We conducted a case-control study in seven cities in Central and Eastern Europe: Prague, Brno, Ceske Budejovice, and Olomouc (Czech Republic), Lodz (Poland), Bucharest (Romania), and Moscow (Russia). Each study centre followed an identical protocol and was responsible for recruitment of a consecutive group of newly diagnosed kidney cancer patients. Diagnostic procedures were comparable in all study areas, and the proportion of patients undergoing surgery was high in all study areas. To try to eliminate differences across centers, we conducted backward and forward translation of questionnaires and centralized training of interviewers.
Cases had histologically confirmed kidney cancer (ICD-0-2 code C64) and were admitted to one of the participating hospitals from 1999–2003; all histological diagnoses were subsequently reviewed by one pathologist, and the current analysis is restricted to RCC cases only. RCC cases included clear cell carcinoma (N=897, 90.4%), papillary (N=71, 7.2%), chromophobe (N=22, 2.2%), and 2 cases (0.2%) of oncocytic neoplasm. Controls were recruited in the same hospitals and were chosen from patients suffering from a predefined list of diseases that excluded malignant neoplasms, other conditions related to smoking, diseases of the respiratory system, some endocrine, metabolic and neurological diseases, as well as trauma. No single disease made up more than 25% of the control group (diseases of digestive system: 24%, musculoskeletal system/connective tissue: 12%, genitourinary system: 11%, skin and subcutaneous tissue: 10%, circulatory system: 9%, central nervous system: 9%, eye and ear: 8% and other smaller categories combined: 17%). Country-specific participation rates ranged from 90% to 99% among cases and from 90% to 96% among controls.
Cases and controls underwent a detailed personal interview in which they provided information on occupational history, personal medical history, family history of cancer, tobacco smoking, alcohol drinking, dietary and anthropometric factors, and other lifestyle habits. The occupational interview consisted of a general questionnaire for each job, and for 16 prespecified jobs a specific questionnaire was also used. The general questionnaire intended to ascertain complete occupational history and additional information relevant to exposure assessment, including job titles, tasks, industries, starting and stopping dates, full-time/part-time status, working environments, and specific exposures. The separate, more specific questionnaire was completed for employment in any of the following jobs or industries: toolmaker or machinist, motor vehicle mechanic, miner/quarryman, woodworker, painter, welder, insulation worker, meat worker or farmer, and the steel, coke manufacture, foundry, glass, tannery, chemical, and rubber industries.
The occupational exposure assessment was completed by localexperts, including chemists, industrial hygienists, and occupational physicians, who hadpractical experience in industrial hygiene and took into account regional differences in use of materials, production processes, and prevention measures and changes in exposure patterns within and across jobs and industries over time for the different exposures. We attempted to standardize exposure assessment through yearly workshops and coding exercises. All participating study centers applied the same occupational questionnaires and the same protocol for expert assessment. We assessed interrater agreement, finding reasonably good agreement between experts (κ between 0.53 and 0.64).23
Coders, blinded to case-control status, classified positions using the International Standard Classification of Occupation 1968 version (ISCO-68),24
while industries were coded according to the Statistical Classification of Economic Activities of the European Community, 1999 version (NACE-99).25
The present study reports the results of job and industry titles, while the analysis of specific exposures will be reported elsewhere.
We retained in the analysis 2-digit job and industry titles in which more than 10 cases had ever been employed. Several occupational categories that were previously associated with renal cell cancer, including employment in dry cleaning or exposure to solvents, 10–12, 17, 26–29
exposure to gasoline or its derivatives,17, 18
or employment as a firefighter,30, 31
had less than 10 cases per category. These results were reported in a supplemental table
We conducted tests for heterogeneity by study center, which showed that a minority of occupational categories exhibited heterogeneity. Random effects models were used in analysis. To control for potential confounders, we included in the regression models terms for study centre, age (5-year categories), sex, tobacco smoking (person-years), body mass index (less than 25, 25–29.9, 30 or more), hypertension (self-reported, yes/no), educational attainment (low, medium, high), and alcohol use (never drinkers, <8 ml/day, 8–18 ml/day, 18+ ml/day). We examined a potential confounding effect from urban vs. rural residence, but due to collinearity between that variable and some occupational categories, it was taken out of the final model. All statistical analyses were performed using SAS 9.1 (Cary, NC, USA). As some previous studies have reported gender-specific risks associated with occupational exposures,32
we also provided stratified effect estimates by gender.
When an increased risk (at p<0.10) was identified for a job or an industry title, we conducted further analyses to assess the effect of duration of employment. We additionally conducted sensitivity analyses, stratifying the agricultural findings by urban or rural residence.