Development of a predictive model and nomogram in sperm retrieval rate based on testicular pathological morphometric...

Microdissection testicular sperm extraction (micro-TESE) is an effective method to retrieve sperm from non-obstructive azoospermia (NOA) patients. However, the predictive factors for sperm retrieval rate (SRR) remain confused. The goal of our study was to identify the role of testicular pathological morphometric parameters, including diameter of tubule (DT), height of spermatogenic epithelium (HSE), and thickness of basement-membrane (TBM) in NOA patients, and to develop a predictive model and nomogram to predict SRR based on these morphometric parameters.

This study involved two cohorts including 406 men with NOA. A retrospective cohort of 313 males with NOA who underwent micro-TESE at Northwest Women's and Children's Hospital (Xi'an, China) were included to build a prediction model of SRR. Then, another retrospective cohort of 93 males with NOA from Ren Ji Hospital (Shanghai, China) were recruited to validate the prediction model. The measurement of testicular morphometric parameters as well as the assessment of Johnsen score and pathological diagnostic types were performed by at least two pathologists. Testicular volumes as well as level of serum hormones including follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T) were also measured. Logistic regressions were used to test potential predictors of SRR. Area under curve (AUC) estimates was used to evaluate the predictive accuracy. The validation datasets were used to validate the prediction model by prediction accuracy.

Our study demonstrated that DT and HSE were significantly longer in successful sperm retrieval group than in failed sperm retrieval group. In addition, DT and HSE were positively correlated with Johnsen score, testicular volume, and serum T, while, were negatively correlated with serum FSH and serum LH. On the contrary, TBM demonstrated exact opposite results. Moreover, univariate logistic analyses illustrated that longer DT and HSE was associated with a high SRR, respectively. Further multivariate logistic analyses constructed multi-variables models with better predictive abilities compared with single-variables models. A multi-variables model (predicting score = -0.612-0.018 × DT + 0.040 × HSE + 0.097 × Johnsen score-0.004 × serum FSH) was finally constructed with the best predictive ability (AUC = 0.839, sensitivity = 71.4% specificity = 77.5%, cut-off value = 0.489). A higher predicting score indicated a higher possibility of successful sperm retrieval. The predictive accuracy was 89.25% in the external validation dataset.

We report for the first time that DT and HSE have pretty ability to predict SRR in NOA patients.