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Background and purpose: We analyzed the distribution of metastatic sites and survival of lung cancer patients with metastases based on hospital registration to provide real-world data support for the treatment and survival management of lung cancer patients. Methods: A total of 1 490 lung cancer patients who developed metastasis during the follow-up in Fudan University Shanghai Cancer Center from 2008 to 2017 were enrolled in this study. Medical records review, telephone visits and death registry data linkage were applied in collecting endpoint data. The effects of age at diagnosis, gender and histological subtype on the distribution of metastases were studied. The Kaplan-Meier method was used to evaluate the overall survival (OS) rates of different metastatic sites. Results: The median follow-up time was 40.8 months. During the follow-up period, 937 cases died from all causes. 67.7% of patients only had single-site metastasis, while 32.3% of patients had multiple-site metastases. The common metastatic sites were bone (33.8%), brain (33.6%), lung (22.8%), liver (12.0%) and adrenal gland (3.7%). Female patients had more metastases to brain (37.8% vs 31.4%). Younger patients were more likely to develop multiple-site metastases, and small cell carcinomas patients had more brain metastases (47.2%) and liver metastases (20.9%). Lung metastasis featured relatively best survival (1-year OS rate: 78.3%, 3-year OS rate: 47.1%, 5-year OS rate: 29.5%), whereas liver metastasis had relatively the worst prognosis (1-year OS rate: 46.4%, 3-year OS rate: 15.2%, 5-year OS rate: 3.6%). Conclusion: The proportions of bone and brain metastases in lung cancer patients with metastasis are high. The distribution of metastatic sites is associated with gender, age at diagnosis and histological type. The prognosis of patient with different metastatic sites is different. Mechanisms or clinical treatment plans can be studied for different metastatic sites to improve the prognosis of late-stage lung cancer patients in future research.

Background We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test. Methods We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. Results The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (P difference =.001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. Conclusion Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung. [ABSTRACT FROM AUTHOR]

Identification of risk biomarkers may enhance early detection of smoking-related lung cancer. We measured between 392 and 1,162 proteins in blood samples drawn at most three years before diagnosis in 731 smoking-matched case-control sets nested within six prospective cohorts from the US, Europe, Singapore, and Australia. We identify 36 proteins with independently reproducible associations with risk of imminent lung cancer diagnosis (all p < 4 × 10−5). These include a few markers (e.g. CA-125/MUC-16 and CEACAM5/CEA) that have previously been reported in studies using pre-diagnostic blood samples for lung cancer. The 36 proteins include several growth factors (e.g. HGF, IGFBP-1, IGFP-2), tumor necrosis factor-receptors (e.g. TNFRSF6B, TNFRSF13B), and chemokines and cytokines (e.g. CXL17, GDF-15, SCF). The odds ratio per standard deviation range from 1.31 for IGFBP-1 (95% CI: 1.17–1.47) to 2.43 for CEACAM5 (95% CI: 2.04–2.89). We map the 36 proteins to the hallmarks of cancer and find that activation of invasion and metastasis, proliferative signaling, tumor-promoting inflammation, and angiogenesis are most frequently implicated. Lung cancer screening could enhance early diagnosis and treatment. Here, the authors used proteomic analysis of pre-diagnosis samples across 6 cohorts to identify 36 proteins associated with imminent lung cancer diagnosis. [ABSTRACT FROM AUTHOR]

The EarlyCDT‐Lung test is a blood‐based autoantibody assay intended to identify high‐risk individuals for low‐dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT‐Lung test in ever‐smokers. We conducted a nested case‐control study within two prospective cohorts to evaluate the risk‐discriminatory performance of the EarlyCDT‐Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT‐Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT‐Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34‐2.30) for a moderate risk EarlyCDT‐Lung test result and 1.09 (95% CI: 0.48‐2.47) for a high‐risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6‐14) and overall specificity was 92% (95% CI: 87‐96) when considering a high‐risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2‐32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT‐Lung test in identifying the high‐risk subjects in ever‐smokers for lung cancer screening in the EPIC and NSHDS cohorts. [ABSTRACT FROM AUTHOR]

