Development of a predictive nomogram for testicular sperm extraction outcomes in patients with non-obstructive azoospermia using testicular volume, follicle-stimulating hormone levels, and testosterone levels as key parameters

Introduction

Male infertility refers to the inability of a male to make a female partner conceive naturally within one year of regular unprotected intercourse, and is attributed to factors related to the male. Azoospermia can be classified into obstructive and non-obstructive azoospermia (NOA) based on testicular sperm production and transport pathways, with incidence rates ranging between 1–15% (1,2). Clinically, NOA is more prevalent, accounting for nearly 60% of azoospermia cases (3). NOA is the most severe form of male infertility. Congenital causes of NOA include Klinefelter syndrome, Y chromosome microdeletions, cryptorchidism, testicular dysgenesis, and spermatogenic dysfunction. Acquired causes include tumor chemotherapy, radiotherapy, genital trauma, and secondary azoospermia, resulting from mumps orchitis (4). Additionally, idiopathic NOA accounts for approximately 15% of NOA cases (5). In cases of NOA where viable sperm can be successfully retrieved from the testis, patients still have the potential to achieve biological parenthood (6). Therefore, successful sperm retrieval is crucial for NOA treatment.

Most NOA cases are related to spermatogenic failure, which is generally unresponsive to medical treatments. In such cases, patients can resort to surgical sperm retrieval combined with intracytoplasmic sperm injection to achieve parenthood. Currently, the most commonly used surgical sperm retrieval techniques include testicular sperm aspiration (TESA), testicular sperm extraction (TESE), and micro-TESE (7). TESA, which involves negative pressure aspiration using a syringe, is simple to perform, but has certain drawbacks, such as limited tissue acquisition and the risk of postprocedural intradermal hematoma, owing to its blind biopsy approach. Additionally, in patients with NOA, the sperm-producing cells in the testicular tissue are unevenly distributed. This irregular distribution challenges the effectiveness of TESA, as the technique may collect tissue from regions without sperm, thereby resulting in a lower success rate of sperm retrieval (8). Studies have indicated that both TESE and micro-TESE are viable options over TESA for patients with NOA, with TESE often being employed in practice due to its balance of invasiveness and effectiveness for certain patients (9,10). Although micro-TESE offers a high success rate and is increasingly adopted, our study emphasizes the significance of developing a reliable predictive model for TESE in patients with NOA. By identifying patients with higher probabilities of success, we can reduce unnecessary surgical interventions and their associated risks, such as hematoma, infection, and vascular damage (11,12). This approach not only enhances clinical outcomes but also helps minimize the economic and psychological burden on patients (13).

Current literature suggests that factors, such as body mass index (BMI), testicular volume, serum follicle-stimulating hormone (FSH), inhibin B, testosterone, and anti-Müllerian hormone (AMH), are predictive factors for testicular sperm retrieval because of their pivotal roles in spermatogenesis and as markers of Sertoli cell function (14,15). However, many of these studies were based on univariate analyses, and detailed studies on the preoperative predictors of positive sperm retrieval outcomes are lacking. Predictive factors for successful surgical sperm retrieval in patients with NOA remain controversial. Although various predictive models have been developed, existing models have yet to demonstrate satisfactory predictive power (16).

While previous studies have identified individual factors associated with successful sperm retrieval in NOA patients, our study uniquely integrates multiple clinical parameters into a comprehensive predictive model. This model offers a more robust tool for assessing the likelihood of successful sperm retrieval, thereby addressing inconsistencies and gaps identified in earlier research. Furthermore, our study’s extensive dataset, drawn from a sizable patient cohort over several years, enhances its reliability and applicability in diverse clinical settings. In clinical practice, the predictive model serves as a valuable tool to assist clinicians in educating and counseling patients about their individual success rates and setting realistic expectations for TESE outcomes. By providing insight into the likelihood of successful sperm retrieval based on clinical biomarkers, this tool can guide shared decision-making between clinicians and patients, ultimately leading to more informed choices and optimal management strategies. We present this article in accordance with the TRIPOD reporting checklist (available at https://tau.amegroups.com/article/view/10.21037/tau-24-531/rc).

