Repository of Research and Investigative Information

Repository of Research and Investigative Information

Baqiyatallah University of Medical Sciences

Logistic regression models for predicting physical and mental health-related quality of life in rheumatoid arthritis patients

(2008) Logistic regression models for predicting physical and mental health-related quality of life in rheumatoid arthritis patients. Modern Rheumatology. pp. 601-608. ISSN 1439-7595

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Abstract

The aim of this work was to develop two logistic regression models capable of predicting physical and mental health related quality of life (HRQOL) among rheumatoid arthritis (RA) patients. In this cross-sectional study which was conducted during 2006 in the outpatient rheumatology clinic of our university hospital, Short Form 36 (SF-36) was used for HRQOL measurements in 411 RA patients. A cutoff point to define poor versus good HRQOL was calculated using the first quartiles of SF-36 physical and mental component scores (33.4 and 36.8, respectively). Two distinct logistic regression models were used to derive predictive variables including demographic, clinical, and psychological factors. The sensitivity, specificity, and accuracy of each model were calculated. Poor physical HRQOL was positively associated with pain score, disease duration, monthly family income below 300 US, comorbidity, patient global assessment of disease activity or PGA, and depression (odds ratios: 1.1; 1.004; 15.5; 1.1; 1.02; 2.08, respectively). The variables that entered into the poor mental HRQOL prediction model were monthly family income below 300 US, comorbidity, PGA, and bodily pain (odds ratios: 6.7; 1.1; 1.01; 1.01, respectively). Optimal sensitivity and specificity were achieved at a cutoff point of 0.39 for the estimated probability of poor physical HRQOL and 0.18 for mental HRQOL. Sensitivity, specificity, and accuracy of the physical and mental models were 73.8, 87, 83.7 and 90.38, 70.36, 75.43, respectively. The results show that the suggested models can be used to predict poor physical and mental HRQOL separately among RA patients using simple variables with acceptable accuracy. These models can be of use in the clinical decision-making of RA patients and to recognize patients with poor physical or mental HRQOL in advance, for better management.

Item Type: Article
Keywords: Rheumatoid arthritis Quality of life Prediction model disease outcomes sf-36 questionnaires disability symptoms impact care Rheumatology
Divisions:
Page Range: pp. 601-608
Journal or Publication Title: Modern Rheumatology
Journal Index: ISI
Volume: 18
Number: 6
Identification Number: https://doi.org/10.1007/s10165-008-0092-6
ISSN: 1439-7595
Depositing User: مهندس مهدی شریفی
URI: http://eprints.bmsu.ac.ir/id/eprint/6984

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