Body mass index, lifetime smoking intensity and lung cancer risk

Leptin: A Heavyweight Player in Obesity-Related Cancers

Obesity, defined as the abnormal or excessive expansion of white adipose tissue, has reached pandemic proportions and is recognized as an important health concern since it is a common root for several comorbidities, including malignancies. Indeed, the current knowledge of the white adipose tissue, which shifts its role from an energy storage tissue to an important endocrine and metabolic organ, has opened up new avenues for the discovery of obesity's effects on tumor biology. In this review, we will report the epidemiological studies concerning the strong impact of obesity in several types of cancer and describe the mechanisms underlying the heterotypic signals between cancer cell lines and adipocytes, with particular emphasis on inflammation, the insulin/IGF-1 axis, and adipokines. Among the adipokines, we will further describe the in vitro, in vivo, and clinical data concerning the role of leptin, recognized as one of the most important mediators of obesity-associated cancers. In fact, leptin physiologically regulates energy metabolism, appetite, and reproduction, and several studies have also described the role of leptin in affecting cancer development and progression. Finally, we will summarize the newest pharmacological strategies aimed at mitigating the protumorigenic effects of leptin, underlining their mechanisms of action.

BMI changes and the risk of lung cancer in male never-smokers: A prospective cohort study

BACKGROUND

To investigate the association between the risk of lung cancer and short-term body mass index (BMI) changes in male never-smokers of a large population-based prospective study.

METHODS

A total of 37,085 male never-smokers from Kailuan cohort with at least ≥2 BMI measurements were recruited in the present study. The BMI change in the follow-up was calculated as the annual percent change between BMI at last examination and that at baseline, and categorized into five groups: stable (-0.1 to <0.1 kg/m2 /year), minor loss (-1.0 to <0.1 kg/m2 /year) or gain (0.1 to <1.0 kg/m2 /year), and major loss (<-1.0 kg/m2 /year) or gain (≥1.0 kg/m2 /year). The hazards ratios (HRs) and its 95% confidence intervals (CI) were estimated using Cox regression models.

RESULTS

During a median follow-up of 5.16 years, 224 lung cancer cases were identified. We found a U-shaped association between BMI changes and lung cancer risk. Compared to men with stable BMI, those with major loss had a nearly twofold higher risk of lung cancer (HR = 1.97, 95% CI: 1.12-3.45), as well as those with major gain had more than twofold higher risk of lung cancer (HR = 2.15, 95% CI: 1.15-4.02). The associations existed when the analysis was stratified by BMI, waist circumference and blood lipids, and lipoproteins concentration at baseline examination.

CONCLUSIONS

The dramatic changes in BMI, both gain and loss, might increase lung cancer risk. The control of body weight would be a potential way for lung cancer prevention especially for the nonsmokers.

Non-small cell lung carcinoma histopathological subtype phenotyping using high-dimensional multinomial multiclass CT radiomics signature

OBJECTIVE

The aim of this study was to identify the most important features and assess their discriminative power in the classification of the subtypes of NSCLC.

METHODS

This study involved 354 pathologically proven NSCLC patients including 134 squamous cell carcinoma (SCC), 110 large cell carcinoma (LCC), 62 not other specified (NOS), and 48 adenocarcinoma (ADC). In total, 1433 radiomics features were extracted from 3D volumes of interest drawn on the malignant lesion identified on CT images. Wrapper algorithm and multivariate adaptive regression splines were implemented to identify the most relevant/discriminative features. A multivariable multinomial logistic regression was employed with 1000 bootstrapping samples based on the selected features to classify four main subtypes of NSCLC.

RESULTS

The results revealed that the texture features, specifically gray level size zone matrix features (GLSZM), were the significant indicators of NSCLC subtypes. The optimized classifier achieved an average precision, recall, F1-score, and accuracy of 0.710, 0.703, 0.706, and 0.865, respectively, based on the selected features by the wrapper algorithm.

CONCLUSIONS

Our CT radiomics approach demonstrated impressive potential for the classification of the four main histological subtypes of NSCLC, It is anticipated that CT radiomics could be useful in treatment planning and precision medicine.

Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization

At the time of cancer diagnosis, body mass index (BMI) is inversely correlated with lung cancer risk, which may reflect reverse causality and confounding due to smoking behavior. We used two-sample univariable and multivariable Mendelian randomization (MR) to estimate causal relationships of BMI and smoking behaviors on lung cancer and histological subtypes based on an aggregated genome-wide association studies (GWASs) analysis of lung cancer in 29 266 cases and 56 450 controls. We observed a positive causal effect for high BMI on occurrence of small-cell lung cancer (odds ratio (OR) = 1.60, 95% confidence interval (CI) = 1.24-2.06, P = 2.70 × 10-4 ). After adjustment of smoking behaviors using multivariable Mendelian randomization (MVMR), a direct causal effect on small cell lung cancer (ORMVMR = 1.28, 95% CI = 1.06-1.55, PMVMR = .011), and an inverse effect on lung adenocarcinoma (ORMVMR = 0.86, 95% CI = 0.77-0.96, PMVMR = .008) were observed. A weak increased risk of lung squamous cell carcinoma was observed for higher BMI in univariable Mendelian randomization (UVMR) analysis (ORUVMR = 1.19, 95% CI = 1.01-1.40, PUVMR = .036), but this effect disappeared after adjustment of smoking (ORMVMR = 1.02, 95% CI = 0.90-1.16, PMVMR = .746). These results highlight the histology-specific impact of BMI on lung carcinogenesis and imply mediator role of smoking behaviors in the association between BMI and lung cancer.

Statistical Assessment of Toxic and Essential Metals in the Serum of Female Patients with Lung Carcinoma from Pakistan

Lung cancer (LC) is the number one cancer killer of women both in the USA and around the world. Besides cigarette smoking, an important feature in the etiology of LC is its strong association with exposure of toxic metals. The primary objective of the present investigation was to assess the concentrations of toxic/essential elements (Ni, Ca, Se, Zn, Co, K, Cr, As, Cu, Na, Fe, Hg, Cd, Mg, Mn, and Pb) in the serum samples of LC female patients with female controls by atomic absorption spectrometry after wet-acid digestion procedure. Carcinoembryonic antigen (CEA) was also measured in the serum of the patients using immunoradiometric method. Comparative appraisal of the data revealed that concentrations of Cr, Mg, Cd, Pb, Hg, As, and Ni were noted to be high significantly in serum of LC female patients, while the average Fe, Co, Mn, Na, K, Zn, Ca, and Se were observed at higher levels in female controls (p < 0.05). The correlation study revealed significantly different mutual associations among the elements in the both donor groups. Markedly, variations in the elemental levels were also noted for different types (non-small cell lung cancer and small cell lung cancer) and stages (I, II, III, & IV) of LC patients. Multivariate analyses showed substantially diverse apportionment of the metals in the female patients and female controls. Hence, present findings suggest that the toxic and essential metals accumulated in the body may pose a high risk for LC progression in Pakistani females.

Quantitative Pectoralis Muscle Area is Associated with the Development of Lung Cancer in a Large Lung Cancer Screening Cohort

BACKGROUND

Studies have demonstrated an inverse relationship between body mass index (BMI) and the risk of developing lung cancer. We conducted a retrospective cohort study evaluating baseline quantitative computed tomography (CT) measurements of body composition, specifically muscle and fat area in a large CT lung screening cohort (CTLS). We hypothesized that quantitative measurements of baseline body composition may aid in risk stratification for lung cancer.

METHODS

Patients who underwent baseline CTLS between January 1st, 2012 and September 30th, 2014 and who had an in-network primary care physician were included. All patients met NCCN Guidelines eligibility criteria for CTLS. Quantitative measurements of pectoralis muscle area (PMA) and subcutaneous fat area (SFA) were performed on a single axial slice of the CT above the aortic arch with the Chest Imaging Platform Workstation software. Cox multivariable proportional hazards model for cancer was adjusted for variables with a univariate p < 0.2. Data were dichotomized by sex and then combined to account for baseline differences between sexes.

RESULTS

One thousand six hundred and ninety six patients were included in this study. A total of 79 (4.7%) patients developed lung cancer. There was an association between the 25th percentile of PMA and the development of lung cancer [HR 1.71 (1.07, 2.75), p < 0.025] after adjusting for age, BMI, qualitative emphysema, qualitative coronary artery calcification, and baseline Lung-RADS® score.

CONCLUSIONS

Quantitative assessment of PMA on baseline CTLS was associated with the development of lung cancer. Quantitative PMA has the potential to be incorporated as a variable in future lung cancer risk models.

Exploratory study on classification of lung cancer subtypes through a combined K-nearest neighbor classifier in breathomics

Accurate classification of adenocarcinoma (AC) and squamous cell carcinoma (SCC) in lung cancer is critical to physicians’ clinical decision-making. Exhaled breath analysis provides a tremendous potential approach in non-invasive diagnosis of lung cancer but was rarely reported for lung cancer subtypes classification. In this paper, we firstly proposed a combined method, integrating K-nearest neighbor classifier (KNN), borderline2-synthetic minority over-sampling technique (borderlin2-SMOTE), and feature reduction methods, to investigate the ability of exhaled breath to distinguish AC from SCC patients. The classification performance of the proposed method was compared with the results of four classification algorithms under different combinations of borderline2-SMOTE and feature reduction methods. The result indicated that the KNN classifier combining borderline2-SMOTE and feature reduction methods was the most promising method to discriminate AC from SCC patients and obtained the highest mean area under the receiver operating characteristic curve (0.63) and mean geometric mean (58.50) when compared to others classifiers. The result revealed that the combined algorithm could improve the classification performance of lung cancer subtypes in breathomics and suggested that combining non-invasive exhaled breath analysis with multivariate analysis is a promising screening method for informing treatment options and facilitating individualized treatment of lung cancer subtypes patients.