Methods

Inclusion and exclusion criteria

NOA is defined as the absence of spermatozoa in the ejaculate after centrifugation and examination of the pellet, confirmed by at least two semen analyses and coupled with evidence of impaired spermatogenesis in the testes. The diagnosis of NOA in our study was made based on a combination of clinical criteria, including: (I) a thorough medical history and physical examination focusing on testicular size and consistency; (II) seminal analysis confirming azoospermia, where semen samples were centrifuged at 3,000 ×g for 15 minutes to ensure complete absence of sperm; (III) hormonal assays showing elevated FSH levels, often accompanied by normal or low serum testosterone, indicating testicular dysfunction; (IV) testicular biopsy or ultrasonography in some cases to rule out obstructive causes and confirm testicular failure where clinically indicated.

Inclusion criteria were as follows: (I) patients with NOA who underwent TESE at our hospital; (II) diagnosis consistent with urological guidelines; and (III) complete clinical data.

Exclusion criteria: (I) genetic abnormalities, such as Klinefelter syndrome and Y chromosome microdeletions, and both unilateral and bilateral cryptorchidism; (II) severe sexual dysfunction, particularly conditions significantly impacting the ability to produce a semen sample; (III) congenital obstruction or surgical removal resulting in absence of the vas deferens or ejaculatory duct; (IV) chronic epididymitis with pronounced epididymal duct swelling and dilation; (V) hypogonadism syndrome; (VI) use of medications affecting hormone levels during the course of azoospermia treatment, such as exogenous testosterone, selective estrogen receptor modulators, gonadotropins, or aromatase inhibitors.

Collection of clinical data

This was a retrospective study. All data for this study were sourced from patients who underwent TESE at the Reproductive Center of the First Affiliated Hospital of Soochow University between January 2010 and January 2024 and analyzed retrospectively. Clinical data and surgical outcomes of 425 patients with NOA who underwent TESE were collected. Each patient underwent thorough medical history inquiries, strict physical examinations, reproductive hormone assessments, genital ultrasonography, and preoperative assessments. It should be noted that the affected side of the varicocele was not related to the side of the biopsy. All enrolled patients were included only once in the analysis. Our records indicated no instances of patients undergoing more than one TESE procedure within the study period. This approach ensured that our data accurately reflected each individual’s initial outcome without any duplication. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (No. 482 of Year 2024). Informed consent was obtained from all the participants.

Procedure for TESE surgery

After routine disinfection and draping, the patient was placed in the supine position and a more fully developed testis was selected. Under spermatic cord block and topical anesthesia, an incision was made through the skin down to the tunica albuginea. A small 1–3 mm cut was made gently on the tunica albuginea using a sharp blade. The vas deferens dissector or mosquito forceps was then used to extract a large amount of testicular tissue (7–10 seminiferous tubule tissues). The incision in the tunica albuginea was closed using absorbable sutures in a figure-eight manner. The surgical site was closed after confirming the absence of significant bleeding. In the laboratory, a technician mechanically dissected the seminiferous tubules in a drop of culture medium on a slide, using needle tips to shed the tubules as much as possible. A sperm search was performed under a high-power microscope (magnification ×400), and the morphology and motility of mature sperms were observed. Normal sperm cells were identified based on the World Health Organization (WHO) standards (17): the sperm head should be 2.5–3.5 µm in width and 4.0–4.5 µm in length; the length-to-width ratio should be 1.5–1.75, with a clearly defined acrosome occupying approximately 40–70% of the head; the midpiece should be slender, 1 µm in width and about 1.5 times the length of the head, with the axis aligned with the head; cytoplasmic droplets should be <50% of the head size; the tail should be uniform and straight, thinner than the midpiece, non-coiled, and approximately 45 µm in length. Sperm capable of achieving fertilization and subsequent embryo development, even if they do not conform to conventional morphological standards, are still considered normal, and successful sperm retrieval has been confirmed. If sperms are not obtained from one testicle during sperm retrieval, the same method should be used. The morphology of surgically retrieved spermatozoa is typically very different from that of ejaculated spermatozoa. Testicular sperm may look grossly abnormal compared with ejaculated sperm. Acceptable fertilization, embryo development, and pregnancy can be achieved by selecting these spermatozoa.

