Impact of smoke-free ordinance strength on smoking prevalence and lung cancer incidence.

6578 Background: Smoke-free ordinances (SFO) have been shown to decrease the prevalence of cardiovascular and pulmonary disease, but there is limited data on the impact of such policies on lung cancer incidence. We investigated the relationship between strength of county-level SFO with smoking prevalence and lung cancer incidence in Indiana. Methods: Following IRB approval, we queried the Indiana State Cancer Registry and Indiana Tobacco Prevention and Cessation Commission’s policy database between 1995 and 2016. County-level characteristics included population, income, poverty, education, race/ethnicity, sex, and rurality. Lung cancer diagnosis and stage were also collected. Using generalized estimating equations (GEE) with robust standard errors and accounting for the clustering effect at county level, we performed multivariable analyses of smoking prevalence and age-adjusted lung cancer rates with respect to the strength of smoke-free ordinances at the county level over time. Results: Indiana consists of 92 counties, 24 of which had SFO by 2011. In 2012, Indiana enacted a law mandating at least a moderate state-wide SFO. From 1995 to 2016, 110,935 Indiana residents were diagnosed with lung cancer. Indiana also had an average age-adjusted yearly lung cancer incidence of 76.8 per 100,000 population and average yearly smoking prevalence of 25% during this time. Smoking prevalence was 1.2% (95% CI [-1.88, -0.52]) lower in counties with comprehensive or moderate SFO compared with those with weak or no SFO. Counties that had comprehensive or moderate SFO had an 8.36 (95% CI [-11.45, -5.27]) decrease in new lung cancer diagnosis per 100,000 population per year compared with counties that had weak or no SFO. Conclusions: Stronger municipal smoke-free air ordinances are associated with decreased smoking prevalence and fewer new lung cancer cases. Strengthening smoke-free ordinances is paramount to decreasing lung cancer incidence.

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Impact of smoke-free ordinance strength on smoking prevalence and lung cancer incidence

PLoS ONE ◽

10.1371/journal.pone.0250285 ◽

2021 ◽

Vol 16 (4) ◽

pp. e0250285

Author(s):

Ryan H. Nguyen ◽

Laura B. Vater ◽

Lava R. Timsina ◽

Gregory A. Durm ◽

Katelin Rupp ◽

...

Keyword(s):

Lung Cancer ◽

Cancer Incidence ◽

Smoking Prevalence ◽

Tobacco Prevention ◽

County Level ◽

Lung Cancer Incidence ◽

Lung Cancer Diagnosis ◽

Free Air ◽

Effective Public Health ◽

The Impact

Background Smoke-free ordinances (SFO) have been shown to be effective public health interventions, but there is limited data on the impact SFO on lung cancer outcomes. We explored the effect of county-level SFO strength with smoking prevalence and lung cancer incidence in Indiana. Methods We obtained county-level lung cancer incidence from the Indiana State Cancer Registry and county-level characteristics from the Indiana Tobacco Prevention and Cessation Commission’s policy database between 1995 and 2016. Using generalized estimating equations, we performed multivariable analyses of smoking prevalence and age-adjusted lung cancer rates with respect to the strength of smoke-free ordinances at the county level over time. Results Of Indiana’s 92 counties, 24 had a SFO by 2011. In 2012, Indiana enacted a state-wide SFO enforcing at least moderate level SFO protection. Mean age-adjusted lung cancer incidence per year was 76.8 per 100,000 population and mean smoking prevalence per year was 25% during the study period. Counties with comprehensive or moderate SFO had a smoking prevalence 1.2% (95% CI [-1.88, -0.52]) lower compared with counties with weak or no SFO. Counties that had comprehensive or moderate SFO also had an 8.4 (95% CI [-11.5, -5.3]) decrease in new lung cancer diagnosis per 100,000 population per year compared with counties that had weak or no SFO. Conclusion Counties with stronger smoke-free air ordinances were associated with decreased smoking prevalence and fewer new lung cancer cases per year. Strengthening SFO is paramount to decreasing lung cancer incidence.

