ABSTRACT
Background: Adverse drug reactions are common with multidrug therapy in tuberculosis, if detected early can improve patient compliance and prevent emergence of resistance.Methods: A prospective observational study as a part of Pharmacovigilance Program under Central Drugs Standard Control Organisation was conducted in Kasturba hospital, Manipal to collect adverse drug reactions (ADR). Data of patients reported with antitubercular treatment (ATT) related ADRs from September 2012 to August 2013 was evaluated for patient demography, type of tuberculosis, ATT regimen, organ/ system affected and time of onset of ADR. ADRs were then subjected to causality assessment as per WHO scale.Results: A total of 65 ADRs were reported in 60 patients during the study period, of which 46.7% were in males and 53.3% in females. 85% of ADRs were reported in patients with pulmonary tuberculosis. 77% of ADRs were observed with daily regimen. Common ADRs were hepatitis (40%), gastritis (15%), skin reactions (15%), peripheral neuropathy (14%), gout (6%) and nephritis (3%). Median duration for the onset of ADR was 31 days each for hepatitis, gout, nephritis and 20, 11, 9 days for gastritis, peripheral neuropathy and skin reactions respectively. As per causality assessment, 80% of ADRs were assigned “possible”, 11% “probable” and 9% “certain”. As per severity scale 27.7% of ADR were severe, 36.9% were moderate.Conclusions: Early detection and management of ADRs is vital for the success of ATT and patient adherence.
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.