Air pollution and lung cancer survival in Pennsylvania

Impact of air pollution on the progress-free survival of non-small cell lung cancer patients with anti-PD-1/PD-L1 immunotherapy: A cohort study

Air pollution is a well-established risk factor for lung cancer, but limited evidence exists on its impact on the treatment of lung cancer. The objective of this study was to investigate the impact of key pollutants on the efficacy of PD-1/PD-L1 inhibitor immunotherapy in non-small cell lung cancer (NSCLC) patients, thereby providing clinicians with evidence to potentially enhance the efficacy of PD-1 therapy and inform policy decisions for cancer care. To this end, we conducted a study involving 361 NSCLC patients who received PD-1/PD-L1 inhibitor immunotherapy, examining the correlation between air pollution exposure and progression-free survival (PFS) following immunotherapy treatment. Their moving-average ambient levels up to 1 year of PM2.5 and its constituents (organic matter (OM), black carbon (BC), nitrate (NO3-), sulfate (SO42-), and ammonium (NH4+)), as well as ozone (O3) were estimated using the Tracking Air Pollution in China dataset. Cox proportional hazards models were adopted to estimate the effects of exposure to each pollutant on PFS risk for NSCLC. 179 patients obtained the progression of NSCLC. While PM2.5 exposure prior to the immunotherapy was not associated with NSCLC progression, long-term exposure to BC and OM, the important organic components of PM2.5, were significantly associated with a higher risk of NSCLC progression with corresponding hazard ratios (HRs, 95% confidence intervals) of 2.42 (1.39, 4.23) and 2.41 (1.40, 4.14) for 1-year moving average, respectively. Short-term exposure to O3 was also associated with PFS with a HR of 1.64 (1.08, 2.50) for 3-month averaged exposure. Monotonic increasing dose-response relationships were further observed for the associations of BC, OM and O3 with PFS. Our findings imply the need of implementing effective measures for targeted reduction in specific sources of PM2.5 constituents (especially BC and OM) and O3 at different time windows to improve the prognosis of NSCLC patients especially for their PFS.

Ambient beta particle radioactivity and lung cancer survival: Results from the Boston Lung Cancer Study

BACKGROUND

Exposure to ionizing radiation is known to increase the risk of lung cancer. However, studies on the effect of environmental radiation associated with ambient particle air pollution on lung cancer survival are limited. We investigated the association between ambient beta particle radioactivity (PR-β) after a diagnosis and lung cancer survivals.

METHODS

The Boston Lung Cancer Survival (BLCS) cohort consisted of histologically confirmed patients enrolled at Massachusetts General Hospital (MGH) and the Dana-Farber Cancer Institute (DFCI) in Boston, U.S. The primary outcomes included overall survival, 5-year survival, and 3-year survival probability. We estimated ambient PR-β exposure at the ZIP code of residence from 2001 through 2017. Cox-proportional hazards models were constructed to estimate hazard ratios (HRs) for the associations between ambient PR-β and survival outcomes while controlling for covariates.

RESULTS

The analysis included 2795 patients with complete information, with 97,330 person-months of follow-up. The interquartile range (IQR) increase in PR-β was significantly associated with worse overall survival (HR:1.63, 95% CI:1.52, 1.76), 5-year survival (HR:1.33, 95% CI:1.23, 1.44), and 3-year survival (HR:1.22, 95% CI:1.12, 1.33) while adjusting for covariates, including age at diagnosis, sex, race, smoking, stage, histology, and adjusted gross income. Similar associations were found while additionally adjusting for the estimated residential radon exposure. In addition, the survival associated with PR-β exposure was significantly worse for patients in the early stages (HR:2.16, 95% CI:1.84, 2.52).

CONCLUSION

The findings from this study provide new evidence suggesting that environmental exposure to radioactive particles after lung cancer diagnosis may have a pronounced effect on survival, particularly in patients with early stages.

