Propensity score analysis of lung cancer risk in a population with high prevalence of non-smoking related lung cancer

Association between family history with lung cancer incidence and mortality risk in the Asia Cohort Consortium

Family history of lung cancer (FHLC) has been widely studied but most prospective cohort studies have primarily been conducted in non-Asian countries. We assessed the association between FHLC with risk of lung cancer (LC) incidence and mortality in a population of East Asian individuals. A total of 478,354 participants from 11 population-based cohorts in the Asia Cohort Consortium were included. A Cox proportional hazards regression model was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). A total of 7,785 LC incident cases were identified. FHLC (any LC subtype) was associated with an increased risk of LC incidence (HR = 1.45, 95% CI = 1.30-1.63). The positive association was observed in men and women (HR = 1.44, 95% CI = 1.26-1.66 in men; HR = 1.47, 95% CI = 1.22-1.79 in women), and in both never-smokers and ever-smokers (HR = 1.43, 95% CI = 1.18-1.73 in never-smokers; HR = 1.46, 95% CI =1.27-1.67 in ever-smokers). FHLC was associated with an increased risk of lung adenocarcinoma (HR = 1.63, 95% CI: 1.36-1. 94), squamous cell carcinoma (HR = 1.88, 95% CI: 1.46-2.44), and other non-small cell LC (HR = 1.94, 95% CI: 1.02-3.68). However, we found no evidence of significant effect modification by sex, smoking status, and ethnic groups. In conclusion, FHLC was associated with increased risk of LC incidence and mortality, and the associations remained consistent regardless of sex, smoking status and ethnic groups among the East Asian population.

Construction and validation of a predictive model of invasive adenocarcinoma in pure ground-glass nodules less than 2 cm in diameter

OBJECTIVES

In this study, we aimed to develop a multiparameter prediction model to improve the diagnostic accuracy of invasive adenocarcinoma in pulmonary pure glass nodules.

METHOD

We included patients with pulmonary pure glass nodules who underwent lung resection and had a clear pathology between January 2020 and January 2022 at the Qilu Hospital of Shandong University. We collected data on the clinical characteristics of the patients as well as their preoperative biomarker results and computed tomography features. Thereafter, we performed univariate and multivariate logistic regression analyses to identify independent risk factors, which were then used to develop a prediction model and nomogram. We then evaluated the recognition ability of the model via receiver operating characteristic (ROC) curve analysis and assessed its calibration ability using the Hosmer-Lemeshow test and calibration curves. Further, to assess the clinical utility of the nomogram, we performed decision curve analysis.

RESULT

We included 563 patients, comprising 174 and 389 cases of invasive and non-invasive adenocarcinoma, respectively, and identified seven independent risk factors, namely, maximum tumor diameter, age, serum amyloid level, pleural effusion sign, bronchial sign, tumor location, and lobulation. The area under the ROC curve was 0.839 (95% CI: 0.798-0.879) for the training cohort and 0.782 (95% CI: 0.706-0.858) for the validation cohort, indicating a relatively high predictive accuracy for the nomogram. Calibration curves for the prediction model also showed good calibration for both cohorts, and decision curve analysis showed that the clinical prediction model has clinical utility.

CONCLUSION

The novel nomogram thus constructed for identifying invasive adenocarcinoma in patients with isolated pulmonary pure glass nodules exhibited excellent discriminatory power, calibration capacity, and clinical utility.

Managing Persistent Subsolid Nodules in Lung Cancer: Education, Decision Making, and Impact of Interval Growth Patterns

With the popularization of lung cancer screening, many persistent subsolid nodules (SSNs) have been identified clinically, especially in Asian non-smokers. However, many studies have found that SSNs exhibit heterogeneous growth trends during long-term follow ups. This article adopted a narrative approach to extensively review the available literature on the topic to explore the definitions, rationale, and clinical application of different interval growths of subsolid pulmonary nodule management and follow-up strategies. The development of SSN growth thresholds with different growth patterns could support clinical decision making with follow-up guidelines to reduce over- and delayed diagnoses. In conclusion, using different SSN growth thresholds could optimize the follow-up management and clinical decision making of SSNs in lung cancer screening programs. This could further reduce the lung cancer mortality rate and potential harm from overdiagnosis and over management.

ACR Appropriateness Criteria® Lung Cancer Screening: 2022 Update

Lung cancer remains the leading cause of cancer-related mortality for men and women in the United States. Screening for lung cancer with annual low-dose CT is saving lives, and the continued implementation of lung screening can save many more. In 2015, the CMS began covering annual lung screening for those who qualified based on the original United States Preventive Services Task Force (USPSTF) lung screening criteria, which included patients 55 to 77 year of age with a 30 pack-year history of smoking, who were either currently using tobacco or who had smoked within the previous 15 years. In 2021, the USPSTF issued new screening guidelines, decreasing the age of eligibility to 80 years of age and pack-years to 20. Lung screening remains controversial for those who do not meet the updated USPSTF criteria, but who have additional risk factors for the development of lung cancer. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

An integrated nomogram combined semantic-radiomic features to predict invasive pulmonary adenocarcinomas in subjects with persistent subsolid nodules

Background

Patients with persistent pulmonary subsolid nodules have a relatively high incidence of lung adenocarcinoma. Preoperative early diagnosis of invasive pulmonary adenocarcinoma spectrum lesions could help avoid extensive advanced cancer management and overdiagnosis in lung cancer screening programs.

