Sharpe and Skakkebaek 2003 Skakkebaek et al. 2001 Palmlund et al. 1993 Herbst et al. 1971 Bibbo et al. 1977 Joffe 2001 Vidaeff and Sever 2005 Sharpe and Skakkebaek 2003 Vidaeff and Sever 2005 Colborn et al. 1993 Raman-Wilms et al. 1995 Storgaard et al. 2006 Toppari et al. 1996 Vidaeff and Sever 2005 in utero Couse et al. 2001 Gray et al. 1999 2000 Joffe 2001 Toppari et al. 1996 The objectives of this research were therefore to carry out a quantitative meta-analysis of the association between three of the end points related to TDS and prenatal exposure to estrogenic agents that would account for both the size and quality of the studies included and yield updated summary estimates in light of the body of research carried out since the formulation of the estrogen hypothesis. Inclusion in this analysis was based on mechanistic criteria, and the plausibility of an ER-α–mediated mode of action was specifically explored. Moreover, subset analysis has been applied to categories of compounds with estrogenic potencies differing by several orders of magnitude in an attempt to detect the existence of any potency–response trend. Most of the studies of sperm quantity or quality have been concerned with time trends rather than etiology, and this end point was not considered further here. Material and Methods Identification and selection of literature National Center for Biotechnology Information 2007 ISI Web of Knowledge 2007 a b c d The following exclusion criteria were used: Exposure to a group of compounds (suspected endocrine disruptors) for which mode of action was unspecified, for example, pesticides. Mueller et al. 2004 Studies of maternal endogenous hormones. Studies of the same cohort as this would bias the results towards the particular studies. Incomplete data. Data extraction and quality rating In addition to the number of exposed and nonexposed cases and controls, and risk ratios (RRs) with their confidence intervals (CIs), information regarding the study design, estrogenic agent, geographic location of the study, and year of publication were extracted from the selected literature to allow subset analysis to be carried out. When more than one RR was reported, the following priorities were set for choice: Adjusted RRs were used, except when the study provided only unadjusted estimates. When multiple estimates were given, the RR estimator on which the authors had relied for their assessment of causal association was used. Overall RRs were chosen instead of those derived from further stratifications. If an overall estimate was not provided, the RRs of the maximum duration of exposure or the maximum exposure concentration were chosen. Altman 1991 Rushton 2000 Data analysis Graphical representation Sterne et al. 2001 Statistical pooling Pooled estimates and 95% CIs were calculated using both a fixed-effects model (Mantel–Haenszel method) and a random-effects model (DerSimonian–Laird method), allowing evaluation of the dependence of the conclusions of the analysis on the model assumptions. A summary estimate is considered statistically significant at the 0.05 level if its CI does not include unity. Q Subset and sensitivity analyses To investigate potential sources of heterogeneity between studies, we performed subset analyses for the study design, estrogenic agent, and geographic location. Some studies exploring the influence of hormonal treatment during pregnancy did not specify the type of hormone. From what is known of the hormonal treatment of common conditions occurring during pregnancy, it was deemed reasonable to assume that they would have been likely to include estrogens, and these studies were included in the analysis. The validity of this assumption was tested by applying stricter criteria and calculating a summary estimate of effect excluding any study in which the hormone used had not been specified. Further sensitivity analysis was performed by excluding low-quality studies and extremes (exclusion of the studies with the largest and smallest RR estimators and exclusion of the studies with the largest and smallest weights) to verify that either the quality of the studies or one particular study did not have an excessive influence on the pooled estimate. Results in utero Table 1 in utero Table 2 Hypospadias Table 3 Figure 1 Figure 2 in utero Table 4 in utero Klip et al. (2002) in utero Hernandez-Diaz 2002 Vrijheid et al. (2003) Table 4 Monteleone-Neto et al. (1981) Cryptorchidism Table 5 Figure 3 Figure 4 Table 6 in utero Depue (1988) Depue (1988) in utero Testicular cancer Table 7 Toppari et al. (1996) Figure 5 Figure 6 Figure 7 Table 8 in utero Hardell et al. (2004) Brown et al. (1986) Gershman and Stolley (1988) Henderson et al. (1979) Weir et al. (2000) Discussion Raman-Wilms et al. 1995 Toppari et al. 1996 a b c d Vrijheid et al. (2003) Zhu et al. 2006 McGlynn et al. 2005 Zhang et al. 2005 Fisher 2004 Veeramachaneni 2000 Habert et al. 2006 Mueller et al. 2004 Habert et al. 2006 Gaskell et al. (2003) Shapiro et al. (2005) Sharpe 2006 Boisen et al. 2004 Richiardi et al. 2004 Martin et al. 2007 Beleza-Meireles et al. 2006 Kurahashi et al. 2005 Starr et al. 2005 Yoshida et al. 2005 Watanabe et al. 2007 Yoshida et al. 2005 Galan et al. 2007 Conclusion The modest increase in risk for all three end points associated with DES exposure is consistent with a shared etiology and the TDS hypothesis, whereas the results of the subset analyses suggest the existence of yet unidentified sources of heterogeneity between studies or within the study populations. Although 10 years of further research on the potential effects of endocrine disruptors on male reproductive health have provided some clues regarding the etiology and mechanism of conditions such as hypospadias, cryptorchidism, and testicular cancer, there is still no conclusive evidence of the role played by environmental estrogens.