Effect of cumulative radiation exposure from Coronary catheterization on lung cancer mortality.

BACKGROUND: Coronary catheterization (CC) procedure inevitably exposes patients with cardiovascular disease (CVD) to radiation, while cumulative radiation exposure may lead to higher risk of cancer. METHODS: This multi-center, retrospective study was based on the CC procedure in Cardiorenal ImprovemeNt II cohort (CIN-II, NCT05050877) among five regional central tertiary teaching hospitals in China between 2007 and 2020. Patients without known cancer were stratified according to the times they received CC procedure. Baseline information from their last CC procedure was analyzed. Cox regression and Fine-Gray competing risk models were used to assess the relationship between cumulative radiation exposure from CC procedures and cancer-specific, all-cause and cardiovascular mortality. RESULTS: Of 136,495 hospitalized survivors without cancer at baseline (mean age: 62.3 ± 11.1 years, 30.9% female), 116,992 patients (85.7%) underwent CC procedure once, 15,184 patients (11.1%) on twice, and 4,319 patients (3.2%) underwent CC procedure more than three times. During the median follow-up of 4.7 years (IQR: 2.5 to 7.4), totally 18,656 patients (13.7%) died after discharge, of which 617 (0.5%) died of lung cancer. Compared with the patients who underwent CC procedure once, the risk of lung cancer mortality increased significantly with the increase of the number of CC procedure (CC 2 times vs. 1 time: HR 1.42, 95% CI 1.13 to 1.78, P < 0.001; CC ≥ 3 times vs. 1 time: HR 1.64, 95%CI 1.13 to 2.39, P < 0.05). Similar results were observed in all-cause mortality and cardiovascular mortality, but not in other cancer-specific mortality. CONCLUSIONS: Our data suggest that substantial proportion of CVD patients are exposed to multiple high levels of low-dose ionizing radiation from CC procedure, which is associated with an increased risk of cancer mortality in this population. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05050877; URL: http://www. CLINICALTRIALS: gov ; 21/09/2021.

Racial, ethnic and gender trends in lung cancer mortality rates in the United States-Mexico border and non-border areas.

BACKGROUND: Geographic patterns of lung cancer mortality rate differ in the region bordering Mexico in contrast to the US. This study compares lung cancer mortality between border and non-border counties by race/ethnicity and gender. METHODS: This study utilized population-level death certificate data from US Centers for Disease Control and Prevention Public Internet Wide-Ranging Online Data for Epidemiologic Research dataset between 1999 and 2020. Established algorithms were implemented to examine lung cancer deaths among US residents. We analyzed the age-adjusted data by year, race/ethnicity, gender, and geographic region. Joinpoint regression was used to determine mortality trends across time. RESULTS: Lung cancer mortality rates were lower in border counties compared to non-border counties across time (p < 0.05). Hispanic lung cancer mortality rates were not different in border counties compared to non-border counties during the same period (p > 0.05). Lung cancer mortality among non-Hispanic White living in border counties was lower than non-Hispanic White residing in non-border counties (p < 0.01), and non-Hispanic Black living in border counties had lower lung cancer mortality than non-Hispanic Black in non-border counties in all but three years (p < 0.05). Both female and male mortality rates were lower in border counties compared to non-border counties (p < 0.05). CONCLUSION: Differences in lung cancer mortality between border counties and non-border counties reflect lower mortality in Hispanics overall and a decline for non-Hispanic White and non-Hispanic Black living in border counties experiencing lower lung cancer mortality rates than non-border counties. Further studies are needed to identify specific causes for lower mortality rates in border counties.

Short-term association of air pollution with lung cancer mortality in Osaka, Japan.

Long-term air pollution exposure has been linked to increased lung cancer mortality. However, little is known about whether day-to-day fluctuations in air pollution levels are in relation to lung cancer mortality, particularly in low-exposure settings. This study aimed to evaluate the short-term associations between air pollution and lung cancer mortality. Daily data on lung cancer mortality, fine particulate matter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and weather conditions were collected from Osaka Prefecture, Japan, from 2010 to 2014. Generalized linear models were combined with quasi-Poisson regression were applied to evaluate the associations between each air pollutant and lung cancer mortality after adjusting for potential confounders. Mean (standard deviation) concentrations of PM2.5, NO2, SO2, and CO were 16.7 (8.6) µg/m3, 36.8 (14.2) µg/m3, 11.1 (4.0) µg/m3, and 0.51 (0.16) mg/m3, respectively. Interquartile range increases in concentrations of PM2.5, NO2, SO2, and CO (2-d moving average) were associated with 2.65% (95% confidence intervals [CIs]: 0.96%-4.37%), 4.28% (95% CIs: 2.24%-6.36%), 3.35% (95% CIs: 1.03%-5.73%), and 4.60% (95% CIs: 2.19%-7.05%) increased risk of lung cancer mortality, respectively. Stratified analyses showed that the associations were strongest in the older population and men. Exposure‒response curves showed a continuously increasing mortality risk from lung cancer with elevation of air pollution levels, without discernible thresholds. In summary, we found evidence of increased lung cancer mortality in relation to short-term elevations in ambient air pollution. These findings may merit further research to better understand this issue.