Predicted lean body mass, fat mass and risk of lung cancer: prospective US cohort study

An inverse association between body mass index (BMI) and risk of lung cancer has been reported. However, the association of body composition such as fat mass (FM) and lean body mass (LBM) with risk of lung cancer has not been fully investigated. Using two large prospective cohort studies (Nurses' Health Study, 1986-2014; Health Professionals Follow-up Study, 1987-2012) in the United States, we included 100,985 participants who were followed for occurrence of lung cancer. Predicted FM and LBM derived from validated anthropometric prediction equations were categorized by sex-specific deciles. During an average 22.3-year follow-up, 2615 incident lung cancer cases were identified. BMI showed an inverse association with lung cancer risk. Participants in the 10th decile of predicted FM and LBM had a lower risk of lung cancer compared with those in the 1st decile, but when mutually adjusted for each other, predicted FM was not associated with lung cancer risk (adjusted hazard ratio [aHR] = 0.98, 95% confidence interval [CI] 0.72-1.35; P(trend) = 0.97) whereas predicted LBM had an inverse association (aHR = 0.73, 95% CI 0.53-1.00; P(trend) = 0.03), especially among participants who were current smokers or had smoked in the previous 10 years (aHR = 0.55, 95% CI 0.36-0.84; P(trend) = 0.008). In conclusion, BMI was inversely associated with lung cancer risk. Based on anthropometric prediction equations, low LBM rather than low FM accounted for the inverse association between BMI and lung cancer risk.

Global patterns in excess body weight and the associated cancer burden

The prevalence of excess body weight and the associated cancer burden have been rising over the past several decades globally. Between 1975 and 2016, the prevalence of excess body weight in adults-defined as a body mass index (BMI) ≥ 25 kg/m² -increased from nearly 21% in men and 24% in women to approximately 40% in both sexes. Notably, the prevalence of obesity (BMI ≥ 30 kg/m² ) quadrupled in men, from 3% to 12%, and more than doubled in women, from 7% to 16%. This change, combined with population growth, resulted in a more than 6-fold increase in the number of obese adults, from 100 to 671 million. The largest absolute increase in obesity occurred among men and boys in high-income Western countries and among women and girls in Central Asia, the Middle East, and North Africa. The simultaneous rise in excess body weight in almost all countries is thought to be driven largely by changes in the global food system, which promotes energy-dense, nutrient-poor foods, alongside reduced opportunities for physical activity. In 2012, excess body weight accounted for approximately 3.9% of all cancers (544,300 cases) with proportion varying from less than 1% in low-income countries to 7% or 8% in some high-income Western countries and in Middle Eastern and Northern African countries. The attributable burden by sex was higher for women (368,500 cases) than for men (175,800 cases). Given the pandemic proportion of excess body weight in high-income countries and the increasing prevalence in low- and middle-income countries, the global cancer burden attributable to this condition is likely to increase in the future. There is emerging consensus on opportunities for obesity control through the multisectoral coordinated implementation of core policy actions to promote an environment conducive to a healthy diet and active living. The rapid increase in both the prevalence of excess body weight and the associated cancer burden highlights the need for a rejuvenated focus on identifying, implementing, and evaluating interventions to prevent and control excess body weight.

Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Observational epidemiologic studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) uses genetic variants to proxy modifiable exposures to generate more reliable estimates of the causal effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within cardio-metabolic epidemiology, but also holds much promise for identifying possible interventions for cancer prevention and treatment. However, some methodologic challenges in the implementation of MR are particularly pertinent when applying this method to cancer etiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies. In this review, we provide an overview of the key principles and assumptions of MR, focusing on applications of this method to the study of cancer etiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared with conventional epidemiological studies. Finally, limitations of MR and recent methodologic developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer. Cancer Epidemiol Biomarkers Prev; 27(9); 995-1010. ©2018 AACR.

BMI-mortality association: shape independent of smoking status but different for chronic lung disease and lung cancer

Background

Besides smoking, low or high body mass index (BMI) is associated with chronic lung disease (CLD). It is unclear how CLD is associated with BMI, whether smoking interacts with this association, and how the associations differ from the patterns known for lung cancer.

