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McEntee ML, Gandek B, Ware JE. Improving multimorbidity measurement using individualized disease-specific quality of life impact assessments: predictive validity of a new comorbidity index. Health Qual Life Outcomes 2022; 20:108. [PMID: 35820890 PMCID: PMC9277868 DOI: 10.1186/s12955-022-02016-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 06/25/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Interpretation of health-related quality of life (QOL) outcomes requires improved methods to control for the effects of multiple chronic conditions (MCC). This study systematically compared legacy and improved method effects of aggregating MCC on the accuracy of predictions of QOL outcomes. METHODS Online surveys administered generic physical (PCS) and mental (MCS) QOL outcome measures, the Charlson Comorbidity Index (CCI), an expanded chronic condition checklist (CCC), and individualized QOL Disease-specific Impact Scale (QDIS) ratings in a developmental sample (N = 5490) of US adults. Controlling for sociodemographic variables, regression models compared 12- and 35-condition checklists, mortality vs. population QOL-weighting, and population vs. individualized QOL weighting methods. Analyses were cross-validated in an independent sample (N = 1220) representing the adult general population. Models compared estimates of variance explained (adjusted R2) and model fit (AIC) for generic PCS and MCS across aggregation methods at baseline and nine-month follow-up. RESULTS In comparison with sociodemographic-only regression models (MCS R2 = 0.08, PCS = 0.09) and Charlson CCI models (MCS R2 = 0.12, PCS = 0.16), increased variance was accounted for using the 35-item CCC (MCS R2 = 0.22, PCS = 0.31), population MCS/PCS QOL weighting (R2 = 0.31-0.38, respectively) and individualized QDIS weighting (R2 = 0.33 & 0.42). Model R2 and fit were replicated upon cross-validation. CONCLUSIONS Physical and mental outcomes were more accurately predicted using an expanded MCC checklist, population QOL rather than mortality CCI weighting, and individualized rather than population QOL weighting for each reported condition. The 3-min combination of CCC and QDIS ratings (QDIS-MCC) warrant further testing for purposes of predicting and interpreting QOL outcomes affected by MCC.
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Affiliation(s)
- Mindy L McEntee
- College of Health Solutions, Arizona State University, 500 N. 3rd Street, Phoenix, AZ, 85004-0698, USA.
| | - Barbara Gandek
- University of Massachusetts Medical School, Worchester, MA, USA
- John Ware Research Group, Inc., Watertown, MA, USA
| | - John E Ware
- College of Health Solutions, Arizona State University, 500 N. 3rd Street, Phoenix, AZ, 85004-0698, USA
- University of Massachusetts Medical School, Worchester, MA, USA
- John Ware Research Group, Inc., Watertown, MA, USA
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Abu HO, Saczynski JS, Ware J, Mehawej J, Paul T, Awad H, Bamgbade BA, Pierre-Louis IC, Tisminetzky M, Kiefe CI, Goldberg RJ, McManus DD. Impact of comorbid conditions on disease-specific quality of life in older men and women with atrial fibrillation. Qual Life Res 2020; 29:3285-3296. [PMID: 32656722 DOI: 10.1007/s11136-020-02578-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/02/2020] [Indexed: 02/08/2023]
Abstract
BACKGROUND Older persons with atrial fibrillation (AF) experience significant impairment in quality of life (QoL), which may be partly attributable to their comorbid diseases. A greater understanding of the impact of comorbidities on QoL could optimize patient-centered care among older persons with AF. OBJECTIVE To assess impairment in disease-specific QoL due to comorbid conditions in older adults with AF. METHODS Patients aged ≥ 65 years diagnosed with AF were recruited from five medical centers in Massachusetts and Georgia between 2015 and 2018. At 1 year of follow-up, the Quality of Life Disease Impact Scale-for Multiple Chronic Conditions was used to provide standardized assessment of patient self-reported impairment in QoL attributable to 34 comorbid conditions grouped in 10 clusters. RESULTS The mean age of study participants (n = 1097) was 75 years and 48% were women. Overall, cardiometabolic, musculoskeletal, and pulmonary conditions were the most prevalent comorbidity clusters. A high proportion of participants (82%) reported that musculoskeletal conditions exerted the greatest impact on their QoL. Men were more likely than women to report that osteoarthritis and stroke severely impacted their QoL. Patients aged < 75 years were more likely to report that obesity, hip/knee joint problems, and fibromyalgia extremely impacted their QoL than older participants. CONCLUSIONS Among older persons with AF, while cardiometabolic diseases were highly prevalent, musculoskeletal conditions exerted the greatest impact on patients' disease-specific QoL. Understanding the extent of impairment in QoL due to underlying comorbidities provides an opportunity to develop interventions targeted at diseases that may cause significant impairment in QoL.