The association between ambient PM2.5's constituents exposure and cervical cancer survival

Increasing evidence links exposure to ambient particulate matter with a diameter less than 2.5 μm (PM2.5) with reduced survival in cancer survivors, but little was known about the association between PM2.5 exposure and cervical cancer survival. We analyzed data from 5144 cervical cancer patients diagnosed between January 2014 and December 2020, who completed recommended treatments. Exposure levels were determined by the monthly average concentration of ambient PM2.5 and its five constituents, obtained from Tracking Air Pollution in China (TAP) based on individual residential addresses. Log-rank tests and multivariate Cox Proportional Hazardous regression were performed to examine the impacts of PM2.5 and its constituents on overall survival (OS) of cervical cancer patients. We observed that for every increase of 1 μg/m3 in average individual exposure, the hazard ratios (95%CI) for ambient PM2.5, sulfate (SO42-), ammonium (NH4+), and nitrates (NO3-) were 1.078(1.069-1.086), 6.755(5.707-7.996), 2.123(1.935-2.329), and 3.717(3.237-4.267), respectively. Subgroups with longer OS had larger HRs of PM2.5 and its constituents, which might attributed to more cumulative exposure. No evidence of a threshold for the hazardous effects of PM2.5 on the OS of cervical cancer patients was identified. Furthermore, long-term exposure to PM2.5 was negatively associated with pretreatment counts of monocytes, neutrophils, and lymphocytes in peripheral blood of cervical cancer patients. In conclusion, elevated levels of PM2.5 mass, SO42-, NH4+, and NO3- in ambient PM2.5 exposure were associated with reduced OS among cervical cancer patients. There may be no discernible threshold effect of PM2.5 on the risk for cervical cancer patients.

The Effects of Environmental Factors on General Human Health: A Scoping Review

Background/Objectives: The external environment constantly influences human health through many factors, including air quality, access to green spaces, exposure to pollutants, and climate change. Contamination poses a substantial threat to human well-being; conversely, environmental factors also positively impact health. The purpose of this study is to provide a comprehensive review of the complex relationship between various environmental factors and human health. While individual studies have explored specific aspects, a broader integrative understanding is lacking. Methods: Through databases (PubMed, Cochrane, Copernicus), 4888 papers were identified, with 166 selected for detailed analysis. Results: We summarized recent research, identifying multiple associations between environmental factors such as air pollution, climate change, solar radiation, and meteorological conditions and their impact on various health outcomes, including respiratory, cardiovascular, metabolic and gastrointestinal, renal and urogenital, neurological and psychological health, infectious and skin diseases, and major cancers. We use chord diagrams to illustrate these links. We also show the interaction between different environmental factors. Findings begin with exploring the direct impact of environmental factors on human health; then, the interplay and combined effects of environmental factors, elucidating their (often indirect) interaction and collective contribution to human health; and finally, the implications of climate change on human health. Conclusions: Researchers and policymakers need to consider that individuals are exposed to multiple pollutants simultaneously, the "multipollutant exposure phenomenon". It is important to study and regulate environmental factors by considering the combined impact of various pollutants rather than looking at each pollutant separately. We emphasize actionable recommendations and solutions.

Causal effects of air pollutants on lung function and chronic respiratory diseases: a Mendelian randomization study

Objectives

Our study aims to clarify the causality between air pollutants and lung function, chronic respiratory diseases, and the potential mediating effects of inflammatory proteins.

Method

We employed Mendelian Randomization (MR) analysis with comprehensive instrumental variables screening criteria to investigate the effects of air pollutants on lung function and chronic lung diseases. Our study incorporated genetic instruments for air pollutants, ensuring F-statistics above 20.86. A total of 18 MR analyses were conducted using the inverse-variance weighted approach, along with heterogeneity and pleiotropy tests to validate the results. Mediated MR analysis was utilized to evaluate the inflammatory proteins mediating the effects of air pollutants.

Result

MR analysis demonstrated significant causal interactions of particulate matter 2.5 (PM2.5), PM10, and Nitrogen dioxide (NO2) with lung function decline. Specifically, PM10 negatively affected forced expiratory volume in one second (FEV1) (OR: 0.934, 95% CI: 0.904-0.965, p = 4.27 × 10-5), forced vital capacity (FVC) (OR: 0.941, 95% CI: 0.910-0.972, p = 2.86 × 10-4), and FEV1/FVC (OR: 0.965, 95% CI: 0.934-0.998, p = 0.036). PM2.5 and NO2 were identified as potential risk factors for impairing FEV1 (OR: 0.936, 95% CI: 0.879-0.998, p = 0.042) and FEV1/FVC (OR: 0.943, 95% CI: 0.896-0.992, p = 0.024), respectively. For chronic respiratory diseases, PM2.5 and NO2 were associated with increased COPD incidence (OR: 1.273, 95% CI: 1.053-1.541, p = 0.013 for PM2.5; OR: 1.357, 95% CI: 1.165-1.581, p = 8.74 × 10-5 for NO2). Sensitivity analyses confirmed the robustness of these findings, with no significant heterogeneity or horizontal pleiotropy detected.