Population and Methods

Our population comprised 35,212 individuals aged 14–99, who participated in population-based surveys conducted in 1977–1993 in Switzerland (mortality follow-up until 2014). We categorized smokers into never, former, light, and heavy; and BMI into underweight, normal weight, overweight, and obese. Hazard ratios (HRs) were obtained with multivariable Cox proportional hazards models.

Results

CLD mortality was strongly associated with being underweight. This was mainly due to the effect in men (HR 5.04 [2.63–9.66]) and also prevailed in never smokers (HR 1.81 [1.11–3.00]). Obesity was also associated with CLD mortality (HR men: 1.37 [1.01–1.86], women: 1.39 [0.90–2.17]), but not with lung cancer mortality. In line with lung cancer, for CLD, the BMI–mortality association followed the same shape in all smoking categories, suggesting that this association was largely independent of smoking status.

Conclusion

The shape of the BMI–mortality association was inversely linear for lung cancer but followed a U-shape for CLD. Further research should examine the potentially protective effect of obesity on lung cancer occurrence and the possibly hazardous impact of underweight on CLD development.

Body mass index and lung cancer risk in never smokers: a meta-analysis

Background

Obesity is found to increase the risk of most cancer types, but reduce lung cancer risk in many studies. However, the association between obesity and lung cancer is still controversial, mainly owing to the confounding effect of smoking.

Methods

Eligible studies were identified from electric databases to July 1, 2017. Relevant data were extracted and pooled using random-effects models; dose-response and subgroup analyses were also performed.

Results

Twenty-nine studies with more than 10,000 lung cancer cases in15 million never smokers were included. Compared with normal weight, the summary relative risk (RR) was 0.77(95% confidence interval [CI]: 0.68–0.88, P < 0.01) for excess body weight (body mass index [BMI] ≥ 25 kg/m²). An inverse linear dose-response relationship was observed between BMI and lung cancer risk in never smokers, with an RR of 0.89(95% CI: 0.84–0.95, P < 0.01) per 5 kg/m² increment in BMI. The results remained stable in most subgroup analyses. However, when stratified by sex, a significant inverse association existed in women but not in men. Similar results were found in analyses for other categories of BMI.

Conclusion

Our results indicate that higher BMI is associated with lower lung cancer risk in never smokers.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4543-y) contains supplementary material, which is available to authorized users.

Number of Cigarettes Smoked Per Day, Smoking Index, and Intracranial Aneurysm Rupture: A Case-Control Study

Background and purpose

We aimed to investigate the effect of smoking on the risk of intracranial aneurysm (IA) rupture (IAR), specifically relationship between the number of cigarettes smoked per day (CPD) or smoking index and the risk of IAR.

Methods

We performed a single-center case-control study of consecutive patients evaluated or treated for IA at our institution from June 2015 to July 2016. Cases were patients with a ruptured IA. Two age- and sex-matched controls with an unruptured IA were included per case. Conditional logistic regression models were used to assess the relationship between both the CPD and smoking index (CPD × years of smoking) and IAR.

Results

The study population included 127 cases of IAR and 254 controls. The higher IAR risk was associated with cigarette smoking (both current and former) (OR, 2.3; 95% CI, 1.1-4.8; P = 0.029). Our subgroup analysis of smokers revealed a significant association between IAR risk and current smoking (OR, 2.8; 95% CI, 1.2-6.3; P = 0.012), current heavy smoking (CPD ≥ 20) (OR, 3.9; 95% CI, 1.4-11.0; P = 0.007), and a smoking index ≥800 (OR, 11.4; 95% CI, 2.3-24.5; P = 0.003). Former smoking was not significantly associated with IAR (OR, 1.1; 95% CI, 0.3-4.0; P = 0.929).

Conclusion

A dose-response relationship has been noted for intensity and duration of smoking consumption and increased risk of IAR. As smoking is modifiable, this finding is important to managing patients with IAs to quit or reduce smoking prior to life-threatening subarachnoid hemorrhage.

Body mass index and lung cancer risk: a pooled analysis based on nested case-control studies from four cohort studies

BACKGROUND

Obesity has been proposed as a potential protective factor against lung cancer. We examined the association between BMI and lung cancer risk in a pooled analysis based on nested case-control studies from four cohort studies.

METHODS

A case-control study was nested within four cohorts in USA, Europe, China and Singapore that included 4172 cases and 8471 control subjects. BMI at baseline was calculated as weight in kilograms divided by height in meters squared (kg/m2), and classified into 4 categories: underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 25), overweight (25 ≤ BMI < 30) and obese (≥30). Odds ratios (ORs) and 95% confidence intervals (CIs) for BMI-lung cancer associations were estimated using unconditional logistic regression, adjusting for potential confounders.