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Venous and Lung Thromboembolism in the Context of Lung Cancer: Clinical Manifestations, Risk Factors and Prognosis

Acta Médica Portuguesa ◽

10.20344/amp.10260 ◽

2019 ◽

Vol 32 (10) ◽

pp. 647 ◽

Cited By ~ 1

Author(s):

Rosana Maia ◽

Inês Neves ◽

António Morais ◽

Henrique Queiroga

Keyword(s):

Lung Cancer ◽

Venous Thromboembolism ◽

Cancer Diagnosis ◽

Negative Impact ◽

Clinical Manifestations ◽

Research Subjects ◽

Lung Cancer Diagnosis ◽

The Impact ◽

The Relationship

Introduction: The relationship between cancer and thromboembolic events has been known for a long time. Lung and venous thromboembolism are frequent complications of lung cancer and its treatment, being a great cause of morbidity and mortality. We pretend to establish the relationship between lung and venous thromboembolism and lung cancer, describe patient characteristics and analyze the impact in the survival and prognosis.Material and Methods: It was a retrospective study. All research subjects were selected from lung cancer patients with a newly diagnosed lung and venous thromboembolism event admitted to Hospital S. João, between January 2008 and December 2013 and were followed until December 2014. Statistical analysis was performed with SPSS.Results: From the search, we obtained 113 patients. The majority was male, smokers or ex-smokers, and adenocarcinoma was the most frequent histologic type, being diagnosed mostly in advanced stages. We noticed that the median time between lung cancer diagnosis and lung venous thromboembolism was 2.9 months. In 24 patients (21.4%), the lung cancer diagnosis occurred after the lung and venous thromboembolism event and in 86 patients (76.8%), it occurred before the event. After a median follow up of 1.4 months, 107 (94.7%) patients died, 1 (0.9%) was lost to follow-up and 5 (4.4%) were still alive. The median survival rate was 1.5 months.Discussion: The diagnosis of lung and venous thromboembolism in patients with lung cancer is associated with bad prognosis. It occurs most frequently in patients with advanced disease, in the first months after lung cancer diagnosis and after beginning chemotherapy.Conclusion: Disease progression is an independent predictor with negative impact in overall survival.

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Changes in Black-White Difference in Lung Cancer Incidence among Young Adults

JNCI Cancer Spectrum ◽

10.1093/jncics/pkaa055 ◽

2020 ◽

Vol 4 (4) ◽

Author(s):

Ahmedin Jemal ◽

Kimberly D Miller ◽

Ann Goding Sauer ◽

Priti Bandi ◽

Miranda M Fidler-Benaoudia ◽

...

Keyword(s):

Lung Cancer ◽

Black Men ◽

Cancer Incidence ◽

Smoking Prevalence ◽

White Men ◽

The United States ◽

Lung Cancer Incidence ◽

Birth Cohorts ◽

Incidence Data ◽

Blacks And Whites

Abstract Background We previously reported that lung cancer incidence between Blacks and Whites younger than 40 years of age converged in women and approached convergence in men. Whether this pattern has continued in contemporary young birth cohorts is unclear. Methods We examined 5-year age-specific lung cancer incidence in Blacks and Whites younger than 55 years of age by sex and calculated the Black-to-White incidence rate ratios (IRRs) and smoking prevalence ratios by birth cohort using nationwide incidence data from 1997 to 2016 and smoking data from 1970 to 2016 from the National Health Interview Survey. Results Five-year age-specific incidence decreased in successive Black and White men born since circa 1947 and women born since circa 1957, with the declines steeper in Blacks than Whites. Consequently, the Black-to-White IRRs became unity in men born 1967-1972 and reversed in women born since circa 1967. For example, the Black-to-White IRRs in ages 40-44 years born between 1957 and 1972 declined from 1.92 (95% confidence interval [CI] = 1.82 to 2.03) to 1.03 (95% CI = 0.93 to 1.13) in men and from 1.32 (95% CI = 1.24 to 1.40) to 0.71 (95% CI = 0.64 to 0.78) in women. Similarly, the historically higher sex-specific smoking prevalence in Blacks than Whites disappeared in men and reversed in women born since circa 1965. The exception to these patterns is that the incidence became higher in Black men than White men born circa 1977-1982. Conclusions The historically higher lung cancer incidence in young Blacks than young Whites in the United States has disappeared in men and reversed in women, coinciding with smoking patterns, though incidence again became higher in Black men than White men born circa 1977-1982.