Definition and reference ranges of semen analysis parameters

The parameters for semen analysis and their reference ranges were based on the fifth edition of the WHO guidelines (17). Azoospermia was defined as the absence of sperm in the pellet after centrifugation of a semen sample at 3,000 ×g for 15 min, and confirmed by at least two semen analyses. Testicular volume was measured via ultrasound on the side from which the sample was taken and calculated using the following formula: length (cm) × width (cm) × height (cm) × 0.71, if biopsies were conducted on both sides, we calculated the mean volume of both testes to provide a representative value. Prostate volume was also measured via ultrasound and the calculation for determining the prostate volume was based on the ellipsoid formula: length (cm) × width (cm) × height (cm) × 0.71. To assess hormone levels, fasting venous blood samples were collected from each patient between 8:00 AM and 11:00 AM. Reference ranges for hormone levels and blood parameters are as follows: FSH: 1.27–19.26 mIU/mL; luteinizing hormone (LH): 1.24–8.62 mIU/mL; 17β-estradiol: 15–38.95 pg/mL; prolactin: 2.64–13.13 ng/mL; testosterone: 1.75–7.81 ng/mL; hemoglobin: 120–160 g/L; red blood cells: (4–5.5)×10¹²/L; white blood cells: [4–10]×10⁹/L; platelets: [100–300]×10⁹/L; alanine aminotransferase: 7–40 U/L; aspartate aminotransferase: 13–35 U/L; gamma-glutamyl transferase: 7–45 IU/L; creatinine: 44–133 µmol/L; urea nitrogen: 2.9–7.5 mmol/L; and uric acid: 90–420 µmol/L. All blood samples were tested at our hospital’s clinical testing center, and all semen samples were analyzed at the andrology laboratory of our hospital’s reproductive center.

Statistical analysis

This study utilized R language (version 4.2.1) for statistical analysis, employing R packages, such as “stats [4.2.1]”, “rms [6.4.0]”, “Resource Selection [0.3–5]”, “p ROC [1.18.0]”, “ggplot2 [3.3.6]”, “rmda [1.6]”v and “Resource Selection [0.3–5]”. If the data exhibited a normal distribution, mean ± standard deviation of the corresponding variables was reported; otherwise, median [interquartile range (IQR)] was presented. For comparisons between two groups, if the data followed a normal distribution and met the homogeneity of variance test, a t-test was used; if the data followed a normal distribution but did not meet the homogeneity of variance test, the Welch’s t-test was applied; and if the data did not follow a normal distribution, the Wilcoxon test was used. The Chi-squared test was used for comparisons of categorical data between the two groups. Logistic multivariate regression analysis was used to identify the independent risk factors for significantly different factors between the two groups, creating a predictive nomogram with the model’s goodness of fit assessed using a calibration curve. Diagnostic performance of the model was evaluated using a receiver operating characteristic (ROC) curve, and the net benefit was assessed using decision curve analysis (DCA). The sample size calculation was calculated by R software (version 4.1.0) and the number calculated based on a formal power analysis in our study to show significance was 50 (18). Statistical significance was set at P<0.05.

Results

Comparison of baseline data between sperm-positive and sperm-negative groups

Out of the 425 patients who met the inclusion criteria and underwent TESE, they were categorized into two groups based on their sperm retrieval outcomes: 216 patients (50.8%) were classified as sperm-positive, and 209 patients (49.2%) as sperm-negative. Differences in various parameters between the groups were compared. The sperm-positive group had significantly lower serum FSH (9.35 vs. 20.59 mIU/mL, respectively; P<0.001), BMI (23.121 vs. 23.739 kg/m², respectively; P=0.04), and elastase levels (225.23 vs. 272.17 ng/mL, respectively; P=0.005) compared to the sperm-negative group. Additionally, the testicular volume (12.375 vs. 6.25 mL, respectively; P<0.001) and serum testosterone (3.955 vs. 3.25 ng/mL, respectively; P<0.001) were higher in the sperm-positive group. The success rate of sperm retrieval was notably low in patients with testicular microlithiasis (18.1% vs. 29.7%, respectively; P=0.005). See Table 1 for further details.

