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Background: Dioxins and polychlorobiphenyls (PCBs) are persistent organic pollutants that have demonstrated endocrine disrupting properties. Several of these chemicals are carcinogenic and positive associations have been suggested with breast cancer risk. In general population, diet represents the main source of exposure. Methods: Associations between dietary intake of 17 dioxins and 35 PCBs and breast cancer were evaluated in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from nine European countries using multivariable Cox regressions. The present study included 318,607 women (mean ± SD age: 50.7 ± 9.7) with 13,241 incident invasive breast cancers and a median follow-up of 14.9 years (IQR = 13.5–16.4). Dietary intake of dioxins and PCBs was assessed combining EPIC food consumption data with food contamination data provided by the European Food Safety Authority. Results: Exposure to dioxins, dioxins + Dioxin-Like-PCBs, Dioxin-Like-PCBs (DL-PCBs), and Non-Dioxin-Like-PCBs (NDL-PCBs) estimated from reported dietary intakes were not associated with breast cancer incidence, with the following hazard ratios (HRs) and 95% confidence intervals for an increment of 1 SD: HRdioxins = 1.00 (0.98 to 1.02), HRdioxins+DL-PCB = 1.01 (0.98 to 1.03), HRDL-PCB = 1.01 (0.98 to 1.03), and HRNDL-PCB = 1.01 (0.99 to 1.03). Results remained unchanged when analyzing intakes as quintile groups, as well as when analyses were run separately per country, or separating breast cancer cases based on estrogen receptor status or after further adjustments on main contributing food groups to PCBs and dioxins intake and nutritional factors. Conclusions: This large European prospective study does not support the hypothesis of an association between dietary intake of dioxins and PCBs and breast cancer risk.

Objetivo: Validar la capacidad del Conjunto Mínimo Básico de Datos (CMBD) para detectar casos incidentes de cáncer de colon y recto utilizando como estándar de referencia el Registro de Cáncer de Murcia (RCM) y medir la concordancia entre el CMBD y el registro de cáncer en tumores colorrectales. Material y método: Estudio de validación transversal del CMBD del Hospital Virgen de la Arrixaca de Murcia. La población de estudio son los casos incidentes de colon-recto del año 2000 del RCM y los casos del CMBD en el citado hospital para el mismo año con algún código diagnóstico CIE-9 entre 153.0 y 154.1 eliminando reingresos. Durante el proceso se van a realizar 2 análisis: sólo con el diagnóstico principal y con todos los diagnósticos. Se calcula la sensibilidad, la especificidad, el valor predictivo positivo (VPP) y negativo (VPN) y la concordancia con sus intervalos de confianza (IC) del 95%. Resultados: Con sólo el primer diagnóstico, el CMBD detecta el 80% de los casos incidentes de cáncer colorrectal con un VPP del 75%; considerando todos los diagnósticos, detecta el 85% con un VPP del 64%. La concordancia en la codificación es elevada tanto con 3 dígitos (índice kappa del 88% (IC del 95%, 0,79-0,97) en primer diagnóstico, y del 89% (IC del 95%, 0,80-0,97) en todos los diagnósticos) como de 4 dígitos (índice kappa del 77% (IC del 95%, 0,68-0,85) en el primer diagnóstico, y del 78% (IC del 95%, 0,70-0,86) en todos diagnósticos) en ambos análisis. Conclusiones: El CMBD es una buena fuente para detectar casos incidentes de cáncer al presentar una elevada sensibilidad. La alta concordancia encontrada en las localizaciones tumorales de colon-recto contribuye a consolidar el CMBD como fuente de datos para los registros de cáncer.Objectives: To validate the ability of a hospital administration data set (minimum data set [MDS]) to detect incident cases of colorectal cancer using the Murcia Cancer Registry (MCR) as the gold standard and to measure agreement between the MDS and registration of colorectal cancer. Material and method: A cross sectional validation study of the MDS of the main hospital in the region of Murcia (Spain) was conducted. The study population consisted of incident cases of colorectal cancer in 2000 obtained from the MCR and cases in the MDS of the above-mentioned hospital for the same year with an ICD-9 diagnostic code between 153.0 and 154.1, eliminating readmissions. During the process, two analyses were performed: one analysis with the principal diagnosis only and another with all the diagnostic codes. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and agreement was calculated with their 95% confidence intervals (CI). Results: With the first diagnosis only, the MDS detected 80% of the incident cases of colorectal cancer with a PPV of 75%. With all the diagnoses, the MDS detected 85% of the cases with a PPV of 64%. The agreement in codification was high at three digits (kappa 88% (95% CI, 0.79-0.97) first diagnosis, 89% (95% CI, 0.80-0.97) all diagnoses) as well as at four digits (kappa 77% (IC, 0.68-0.85) first diagnosis, 78% (95% CI, 0.70-0.86) all diagnoses) in both analyses. Conclusions: Because of its high sensitivity, the MDS is a good source for detecting incident cases of cancer. The high agreement found in the site of colorectal cancer helps to consolidate the MDS as a data source for cancer registration.

Background: Self-reported data about environmental exposures can lead to measurement error. Objectives: To validate the self-reported perception of proximity to industrial facilities. Methods: MCC-Spain is a population-based multicase-control study of cancer in Spain that recruited incident cases of breast, colorectal, prostate, and stomach cancer. The participant’s current residence and the location of the industries were geocoded, and the linear distance between them was calculated (gold standard). The epidemiological questionnaire included a question to determine whether the participants perceived the presence of any industry at ≤1 km from their residences. Sensitivity and specificity of individuals' perception of proximity to industries were estimated as measures of classification accuracy, and the area under the curve (AUC) and adjusted odds ratios (aORs) of misclassification were calculated as measures of discrimination. Analyses were performed for all cases and controls, and by tumor location, educational level, sex, industrial sector, and length of residence. Finally, aORs of cancer associated with real and self-reported distances were calculated to explore differences in the estimation of risk between these measures. Results: Sensitivity of the questionnaire was limited (0.48) whereas specificity was excellent (0.89). AUC was sufficient (0.68). Participants with breast (aOR(95%CI) = 2.03 (1.67;2.46)), colorectal (aOR(95%CI) = 1.41 (1.20;1.64)) and stomach (aOR(95%CI) = 1.59 (1.20;2.10)) cancer showed higher risk of misclassification than controls. This risk was higher for lower educational levels (aOR15 years (95%CI) = 0.56 (0.36;0.85)). The use of self-reported proximity vs. real distance to industrial facilities biased the effect on cancer risk towards the nullity. Conclusions: Self-reported distance to industrial facilities can be a useful tool for hypothesis generation, but hypothesis-testing studies should use real distance to report valid conclusions. The sensitivity of the question might be improved with a more specific formulation. Keywords: Self-reported perception, Residential proximity, Case-control study, Sensitivity, Specificity, AUC, Industrial pollution, MCC-Spain