Performance of the postwash total motile sperm count as a predictor of pregnancy at the time of intrauterine insemination: a meta-analysis

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1 FERTILITY AND STERILITY VOL. 82, NO. 3, SEPTEMBER 2004 Copyright 2004 American Society for Reproductive Medicine Published by Elsevier Inc. Printed on acid-free paper in U.S.A. Performance of the postwash total motile sperm count as a predictor of pregnancy at the time of intrauterine insemination: a meta-analysis Janne-Meije van Weert, M.D., a Sjoerd Repping, M.Sc., Ph.D., a Bradley J. Van Voorhis, M.D. b Fulco van der Veen, M.D., Ph.D. a, Patrick M. M. Bossuyt, M.Sc., Ph.D., c and Ben W. J. Mol, M.D., Ph.D. a,c,d Center for Reproductive Medicine, Academic Medical Center, Amsterdam, The Netherlands Received September 30, 2003; revised and accepted January 28, Reprint requests: Janne- Meije van Weert, M.D., Center for Reproductive Medicine, Division of Obstetrics and Gynecology, Academic Medical Center, Meibergdreef AZ, Amsterdam, the Netherlands (FAX: ; j.m.vanweert@amc.uva.nl). a Center for Reproductive Medicine, Division of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, The Netherlands. b Department of Obstetrics and Gynecology, University of Iowa Hospitals and Clinics, Iowa City, Iowa. c Department of Clinical Epidemiology, Academic Medical Center, Amsterdam, The Netherlands. d Máxima Medical Center, Veldhoven, The Netherlands /04/$30.00 doi: /j.fertnstert Objective: To assess the performance and clinical value of the postwash total motile sperm count (postwash TMC) as a test to predict intrauterine insemination (IUI) outcome. Design: Meta-analysis of diagnostic tests. Setting: Tertiary fertility center. Patient(s): Patients undergoing IUI. Intervention(s): None. Result(s): We detected 16 studies that reported on postwash TMC at insemination and IUI outcome. Summary receiver operating characteristics (ROC) curves indicated a reasonable predictive performance toward IUI outcome, and, at cut-off levels between 0.8 to 5 million motile spermatozoa, the postwash TMC provided a substantial discriminative performance. At these cut-off levels, the specificity of the postwash TMC, defined as the ability to predict failure to become pregnant, was as high as 100%; the sensitivity of the test, defined as the ability to predict pregnancy, was limited. Conclusion(s): The postwash TMC at insemination could potentially be used in counseling patients for either IUI or IVF. However, to enable patient counseling before the start of treatment, further studies are needed to establish the accuracy of a postwash TMC during the fertility workup rather than at insemination. (Fertil Steril 2004;82: by American Society for Reproductive Medicine.) Key Words: : Intrauterine insemination, male factor infertility, meta-analysis, postwash total motile sperm count, pregnancy In reproductive medicine, both patients and clinicians need tests that identify which subfertile couples are likely to benefit from intrauterine insemination (IUI) and which are more likely to benefit from in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI). The effectiveness of IUI depends on many factors, including semen quality (1 4). Normal semen quality is usually verified with the use of the World Health Organization (WHO) criteria, but these criteria have little prognostic value in IUI, as pregnancy rates after IUI are acceptable even below the WHO thresholds for normal semen quality (5, 6). A clear drop in pregnancy rate in IUI has been reported in the presence of severe teratozoospermia that is, less than 4% to 5% normal forms (7, 8); however, other investigators have reported no such association (9 11). In view of these data, the postwash total motile sperm count (TMC) has been proposed as a test to help distinguish the couples who would benefit from IUI from the couples who would benefit more from IVF or ICSI (12, 13). The postwash TMC represents the total number of motile sperm that are present after preparation and are subsequently available for insemination in IUI. This postwash TMC may be assessed during the fertility workup or at the actual time of insemination. There are no reports on the relationship between the postwash TMC during the fertility workup and IUI outcome, although many have reported on postwash TMC at insemination and its implications for IUI. The proposed cut-off values below which IUI is not advised range 612

