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• W1482172783 abstract "In clinical settings it is usually recommended that at least 2 semen samples are obtained, because this decreases the error rate in classifying men as fertile, subfertile, or infertile (Berman et al, 1996; World Health Organization, 1999; Sharlip et al, 2002). In fact, some authors have recommended that 3 samples be collected because of the large within-man variability of semen parameters (Keel, 2006). In our prospective study of semen quality in partners of pregnant women (the Study for Future Families, or SFF), we requested 2 semen samples from each participant in order to reduce the variability of our estimates of semen quality. However, population studies of semen quality frequently collect only 1 sample from each participant (Auger and Jouannet, 1997; Jorgensen et al, 2001, 2002). Is this optimal when conducting a population study of semen quality when resources are limited? If the total number of samples to be collected is fixed, it is preferable, from a purely statistical standpoint, to take a single sample from as many men as possible, because a larger sample size will increase the precision of the population estimates. From an epidemiologic point of view, it is necessary to consider whether requesting a second sample will decrease participation or lead to a less representative study population. From a practical standpoint one needs to consider the cost of participant recruitment relative to the cost of sample analysis. In SFF we found that the cost of recruiting a participant far outweighs the cost of analyzing the semen sample(s) he provides, and the added cost for a second sample is relatively minimal. In addition, we found that once a man has agreed to provide 1 semen sample he is likely to agree to provide additional samples (88% did). However, if multiple samples are collected, and particularly if the number of samples per man varies, this raises some statistical issues, which we address here. In this study, we ask 2 questions and use data from SFF to address these. We consider the appropriateness of (1) combining data from men who gave 1 sample and data from men who gave 2 samples in the analysis and (2) combining data from both samples from men who gave 2. For the first question, we ask whether men who give 1 sample and men who give 2 samples differ, on average, with respect to either subject characteristics or semen parameters. For the second, we ask whether semen parameters differed, on average, between the first and second sample among men who gave 2 samples in our study population. We examined these 2 questions in SFF, a clinic-based study of partners of pregnant women. Methods have been described elsewhere (Swan et al, 2003). Briefly, women were recruited at prenatal clinics affiliated with university hospitals in Los Angeles, California (Harbor-UCLA Medical Center and Cedars-Sinai Medical Center); Minneapolis, Minnesota (University of Minnesota Health Center); Columbia, Missouri (University Physicians); and Iowa City, Iowa (University of Iowa). Only pregnancies that were conceived without medical intervention were eligible. The male partner was recruited if the woman agreed, and all men were asked to give 2 semen samples. The number of subjects varied by center, as did the proportion of men giving 2 semen samples. For SFF 2 samples were requested but were not required for participation. Center directors had discretion as to the emphasis they placed on obtaining the second sample; in most centers this was strongly emphasized, but in Iowa, which was added later in the study, it was stressed less. Men were requested to observe a 2–5 day abstinence period before providing each semen sample. Prior to each of the 2 visits, which were approximately 3 weeks apart, we mailed instructions regarding specimen collection, including a schedule to assist the subject in timing his last ejaculation prior to the visit. At the time of the visit the importance of accurately reporting the actual abstinence period was stressed, and the men were assured that their sample would not be rejected if they deviated from the recommended abstinence protocol. At the study visit men collected semen samples by masturbation at the clinic, and these were analyzed, on average, within 27 minutes of collection (range, 10–105 minutes). Nine subjects were excluded from our study because the analysis was started less than 10 minutes after the sample was collected. Methods used for semen evaluation have been described previously (Brazil et al, 2004a). Briefly, concentration assessments were evaluated using both hemacytometer and MicroCell counting chambers for the first semen evaluation and only MicroCell chambers for the second semen evaluation. For both methods, the final concentration was the mean of the concentration values from the separate dilutions of 2 drops, when these differed by less than 10%. If the duplicate concentrations varied by more than 10%, a third dilution was prepared and counted and the median of the 3 values used as the estimate of concentration. On average, 200–300 sperm were counted for each dilution. For MicroCell counting, semen was always diluted with equal parts of fixative to immobilize the sperm. Ejaculate volumes were estimated by specimen weight, assuming a semen density of 1.0 g/mL. For this calculation each container was preweighed and the weight (written on the container) was subtracted from the weight of the container plus the sample. In this analysis the percent motile sperm was counted in a MicroCell chamber (Overstreet and Brazil, 1997) and refers to the percentage of sperm with any flagellar movement, whether twitching or progressive. Seminal smears were prepared at the clinical centers and shipped to the Andrology Coordinating Center at the University of California, Davis, for Papanicolaou staining, analysis, and storage. A single technician assessed sperm morphology using the strict morphology method, the method recommended by the World Health Organization (1999; Guzick et al, 2001). A second technician made assessments