Volume 5, Issue 2 (APRIL 2006)
Payesh 2006, 5(2): 0-0 |
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Kheil Tash A, Montazeri A, Nabaei B. Factors predicting quality of life in patients with leukemia and lymphoma. Payesh 2006; 5 (2)
URL: http://payeshjournal.ir/article-1-742-en.html
URL: http://payeshjournal.ir/article-1-742-en.html
Abstract: (6287 Views)
Objective (s): With increasingly sophisticated chemotherapy regimens being prescribed the quality of life of cancer patients have become a key outcome measure. Little has been reported concerning the experience of patients with hematological malignancy receiving chemotherapy. The objectives of this study were to analyze current levels of health-related quality of life in individuals with leukemia and lymphoma and predicting some prognostic factors.
Methods: This was a cross-sectional study of quality of life carried out in the hematological clinic at Imam Khomeini Hospital in Tehran, Iran. Quality of life was measured using the SF-36 questionnaire. Then the results were analyzed using the logistic regression model.
Results: In all 94 patients were studied. The mean survival time for patients was 40.1 months (SEM = 4.3). The analysis showed that predicting factors for Physical Component Summary (PCS) scores of the SF-36 were: type of diagnosis (OR= 16.32, 95% CI= 4.03-55.71), education (OR= 0.88, 95% CI= 0.01-0.749), and gender (OR= 10.25, 95% CI= 2.65-39.6). For the Mental Component Summary (MCS) scores of the SF-36 predicting factors were: type of diagnosis (OR= 4.75, 95% CI= 1.76-12.77), education (OR= 0.13, 95% CI= 0.02-0.89) and income (OR= 5.01, 95% CI= 1.69-14.82).
Conclusion: We found that having non-aggressive disease and being low educated and male are as good prognostic factors to predict the PCS, while having high income, non-aggressive disease and low education predict better for the MCS scores.
Methods: This was a cross-sectional study of quality of life carried out in the hematological clinic at Imam Khomeini Hospital in Tehran, Iran. Quality of life was measured using the SF-36 questionnaire. Then the results were analyzed using the logistic regression model.
Results: In all 94 patients were studied. The mean survival time for patients was 40.1 months (SEM = 4.3). The analysis showed that predicting factors for Physical Component Summary (PCS) scores of the SF-36 were: type of diagnosis (OR= 16.32, 95% CI= 4.03-55.71), education (OR= 0.88, 95% CI= 0.01-0.749), and gender (OR= 10.25, 95% CI= 2.65-39.6). For the Mental Component Summary (MCS) scores of the SF-36 predicting factors were: type of diagnosis (OR= 4.75, 95% CI= 1.76-12.77), education (OR= 0.13, 95% CI= 0.02-0.89) and income (OR= 5.01, 95% CI= 1.69-14.82).
Conclusion: We found that having non-aggressive disease and being low educated and male are as good prognostic factors to predict the PCS, while having high income, non-aggressive disease and low education predict better for the MCS scores.
type of study: Descriptive |
Accepted: 2018/11/28 | Published: 2006/04/15
Accepted: 2018/11/28 | Published: 2006/04/15
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