Development of a Predictor Model for Quality of Life in Cancer Patients with Adverse Drug Reactions due to Cancer Chemotherapy

Khandelwal, Smita and Bairy, Laxminarayana K and Vidyasagar, MS and Kamath, Asha and Gonsalves, James and Chogtu, Bharti (2016) Development of a Predictor Model for Quality of Life in Cancer Patients with Adverse Drug Reactions due to Cancer Chemotherapy. Journal of Applied Pharmaceutical Science, 6 (5). pp. 22-28. ISSN 2231-3354

[img] PDF
DisplayPdf.pdf - Published Version
Restricted to Registered users only

Download (796kB) | Request a copy

Abstract

Cancer is one of the leading causes of morbidity and mortality worldwide. There are various detrimental symptoms experienced by a cancer patient due to the disease and the undergoing treatment which adversely affects the Quality of Life (QOL) in these patients. Therefore, QOL and its evaluation have turned out to be progressively vital in the health care system. Hence, the aim of our study was to develop a predictor model to predict the QOL in cancer patients receiving chemotherapy. The study was carried out in the Department of Radiotherapy and Oncology, Kasturba hospital, Manipal, a tertiary care hospital. Predictor model was developed to predict the Quality of Life Scores (QOLS) using multivariate regression analysis. A total of 387 patients participated in the study. Mean age of the patients was 50.85 ± 11.82 years (95% CI, 49.66-52.03). In our study, 16.54% had poor global health status/QOL, 72.35% had average and 11.11% had a high global health status/QOL. A significant difference was found in the QOLS based on the age group, site of cancer, drugs used in treatment of cancer, age as a predisposing factor and organ system affected due to ADRs (respiratory system, sensory system, skin and appendages). In the predictor model, the Coefficient of determination R-square (R2) was found to be 0.3267 indicating that 32.67% of the variation in the ‘quality of life score’ is explained by the independent variables included in the model. The F (45, 341) = 3.67, p < 0.001 indicating the overall significance of the regression model. Thus, the study showed that there are various predictors that can assess the QOL in cancer patients which can further serve as a guide to implement timely interventions to improve patients QOL.

Item Type: Article
Uncontrolled Keywords: Quality of life; Chemotherapy; Tertiary care hospital; Multivariate regression; Predictor model
Subjects: Medicine > KMC Manipal > Community Medicine
Medicine > MMMC Manipal > Pharmacology
Medicine > MMMC Manipal > Physiology
Medicine > KMC Manipal > Pharmacology
Medicine > KMC Manipal > Radiotherapy and Oncology
Depositing User: KMC Library
Date Deposited: 03 Jun 2016 09:19
Last Modified: 03 Jun 2016 09:19
URI: http://eprints.manipal.edu/id/eprint/146262

Actions (login required)

View Item View Item