RESULTS

Considering all participants, and using normal weight as the reference group, a decreased risk of lung cancer was observed for those who were overweight (OR 0.77, 95% CI: 0.68-0.86) and obese (OR 0.69, 95% CI: 0.59-0.82). In the stratified analysis by smoking status, the decreased risk for lung cancer was observed among current, former and never smokers (P for interaction 0.002). The adjusted ORs for overweight and obese groups were 0.79 (95% CI: 0.68-0.92) and 0.75 (95% CI: 0.60-0.93) for current smokers, 0.70 (95% CI: 0.53-0.93) and 0.55 (95% CI: 0.37-0.80) for former smokers, 0.77 (95% CI: 0.59-0.99), and 0.71 (95% CI: 0.44-1.14) for never smokers, respectively. While no statistically significant association was observed for underweight subjects who were current smokers (OR 1.24, 95% CI: 0.98-1.58), former smokers (OR 0.27, 95% CI: 0.12-0.61) and never smokers (OR 0.83, 95% CI: 0.5.-1.28).

CONCLUSION

The results of this study provide additional evidence that obesity is associated with a decreased risk of lung cancer. Further biological studies are needed to address this association.

Significant Association Between Polymorphisms of Wnt Antagonist Genes and Lung Cancer

Further elucidation of the molecular mechanisms underlying lung cancer (LC) is essential for the development of new effective therapeutic agents. Recently, involvement of Wnt antagonists in oncogenesis has been demonstrated in several cancers. The investigation of their contribution to lung carcinogenesis is still under investigation. We aimed to investigate whether there is a susceptibility or preventive effect of Wnt antagonist gene polymorphisms on the development and/or prognosis of LC. We investigated 110 LC patients and 160 controls. Single-nucleotide polymorphisms of Wnt antagonist genes including DKK2 (rs17037102), DKK3 (rs3206824), DKK3 intron4 G/C (rs7396187), DKK4 (rs2073664), and sFRP4 (rs1802074) were analyzed using nested polymerase chain reaction and restriction fragment length polymorphism. Results showed that patients with DKK3 AA compared with controls have a decreased risk of LC (adjusted for smoking habit, body mass index, and familial history) (P = 0.02; odds ratio [OR],0.08; 95% confidence interval [95% CI], 0.01-0.7). It was found that, for sFRP4 polymorphism, patients with GG and GA genotypes versus AA genotype controls showed a decreased risk for LC (P = 0.01; [OR, 0.19; 95% CI, 0.05-0.73 for GG genotype]; [OR = 0.18, 95% CI, 0.04-0.72 for GA genotype]). In addition, a decreased risk of LC was also found for the genotype combination of DKK3 (rs3206824) GG and sFRP4 AG + GG (P = 0.004; OR, 0.12; 95% CI, 0.02-0.58). We suggest that these 2 polymorphisms have a protective effect on LC in this study.

Cigarette use, comorbidities, and prognosis in a prospective head and neck squamous cell carcinoma population

BACKGROUND

To better understand the associations between a history of tobacco use and survival outcomes, cigarette use was prospectively surveyed in 687 previously untreated patients with cancer of the oral cavity (n = 271), oropharynx (n = 257), larynx (n = 135), or hypopharynx (n = 24).

METHODS

Kaplan-Meier and Cox models explored the associations of tobacco use intensity (packs/day), duration (years of use), and timing before diagnosis with overall survival (OS), disease-specific survival (DSS), and recurrence-free survival (RFS).

RESULTS

Cigarette use duration, timing, and intensity were significant predictors for all outcomes in univariate analysis. Never smoking and pack-years were not significantly associated with outcomes after adjustment for prognostic factors, such as stage, comorbidities, and human papillomavirus (HPV) status, which were strongly associated with clinical outcomes.

CONCLUSION

The findings confirm the association between smoking history and survival and the importance of clinical variables in evaluating smoking as a prognostic factor. Timing, intensity, and duration of cigarette use should be considered with other prognostic factors when considering risk stratification for treatment planning. © 2016 Wiley Periodicals, Inc. Head Neck 38: 1810-1820, 2016.

