Dataset Information

A reporting checklist for HealthMeasures' patient-reported outcomes: ASCQ-Me, Neuro-QoL, NIH Toolbox, and PROMIS.

ABSTRACT:

Background

ASCQ-Me®, Neuro-QoL™, NIH Toolbox®, and PROMIS®, which are health-related quality of life measures collectively known as HealthMeasures, have experienced rapid uptake in the scientific community with over 1700 peer-reviewed publications through 2018. Because of their proliferation across multiple research disciplines, there has been significant heterogeneity in the description and reporting of these measures. Here, we provide a publication checklist to promote standardization and comparability across different reports. This checklist can be used across all HealthMeasures systems. Checklist Development: Authors drafted a draft checklist, circulated among the HealthMeasures Steering Committee and PROMIS Health Organization until the members reached consensus. Checklist: The final checklist has 21 entries in 4 categories: measure details, administration, scoring, and reporting. Most entries (11) specify necessary measure-specific details including version number and administration language(s). Administration (4 entries) reminds authors to include details such as use of proxy respondents and the assessment platform. Scoring (3 entries) is necessary to ensure replication and cross-study comparisons. Reporting (3 entries) reminds authors to always report scores on the T-score metric.

Conclusion

Consistent documentation is necessary to ensure transparent and reproducible methods and support the accumulation of evidence across studies. This checklist promotes standardization and completeness in documentation for ASCQ-Me, Neuro-QoL, PROMIS, and NIH Toolbox measures.

SUBMITTER: Hanmer J

PROVIDER: S-EPMC7096598 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Publications

A reporting checklist for HealthMeasures' patient-reported outcomes: ASCQ-Me, Neuro-QoL, NIH Toolbox, and PROMIS.

Hanmer Janel J Jensen Roxanne E RE Rothrock Nan N

Journal of patient-reported outcomes 20200326 1

<h4>Background</h4>ASCQ-Me®, Neuro-QoL™, NIH Toolbox®, and PROMIS®, which are health-related quality of life measures collectively known as HealthMeasures, have experienced rapid uptake in the scientific community with over 1700 peer-reviewed publications through 2018. Because of their proliferation across multiple research disciplines, there has been significant heterogeneity in the description and reporting of these measures. Here, we provide a publication checklist to promote standardization ...[more]

PMID: 32215788

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Project description:ImportanceCognitive dysfunction (CD) is recognized by the American Cancer Society as a treatment effect in head and neck cancer, but the extent of this problem at baseline in oropharyngeal cancer (OPC), the most common subsite in current practice, to our knowledge has never been studied.ObjectiveTo assess the baseline cognition of patients with OPC using National Institutes of Health (NIH)-sponsored instruments of Patient-Reported Outcomes Measurement Information System (PROMIS) and NIH Toolbox Cognitive Battery (NIHTB-CB).Design, setting, and participantsThis was a prospective cohort study conducted at a tertiary academic center. Of 83 consecutive patients, newly diagnosed as having OPC from September 2016 to May 2017, 16 were ineligible, 8 refused to participate, and 3 were lost to follow-up after screening, resulting in 56 study participants.Main outcomes and measuresSelf-perceived and objective cognition with PROMIS and NIHTB-CB standardized T scores, respectively, were main outcomes. Impairment was defined as (1) T scores less than 0.5 SD for PROMIS; (2) T score less than 1.5 SD in at least 1 cognitive domain or less than 1 SD in 2 or more domains for NIHTB-CB total cognition; and (3) T score per previously published criteria for NIHTB-CB intelligence-stratified cognition.ResultsOf the 56 study participants (52 men, 4 women; median age, 59 years [range, 42-77 years]), 19 (34%) had a college degree, and 20 (36%) had a professional or technical occupation. Thirty (about 53%) were never-smokers, 26 (46%) were never-drinkers, 29 (52%) were obese, 13 (23%) had a moderate to severe comorbidity, 3 (5%) used antidepressants, and 25 (52%) had hearing loss. Impaired self-reported, NIHTB-CB total, and intelligence-stratified cognition scores were observed in 6 (11%), 18 (32%), and 12 (21%), respectively. Among all variables, objective impairment was more common in men (23% vs 0%) and those with p16-negative OPC (33% vs 20%), moderate to severe comorbidity (31% vs 18%), and hearing loss (31% vs 12%).Conclusions and relevanceImpaired objective cognition was more common at baseline than self-reported, and was more frequent in men, participants with p16-negative OPC, moderate to severe comorbidity, and hearing loss. NIHTB-CB allowed immediate scoring of demographically adjusted cognitive function. In clinical practice, these scores can be used to identify patients with impaired cognition at baseline who may be susceptible to developing further impairment after treatment. Identification of impairment at baseline will help to institute early cognitive interventions, which may lead to an improved posttreatment quality of life.