using the 1987 World Health Organization criteria. For each determination, 200 or 300 sperm were scored. One hundred sperm were scored in each of 2 areas of the slide, and if the differences were acceptable (10% using 1987 World Health Organization criteria and 5 sperm out of 100 using 1999 World Health Organization criteria) the mean was determined. If the difference was not acceptable, an additional 100 sperm were scored from a third area and the median value used. The SFF was approved by human subject committees at all participating institutions, and all subjects signed informed consents. In these analyses we are interested in the 4 semen parameters described above: concentration, motility, morphology, and volume. Because sperm concentration has a skewed (nonnormal) distribution, we transformed concentration using the logarithm (base 10), as has been recommended (Berman et al, 1996). Semen volume, motility, and morphology, which were not markedly skewed, were analyzed without transformation. Following the procedures of previous SFF studies (Swan et al, 2003), all analyses excluded data from men for whom either the first or second abstinence time was missing, unknown, less than 2 hours, or more than 10 days. Men who gave 1 and 2 samples were compared with respect to center as well as the following self-reported subject characteristics: education, race, smoking status, recent fever, history of sexually transmitted disease (STD), age, body mass index (BMI), and recent employment status. To address the first question (ie, whether men who gave 1 and 2 semen samples differed), we first compared all continuous variables—semen parameters, BMI, and age—between the 2 groups using t-tests. Any variable that differed significantly was then examined by center. We also compared the categorical subject characteristics between these 2 groups of men using the χ2 test for independence. We also performed covariate-adjusted analyses to compare these 2 groups. We first used a multivariate logistic regression model (Hosmer and Lemeshow, 2000) to model whether the man gave 1 or 2 samples as a function of the complete set of subject characteristics and center. We then used linear regression to model each semen parameter as a function of the complete set of subject characteristics, center, an indicator variable denoting whether 1 or 2 samples was given, abstinence time, and time to start the analysis. To address the second question (ie, whether semen parameters from the first and second semen samples differed among men who gave 2 samples), we used paired t-tests for univariate comparisons of mean differences of semen parameters between the first and second sample and examined any significant differences by center. In addition, we analyzed the difference in each semen parameter using multiple linear regression models (Weisberg, 2005), adjusting for difference in abstinence time, difference in time to start the analyses, and center. Because the 2 samples were collected only 3 weeks apart (on average), we assumed subject characteristics (eg, age, smoking) had not changed, and these were not included in these models. We included center because any possible changes in how the samples were analyzed in the time between the first and second sample collection would not necessarily be the same across center (eg, the technician may have been different for the first and second samples.) Recent fever, which may have changed between visits, was not included because it was only recorded at study entry. In these multivariate regression models, adjusted differences in semen parameters between the first and second samples would be reflected in the model intercept. After exclusions for long (n = 29), short (n = 1), or missing (n = 23) abstinence times, 697 men were available for analysis, of whom 615 provided 2 semen samples, an average of 24 days apart. A total of 177 were from California (96% gave 2 samples), 199 were from Minnesota (93% gave 2 samples), 183 were from Missouri (92% gave 2 samples), and 138 were from Iowa (66% gave 2 samples). The results of the univariate comparisons of subject characteristics for men who gave 1 and 2 samples are summarized in Table 1. The χ2 tests (using a continuity correction) show no appreciable differences except center (P < .001) and a suggestion of a difference in STD history (P = .079). Results of the multivariate logistic regression of the number of samples given are similar to the unadjusted results and are not reported. Centers differed with respect to the proportion of men giving 2 samples primarily because fewer men in Iowa gave 2 samples than men from other centers. We also compared the semen parameters between men who gave 1 and men who gave 2 samples. The unadjusted comparisons used paired t-tests assuming common variance (Table 2, columns A and B). There was an indication that strict morphology differed significantly between the 2 groups (P = .050). We examined this difference by center and saw that it was greatest in Minnesota (2.27%). Moreover, this difference in morphology between men giving 1 and 2 samples was not confirmed by a comparison of World Health Organization morphology (1987) measurements (P = .296). In the adjusted linear regression models for each semen quality outcome, the indicator variable for whether the man gave 1 or 2 samples was not a significant predictor for any outcome (data not shown). As expected, greater abstinence time was associated with a significantly greater log concentration and greater volume (P < .0001 for both) but was not significantly associated with either motility or morphology. A longer time before starting analysis was associated with a lower motility (P = .015). Several self-reported characteristics were significantly associated with semen quality measures; men who had a recent fever tended to have a lower motility (P = .01), smokers had on average a smaller volume (P = .005), and there were some center differences. BMI was not included as a covariate in the linear models because it was missing for many subjects and the t-tests showed no difference in BMI for