Indoor radon exposure and excess of lung cancer mortality: the case of Mexico-an ecological study.

Radon is a radioactive gas that can migrate from soils and rocks and accumulate in indoor areas such as dwellings and buildings. Many studies have shown a strong association between the exposure to radon, and its decay products, and lung cancer (LC), particularly in miners. In Mexico, according to published surveys, there is evidence of radon exposure in large groups of the population, nevertheless, only few attention has been paid to its association as a risk factor for LC. The aim of this ecological study is to evaluate the excess risk of lung cancer mortality in Mexico due to indoor radon exposure. Mean radon levels per state of the Country were obtained from different publications and lung cancer mortality was obtained from the National Institute of Statistics, Geography and Informatics for the period 2001-2013. A model proposed by the International Commission on Radiological Protection to estimate the annual excess risk of LC mortality (per 105 inhabitants) per dose unit of radon was used. The average indoor radon concentrations found rank from 51 to 1863 Bq m-3, the higher average dose exposure found was 3.13 mSv year-1 in the north of the country (Chihuahua) and the mortality excess of LC cases found in the country was 10 ± 1.5 (range 1-235 deaths) per 105 inhabitants. The highest values were found mainly in the Northern part of the country, where numerous uranium deposits are found, followed by Mexico City, the most crowded and most air polluted area in the country. A positive correlation (r = 0.98 p < 0.0001) was found between the excess of LC cases and the dose of radon exposure. Although the excess risk of LC mortality associated with indoor radon found in this study was relatively low, further studies are needed in order to accurately establish its magnitude in the country.

Non-lung cancer specific mortality after lobectomy or sublobectomy in patients with stage IA non-small cell lung cancer ≤2 cm: A propensity score analysis.

BACKGROUND AND OBJECTIVES: To investigate non-lung cancer specific mortality between stage IA non-small cell lung cancer (NSCLC) tumors less than and equal to 2 cm treated with lobectomy and sublobectomy. METHODS: Surveillance, epidemiology, and end results database was queried for patients who underwent lobectomy and sublobectomy. Propensity score matching (PSM) was used to achieve balance in clinicopathological characteristics. We used Fine-and-Gray hazard functions to analyze cause-specific mortality and risk factors. Standardized mortality ratios were calculated to describe cause specific mortality relative to the general population. RESULTS: After PSM, 3,844 patients underwent lobectomy and 1,922 patients underwent sublobectomy. Three leading causes of non-lung cancer mortality were cardiovascular disease (CVD), chronic obstructive pulmonary diseases (COPD), and other cancers. The 5-year cumulative non-lung cancer mortality of lobectomy and sublobectomy groups were 11.4% and 14.0%, respectively (P = .090). Multivariate analyses revealed that age, sex, histology, tumor size, and marital status (P < .01) were independent predictors of non-lung cancer specific mortality. In both groups, risks of CVD specific mortality were comparable to that in the general population, whereas the risk of COPD specific mortality was higher relative to the general population. CONCLUSIONS: As a significant competing event, non-lung cancer specific mortality is comparable between stage IA NSCLC tumors less than equal to 2 cm treated with lobectomy and sublobectomy.

Short-term association between ambient air pollution and lung cancer mortality.

