Journal of Experimental & Clinical Cancer Research 2009, 28:135 http://www.jeccr.com/content/28/1/135 16α-OHE1 by tertiles of urine concentrations. We used the same models to test for significance in trends of asso- ciation for any of the independent variables. We com- puted the cut-off points of the previously mentioned tertiles based on the distributions of estrogen metabolites in control subjects. We analyzed each independent varia- ble separately. Based on the published literature, we iden- tified age, race, education level, BMI and waist-to-hip ratio as possible covariates and tested them using regression models. Although none of them was a confounder for the investigated associations, we included age in years in fur- ther analyses based on its biological relevance in prostate carcinogenesis [2]. We verified several sources of potential bias. Because the exclusion of participants with missing data for any of the two outcome variables could have introduced a source of bias in our final sample, we examined data by subsets. Each of the two datasets included men with no missing data for either urinary levels of 2-OHE1 or 16-αOHE1. We then examined by case-case and control-control compar- ing the characteristics of the 136 subjects (110 controls and 26 cases) with no data missing for any of the consid- ered variables and those of the subjects (534 controls and 41 cases) who fulfilled our study eligibility criteria. Finally, we compared the subjects in the latter category [575] to the 517 original cohort members who did not join the study either because they did not fulfil the inclu- sion criteria, were lost to follow-up or were not willing to participate. To date, no data exists related specifically to any of these three categories (i.e. co-morbidity data pertinent to the WNYCS). Thus, we considered these 517 male subjects as part of an overall, although heterogeneous, category. As expected, the 517 males from the original cohort who did not ultimately join our study showed statistically signifi- cant differences when compared to the 575 included study participants. We analyzed these data using SPSS ver- sion 14.0 (SPSS, Inc., Chicago, IL). Meta-analysis We planned to combine the results from the current study with those identified in the systematic review using the DerSimonian-Laird random effects method expressing the pooled estimates in terms of summary OR and 95% CI. We calculated I2 to assess heterogeneity across study results applying the following interpretation for I2 (J Hig- gins, personal communication): 0-50 = low; 50-80 = mod- erate and worthy of investigation; 80-100 = severe and worthy of understanding; 95-100 = aggregate with major caution [23]. We used Revman 5.0 for the meta-analysis (Copenhagen: The Nordic Cochrane Centre, The Cochrane Collaboration, 2008). Results Table 1 shows the descriptive characteristics of the study participants. No significant differences emerge when com- paring cases and controls by age, race, education, and anthropometrics. In Table 2, we report crude and age-adjusted Pca risk esti- mates in relation to tertiles of urinary estrogen metabo- lites and their ratio. The OR in the highest compared to the lowest tertile of 2-OHE1 was 0.72 (95% CI 0.25-2.10). Conversely, the odds in the highest tertile of 16α-OHE1 was 1.76 (95% CI 0.62-4.98). Finally, the 2-OHE1 to 16α- OHE1 ratio showed a non-significant risk reduction Table 1: Participants Descriptive Characteristics by Case- Control Status, PROMEN Study, 1996-2001 n Control % Prostate Cancer Case n % two-tails p-value Age 50-59 60-69 70-79 Race Black White BMI ≤ 25 25-30 ≥ 30 Years of Education 8-13 66 14-18 44 110 31 40 39 4 106 25 55 29 Waist circumference ≤ 97,50 56 > 97,50 53 Hip circumference ≤ 102,50 56 > 102,50 53 Waist to hip ratio ≤ 0,95 > 0,95 55 54 80.88 28.20 36.40 35.50 3.60 96.0 60.00 40.00 22.90 50.50 26.60 51.40 48.60 51.40 48.60 50.50 49.50 26 7 9 10 1 25 16 10 6 11 9 10 16 12 14 14 11 19.12 26.90 34.60 38.50 61.50 38.50 23.10 42.30 34.60 38.50 61.50 46.20 53.80 56.00 44.00 0,902 1.000 1.00 0.683 0.279 0.668 0.662 *BMI: body mass index expressed as weight in kilograms divided by the square of height in meters (kg/m2) Page 4 of 8 (page number not for citation purposes)