Prediction model for testis histology in men with non-obstructive azoospermia: evidence for a limited predictive role of serum follicle-stimulating hormone
The present prediction model was intended to verify whether serum FSH level could be predictive of testis histology in patients with non-obstructive azoospermia (NOA).
We evaluated two datasets of patients with NOA: the first (San Paolo dataset) comprising 558 patients, 18–63 years old, the second (Procrea dataset) composed by 143 patients, 26–62 years old; bot datasets were combined to obtain a validation set. Multinomial logistic regression was first run with serum FSH and testis volume as independent predictors of testis histology, then, the correctly classified histological subcategories were set as outcome variables of a prediction model in both development and validation sets.
Multinomial logistic regression showed that FSH was a significant predictor of testis histology in 58% of cases, although it was unable to correctly classify cases with focal SCO or maturation arrest (MA). A prediction model was then run with hypospermatogenesis (HYPO) and Sertoli-only syndrome (SCO) as outcome variables of a binary logistic regression. FSH significantly predicted both HYPO and SCO, with a sensitivity of 40.9 and 80.7 and a specificity of 84.3 and 46.8 respectively. The model showed a fair discriminative ability (ROC AUC 0.705 and 0.709 respectively) and was adequately calibrated.
Supported by a robust statistical analysis, we conclude that serum FSH level cannot be considered a prognostic marker of spermatogenic dysfunction in patients with NOA
KeywordsFSH Testis histology Testis volume Non-obstructive azoospermia Prediction model
Compliance with ethical standards
Conflict of interest
Caroppo E. reports personal fees from Ferring Pharmaceutical, outside of the submitted work. Colpi EM, D’Amato G, Gazzano G, and Colpi GM has nothing to disclose.
The present study did not involve human or animal participants, being a retrospective analysis of de-identified data from two separate databases. For this type of study formal consent is not required.
This is a secondary analysis of already published data. For both datasets, local IRB approval for the retrospective analysis of de-identified data had been obtained before conducting the original research. The present study was performed on de-identified, non-coded data.
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