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Collateral effects of the coronavirus disease 2019 pandemic on lung cancer diagnosis in Korea

BMC Cancer ◽

10.1186/s12885-020-07544-3 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Ji Young Park ◽

Ye Jin Lee ◽

Taehee Kim ◽

Chang Youl Lee ◽

Hwan Il Kim ◽

...

Keyword(s):

Lung Cancer ◽

Cancer Diagnosis ◽

Rapid Progression ◽

Lung Cancers ◽

The Past ◽

Lung Cancer Diagnosis ◽

Number Of Patients ◽

Wide Range ◽

Collateral Effects ◽

The Impact

Abstract Background The COVID-19 pandemic is predicted to significantly affect patients with lung cancer, owing to its rapid progression and high mortality. Studies on lung cancer diagnosis and treatment during an epidemic are lacking. We analyzed the impact of COVID-19 on lung cancer diagnosis in Korea, where lung cancer incidence continues to rise. Methods The number of newly diagnosed lung cancer cases in three university-affiliated hospitals during the pandemic and their clinical features were compared with lung cancer cases diagnosed during the same period in the past 3 years. The effectiveness of measures taken by the study hospitals to prevent nosocomial transmission was reviewed. Results A total of 612 patients were diagnosed with lung cancer from February through June, 2017–2020. During the pandemic, the number of patients who sought consultation at the division of pulmonology of study hospitals dropped by 16% from the previous year. Responding to the pandemic, the involved hospitals created physically isolated triage areas for patients with acute respiratory infection symptoms. Wide-range screening and preventive measures were implemented, thus minimizing the delay in lung cancer diagnosis. No patient acquired COVID-19 due to hospital exposure. The proportion of patients with stage III–IV non-small-cell lung cancer (NSCLC) significantly increased (2020: 74.7% vs. 2017: 57.9%, 2018: 66.7%, 2019: 62.7%, p = 0.011). The number of lung cancers diagnosed during this period and the previous year remained the same. Conclusions The proportion of patients with advanced NSCLC increased during the COVID-19 pandemic.

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The lung cancer obesity paradox: An analysis of 432,924 patients.

Journal of Clinical Oncology ◽

10.1200/jco.2021.39.15_suppl.10578 ◽

2021 ◽

Vol 39 (15_suppl) ◽

pp. 10578-10578

Author(s):

Brittany Miles ◽

James David Mackey

Keyword(s):

