Huiyu Xu1, Yuan Wei2, Rui Yang1, Guoshuang Feng3, Wenhao Tang4, Hongxia Zhang1, Yilei He1, Ying Feng1, Rong Li5, Jie Qiao1. 1. Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China; Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Beijing 100191, China; National Clinical Research Center for Obstetrics and Gynecology, Beijing 100191, China; Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing 100191, China. 2. Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China. 3. Center for Clinical Epidemiology & Evidence-based Medicine, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China. 4. Department of Urology, Peking University Third Hospital, Beijing 100191, China. 5. Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China; Key Laboratory of Assisted Reproduction (Peking University), Ministry of Education, Beijing 100191, China; National Clinical Research Center for Obstetrics and Gynecology, Beijing 100191, China; Beijing Key Laboratory of Reproductive Endocrinology and Assisted Reproductive Technology, Beijing 100191, China. Electronic address: roseli001@sina.com.
Abstract
PURPOSE: This study sought to identify the significant factors related to ongoing pregnancy (OP) and to discover the most reliable model to distinguish OP from non-OP in early gestational age. METHODS: A total of 1650 cycles were enrolled in this study. Univariate Logistic Regression was used to identify the predictors included in multivariable analysis. The dataset was then randomly split into training set and test set with proportion of 70% and 30%. Forward stepwise multivariable logistic regression with 5-fold cross validation was used to build the final mathematic model. The performance of the model was determined by the arguments of test set. The area under receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and misclassification rate (MR) were then calculated for model evaluation. RESULTS: Seven predictors were related to OP by univariate analysis. The serum hCG level on 14th day post-embryo-transfer (hCG14) and 21th day post-embryo-transfer (hCG21) were linear correlated. Therefore, different multivariate regression models were built using hCG14 or hCG21, respectively. After multivariate regression with 5-fold validation, the final indicators in model-1 were age_group, hCG21 and hCG21/hCG14, while age_group, hCG14, and calculated 48-hour-rising-ratio of hCG were the significant predictors in model-2. Model-2 showed better sensitivity and NPV, lower MR, and similar specificity and PPV. CONCLUSION: This study provided an effective mathematic model for early prediction of OP. The model could be of better clinical significance, especially for clinical counseling to manage patients' stress and anxiety, and for early warning of threatened miscarriage.
PURPOSE: This study sought to identify the significant factors related to ongoing pregnancy (OP) and to discover the most reliable model to distinguish OP from non-OP in early gestational age. METHODS: A total of 1650 cycles were enrolled in this study. Univariate Logistic Regression was used to identify the predictors included in multivariable analysis. The dataset was then randomly split into training set and test set with proportion of 70% and 30%. Forward stepwise multivariable logistic regression with 5-fold cross validation was used to build the final mathematic model. The performance of the model was determined by the arguments of test set. The area under receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and misclassification rate (MR) were then calculated for model evaluation. RESULTS: Seven predictors were related to OP by univariate analysis. The serum hCG level on 14th day post-embryo-transfer (hCG14) and 21th day post-embryo-transfer (hCG21) were linear correlated. Therefore, different multivariate regression models were built using hCG14 or hCG21, respectively. After multivariate regression with 5-fold validation, the final indicators in model-1 were age_group, hCG21 and hCG21/hCG14, while age_group, hCG14, and calculated 48-hour-rising-ratio of hCG were the significant predictors in model-2. Model-2 showed better sensitivity and NPV, lower MR, and similar specificity and PPV. CONCLUSION: This study provided an effective mathematic model for early prediction of OP. The model could be of better clinical significance, especially for clinical counseling to manage patients' stress and anxiety, and for early warning of threatened miscarriage.