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      A Novel Nomogram for Individualized Gonadotropin Starting Dose in GnRH Antagonist Protocol

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          Abstract

          Controlled ovarian stimulation (COS) is one of the most vital parts of in vitro fertilization-embryo transfer (IVF-ET). At present, no matter what kinds of COS protocols are used, clinicians have to face the challenge of selection of gonadotropin starting dose. Although several nomograms have been developed to calculate the appropriate gonadotropin starting dose in gonadotropin releasing hormone (GnRH) agonist protocol, no nomogram was suitable for GnRH antagonist protocol. This study aimed to develop a predictive nomogram for individualized gonadotropin starting dose in GnRH antagonist protocol. Single-center prospective cohort study was conducted, with 198 women aged 20-45 years underwent IVF/intracytoplasmic sperm injection (ICSI)-ET cycles. Blood samples were collected on the second day of the menstrual cycle. All women received ovarian stimulation using GnRH antagonist protocol. Univariate and multivariate analysis were performed to identify predictive factors of ovarian sensitivity (OS). A nomogram for gonadotropin starting dose was developed based on the multivariate regression model. Validation was performed using concordance statistics and bootstrap resampling. A multivariate regression model based on serum anti-Müllerian hormone (AMH) level, antral follicle count (AFC), and body mass index (BMI) was developed and accounted for 59% of the variability of OS. An easy-to-use predictive nomogram for gonadotropin starting dose was established with excellent accuracy. The concordance index (C-index) of the nomogram was 0.833 (95% CI, 0.829-0.837). Internal validation using bootstrap resampling further showed the good performance of the nomogram. In conclusion, gonadotropin starting dose in antagonist protocol can be predicted precisely by a novel nomogram.

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          Most cited references25

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          Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

          The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model. Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects. We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction. Random samples with a size between n = 572 and n = 9165 were drawn from a large data set (GUSTO-I; n = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable. Independent performance was determined on the remaining subjects. Performance measures included discriminative ability, calibration and overall accuracy. We found that split-sample analyses gave overly pessimistic estimates of performance, with large variability. Cross-validation on 10% of the sample had low bias and low variability, but was not suitable for all performance measures. Internal validity could best be estimated with bootstrapping, which provided stable estimates with low bias. We conclude that split-sample validation is inefficient, and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model.
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            Association between the number of eggs and live birth in IVF treatment: an analysis of 400 135 treatment cycles.

            While live birth is the principal clinical outcome following in vitro fertilization (IVF) treatment, the number of eggs retrieved following ovarian stimulation is often used as a surrogate outcome in clinical practice and research. The aim of this study was to explore the association between egg number and live birth following IVF treatment and identify the number of eggs that would optimize the IVF outcome. Anonymized data on all IVF cycles performed in the UK from April 1991 to June 2008 were obtained from the Human Fertilization and Embryology Authority (HFEA). We analysed data from 400 135 IVF cycles. A logistic model was fitted to predict live birth using fractional polynomials to handle the number of eggs as a continuous independent variable. The prediction model, which was validated on a separate HFEA data set, allowed the estimation of the probability of live birth for a given number of eggs, stratified by age group. We produced a nomogram to predict the live birth rate (LBR) following IVF based on the number of eggs and the age of the female. The median number of eggs retrieved per cycle was 9 [inter-quartile range (IQR) 6-13]. The overall LBR was 21.3% per fresh IVF cycle. There was a strong association between the number of eggs and LBR; LBR rose with an increasing number of eggs up to ∼15, plateaued between 15 and 20 eggs and steadily declined beyond 20 eggs. During 2006-2007, the predicted LBR for women with 15 eggs retrieved in age groups 18-34, 35-37, 38-39 and 40 years and over was 40, 36, 27 and 16%, respectively. There was a steady increase in the LBR per egg retrieved over time since 1991. The relationship between the number of eggs and live birth, across all female age groups, suggests that the number of eggs in IVF is a robust surrogate outcome for clinical success. The results showed a non-linear relationship between the number of eggs and LBR following IVF treatment. The number of eggs to maximize the LBR is ∼15.
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              Anti-Mullerian hormone (AMH) as a predictive marker in assisted reproductive technology (ART).

              In women, anti-Müllerian hormone (AMH) levels may represent the ovarian follicular pool and could be a useful marker of ovarian reserve. The clinical application of AMH measurement has been proposed in the prediction of quantitative and qualitative aspects in assisted reproductive technologies (ART). In men AMH is secreted in both the serum and seminal fluid. Its measurement may be useful in clinical evaluation of the infertile male. The PubMed database was systematically searched for studies published until the end of January 2009, search criteria relevant to AMH, ovarian reserve, ovarian response to gonadotrophin stimulation, spermatogenesis and azoospermia were used. AMH seems to be a better marker in predicting ovarian response to controlled ovarian stimulation than age of the patient, FSH, estradiol and inhibin B. A similar performance for AMH and antral follicular count has been reported. In clinical practice, AMH measurement may be useful in the prediction of poor response and cycle cancellation and also of hyper-response and ovarian hyperstimulation syndrome. In the male, the wide overlap of AMH values between controls and infertile men precludes this hormone from being a useful marker of spermatogenesis. As AMH may permit the identification of both the extremes of ovarian stimulation, a possible role for its measurement may be in the individualization of treatment strategies in order to reduce the clinical risk of ART along with optimized treatment burden. It is fundamental to clarify the cost/benefit of its use in ovarian reserve testing. Regarding the role of AMH in the evaluation of infertile men, AMH as single marker of spermatogenesis does not seem to reach a satisfactory clinical utility.
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                Author and article information

                Contributors
                Journal
                Front Endocrinol (Lausanne)
                Front Endocrinol (Lausanne)
                Front. Endocrinol.
                Frontiers in Endocrinology
                Frontiers Media S.A.
                1664-2392
                14 September 2021
                2021
                : 12
                : 688654
                Affiliations
                [1] 1Reproductive Medicine Center, The First Affiliated Hospital, Sun Yat-sen University , Guangzhou, China
                [2] 2Guangdong Provincial Key Laboratory of Reproductive Medicine , Guangzhou, China
                [3] 3Department of Obstetrics & Gynecology, National University Hospital , Singapore, Singapore
                Author notes

                Edited by: Panagiotis Drakopoulos, University Hospital Brussels, Belgium

                Reviewed by: Syeda Sadia Fatima, Aga Khan University, Pakistan; Arezoo Arabipoor, Royan Institute, Iran

                *Correspondence: Yuan Yuan, yuanyuan3@ 123456mail.sysu.edu.cn ; Yanwen Xu, xuyanwen@ 123456live.cn

                †These authors have contributed equally to this work and share first authorship

                This article was submitted to Reproduction, a section of the journal Frontiers in Endocrinology

                Article
                10.3389/fendo.2021.688654
                8476945
                34594300
                6b86f2e5-abba-4b63-b553-fb3fedd86205
                Copyright © 2021 Li, Duan, Yuan, Cai, Xu and Yuan

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 31 March 2021
                : 25 August 2021
                Page count
                Figures: 1, Tables: 3, Equations: 1, References: 25, Pages: 7, Words: 3582
                Categories
                Endocrinology
                Original Research

                Endocrinology & Diabetes
                ivf,icsi,gnrh antagonist protocol,gonadotropin starting dose,ovarian sensitivity,nomogram

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