Factors associated with livebirth in couples undergoing their first in vitro fertilization cycle: An internally validated prediction model.

OBJECTIVE

The aim of the study is to create a new model to predict successful outcome in assisted reproductive techniques.

MATERIALS AND

METHODS

A retrospective cohort study was conducted in tertiary fertility center between 2010 and 2017. Nulliparous women younger than 45 years-old undergoing in vitro fertilization/intracytoplasmic sperm injection (IVF/ICSI) for the first time were included; frozen embryo transfers, canceled induction cycles, freeze-all cycles were excluded. Two prediction models were built using multivariate logistic regression with a subset of the dataset and then were internally validated using bootstrapping methods.

RESULTS

Four hundred eighty eight women were included with 136 (27.9%) live births. The basal model was built using variable age, antral follicle count (AFC), and basal luteinizing hormone (LH) levels. Age over 37 years [odds ratio (OR): 0.07, 95% confidence interval (CI): 0.00-0.36] and AFC below 5 (OR: 0.15, 95% CI: 0.02-0.53) was associated with poorer outcomes whereas an LH level above 6 mIU/mL (OR: 2.24, 95% CI: 1.27-3.94) was associated with better outcomes. Optimism adjusted area under the curve (AUC) of this model was 0.68 (95% CI: 0.62-0.74). Combined model in addition to basal model variables included the length of induction cycle, the endometrial thickness at the day of transfer, grade and count of the transferred embryo. Cycles lasting more than ten days (OR: 2.23, 95% CI: 1.17-4.42), an endometrial thickness greater than 9 mm (OR: 2.07, 95% CI: 1.00-4.53) were associated with better outcomes. Optimism adjusted AUC of this model was 0.76 (95% CI: 0.70-0.81). Calibration of both models was good according to Hosmer Lemeshow test (p=0.979 and p=0.848, respectively).

CONCLUSION

This internally validated prediction model has good calibration and can be used predicting outcomes in first time IVF/ICSI cycles with modest sensitivity.