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ORIGINAL ARTICLE
Year : 2019  |  Volume : 3  |  Issue : 2  |  Page : 77-83

Development and validation of a nomogram for predicting the probability of live birth in infertile women


1 Reproductive Medicine Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, Xinjiang, China
2 Center of Statistics and Information, The First Affiliated Hospital of Xinjiang Medical University, Urumqi 830054, Xinjiang, China
3 Department of Clinical Sciences and International Public Health, Liverpool School of Tropical Medicine, University of Liverpool, Liverpool L69 3BX, United Kingdom

Correspondence Address:
Prof Xiao-Lin La
Department of Reproductive Medicine, The First Affiliated Hospital of Xinjiang Medical University, 137 Liyushan Road, Urumqi 830054
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2096-2924.262388

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Objective: To develop a nomogram to predict the probability of live birth on the basis of the association of patient characteristics in subfertile individuals or couples. Methods: A retrospective study was conducted from January 2014 to December 2015. A nomogram was built from a training cohort and tested on an independent validation cohort. A total of 2,257 patients who had undergone their first nondonor cycle of in vitro fertilization (IVF) (including intracytoplasmic sperm injection) were randomly split 2:1 into training (n = 1,527) and validation (n = 730) cohorts. Results: There were no statistically significant differences in the patients' baseline and cycle characteristics between the training and validation cohorts. On multiple logistic regression analysis, female age, antral follicle count, tubal factor, anovulation, ethnicity, unexplained fertility, and male factor were significantly associated with live birth. The nomogram had a C-index of 0.700 (95% confidence interval [CI]: 0.698–0.701) in the training cohort and 0.684 (95% CI: 0.681–0.687) in the validation cohort. Conclusions: Our nomogram can predict the probability of live birth for infertile women and can be used to guide clinicians and couples to decide on an IVF treatment option.


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