men who gave 1 or 2 samples. Semen parameters for the first and second sample, from men who gave both, are summarized in Table 2 (columns B and C). The paired t-test indicated no significant difference between sample 1 and 2 for volume. Mean concentration differed significantly between the samples (P = .044), but the estimated difference was only 1 × 106/mL (64.3 vs 65.3 × 106/mL). Mean morphology differed between samples (P = .018), but again this difference was not confirmed by a test of World Health Organization morphology (P = .131). Mean percent motility differed significantly between the first and second samples (P = .0007), although this represents a difference of only 1% between samples (51% vs 52% motile). We examined the difference in motility for each center individually and found it to be significant only in Iowa (percent motile sample 1 = 49, percent motile sample 2 = 54; P = .0015). Results of modeling the differences between semen parameters on the first and second samples by linear regression are given in Table 3. The difference in abstinence time had a significant effect on the differences in both concentration (P < .0001) and volume (P < .0001), which agrees with previously reported data (Jorgensen et al, 2001; Swan et al, 2003; Carlsen et al, 2005). The relationship between the differences in time to start the analysis and motility (P = .017) is also reported in the literature (Jorgensen et al, 2001; Swan et al, 2003). Consistent with the univariate analysis, the degree to which motility differed between samples varied by center, being most marked in Iowa (P = .0002), where the motility measurements for the second samples were on average larger than those for the first sample. Most importantly, after controlling for abstinence time, time to start the analysis, and center, the intercept was not statistically significant for any of the differences in semen parameter outcomes. This indicates that after adjustment, semen parameters are not significantly different between the first and second samples (P values are given in Table 3). In clinical settings, it is standard practice to obtain multiple semen samples in the investigation for an infertile couple, but in population studies of semen quality the desirability of requesting multiple samples is less clear. Obtaining more than 1 semen sample will, on average, reduce measurement error in estimating population semen parameters, but requiring more than 1 sample from study subjects may reduce participation. In SFF about 12% of the 697 men chose to give only 1 of the 2 requested samples. This provided us with the opportunity to address 2 issues that arise when the number of samples per man varies. First, are there systematic ways in which men who give 2 samples differ from men who give only 1? Second, among men who give 2 samples, are there systematic differences in semen quality between these samples? This is important because the choice of the appropriate statistical model for the analysis of these semen samples depends on the answers to these 2 questions. In SFF the percent of men who gave 2 samples varied by center and reflected a between-center difference in the degree to which the need for 2 samples was stressed at the time of recruitment. The greatest difference was between California and Iowa, with 4% and 34% giving only 1 sample, respectively. Aside from center, no subject characteristic differed between men who gave 1 versus 2 samples, although men with a history of STD were somewhat less likely to give 2 samples (P = .08). No other characteristics predicted whether a man would give 1 or 2 samples, either in unadjusted or covariate-adjusted models. Moreover, semen quality did not differ significantly between men who gave 1 or 2 samples, except strict morphology without covariate adjustment. Thus, it is appropriate to combine data from men who gave 1 and 2 samples in an analysis of semen quality. One of the strengths of this study is that these data are drawn from a large population-based study with extensive quality control (Brazil et al, 2004b). A limitation of this study, however, is that all subjects are (presumably) fertile; their partners were pregnant at the time of recruitment. Therefore, the extent to which these results can be generalized to a population of men of unknown fertility is unclear. If this population had included infertile men, the range in semen quality would have been greater, and perhaps a stronger relationship between subject characteristics and semen quality would have been observed, but the impact of this on our 2 study questions is unclear. In principle, men with unknown fertility status might be less likely to return once they are given results of their sperm analysis. But this is unlikely to be relevant here because our study participants were not given their results. Our finding that semen parameters do not vary appreciably between the first and second sample, among men who give 2 samples, is likely to also be seen in a sample from the general population; there is no a priori reason to believe the second sample would systematically differ from the first among infertile men when it did not among fertile men Our results should be reassuring for investigators who are conducting population studies in which men give a variable number of samples. While none of the men in this population gave more than 2 samples, it seems likely that similar resolutions would hold for several samples given in a short time. However, this may change, for example, for sperm donors giving large numbers of samples over many years. The “dividing line” between these situations needs to be determined by studies of such donors. Our findings should also reassure researchers that data from multiple semen samples can be used in a single model as long as the model accounts appropriately for repeated measures and adjusts for all relevant covariates." @default.
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• W1482172783 title "One Semen Sample or 2? Insights From a Study of Fertile Men" @default.
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