Prediction model for clinical pregnancy for ICSI after surgical sperm retrieval in different types of azoospermia.

Can a counselling tool be developed for couples with different types of azoospermia to predict the probability of clinical pregnancy in ICSI after surgical sperm retrieval? A prediction model for clinical pregnancy in ICSI after surgical sperm retrieval in different types of azoospermia was created and clinical type of azoospermia, testicular size, male FSH, male LH, male testosterone, female age, female antral follicle count (AFC) and female anti-Müllerian hormone (AMH) were used as predictors. Prediction models are used frequently to predict treatment success in reproductive medicine; however, there are few prediction models only for azoospermia couples who intend to conceive through surgical sperm retrieval and ICSI. Furthermore, no specific clinical types of azoospermia have been reported as predictors. A cohort study of 453 couples undergoing ICSI was conducted between 2016 and 2019 in an academic teaching hospital. Couples undergoing ICSI with surgically retrieved sperm were included, with 302 couples included in the development set and 151 couples included in the validation set. We constructed a prediction model using multivariable logistic regression analysis. The internal validation was based on discrimination and calibration. We found that for male patients involved in our model, different clinical types of azoospermia are associated with different clinical pregnancy outcomes after ICSI. Considering the clinical type of azoospermia, larger testicular volume and higher levels of FSH, LH and testosterone in the body are associated with higher clinical pregnancy success rates. For women involved in our model, younger age and higher AFC and AMH levels are associated with higher clinical pregnancy success rates. In the development set, the AUC was 0.891 (95% CI 0.849-0.934), indicating that the model had good discrimination. The slope of the calibration plot was 1.020 (95% CI 0.899-1.142) and the intercept of the calibration plot was -0.015 (95% CI -0.112 to 0.082), indicating that the model was well-calibrated. From the validation set, the model had good discriminative capacity (AUC 0.866, 95% CI 0.808-0.924) and calibrated well, with a slope of 1.015 (95% CI 0.790-1.239) and an intercept of -0.014 (95% CI -0.180 to 0.152) in the calibration plot. We found that BMI was not an effective indicator for predicting clinical pregnancy, which was inconsistent with some other studies. We lacked data about the predictors that reflected sperm characteristics, therefore, we included the clinical type of azoospermia instead as a predictor because it is related to sperm quality. We found that almost all patients did not have regular alcohol consumption, so we did not use alcohol consumption as a possible predictor, because of insufficient data on drinking habits. We acknowledge that our development set might not be a perfect representation of the population, although this is a common limitation that researchers often encounter when developing prediction models. The number of non-obstructive azoospermia patients that we could include in the analysis was limited due to the success rate of surgical sperm retrieval, although this did not affect the establishment and validation of our model. Finally, this prediction model was developed in a single centre. Although our model was validated in an independent dataset from our centre, validation for different clinical populations belonging to other centres is required before it can be exported. This model enables the differentiation between couples with a low or high chance of reaching a clinical pregnancy through ICSI after surgical sperm retrieval. As such it can provide couples dealing with azoospermia a new approach to help them choose between surgical sperm retrieval with ICSI and the use of donor sperm. This work was supported by a grant from the National Natural Science Foundations of China (81501246 and 81501020 and 81671443). The authors declare no competing interest. N/A.

Song J ，Gu L ，Ren X ，Liu Y ，Qian K ，Lan R ，Wang T ，Jin L ，Yang J ，Liu J ... -  《-》

Prediction model for live birth in ICSI using testicular extracted sperm.

Which parameters have a predictive value for live birth in couples undergoing ICSI after successful testicular sperm extraction (TESE-ICSI)? Female age, a first or subsequent started TESE-ICSI cycle, male LH, male testosterone, motility of the spermatozoa during the ICSI procedure and the initial male diagnosis before performing TESE were identified as relevant and independent parameters for live birth after TESE-ICSI. In reproductive medicine prediction models are used frequently to predict treatment success, but no prediction model currently exists for live birth after TESE-ICSI. A retrospective cohort study between 2007 and 2015 in two academic hospitals including 1559 TESE-ICSI cycles. The prediction model was developed using data from one centre and validation was performed with data from the second centre. We included couples undergoing ICSI treatment with surgically retrieved sperm from the testis for the first time. In the development set we included 526 couples undergoing 1006 TESE-ICSI cycles. In the validation set we included 289 couples undergoing 553 TESE-ICSI cycles. Multivariable logistic regression models were constructed in a stepwise fashion (P < 0.2 for entry). The external validation was based on discrimination and calibration. We included 224 couples (22.3%) with a live birth in the development set. The occurrence of a live birth was associated with lower female age, first TESE-ICSI cycle, lower male LH, higher male testosterone, the use of motile spermatozoa for ICSI and having obstructive azoospermia as an initial suspected diagnosis. The area under the receiver operating characteristic (ROC) curve was 0.62. From validation data, the model had moderate discriminative capacity (c-statistic 0.67, 95% confidence interval: 0.62-0.72) but calibrated well, with a range from 0.06 to 0.56 in calculated probabilities. We had a lack of data about the motility of spermatozoa during TESE, therefore, we used motility of the spermatozoa used for ICSI after freeze-thawing, information which is only available during treatment. We had to exclude data on paternal BMI in the model because too many missing values in the validation data hindered testing. We did not include a histologic diagnosis, which would have made our data set less heterogeneous and, finally, our model may not be applicable in centres which have a different policy for the indication for performing sperm extraction. The prognostic value of the model is limited because of a low 'area under the curve'. This model enables the differentiation between couples with a low or high chance to reach a live birth using TESE-ICSI. As such it can aid in the counselling of patients and in clinical decision-making. This study was partly supported by an unconditional grant from Merck Serono (to D.D.M.B. and K.F.) and by the Department of Obstetrics and Gynaecology of Radboud University Medical Center, Nijmegen, The Netherlands, the Department of Obstetrics and Gynaecology, Jeroen Bosch Hospital, Den Bosch, The Netherlands, and the Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands. Merck Serono had no influence in concept, design, nor elaboration of this study. Not applicable.

