Volume 25, Issue 9 (12-2018)
RJMS 2018, 25(9): 38-46 |
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Nademi M, Rasekhi A, Moini A. Cumulative Logit Model in Endometriosis Risks Analysis and its Severity. RJMS 2018; 25 (9) :38-46
URL: http://rjms.iums.ac.ir/article-1-4520-en.html
URL: http://rjms.iums.ac.ir/article-1-4520-en.html
Tarbiat Modares University, Tehran, Iran , rasekhi@modares.ac.ir
Abstract: (3223 Views)
Background: Endometriosis is one of the prevalent chronic diseases in women that causes infertility and other problems. Since severity of this disease is expressed in ordinal scale, the aim of this study is to analyze risk factors and progress of the disease by ordinal logistic regression and cumulative logit model.
Methods: In this cross-sectional study, we studied infertile women that referred to two infertility clinics. Based on laparoscopy results, the severity of endometriosis was divided into three levels, control (without disease), mild disease (stages I and II of the disease) and severe disease (stages III and IV of the disease), and cumulative logit model was used to study risk factors related to endometriosis. Proportional odds for each significant variable, test of parallel lines and Area Under Curve (AUC) were found. Significance level was set at 0.05 and the analysis was done by R 3.4.0
Results: Cumulative logit model showed that family history, Body Mass Index (BMI), age, dyspareunia, contraceptive use, duration of menstrual pattern, amount of menstrual bleeding, and pelvic pain were significant. Among these factors, the effects of family history, pelvic pain, dyspareunia and amount of menstrual bleeding were noticeable. The AUC was 0.79 which showed predictive power of the model.
Conclusion: Any type of endometriosis could be predicted using ordinal regression model better than logistic regression. This model has more application and better interpretation and besides incidenc, shows progress of the diseases.
Methods: In this cross-sectional study, we studied infertile women that referred to two infertility clinics. Based on laparoscopy results, the severity of endometriosis was divided into three levels, control (without disease), mild disease (stages I and II of the disease) and severe disease (stages III and IV of the disease), and cumulative logit model was used to study risk factors related to endometriosis. Proportional odds for each significant variable, test of parallel lines and Area Under Curve (AUC) were found. Significance level was set at 0.05 and the analysis was done by R 3.4.0
Results: Cumulative logit model showed that family history, Body Mass Index (BMI), age, dyspareunia, contraceptive use, duration of menstrual pattern, amount of menstrual bleeding, and pelvic pain were significant. Among these factors, the effects of family history, pelvic pain, dyspareunia and amount of menstrual bleeding were noticeable. The AUC was 0.79 which showed predictive power of the model.
Conclusion: Any type of endometriosis could be predicted using ordinal regression model better than logistic regression. This model has more application and better interpretation and besides incidenc, shows progress of the diseases.
Type of Study: Research |
Subject:
Gynecology
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