Background: Little is known about the prognostic advantage of sex for pulmonary adenocarcinoma among Chinese patients. In this study, we aimed to investigate the true sex differences in prognosis by adjusting for confounders and to explore whether the differences were time‐varying. Methods: We identified 4438 lung adenocarcinoma patients who underwent surgery at a regional Cancer Center of China from 2008 to 2016, retrospectively. Sex, age group, smoking history, year of diagnosis and pathological stage were collected. Time‐dependent Cox regression models with inverse probability of treatment weighting (IPTW) based on propensity score were used to assess the effect of sex and account for confounders. Landmark analyses were conducted to assess survival before, and after, five years. Results: Of these patients, 1761 (39.7%) were men and 2677 (60.3%) were women. Median follow‐up time was 52.6 months. After IPTW adjustment, women were found to have significantly better survival than men varying with time in both crude and IPTW models (hazard ratio [HR] [t] = 0.453*1.015t, where t is the length of time from treatment and its unit is month, p < 0.001). Women had significantly better survival than men within 0–5 years after surgery (HR = 0.763, 95% CI: 0.649–0.897, p = 0.001), whereas there was no difference after five years (HR = 1.135, 95% CI: 0.803–1.605, p = 0.472). In subgroup analysis, women in the 61–71+ age group, in the more than 20 year packs group, pathological stage 0–IB group, and 2013–2016 diagnosis period group revealed the same prognostic pattern. Conclusions: Compared with men, women had better survival after surgical resection of lung adenocarcinoma, especially those who were older and nonsmokers or heavy‐smokers and were pathological stage 0–IB in early years, while the advantage for women diminished with time. [ABSTRACT FROM AUTHOR]

Background: The role of adjuvant chemotherapy (ACT) for patients with stage IB–IIA non‐small cell lung cancer (NSCLC) according to the eighth edition of the AJCC TNM staging system remains controversial. Methods: Data were collected from patients with NSCLC stage IB–IIA according to the eighth edition of the AJCC TNM staging system who underwent surgical resection from 2008 to 2015. The relationship between ACT and overall survival (OS) or disease‐free survival (DFS) was analyzed using the Kaplan–Meier method and Cox proportional hazards model. Results: The study included 648 patients with completely resected NSCLC stage IB–IIA; 312 underwent ACT after surgical resection and 336 were placed under observation. After propensity score matching, 247 pairs of patients were matched and the five‐year OS was 88.08% and 83.12% (P = 0.13) in ACT and non‐ACT settings, respectively. Subgroup analyses demonstrated that ACT treatment was correlated with an improved five‐year OS in patients with visceral pleural invasion (VPI) in the 3 < tumor ≤ 4 cm subgroup (93.98% and 68.93%, P < 0.01). Conclusions: ACT was not significantly associated with improved five‐year OS in stage IB–IIA NSCLC patients. However, further subgroup analysis showed that patients with VPI in the 3 < tumor ≤ 4 cm (T2aN0M0, stage IB) subgroup might benefit more from ACT. Further studies are required to validate the findings and better systemic strategies need to be developed in these patients. Key points: Significant findings of the study: For patients with stage IB–IIA NSCLC according to the eighth edition of the AJCC TNM staging system, the effect of ACT remains unclear.ACT was not significantly associated with improved five‐year OS in stage IB–IIA NSCLC patients. However, it was correlated with better DFS before or after PSM.Patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit from ACT. What this study adds: ACT was not significantly associated with improved five‐year OS in stage IB–IIA NSCLC patients. However, it was correlated with better DFS before or after PSM.Patients with VPI in the 3 < tumor ≤ 4 cm subgroup may benefit from ACT. [ABSTRACT FROM AUTHOR]