Lung Cancer ◽

Cancer Incidence ◽

Radiation Treatment ◽

Positive Impact ◽

Obesity Paradox ◽

Overweight And Obesity ◽

Research Network ◽

P Value ◽

Lung Cancer Incidence ◽

The Impact

10578 Background: The lung cancer obesity paradox is the unexpected inverse relationship between body mass index (BMI) and lung cancer mortality. While there is a growing body of evidence to support the existence of the obesity paradox in lung cancer, little is known about its magnitude and relationship to cancer incidence and its impact on outcomes from surgery, chemotherapy, immunotherapy, and radiation treatment. Methods: To evaluate the impact of obesity on lung cancer incidence, we used TriNetX, a global federated health research network providing access to electronic medical records (diagnoses, procedures, medications, laboratory values, genomic information) from approximately 69 Million patients in 49 large Healthcare Organizations. We evaluated 2 patient cohorts of 216,462 adult smokers aged 18 to 75 that were matched for age, race, gender, and ethnicity. One cohort of patients carried a diagnosis of overweight and obesity (ICD-10 code E66), while the other cohort required exclusion of those diagnoses. Results: We found a statistically significant decrease in lung cancer incidence for patients with obesity (1.407% vs 2.039%, p < 0.0001), in addition to superior overall survival (95.344% vs 92.039%, p < 0.0001). A subset analysis of patients who contracted lung cancer showed a statistically significant benefit in median survival in favor of patients with overweight and obesity (851 vs 602 days, p value 0.0009). Conclusions: These findings support the existence of the obesity paradox in lung cancer, and its positive impact on both lung cancer incidence and outcome.

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The impact of the COVID-19 pandemic on lung cancer diagnosis and stage at Plymouth NHS Trust

Lung Cancer ◽

10.1016/s0169-5002(21)00239-7 ◽

2021 ◽

Vol 156 ◽

pp. S17

Author(s):

Helen McDill ◽

Maged Hassan ◽

Lindsey Taylor ◽

John Corcoran ◽

Cyrus Daneshvar

Keyword(s):

Lung Cancer ◽

Cancer Diagnosis ◽

Lung Cancer Diagnosis ◽

The Impact

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Cluster Analysis Evaluating PM2.5, Occupation Risk and Mode of Transportation as Surrogates for Air-pollution and the Impact on Lung Cancer Diagnosis and 1-Year Mortality

Asian Pacific Journal of Cancer Prevention ◽

10.31557/apjcp.2019.20.7.1959 ◽

2019 ◽

Vol 20 (7) ◽

pp. 1959-1965

Author(s):

Sopian Abdul Wahab ◽

Astrid Hassan ◽

Mohd Talib Latif ◽

Yasheeny Vadiveel ◽

Tamyenthini Jeyabalan ◽

...

Keyword(s):

Lung Cancer ◽

Air Pollution ◽

Cluster Analysis ◽

Cancer Diagnosis ◽

Lung Cancer Diagnosis ◽

Mode Of Transportation ◽

The Impact

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Exposure–lag response of smoking prevalence on lung cancer incidence using a distributed lag non-linear model

Scientific Reports ◽

10.1038/s41598-021-91644-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Daniel Robert Smith ◽

Alireza Behzadnia ◽

Rabbiaatul Addawiyah Imawana ◽

Muzammil Nahaboo Solim ◽

Michaela Louise Goodson

Keyword(s):

Lung Cancer ◽

Incidence Rate ◽

Linear Model ◽

Cancer Incidence ◽

Rate Ratio ◽

Smoking Prevalence ◽

Incidence Rate Ratio ◽

Lung Cancer Incidence ◽

Distributed Lag ◽

Lag Period

AbstractThe prevalence of smokers is a major driver of lung cancer incidence in a population, though the “exposure–lag” effects are ill-defined. Here we present a multi-country ecological modelling study using a 30-year smoking prevalence history to quantify the exposure–lag response. To model the temporal dependency between smoking prevalence and lung cancer incidence, we used a distributed lag non-linear model (DLNM), controlling for gender, age group, country, outcome year, and population at risk, and presented the effects as the incidence rate ratio (IRR) and cumulative incidence rate ratio (IRRcum). The exposure–response varied by lag period, whilst the lag–response varied according to the magnitude and direction of changes in smoking prevalence in the population. For the cumulative lag–response, increments above and below the reference level was associated with an increased and decreased IRRcum respectively, with the magnitude of the effect varying across the lag period. Though caution should be exercised in interpretation of the IRR and IRRcum estimates reported herein, we hope our work constitutes a preliminary step towards providing policy makers with meaningful indicators to inform national screening programme developments. To that end, we have implemented our statistical model a shiny app and provide an example of its use.

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