Logistic univariate and multivariate analysis of TESA outcomes in patients with NOA

Logistic univariate analysis of relevant clinical parameters revealed that age (P=0.02), bilateral testicular microlithiasis (P=0.005), testicular volume (P<0.001), laterality (P<0.001), FSH (P<0.001), and testosterone (P<0.001) were significantly associated with positive TESE outcomes. Age [odds ratio (OR) =1.051, 95% confidence interval (CI): 1.007–1.096, P=0.02], testicular volume (OR =1.513, 95% CI: 1.398–1.637, P<0.001), right TESE (OR =1.988, 95% CI: 1.342–2.947, P<0.001), and testosterone (OR =1.383, 95% CI: 1.187–1.612, P<0.001) showed a positive correlation. Conversely, FSH (OR =0.886, 95% CI: 0.863–0.911, P<0.001) and testicular microlithiasis showed a negative correlation (OR =0.522, 95% CI: 0.331–0.825, P=0.005). Factors with P<0.1 in the univariate analysis were included in the multivariate logistic regression to construct a predictive model. Multivariate analysis indicated that only FSH, testicular volume, and testosterone were independently associated with positive TESE outcomes. FSH levels were negatively correlated (OR =0.905, 95% CI: 0.876–0.935, P<0.001), indicating that higher FSH is a risk factor for unsuccessful TESE. Testicular volume (OR =1.453, 95% CI: 1.328–1.591, P<0.001) and testosterone (OR =1.326, 95% CI: 1.098–1.601, P=0.003) were positively correlated, suggesting that larger testicular volume and higher testosterone are protective factors against unsuccessful TESE. The other parameters did not show any significant correlations (Table 2).

Establishment of a predictive nomogram for TESE outcomes

We developed a predictive nomogram that incorporated testicular volume and FSH and testosterone (Figure 1A). The total score was obtained by locating the corresponding values for testicular volume, FSH, and testosterone on the nomogram and summing these values. The total score corresponds to the predicted success rate of sperm retrieval. A calibration curve was plotted for the nomogram to assess goodness of fit. The 45° dashed line represents ideal prediction, whereas the red line represents the performance of the nomogram predictions (Figure 1B). The closer the red line aligns with the ideal prediction line, the better the predictive accuracy of the model. The nomogram showed a good fit.

Figure 1 Establishment of a predictive nomogram for TESE outcomes. (A) The nomogram can predict the probability of successful sperm retrieval via TESE. Each variable is positioned along its respective axis. A vertical line was drawn upwards from each variable to the “Points” axis to determine the score associated with each variable. These scores were summed to obtain the total score, which was then located on the “Total Score” axis. Finally, a vertical line was drawn downwards from the total score to find the likelihood of successful sperm retrieval. (B) Calibration curve for the nomogram. The curve represents the relationship between the clinically predicted probability of positive testicular sperm extraction and actual probability across our study population. The ideal curve is the 45° line. TESE, testicular sperm aspiration; FSH, follicle-stimulating hormone.

Evaluating the diagnostic performance of the predictive model using ROC curve analysis

Based on the predictive model established using independent risk factors, we plotted the ROC curves for each individual risk factor and predictive model. The area under the ROC curve (AUC) was 0.839, 0.774, and 0.671 for testicular volume, FSH, and T, whereas the AUC for the predictive model was 0.879. The difference between the AUC of the predictive model and the AUCs of the individual indicators was statistically significant according to the results of DeLong’s test (P<0.05; Figure 2).