RATIONALE: Long-term exposure to air pollution has been associated with increased lung cancer incidence and mortality. However, the short-term association between air pollution and lung cancer mortality (LCM) remains largely unknown. METHODS: We collected daily data on particulate matter with diameter <2.5 µm (PM2.5), particulate matter with diameter < 10 µm (PM10), sulfur dioxide (SO2), and ozone (O3), and LCM in three of the biggest cities in China, i.e. Beijing, Chongqing, and Guangzhou, from 2013 to 2015. We first estimated city-specific relationships between air pollutants and LCM using time-series generalized linear models, adjusting for potential confounders. A classification and regression tree (CART) model was used to stratify LCM risk based on combinations of air pollutants and meteorological factors in each city. Then we pooled the city-specific associations using random-effects meta-analysis. Meta regression was used to explore if city-specific characteristics modified the air pollution-LCM association. Finally, we stratified the analyses by season, age, and sex. RESULTS: Over the entire period, the current-day concentrations of PM2.5 and PM10 in Chongqing and PM2.5, PM10, and SO2 in Guangzhou were positively associated with LCM (Excess risk ranged from 0.72% (95% CI 0.27%-1.17%) to 6.06% (95% CI 0.76%-11.64%) with each 10 µg/m3 increment in different pollutants), but the association between current-day air pollution and LCM in Beijing was not significant (P > 0.05). When considering the environmental and weather factors simultaneously, current-day PM2.5, relative humidity, and PM10 were the most important factors associated with LCM in Beijing, Chongqing, and Guangzhou, respectively. LCM risk related with daily PM2.5, PM10, and SO2 significantly increased with the increasing annual mean temperature and humidity of the city, while LCM risk related with daily O3 significantly increased with the increases of latitude, annual mean O3 concentration, and socioeconomic level. After stratification, the current-day PM2.5, PM10, and O3 during the warm season in Beijing and PM2.5, PM10, and SO2 during the cool season in Chongqing and Guangzhou were positively associated with LCM (Excess risk ranged from 0.93% (95% CI 0.42%-1.45%) to 7.16% (95% CI 0.64%-14.09%) with each 10 µg/m3 increment in different pollutants). Male and the elderly lung cancer patients were more sensitive to the short-term effect of air pollution. CONCLUSIONS: Lung cancer patients should enhance protection measures against air pollution. More attentions should be paid for the high PM2.5, PM10, and O3 during the warm season in Beijing, and high PM2.5, PM10, and SO2 during the cool season in Chongqing and Guangzhou.

Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners.

Exposure-lag-response associations shed light on the duration of pathogenesis for radiation-induced diseases. To investigate such relations for lung cancer mortality in the German uranium miners of the Wismut company, we apply distributed lag non-linear models (DLNMs) which offer a flexible description of the lagged risk response to protracted radon exposure. Exposure-lag functions are implemented with B-Splines in Cox models of proportional hazards. The DLNM approach yielded good agreement of exposure-lag-response surfaces for the German cohort and for the previously studied cohort of American Colorado miners. For both cohorts, a minimum lag of about 2 year for the onset of risk after first exposure explained the data well, but possibly with large uncertainty. Risk estimates from DLNMs were directly compared with estimates from both standard radio-epidemiological models and biologically based mechanistic models. For age > 45 year, all models predict decreasing estimates of the Excess Relative Risk (ERR). However, at younger age, marked differences appear as DLNMs exhibit ERR peaks, which are not detected by the other models. After comparing exposure-responses for biological processes in mechanistic risk models with exposure-responses for hazard ratios in DLNMs, we propose a typical period of 15 year for radon-related lung carcinogenesis. The period covers the onset of radiation-induced inflammation of lung tissue until cancer death. The DLNM framework provides a view on age-risk patterns supplemental to the standard radio-epidemiological approach and to biologically based modeling.

LncRNA LCPAT1 Mediates Smoking/ Particulate Matter 2.5-Induced Cell Autophagy and Epithelial-Mesenchymal Transition in Lung Cancer Cells via RCC2.

BACKGROUND/AIMS: Ecological studies have shown that air pollution and prevalence of cigarette smoking are positively correlated. Evidence also suggests a synergistic effect of cigarette smoking and PM2.5 exposure (Environmental Particulate Matter ≤ 2.5 µm in diameter) on lung cancer risk. We aimed to evaluate the interaction between smoking prevalence and PM2.5 pollution in relation to lung cancer mortality and determine its underlying mechanisms in vitro. METHODS: "MOVER" method was used to analyze the interaction between smoking prevalence and PM2.5 pollution in relation to lung cancer mortality. Cell autophagy and malignant behaviors induced by cigarette smoke extract (CSE) and PM2.5 exposure were examined in vitro. Gene expression was examined by qRT-PCR and western blot. RNA and protein interaction was determined using a RNA binding protein immunoprecipitation assay. RESULTS: An increased risk for lung cancer death (RERI (the relative excess risk) =0.28) was observed with a synergistic interaction between cigarette smoking and PM2.5 pollution. Cell migration, invasion, EMT (epithelial-mesenchymal transition) and autophagy were elevated when lung cancer cells were treated with CSE and PM2.5 in combination. A lncRNA, named lung cancer progression-association transcript 1 (LCPAT1), was up-regulated after the treatment of CSE and PM2.5, and knocking down the lncRNA impaired the effect of CSE and PM2.5 on lung cancer cells. In addition, LCPAT1 was shown to bind to RCC2, and RCC2 mediated the effect of LCPAT1 on cell autophagy, migration, invasion and EMT in lung cancer. CONCLUSIONS: Our results suggest that combined exposure to CSE and PM2.5 induces LCPAT1 expression, which up-regulates autophagy, and promotes lung cancer progression via RCC2.

