Cancer clusters in the USA: what do the last twenty years of state and federal investigations tell us?

Capturing emergency dispatch address points as geocoding candidates to quantify delimited confidence in residential geolocation

BACKGROUND

In response to citizens' concerns about elevated cancer incidence in their locales, US CDC proposed publishing cancer incidence at sub-county scales. At these scales, confidence in patients' residential geolocation becomes a key constraint of geospatial analysis. To support monitoring cancer incidence in sub-county areas, we presented summary metrics to numerically delimit confidence in residential geolocation.

RESULTS

We defined a concept of Residential Address Discriminant Power (RADP) as theoretically perfect within all residential addresses and its practical application, i.e., using Emergency Dispatch (ED) Address Point Candidates of Equivalent Likelihood (CEL) to quantify Residential Geolocation Discriminant Power (RGDP) to approximate RADP. Leveraging different productivity of probabilistic, deterministic, and interactive geocoding record linkage, we simultaneously detected CEL for 5,807 cancer cases reported to North Carolina Central Cancer Registry (NC CCR)- in January 2022. Batch-match probabilistic and deterministic algorithms matched 86.0% cases to their unique ED address point candidates or a CEL, 4.4% to parcel site address, and 1.4% to street centerline. Interactively geocoded cases were 8.2%. To demonstrate differences in residential geolocation confidence between enumeration areas, we calculated sRGDP for cancer cases by county and assessed the existing uncertainty within the ED data, i.e., identified duplicate addresses (as CEL) for each ED address point in the 2014 version of the NC ED data and calculated ED_sRGDP by county. Both summary RGDP (sRGDP) (0.62-1.00) and ED_sRGDP (0.36-1.00) varied across counties and were lower in rural counties (p < 0.05); sRGDP correlated with ED_sRGDP (r = 0.42, p < 0.001). The discussion covered multiple conceptual and economic issues attendant to quantifying confidence in residential geolocation and presented a set of organizing principles for future work.

CONCLUSIONS

Our methodology produces simple metrics - sRGDP - to capture confidence in residential geolocation via leveraging ED address points as CEL. Two facts demonstrate the usefulness of sRGDP as area-based summary metrics: sRGDP variability between counties and the overall lower quality of residential geolocation in rural vs. urban counties. Low sRGDP for the cancer cases within the area of interest helps manage expectations for the uncertainty in cancer incidence data. By supplementing cancer incidence data with sRGDP and ED_sRGDP, CCRs can demonstrate transparency in geocoding success, which may help win citizen trust.

Changes in spatial clusters of cancer incidence and mortality over 15 years in South Korea: Implication to cancer control

BACKGROUND

The temporal investigation of high-risk areas of cancer incidence and mortality can provide practical implications in cancer control. We aimed to investigate the changes in spatial clusters of incidence and mortality from 1999 through 2013 by major cancer types in South Korea.

METHODS

We applied flexible scan statistics to identify spatial clusters of cancer incidence and mortality by three 5-year periods and seven major cancer types using the counts of new cases and deaths and population in 244 districts during 1999-2013. Then, we compared the changes across three periods in the locations of primary clusters of incidence and mortality by cancer types. To explore the determinants that possibly affect cancer cluster areas, we compared geographic characteristics between clustered and non-clustered areas.

RESULTS

While incidence clusters for lung, stomach, and liver cancer remained in the same areas over 15 years, mortality clusters were relocated to the areas similar to those of incidence clusters. In contrast, colorectal, breast, cervical, and prostate cancer displayed consistently different locations of clusters over time, indicating the disappearance of existing clusters and the appearance of new clusters. Cluster areas tended to show higher portions of older population, unemployment, smoking, and cancer screening compared to non-cluster areas particularly for mortality.

CONCLUSIONS

Our findings of diverse patterns of changes in cancer incidence and mortality clusters over 15 years can indicate the degree of effectiveness in cancer prevention and treatment depending on the area and suggest the need for area-specific applications of different cancer control programs.

Investigating reports of cancer clusters in Canada: a qualitative study of public health communication practices and investigation procedures

INTRODUCTION:

Public health officials provide an important public service responding to community concerns around cancer and often receive requests to investigate patterns of cancer incidence and communicate findings with citizens. In this study, we identified procedures Canadian public health officials followed when investigating reports of cancer clusters, and explored the challenges officials faced conducting risk communication with communities.

