Identification of spatio-temporal clusters of lung cancer cases in Pennsylvania, USA: 2010-2017

Influence of the atmospheric environment on spatial variation of lung cancer incidence in China

Conducting this research contributes to a deeper understanding of the correlation between atmospheric environmental quality and lung cancer incidence, and provides the scientific basis for formulating effective environmental protection and lung cancer prevention and control strategies. Lung cancer incidence in China has strong spatial variation. However, few studies have systematically revealed the characteristics of the spatial variation in lung cancer incidence, and have explained the causes of this spatial variation in lung cancer incidence from the perspectives of multiple components of the atmospheric environment to explain this spatial variation in lung cancer incidence. To address research limitations, we first analyze the spatial variation and spatial correlation characteristics of lung cancer incidence in China. Then, we build a spatial regression model using GeoDa software with lung cancer incidence as the dependent variable, five atmospheric environment factors-particulate matter 2.5 (PM2.5) concentration, temperature, atmospheric pressure, and elevation as explanatory variables, and four socio-economic characteristics as control variables to systematically analyze the influence and intensity of these factors on lung cancer incidence. The results show that lung cancer incidence in China has apparent changes in geographical and spatial unevenness, and spatial autocorrelation characteristics. In China, the lung cancer incidence is relatively high in Northeast China, while some areas of high lung cancer incidence still exist in Central China, Southwest China and South China, although the overall lung cancer incidence is relatively low. The atmospheric environment significantly affects lung cancer incidence. Different elements of the atmospheric environment vary in the direction and extent of their influence on the development of lung cancer. A 1% increase in PM2.5 concentration is associated with a level of 0.002975 increase in lung cancer incidence. Atmospheric pressure positively affects lung cancer incidence, and an increase in atmospheric pressure by 1% increases lung cancer incidence by a level of 0.026061. Conversely, a 1% increase in temperature is linked to a level of 0.006443 decreases in lung cancer incidence, and a negative correlation exists between elevation and lung cancer incidence, where an increase in elevation by 1% correlates with a decrease in lung cancer incidence by a level of 0.000934. The core influencing factors of lung cancer incidence in the seven geographical divisions of China exhibit variations. This study facilitates our understanding of the spatial variation characteristics of lung cancer incidence in China on a finer scale, while also offering a more diverse perspective on the impact of the atmospheric environment on lung cancer incidence.

Spatial and spatio-temporal clusters of lung cancer incidence by stage of disease in Michigan, United States 1985-2018

Lung cancer is the most common cause of cancer-related death in Michigan. Most patients are diagnosed at advanced stages of the disease. There is a need to detect clusters of lung cancer incidence over time, to generate new hypotheses about causation and identify high-risk areas for screening and treatment. The Michigan Cancer Surveillance database of individual lung cancer cases, 1985 to 2018 was used for this study. Spatial and spatiotemporal clusters of lung cancer and level of disease (localized, regional and distant) were detected using discrete Poisson spatial scan statistics at the zip code level over the study time period. The approach detected cancer clusters in cities such as Battle Creek, Sterling Heights and St. Clair County that occurred prior to year 2000 but not afterwards. In the northern area of the lower peninsula and the upper peninsula clusters of late-stage lung cancer emerged after year 2000. In Otter Lake Township and southwest Detroit, late-stage lung cancer clusters persisted. Public and patient education about lung cancer screening programs must remain a health priority in order to optimize lung cancer surveillance. Interventions should also involve programs such as telemedicine to reduce advanced stage disease in remote areas. In cities such as Detroit, residents often live near industry that emits air pollutants. Future research should therefore, continue to focus on the geography of lung cancer to uncover place-based risks and in response, the need for screening and health care services.

Air pollution and lung cancer survival in Pennsylvania

OBJECTIVE

Lung cancer is a leading cause of cancer death in the United States. Exposure to outdoor air pollution (OAP) is associated with increased lung cancer incidence, however little is known about the association of OAP and survival after diagnosis.

METHODS

We investigated the effects of OAP and lung cancer survival in Pennsylvania using data from Pennsylvania Cancer Registry. The study population consisted of 252,123 patients diagnosed between 1990 and 2017. The Environmental Protection Agency's ambient air monitoring network provided information on OAP exposure of NO₂, O₃, PM_2.5, and PM₁₀. Mean OAP exposures were calculated by interpolating exposure concentrations from the five nearest monitors within a 50-kilometer radius of each patient's residential address from date of diagnosis to date of death or last contact. Cox proportional-hazards models were used to estimate the hazard ratios (HR) for OAP exposures for overall and lung cancer-specific survival. Statistical analyses were stratified by SEER cancer stage groupings (localized, regional, and distant) and adjusted for individual-level and area-level covariates.

RESULTS

Median survival time was 0.76 [CIs: 0.75, 0.77] years for the study population and for localized, regional, and distant site diagnosis were 2.2 [CIs: 2.17, 2.23], 1.13 [CIs: 1.12, 1.15], and 0.42 [CIs: 0.41, 0.43] years, respectively. NO₂ indicated the greatest HR which increased with increasing magnitude of exposure across all cancer staging groups for deaths before 2-years post-diagnosis. HRs varied by stage and magnitude of OAP exposure with greatest overall effects shown in NO₂ followed by PM_2.5, O_3, and PM₁₀. A subgroup analysis of patients with treatment status information (2010-2017) showed similar associations of increasing HRs with increasing exposure.

CONCLUSION

These findings supported the hypotheses that OAP can influence the carcinogenic process, impairing chemotherapy treatment, and provide important public health implications since environmental factors are not often considered in prognosis of survival after diagnosis.