Anthropometry and the Risk of Lung Cancer in EPIC

The associations of body mass index (BMI) and other anthropometric measurements with lung cancer were examined in 348,108 participants in the European Investigation Into Cancer and Nutrition (EPIC) between 1992 and 2010. The study population included 2,400 case patients with incident lung cancer, and the average length of follow-up was 11 years. Hazard ratios were calculated using Cox proportional hazard models in which we modeled smoking variables with cubic splines. Overall, there was a significant inverse association between BMI (weight (kg)/height (m)(2)) and the risk of lung cancer after adjustment for smoking and other confounders (for BMI of 30.0-34.9 versus 18.5-25.0, hazard ratio = 0.72, 95% confidence interval: 0.62, 0.84). The strength of the association declined with increasing follow-up time. Conversely, after adjustment for BMI, waist circumference and waist-to-height ratio were significantly positively associated with lung cancer risk (for the highest category of waist circumference vs. the lowest, hazard ratio = 1.25, 95% confidence interval: 1.05, 1.50). Given the decline of the inverse association between BMI and lung cancer over time, the association is likely at least partly due to weight loss resulting from preclinical lung cancer that was present at baseline. Residual confounding by smoking could also have influenced our findings.

Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer

BACKGROUND

Adiposity traits have been associated with risk of many cancers in observational studies, but whether these associations are causal is unclear. Mendelian randomization (MR) uses genetic predictors of risk factors as instrumental variables to eliminate reverse causation and reduce confounding bias. We performed MR analyses to assess the possible causal relationship of birthweight, childhood and adult body mass index (BMI), and waist-hip ratio (WHR) on the risks of breast, ovarian, prostate, colorectal and lung cancers.

METHODS

We tested the association between genetic risk scores and each trait using summary statistics from published genome-wide association studies (GWAS) and from 51 537 cancer cases and 61 600 controls in the Genetic Associations and Mechanisms in Oncology (GAME-ON) Consortium.

RESULTS

We found an inverse association between the genetic score for childhood BMI and risk of breast cancer [odds ratio (OR) = 0.71 per standard deviation (s.d.) increase in childhood BMI; 95% confidence interval (CI): 0.60, 0.80; P = 6.5 × 10(-5)). We also found the genetic score for adult BMI to be inversely associated with breast cancer risk (OR = 0.66 per s.d. increase in BMI; 95% CI: 0.57, 0.77; P = 2.5 × 10(-7)), and positively associated with ovarian cancer (OR = 1.35; 95% CI: 1.05, 1.72; P = 0.017), lung cancer (OR = 1.27; 95% CI: 1.09, 1.49; P = 2.9 × 10(-3)) and colorectal cancer (OR = 1.39; 95% CI: 1.06, 1.82, P = 0.016). The inverse association between genetically predicted adult BMI and breast cancer risk remained even after adjusting for directional pleiotropy via MR-Egger regression.

CONCLUSIONS

Findings from this study provide additional understandings of the complex relationship between adiposity and cancer risks. Our results for breast and lung cancer are particularly interesting, given previous reports of effect heterogeneity by menopausal status and smoking status.

Exploratory Study to Identify Radiomics Classifiers for Lung Cancer Histology

Background

Radiomics can quantify tumor phenotypic characteristics non-invasively by applying feature algorithms to medical imaging data. In this study of lung cancer patients, we investigated the association between radiomic features and the tumor histologic subtypes (adenocarcinoma and squamous cell carcinoma). Furthermore, in order to predict histologic subtypes, we employed machine-learning methods and independently evaluated their prediction performance.

Methods

Two independent radiomic cohorts with a combined size of 350 patients were included in our analysis. A total of 440 radiomic features were extracted from the segmented tumor volumes of pretreatment CT images. These radiomic features quantify tumor phenotypic characteristics on medical images using tumor shape and size, intensity statistics, and texture. Univariate analysis was performed to assess each feature’s association with the histological subtypes. In our multivariate analysis, we investigated 24 feature selection methods and 3 classification methods for histology prediction. Multivariate models were trained on the training cohort and their performance was evaluated on the independent validation cohort using the area under ROC curve (AUC). Histology was determined from surgical specimen.

Results

In our univariate analysis, we observed that fifty-three radiomic features were significantly associated with tumor histology. In multivariate analysis, feature selection methods ReliefF and its variants showed higher prediction accuracy as compared to other methods. We found that Naive Baye’s classifier outperforms other classifiers and achieved the highest AUC (0.72; p-value = 2.3 × 10⁻⁷) with five features: Stats_min, Wavelet_HLL_rlgl_lowGrayLevelRunEmphasis, Wavelet_HHL_stats_median, Wavelet_HLL_stats_skewness, and Wavelet_HLH_glcm_clusShade.

Conclusion

Histological subtypes can influence the choice of a treatment/therapy for lung cancer patients. We observed that radiomic features show significant association with the lung tumor histology. Moreover, radiomics-based multivariate classifiers were independently validated for the prediction of histological subtypes. Despite achieving lower than optimal prediction accuracy (AUC 0.72), our analysis highlights the impressive potential of non-invasive and cost-effective radiomics for precision medicine. Further research in this direction could lead us to optimal performance and therefore to clinical applicability, which could enhance the efficiency and efficacy of cancer care.

