MO867: Confirmatory Factor Analysis and Computer Adaptive Testing System Prototype Based on Multidimensional Item Response Theory of KDQOL-36 Among a Large Sample of Spanish Dialysis Patients
Authors: Neri Luca , Ion Titapiccolo Jasmine , Bellocchio Francesco , Rincon Bello Abraham , Lopez Herradon Ana , Cerezo Cristina , Berdud-Godoy Isabel , Cebrián Andrada Clarencio , Eva Baró Salvador Maria , Gervasoni Federica , Ramos Sanchez Rosa , Stuard Stefano 
Published: May 2022

Abstract

BACKGROUND AND AIMS
The Kidney Disease Quality of Life (KDQOL™-36) is widely used to assess the quality of life of dialysis patients worldwide. It combines disease-specific and generic scales capturing unique facets of patients’ adaptation to the physical and mental burden of renal disease and dialysis treatment. the KDQOL™-36 psychometric properties and cross-national validation have been subject to intense review in latest years suggesting mixed replicability in different populations. Furthermore, its length may hamper its wider use in clinical practice as respondent burden may be substantial if used longitudinally within continuous quality improvement programs. Therefore, we sought to evaluate its measurement properties and develop an item response theory model enabling personalized survey administration while maximizing measurement efficiency.

METHOD
This is a retrospective, observational analysis of Patient-Reported Outcomes Measures (PROM) collected in Spanish NephroCare clinics during 2019 as part of a continuous quality improvement program launched by the country medical director of Spain. We used Multidimensional Item Response Theory (MIRT) models to confirm the theoretical factor structure underlying the measurement model of KDQOL™-36. MIRT extends classical IRT in that it allows complex factor structures in the multifactorial space. A critical advantage of scoring systems based on MIRT models over classical test theory models is the ability to personalize survey administration based on patient's characteristics and previous responses, reduction of measurement error, objective calibration, evaluation of test and item bias, greater accuracy in the assessment of change due to therapeutic intervention, and evaluation of model and person fit. We specified 4 competitive theoretical models for the SF-12 and the disease-specific KDQOL items (Figure 1). First, we fitted a unidimensional model, to exclude that one single factor could explain the response pattern of the questionnaire. Second, we tested a two-factor (or three-factor) orthogonal model for the SF-12 (and disease-specific KDQOL) to account for the standard scoring structure of the KDQOL™-36 questionnaire. Third, we tested the hypothesis of correlated two-factor (or three-factor) structure. Fourth, we tested a bifactor model structure, which accounts for a general HRQOL latent construct as well as lower order dimensions tapping specific dimensions of health. We expect the bifactor model would capture the pleiotropic effect of ESKD on patients’ life adjustment. We compared model fit with RMSEA, CFI and TLI statistics. For illustrative purposes, we simulated MIRT-based adaptive testing using different Delta Thetas as stopping rules to assesses measurement efficiency for the SF-12 component of the questionnaire.

RESULTS
Among patients completing the survey in the 2019 ePROM Spanish wave, 1838 (80.6%) dialysis prevalent patients met the inclusion criteria for the present analysis. Mean age was 68.8 ± 14.4, 60% were men, 65% had an arteriovenous fistula, and 66% were on HDF.
For both generic and disease-specific KDQOL-36 components, the bifactor model significantly improved empirical fit (Figure 1). Despite slightly inferior compared with the bifactor model solutions, a simpler correlated second-order factor solution showed acceptable model fit. CAT simulation of the SF-12 showed reduction in the amount of administered item while preserving measurement reliability (Figure 2).

CONCLUSION
As previously reported, a correlated two factor structure and three-factor structure for the SF-12 and disease-specific KDQOL, respectively, showed acceptable fit to the observed response pattern. However, a bifactor model structure improved model fit. CAT simulation based on delta theta rules for the SF-12 questionnaire demonstrated promising results as an item selection strategy.