METHODS:

Thirteen interviews were administered by telephone with 15 officials across Canadian jurisdictions and analyzed using thematic analysis. A content analysis of procedural documents received from five provinces was also undertaken.

RESULTS:

A third of provinces/territories in this study did not use any consistent guidelines to investigate reports of cancer clusters, a third used their own guidelines and a third used guidelines from other countries. Each Canadian jurisdiction identified a different agency or individual responsible for investigating cluster inquiries. Officials in most interviews considered public education to be the primary objective of risk communication during an investigation. Officials in only 4 of 13 interviews cited an overall positive response from the public after investigating reports of a cancer cluster.

CONCLUSION:

Differences in practices used to investigate suspected cancer clusters by public health officials were revealed in this work. Establishing pan-Canadian cancer cluster guidelines could improve procedural consistency across jurisdictions and offer enhanced opportunities to compare cluster responses for evaluation. A reporting system to track reported clusters may improve information sharing between federal, provincial/territorial and local investigators. During formal investigations, face-to-face participatory communication approaches should be explored to improve citizen engagement and manage community concerns.

Mapping the Way to Good Health: The Interdisciplinary Challenges of Geographers in Medical Research

Geography has an important role to play in shaping the direction of medical research. In particular, its tools and theory provide essential understanding to the impacts of place on health behaviors and outcomes. Understanding some of its evolution-particularly into the subfield of medical geography-is therefore useful both for geographers and medical researchers. In this paper, we present some of the debates that geographers have grappled with, the growth of GIS (particularly in the context of medical research), some important methodological considerations that geographers help center, and some recommendations for future work at this nexus. Throughout, we speak from the perspective of geographers who have worked nearly exclusively in the health sciences since obtaining our PhDs.

A Flexible Method for Identifying Spatial Clusters of Breast Cancer Using Individual-Level Data

Prior research has shown that cancer risk varies by geography, but scan statistics methods for identifying cancer clusters in case-control studies have been limited in their ability to identify multiple clusters and adjust for participant-level risk factors. We develop a method to identify geographic patterns of breast cancer odds using the Wisconsin Women's Health Study, a series of 5 population-based case-control studies of female Wisconsin residents aged 20-79 enrolled in 1988-2004 (cases=16,076, controls=16,795). We create sets of potential clusters by overlaying a 1 km grid over each county-neighborhood and enumerating a series of overlapping circles. Using a two-step approach, we fit a penalized binomial regression model to the number of cases and trials in each grid cell, penalizing all potential clusters by the least absolute shrinkage and selection operator (Lasso). We use BIC to select the number of clusters, which are included in a participant-level logistic regression model. We identify 15 geographic clusters, resulting in 23 areas of unique geographic odds ratios. After adjustment for known risk factors, confidence intervals narrowed but breast cancer odds ratios did not meaningfully change; one additional hotspot was identified. By considering multiple overlapping spatial clusters simultaneously, we discern gradients of spatial odds across Wisconsin.

Cancer and the Environment projects with four First Nations organizations: working together to address concerns about carcinogens in the environment

Setting

For First Nations people, human health and well-being are interconnected with a healthy environment. First Nations organizations commonly raise concerns regarding carcinogens in the environment; however, few case studies are available as guidance for working in a participatory and respectful way to help assess and address these concerns.

Intervention

Through four community-led pilot projects executed over two years, we collaborated with 15 participants from four First Nations organizations across four provinces to identify concerns related to environmental carcinogens and to address those concerns through an integrated knowledge translation (KT) approach. We co-developed and implemented strategic KT plans for each pilot project, and conducted evaluation surveys and interviews with participants at multiple time points to assess process, progress, barriers and facilitators, and impact.

Outcomes

The activities and outputs of the pilot projects are available at www.carexcanada.ca. Participants identified 18 concerns, and we co-developed 24 knowledge products. Tailored fact sheets for communities and briefing notes for leadership were deemed most useful; interactive maps were deemed less useful. Evaluation indicated that the collaborative projects were effective in addressing the concerns raised regarding exposures to carcinogens.

Implications

The participant-led approach and multi-year funding to support capacity enhancement and face-to-face engagement were facilitators to project success. However, participants did face important barriers to collaborate which should be considered in future projects of this kind: the most important being a lack of resources (people and time), given competing and often more urgent priorities.

