Jiaying Fan1, Kang Qin2, Kuanrong Li2, Xiaojun Li2, Qingsheng Huang2, Yunsheng Liao1, Huiying Liang2, Jingying Xie1, Yan Yang1, Qingfeng Li3. 1. Department of Gynecology and Obstetrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Guangzhou, 510120, China. 2. Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China. 3. Department of Gynecology and Obstetrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Guangzhou, 510120, China. liqingfeng@gwcmc.org.
Abstract
OBJECTIVE: To examine whether a modified endometriosis fertility index (EFI) can better predict the rate of pregnancy without assisted reproductive technologies (ART) after laparoscopic surgery in infertile Chinese women with endometriosis. METHODS: 564 infertile women undergoing laparoscopy for endometriosis were retrospectively collected from January 2014 to December 2018. 472 patients were used to modify the EFI based on new, optimal cutoffs for its predictor variables. The predictive accuracy of the modified EFI was examined in the other 92 patients. RESULTS: Among the patients for the EFI modification, the multivariable Cox regression results showed that historical factors made more contribution in predicting non-ART pregnancy rate than surgical factors both in modified EFI (C-index: historical factors 0.617 vs surgical factors 0.558) and original EFI (C-index: historical factors 0.600 vs surgical factors 0.549). No significant relationship between the prior pregnancy and post-operative non-ART pregnancy rates was detected by both modified EFI and original EFI (p = 0.530 and 0.802, respectively). To assess the predictive effect of modified EFI, the two versions of modified EFI not only had higher predictive accuracy (C-index: 0.627 and 0.632) for non-ART pregnancy rates than that of the original EFI (C-index: 0.602) in the patients undergoing surgery during 2014-2017, but also higher than that of the original EFI (C-index: 0.638 and 0.612 vs 0.560) in the externally validated population in 2018. CONCLUSIONS: A modified EFI based on population-specific optimal cutoffs and weights might be more suitable for estimating the rate of non-ART pregnancy after laparoscopic surgery in infertile women with endometriosis.
OBJECTIVE: To examine whether a modified endometriosis fertility index (EFI) can better predict the rate of pregnancy without assisted reproductive technologies (ART) after laparoscopic surgery in infertile Chinese women with endometriosis. METHODS: 564 infertile women undergoing laparoscopy for endometriosis were retrospectively collected from January 2014 to December 2018. 472 patients were used to modify the EFI based on new, optimal cutoffs for its predictor variables. The predictive accuracy of the modified EFI was examined in the other 92 patients. RESULTS: Among the patients for the EFI modification, the multivariable Cox regression results showed that historical factors made more contribution in predicting non-ART pregnancy rate than surgical factors both in modified EFI (C-index: historical factors 0.617 vs surgical factors 0.558) and original EFI (C-index: historical factors 0.600 vs surgical factors 0.549). No significant relationship between the prior pregnancy and post-operative non-ART pregnancy rates was detected by both modified EFI and original EFI (p = 0.530 and 0.802, respectively). To assess the predictive effect of modified EFI, the two versions of modified EFI not only had higher predictive accuracy (C-index: 0.627 and 0.632) for non-ART pregnancy rates than that of the original EFI (C-index: 0.602) in the patients undergoing surgery during 2014-2017, but also higher than that of the original EFI (C-index: 0.638 and 0.612 vs 0.560) in the externally validated population in 2018. CONCLUSIONS: A modified EFI based on population-specific optimal cutoffs and weights might be more suitable for estimating the rate of non-ART pregnancy after laparoscopic surgery in infertile women with endometriosis.
Authors: Dominique de Ziegler; Paul Pirtea; Marie Carbonnel; Marine Poulain; Ettore Cicinelli; Carlo Bulletti; Konstantinos Kostaras; George Kontopoulos; David Keefe; Jean Marc Ayoubi Journal: Best Pract Res Clin Endocrinol Metab Date: 2018-11-03 Impact factor: 4.690
Authors: Christel Meuleman; Carl Tomassetti; Albert Wolthuis; Ben Van Cleynenbreugel; Annouschka Laenen; Freddy Penninckx; Ignace Vergote; André DʼHoore; Thomas DʼHooghe Journal: Ann Surg Date: 2014-03 Impact factor: 12.969
Authors: G A J Dunselman; N Vermeulen; C Becker; C Calhaz-Jorge; T D'Hooghe; B De Bie; O Heikinheimo; A W Horne; L Kiesel; A Nap; A Prentice; E Saridogan; D Soriano; W Nelen Journal: Hum Reprod Date: 2014-01-15 Impact factor: 6.918