Meijerink AM ，Cissen M ，Mochtar MH ，Fleischer K ，Thoonen I ，de Melker AA ，Meissner A ，Repping S ，Braat DD ，van Wely M ，Ramos L ... -  《-》

Prediction model for obtaining spermatozoa with testicular sperm extraction in men with non-obstructive azoospermia.

Can an externally validated model, based on biological variables, be developed to predict successful sperm retrieval with testicular sperm extraction (TESE) in men with non-obstructive azoospermia (NOA) using a large nationwide cohort? Our prediction model including six variables was able to make a good distinction between men with a good chance and men with a poor chance of obtaining spermatozoa with TESE. Using ICSI in combination with TESE even men suffering from NOA are able to father their own biological child. Only in approximately half of the patients with NOA can testicular sperm be retrieved successfully. The few models that have been developed to predict the chance of obtaining spermatozoa with TESE were based on small datasets and none of them have been validated externally. We performed a retrospective nationwide cohort study. Data from 1371 TESE procedures were collected between June 2007 and June 2015 in the two fertility centres. All men with NOA undergoing their first TESE procedure as part of a fertility treatment were included. The primary end-point was the presence of one or more spermatozoa (regardless of their motility) in the testicular biopsies.We constructed a model for the prediction of successful sperm retrieval, using univariable and multivariable binary logistic regression analysis and the dataset from one centre. This model was then validated using the dataset from the other centre. The area under the receiver-operating characteristic curve (AUC) was calculated and model calibration was assessed. There were 599 (43.7%) successful sperm retrievals after a first TESE procedure. The prediction model, built after multivariable logistic regression analysis, demonstrated that higher male age, higher levels of serum testosterone and lower levels of FSH and LH were predictive for successful sperm retrieval. Diagnosis of idiopathic NOA and the presence of an azoospermia factor c gene deletion were predictive for unsuccessful sperm retrieval. The AUC was 0.69 (95% confidence interval (CI): 0.66-0.72). The difference between the mean observed chance and the mean predicted chance was <2.0% in all groups, indicating good calibration. In validation, the model had moderate discriminative capacity (AUC 0.65, 95% CI: 0.62-0.72) and moderate calibration: the predicted probability never differed by more than 9.2% of the mean observed probability. The percentage of men with Klinefelter syndrome among men diagnosed with NOA is expected to be higher than in our study population, which is a potential selection bias. The ability of the sperm retrieved to fertilize an oocyte and produce a live birth was not tested. This model can help in clinical decision-making in men with NOA by reliably predicting the chance of obtaining spermatozoa with TESE. This study was partly supported by an unconditional grant from Merck Serono (to D.D.M.B. and K.F.) and by the Department of Obstetrics and Gynaecology of Radboud University Medical Center, Nijmegen, The Netherlands, the Department of Obstetrics and Gynaecology, Jeroen Bosch Hospital, Den Bosch, The Netherlands, and the Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands. Merck Serono had no influence in concept, design nor elaboration of this study. Not applicable.

Cissen M ，Meijerink AM ，D'Hauwers KW ，Meissner A ，van der Weide N ，Mochtar MH ，de Melker AA ，Ramos L ，Repping S ，Braat DD ，Fleischer K ，van Wely M ... -  《-》

A risk prediction model of sperm retrieval failure with fine needle aspiration in males with non-obstructive azoospermia.

Ma Y ，Li F ，Wang L ，Zhao W ，Li D ，Xian Y ，Jiang X ... -  《-》

Microsurgical vasoepididymostomy is an effective treatment for azoospermic patients with epididymal obstruction and prior failure to achieve pregnancy by sperm retrieval with intracytoplasmic sperm injection.

Peng J ，Yuan Y ，Zhang Z ，Cui W ，Song W ，Gao B ... -  《-》