Conclusion

Our study ascertained the causal correlations of air pollutants with lung function and COPD, emphasizing the importance of reducing air pollution. Interleukin-17A mediates the reduction of FEV1 and FVC by PM10, revealing potential therapeutic targets.

Area-Level Social Vulnerability and Severe COVID-19: A Case-Control Study Using Electronic Health Records from Multiple Health Systems in the Southeastern Pennsylvania Region

Knowledge about neighborhood characteristics that predict disease burden can be used to guide equity-based public health interventions or targeted social services. We used a case-control design to examine the association between area-level social vulnerability and severe COVID-19 using electronic health records (EHR) from a regional health information hub in the greater Philadelphia region. Severe COVID-19 cases (n = 15,464 unique patients) were defined as those with an inpatient admission and a diagnosis of COVID-19 in 2020. Controls (n = 78,600; 5:1 control-case ratio) were a random sample of individuals who did not have a COVID-19 diagnosis from the same geographic area. Retrospective data on comorbidities and demographic variables were extracted from EHR and linked to area-level social vulnerability index (SVI) data using ZIP codes. Models adjusted for different sets of covariates showed incidence rate ratios (IRR) ranging from 1.15 (95% CI, 1.13-1.17) in the model adjusted for individual-level age, sex, and marital status to 1.09 (95% CI, 1.08-1.11) in the fully adjusted model, which included individual-level comorbidities and race/ethnicity. The fully adjusted model indicates that a 10% higher area-level SVI was associated with a 9% higher risk of severe COVID-19. Individuals in neighborhoods with high social vulnerability were more likely to have severe COVID-19 after accounting for comorbidities and demographic characteristics. Our findings support initiatives incorporating neighborhood-level social determinants of health when planning interventions and allocating resources to mitigate epidemic respiratory diseases, including other coronavirus or influenza viruses.

Correlation of time trends of air pollutants, greenspaces and tracheal, bronchus and lung cancer incidence and mortality among the adults in United States

Background

Tracheal, Bronchus, and Lung (TBL) cancer continues to represent the majority of cancer-related incidence and mortality in United States (U.S.). While air pollutants are considered essential risk factors, both global and national average concentrations of major harmful air pollutants have significantly decreased over the decades. Green space may have a beneficial effect on human health.

Methods

We obtained data on national and state-level burden of TBL cancer, the annual average concentration of main air pollutants, and levels of green spaces in 2007, 2013, and 2019. According to generalized estimating equation (GEE), we examine the associations among incidence and mortality of TBL cancer, air pollutants, and greenspaces, represented by the Normalized Difference Vegetation Index (NDVI) in different age groups with models adjusted with meteorological, and socio-demographic. We observed additional effects of the interaction between the NDVI, Ozone, PM2.5, and other factors, which helped us to interpret and understand our results. Also, we collated states that witnessed net increments in forest coverage and conducted the same analysis separately.

Results

In our analysis, the majority of associations between NDVI and air pollutants with TBL cancer remained significantly positive, particularly noticeable among individuals aged 20 to 54. However, our findings did not explore air pollution as a potential mediator between greenspace exposure and TBL cancer. While the associations of PM2.5 with TBL cancer remained positive, the other four pollutants showed positive but statistically insignificant associations. Our interaction analysis yielded that there were positive associations between NDVI and ozone, PM2.5, and tobacco use. Max NDVI acts as a protective factor along with high HDI. Additionally, PM2.5 and HDI also showed a negative association. In 18 states with more forest, NDVI acts as a protective factor along with higher health care coverage, better health status, and participation in physical activities.

Conclusion

In the state-level of U.S., the effects of total greenspace with TBL cancer are mixed and could be modified by various socio-economic factors. PM2.5 has a direct correlation with TBL cancer and the effects can be influenced by underlying socioeconomic conditions.

Air pollution and survival in patients with malignant mesothelioma and asbestos-related lung cancer: a follow-up study of 1591 patients in South Korea

BACKGROUND

Despite significant advancements in treatments such as surgery, radiotherapy, and chemotherapy, the survival rate for patients with asbestos-related cancers remains low. Numerous studies have provided evidence suggesting that air pollution induces oxidative stress and inflammation, affecting acute respiratory diseases, lung cancer, and overall mortality. However, because of the high case fatality rate, there is limited knowledge regarding the effects of air pollution exposures on survival following a diagnosis of asbestos-related cancers. This study aimed to determine the effect of air pollution on the survival of patients with malignant mesothelioma and asbestos-related lung cancer.