Study on PM2.5 pollution and the mortality due to lung cancer in China based on geographic weighted regression model.

BACKGROUND: PM2.5 has become a major component of air pollution in China and has led to a series of health problems. The mortality rate caused by lung cancer has reached the point where it cannot be ignored in China. Air pollution is becoming more and more serious in China, which is increasingly affecting people's lives and health. METHODS: Considering the variations in the geographical environment in China, this paper studied the relationship between PM2.5 concentration and lung cancer mortality based on the geographical weighted regression model in 31 provinces in 2004 and 2008, autonomous regions and municipalities of China. RESULTS: The results indicated there was a significant positive correlation between PM2.5 concentration and lung cancer mortality (r = 0.0052, P = 0.036). Additionally, the longer the time of exposure to PM2.5 is, the higher morbidity is. CONCLUSION: It is suggested that the Chinese government should launch some environmental policy, especially in those areas with severe PM2.5 pollutions, and keep the citizens away from exposure to PM2.5 pollution in the long term.

[Establishing a Combination Model in Predicting Mortality of Lung Cancer].

OBJECTIVE: To identify a good combination model for predicting the mortality of lung cancer. METHODS: Mortality data of lung cancer from 2001-2013 were used to test three prediction model: dynamic series, exponential smoothing, and Joinpoint regression. Weight coefficients of the combination models were calculated using the arithmetic average method, the variance inverse method, the mean square error inverse method, and the simple weighted average method. RESULTS: The exponential smoothing model had the highest accuracy (79.67%) of prediction, followed by the Joinpoint linear model (74.27%). The combination of these two models resulted in better results. The arithmetic average method and the mean square error inverse method had the best prediction, with an accuracy of 86.87% and 85.80%, respectively. CONCLUSIONS: The combined model has higher accuracy than the single models in predicting the mortality of lung cancer.

Long-Term PM2.5 Exposure and Respiratory, Cancer, and Cardiovascular Mortality in Older US Adults.

The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-µg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease.

Metabolic syndrome and total cancer mortality in the Third National Health and Nutrition Examination Survey.

PURPOSE: Although metabolic syndrome incidence has substantially increased during the last few decades, it largely remains unclear whether this metabolic disorder is associated with total cancer mortality. The present study was carried out to investigate this important question. METHODS: A total of 687 cancer deaths were identified from 14,916 participants in the third National Health and Nutrition Examination Survey by linking them to the National Death Index database through December 31, 2006. Cox proportional hazards regression was performed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for total cancer mortality in relation to metabolic syndrome and its individual components. RESULTS: After adjustment for confounders, a diagnosis of metabolic syndrome was associated with 33% elevated total cancer mortality. Compared with individuals without metabolic syndrome, those with 3, 4 and 5 abnormal components had HRs (95% CIs) of 1.28 (1.03-1.59), 1.24 (0.96-1.60), and 1.87 (1.34-2.63), respectively (p-trend = 0.0003). Systolic blood pressure and serum glucose were associated with an increased risk of death from total cancer [HR (95% CI) for highest vs. lowest quartiles: 1.67 (1.19-2.33), p-trend = 0.002 and 1.34 (1.04-1.74), p-trend = 0.003, respectively]. Overall null results were obtained for lung cancer mortality. The effects of metabolic syndrome and its components on non-lung cancer mortality were generally similar to, but somewhat larger than, those for total cancer mortality. CONCLUSION: Our study is among the first to reveal that metabolic syndrome is associated with increased total cancer mortality.

Application of morphometric analysis to patients with lung cancer metastasis to the spine: a clinical study.