Statistical methods for spatial cluster detection in childhood cancer incidence: A simulation study

BACKGROUND AND OBJECTIVE

The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of such clusters may help to better understand etiology and develop preventive strategies. We evaluated widely used statistical approaches to cluster detection in this context.

METHODS

Incidence of newly diagnosed childhood cancer (140/1,000,000 children under 15 years) and nephroblastoma (7/1,000,000) was simulated. Clusters of defined size (1-50) were randomly assembled on the district level in Germany. Each cluster was simulated with different relative risk levels (1-100). For each combination 2000 iterations were done. Simulated data was then analyzed by three local clustering tests: Besag-Newell method, spatial scan statistic and Bayesian Besag-York-Mollié with Integrated Nested Laplace Approximation approach. The operating characteristics (sensitivity, specificity, predictive values, power and correct classification) of all three methods were systematically described.

RESULTS

Performance varied considerably within and between methods, depending on the simulated setting. Sensitivity of all methods was positively associated with increasing size, incidence and RR of the high-risk area. Besag-York-Mollié showed highest specificity for minimally increased RR in most scenarios. The performance of all methods was lower in the nephroblastoma scenario compared with the scenario including all cancer cases.

CONCLUSION

This study illustrates the challenge to make reliable inferences on the existence of spatial clusters based on single statistical approaches in childhood cancer. Application of multiple methods, ideally with known operating characteristics, and a critical discussion of the joint evidence seems recommendable when aiming to identify high-risk clusters.

A causal inference framework for cancer cluster investigations using publicly available data

Often, a community becomes alarmed when high rates of cancer are noticed, and residents suspect that the cancer cases could be caused by a known source of hazard. In response, the US Centers for Disease Control and Prevention recommend that departments of health perform a standardized incidence ratio (SIR) analysis to determine whether the observed cancer incidence is higher than expected. This approach has several limitations that are well documented in the existing literature. In this paper we propose a novel causal inference framework for cancer cluster investigations, rooted in the potential outcomes framework. Assuming that a source of hazard representing a potential cause of increased cancer rates in the community is identified a priori, we focus our approach on a causal inference estimand which we call the causal SIR (cSIR). The cSIR is a ratio defined as the expected cancer incidence in the exposed population divided by the expected cancer incidence for the same population under the (counterfactual) scenario of no exposure. To estimate the cSIR we need to overcome two main challenges: 1) identify unexposed populations that are as similar as possible to the exposed one to inform estimation of the expected cancer incidence under the counterfactual scenario of no exposure, and 2) publicly available data on cancer incidence for these unexposed populations are often available at a much higher level of spatial aggregation (e.g. county) than what is desired (e.g. census block group). We overcome the first challenge by relying on matching. We overcome the second challenge by building a Bayesian hierarchical model that borrows information from other sources to impute cancer incidence at the desired level of spatial aggregation. In simulations, our statistical approach was shown to provide dramatically improved results, i.e., less bias and better coverage, than the current approach to SIR analyses. We apply our proposed approach to investigate whether trichloroethylene vapor exposure has caused increased cancer incidence in Endicott, New York.

Developmental toxicity of trichloroethylene in zebrafish (Danio rerio)

Trichloroethylene (TCE), an industrial solvent and degreaser, is an environmental toxicant that contaminates over half of Superfund sites, is a known carcinogen, and is linked to congenital defects and neurodegenerative disease. The developmental toxicity of TCE near ecologically relevant levels needs further characterization in order to better assess health risks of exposure. In this study, the toxicodynamics of TCE in the zebrafish (Danio rerio) model was investigated through the establishment of a LC50 concentration and by monitoring the acute developmental toxicity of ecologically relevant concentrations (0, 5, 50, and 500 parts per billion; ppb) of TCE during two different exposure lengths (1-72 hours post fertilization (hpf) and 1-120 hpf). Acute developmental toxicity was assessed by monitoring survival and hatching, larval morphology, larval heart rate, and behavioral responses during an embryonic photomotor response test and a larval visual motor response test. Embryonic exposure to TCE was associated with decreased percent hatch at 48 hpf, altered larval morphology, increased heart rate, and altered behavioral responses during the photomotor response test and visual motor response test. Larval morphology and behavioral alterations were more pronounced in the 1-120 hpf exposure length trials. The observed alterations suggest developmental TCE toxicity is still a concern at regulatory concentrations and that timing of exposure influences developmental toxicity.