Figure 2 ROC curves for significant indicators and combined indicators from logistic multivariate analysis. The ROC curve was used to evaluate the accuracy of the TESE predictive model, resulting in an area under the ROC curve of 0.879. TESE, testicular sperm aspiration; TPR, true positive rate; FPR, false positive rate; AUC, area under the curve; FSH, follicle-stimulating hormone; T, testosterone; ROC, receiver operating characteristic.

DCA curve evaluation of clinical benefit

The DCA curve demonstrated that within high-risk thresholds ranging from approximately 20% to 95%, the predictive model may offer greater clinical benefits to patients than individual indicators alone (Figure 3).

Figure 3 Decision curve analysis curve for evaluating the clinical benefit rate of the predictive model. T, testosterone; FSH, follicle-stimulating hormone.

Discussion

Azoospermia is a severe form of male infertility, affecting 1–2% of the general population and 13–17% of infertile male population. NOA accounts for 55–65% of azoospermia cases (19,20). Historically, artificial insemination of donor sperms has been the only treatment option. However, with advancements in assisted reproductive technologies and ongoing studies on sperm extraction from the testes of patients with NOA, it is now possible for some patients to produce biological offspring. TESE is an invasive surgery with advantages, such as minimal trauma, a high sperm retrieval rate, and fewer complications. It is currently the primary surgical procedure used for treating NOA in clinical practice, with success rates varying significantly among patients (12). These variations are influenced by several clinical parameters, including testicular volume, hormone levels (such as FSH and testosterone), and other individual patient characteristics. Researchers have pointed out that such parameters can be utilized to predict TESE outcomes in patients with NOA. By understanding the factors contributing to these variations, we aim to refine predictive models and improve patient-specific prognostics. This approach minimizes unnecessary surgical trauma, improves success rates, and reduces the financial burden on patients. This study retrospectively analyzed 425 patients with NOA who underwent TESE, of whom 216 (50.8%) successfully obtained sperms during the surgery. In patients with NOA, testicular volume and testosterone in the successful surgery group were significantly higher than those in the failed surgery group, while FSH was significantly lower than those in the failed surgery group. Testicular volume, testosterone, and FSH have important predictive values for the success of TESE in patients with NOA.

Our study identifies FSH, testicular volume, and testosterone as key predictors of successful TESE outcomes in patients with NOA. This finding is intrinsically related to the complex role that reproductive endocrine hormones play in regulating spermatogenesis through the hypothalamic-pituitary-gonadal axis. The gonadotropins, FSH and LH, secreted by the anterior pituitary gland, stimulate the testes to secrete Inhibin B, AMH, and testosterone (21). FSH and LH are key molecules in the hypothalamic-pituitary-gonadal axis, which maintain normal spermatogenesis by regulating the functions of testicular Sertoli and stromal cells, respectively (22). Testosterone regulates spermatogenesis through Sertoli cells. Once secreted by the Leydig cells, testosterone enters the seminiferous tubules through the Sertoli cells. It can be converted into dihydrotestosterone, which binds to androgen receptors on spermatogenic cells to promote spermatogenesis (23). Over the past decade, surgical techniques for sperm retrieval have significantly evolved, resulting in higher extraction rates and reduced testicular damage in patients with NOA. Among these techniques, micro-TESE has shown promising outcomes and is often considered due to its potential benefits over conventional TESE procedures (24). However, it’s crucial to evaluate each surgical option based on individual patient needs and clinical indications. Our study, however, specifically addresses predictive factors within the context of TESE rather than micro-TESE. The variability in success rates across different techniques underscores the importance of identifying reliable predictive factors for TESE.