Body mass index and risk of lung cancer: Systematic review and dose-response meta-analysis

Questions remain about the significance of the dose-response relationship between body mass index (BMI) and lung cancer (LC) risk. Pertinent studies were identified through a search in EMBASE and PUBMED from July 2014 until March 2015. The summary relative risk (SRR) and confidence interval (CI) were estimated. The dose-response relationship was assessed using a restricted cubic spline. The overall meta-analysis showed evidence of a nonlinear association between BMI and LC risk (Pnonlinearity < 0.001). The SRR were 0.98 (95%CI: 0.95-1.01) for 25 kg/m(2), 0.91 (95%CI: 0.85-0.98) for 30 kg/m(2) and 0.81 (95% CI: 0.72-0.91) for 35 kg/m(2), with mild between-study heterogeneity (I(2) = 5%). The results of the stratified analysis by gender were comparable to those of the overall meta-analysis. When stratified by smoking status, linear dose-response associations were observed for current smokers, ex-smokers and non-smokers (Pnonlinearity > 0.05), whereas the effects were attenuated when restricting analysis to non-smokers, and at the point of 30 kg/m(2), the SRR was 0.96 (95%CI: 0.86-1.07) for males and 0.95 (95%CI: 0.89-1.02) for females. This meta-analysis provides quantitative evidence that increasing BMI is a protective factor against LC. Keeping normal-to-moderate BMI should be prescribed as an evidence-based lifestyle tip for LC prevention in smokers.

Lack of a protective effect of cotton dust on risk of lung cancer: evidence from two population-based case-control studies

BACKGROUND

Lung cancer is the leading cause of cancer death in North America. Exposure to cotton dust has previously been reported to decrease the risk of lung cancer.

METHODS

We used data from two large case-control studies conducted in Montreal from 1979-1986 (Study 1) and 1996-2002 (Study 2) respectively, to examine the association between occupational exposure to cotton dust and risk of lung cancer. Cases were diagnosed with incident histologically-confirmed lung cancer (857 in Study 1, 1203 in Study 2). Population controls were randomly selected from electoral lists and frequency-matched to cases by age and sex (533 in Study 1, 1513 in Study 2). Interviews for the two studies used a virtually identical questionnaire to obtain lifetime occupational and smoking history, and several lifestyle covariates. Each participant's lifetime occupational history was reviewed by experts to assess exposure to a number of occupational agents, including cotton dust. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated by unconditional logistic regression, adjusting for potential confounders.

RESULTS

The lifetime prevalence of exposure to cotton dust was approximately 10%-15% in both studies combined, with some variation by study and by sex. Overall there was no decreased risk of lung cancer among subjects exposed to cotton dust. Rather, among all subjects there was a suggestion of slightly increased risk associated with any lifetime exposure to cotton dust (OR = 1.2, 95% CI: 1.0-1.5). This risk appeared to be concentrated among cases of adenocarcinoma (OR = 1.6, 95% CI: 1.2-2.2), and among moderate and heavy smokers (OR = 1.3, 95% CI: 1.0-1.7). There was no association when restricting to cases of either squamous cell or small cell cancer, or among never smokers and light smokers. An analogous examination of subjects exposed to wool dust revealed neither increased nor decreased risks of lung cancer.

CONCLUSIONS

There was no evidence that cotton dust exposure decreased risks of lung cancer.

Body mass index, cholesterol level and risk of lung cancer in Lithuanian men

OBJECTIVE

Our objective was to investigate the association between body mass index (BMI), total serum cholesterol (TSC) level and risk of lung cancer in a Lithuanian population-based cohort study.

MATERIALS AND METHODS

The study included 6729 men initially free from cancer. During the follow-up (1978-2008), 358 lung cancer cases were identified. Cox proportional hazards models were used to estimate hazard ratios (HR) and corresponding 95% confidence intervals (95% CI).

RESULTS

Following adjustment for age, smoking, alcohol consumption, and education, BMI 25-29.9 and ≥30.0kg/m(2) hazard ratios (HR) were significantly associated with decreasing risk for lung cancer, HR=0.73; 95% CI: 0.59, 0.91 and 0.62; 95% CI: 0.45, 0.87, respectively (ptrend=0.001) compared to BMI<25 kg/m(2). Inverse association between BMI and lung cancer was observed among current smokers. We found no evidence that BMI was associated with decreased lung cancer risk in never smokers, although small sample size precluded meaningful analysis. Not significantly lower risk of lung cancer among participants in the 5th quintile compared with the 1st quintile of TSC concentrations was observed. HR per 1 mmol/l increase of TSC was 0.90; 95% CI: 0.82, 1.00. Findings suggest consistent effects of BMI and TSC when follow-up was 1993-2008.

