Ovarian reserve as a predictor of cumulative live birth

Balachandren, Neerujah; Salman, Mona; Diu, N.L.; Schwab, S.; Rajah, K.; Mavrelos, D.

doi:10.1016/j.ejogrb.2020.06.063

Cited by 11 publications

(8 citation statements)

References 10 publications

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“…We find that the predicted value of the model with more factors is higher than that of the model with fewer factors. Balachandren found that the combined model of maternal age, FSH category, and AMH category had good predictive value for CLBR, with the AUC of the ROC being 0.68(95%CI:0.63-0.73) ( 41 ). In our study, the area under the ROC curve of the optimal model constructed for predicting cumulative live birth was 0.649 (0.615–0.682).…”

Section: Discussionmentioning

confidence: 99%

Analysis of cumulative outcomes and influencing factors of patients with discrepancies between age and AMH levels in the early follicular phase prolonged protocol

Wang

Guan²,

Zhang³

et al. 2023

Front. Endocrinol.

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ObjectiveTo explore the cumulative outcomes and influencing factors of patients with discrepancies between age and Anti-Müllerian hormone (AMH) levels in the early follicular phase prolonged protocol.MethodsA total of 1282 cycles of in-vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) assisted pregnancy with the early follicular phase prolonged protocol in the Reproductive Medicine Center of the Third Affiliated Hospital of Zhengzhou University from September 2015 to December 2020 were retrospectively analyzed. They were divided into the young low-AMH group (n=1076) and the older high-AMH group (n=206). The primary outcomes included cumulative clinical pregnancy rate (CCPR) and cumulative live birth rate (CLBR). Secondary outcomes included the number of oocytes retrieved, number of available embryos, clinical pregnancy rate (CPR), live birth rate (LBR), miscarriage rate (MR), pregnancy complications, and neonatal outcomes.ResultsThe CPR (68.7% vs. 59.4%) and the LBR (60.7% vs. 43.1%) in the young low-AMH group were higher than those in the older high-AMH group. In contrast, the number of oocytes retrieved (11 vs. 17), number of available embryos (5 vs. 8), and MR (10.6% vs. 18.3%) in the young low-AMH group were lower. There was no significant difference between the two groups in the CCPR, CLBR, pregnancy complications, and neonatal outcomes. Logistic regression analysis showed that infertility duration, basal follicle-stimulating hormone (FSH), and antral follicle count (AFC) correlated with CCPR, while maternal age, type of infertility, basal FSH, AFC, and infertility duration correlated with CLBR. The area under the receiver operating characteristic curves (ROC) curve for the combined model of infertility duration, AFC, and basal FSH to predict cumulative pregnancy was 0.629 (95%CI:0.592-0.666), while the combined model of maternal age, AFC, basal FSH, infertility duration, and type of infertility to predict cumulative live birth was 0.649 (95%CI:0.615-0.682).ConclusionAlthough AMH levels are low by contrast, young patients have a favorable outcome after IVF/ICSI. In patients with discrepancies between age and AMH levels in the early follicular phase prolonged protocol, maternal age correlates better with cumulative live birth. The model that combines maternal age and other factors can help predict cumulative live birth, but its value is limited.

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Section: Discussionmentioning

confidence: 99%

Analysis of cumulative outcomes and influencing factors of patients with discrepancies between age and AMH levels in the early follicular phase prolonged protocol

Wang

Guan²,

Zhang³

et al. 2023

Front. Endocrinol.

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“…The model shows that women delivering a live birth had a signi cantly lower median age and FSH and a signi cantly higher AMH and AFC. The authors suggested that age, FSH and AMH were independent predictors (25).…”

Section: Discussionmentioning

confidence: 99%

How to estimate the probability of a live birth after one or more complete IVF cycles？The development of a novel model in a single-center

