Predicting live birth chances for women with multiple consecutive failing IVF cycles: a simple and accurate prediction for routine medical practice

Table 2 The main predictive data from the logistic regression model

Effects	Logistic Model				Linear Simplified Model
	OR	95% CI		P	Incr	95% CI		P
Intercept	0.044	0.006;	0.392	0.004	0.045	0;	0.350	0.047
Women age	0.868	0.782;	0.964	0.008	−0.023	−0.039;	−0.006	0.009
FSH < 10 IU/L	4.222	1.267;	14.077	0.019	0.200	0.039;	0.361	0.016
Male Infertility Etiology (MI)	3.862	1.097;	13.595	0.035	0.172	0.011;	0.334	0.038
occurrence of at least one GS (OGS)	3.099	1.395;	6.884	0.005	0.174	0.047;	0.302	0.008
Mean number of GQE (MQE)	2.422	1.322;	4.437	0.004	0.168	0.064;	0.263	0.003

Proportion of variability due to covariates R²=0.2955; ROC curve AUC (C) = 0.76 (95% CI [0.71–0.81]) and the simplified model (from an ordinary least squares procedure suited to binary data). OR: odds ratio; CI: confidence interval. Logistic model coefficients can be assimilated to OR, and linear model coefficients to incremental values (Incr). For interpreting OR and Incr, age, number of cycles with at least one sac, and mean number are continuous values, while FSH<10 IU/L and Male infertility are binary values.

ISSN: 1477-7827