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Affiliation(s)
- Hawa O Abu
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA.
| | - Jane S Saczynski
- Department of Pharmacy and Health Systems Sciences, School of Pharmacy, Northeastern University, Boston, MA, USA
| | - John Ware
- John Ware Research Group, Watertown, MA, USA
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jordy Mehawej
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA
| | - Tenes Paul
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA
| | - Hamza Awad
- Departments of Community Medicine and Internal Medicine, Mercer University School of Medicine, Macon, GA, USA
| | - Benita A Bamgbade
- Department of Pharmacy and Health Systems Sciences, School of Pharmacy, Northeastern University, Boston, MA, USA
| | - Isabelle C Pierre-Louis
- Department of Pharmacy and Health Systems Sciences, School of Pharmacy, Northeastern University, Boston, MA, USA
| | - Mayra Tisminetzky
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
- Division of Geriatrics, Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Catarina I Kiefe
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Robert J Goldberg
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - David D McManus
- Division of Cardiovascular Medicine, Department of Medicine, University of Massachusetts Medical School, 55 Lake Avenue North, Worcester, MA, 01655, USA
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Fischer HF, Wahl I, Nolte S, Liegl G, Brähler E, Löwe B, Rose M. Language-related differential item functioning between English and German PROMIS Depression items is negligible. Int J Methods Psychiatr Res 2017; 26:e1530. [PMID: 27747969 PMCID: PMC6877152 DOI: 10.1002/mpr.1530] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Revised: 07/21/2016] [Accepted: 07/30/2016] [Indexed: 11/08/2022] Open
Abstract
To investigate differential item functioning (DIF) of PROMIS Depression items between US and German samples we compared data from the US PROMIS calibration sample (n = 780), a German general population survey (n = 2,500) and a German clinical sample (n = 621). DIF was assessed in an ordinal logistic regression framework, with 0.02 as criterion for R2 -change and 0.096 for Raju's non-compensatory DIF. Item parameters were initially fixed to the PROMIS Depression metric; we used plausible values to account for uncertainty in depression estimates. Only four items showed DIF. Accounting for DIF led to negligible effects for the full item bank as well as a post hoc simulated computer-adaptive test (< 0.1 point on the PROMIS metric [mean = 50, standard deviation =10]), while the effect on the short forms was small (< 1 point). The mean depression severity (43.6) in the German general population sample was considerably lower compared to the US reference value of 50. Overall, we found little evidence for language DIF between US and German samples, which could be addressed by either replacing the DIF items by items not showing DIF or by scoring the short form in German samples with the corrected item parameters reported.