OBJECTIVE Predicting the survival rate for patients with cancer is currently performed using the TNM Classification of Malignant Tumors (TNM). Identifying accurate prognostic markers of survival would allow better treatment stratification between more aggressive treatment strategies or palliation. This is especially relevant for patients with spinal metastases, who all have identical TNM staging and whose surgical decision-making is potentially complex. Analytical morphometrics quantifies patient frailty by measuring lean muscle mass and can predict risk for postoperative morbidity after lumbar spine surgery. This study evaluates whether morphometrics can be predictive of survival in patients with spinal metastases. METHODS Utilizing a retrospective registry of patients with spinal metastases who had undergone stereotactic body radiation therapy, the authors identified patients with primary lung cancer. Morphometric measurements were taken of the psoas muscle using CT of the lumbar spine. Additional morphometrics were taken of the L-4 vertebral body. Patients were stratified into tertiles based on psoas muscle area. The primary outcome measure was overall survival, which was measured from the date of the patient's CT scan to date of death. RESULTS A total of 168 patients were identified, with 54% male and 54% having multiple-level metastases. The median survival for all patients was 185.5 days (95% confidence interval [CI] 146-228 days). Survival was not associated with age, sex, or the number of levels of metastasis. Patients in the smallest tertile for the left psoas area had significantly shorter survival compared with a combination of the other two tertiles: 139 days versus 222 days, respectively, hazard ratio (HR) 1.47, 95% CI 1.06-2.04, p = 0.007. Total psoas tertiles were not predictive of mortality, but patients whose total psoas size was below the median size had significantly shorter survival compared with those greater than the median size: 146 days versus 253.5 days, respectively, HR 1.43, 95% CI 1.05-1.94, p = 0.025. To try to differentiate small body habitus from frailty, the ratio of psoas muscle area to vertebral body area was calculated. Total psoas size became predictive of mortality when normalized to vertebral body ratio, with patients in the lowest tertile having significantly shorter survival (p = 0.017). Left psoas to vertebral body ratio was also predictive of mortality in patients within the lowest tertile (p = 0.021). Right psoas size was not predictive of mortality in any calculations. CONCLUSIONS In patients with lung cancer metastases to the spine, morphometric analysis of psoas muscle and vertebral body size can be used to identify patients who are at risk for shorter survival. This information should be used to select patients who are appropriate candidates for surgery and for the tailoring of oncological treatment regimens.

[Prerequisites for a successful lung cancer screening program]. / Voraussetzungen für ein erfolgreiches Lungenkrebsscreeningprogramm.

The American national lung cancer screening trial (NLST) has provided the first confirmation of a reduction in lung cancer mortality by using low-dose multislice computed tomography (MSCT). Preliminary evaluations of smaller European trials could not confirm such a reduction. The final evaluation of the larger Dutch-Belgian NELSON trial and five other European trials are expected within the next 1-2 years. The results of the completed rounds of screening in all these studies indicate that the margin between a positive and a negative benefit-to-harm balance will be narrow. In such a scenario it will be crucial to optimize the definition of the target population for screening as a high-risk group for lung cancer, the quality of screening in terms of high sensitivity and specificity as well as high quality treatment and an effective ongoing control of program quality. Not all healthcare systems are suitable to fulfill these prerequisites.

[Lung cancer screening - risk stratification : Who should undergo screening?]. / Bronchialkarzinomscreening - Risikostratifizierung : Wer soll gescreent werden?

Lung cancer is one of the leading causes of deaths in Europa and the USA. In approximately 75 % of lung cancer patients, bronchogenic carcinoma is detected at an advanced tumor stage; therefore, therapeutic options which aim at curing the disease in these patients are limited and treatment is mostly palliative. A relatively good prognosis is reserved for the minority of patients where the tumor is detected at an early stage and treatment is potentially curative. For this reason, early diagnosis of lung cancer could save lives. Retrospective analyses of the US national lung screening trial (NLST) showed that especially high-risk populations (e. g. higher age, positive smoking history, overweight and a positive family history for lung cancer) benefit most from lung cancer screening. Thus, the effectiveness of computed tomography (CT) screening can be improved by focusing on high-risk populations. This review article summarizes the risk stratification models of the large European and American screening studies and discusses possible future biomarkers for risk stratification.

[Lung cancer screening with thoracic X­ray and CT : Current situation]. / Lungenkarzinomscreening mit Röntgenthorax oder CT : Aktuelle Datenlage.