2 between 0.3 and 20 million postwash progressively motile spermatozoa (5, 14 20). Because of the diversity in cut-off values for postwash TMC at insemination and the lack of information on postwash TMC during the fertility workup, the question arises as to whether the postwash TMC at insemination really is able to distinguish between couples who are likely to benefit from IUI and those more likely to benefit from IVF or ICSI. We performed a meta-analysis to evaluate this possible prognostic value of the postwash TMC in couples selected for IUI. The aim of the analysis was to determine the accuracy of the postwash TMC at insemination for predicting pregnancy after IUI. In addition, we assessed the clinical value of postwash TMC at the time of insemination using the results of our meta-analysis. MATERIALS AND METHODS Search Strategy A computerized MEDLINE and EMBASE search was performed to identify articles published up to March 2003, using the keywords motile sperm count, male subfertility, or male infertility and intrauterine insemination. The search was limited to studies with abstracts that had involved human subjects. One investigator (JMvW) read all the abstracts of articles identified by the search, and articles reporting on the association between the postwash TMC and IUI outcome were preselected. Subsequently, all preselected articles were judged independently by two investigators (JMvW and BWM), and separate 2 2 tables were constructed for cross-classification of the test results and the occurrence of pregnancy. Studies in which it was not possible to construct 2 2 tables were excluded. In the event of disagreement, the judgment of a third author (SR) was decisive. Cross-references in all selected articles were checked, and, if applicable, additional studies were added to the analysis. The primary outcomes of choice in our analyses were ongoing pregnancy or live-birth rates. If these were not available, clinical pregnancy rates were used. Each study was scored on the following characteristics: [1] sampling (consecutive versus nonconsecutive), [2] data collection (prospective versus retrospective), [3] study design (cohort study versus case-control study), [4] selection bias, and [5] verification bias (21). Selection bias is present when not all patients presenting with the relevant condition here, couples with their particular semen quality are included in the study. Verification bias looms when the decision to verify a case here, the decision for either IUI or IVF is influenced by the test result (22). Furthermore, we documented IUI inclusion criteria per study, the method of motile sperm isolation before insemination (sperm preparation technique), pregnancy definition, and whether a study reported on only one cycle per couple or on multiple IUI attempts. Analysis Assessment of Predictive Performance The performance of postwash TMC as a prognosticator for IUI outcome was assessed with respect to pregnancy rates. Data on clinical and ongoing pregnancies were not analyzed separately because in most studies this distinction could not be made. The analysis was done with the cycle as unit of analysis because all studies reported on pregnancy rate per cycle. The analysis was conducted according to a methodology that has been described in detail elsewhere (23, 24). In brief, for each study the sensitivity and specificity as well as likelihood ratios were calculated from the published data. If it appeared possible to extract data on the performance of postwash TMC at more than one cut-off value, then all possible cut-off levels were used. All sensitivity and specificity points were plotted in a receiver operating characteristic (ROC) space. To account for possible publication bias, we plotted the effect estimates of test accuracy the diagnostic odds ratio against sample size in a funnel plot (25). We used logistic regression analysis to evaluate whether characteristics of each individual study (i.e., consecutive or nonconsecutive sampling, prospective or retrospective data collection, selection bias, verification bias, differences in inclusion criteria, and method of sperm preparation for IUI) were associated with the discriminative capacity of the postwash TMC as reported in each study. To explore whether the differences in sensitivity and specificity combinations were related to the use of different cut-off levels in the test under study, a Spearman correlation coefficient was calculated to assess the association between sensitivity and specificity. If there was a negative correlation between sensitivity and specificity, as defined by a correlation coefficient of 0.5 or stronger, the individual pairs of sensitivity and specificity were considered to originate from a single ROC curve, and a summary ROC curve was estimated using a random-effects regression model. Assessment of Clinical Value The clinical value of the postwash TMC was assessed by taking the prior plausibility of failure to become pregnant into account. The a priori chance of pregnancy failure (i.e., the prevalence of nonpregnancy in the study population) was then combined with the results of the test (here, the postwash TMC) to calculate a posterior chance. To achieve this, for each individual study we calculated the pretest probabilities and posttest probabilities of the postwash TMC of pregnancy failures using the likelihood ratio for a positive test result. A positive test result was defined as a postwash TMC value below the cut-off value for each individual study. Posttest probabilities for the prediction of a failure to become pregnant were also calculated using the estimated summary ROC curves and assuming the pregnancy rate of FERTILITY & STERILITY 613

