Geographical differences in cancer incidence in the Belgian province of Limburg.

Correctly addressing the questions of worried citizens with respect to possible clusters of cancer occurrence requires a risk communication strategy that is informed by a previously established analytical procedure. The aim of this study was to analyse cancer registration data in order to identify municipalities or clusters of municipalities with an increased incidence of one or more cancer types, adjusted for background characteristics at the same level. Ideally, the approach is proactive, straightforward, and easy for untrained citizens to follow and imprecision effects are taken into account. For all municipalities and most cancers, all relevant calculations were performed proactively and all methods and decision thresholds were defined beforehand. For each municipality, standardised incidence ratios (SIRs) were calculated and smoothed using a Poisson-gamma (PG) and a conditional autoregressive (CAR) model. Clusters were confirmed using the Spatial scan statistic of Kulldorff. Identified clusters were tested for possible confounders using all information that was available for each municipality. The Limburg Cancer Registry, serving the population of the Belgian province of Limburg (n=781 759) was used. We identified a possible cluster of increased prostate cancer incidence (smoothed SIRs around 1.2) and a cluster of increased bladder cancer incidence in males that included seven municipalities with CAR-smoothed SIRs between 1.5 and 2.1. SIRs followed a more or less circular decrease around the centre that was situated in Alken and Hasselt, the provincial capital. Bladder cancer incidence was positively related to an index of socio-economic status (SES) per municipality. No relationship was found with the other indexes that were available. 82% of all bladder cancers were transitional cell carcinomas (TCC). A repeated analysis based on TCCs only resulted in similar results with CAR-smoothed relative risks that tended to be even higher in the cluster zone. A pre-emptive analysis of possible cancer incidence clustering on the municipality level proved to be feasible.

Prostate-specific antigen screening coverage and prostate cancer incidence rates in the Belgian province of Limburg in 1996-1998.

According to the 1996-1998 cancer incidence report of the cancer registry of the Belgian province of Limburg (LIKAR), prostate cancer is the most common cancer in men with a crude invasive cancer incidence rate of 123.7 per 100000 person-years (125.4 and 81.8 after standardization for the European and the world standard population). In a study on geographical differences between the occurrence of cancers in municipalities, prostate cancer standardized incidence rates (SIRs) were significantly higher in a number of municipalities, with mean relative risks of 1.2 and 1.3 after full Bayesian smoothing. We hypothesized that prostate cancer incidence rates are largely influenced by the prostate-specific antigen (PSA) screening policy of local physicians and that differences between municipalities are more informative about local screening habits then about real differences in cancer occurrence. The aim of this study was to test this hypothesis by relating local prostate cancer SIRs to the PSA screening coverage of the population of men in each municipality. The SIRs of prostate cancer in 1996-1998 for each municipality were provided by LIKAR. They related to all histologically or cytologically proven new invasive prostate cancers during these years. For each municipality, PSA coverage data were provided by the largest sick fund of the region. Coverage was defined as the proportion of men above the age of 40 that was tested at least once within the registration period. The SIR of each municipality (dependent variable) was related to the age-standardized corresponding coverage (independent variable) by linear regression and was adjusted for the number of inhabitants per municipality: log (standardized incidence rate) = 164 + 602 * (standardized PSA coverage), = 0.12. The model explained 6% of the variance in incidence. In conclusion, in this study no statistically significant relationship was identified between PSA coverage and prostate cancer incidence rate per municipality. This could result from no such relationship existing or from low statistical power.