Rossi et al. Hiyama et al. 2008; Parl 2005; Shi et al. 2008; White et al. 2008). The availability in the ESCH database of a group of subjects genotyped for GSTM1 and GSTT1 genes in three national labora- tories allowed us to address the question if these genetic polymorphisms can modify the strength of the association between CA and cancer risk. In a group of subjects from Pisa, Italy—not included in the original ESCH database—cytogenetic slides could be retrieved from freezers, stained, and scored all together, minimizing the impact of protocol variation, reagents drift, and scorer heterogeneity. The small size of study groups is a com- mon limitation of biomarker validation studies. The presence of sparse data and miss- ing covariates are conditions for which the Bayesian paradigm presents some advantages over the frequentist paradigm. In particular, Bayes’ rule opens the possibility of improving the estimation of the parameters of interest by including the prior probability, based on knowledge already available—in this case, the association of CA with cancer risk. This study aimed at a) confirming the presence of the association between CA and cancer risk in a partially new data set, and b) evaluating the role of GSTM1 and GSTT1 polymorphisms as effect modifiers of this association. Ancillary but still important aims were to evaluate the impact of reduced labo- ratory/technical variability on risk estimates and to verify whether Bayesian statistics can provide reliable estimates in small strata. Material and Methods Subjects. A nested case–control study was performed pooling data from cytogenetic surveillance studies carried out from 1974 to 1995 at the Department of Biology, University of Pisa, Pisa, Italy; the Department o f O c c u p a t i o n a l M e d i c i n e , T e l e m a r k Hospital, Skien, Norway; and the Danish National Institute of Occupational Health, Copenhagen, Denmark. These laboratories analyzed GSTM1 and GSTT1 polymorphisms in subjects screened for CA and followed up in the framework of the ESCH (Bonassi et al. 2000; Hagmar et al. 1998, 2004) and the more recent CancerRiskBiomarkers (Cytogenetic Biomarkers and Human Cancer Risk) (Norppa et al. 2006) collaborative projects. The Italian cohort consisted of 1,650 healthy subjects selected from the general popu- lation living in three areas in Tuscany (Pisa, Cascina, and Navacchio) enrolled between 1991 and 1993 (Barale et al. 1998a, 1998b; Landi et al.1999; Milillo et al. 1996). The Norwegian cohort included 681 healthy sub- jects, either occupationally exposed or referents, collected between 1974 and 1990 (Brøgger et al. 1990; Hansteen et al. 1978, 1984). The Danish data arose from a biomonitoring study 204 conducted in 1987 in a group of 226 male stainless steel welders and referents (Knudsen et al. 1992). Information was gathered on demographic, occupational, and lifestyle factors at the time of blood sampling. In the Nordic countries, all malignant tumors diagnosed from the date of CA test- ing until the end of the follow-up (2006 in Norway, and 2003 in Denmark) were retrieved through linkage from national can- cer registries. In Italy, the cause of death was obtained from the municipality of residence (2006). At the end of the follow-up, a total of 107 cancer cases with information about GST polymorphism were tracked (105/107 cases genotyped for GSTM1 and 77/107 for GSTT1). Within each national cohort, con- trols were matched with their corresponding case by sex, age (± 10 years), and year of CA test (± 5 years). The overall cases to controls ratio was around 1:3 (107 cases/291 controls). In all participating laboratories, the stand- ard cytogenetic protocol was applied using heparinized whole blood and harvesting the cells after 48 hr of culture (Buckton and Evans 1973). CA preparations were stained with Giemsa. In Italy, the slides were banked at –20°C at the time of the original cytogenetic study (1991–1993) and stained in Giemsa immediately before the new CA analysis. In Italy, 150 and in Denmark, 100 metaphases per donor were scored for