3 IUI to be 10% per cycle (and the nonpregnancy rate 90% per cycle). A likelihood ratio for an abnormal test result was derived from all points of the estimated ROC curve. Subsequently, the posttest probabilities of failure to become pregnant at various likelihood ratio values were computed. RESULTS Search The computerized search detected 310 studies, of which 181 studies were excluded based on the title. Another 100 studies were excluded on the basis of no report in the abstract of the capacity of postwash TMC to predict a pregnancy after IUI. From the cross-references of the 29 selected articles, four additional studies were identified for further reading. Of this total of 33 articles, 17 articles were found to be inappropriate for analysis for the following reasons: 2 2 tables could not be derived from nine studies (12, 15, 26 32); closer inspection of eight studies revealed no report on the predictive capacity of the postwash TMC, and that other sperm parameters or no sperm parameters were specified (4, 13, 33 37). One study applied three different methods of insemination (tubal perfusion, split insemination, and IUI) and was excluded because these treatment modalities were not separately analyzed (6). We did not contact the investigators from any of the excluded studies to obtain 2 2 tables or missing data. Eventually, a total of 16 studies were suitable for analysis (1, 3, 5, 14, 16, 17 20, 38 44). There was no discordance between the two authors who judged the preselected articles. The postwash TMC was assessed at the time of insemination in all of the selected studies. None of the studies reported explicitly that observers who determined the pregnancy were unaware of the results of the test under study. All studies were cohort studies. One study had a randomized crossover design to study the effect of controlled ovarian hyperstimulation on IUI outcome, with the postwash TMC as an associated variable (38). Prospective data collection was performed in two studies (5, 38). Data sampling was not consecutive in three studies (5, 38, 41). Data from all except one study were from multiple cycles and were reported as outcomes per cycle (43). We could not detect verification bias in any of the analyzed studies. Selection bias was present in nine studies. Five studies excluded couples from IUI based on a pretreatment postwash TMC, with different cut-off levels in different studies (3, 5, 19, 39, 42). In two studies, the presence of antisperm antibodies ( 50% positive) was considered an exclusion factor (19, 20). Three studies appeared to have no selection bias based on sperm parameters (14, 16, 20). In one study, only couples suffering from male subfertility were included in the study (44). In five studies, no statement was made on whether selection of patients for IUI was performed with consideration to the pretreatment postwash TMC or other semen parameters (1, 17, 40, 41, 43). Characteristics of the included studies are listed in Table 1. Inclusion criteria for duration of subfertility and the woman s age were infrequently mentioned (1, 5, 20, 39, 42). Only one study examined the possible relationship between the woman s age and the postwash TMC (1). Data were insufficient to enable logistic regression analysis to account for the possible confounding effect of the woman s age or duration of subfertility. Furthermore, six studies included women with only one patent tube (1, 3, 19, 20, 43, 44). Ovarian hyperstimulation was applied in most studies, varying from clomiphene citrate or hmg/fsh alone to clomiphene citrate with hmg. Two studies only applied ovulation induction in anovulatory or oligomenorrheic women (1, 5). Only one study analyzed the effect of ovarian hyperstimulation on IUI outcome in relation to the postwash TMC (38). The great diversity in stimulation agents and regimens between and within studies made it impossible to find an applicable scoring system to allow for logistic regression analysis. Sperm preparation techniques also differed between studies. The majority of studies, seven, performed their sperm preparation with the use of one or more (Percoll or Perwash) density gradients, with or without additional washing and