: S-EPMC7269185 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Computing PROPr Utility Scores for PROMIS® Profile Instruments.

Dewitt Barry B Jalal Hawre H Hanmer Janel J

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research 20191230 3

<h4>Objectives</h4>The Patient-Reported Outcomes Measurement Information System® (PROMIS) Profile instruments measure health status on 8 PROMIS domains. The PROMIS-Preference (PROPr) score provides a preference-based summary score for health states defined by 7 PROMIS domains. The Profile and PROPr share 6 domains; PROPr has 1 unique domain (Cognitive Function-Abilities), and the Profile has 2 unique domains (Anxiety and Pain Intensity). We produce an equation for calculating PROPr utility score ...[more]

PMID: 32197733

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Project description:Background Bringing together generic and heart failure (HF)-specific items in a publicly available, patient-reported outcome measure may facilitate routine health status assessment for improving clinical care and shared decision-making, assessing quality of care, evaluating new interventions, and comparing groups with different conditions. Methods and Results We performed a mixed-methods study to develop and validate the PROMIS®-Plus-HF (Patient-Reported Outcomes Measurement Information System®-Plus-Heart Failure) profile measure-a HF-specific instrument based on the generic PROMIS. We conducted 8 focus groups with 61 patients with HF and phone interviews with 10 HF clinicians. The measure was developed via an iterative process of reviewing existing PROMIS items and developing and testing new HF items. In a 600-patient sample, we estimated reliability (internal consistency; test-retest, with n=100 participants). We conducted validity analyses using Pearson r and Spearman ρ correlations with Kansas City Cardiomyopathy Questionnaire subscores. In a longitudinal sample, we performed responsiveness testing (paired t tests) with 75 patients with HF receiving interventions with expected health status improvement. The PROMIS-Plus-HF measure comprises 86 items (64 existing; 22 new) across 18 domains. Internal consistency reliability (Cronbach α) coefficients ranged from 0.52 to 0.96, with α≥0.70 in 12 of 17 domains. Test-retest intraclass correlation coefficients were ≥0.90. Correlations with Kansas City Cardiomyopathy Questionnaire subscores supported expected convergent ( r/ρ>0.60) and divergent validity ( r/ρ<0.30). In the longitudinal sample, 10 of 18 domains had improved ( P<0.05) scores from baseline to follow-up. Conclusions The PROMIS-Plus-HF profile measure-a complete assessment of physical, mental, and social health-exhibited good psychometric characteristics and may facilitate patient-centered care and research. Subsets of domains and items can be used depending on the clinical or research purpose.

Project description:Background and objectivesA preference-based health utility score (PROPr) can be calculated using Patient-Reported Outcomes Measurement Information System domain scores. We assessed the construct validity of PROPr among patients treated with KRT (hemodialysis or kidney transplant).Design, setting, participants, & measurementsWe performed a secondary analysis of data collected in multicenter, cross-sectional studies of adults treated with KRT, recruited between April 2016 to March 2020 in Toronto, Canada. All participants provided informed consent. The outcome was the PROPr score. Coadministered outcome variables included the Short-Form Six-Domain (SF-6D) and EuroQol Five-Domain Five-Level (EQ-5D-5L) scores. Socioeconomic and clinical variables included age, sex, diabetes, eGFR, serum albumin, hemoglobin, KRT, and Charlson Comorbidity Index. Construct validity was assessed through correlations between PROPr and SF-6D or EQ-5D-5L, and associations between PROPr and other exposure variables. Health-condition impact estimates (coefficients for health conditions compared with a referent category, e.g., dialysis versus kidney transplant) were calculated using multivariable linear regression.ResultsThe mean (SD) age of the 524 participants was 57 (17) years, 58% were male, and 45% were White. Median (interquartile range) score was 0.39 (0.24-0.58) for PROPr, 0.69 (0.58-0.86) for SF-6D, and 0.85 (0.70-0.91) for EQ-5D-5L. Large correlations were observed between PROPr versus SF-6D (0.79; 95% confidence interval [95% CI], 0.76 to 0.82) and EQ-5D-5L (0.71; 95% CI, 0.66 to 0.75). Both PROPr and the other utility indices demonstrated health-condition impact in the expected direction. For example, the estimate for PROPr was -0.17 (95% CI, -0.13 to -0.21) for dialysis (versus kidney transplant), -0.05 (95% CI, -0.11 to 0.01; P=0.08) for kidney transplant recipients with an eGFR of <45 versus ≥45 ml/min per 1.73 m2, and -0.28 (95% CI, -0.22 to -0.33) for moderate/severe versus no/mild depressive symptoms.ConclusionsOur results support the validity of PROPr among patients treated with KRT.

