Analysis of ectopic pregnancy data using marginal and conditional models.
This work is motivated by a longitudinal study of women and their ectopic pregnancy outcomes in Lund, Sweden. In this article, we review and apply the Liang-Zeger methodology to the Lund ectopic pregnancy data set. We further analyse the ectopic pregnancy data using conditional modelling approaches suggested by Rosner and Bonney. From the Lund ectopic pregnancy data, we learned that PID is the strongest predictor of subsequent development of ectopic pregnancy and that there is a monotone relationship between PID severity and ectopic pregnancy. We also learned that the presence of mycoplasma from lower or upper genital tract sites at index laparoscopy is also a strong predictor of ectopic pregnancy. Other correlates of ectopic pregnancy include age at pregnancy and history of gynaecologic surgery.
Hadgu
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A
Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
Koch
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Westrom
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L
D000293:Adolescent; D000328:Adult; D016009:Chi-Square Distribution; D002648:Child; D015331:Cohort Studies; D005260:Female; D005831:Genital Diseases, Female / Q000150:complications / Q000175:diagnosis; D006801:Humans; D010535:Laparoscopy; D016015:Logistic Models; D008137:Longitudinal Studies; D015233:Models, Statistical; D009175:Mycoplasma Infections / Q000150:complications / Q000175:diagnosis; D000292:Pelvic Inflammatory Disease / Q000150:complications / Q000175:diagnosis; D011247:Pregnancy; D011256:Pregnancy Outcome; D011271:Pregnancy, Ectopic / Q000209:etiology; D011446:Prospective Studies; D012044:Regression Analysis; D012307:Risk Factors