without swim-up (3, 5, 18, 20, 38, 41, 43). Only a few studies used the swim-up method as the only sperm preparation technique (14, 16, 42). The remaining studies applied Percoll gradients and swim-up alternately or in combination; others used highly variable combinations of sperm preparation techniques. Three studies did not mention a definition of pregnancy (1, 42, 44). From nine studies only data on chemical and clinical pregnancies were available, usually defined as the presence of hcg in urine or serum and the presence of an embryonic sac on ultrasound examination, respectively (5, 16, 17, 20, 38 41, 43). In four other studies data on live births were also available (3, 14, 19, 20). Assessment of Predictive Performance of Postwash TMC Values Sensitivities and specificities for the prediction of nonpregnancy, as calculated from each study, are summarized in Table 2. The number of cycles per study varied between 96 and 4,892 cycles, with a mean of 1,314 cycles per study. The funnel plot confirmed that there were no differences in estimated effect between larger and smaller studies (Fig. 1). The cut-off values for the postwash TMC applied by different studies varied between and The sensitivities and specificities were equally diverse among studies, regardless of the cut-off value used. However, in studies with more than one cut-off value for the postwash 614 van Weert et al. Meta-analysis of postwash total motile sperm count Vol. 82, No. 3, September 2004

4 TABLE 1 Characteristics of included studies. Study Inclusion criteria for IUI Controlled ovarian hyperstimulation Sperm preparation technique Definition main IUI outcome Lee et al. (39) Subfertility 1 year and 10 years, postwash TMC , age 40 years Pasqualotto et al. (18) van der Westerlaken et al. (43) CC hmg first cycle, hmg in consecutive cycles No stimulation or hmg Swim-up or mini- Percoll gradient At least one patent tube, subfertility 1 year Two-layered PerWash gradient and wash At least one patent tube CC First 70/80% Percoll gradient, then two washings or another Percoll gradient and two washings Stone et al. (41) N.m. CC, hmg, or both Different types of Percoll gradients, mainly 55/90% and wash Cohlen et al. (38) Ombelet et al. (19) Berg et al. (14) Campana et al. (1) Two patent tubes, no antisperm antibodies, no cervical factor At least one patent tube, postwash TMC , 50% antisperm antibodies Two patent tubes, all semen quality, no oligomenorrhea At least one patent tube, abnormal PCT hmg vs. no hmg CC CC Only in amenorrheic or oligomenorrheic patients Huang et al. (17) N.m. CC hmg CC hmg Tomlinson et al. (42) Branigan et al. (5) Two patent tubes, subfertility 3 years, postwash TMC Two patent tubes, postwash TMC , ovulatory (naturally or with CC), age 36 years At least one patent tube, GnRH agonist and hmg or FSH None 70% Percoll gradient and two washing procedures Conventional swim-up, if count mini-percoll gradient and wash First two washings, then a swim up through a density gradient Swim-up or mini- Percoll gradient with low sperm count Two washings and swim-up or Percoll gradient and wash Just swim-up and wash First two-layered Percoll gradient 40/ 80%, then two wash procedures CC hmg 40%/80% Percoll Khalil et al. (3) postwash TMC gradient and wash Miller et al. (40) N.m. CC or FSH Different methods used, not specified Horvath et al. (16) Sperm WHO or poor CC hmg First washing then cervical mucus/poor PCT swim-up Paulmyer-Lacroix et Two patent tubes, 50% CC, hmg, or FSH Percoll gradient, only al. (20) antisperm antibodies part of the ejaculate used Delepine et al. (44) At least one patent tube hmg Percoll gradient 100/ 70/40 for spermatozoa/ml. Swim-up for spermatozoa per ml or wash Chemical and viable (fetal heart activity) pregnancy Clinical pregnancy and live birth Clinical pregnancy Chemical, clinical, and ongoing pregnancy Clinical pregnancy Chemical, clinical pregnancy, and baby take-home rate ( 500/g) Conceptions, miscarriages, and live birth N.m. Clinical pregnancy N.m. Chemical and clinical pregnancy Clinical pregnancy and live birth Chemical or clinical pregnancy Chemical pregnancy Clinical pregnancy Note: CC clomiphene citrate; hmg human menopausal gonadotropin; FSH follicle-stimulating hormone; IUI intrauterine insemination; N.m. not mentioned; PCT postcoital test; TMC total motile sperm count. N.m. FERTILITY & STERILITY 615