METHODS

We followed up with 593 patients with malignant mesothelioma and 998 patients with lung cancer identified as asbestos victims between 2009 and 2022. Data on five air pollutants-sulfur dioxide, carbon monoxide, nitrogen dioxide, fine particulate matter with a diameter < 10 μm, and fine particulate matter with a diameter < 2.5 μm-were obtained from nationwide atmospheric monitoring stations. Cox proportional hazard models were used to estimate the association of cumulative air pollutant exposure with patient mortality, while adjusting for potential confounders. Quantile-based g-computation was used to assess the combined effect of the air pollutant mixture on mortality.

RESULTS

The 1-, 3-, and 5-year survival rates for both cancer types decreased with increasing exposure to all air pollutants. The estimated hazard ratios rose significantly with a 1-standard deviation increase in each pollutant exposure level. A quartile increase in the pollutant mixture was associated with a 1.99-fold increase in the risk of malignant mesothelioma-related mortality (95% confidence interval: 1.62, 2.44). For lung cancer, a quartile increase in the pollutant mixture triggered a 1.87-fold increase in the mortality risk (95% confidence interval: 1.53, 2.30).

CONCLUSION

These findings support the hypothesis that air pollution exposure after an asbestos-related cancer diagnosis can negatively affect patient survival.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

Construction and validation of a nomogram to predict the overall survival of small cell lung cancer: a multicenter retrospective study in Shandong province, China

BACKGROUND

Patients diagnosed with small cell lung cancer (SCLC) typically experience a poor prognosis, and it is essential to predict overall survival (OS) and stratify patients based on distinct prognostic risks.

METHODS

Totally 2309 SCLC patients from the hospitals in 15 cities of Shandong from 2010 - 2014 were included in this multicenter, population-based retrospective study. The data of SCLC patients during 2010-2013 and in 2014 SCLC were used for model development and validation, respectively. OS served as the primary outcome. Univariate and multivariate Cox regression were applied to identify the independent prognostic factors of SCLC, and a prognostic model was developed based on these factors. The discrimination and calibration of this model were assessed by the time-dependent C-index, time-dependent receiver operator characteristic curves (ROC), and calibration curves. Additionally, Decision Curve Analysis (DCA) curves, Net Reclassification Improvement (NRI), and Integrated Discriminant Improvement (IDI) were used to assess the enhanced clinical utility and predictive accuracy of the model compared to TNM staging systems.

RESULTS

Multivariate analysis showed that region (Southern/Eastern, hazard ratio [HR] = 1.305 [1.046 - 1.629]; Western/Eastern, HR = 0.727 [0.617 - 0.856]; Northern/Eastern, HR = 0.927 [0.800 - 1.074]), sex (female/male, HR = 0.838 [0.737 - 0.952]), age (46-60/≤45, HR = 1.401 [1.104 - 1.778]; 61-75/≤45, HR = 1.500 [1.182 - 1.902]; >75/≤45, HR = 1.869 [1.382 - 2.523]), TNM stage (II/I, HR = 1.119[0.800 - 1.565]; III/I, HR = 1.478 [1.100 - 1.985]; IV/I, HR = 1.986 [1.477 - 2.670], surgery (yes/no, HR = 0.677 [0.521 - 0.881]), chemotherapy (yes/no, HR = 0.708 [0.616 - 0.813]), and radiotherapy (yes/no, HR = 0.802 [0.702 - 0.917]) were independent prognostic factors of SCLC patients and were included in the nomogram. The time-dependent AUCs of this model in the training set were 0.699, 0.683, and 0.683 for predicting 1-, 3-, and 5-year OS, and 0.698, 0.698, and 0.639 in the validation set, respectively. The predicted calibration curves aligned with the ideal curves, and the DCA curves, the IDI, and the NRI collectively demonstrated that the prognostic model had a superior net benefit than the TNM staging system.

CONCLUSION

The nomogram using SCLC patients in Shandong surpassed the TNM staging system in survival prediction accuracy and enabled the stratification of patients with distinct prognostic risks based on nomogram scores.

Air Pollution and Lung Cancer: A Review by International Association for the Study of Lung Cancer Early Detection and Screening Committee

INTRODUCTION

The second leading cause of lung cancer is air pollution. Air pollution and smoking are synergistic. Air pollution can worsen lung cancer survival.