Prior to this study, several related studies attempted to predict sperm retrieval outcomes using models for patients with NOA undergoing TESA (25-31). Ma et al. found that FSH, age, and testicular volume were associated with risk of unsuccessful sperm retrieval in patients treated with TESA (25). Additionally, multiple studies have shown that clinical indicators, such as testicular volume, LH, and inhibin B levels are significantly correlated with surgical outcomes (26-28). The predictive capabilities of these models varied, likely because of differences in the variables included (29). To develop a more accurate predictive model, our study included a wider range of variables, such as reproductive endocrine hormones, testicular volume, seminal parameters, and blood biochemical indices. In our study, we identified serum FSH, testicular volume, and serum testosterone as significant predictors of successful TESE outcomes. Testicular volume and testosterone were positively correlated with sperm retrieval success, while high levels of FSH were negatively correlated (28-30). Our development of a predictive nomogram incorporating these factors demonstrated strong diagnostic performance, with an AUC of 0.879, highlighting its effectiveness in clinical decision-making. This aligns with other studies that identify similar predictors; for instance, research by Ma et al. has also highlighted the relevance of FSH and testicular volume in predicting sperm retrieval outcomes (25). While previous studies, such as the 2024 multi-center study by Ceyhan et al. has also developed nomograms for predicting TESE success, our study introduces several innovations (31). Specifically, we have integrated a wider array of clinical parameters, including seminal plasma fructose and elastase levels, alongside reproductive hormones, to refine prediction accuracy. Additionally, our study is among the first to validate these predictors within a single-center context, offering a detailed analysis of their interrelations and direct application in clinical practice. By comparing our model with existing studies, we confirm the robustness of these parameters as predictors for TESE success, contributing to a more informed and patient-specific approach in clinical practice. To note, the model is intended to provide patients and clinicians with additional information to make informed decisions, rather than outright preventing patients from undergoing TESE. For some patients, understanding the likelihood of success may help them prepare psychologically and consider other fertility options sooner if TESE is unsuccessful. For clinicians, the model offers a tool to better inform and counsel patients about their chances, potential risks, and alternatives, allowing for a more tailored approach based on individual circumstances and desires.

In addition to our nomogram, which utilizes clinical biomarkers like testicular volume, serum FSH, and testosterone, there are other pioneering approaches that employ different types of markers for predicting TESE success. For instance, a recent study by Shi et al. developed a nomogram based on a circular RNA biomarker to predict successful sperm retrieval via microdissection TESE specifically in patients with idiopathic NOA (32). This innovative use of molecular biomarkers, such as mRNA, highlights a different avenue for enhancing predictive accuracy and sheds light on the complex biological underpinnings of spermatogenic failure. These diverse approaches to prediction underscore the ongoing need to develop robust models that can accommodate varying clinical settings and patient profiles. While our study focuses on readily accessible clinical parameters, integrating molecular biomarkers could offer even more precise insights. The Exploration of such diverse predictors emphasizes the significant efforts within the scientific community to refine and expand the toolbox available for predicting TESE outcomes, ultimately aiming to improve patient counseling and clinical decision-making.

There are some limitations in this study. The single-center retrospective design restricts the generalizability of the model, emphasizing the need for larger multicenter prospective studies to further validate the sensitivity and specificity of the model using external data. Additionally, further studies are required to determine whether this model can predict the outcomes of other sperm retrieval techniques. Meanwhile, our study encompasses TESE procedures conducted between 2012 and 2024, spanning a significant period. During this time, it is likely that different operators were involved and that surgical methods and technology have evolved. These factors could introduce variability in procedural outcomes, potentially affecting the consistency of our data. As such, this variability is an important limitation of our study. Future studies could benefit from a standardized approach to further minimize these variations. Furthermore, we acknowledge that our predictive model may be biased towards parameters associated with obstructive azoospermia (OA), which limits its effectiveness for NOA patients, particularly in advanced procedures like micro-TESE. Our study specifically focused on conventional TESE in NOA patients, and we have stated that the model’s applicability is limited when more exhaustive sampling, such as with micro-TESE, is possible. Additionally, while our model may underestimate success rates for certain NOA cases, such as those with Klinefelter’s syndrome, micro-TESE can achieve higher retrieval rates in these scenarios. We recommend further studies to improve predictive models for micro-TESE by incorporating diverse clinical data, including genetic profiles. Lastly, we have revised our manuscript to advise cautious interpretation of our model’s predictions, emphasizing the importance of considering the specific context of sperm retrieval techniques.