5 TABLE 2 Performance of the postwash total motile sperm count test in the prediction of pregnancy and shift from pretest to posttest probability of no pregnancy for patients with an abnormal (lower than the cut-off) postwash test result. Study Cycles (n) Postwash TMC cut-off value ( 10 6 ) Prediction of no pregnancy Sensitivity Specificity LR a Pretest probability (%) Posttest probability (%) Proportion of patients/cycles with abnormal postwash TMC level (%) Lee et al. (39) 1, Pasqualotto et al. (18) 1, van der Westerlaken et al. (43) Stone et al. (41) 4, Cohlen et al. (38) Ombelet et al. (19) 1, Berg et al. (14) 3, Campana et al. (1) 1, Huang et al. (17) 1, Tomlinson et al. (42) Branigan et al. (5) Khalil et al. (3) 2, Miller et al. (40) 1, Horvath et al. (16) Paulmyer-Lacroix et al. (20) Delepine et al. (44) Note: a LR likelihood ratio of a positive test result. means the LR reaches infinity because of zero in the equation. Bold print studies in which an LR 3 was found. TMC, specificity increased and sensitivity decreased with the decrease of the cut-off value. Apparently, the interstudy variations in cut-off value did not provide a pattern in changes in sensitivity and specificity but the intrastudy variations in cut-off value did. Not one single study achieved a high sensitivity, but two studies achieved a specificity of 100% for their study population at a cut-off value for the postwash TMC of (5) and (42). High specificity had an unfavorable influence on sensitivity and vice versa. Logistic regression analysis did not indicate a statistically significant association between study characteristics and the performance of the postwash TMC. The odds ratios were 0.95 (95% confidence interval [CI], ) for selection bias, 0.90 (95% CI, ) for inclusion of one-sided tubal disease, 0.87 (95% CI, ) for sperm preparation method, 0.29 (95% CI, ) for prospective studies, and 0.55 (95% CI, ) for consecutive studies. Thus, we decided not to exclude any of the studies that were initially selected. 616 van Weert et al. Meta-analysis of postwash total motile sperm count Vol. 82, No. 3, September 2004

6 FIGURE 1 Funnel plot: estimated effect in relation to sample size. The Spearman correlation coefficient for sensitivity and specificity was 0.88, which was judged to be sufficient to estimate a summary ROC curve. The summary ROC curve demonstrating the capacity of the postwash TMC to predict nonpregnancy is steep at the left lower segment of the ROC-sheet (Fig. 2). However, beyond the coordinate defined by specificity 0.84 and sensitivity 0.36, the summary ROC curve almost runs parallel to the line of equality. This indicates that the gain in sensitivity is almost equal to the decrease in specificity, when moving up the curve, and vice versa. Therefore, this segment of the curve is noninformative (likelihood ratio 1). Because of the clustering of points and the unclear picture they formed, we decided to take a detailed look at the steep part of the ROC curve (see inlay in Fig. 2). The cut-off values for the postwash TMC from the studies represented in this part of the curve with the highest specificities were or less. The studies by Branigan et al. (5) and Miller et al. (40) at cut-off values of were the exceptions to the rule. Assessment of the Clinical Value of Postwash TMC Measurements Likelihood ratios, and pretest and posttest probabilities of pregnancy from each study are listed in Table 2. The likelihood ratio of a positive test result is applied to calculate the posttest probability of the disease (here, failure to achieve pregnancy). Pretest and posttest probabilities of pregnancy are presented to demonstrate the effect of postwash TMC on pregnancy rates. If a study reported on multiple cut-off values, data for all cut-off values are shown. The posttest probability of no pregnancy could be as high as 99% to 100%, with a difference of 20% of the pretest probability; but no uniform cut-off value could be extracted from the included studies. These cut-off values ranged between 0.8 and 5.0 million motile sperm after preparation for the studies with a posttest probability of no pregnancy of 99% to 100%. However, the proportion of cycles with an abnormal test result in these studies was low, 3% to 16%. High sensitivities were not achieved. No optimal cut-off value could be extracted from the summary ROC curve. Table 3 depicts the probability of obtaining a certain postwash TMC result and the corresponding likelihood ratio within different likelihood ratio ranges for the prediction of failure to achieve pregnancy. At a likelihood ratio above three, the posttest probability of no pregnancy will be approximately 96% if the pretest probability (i.e., here, the failure to achieve pregnancy) is assumed to be as high as 90%. As is apparent from this table, the probability of obtaining a positive test result (postwash TMC below a certain cut-off value) with a likelihood ratio 3 is small, 1%. This is consistent with the likelihood ratios from the individual studies (see Table 2). The probability of obtaining a positive test result with a likelihood ratio 2 is 11%, with a corresponding posttest probability of no pregnancy of 95%. DISCUSSION The choice