CLINICAL/METHODICAL ISSUE: Attempts at the early detection of lung cancer using imaging methods began as far back as the 1950s. STANDARD RADIOLOGICAL METHODS: Several studies attempted to demonstrate a reduction of lung cancer mortality by chest radiography screening but all were unsuccessful. METHODICAL INNOVATIONS: Even the first small screening studies using computed tomography (CT) could not demonstrate a reduction in lung cancer-specific mortality until in 2011 the results of the largest randomized controlled low-dose CT screening study in the USA (NLST) were published. The NLST results could show a significant 20 % reduction of lung cancer mortality in elderly and heavy smokers using CT. PERFORMANCE: Confirmation of the NLST results are urgently needed so that the data of the largest European study (NELSON) are eagerly awaited. ACHIEVEMENTS: Pooled with the data from several smaller European studies these results will provide important information and evidence for the establishment of future CT screening programs in Europe. PRACTICAL RECOMMENDATIONS: Randomized controlled trials are the basis of evidence-based medicine; therefore, the positive results of the methodologically very good NLST study cannot be ignored, even if it is the only such study completed so far with highly convincing conclusions. The NLST results clearly demonstrate that positive effects for the health of the population can only be expected if the processes are clearly defined and the quality is assured.

Interactions between cigarette smoking and fine particulate matter in the Risk of Lung Cancer Mortality in Cancer Prevention Study II.

The International Agency for Research on Cancer recently classified outdoor air pollution and airborne particulate matter as carcinogenic to humans. However, there are gaps in the epidemiologic literature, including assessment of possible joint effects of cigarette smoking and fine particulate matter (particulate matter less than or equal to 2.5 µm in diameter) on lung cancer risk. We present estimates of interaction on the additive scale between these risk factors from Cancer Prevention Study II, a large prospective US cohort study of nearly 1.2 million participants recruited in 1982. Estimates of the relative excess risk of lung cancer mortality due to interaction, the attributable proportion due to interaction, and the synergy index were 2.19 (95% confidence interval (CI): -0.10, 4.83), 0.14 (95% CI: 0.00, 0.25), and 1.17 (95% CI: 1.00, 1.37), respectively, using the 25th and 75th percentiles as cutpoints for fine particulate matter. This suggests small increases in lung cancer risk among persons with both exposures beyond what would be expected from the sum of the effects of the individual exposures alone. Although reductions in cigarette smoking will achieve the greatest impact on lung cancer rates, these results suggest that attempted reductions in lung cancer risk through both tobacco control and air quality management may exceed expectations based on reducing exposure to either risk factor alone.

A Bayesian generalized age-period-cohort power model for cancer projections.

Age-period-cohort (APC) models are the state of art in cancer projections, assessing past and recent trends and extrapolating mortality or incidence data into the future. Nordpred is a well-established software, assuming a Poisson distribution for the counts and a log-link or power-link function with fixed power; however, its predictive performance is poor for sparse data. Bayesian models with log-link function have been applied, but they can lead to extreme estimates. In this paper, we address criticisms of the aforementioned models by providing Bayesian formulations based on a power-link and develop a generalized APC power-link model, which assumes a random rather than fixed power parameter. In addition, a power model with a fixed power parameter of five was formulated in the Bayesian framework. The predictive performance of the new models was evaluated on Swiss lung cancer mortality data using model-based estimates of observed periods. Results indicated that the generalized APC power-link model provides best estimates for male and female lung cancer mortality. The gender-specific models were further applied to project lung cancer mortality in Switzerland during the periods 2009-2013 and 2014-2018.

Potential causal links and mediation pathway between urban greenness and lung cancer mortality: Result from a large cohort (2009 to 2020).

Urban greenness, as a vital component of the urban environment, plays a critical role in mitigating the adverse effects of rapid urbanization and supporting urban sustainability. However, the causal links between urban greenness and lung cancer mortality and its potential causal pathway remain poorly understood. Based on a prospective community-based cohort with 581,785 adult participants in southern China, we applied a doubly robust Cox proportional hazard model to estimate the causal associations between urban greenness exposure and lung cancer mortality. A general multiple mediation analysis method was utilized to further assess the potential mediating roles of various factors including particulate matter (PM1, PM2.5-1, and PM10-2.5), temperature, physical activity, and body mass index (BMI). We observed that each interquartile range (IQR: 0.06) increment in greenness exposure was inversely associated with lung cancer mortality, with a hazard ratio (HR) of 0.89 (95 % CI: 0.83, 0.96). The relationship between greenness and lung cancer mortality might be partially mediated by particulate matter, temperature, and physical activity, yielding a total indirect effect of 0.826 (95 % CI: 0.769, 0.887) for each IQR increase in greenness exposure. Notably, the protective effect of greenness against lung cancer mortality could be achieved primarily by reducing the particulate matter concentration.