METHODS

The Early Detection and Screening Committee of the International Association for the Study of Lung Cancer formed a working group to better understand issues in air pollution and lung cancer. These included identification of air pollutants, their measurement, and proposed mechanisms of carcinogenesis. The burden of disease and the underlying epidemiologic evidence linking air pollution to lung cancer in individuals who never and ever smoked were summarized to quantify the problem, assess risk prediction models, and develop recommended actions.

RESULTS

The number of estimated attributable lung cancer deaths has increased by nearly 30% since 2007 as smoking has decreased and air pollution has increased. In 2013, the International Agency for Research on Cancer classified outdoor air pollution and particulate matter with aerodynamic diameter less than 2.5 microns in outdoor air pollution as carcinogenic to humans (International Agency for Research on Cancer group 1) and as a cause of lung cancer. Lung cancer risk models reviewed do not include air pollution. Estimation of cumulative exposure to air pollution exposure is complex which poses major challenges with accurately collecting long-term exposure to ambient air pollution for incorporation into risk prediction models in clinical practice.

CONCLUSIONS

Worldwide air pollution levels vary widely, and the exposed populations also differ. Advocacy to lower sources of exposure is important. Health care can lower its environmental footprint, becoming more sustainable and resilient. The International Association for the Study of Lung Cancer community can engage broadly on this topic.

Effect of high-level PM2.5 on survival in lung cancer: a multicenter cohort study from Hebei Province, China

Globally, air pollution is the fourth leading risk factor for death, while lung cancer (LC) is the leading cause of cancer-related death. The aim of this study was to explore the prognostic factors of LC and the influence of high fine particulate matter (PM2.5) on LC survival. Data on LC patients were collected from 133 hospitals across 11 cities in Hebei Province from 2010 to 2015, and survival status was followed up until 2019. The personal PM2.5 exposure concentration (μg/m3) was matched according to the patient's registered address, calculated from a 5-year average for every patient, and stratified into quartiles. The Kaplan-Meier method was used to estimate overall survival (OS), and Cox's proportional hazard regression model was used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). The 1-, 3-, and 5-year OS rates of the 6429 patients were 62.9%, 33.2%, and 15.2%, respectively. Advanced age (75 years or older: HR = 2.34, 95% CI: 1.25-4.38), subsite at overlapping (HR = 4.35, 95% CI: 1.70-11.1), poor/undifferentiated differentiation (HR = 1.71, 95% CI: 1.13-2.58), and advanced stages (stage III: HR = 2.53, 95% CI: 1.60-4.00; stage IV: HR = 4.00, 95% CI: 2.63-6.09) were risk factors for survival, while receiving surgical treatment was a protective factor (HR = 0.60, 95% CI: 0.44-0.83). Patients exposed to light pollution had the lowest risk of death with a 26-month median survival time. The risk of death in LC patients was greatest at PM2.5 concentrations of 98.7-108.9 μg/m3, especially for patients at advanced stage (HR = 1.43, 95% CI: 1.29-1.60). Our study indicates that the survival of LC is severely affected by relatively high levels of PM2.5 pollution, especially in those with advanced-stage cancer.

The PM2.5 concentration reduction improves survival rate of lung cancer in Beijing

INTRODUCTION

Long-term exposure to ambient fine particulate matter (PM_2.5) has been linked to increases in the incidence of lung cancer. However, more evidence is needed to conclude its effects on lung cancer survival.

OBJECTIVES

The study aimed to explore the relationship between long-term PM_2.5 exposure and lung cancer survival and evaluated the benefits of clean air actions in Beijing.

METHODS

A whole-population cohort study was conducted on lung cancer patients diagnosed between 2001 and 2017. An atmospheric chemical transport model was used to estimate exposure under a counterfactual scenario without the policy and then quantified the effect of the policy. Cox regression models were used with the seasonality-adjusted PM_2.5 as the main effect.

RESULTS

A 10 μg/m³ increase in PM_2.5 was estimated to be with a 6.5 % (95 % CI: 4.8 %, 8.2 %) increase in the mortality rates. The association was heterogeneous and modified by individual-level characteristics. The clean air actions were estimated to have prevented 3548 (95 % CI: 3280, 3825) premature deaths and to have prolonged survival time by 4.29 months (95 % CI: 0.01, 25.11).

CONCLUSION

Our findings suggest that PM_2.5 exposure lowers the survival rate for lung cancer. The clean air actions implemented in Beijing can protect lung cancer patients by increasing their survival time.

SYNOPSIS

Long-term exposure to PM_2.5 can lower lung patients' survival rates whereas the clean air actions in Beijing have prolonged these patients' survival time by reducing PM_2.5 level.