Evidence map›Paper›PMID 41327319›Full record

ArticleReproductive biology and endocrinology : RB&E2025

Development of a predictive model and nomogram in sperm retrieval rate based on testicular pathological morphometric parameters in non-obstructive azoospermia patients: a multi-center study.

Hong-Xiang Wang, Jia-Xi He, Yi-Min Guo, Liang Zhou, Si-Xuan Li, Zi-Tong He, Qi-Ya Jing, Pei-Quan Wang, Liu-Qing Qu, Jun-Cheng Gao and 9 more

Abstract readMulticenter Study
In one paragraph

Article in Reproductive biology and endocrinology : RB&E, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Hong-Xiang WangDepartment of Urology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
Jia-Xi HeHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Yi-Min GuoHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Liang ZhouAssisted Reproduction Center, Northwest Women's and Children's Hospital, Xi'an, 710003, China.
Si-Xuan LiHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Zi-Tong HeHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Qi-Ya JingHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Pei-Quan WangHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Liu-Qing QuHealth Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Jun-Cheng GaoNorthwest A&F University, Xianyang, 712100, China.
Guan-Chen LiuSchool of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
Hai-Xu WangAssisted Reproduction Center, Xijing Hospital of Air Force Medical University (the former the Fourth Military Medical University), Xi'an, 710032, China.
Yan-Qi YangDepartment of Pathology, Medical School, Xi'an Jiaotong University, Xi'an, 710061, China.
Pan GeDepartment of Pathology, Medical School, Xi'an Jiaotong University, Xi'an, 710061, China.
Jian ZhangDepartment of Pathology, Medical School, Xi'an Jiaotong University, Xi'an, 710061, China.
Xiao-Ting WangReproductive Medicine Center, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, 710004, China. 369542541@qq.com.
Mo-Qi LvDepartment of Pathology, Medical School, Xi'an Jiaotong University, Xi'an, 710061, China. lvmoqi@xjtu.edu.cn.
Hai-Ge ChenDepartment of Urology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China. rjbladder@163.com.
Dang-Xia ZhouDepartment of Pathology, Medical School, Xi'an Jiaotong University, Xi'an, 710061, China. zdxtougao@163.com.

Funding

China Postdoctoral Science Foundation 2022M722540Clinical Research Plan of SHDC SHDC2020CR4035EPA EP-C-17-017Foundation of Shanghai Hospital Development Center SHDC12015125Innovation Project for Medical Integration in XJTU YXJLRH2022080National Natural Science Foundation of China 81673224National Natural Science Foundation of China 82173076Natural Science Foundation of Shaanxi Province 2023-JC-QN-0819Natural Science Foundation of Shanghai Municipality 16ZR1420300, 18410720400, 19431907400, and 20Y11904900Renji Hospital Research Funding Projects RJZZ18-020, PYIII-17-017, and PY2018-IIC-02Shanghai Jiao Tong University School of Medicine Research Funding Projects TM201708Shanghai Municipal Health Commission for advanced and suitable technology promotion projects 2019SY056
6 · The paper itself

Abstract

backgroundMicrodissection 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.

methodsThis 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.

resultsOur 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.

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

Indexed as

AzoospermiaNomogramsSperm RetrievalTestisAdultChinaHumansMalePredictive Value of TestsRetrospective StudiesDiagnostic accuracyNon-obstructive azoospermia (NOA)Pathological morphometryPrediction modelTesticular sperm retrieval

Identifiers

PMID41327319
PMCPMC12771997

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