Spatial-Temporal Cluster Analysis of Childhood Cancer in California

BACKGROUND

The observance of nonrandom space-time groupings of childhood cancer has been a concern of health professionals and the general public for decades. Many childhood cancers are suspected to have initiated in utero; therefore, we examined the spatial-temporal randomness of the birthplace of children who later developed cancer.

METHODS

We performed a space-time cluster analysis using birth addresses of 5,896 cases and 23,369 population-based, age-, sex-, and race/ethnicity-matched controls in California from 1997 to 2007, evaluating 20 types of childhood cancer and three a priori designated subgroups of childhood acute lymphoblastic leukemia (ALL). We analyzed data using a newly designed semiparametric analysis program, ClustR, and a common algorithm, SaTScan.

RESULTS

We observed evidence for nonrandom space-time clustering for ALL diagnosed at 2-6 years of age in the South San Francisco Bay Area (ClustR P = 0.04, SaTScan P = 0.07), and malignant gonadal germ cell tumors in a region of Los Angeles (ClustR P = 0.03, SaTScan P = 0.06). ClustR did not identify evidence of clustering for other childhood cancers, although SaTScan suggested some clustering for Hodgkin lymphoma (P = 0.09), astrocytoma (P = 0.06), and retinoblastoma (P = 0.06).

CONCLUSIONS

Our study provides evidence that childhood ALL diagnosed at 2-6 years and malignant gonadal germ cell tumors sporadically occurs in nonrandom space-time clusters. Further research is warranted to identify epidemiologic features that may inform the underlying etiology.

Protecting Children from Toxic Waste: Data-Usability Evaluation Can Deter Flawed Cleanup

Nearly 25 percent of US children live within 2 km of toxic-waste sites, most of which are in urban areas. They face higher rates of cancer than adults, partly because the dominant contaminants at most US hazardous-waste sites include genotoxic carcinogens, like trichloroethylene, that are much more harmful to children. The purpose of this article is to help protect the public, especially children, from these threats and to improve toxics-remediation by beginning to test our hypothesis: If site-remediation assessments fail data-usability evaluation (DUE), they likely compromise later cleanups and public health, especially children’s health. To begin hypothesis-testing, we perform a focused DUE for an unremediated, Pasadena, California toxic site. Our DUE methods are (a) comparing project-specific, remediation-assessment data with the remediation-assessment conceptual site model (CSM), in order to identify data gaps, and (b) using data-gap directionality to assess possible determinate bias (whether reported toxics risks are lower/higher than true values). Our results reveal (1) major CSM data gaps, particularly regarding Pasadena-toxic-site risks to children; (2) determinate bias, namely, risk underestimation; thus (3) likely inadequate remediation. Our discussion shows that if these results are generalizable, requiring routine, independent, DUEs might deter flawed toxic-site assessment/cleanup and resulting health threats, especially to children.

A survey of trace metal burdens in increment cores from eastern cottonwood (Populus deltoides) across a childhood cancer cluster, Sandusky County, OH, USA

A dendrochemical study of cottonwood trees (Populus deltoides) was conducted across a childhood cancer cluster in eastern Sandusky County (Ohio, USA). The justification for this study was that no satisfactory explanation has yet been put forward, despite extensive local surveys of aerosols, groundwater, and soil. Concentrations of eight trace metals were measured by ICP-MS in microwave-digested 5-year sections of increment cores, collected during 2012 and 2013. To determine whether the onset of the first cancer cases could be connected to an emergence of any of these contaminants, cores spanning the period 1970-2009 were taken from 51 trees of similar age, inside the cluster and in a control area to the west. The abundance of metals in cottonwood tree annual rings served as a proxy for their long-term, low-level accumulation from the same sources whereby exposure of the children may have occurred. A spatial analysis of cumulative metal burdens (lifetime accumulation in the tree) was performed to search for significant 'hotspots', employing a scan statistic with a mask of variable radius and center. For Cd, Cr, and Ni, circular hotspots were found that nearly coincide with the cancer cluster and are similar in size. No hotspots were found for Co, Cu, and Pb, while As and V were largely below method detection limits. Whereas our results do not implicate exposure to metals as a causative factor, we conclude that, after 1970, cottonwood trees have accumulated more Cd, Cr, and Ni, inside the childhood cancer cluster than elsewhere in Sandusky County.