Conclusions

Our study presents a robust risk-prediction model incorporating FSH, testicular volume, and testosterone as primary parameters to predict the outcomes of TESE in patients with NOA. Clinically, this model offers substantial benefits, providing physicians with a powerful tool to estimate the likelihood of successful sperm retrieval, thus informing patient counseling and management strategies. By identifying patients with higher probabilities of successful TESE outcomes, this model allows for more personalized treatment approaches, reducing unnecessary surgical interventions and associated risks. Furthermore, understanding the predictive landscape of TESE outcomes can help streamline clinical decision-making processes, enhance patient satisfaction by setting realistic expectations, and optimize resource allocation within healthcare settings. The integration of this model into clinical practice has the potential to improve the overall management of infertility in NOA patients, ultimately guiding them towards achieving their reproductive goals more effectively.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://tau.amegroups.com/article/view/10.21037/tau-24-531/rc

Data Sharing Statement: Available at https://tau.amegroups.com/article/view/10.21037/tau-24-531/dss

Peer Review File: Available at https://tau.amegroups.com/article/view/10.21037/tau-24-531/prf

Funding: This study was supported by the Suzhou Science and Technology Project (No. SLJ201906).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tau.amegroups.com/article/view/10.21037/tau-24-531/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Ethics Committee of the First Affiliated Hospital of Soochow University (No. 482 of Year 2024). Informed consent was obtained from all the participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Fainberg J, Kashanian JA. Recent advances in understanding and managing male infertility. F1000Res 2019;8:F1000 Faculty Rev-670.
2. Arshad MA, Majzoub A, Esteves SC. Predictors of surgical sperm retrieval in non-obstructive azoospermia: summary of current literature. Int Urol Nephrol 2020;52:2015-38. [Crossref] [PubMed]
3. Jarow JP, Espeland MA, Lipshultz LI. Evaluation of the azoospermic patient. J Urol 1989;142:62-5. [Crossref] [PubMed]
4. Eisenberg ML, Esteves SC, Lamb DJ, et al. Male infertility. Nat Rev Dis Primers 2023;9:49. [Crossref] [PubMed]
5. Esteves SC. Clinical management of infertile men with nonobstructive azoospermia. Asian J Androl 2015;17:459-70. [Crossref] [PubMed]
6. Vander Borght M, Wyns C. Fertility and infertility: Definition and epidemiology. Clin Biochem 2018;62:2-10. [Crossref] [PubMed]
7. Miller D, Vukina J. Recent advances in clinical diagnosis and treatment of male factor infertility. Postgrad Med 2020;132:28-34. [Crossref] [PubMed]
8. Beliveau ME, Turek PJ. The value of testicular 'mapping' in men with non-obstructive azoospermia. Asian J Androl 2011;13:225-30. [Crossref] [PubMed]
9. Schlegel PN, Sigman M, Collura B, et al. Diagnosis and Treatment of Infertility in Men: AUA/ASRM Guideline PART II. J Urol 2021;205:44-51. [Crossref] [PubMed]
10. Minhas S, Bettocchi C, Boeri L, et al. European Association of Urology Guidelines on Male Sexual and Reproductive Health: 2021 Update on Male Infertility. Eur Urol 2021;80:603-20. [Crossref] [PubMed]
11. Schlegel PN. Testicular sperm extraction: microdissection improves sperm yield with minimal tissue excision. Hum Reprod 1999;14:131-5. [Crossref] [PubMed]
12. Halpern JA, Brannigan RE, Schlegel PN. Fertility-enhancing male reproductive surgery: glimpses into the past and thoughts for the future. Fertil Steril 2019;112:426-37. [Crossref] [PubMed]
