BACKGROUND: Although semen analysis is routinely used to evaluate the male partner in infertile couples, sperm measurements that discriminate between fertile and infertile men are not well defined. METHODS: We evaluated two semen specimens from each of the male partners in 765 infertile couples and 696 fertile couples at nine sites. The female partners in the infertile couples had normal results on fertility evaluation. The sperm concentration and motility were determined at the sites; semen smears were stained at the sites and shipped to a central laboratory for an assessment of morphologic features of sperm with the use of strict criteria. We used classification-and-regression-tree analysis to estimate threshold values for subfertility and fertility with respect to the sperm concentration, motility, and morphology. We also used an analysis of receiver-operating-characteristic curves to assess the relative value of these sperm measurements in discriminating between fertile and infertile men. RESULTS: The subfertile ranges were a sperm concentration of less than 13.5 x 10(6) per milliliter, less than 32 percent of sperm with motility, and less than 9 percent with normal morphologic features. The fertile ranges were a concentration of more than 48.0 x 10(6) per milliliter, greater than 63 percent motility, and greater than 12 percent normal morphologic features. Values between these ranges indicated indeterminate fertility. There was extensive overlap between the fertile and the infertile men within both the subfertile and the fertile ranges for all three measurements. Although each of the sperm measurements helped to distinguish between fertile and infertile men, none was a powerful discriminator. The percentage of sperm with normal morphologic features had the greatest discriminatory power. CONCLUSIONS: Threshold values for sperm concentration, motility, and morphology can be used to classify men as subfertile, of indeterminate fertility, or fertile. None of the measures, however, are diagnostic of infertility.
BACKGROUND: Although semen analysis is routinely used to evaluate the male partner in infertile couples, sperm measurements that discriminate between fertile and infertile men are not well defined. METHODS: We evaluated two semen specimens from each of the male partners in 765 infertile couples and 696 fertile couples at nine sites. The female partners in the infertile couples had normal results on fertility evaluation. The sperm concentration and motility were determined at the sites; semen smears were stained at the sites and shipped to a central laboratory for an assessment of morphologic features of sperm with the use of strict criteria. We used classification-and-regression-tree analysis to estimate threshold values for subfertility and fertility with respect to the sperm concentration, motility, and morphology. We also used an analysis of receiver-operating-characteristic curves to assess the relative value of these sperm measurements in discriminating between fertile and infertile men. RESULTS: The subfertile ranges were a sperm concentration of less than 13.5 x 10(6) per milliliter, less than 32 percent of sperm with motility, and less than 9 percent with normal morphologic features. The fertile ranges were a concentration of more than 48.0 x 10(6) per milliliter, greater than 63 percent motility, and greater than 12 percent normal morphologic features. Values between these ranges indicated indeterminate fertility. There was extensive overlap between the fertile and the infertile men within both the subfertile and the fertile ranges for all three measurements. Although each of the sperm measurements helped to distinguish between fertile and infertile men, none was a powerful discriminator. The percentage of sperm with normal morphologic features had the greatest discriminatory power. CONCLUSIONS: Threshold values for sperm concentration, motility, and morphology can be used to classify men as subfertile, of indeterminate fertility, or fertile. None of the measures, however, are diagnostic of infertility.
Authors: C Di Bisceglie; R Fornengo; M Grosso; C Gazzera; A Mancini; B Andriani; F Lanfranco; L Brocato; G Gandini; C Manieri Journal: J Endocrinol Invest Date: 2003-11 Impact factor: 4.256
Authors: Prajna Banerjee; Bokyung Choi; Lora K Shahine; Sunny H Jun; Kathleen O'Leary; Ruth B Lathi; Lynn M Westphal; Wing H Wong; Mylene W M Yao Journal: Proc Natl Acad Sci U S A Date: 2010-07-19 Impact factor: 11.205
Authors: Feiby L Nassan; Brent A Coull; Niels E Skakkebaek; Michelle A Williams; Ramace Dadd; Lidia Mínguez-Alarcón; Stephen A Krawetz; Elizabeth J Hait; Joshua R Korzenik; Alan C Moss; Jennifer B Ford; Russ Hauser Journal: Environ Int Date: 2016-08-26 Impact factor: 9.621