ClustR: A Space-Time Cluster Analysis R Package for Individual-level Data

BACKGROUND

Until recently, large individual-level longitudinal data were unavailable to investigate clusters of disease, driving a need for suitable statistical tools. We introduce a robust, efficient, intuitive R package, ClustR, for space-time cluster analysis of individual-level data.

METHODS

We developed ClustR and evaluated the tool using a simulated dataset mirroring the population of California with constructed clusters. We assessed Cluster's performance under various conditions and compared it with another space-time clustering algorithm: SaTScan.

RESULTS

ClustR mostly exhibited high sensitivity for urban clusters and low sensitivity for rural clusters. Specificity was generally high. Compared with SaTScan, ClustR ran faster and demonstrated similar sensitivity, but had lower specificity. Select cluster types were detected better by ClustR than SaTScan and vice versa.

CONCLUSION

ClustR is a user-friendly, publicly available tool designed to perform efficient cluster analysis on individual-level data, filling a gap among current tools. ClustR and SaTScan exhibited different strengths and may be useful in conjunction.

Disparities in hepatocellular carcinoma incidence by race/ethnicity and geographic area in California: Implications for prevention

BACKGROUND

The incidence of hepatocellular carcinoma (HCC) has been rising rapidly in the United States. California is an ethnically diverse state with the largest number of incident HCC cases in the country. Characterizing HCC disparities in California may inform priorities for HCC prevention.

METHODS

By using data from the Surveillance, Epidemiology, and End Results 18-Registry Database and the California Cancer Registry, age-adjusted HCC incidence in California from 2009 through 2013 was calculated by race/ethnicity and neighborhood ethnic enclave status. A geographic analysis was conducted using Medical Service Study Areas (MSSAs) as the geographic unit, and race/ethnicity-specific standardized incidence ratios (SIRs) were calculated to identify MSSAs with higher-than-expected HCC incidence compared with the statewide average.

RESULTS

During 2009 through 2013, the age-adjusted incidence of HCC in California was the highest in Asians/Pacific Islanders (APIs) and Hispanics (>100% higher than whites), especially those living in more ethnic neighborhoods (20%-30% higher than less ethnic neighborhoods). Of the 542 MSSAs statewide, 42 had elevated HCC incidence (SIR ≥ 1.5; lower bound of 95% confidence interval > 1) for whites, 14 for blacks, 24 for APIs, and 36 for Hispanics. These MSSAs have 24% to 52% higher proportions of individuals below the 100% federal poverty line than other MSSAs.

CONCLUSIONS

APIs and Hispanics residing in more ethnic neighborhoods and individuals residing in lower income neighborhoods require more extensive preventive efforts tailored toward their unique risk factor profiles. The current race/ethnicity-specific geographic analysis can be extended to other states to inform priorities for HCC targeted prevention at the subcounty level, eventually reducing HCC burden in the country.

Residential cancer cluster investigation nearby a Superfund Study Area with trichloroethylene contamination

PURPOSE

Trichloroethylene (TCE) is an industrial solvent associated with liver cancer, kidney cancer, and non-Hodgkin's lymphoma (NHL). It is unclear whether an excess of TCE-associated cancers have occurred surrounding the Middlefield-Ellis-Whisman Superfund site in Mountain View, California. We conducted a population-based cancer cluster investigation comparing the incidence of NHL, liver, and kidney cancers in the neighborhood of interest to the incidence among residents in the surrounding four-county region.

METHODS

Case counts and address information were obtained using routinely collected data from the Greater Bay Area Cancer Registry, part of the Surveillance, Epidemiology, and End Results program. Population denominators were obtained from the 1990, 2000, and 2010 US censuses. Standardized incidence ratios (SIRs) with two-sided 99 % confidence intervals (CIs) were calculated for time intervals surrounding the US Censuses.

RESULTS

There were no statistically significant differences between the neighborhood of interest and the larger region for cancers of the liver or kidney. A statistically significant elevation was observed for NHL during one of the three time periods evaluated (1996-2005: SIR = 1.8, 99 % CI 1.1-2.8). No statistically significant NHL elevation existed in the earlier 1988-1995 (SIR = 1.3, 99 % CI 0.5-2.6) or later 2006-2011 (SIR = 1.3, 99 % CI 0.6-2.4) periods.