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Affiliation(s)
- H Felix Fischer
- Department of Psychosomatic Medicine, Clinic for Internal Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Institute for Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Inka Wahl
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf & Schön Klinik Hamburg Eilbek, Hamburg, Germany
| | - Sandra Nolte
- Department of Psychosomatic Medicine, Clinic for Internal Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Population Health Strategic Research Centre, School of Health and Social Development, Deakin University, Melbourne, Victoria, Australia
| | - Gregor Liegl
- Department of Psychosomatic Medicine, Clinic for Internal Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Elmar Brähler
- Department of Medical Psychology and Medical Sociology, University of Leipzig, Leipzig, Germany.,Klinik und Poliklinik für Psychosomatische Medizin und Psychotherapie, Universitätsmedizin Mainz, Mainz, Germany
| | - Bernd Löwe
- Department of Psychosomatic Medicine and Psychotherapy, University Medical Center Hamburg-Eppendorf & Schön Klinik Hamburg Eilbek, Hamburg, Germany
| | - Matthias Rose
- Department of Psychosomatic Medicine, Clinic for Internal Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany.,Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, Massachusetts, USA
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Ware JE, Gandek B, Guyer R, Deng N. Standardizing disease-specific quality of life measures across multiple chronic conditions: development and initial evaluation of the QOL Disease Impact Scale (QDIS®). Health Qual Life Outcomes 2016; 14:84. [PMID: 27255462 PMCID: PMC4890258 DOI: 10.1186/s12955-016-0483-x] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2016] [Accepted: 05/06/2016] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND To document the development and evaluation of the Quality of life Disease Impact Scale (QDIS®), a measure that standardizes item content and scoring across chronic conditions and provides a summary, norm-based QOL impact score for each disease. METHODS A bank of 49 disease impact items was constructed from previously-used descriptions of health impact to represent ten frequently-measured quality of life (QOL) content areas and operational definitions successfully utilized in generic QOL surveys. In contrast to health in general, all items were administered with attribution to a specific disease (osteoarthritis, rheumatoid arthritis, angina, myocardial infarction, congestive heart failure, chronic kidney disease (CKD), diabetes, asthma, or COPD). Responses from 5418 adults were analyzed as five disease groups: arthritis, cardiovascular, CKD, diabetes, and respiratory. Unidimensionality, item parameter and scale-level invariance, reliability, validity and responsiveness to change during 9-month follow-up were evaluated by disease group and for all groups combined using multi-group confirmatory factor analysis (MGCFA), item response theory (IRT) and analysis of variance methods. QDIS was normed in an independent chronically ill US population sample (N = 4120). RESULTS MGCFA confirmed a 1-factor model, justifying a summary score estimated using equal parameters for each item across disease groups. In support of standardized IRT-based scoring, correlations were very high between disease-specific and standardized IRT item slopes (r = 0.88-0.96), thresholds (r = 0.93-0.99) and person-level scores (r ≥ 0.99). Internal consistency, test-retest and person-level IRT reliability were consistently satisfactory across groups. In support of interpreting QDIS as a disease-specific measure, in comparison with generic measures, QDIS consistently discriminated markedly better across disease severity levels, correlated higher with other disease-specific measures in cross-sectional tests, and was more responsive in comparisons of groups with better, same or worse evaluations of disease-specific outcomes at the 9-month follow-up. CONCLUSIONS Standardization of content and scoring across diseases was shown to be justified psychometrically and enabled the first summary measure of disease-specific QOL impact normed in the chronically ill population. This disease-specific approach substantially improves discriminant validity and responsiveness over generic measures and provides a basis for better understanding the relative QOL impact of multiple chronic conditions in research and clinical practice.
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Affiliation(s)
- John E. Ware
- />John Ware Research Group, 10 Wheeler Court, Watertown, MA 02472 USA
- />Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA USA
| | - Barbara Gandek
- />John Ware Research Group, 10 Wheeler Court, Watertown, MA 02472 USA
- />Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA USA
| | - Rick Guyer
- />John Ware Research Group, 10 Wheeler Court, Watertown, MA 02472 USA
| | - Nina Deng
- />Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA USA
- />Measured Progress, Dover, NH USA
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Ware JE, Gandek B, Allison J. The Validity of Disease-specific Quality of Life Attributions Among Adults with Multiple Chronic Conditions. INTERNATIONAL JOURNAL OF STATISTICS IN MEDICAL RESEARCH 2016; 5:17-40. [PMID: 27087882 PMCID: PMC4831653 DOI: 10.6000/1929-6029.2016.05.01.3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
BACKGROUND A crucial assumption underlying all disease-specific quality of life (QOL) measures, that patients can validly differentiate a specific disease in the presence of multiple chronic conditions, has not been tested using multiple methods. Our objective was to evaluate the convergent and discriminant validity of QOL attributions to specific diseases among adults with multiple chronic conditions (MCC). METHODS Adults age 18 and older (N=4,480) sampled from eight pre-identified condition groups (asthma, COPD, angina/MI with angina, congestive heart failure, diabetes, chronic kidney disease, osteoarthritis, rheumatoid arthritis) completed an Internet survey. Comorbid conditions were determined using a 35-condition checklist. Product-moment correlations were analyzed separately by pre-identified condition group using the multitrait-multimethod of construct validation, where traits were defined by 9-26 conditions and each condition was measured by two methods: disease severity rating and Disease-specific Quality of Life Impact Scale (QDIS) global rating. A third method (symptom or clinical marker) was available for the eight pre-identified conditions. Convergent validity was supported when correlations among different methods of measuring the same condition (trait) were substantial (r≥0.40). Discriminant validity was supported when correlations between the same and different methods of measuring different conditions were significantly lower than corresponding convergent correlations. RESULTS In support of convergent validity, 22 of 24 convergent correlations were substantial (r=0.38-0.84, median=0.53). In support of discriminant validity, 833 of 924 tests (90.2%) yielded significantly higher convergent than discriminant correlations across the eight pre-identified conditions. Exceptions to this pattern of results were most often observed for comorbid conditions within the same clinical area. CONCLUSIONS Collectively, convergent and discriminant test results support the construct validity of disease-specific QOL impact attributions across MCC within the eight pre-identified conditions. Noteworthy exceptions should be considered when interpreting some specific QOL impact attributions and warrant further study. Pursuit of a summary disease-specific QOL impact score standardized across MCC is recommended.