CA by a single scorer. In Norway, 100 or (in more recent studies) 200 cells per subject were scored by the same three microscopists. Savage’s clas- sification criteria for CA were used (Savage 1976). Total CA was defined as the number of cells with aberrations, excluding gaps, per 100 cells. To standardize for interlaboratory variation, all subjects were classified as low (1–33 percentile), medium (34–66 percen- tile), or high (67–100 percentile) according to tertiles of CA frequency distribution. More details on the laboratory protocols can be found in previously published reports (Barale et al. 1998a, 1998b; Bonassi et al. 2000; Hagmar et al. 1994, 1998, 2004; Hansteen et al. 1978, 1984; Knudsen et al. 1992; Landi et al. 1999; Milillo et al. 1996). The study protocols were approved by the ethics com- mittees and legal authorities in each country. DNA extraction and genotype analysis. In Italy, genomic DNA was extracted from frozen whole blood or serum as described by Murgia et al. (2007). In Norway, DNA was extracted from fixed cell suspensions with the method described by Skjelbred et al. (2006). When cell suspensions were not available, DNA was extracted from unstained slides kept at room temperature for 3–26 years. The slides were hydrated, dried carefully before adding 100 µL buffer (50 mM Tris, 1 mM EDTA, 0.5% Triton 100), covered with plastic film, kept for 15 min at 56°C, scraped in 50–100 µL dH2O 2–4 times (total volume 200 µL), and cen- trifuged at 3,000 × g for 5 min; 50 µL buffer (as above) and 5 µL proteinase K (20 mg/ mL) were added to the pellet. The samples were kept on a Thermomixer (Eppendorf, Hamburg, Germany) at 56°C, 1,000 rpm for 3 hr, before deactivating the enzyme on the Thermomixer at 96°C, 1,000 rpm for 10 min. The suspensions were stored at –20°C. The success rate depended upon the amount of cells, the age of the slides, and the genotype tested. In Denmark, DNA from mononuclear blood cells, originally analyzed for DNA repair by the unscheduled DNA synthesis technique and stored frozen in 0.4 M phosphate buffer in 1987, was used for the genotyping. This DNA had been isolated by using Millipore (Bedford, MA, USA) Microcon YM-30 cen- trifugal filter devices. In Italy, genotype analysis was performed by a specific multiplex GSTT1/GSTM1 PCR assay as described by Murgia et al. (2007). In Norway, polymorphisms of the GSTM1 and GSTT1 (and GSTP1) genes were ana- lyzed simultaneously by multiplex polymer- ase chain reaction using primers described by Nedelcheva Kristensen et al. (1998). A detailed report of the methods used for geno- typing the Danish samples can be found in Ko et al. (2000). Statistical analysis. As the response vari- able in the study was binary (cancer yes/ no), we used the standard logistic regression approach in which the response variable is the log odds (or logit). The purpose was to estimate the probability that the ith person will develop a cancer, conditionally on the information about his/her CA frequency Ei [1 = L (low), 2 = M (medium), 3 = H (high)], age Ai, sex Ei, and smoking habit Si, which are the design variables (M1): logit (pi) = β0 + β1Ei2+ β2Ei3 + β3Gi + β4Ai + β5Si. [1] To perform the analysis, we used the Gibbs sampler, which is a Monte Carlo Markov Chain (MCMC) sampling algorithm. MCMC is a class of methods for sampling from probability distributions based on constructing Markov chains. The iterative procedure simulates a Markov chain, which has the desired posterior distribution as its stationary distribution. We used the statistical software WinBUGS (http://www.mrc-bsu.cam.ac.uk) (Lunn et al. 2000) to set up a Bayesian model specify- ing an informative normal prior distribution for the regression coefficients where existing knowledge was available. More precisely, from the pooled cohort analysis of 22,358 subjects examined for CAs in 11 countries (Bonassi et al. 2008), we knew that the overall odds ratio (OR) for the medium tertile compared with the low was 1.3 with a 95% confidence ovlume 117 | number 2 | February 2009 • Environmental Health Perspectives