Space-Time Analysis of Testicular Cancer Clusters Using Residential Histories: A Case-Control Study in Denmark

Abstract

Though the etiology is largely unknown, testicular cancer incidence has seen recent significant increases in northern Europe and throughout many Western regions. The most common cancer in males under age 40, age period cohort models have posited exposures in the in utero environment or in early childhood as possible causes of increased risk of testicular cancer. Some of these factors may be tied to geography through being associated with behavioral, cultural, sociodemographic or built environment characteristics. If so, this could result in detectable geographic clusters of cases that could lead to hypotheses regarding environmental targets for intervention. Given a latency period between exposure to an environmental carcinogen and testicular cancer diagnosis, mobility histories are beneficial for spatial cluster analyses. Nearest-neighbor based Q-statistics allow for the incorporation of changes in residency in spatial disease cluster detection. Using these methods, a space-time cluster analysis was conducted on a population-wide case-control population selected from the Danish Cancer Registry with mobility histories since 1971 extracted from the Danish Civil Registration System. Cases (N=3297) were diagnosed between 1991 and 2003, and two sets of controls (N=3297 for each set) matched on sex and date of birth were included in the study. We also examined spatial patterns in maternal residential history for those cases and controls born in 1971 or later (N= 589 case-control pairs). Several small clusters were detected when aligning individuals by year prior to diagnosis, age at diagnosis and calendar year of diagnosis. However, the largest of these clusters contained only 2 statistically significant individuals at their center, and were not replicated in SaTScan spatial-only analyses which are less susceptible to multiple testing bias. We found little evidence of local clusters in residential histories of testicular cancer cases in this Danish population.

Comparing spatial patterns of 11 common cancers in Mainland China

“…Male breast cancer is a rare carcinoma, and there is no evidence of its spatial clustering [ 66 ]. A study using population-level data in Britain [ 67 ] and a study using individual-level data in Denmark [ 68 ] did not find evidence of spatial clustering in testicular cancer. Environmental or human behavioral factors might not play a strong role in the spatial pattern of these cancers.…”

Evidence of Transgenerational Effects on Autism Spectrum Disorder Using Multigenerational Space-Time Cluster Detection

“…The Bernoulli model is a discrete binomial distribution scan statistic that tests for binary outcomes; 'case' or 'non-case' present in a population at any given place and time using varying size elliptical cylinder windows. [39][40][41] One of the advantages of using the Bernoulli distribution is its sensitivity to point-level location data in case and non-case populations. The statistical signi cance of each cluster (p < 0.05) was estimated using Monte Carlo simulation with 999 permutations representing the random placement of cases.…”

Evidence of transgenerational effects on autism spectrum disorder using multigenerational space-time cluster detection

“…A spatial scan statistic Bernoulli space-time binomial distribution model was used to identify space-time clusters for each group of ancestors at each of the three exposure windows. The Bernoulli model is a discrete binomial distribution scan statistic that tests for binary outcomes; 'case' or 'non-case' present in a population at any given place and time using varying size elliptical cylinder windows [38][39][40]. One of the advantages of using the Bernoulli distribution is its sensitivity to pointlevel location data in case and non-case populations.…”