Clinical parameters associated with altered sperm DNA fragmentation index among primary infertile men: Findings from a real‐life cross‐sectional study

Author:

Pozzi Edoardo12,Fallara Giuseppe12ORCID,Belladelli Federico12,Corsini Christian12,Raffo Massimiliano12,Candela Luigi12,Schifano Nicolò12ORCID,d'Arma Alessia1,Capogrosso Paolo3ORCID,Boeri Luca4ORCID,Cilio Simone15,Montorsi Francesco12,Salonia Andrea12ORCID

Affiliation:

1. Division of Experimental Oncology/Unit of Urology URI IRCCS Ospedale San Raffaele Milan Italy

2. University Vita–Salute San Raffaele Milan Italy

3. Department of Urology Circolo & Fondazione Macchi Hospital ‐ ASST Sette Laghi Varese Italy

4. Department of Urology Foundation IRCCS Ca’ Granda ‐ Ospedale Maggiore Policlinico University of Milan Milan Italy

5. Department of Neurosciences, Reproductive Sciences and Odontostomatology University of Naples Federico II Naples Italy

Abstract

AbstractBackgroundRecurrent pregnancy loss and unexplained infertility are the current indications to test sperm DNA fragmentation according to the European Association of Urology Guidelines on sexual and reproductive health.ObjectiveTo identify a novel and better performing model to diagnose primary infertile men presenting with altered sperm DNA fragmentation and to outline its predictive ability in respect to current European Association of Urology Guidelines’ recommendations.Materials and methodsData from the latest 515 consecutive primary infertile men as for World Health Organization criteria were analyzed. Semen analysis, sperm DNA fragmentation (according to sperm chromatin structure assay), and serum hormones were considered in every patient. Altered sperm DNA fragmentation was defined with levels greater than 30%. Descriptive statistics was applied to compare patients with normal versus SDF > 30%. The new predicting model was identified through logistic regression analysis exploring potential predictors of SDF > 30% at first clinical presentation. Diagnostic accuracy between the two predictive models (European Association of Urology Guidelines vs. new) was assessed, and decision curve analyses tested their clinical benefit.ResultsOf 515, 268 (51.9%) patients had SDF > 30% at clinical presentation. Patients with SDF > 30% were older (median [interquartile range] 39 [35–43] vs. 37 [34–41] years), had lower mean testicular volume (Prader 15 [12–20] vs. 17.5 [13.5–20] and lower total motile sperm count (1.80 [0.7–13.2] vs. 11.82 [4.2–44.5] × 106), all p < 0.001. No other clinical differences were depicted. The two groups showed similar rates of history of recurrent pregnancy loss and unexplained infertility. At multivariable logistic regression analysis, age more than 38 years (odds ratio: 2.43) and baseline total motile sperm count less than 20 × 106 (odds ratio: 3.72) were associated with SDF > 30%, after adjusting for Prader < 15, history of miscarriages and unexplained infertility, all p < 0.0001. The newly identified model (unexplained infertility + history of poli‐abortions + Prader < 15 + age ≥38 years + total motile sperm count <20 × 106) showed higher accuracy to identify SDF > 30% at baseline in respect to European Association of Urology Guidelines (area under the curve: 72.1 vs. 52.7), with superior clinical net benefit use.ConclusionsThe application of the European Association of Urology sexual and reproductive health guidelines does not ensure proper identification of primary infertile men with pathological sperm DNA fragmentation. We propose a novel and better performing predictive model to identify the infertile men with altered sperm DNA fragmentation at first clinical assessment.DiscussionAs altered sperm DNA fragmentation has been widely linked with the inability to conceive, this second‐level test could be further implemented over the diagnostic workup of a broader subset of patients presenting for male factor infertility. We propose a better performing model to identify this specific category of patients.

Publisher

Wiley

Subject

Urology,Endocrinology,Reproductive Medicine,Endocrinology, Diabetes and Metabolism

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