CONCLUSION

There is no evidence of an increased incidence of liver or kidney cancer, and there is a lack of evidence of a consistent, sustained, or more recent elevation in NHL occurrence in this neighborhood. This evaluation included existing cancer registry data, which cannot speak to specific exposures incurred by past or current residents of this neighborhood.

Evolution of research in health geographics through the International Journal of Health Geographics (2002-2015)

Health geographics is a fast-developing research area. Subjects broached in scientific literature are most varied, ranging from vectorial diseases to access to healthcare, with a recent revival of themes such as the implication of health in the Smart City, or a predominantly individual-centered approach. Far beyond standard meta-analyses, the present study deliberately adopts the standpoint of questioning space in its foundations, through various authors of the International Journal of Health Geographics, a highly influential journal in that field. The idea is to find space as the common denominator in this specialized literature, as well as its relation to spatial analysis, without for all that trying to tend towards exhaustive approaches. 660 articles have being published in the journal since launch, but 359 articles were selected based on the presence of the word “Space” in either the title, or the abstract or the text over 13 years of the journal’s existence. From that database, a lexical analysis (tag cloud) reveals the perception of space in literature, and shows how approaches are evolving, thus underlining that the scope of health geographics is far from narrowing.

Two Suspected Worksite or Occupational Cancer Clusters Investigated Using the Cancer Data Registry and Multiple Primary Standardized Incidence Ratios in SEER *Stat-Idaho, 2013-2014

BACKGROUND

Investigations of suspected cancer clusters are resource intensive and rarely identify true clusters: among 428 publicly reported US investigations during 1990-2011, only 1 etiologic cluster was identified. In 2013, the Cancer Data Registry of Idaho (CDRI) was contacted regarding a suspected cancer cluster at a worksite (Cluster A) and among an occupational cohort (Cluster B). We investigated to determine whether these were true clusters.

METHODS

We derived investigation cohorts for Cluster A from facility-provided employee records and for Cluster B from professional licensing records. We used Registry PlusTM Link Plus to conduct probabilistic linkage of cohort members to the CDRI registry and completed matching through manual review by using LexisNexis®, Accurint®, and the Social Security Death Index. We calculated standardized incidence ratios (SIR) using the MP-SIR session type in SEER*Stat and Idaho and US referent populations.

RESULTS

For Cluster A, we identified 34 cancer cases during 9,689 person-years; compared with Idaho and US rates, 95 percent CIs for SIRs included 1.0 for 24 of 24 primary site categories. For Cluster B, we identified 78 cancer cases during 15,154 person-years; compared with Idaho rates, 95 percent CI for SIRs included 1.0 for 23 of 24 primary site categories and was less than 1.0 for lung and bronchus cancers, and compared with US rates, 95 percent CI for SIRs included 1.0 for 22 of 24 primary site categories and was less than 1.0 for lung and bronchus and colorectal cancers.

CONCLUSION

We identified no statistically significant excess in cancer incidence in either cohort. SEER*Stat's MP-SIR is an efficient tool for performing SIR assessments, a Centers for Disease Control and Prevention/Council of State and Territorial Epidemiologists-recommended step when investigating suspected cancer clusters.

Racial disparities of pancreatic cancer in Georgia: a county-wide comparison of incidence and mortality across the state, 2000-2011

Understanding the geographic distribution of pancreatic cancer is important in assessing disease burden and identifying high‐risk populations. This study examined the geographic trends of pancreatic cancer incidence, mortality, and mortality‐to‐incidence ratios (MIRs) in Georgia, with a special focus on racial disparities of disease. Directly age‐adjusted pancreatic cancer incidence and mortality rates for Georgia counties (N = 159) were obtained for 2000–2011. Maps of county age‐adjusted disease rates and MIRs were generated separately for African Americans and Caucasians. Cluster analyses were conducted to identify unusual geographic aggregations of cancer cases or deaths. Pearson correlation coefficients were calculated to examine associations between county health factors (e.g., health behaviors, clinical care, and physical environment) and pancreatic cancer incidence or mortality rates. African Americans displayed a significantly higher age‐adjusted incidence (14.6/100,000) and mortality rate (13.3/100,000), compared to Caucasians. Cluster analyses identified five significant incidence clusters and four significant mortality clusters among Caucasians; one significant incidence cluster and two significant mortality clusters were identified among African Americans. Weak but significant correlations were noted between physical environment and pancreatic cancer incidence (ρ = 0.16, P = 0.04) and mortality (ρ = 0.18, P = 0.02) among African Americans. A disproportion burden of pancreatic cancer incidence and mortality was exhibited among African Americans in Georgia. Disease intervention efforts should be implemented in high‐risk areas, such as the southwest and central region of the state. Future studies should assess health behaviors and physical environment in relationship with the spatial distribution of pancreatic cancer.