Project description:BackgroundThe PROMIS Preference score (PROPr) is a new generic preference-based health-related quality of life (HRQoL) score that can be used as a health state utility (HSU) score for quality-adjusted life years (QALYs) in cost-utility analyses (CUAs). It is the first HSU score based on item response theory (IRT) and has demonstrated favorable psychometric properties in first analyses. The PROPr combines the seven PROMIS domains: cognition, depression, fatigue, pain, physical function, sleep disturbance, and ability to participate in social roles and activities. It was developed based on preferences of the US general population. The aim of this study was to validate the PROPr in a German inpatient sample and to compare it to the EQ-5D.MethodsWe collected PROPr and EQ-5D-5L data from 141 patients undergoing inpatient treatment in the rheumatology and psychosomatic departments. We evaluated the criterion and convergent validity, and ceiling and floor effects of the PROPr and compared those characteristics to those of the EQ-5D.ResultsThe mean PROPr (0.26, 95% CI: 0.23; 0.29) and the mean EQ-5D (0.44, 95% CI: 0.38; 0.51) scores differed significantly (d = 0.18, p < 0.001). Compared to the EQ-5D, the PROPr scores were less scattered across the measurement range which has resulted in smaller confidence intervals of the mean scores. The Pearson correlation coefficient between the two scores was r = 0.72 (p < 0.001). Both scores showed fair agreement with an Intraclass Correlation Coefficient (ICC) of 0.48 (p < 0.05). The PROPr and EQ-5D demonstrated similar discrimination power across sex, age, and conditions. While the PROPr showed a floor effect, the EQ-5D showed a ceiling effect.ConclusionThe PROPr measures HSU considerably lower than the EQ-5D as a result of different construction, anchors and measurement ranges. Because QALYs derived with the EQ-5D are widely considered state-of-the-art, application of the PROPr for QALY measurements would be problematic.

Project description:AimsHeart failure (HF) is a common and morbid condition impacting multiple health domains. We previously reported the development of the PROMIS®-Plus-HF (PROMIS+HF) profile measure, including universal and HF-specific items. To facilitate use, we developed shorter, PROMIS+HF profiles intended for research and clinical use.Methods and resultsCandidate items were selected based on psychometric properties and symptom range coverage. HF clinicians (n = 43) rated item importance and clinical actionability. Based on these results, we developed the PROMIS+HF-27 and PROMIS+HF-10 profiles with summary scores (0-100) for overall, physical, mental, and social health. In a cross-sectional sample (n = 600), we measured internal consistency reliability (Cronbach's alpha and Spearman-Brown), test-retest reliability (intraclass coefficient; n = 100), known-groups validity via New York Heart Association (NYHA) class, and convergent validity with Kansas City Cardiomyopathy Questionnaire (KCCQ) scores. In a longitudinal sample (n = 75), we evaluated responsiveness of baseline/follow-up scores by calculating mean differences and Cohen's d and comparing with paired t-tests. Internal consistency was good to excellent (α 0.82-0.94) for all PROMIS+HF-27 scores and acceptable to good (α/Spearman-Brown 0.60-0.85) for PROMIS+HF-10 scores. Test-retest intraclass coefficients were acceptable to excellent (0.75-0.97). Both profiles demonstrated known-groups validity for the overall and physical health summary scores based on NYHA class, and convergent validity for nearly all scores compared with KCCQ scores. In the longitudinal sample, we demonstrated responsiveness for PROMIS+HF-27 and PROMIS+HF-10 overall and physical summary scores. For the PROMIS+HF overall summary scores, a group-based increase of 7.6-8.3 points represented a small to medium change (Cohen's d = 0.40-0.42). For the PROMIS+HF physical summary scores, a group-based increase of 5.0-5.9 points represented a small to medium change (Cohen's d = 0.29-0.35).ConclusionsThe PROMIS+HF-27 and PROMIS+HF-10 profiles demonstrated good psychometric characteristics with evidence of responsiveness for overall and physical health. These new measures can facilitate patient-centred research and clinical care, such as improving care quality through symptom monitoring, facilitating shared decision-making, evaluating quality of care, assessing new interventions, and monitoring during the initiation and titration of guideline-directed medical therapy.

Dataset Information

Computing PROPr Utility Scores for PROMIS® Profile Instruments.

Objectives

Methods

Results

Conclusion

Publications

Computing PROPr Utility Scores for PROMIS® Profile Instruments.

Similar Datasets

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