Background: Low‐dose computed tomography screening has been proved to reduce lung cancer mortality, however, the issues of high false‐positive rate and overdiagnosis remain unsolved. Risk prediction models for lung cancer that could accurately identify high‐risk populations may help to increase efficiency. We thus sought to develop a risk prediction model for lung cancer incorporating epidemiological and metabolic markers in a Chinese population. Methods: During 2006 and 2015, a total of 122 497 people were observed prospectively for lung cancer incidence with the total person‐years of 976 663. Stepwise multivariable‐adjusted logistic regressions with Pentry =.15 and Pstay =.20 were conducted to select the candidate variables including demographics and metabolic markers such as high‐sensitivity C‐reactive protein (hsCRP) and low‐density lipoprotein cholesterol (LDL‐C) into the prediction model. We used the C‐statistic to evaluate discrimination, and Hosmer‐Lemeshow tests for calibration. Tenfold cross‐validation was conducted for internal validation to assess the model's stability. Results: A total of 984 lung cancer cases were identified during the follow‐up. The epidemiological model including age, gender, smoking status, alcohol intake status, coal dust exposure status, and body mass index generated a C‐statistic of 0.731. The full model additionally included hsCRP and LDL‐C showed significantly better discrimination (C‐statistic = 0.735, P =.033). In stratified analysis, the full model showed better predictive power in terms of C‐statistic in younger participants (<50 years, 0.709), females (0.726), and former or current smokers (0.742). The model calibrated well across the deciles of predicted risk in both the overall population (PHL =.689) and all subgroups. Conclusions: We developed and internally validated an easy‐to‐use risk prediction model for lung cancer among the Chinese population that could provide guidance for screening and surveillance. [ABSTRACT FROM AUTHOR]

To investigate the independent and joint associations of blood lipids and lipoproteins with lung cancer risk in Chinese males, a prospective cohort study was conducted. A total of 109,798 males with baseline information on total cholesterol (TC), triglycerides (TG), low‐density lipoprotein cholesterol (LDL‐C), high‐density lipoprotein cholesterol (HDL‐C) and non‐HDL were prospectively observed from 2006 to 2015 for cancer incidence. Cox proportional hazards models and restricted cubic spline (RCS) analysis were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). During a 9‐year follow‐up, a total of 986 lung cancer cases were identified. Multivariable analyses showed that both males with low TC (HRQ1vs.Q2 = 1.27, 95%CI: 1.02–1.60) and males with high TC (HRQ5vs.Q2 = 1.30, 95%CI: 1.04–1.63) had an increased lung cancer risk, and the U‐shaped association was also revealed in the RCS analysis (poverall = 0.013, pnonlinear = 0.006). Furthermore, both low TG (HRQ1vs.Q2 = 1.24, 95%CI: 0.99–1.54) and high TG (HRQ5vs.Q2 = 1.27, 95%CI: 1.01–1.59) were associated with increased lung cancer risk, while low LDL‐C (HRQ1vs.Q2 = 1.38, 95%CI: 1.11–1.72) was associated with increased lung cancer risk. When TC, TG and LDL‐C were considered jointly, the number of abnormal indicators was linearly associated with an increased risk of lung cancer (ptrend < 0.001), as subjects with three abnormal indicators had a twofold higher risk of developing lung cancer (HR = 2.02, 95%CI: 1.62–2.54). Notably, these associations were statistically significant among never smokers, never drinkers and overweight/obese males. These findings suggest that dyslipidemia may potentially be a modifiable risk factor that has key scientific and clinical significance for lung cancer prevention. What's new? Lung cancer arises from more than just smoking: abnormal blood lipid levels also contribute to the disease. In this report, the authors evaluated the role of cholesterol and triglycerides in lung cancer. They collected information on total cholesterol, triglycerides, LDL‐C, HDL‐C, and non‐HDL‐C from more than 100,000 men in northern China, and tracked cancer incidence for 9 years. Men whose total cholesterol or triglycerides were either low or high had increased risk of lung cancer, they found. Low LDL‐C levels also associated with an increase. Considered jointly, the number of abnormal factors was linearly associated with lung cancer risk. [ABSTRACT FROM AUTHOR]

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies. [ABSTRACT FROM AUTHOR]