of the most appropriate assisted reproductive treatment for the individual couple is often a difficult one. The aim of the clinician is to achieve a live birth with the least invasive technology available. Accordingly, several semen parameters, including the postwash TMC, have been evaluated for their ability to predict the success of IUI. The postwash TMC may have unique value as a prognostic tool in that it reflects both sperm concentration and motility, as well as the effects of sperm processing. However, it is very important to realize that there is a marked difference in the interpretation of the postwash TMC during a fertility workup and the postwash TMC at insemination when used for patient counseling. A recorded cut-off value for the one possibly may not be valid for the other, and the timing of patient counseling is markedly different. In this meta-analysis, only the predictive capacity of the postwash TMC at insemination could be assessed because there were no reports on the predictive capacity of the postwash TMC during the fertility workup in the literature. An optimal cut-off value for the postwash TMC at insemination to use for patient counseling could not be identified in the summary ROC curve. The cut-off values with the greatest shift from pretest to posttest probability varied between 0.8 and 5 million processed motile sperm, but cycles with a postwash TMC below these cut-off values were only present in a minority of cases. The limitations of interpretation of the data from this meta-analysis lie in the heterogeneity of the studies and the fact that IUI outcome depends on multiple factors rather than solely the postwash TMC. The inclusion or exclusion of FERTILITY & STERILITY 617

7 FIGURE 2 Summary ROC curve : numbers attached to the abbreviations are the cut-off values of the particular study Be Berg et al. (14), Br Branigan et al. (5), Ca Campana et al. (1), Co Cohlen et al. (38), De Delepine et al. (44), Ho Horvath et al. (16), Hu Huang et al. (17), Kh Khalil et al. (17), Le Lee et al. (39), Mi Miller et al. (40), Om Ombelet et al. (19), Pa Pasqualotto et al. (18), Pau Paulmyer-Lacroix et al. (20), St Stone et al. (41), To Tomlinson et al. (42), We van der Westerlaken et al. (43). certain patient characteristics could affect the interpretation of IUI outcome in these studies, thus some methodologic issues must be addressed. First, there is sufficient evidence to assume a negative linear association between the woman s age and pregnancy rate after IUI (1, 4, 27, 28, 35, 42). The effect of the woman s age on the predictive capacity of the postwash TMC is still not clear, although some claim that increasing age has more negative effect on IUI outcome than decreasing numbers of total motile sperm in the inseminate (1). The possible confounding factor of increased female age could not be accounted for in the logistic regression analysis because of insufficient data. Second, the effect of ovarian hyperstimulation on IUI outcome is a matter for debate, especially in patients with sperm impairments (1, 27, 33, 34, 38). It is mentioned that in couples with a postwash TMC the use of ovarian stimulation does not improve IUI outcome (38). We have not been able to analyze the possible effect of ovarian hyperstimulation on IUI outcome in relation to the postwash TMC in our meta-analysis because of lack of suitable data and because of lack of consensus on stimulation agents and regimes between the studies. Another limitation is that the analysis was done with the cycle as unit of analysis because all studies reported on pregnancy rate per cycle. The use of multiple cycles per couple bears the risk of overrepresentation of the less fertile couples, as they would need more cycles to conceive. Ideally, the unit of analysis would have been the subfertile couple. Alternatively, the meta-analysis could have been limited to first cycles. However, data presentation in the included studies did not allow data extraction for such an analysis. The presence of one-sided tubal pathology possibly has an unfavorable effect on IUI outcome (4, 28, 35). However, this possible confounding factor did not influence the out- 618 van Weert et al. Meta-analysis of postwash total motile sperm count Vol. 82, No. 3, September 2004