Causes of genome instability: the effect of low dose chemical exposures in modern society

Genome instability is a prerequisite for the development of cancer. It occurs when genome maintenance systems fail to safeguard the genome's integrity, whether as a consequence of inherited defects or induced via exposure to environmental agents (chemicals, biological agents and radiation). Thus, genome instability can be defined as an enhanced tendency for the genome to acquire mutations; ranging from changes to the nucleotide sequence to chromosomal gain, rearrangements or loss. This review raises the hypothesis that in addition to known human carcinogens, exposure to low dose of other chemicals present in our modern society could contribute to carcinogenesis by indirectly affecting genome stability. The selected chemicals with their mechanisms of action proposed to indirectly contribute to genome instability are: heavy metals (DNA repair, epigenetic modification, DNA damage signaling, telomere length), acrylamide (DNA repair, chromosome segregation), bisphenol A (epigenetic modification, DNA damage signaling, mitochondrial function, chromosome segregation), benomyl (chromosome segregation), quinones (epigenetic modification) and nano-sized particles (epigenetic pathways, mitochondrial function, chromosome segregation, telomere length). The purpose of this review is to describe the crucial aspects of genome instability, to outline the ways in which environmental chemicals can affect this cancer hallmark and to identify candidate chemicals for further study. The overall aim is to make scientists aware of the increasing need to unravel the underlying mechanisms via which chemicals at low doses can induce genome instability and thus promote carcinogenesis.

Impacts of soil and water pollution on food safety and health risks in China

Environmental pollution and food safety are two of the most important issues of our time. Soil and water pollution, in particular, have historically impacted on food safety which represents an important threat to human health. Nowhere has that situation been more complex and challenging than in China, where a combination of pollution and an increasing food safety risk have affected a large part of the population. Water scarcity, pesticide over-application, and chemical pollutants are considered to be the most important factors impacting on food safety in China. Inadequate quantity and quality of surface water resources in China have led to the long-term use of waste-water irrigation to fulfill the water requirements for agricultural production. In some regions this has caused serious agricultural land and food pollution, especially for heavy metals. It is important, therefore, that issues threatening food safety such as combined pesticide residues and heavy metal pollution are addressed to reduce risks to human health. The increasing negative effects on food safety from water and soil pollution have put more people at risk of carcinogenic diseases, potentially contributing to 'cancer villages' which appear to correlate strongly with the main food producing areas. Currently in China, food safety policies are not integrated with soil and water pollution management policies. Here, a comprehensive map of both soil and water pollution threats to food safety in China is presented and integrated policies addressing soil and water pollution for achieving food safety are suggested to provide a holistic approach.

Brain Cancer in Workers Employed at a Laboratory Research Facility

BACKGROUND

An earlier study of research facility workers found more brain cancer deaths than expected, but no workplace exposures were implicated.

METHODS

Adding four additional years of vital-status follow-up, we reassessed the risk of death from brain cancer in the same workforce, including 5,284 workers employed between 1963, when the facility opened, and 2007. We compared the work histories of the brain cancer decedents in relationship to when they died and their ages at death.

RESULTS

As in most other studies of laboratory and research workers, we found low rates of total mortality, total cancers, accidents, suicides, and chronic conditions such as heart disease and diabetes. We found no new brain cancer deaths in the four years of additional follow-up. Our best estimate of the brain cancer standardized mortality ratio (SMR) was 1.32 (95% confidence interval [95% CI] 0.66-2.37), but the SMR might have been as high as 1.69. Deaths from benign brain tumors and other non-malignant diseases of the nervous system were at or below expected levels.

CONCLUSION

With the addition of four more years of follow-up and in the absence of any new brain cancers, the updated estimate of the risk of brain cancer death is smaller than in the original study. There was no consistent pattern among the work histories of decedents that indicated a common causative exposure.

