{
    "abstract": "The cumulative live birth rate (CLBR) has been regarded as a key measure of in vitro fertilization (IVF) success after a complete treatment cycle. Women undergoing IVF face great psychological pressure and financial burden. A predictive model to estimate CLBR is needed in clinical practice for patient counselling and shaping expectations.\nThis retrospective study included 32,306 complete cycles derived from 29,023 couples undergoing IVF treatment from 2014 to 2020 at a university-affiliated fertility center in China. Three predictive models of CLBR were developed based on three phases of a complete cycle: pre-treatment, post-stimulation, and post-treatment. The non-linear relationship was treated with restricted cubic splines. Subjects from 2014 to 2018 were randomly divided into a training set and a test set at a ratio of 7:3 for model derivation and internal validation, while subjects from 2019 to 2020 were used for temporal validation.\nPredictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p\u2009=\u20090.687, p\u2009=\u20090.468, p\u2009=\u20090.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05.\nThis study provides three IVF models to predict CLBR according to information from different treatment stage, and these models have been converted into an online calculator ( https://h5.eheren.com/hcyc/pc/index.html#/home ). Internal validation and temporal validation verified the good discrimination of the predictive models. However, temporal validation suggested low accuracy of the predictive models, which might be attributed to time-associated amelioration of IVF practice.",
    "authors": [
        {
            "affiliation": "Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China.\nJiangxi Key Laboratory of Reproductive Health, Nanchang, China.",
            "firstname": "Leizhen",
            "initials": "L",
            "lastname": "Xia"
        },
        {
            "affiliation": "Department of Health Statistics, School of Public Health, China Medical University, Shenyang, China.",
            "firstname": "Shiyun",
            "initials": "S",
            "lastname": "Han"
        },
        {
            "affiliation": "Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China.\nJiangxi Key Laboratory of Reproductive Health, Nanchang, China.",
            "firstname": "Jialv",
            "initials": "J",
            "lastname": "Huang"
        },
        {
            "affiliation": "Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China.",
            "firstname": "Yan",
            "initials": "Y",
            "lastname": "Zhao"
        },
        {
            "affiliation": "Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China.",
            "firstname": "Lifeng",
            "initials": "L",
            "lastname": "Tian"
        },
        {
            "affiliation": "Columbia College of Art and Science, the George Washington University, Washington, DC, USA.",
            "firstname": "Shanshan",
            "initials": "S",
            "lastname": "Zhang"
        },
        {
            "affiliation": "Department of Child Health, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China.",
            "firstname": "Li",
            "initials": "L",
            "lastname": "Cai"
        },
        {
            "affiliation": "Department of Acupuncture, the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine, Nanchang, China. 495380513@qq.com.",
            "firstname": "Leixiang",
            "initials": "L",
            "lastname": "Xia"
        },
        {
            "affiliation": "Department of Health Statistics, School of Public Health, China Medical University, Shenyang, China. nbliu@cmu.edu.cn.",
            "firstname": "Hongbo",
            "initials": "H",
            "lastname": "Liu"
        },
        {
            "affiliation": "Reproductive Medicine Center, Jiangxi Maternal and Child Health Hospital Affiliated to Nanchang Medical College, Nanchang, China. wuqiongfang898@sina.com.",
            "firstname": "Qiongfang",
            "initials": "Q",
            "lastname": "Wu"
        }
    ],
    "conclusions": null,
    "copyrights": "\u00a9 2024. The Author(s).",
    "doi": "10.1186/s12958-024-01237-3\n10.1093/humrep/deab198\n10.1056/NEJMoa0803072\n10.1016/j.fertnstert.2021.09.015\n10.1136/bmj.i5735\n10.1093/humrep/deac152\n10.1093/humrep/dev263\n10.3389/fendo.2022.900829\n10.1186/s12967-019-2062-5\n10.1007/s10815-019-01422-z\n10.21037/tp-21-589\n10.1016/j.fertnstert.2016.12.005\n10.1038/s41598-020-79308-9\n10.1111/jog.14649\n10.1093/humrep/dez258\n10.1093/humrep/der106\n10.1007/s10815-013-0129-4\n10.1093/humrep/dev268\n10.1097/ccm.0000000000001571\n10.1016/j.fertnstert.2011.02.009\n10.1016/s0143-4004(03)00136-x\n10.1007/s10815-018-1304-4\n10.1016/j.fertnstert.2018.04.039\n10.1097/cm9.0000000000001586\n10.1186/s13048-022-01044-7\n10.3389/fendo.2022.803471\n10.1007/s10815-019-01642-3\n10.18632/aging.203282\n10.3389/fendo.2021.606231\n10.1016/s0015-0282(00)01741-6\n10.1016/j.fertnstert.2010.05.042\n10.1016/j.jmig.2019.05.011\n10.3389/fendo.2021.722655\n10.1016/j.fertnstert.2021.02.041\n10.1186/s12958-021-00862-6\n10.1210/clinem/dgab858\n10.1016/j.fertnstert.2014.10.048\n10.1093/humrep/deu189",
    "journal": "Reproductive biology and endocrinology : RB&E",
    "keywords": [
        "Cumulative live birth rate",
        "In vitro fertilization",
        "Predictive model",
        "Restricted cubic splines"
    ],
    "methods": null,
    "publication_date": "2024-06-08",
    "pubmed_id": "38849798\n34601605\n19144939\n34674824\n27852632\n35866894\n26466912\n36093101\n31547822\n30790147\n35800265\n28108009\n33431900\n33398918\n31960915\n21558332\n24202826\n26498177\n26771782\n21411078\n14559024\n30206748\n30196963\n34091521\n36209186\n35185793\n31797243\n34273144\n33995268\n11239536\n20580357\n31146029\n34925227\n33812651\n34893087\n34850010\n25497445\n25073975",
    "results": "Predictors of pre-treatment model included female age (non-linear relationship), antral follicle count (non-linear relationship), body mass index, number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, tubal factor, male factor, and scarred uterus. Predictors of post-stimulation model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), number of previous IVF attempts, number of previous embryo transfer failure, type of infertility, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. Predictors of post-treatment model included female age (non-linear relationship), number of oocytes retrieved (non-linear relationship), cumulative Day-3 embryos live-birth capacity (non-linear relationship), number of previous IVF attempts, scarred uterus, stimulation protocol, as well as endometrial thickness, progesterone and luteinizing hormone on trigger day. The C index of the three models were 0.7559, 0.7744, and 0.8270, respectively. All models were well calibrated (p\u2009=\u20090.687, p\u2009=\u20090.468, p\u2009=\u20090.549). In internal validation, the C index of the three models were 0.7422, 0.7722, 0.8234, respectively; and the calibration P values were all greater than 0.05. In temporal validation, the C index were 0.7430, 0.7722, 0.8234 respectively; however, the calibration P values were less than 0.05.",
    "title": "Predicting personalized cumulative live birth rate after a complete in vitro fertilization cycle: an analysis of 32,306 treatment cycles in China.",
    "xml": "<Element 'PubmedArticle' at 0x7885048c6cf0>"
}