13. Bernie AM, Mata DA, Ramasamy R, et al. Comparison of microdissection testicular sperm extraction, conventional testicular sperm extraction, and testicular sperm aspiration for nonobstructive azoospermia: a systematic review and meta-analysis. Fertil Steril 2015;104:1099-103.e1-3.
14. Qi L, Liu YP, Zhang NN, et al. Predictors of testicular sperm retrieval in patients with non-obstructive azoospermia: a review. J Int Med Res 2021;49:3000605211002703. [Crossref] [PubMed]
15. Ni FD, Hao SL, Yang WX. Multiple signaling pathways in Sertoli cells: recent findings in spermatogenesis. Cell Death Dis 2019;10:541. [Crossref] [PubMed]
16. Tharakan T, Luo R, Jayasena CN, et al. Non-obstructive azoospermia: current and future perspectives. Fac Rev 2021;10:7. [Crossref] [PubMed]
17. Lu WH, Gu YQ. Insights into semen analysis: a Chinese perspective on the fifth edition of the WHO laboratory manual for the examination and processing of human semen. Asian J Androl 2010;12:605-6.
18. Chow SC, Shao J, Wang H. Sample size calculations in clinical research. 2nd ed. Boca Raton: Taylor & Francis, 2008;85.
19. Krausz C. Male infertility: pathogenesis and clinical diagnosis. Best Pract Res Clin Endocrinol Metab 2011;25:271-85. [Crossref] [PubMed]
20. Wosnitzer M, Goldstein M, Hardy MP. Review of Azoospermia. Spermatogenesis 2014;4:e28218. [Crossref] [PubMed]
21. Kaprara A, Huhtaniemi IT. The hypothalamus-pituitary-gonad axis: Tales of mice and men. Metabolism 2018;86:3-17. [Crossref] [PubMed]
22. Oduwole OO, Peltoketo H, Huhtaniemi IT. Role of Follicle-Stimulating Hormone in Spermatogenesis. Front Endocrinol (Lausanne) 2018;9:763. [Crossref] [PubMed]
23. Ohlander SJ, Lindgren MC, Lipshultz LI. Testosterone and Male Infertility. Urol Clin North Am 2016;43:195-202. [Crossref] [PubMed]
24. Donoso P, Tournaye H, Devroey P. Which is the best sperm retrieval technique for non-obstructive azoospermia? A systematic review. Hum Reprod Update 2007;13:539-49. [Crossref] [PubMed]
25. Ma Y, Li F, Wang L, et al. A risk prediction model of sperm retrieval failure with fine needle aspiration in males with non-obstructive azoospermia. Hum Reprod 2019;34:200-8. [Crossref] [PubMed]
26. Gnessi L, Scarselli F, Minasi MG, et al. Testicular histopathology, semen analysis and FSH, predictive value of sperm retrieval: supportive counseling in case of reoperation after testicular sperm extraction (TESE). BMC Urol 2018;18:63. [Crossref] [PubMed]
27. Li H, Chen LP, Yang J, et al. Predictive value of FSH, testicular volume, and histopathological findings for the sperm retrieval rate of microdissection TESE in nonobstructive azoospermia: a meta-analysis. Asian J Androl 2018;20:30-6. [Crossref] [PubMed]
28. Cissen M, Meijerink AM, D'Hauwers KW, et al. Prediction model for obtaining spermatozoa with testicular sperm extraction in men with non-obstructive azoospermia. Hum Reprod 2016;31:1934-41. [Crossref] [PubMed]
29. Deruyver Y, Vanderschueren D, Van der Aa F. Outcome of microdissection TESE compared with conventional TESE in non-obstructive azoospermia: a systematic review. Andrology 2014;2:20-4. [Crossref] [PubMed]
30. Shah R, Gupta C. Advances in sperm retrieval techniques in azoospermic men: A systematic review. Arab J Urol 2017;16:125-31. [Crossref] [PubMed]
31. Ceyhan E, Kayra MV, Gul Ates E, et al. A Nomogram Predicting Testicular Sperm Extraction Success in Men With Non-obstructive Azoospermia: A Multi-center Study. Urology 2024;S0090-4295(24)00924-5.
32. Shi S, Wang T, Wang L, et al. Nomogram based on a circular RNA biomarker for predicting the likelihood of successful sperm retrieval via microdissection testicular sperm extraction in patients with idiopathic non-obstructive azoospermia. Front Endocrinol (Lausanne) 2023;13:1109807. [Crossref] [PubMed]