Kong

Liu

Huang

et al. 2023

Preprint

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Objective To estimate the probability of a live birth for an infertile couple after one or more complete cycles of in vitro fertilization (IVF) by using a Cox regression and Nomogram model. Methods A retrospective study for establishing a prediction model was conducted in the reproductive center of Shenzhen Zhongshan Urology Hospital. A total of 4413 patients who completed ovarian stimulation treatment and reached the trigger were involved. 70% of the patients were randomly placed into the training set (n = 3089) and the remaining 30% of the patients were placed into the validation set (n = 1324) randomly. Live birth rate (LBR) and cumulative LBR (CLBR) were calculated for one retrieval cycle and the subsequent five frozen embryo transfer (FET) cycles. Proportional Hazards (PH) Assumption test was used for selecting the parameter in the predictive model. A Cox regression model was built based on the basis of training set, and ROC curves were used to test the specificity and sensitivity of the prediction model. Subsequently, the validation set was applied to verify the validity of the model. Finally, for a more intuitive assessment of the CLBR more intuitively for clinicians and patients, a Nomogram model was established based on predictive model. By calculating the scores of the model, the clinicians could more effectively predict the probability for an individual patient to obtain at least one live birth. Result(s): In the fresh embryo transfer cycle, the LBR was 38.7%. In the first to fifth FET cycle, the optimal estimate and conservative estimate CLBRs were 59.95%, 65.41%, 66.35%, 66.58%, 66.61% and 56.81%, 60.84%, 61.50%, 61.66%, 61.68%, respectively. Based on PH test results, the potential predictive factors for live birth were insemination method, infertility factors, serum progesterone level (R = 0.043, p = 0.059), and luteinizing hormone level (R = 0.015, p = 0.499) on the day initiated with gonadotropin, basal follicle-stimulating hormone (R = -0.042, p = 0.069) and BMI (R = -0.035, p = 0.123). We used ROC curve to test the predictive power of the model. The AUC was 0.782 (p < 0.01, 95% CI: 0.764–0.801). Then the model was verified using the validation data. The AUC was 0.801 (p < 0.01, 95% CI: 0.774–0.828). A Nomogram model was built based on potential predictive factors that might influence the event of a live birth. Conclusion(s): The Cox regression and Nomogram prediction models effectively predicted the probability of infertile couples having a live birth. Therefore, this model could assist clinicians with making clinical decisions and providing guidance for patients. Trial registration: N/A.

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“…There have been some predictive models about the CLB rate after IVF ( 21 , 22 ). One is a retrospective cohort study reported by Balachandren et al.…”

Section: Discussionmentioning

confidence: 99%

“…One is a retrospective cohort study reported by Balachandren et al. in 2020 ( 21 ). Though this prediction model estimated a couple’s individualized probability of achieving a live birth after their first complete IVF cycle using all known pre-treatment predictors, it only included 516 complete IVF cycles.…”

Section: Discussionmentioning

confidence: 99%

Nomogram for the cumulative live birth in women undergoing the first IVF cycle: Base on 26, 689 patients in China

Chen

Zhao

et al. 2022

Front. Endocrinol.

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ObjectivePredictive models of the cumulative live birth (CLB) in women undergoing in vitro fertilization (IVF) treatment are limited. The aim of this study was to develop and validate a nomogram for the CLB in women undergoing the first IVF cycle.MethodsBased on a cross-sectional study in assisted reproduction center of Northwest Women’s and Children’s Hospital, 26,689 Chinese patients who underwent IVF treatment was used to develop and validate a prediction model for the CLB. Among those participants, 70% were randomly assigned to the training set (18,601 patients), while the remaining 30% were assigned to the validation set (8,088 patients). A nomogram was constructed based on the results of the multivariate logistic regression analysis. The model performance was evaluated using the C statistic and the calibration performance was assessed by Hosmer-Lemeshow (HL) χ2 statistics and calibration plots.ResultsMultivariate logistic regression analyses revealed that female age, female body mass index (BMI), tubal factor infertility, male infertility, uterine factor infertility, unexplained infertility, antral follicle count (AFC) and basal serum follicle stimulating hormone (FSH) were significant factors for CLB in women undergoing the first IVF cycle. An area under the receiver operating characteristic curve (AUC) in the prediction model was 0.676 (95% CI 0.668 to 0.684) in the training group. The validation set showed possibly helpful discrimination with an AUC of 0.672 (95% CI 0.660 to 0.684). Additionally, the prediction model had a good calibration (HL χ2 = 8.240, P=0.410).ConclusionsWe developed and validated a nomogram to predict CLB in women undergoing the first IVF cycle using a single center database in China. The validated nomogram to predict CLB could be a potential tool for IVF counselling.

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Ovarian reserve as a predictor of cumulative live birth

Cited by 11 publications

References 10 publications

Analysis of cumulative outcomes and influencing factors of patients with discrepancies between age and AMH levels in the early follicular phase prolonged protocol

Analysis of cumulative outcomes and influencing factors of patients with discrepancies between age and AMH levels in the early follicular phase prolonged protocol

How to estimate the probability of a live birth after one or more complete IVF cycles？The development of a novel model in a single-center

Nomogram for the cumulative live birth in women undergoing the first IVF cycle: Base on 26, 689 patients in China

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