Project description:BackgroundThe Patient-Reported Outcomes Measurement Information SystemⓇ (PROMISⓇ) is a dynamic system of psychometrically sound patient-reported outcome (PRO) measures. There has been a recent increase in the use of PROMIS measures, yet little has been written about the reporting of these measures in the field of orthopedics. The purpose of this study was to conduct a systematic review to determine the uptake of PROMIS measures across orthopedics and to identify the type of PROMIS measures and domains that are most commonly used in orthopedic research and practice.MethodsWe searched PubMed, Embase, and Scopus using keywords and database-specific subject headings to capture orthopedic studies reporting PROMIS measures through November 2018. Our inclusion criteria were use of PROMIS measures as an outcome or used to describe a population of patients in an orthopedic setting in patients ≥ 18 years of age. We excluded non-quantitative studies, reviews, and case reports.ResultsOur final search yielded 88 studies published from 2013 through 2018, with 57% (50 studies) published in 2018 alone. By body region, 28% (25 studies) reported PROMIS measures in the upper extremity (shoulder, elbow, hand), 36% (32 studies) reported PROMIS measures in the lower extremity (hip, knee, ankle, foot), 19% (17 studies) reported PROMIS measures in the spine, 10% (9 studies) reported PROMIS measures in trauma patients, and 6% (5 studies) reported PROMIS measures in general orthopedic patients. The majority of studies reported between one and three PROMIS domains (82%, 73 studies). The PROMIS Computerized Adaptive Test (CAT) approach was most commonly used (81%, 72 studies). The most frequently reported PROMIS domains were physical function (81%, 71 studies) and pain interference (61%, 54 studies).ConclusionOur review found an increase in the reporting of PROMIS measures over the recent years. Utilization of PROMIS measures in orthopedic populations is clinically appropriate and can facilitate communication of outcomes across different provider types and with reduced respondent burden.RegistrationThe protocol for this systematic review was designed in accordance with the PRISMA guidelines and is registered with the PROSPERO database (CRD42018088260).

Project description:PurposeTo analyze time to completion of preoperative legacy patient-reported outcomes (PROs) and more recent computer adaptive Patient-Reported Outcomes Measurement Information System (PROMIS) questionnaires in patients with symptomatic femoroacetabular impingement syndrome undergoing primary hip arthroscopy.MethodsA retrospective analysis was conducted on patients undergoing hip arthroscopy by a single fellowship-trained hip arthroscopist. Inclusion criteria were patients undergoing primary arthroscopic hip surgery and completion of at least 1 legacy PRO or PROMIS questionnaire at the preoperative time point. Exclusion criteria were history of contralateral or ipsilateral hip surgery, non-English-speaking patients, patients who completed PROs by phone or by paper form, and patients who did not complete preoperative PROs. Legacy PROs included modified Harris Hip Score (mHHS), Hip Outcome Score (HOS), International Hip Outcome Tool (iHOT-12), and Hip Pain Visual Analog Scale (VAS-Pain). PROMIS PROs included Physical Function (PROMIS-PF), Pain Interference (PROMIS-PI), and Depression (PROMIS-D). Only preoperative PROs were included in the analysis. Completion time was calculated using the questionnaire start and stop time reported by the survey collecting software. The median and interquartile range of each PRO were reported for analysis of central tendency and statistical dispersion, respectively.ResultsA total of 1,901 patients and 269 patients were included in the legacy and PROMIS groups, respectively. The median time required for completion of each PRO in (minutes: seconds) format was as follows: mHHS (1:29), HOS (3:58), iHOT (2:11), VAS-Pain (0:32), PROMIS-PF (0:46), PROMIS-PI (0:37), and PROMIS-D (0:43). The interquartile range of the middle 50% of respondents was as follows; mHHS (0:58), HOS (2:46), iHOT (1:22), VAS-Pain (0:28), PROMIS-PI (0:19), PROMIS-D (0:29), and PROMIS-PF (0:20).ConclusionsThis study supports that preoperative PROMIS forms require less time to complete than preoperative legacy PROs and are not significantly influenced by age, race, or workers compensation status.Level of evidenceLevel IV, case series.

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

A reporting checklist for HealthMeasures' patient-reported outcomes: ASCQ-Me, Neuro-QoL, NIH Toolbox, and PROMIS.

Background

Conclusion

Publications

A reporting checklist for HealthMeasures' patient-reported outcomes: ASCQ-Me, Neuro-QoL, NIH Toolbox, and PROMIS.

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