8 TABLE 3 The occurrence of postwash total motile sperm count test results within a specified likelihood ratio range and the concomitant posttest probabilities of no pregnancy, given a 90% prevalence of no pregnancy. Likelihood ratio range Prediction of no pregnancy (pretest probability 90%) Occurrence of test results in this range (%) Posttest probability of no pregnancy (%) come of our meta-analysis as analyzed by logistic regression. Eventually, it was not necessary to adjust for possible confounding factors in this meta-analysis, which made a univariable approach of the postwash TMC justified. In our opinion, three factors ultimately determine the clinical value of a diagnostic test: [1] the shift from pretest to posttest probability in case of an abnormal test result; [2] the proportion of patients for whom the prediction is valid; and [3] the consequences that are drawn from an abnormal test result. Because there is no unequivocal appreciation of false-positive and false-negative results, we have to consider the potential clinical value of the postwash TMC from both the false-positive and the false-negative perspective. A false-positive test result in the prediction of failure to achieve pregnancy that is, the occurrence of pregnancy after a TMC below the cut-off value might imply negative counseling, thus being an unjust denial of entry into the IUI program. On the other hand, couples with a false-negative test result would undergo standard IUI, with physical burden and medical costs, despite having minimal chances of success. A low false-positive rate requires excellent specificity, which in the case of the postwash TMC can only be obtained at the expense of a very low sensitivity. However, the cut-off value necessary to reach such specificity varies among studies. Any shift to a cut-off value with higher sensitivity instantly causes specificity to drop markedly. The data from this meta-analysis indicate that, for postwash TMC as a test for no pregnancy in IUI, there are virtually no combinations of high specificity and high (or even intermediate) sensitivity. In subfertility treatment, however, a clinician would rather distinguish between the very poor responders and the average responders than between the average and good responders, as it is impossible to guarantee a pregnancy after IUI even with a very high postwash TMC. The systematic analysis in the present study has revealed an important issue. Clearly, the predictive accuracy of the postwash TMC toward IUI lies in a high specificity, with different cut-off levels for different clinics. This variability in cut-off values is probably attributable to the different methods of sperm preparation in the various studies. With the swim-up technique, the total number of motile sperm is lower than after Percoll isolation, but the pregnancy rates after IUI are comparable (45). For instance, Berg et al. (14) and Horvath et al. (16) used swim-up as their only sperm preparation technique and generated lower cut-off values than most of the others. Very recently, a randomized, controlled trial was performed to compare a simple wash procedure with discontinuous gradient centrifugation (i.e., Percoll isolation) in IUI, which concluded that there were no differences in IUI outcome for the whole IUI population in this study (25). None of the studies in our meta-analysis, however, used a simple wash procedure to isolate motile spermatozoa. Because of very little evidence in the literature for the superiority of any sperm preparation technique in IUI, the best predictive cut-off value of the postwash TMC can probably be achieved when this cut-off value is based on the clinical population and sperm preparation technique used by the individual clinic. In conclusion, the value of the postwash TMC at insemination lies in the enhancement of patient selection by identifying couples unlikely to conceive with IUI and not in the selection of patients most likely to conceive with IUI. Where a postwash TMC at insemination has limited clinical value because of its timing, a postwash TMC during the fertility workup with such predictive characteristics would have potential in patient counseling for either IUI or IVF. As long as there are no data on the subject, the cut-off value for a postwash TMC during the fertility workup should be based on the clinic s own population and sperm-preparation technique. Further study is needed to evaluate the predictive capacity of the postwash TMC during the fertility workup in relation to other variables known to influence IUI outcome. References 1. Campana A, Sakkas D, Stalberg A, Bianchi PG, Comte I, Pache T, et al. 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Advanced semen analysis: a simple screening test to predict intrauterine insemination success. Fertil Steril 1999;71: Dickey RP, Pyrzak R, Lu PY, Taylor SN, Rye PH. Comparison of the sperm quality necessary for successful intrauterine insemination with World Health Organization threshold values for normal sperm. Fertil Steril 1999;71: Van Waart J, Kruger TF, Lombard CJ, Ombelet W. Predictive value of normal sperm morphology in intrauterine insemination (IUI): a structured literature review. Hum Reprod Update 2001;7: FERTILITY & STERILITY 619

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