Member's paper - Kidney Health Education and Research Group

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Abstract
Oladapo Ekundayo1, Nathaniel Edwards1, Aarushi Bansal1, Abeera Ali1, Evan Tang1, Allen Xu 1, Punithan Thiagalingam1, Marta Novak2, Istvan Mucsi1,
2018
Canadian Society of Nephrology




Full Abstract
Background: Quality of life is a complex construct influenced by sociodemographic, clinical and psycho-social factors. Patient reported outcome measures (PROMs) assess the illness experience from the patient perspective. Although they improve the completeness of the assessment of patients with chronic medical conditions, they are not used routinely in clinical practice. The Patient Reported Outcomes Measurement Information System (PROMIS) project has developed generalizable and universal PROMs. There has been little research to assess the relative contribution of clinical, socio-demographic and PROM variables to explaining health related quality of life in advanced chronic kidney disease (CKD). Objective: To assess if adding PROMIS? domains will increase the explanatory power of models predicting quality of life of patients with advanced CKD. Methods: This cross-sectional analysis of a cohort study involved patients with advanced CKD (dialysis and post-transplant) recruited from two hospitals in Toronto. The depression, physical function, pain, sleep and fatigue domains of the PROMIS-57 questionnaire (exposure) were completed electronically. Socio-demographic and clinical variables were collected from medical records. The EuroQoL (ED-5Q-5L) was used to measure of quality of life (outcome). Linear regression models were fitted with expanding sets of co-variables to detect the effect of the PROMIS domains on predicting quality of life. Results: 339 patients were recruited into the study. Mean (SD) age was 56 (17) years with 58% males and 50% Caucasians. The ED-5Q-5L scores ranged from 0.12 to 0.9. The model that included socio-demographic variables only (age, gender, ethnicity, marital status, education, income) explained only 5% of the variance (adjusted R2=0.05). When clinical factors (renal replacement modality, comorbidities, hemoglobin and albumin levels) were added, the adjusted R2 was 0.17. Addition of the PROMIS domains (pain, physical function, depression, sleep and fatigue) increased variance prediction to 63% (Adjusted R2 = 0.63). Predicted values from the final model showed strong correlation with measured EQ-5D-5L scores (r=0.805, p<0.001). Conclusion: The PROMIS domains provide important additional information about quality of life in patients with advanced CKD . Further research is needed to assess if the PROMIS domains predict additional outcomes (eg. mortality) above and beyond clinical and socio-demographic variables.

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