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Affiliation(s)
- John E. Ware
- University of Massachusetts Medical School, Worcester, MA
- John Ware Research Group, Watertown, MA
| | - Barbara Gandek
- University of Massachusetts Medical School, Worcester, MA
- John Ware Research Group, Watertown, MA
| | - Jeroan Allison
- University of Massachusetts Medical School, Worcester, MA
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Ware JE, Gandek B, Kulasekaran A, Guyer R. Evaluation of smoking-specific and generic quality of life measures in current and former smokers in Germany and the United States. Health Qual Life Outcomes 2015; 13:128. [PMID: 26276447 PMCID: PMC4537546 DOI: 10.1186/s12955-015-0316-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2014] [Accepted: 07/27/2015] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Health-related quality of life (QOL) surveys include generic measures that enable comparisons across conditions and measures that focus more specifically on one disease or condition. We evaluated the psychometric properties of German- and English-language versions of survey scales representing both types of measures in samples of current and former smokers. METHODS TQOLIT(™)v1 integrates new measures of smoking-specific symptoms and QOL impact attributed to smoking with generic SF-36 Health Survey measures. For purposes of evaluation, cross-sectional data were analyzed for two independent samples. Disease-free (otherwise healthy) adults ages 23-55 used a tablet to complete surveys in a clinical trial in Germany (125 current and 54 former smokers). Online general population surveys were completed in the US by otherwise healthy current and former smokers (N = 149 and 110, respectively). Evaluations included psychometric tests of assumptions underlying scale construction and scoring, score distributions, and reliability. Tests of validity included cross-sectional correlations and analyses of variance based on a conceptual framework and hypotheses for groups differing in self-reported smoking behavior (current versus former smoker, cigarettes per day (CPD)) and severity of smoking symptoms in both samples and, in the German trial only, clinical parameters of biomarkers of exposure. RESULTS Tests of scaling assumptions and internal consistency reliability (alpha = 0.71-0.79) of the smoking-specific measures were satisfactory, although ceiling effects attenuated correlations for former smokers in both samples. Correlational evidence supporting validity of smoking-specific symptom and impact measures included their substantial inter-correlation and higher correlations (than generic measures) with smoking behavior (favoring former over current groups) and CPD in both samples. In the German trial, both smoking-specific measures correlated significantly (p < 0.05) with all four biomarkers. QOL impact attributed to smoking correlated with the SF-36 mental but not physical summary measures in both samples. CONCLUSIONS German- and English-language TQOLITv1 surveys have comparable and satisfactory psychometric properties. Cross-sectional tests, including correlations with four biomarkers, support the validity of the new smoking-specific measures for use in studies of otherwise healthy smokers. Smoking-specific measures consistently performed better than generic QOL measures in all tests of validity.
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Affiliation(s)
- John E Ware
- John Ware Research Group, 10 Wheeler Court, Watertown, MA, 02472, USA.
- Department of Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01655, USA.
| | - Barbara Gandek
- John Ware Research Group, 10 Wheeler Court, Watertown, MA, 02472, USA.
- Department of Quantitative Health Sciences, University of Massachusetts Medical School, 368 Plantation Street, Worcester, MA, 01655, USA.
| | - Anuradha Kulasekaran
- British American Tobacco (Investments) Ltd., Group Research & Development, Regents Park Road, Southampton, SO15 8TL, UK.
| | - Rick Guyer
- John Ware Research Group, 10 Wheeler Court, Watertown, MA, 02472, USA.
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