CONCLUSION

Our results show an inverse dose-dependent association between lung cancer risk and BMI in Lithuanian men, especially among current smokers. The inverse association could not be attributed to preclinical cancer effect hypothesis. TSC level was not statistically significantly related to a lung cancer incidence.

Pollution in the working place and social status: co-factors in lung cancer carcinogenesis

INTRODUCTION

Apart from the association with tobacco consumption, other factors of importance for prevention and early diagnosis of lung cancer have received little attention. We present a case-control study focusing on professional exposure to carcinogens and social status.

METHODS

A written questionnaire was completed by 551 consecutive patients with lung cancer and 494 patients with large bowel cancer. The groups were balanced regarding gender and age distribution. The questionnaire included data on place of birth, education, smoking history, diet and alcohol intake, body weight and height, occupation, housing conditions and family income. According to standard epidemiological criteria, professional exposure to carcinogens was classified as professions with exposure to confirmed lung cancer carcinogens, professions with exposure to suspected lung cancer carcinogens and other professions.

RESULTS

As expected, there were significant differences between the two groups regarding smoking status. While there were no significant differences in educational levels, more immigrants were among patients with lung cancer (17.9% vs 11.6%, p=0.005). On average, lung cancer patients had a lower body mass index (BMI) at 24.77, as compared to 26.14 for large bowel cancer (p=0.000). Lung cancer patients had lower income and poorer housing conditions; the bivariate difference was significant both for income levels (p=0.046) and type of residence (p=0.009). The proportion of patients working in professions with exposures to known carcinogens was 33.5% for lung cancer, and 17.1% for large bowel cancer (p=0.000). In the multivariate analysis, smoking (p=0.000), BMI (p=0.000) and type of occupation (p=0.001) were significant factors.

CONCLUSIONS

While there is no doubt about smoking in lung cancer carcinogenesis, professional exposure to carcinogens and belonging to lower socio-economic strata also play an important role.

Serum uric acid and the risk of respiratory disease: a population-based cohort study

Introduction

Uric acid is the most abundant molecule with antioxidant properties found in human blood serum. We examined the relationship between serum uric acid and the incidence of respiratory disease including any effect modification by smoking status.

Methods

A cohort with serum uric acid measured between 1 January 2000 and 31 December 2012 was extracted from The Health Improvement Network primary care research database. New diagnoses of COPD and lung cancer were ascertained based on diagnostic codes entered into the medical records.

Results

During 1 002 496 person years (PYs) of follow-up, there were 3901 COPD diagnoses and 1015 cases of lung cancer. After multivariable adjustment, strong interactions with smoking status were detected (p<0.001) for both outcomes with significant negative relationships between serum uric acid and respiratory disease for current smokers but no strong relationships for never-smokers or ex-smokers. The relationships were strongest for lung cancer in heavy smokers (≥20 cigarettes per day) with predicted incidence rates 97 per 10 000 PYs (95% CI 68 to 126) in the lowest serum uric acid quintile (100–250 µmol/L) compared with a predicted 28 per 10 000 PYs (95% CI 14 to 41) in the highest quintile (438–700 µmol/L).

Conclusions

Low levels of serum uric acid are associated with higher rates of COPD and lung cancer in current smokers after accounting for conventional risk factors.

History of allergic diseases and lung cancer risk

BACKGROUND

The exact nature and direction of the association between a history of allergic diseases and lung cancer risk remain controversial.

OBJECTIVE

To examine the association between self-reported history of allergic diseases and lung cancer using data from a population-based case-control study conducted in the Montreal metropolitan area (1996-2002).

METHODS

The study is based on interview data collected from 1,169 incident lung cancer cases and 1,486 controls. Separate logistic regression models were used to estimate the relative risk of lung cancer, using odds ratios (ORs) and 95% confidence intervals (CIs), in subjects with vs without asthma, eczema, or hay fever after adjustment for several sociodemographic and lifestyle factors, including smoking.

RESULTS

For asthma, the OR was 0.90 (95% CI 0.65-1.24), which decreased to 0.76 (95% CI 0.54-1.08) for subjects whose onset was more than 2 years before lung cancer diagnosis or interview and then to 0.64 (95% CI 0.44-0.93) when restricted to subjects who reported using medication for their asthma. For eczema, the point estimate was 0.73 (95% CI 0.48-1.12), which decreased to 0.63 (95% CI 0.38-1.07) when considering eczema only in those who reported medication use. Hay fever showed the strongest inverse association with lung cancer (OR 0.37, 95% CI 0.24-0.59).

CONCLUSION

All 3 allergic diseases examined were inversely associated with lung cancer, although the strength of the protective effect varied. History of allergic diseases seems to have a protective role in lung cancer incidence, after consideration of potential confounders, including lifetime smoking history.