Leading Clinical Journal Article Shows That New and Briefer Disease-specific Quality of life (QOL) Measures Are Also More Clinically Valid
WATERTOWN, MA, March 21, 2019 – JWRG’s efforts to improve disease-specific health-related QOL measures by broadening item content, strengthening psychometric methods and maintaining 1-minute response times can also make QOL measures more valid and useful clinically, according to a study of patients with chronic kidney disease (CKD) published today in the Journal of the American Society of Nephrology (JASN). Overall, compared with currently-used KDQOL-36 CKD-specific and generic SF-12 measures, new 6-item and computerized adaptive test (CAT) summaries of CKD-specific QOL impact performed better across multiple tests of clinical validity. New CAT surveys were more efficient than fixed-length surveys and were the only measures better in every clinical test.
As Dr. John Ware, JWRG’s Founder and Chief Science Officer, noted in his comments to the American Society of Nephrology “Quality of life is the most important outcome to patients, and the computer adaptive survey pays attention to a patient’s answers, saves time, and doesn’t ask questions that are irrelevant to that individual patient. This research brings us closer to measures of quality of life that are specific to kidney disease and could meaningfully inform the care of individual patients.”
The JASN study included 485 CKD patients (non-dialysis Stages 3-5, on dialysis, post-transplant) from 12 sites across four states. JWRG researchers collaborated with researchers at Tufts Medical Center to compare JWRG’s approach to CKD-specific health-related quality of life measurement with currently-used KDQOL-36 CKD-specific and generic SF-12 survey measures. The new approach summarized QOL impact attributed to CKD across six QOL domains in a single scale score from six-item (fixed-length) and computerized adaptive test (CAT) forms.
Results from four independent tests of CKD clinical status and clinician assessment of CKD-specific change, as well as the presence and number of comorbid conditions, were documented. The new fixed-length and CAT forms consistently discriminated better in terms of measurement variances accounted for by group mean differences by two-fold over KDQOL-36 in head-to-head comparisons with three CKD-specific (Burden, Effects, and Symptoms/Problems) and generic SF-12 physical and mental summary measures.
The next step in the evolution of disease-specific patient-reported health-related QOL measurement has already been taken with further improvements in breadth of QOL content (e.g., adding measures of disease-specific physical functioning), the standardization of survey content and scoring across chronic diseases and the norming of QOL impact in the US chronically-ill population, using the Quality of Life Disease Impact Scale (QDIS) for each of nine diseases including CKD. Clinical validation results published by JASN for a prototype of the QDIS show that JWRG innovations are on the right track toward filling conceptual and methodological gaps between disease-specific symptoms and other effects that do not measure quality of life and generic QOL measures that do not measure disease-specific outcomes.
For more information, see Studies Examine Ways to Assess Quality of Life in Patients with Kidney Disease.
The authors, JE Ware, M Richardson, KB Meyer and B Gandek, acknowledge the National Kidney Foundation for encouraging participants in its Kidney Early Evaluation Program to complete online questionnaires enabling development of the new measures, Tufts Medical Center Division of Nephrology members for valuable comments on study design and recruitment of patients, and the staff and medical directors of Dialysis Clinic, Inc.. Brigham and Women’s Hospital Division of Nephrology and others named in the article for study recruitment, data collection, and management.
The Functional Health Computer Adaptive Test in Chronic Kidney Disease study was funded by the National Institutes of Health (co-investigators: J Ware and K Meyer). A research grant donation from the Amgen Foundation (J Ware) supported project planning and data analysis. John Ware Research Group and Tufts Medical Center also supported data analysis and reporting of this validation study out of their own research funds.