Inflammatory breast cancer clusters: A hypothesis

Cancer clusters have long been a focus of interest because of the possibility of identifying etiologic agents. Only on rare occasions, however, have such cluster investigations been successful. One major difficulty in cluster investigations, particularly in the area of breast cancer, is the long latent period. There have been a number of publications providing a discouraging picture regarding cancer cluster investigations. The possibility of learning from a cluster investigation, however, is greatly increased if the cancer involved is relatively rare and if it has a short latent period. Inflammatory breast cancer (IBC) fits these criteria and is worth pursuing because of the strong evidence that environmental factors play a major role. In this report we describe our experience with several clusters and the lessons learned which are now being utilized to improve investigation of future IBC clusters. The first IBC cluster that we evaluated was in 2000, when we were asked to investigate an apparent cluster of IBC in Castro Valley, California where three women in an office setting of 24 people were diagnosed with IBC in a ten month period from May 1999 to March 2000. Our investigation of this striking cluster did not yield a specific trigger for this cluster but it did indicate that the women involved all had at least two IBC risk factors that may well have made them susceptible to getting IBC. We are now investigating another apparent cluster in Texas and are aware of several others requiring careful consideration. We see a need for a consistent protocol for the evaluation of IBC clusters focusing on the laboratory investigation of environmental triggers, primarily infectious agents and chemical carcinogens.

Evaluating geostatistical modeling of exceedance probability as the first step in disease cluster investigations: very low birth weights near toxic Texas sites

BACKGROUND

The first step in evaluating potential geographic clusters of disease calls for an evaluation of the disease risk comparing the risk in a defined location to the risk in neighboring locations. Environmental exposures, however, represent continuous exposure levels across space not an exposure with a distinct boundary. The objectives of the current study were to adapt, apply and evaluate a geostatistical approach for identifying disease clusters.

METHODS

The exceedance probability for very low birth weight (VLBW; < 1.5 kg) infants was mapped using an Intrinsic Conditional Autoregressive model. The data were applied to a 20 by 20 grid of 1 km2 pixels centered on each of the 13 National Priority List Superfund Sites in Harris County, Texas.

RESULTS

Large clusters of VLBW were identified in close proximity to four of the 13 Superfund Sites. Three of the Superfund Sites, associated with disease clusters, were located close together in central Houston and these sites may have been surrounded by a single, confluent disease cluster.

CONCLUSIONS

Geostatistical modeling of the exceedance probability for very low birth weights identified disease clusters of varying size, shape and statistical certainty near Superfund Sites in Harris County, Texas. The approach offers considerable potential as the first step for investigating potential disease clusters.

Stop and listen to the people: an enhanced approach to cancer cluster investigations

Cancer cluster investigations need to address the disconnect between traditional public health approaches and human needs. Cancer cluster investigations often magnify fear and uncertainty because they rarely find a definitive environmental cause. Traditional approaches emphasize population-level data analysis and undervalue active listening. Because few studies have explored active listening in cancer cluster investigations, we conducted a descriptive oral history case study of a Frederick, Maryland, investigation. We interviewed 12 community members and 9 public health professionals about the investigation of a perceived cancer cluster. Many believed it was linked to environmental contamination at Fort Detrick, a local US Army base. We propose enhanced active listening that seeks out peoples' perspectives, validates their concerns, and engages them in the investigative process.

Cancer cluster investigations: review of the past and proposals for the future

Residential clusters of non-communicable diseases are a source of enduring public concern, and at times, controversy. Many clusters reported to public health agencies by concerned citizens are accompanied by expectations that investigations will uncover a cause of disease. While goals, methods and conclusions of cluster studies are debated in the scientific literature and popular press, investigations of reported residential clusters rarely provide definitive answers about disease etiology. Further, it is inherently difficult to study a cluster for diseases with complex etiology and long latency (e.g., most cancers). Regardless, cluster investigations remain an important function of local, state and federal public health agencies. Challenges limiting the ability of cluster investigations to uncover causes for disease include the need to consider long latency, low statistical power of most analyses, uncertain definitions of cluster boundaries and population of interest, and in- and out-migration. A multi-disciplinary Workshop was held to discuss innovative and/or under-explored approaches to investigate cancer clusters. Several potentially fruitful paths forward are described, including modern methods of reconstructing residential history, improved approaches to analyzing spatial data, improved utilization of electronic data sources, advances using biomarkers of carcinogenesis, novel concepts for grouping cases, investigations of infectious etiology of cancer, and "omics" approaches.

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

Background

There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany.

Methods

Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves.

Results

With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation.

Conclusion

High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage.