Scott M Nelson1, Richard Fleming2, Marco Gaudoin3, Bokyung Choi4, Kenny Santo-Domingo4, Mylene Yao4. 1. School of Medicine, University of Glasgow, Glasgow, United Kingdom. Electronic address: scott.nelson@glasgow.ac.uk. 2. School of Medicine, University of Glasgow, Glasgow, United Kingdom; Glasgow Centre for Reproductive Medicine, Glasgow, United Kingdom. 3. Glasgow Centre for Reproductive Medicine, Glasgow, United Kingdom. 4. Univfy, Los Altos, California.
Abstract
OBJECTIVE: To compare antimüllerian hormone (AMH) and antral follicle count (AFC) separately and in combination with clinical characteristics for the prediction of live birth after controlled ovarian stimulation. DESIGN: Retrospective development and temporal external validation of prediction model. SETTING: Outpatient IVF clinic. PATIENT(S): We applied the boosted tree method to develop three prediction models incorporating clinical characteristics plus AMH or AFC or the combination on 2,124 linked IVF cycles from 2006 to 2010 and temporally externally validated predicted live-birth probabilities with an independent data set comprising 1,121 cycles from 2011 to 2012. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Predictive power (posterior log of odds ratio compared to age, or PLORA), reclassification, receiver operator characteristic analysis, calibration, dynamic range. RESULT(S): Predictive power, was highest for the AMH model (PLORA = 29.1), followed by the AMH-AFC model (PLORA = 28.3) and AFC model (PLORA = 22.5). The prediction errors were 1% to <5% in each prognostic tier for all three models, except for the predicted live-birth probabilities of <10% in the AFC model, where the prediction error was 8%. The improvement in predictive power was highest for the AMH model: 76.2% improvement over age alone relative to 59% improvement for AFC and 73.3% for the combined model. Receiver operating characteristic analysis demonstrated that the AMH and the combined model had comparable discrimination (area under the curve = 0.716) and similar prediction error for high and low strata of live-birth prediction, with an improvement of 6.3% over age alone. CONCLUSION(S): The validated prediction model confirmed that AMH when combined with clinical characteristics can accurately identify the likelihood of live birth with a low prediction error. AFC provided no added predictive value beyond AMH.
OBJECTIVE: To compare antimüllerian hormone (AMH) and antral follicle count (AFC) separately and in combination with clinical characteristics for the prediction of live birth after controlled ovarian stimulation. DESIGN: Retrospective development and temporal external validation of prediction model. SETTING:OutpatientIVF clinic. PATIENT(S): We applied the boosted tree method to develop three prediction models incorporating clinical characteristics plus AMH or AFC or the combination on 2,124 linked IVF cycles from 2006 to 2010 and temporally externally validated predicted live-birth probabilities with an independent data set comprising 1,121 cycles from 2011 to 2012. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Predictive power (posterior log of odds ratio compared to age, or PLORA), reclassification, receiver operator characteristic analysis, calibration, dynamic range. RESULT(S): Predictive power, was highest for the AMH model (PLORA = 29.1), followed by the AMH-AFC model (PLORA = 28.3) and AFC model (PLORA = 22.5). The prediction errors were 1% to <5% in each prognostic tier for all three models, except for the predicted live-birth probabilities of <10% in the AFC model, where the prediction error was 8%. The improvement in predictive power was highest for the AMH model: 76.2% improvement over age alone relative to 59% improvement for AFC and 73.3% for the combined model. Receiver operating characteristic analysis demonstrated that the AMH and the combined model had comparable discrimination (area under the curve = 0.716) and similar prediction error for high and low strata of live-birth prediction, with an improvement of 6.3% over age alone. CONCLUSION(S): The validated prediction model confirmed that AMH when combined with clinical characteristics can accurately identify the likelihood of live birth with a low prediction error. AFC provided no added predictive value beyond AMH.
Authors: Norbert Gleicher; Vitaly A Kushnir; Aritro Sen; Sarah K Darmon; Andrea Weghofer; Yan-Guang Wu; Qi Wang; Lin Zhang; David F Albertini; David H Barad Journal: J Transl Med Date: 2016-06-10 Impact factor: 5.531