Methods

In total, 260 consecutive patients with persistent subsolid nodules ≤30 mm (n=260) confirmed by surgical pathology were retrospectively investigated from February 2016 to August 2020 at the Kaohsiung Veterans General Hospital. All patients underwent surgical resection within 3 months of the chest CT exam. The study subjects were divided into a training cohort (N=195) and a validation cohort (N=65) at a ratio of 3:1. The purpose of our study was to develop and validate a least absolute shrinkage and selection operator-derived nomogram integrating semantic-radiomic features in differentiating preinvasive and invasive pulmonary adenocarcinoma lesions, and compare its predictive value with clinical-semantic, semantic, and radiologist's performance.

Results

In the training cohort of 195 subsolid nodules, 106 invasive lesions and 89 preinvasive lesions were identified. We developed a least absolute shrinkage and selection operator-derived combined nomogram prediction model based on six predictors (nodular size, CTR, roundness, GLCM_Entropy_log10, HISTO_Entropy_log10, and CONVENTIONAL_Humean) to predict the invasive pulmonary adenocarcinoma lesions. Compared with other predictive models, the least absolute shrinkage and selection operator-derived model showed better diagnostic performance with an area under the curve of 0.957 (95% CI: 0.918 to 0.981) for detecting invasive pulmonary adenocarcinoma lesions with balanced sensitivity (92.45%) and specificity (88.64%). The results of Hosmer-Lemeshow test showed P values of 0.394 and 0.787 in the training and validation cohorts, respectively, indicating good calibration power.

Conclusions

We developed a least absolute shrinkage and selection operator-derived model integrating semantic-radiomic features with good calibration. This nomogram may help physicians to identify invasive pulmonary adenocarcinoma lesions for guidance in personalized medicine and make more informed decisions on managing subsolid nodules.

Incidence and mortality of lung cancer in 2018 and the temporal trends from 2010 to 2018 in Henan province, China: a population-based registry study

Background

The disease burden of lung cancer is high in Henan province, China, it is out of the utmost significance to figure the current epidemic status and temporal trend of lung cancer for effective prevention and control.

Methods

The qualified data was obtained from the Henan Provincial Central Cancer Registry of China, covering 30.51% of the whole population. Incidence, mortality, proportions, and cumulative rates (among patients aged 0-74 years old) of lung cancer by areas, sex and age groups were estimated. The world Segi's standard population was applied to calculate the age-standardized rate. Joinpoint regression was used to calculate annual percentage change (APC) and average annual percentage change (AAPC) to evaluate temporal trends from 2010 to 2018.

Results

In 2018, there were about 55,344 new cases of lung cancer in Henan province, with the crude incidence of 50.75/100,000, the age-standardized incidence rate by world standard (Segi's) population (ASIRW) of 37.14/100,000, and the cumulative rate of 4.57%. About 41,782 people died from lung cancer in 2018, with the crude mortality rate of 38.31/100,000, the age-standardized mortality rate by world standard (Segi's) population (ASMRW) of 27.09/100,000, and the cumulative rate of 3.22%. The age-specific incidence and mortality of lung cancer increased gradually as age increased and reached the peak at the age of 85+ years. The overall ASIRW (AAPC =0.3, P=0.531) and ASMRW (AAPC =-0.2, P=0.687) remained stable from 2010 to 2018, but decreased in urban areas from 2014 to 2018 (APC for ASIRW =-4.7, P=0.023; APC for ASMRW =-5.3, P=0.012). From 2010 to 2018, the incidence rate increased in the rural population aged 75+ years old (AAPC =4.2, P=0.023).

Conclusions

The incidence and mortality rates of lung cancer significantly decreased in urban areas partly due to the Cancer Screening Program in Urban China. Nonetheless, the disease burden remains high, especially in males and elderly population. Comprehensive prevention and control programs, such as smoking cessation intervention, screening, early diagnosis and early treatment programs, need to be implemented to reduce the burden of lung cancer.

Derivation and validation of a prediction model for patients with lung nodules malignancy regardless of mediastinal/hilar lymphadenopathy

BACKGROUND

Clinical prediction models to classify lung nodules often exclude patients with mediastinal/hilar lymphadenopathy, although the presence of mediastinal/hilar lymphadenopathy does not always indicate malignancy. Herein, we developed and validated a multimodal prediction model for lung nodules in which patients with mediastinal/hilar lymphadenopathy were included.

METHODS

A single-center retrospective study was conducted. We developed and validated a logistic regression model including patients with mediastinal/hilar lymphadenopathy. Discrimination of the model was assessed by area under the operating curve. Goodness of fit test was performed via the Hosmer-Lemeshow test, and a nomogram of the logistic regression model was drawn.

RESULTS

There were 311 cases included in the final analysis. A logistic regression model was developed and validated. There were nine independent variables included in the model. The aera under the curve (AUC) of the validation set was 0.91 (95% confidence interval [CI]: 0.85-0.98). In the validation set with mediastinal/hilar lymphadenopathy, the AUC was 0.95 (95% CI: 0.90-0.99). The goodness-of-fit test was 0.22.

CONCLUSIONS

We developed and validated a multimodal risk prediction model for lung nodules with excellent discrimination and calibration, regardless of mediastinal/hilar lymphadenopathy. This broadens the application of lung nodule prediction models. Furthermore, mediastinal/hilar lymphadenopathy added value for predicting lung nodule malignancy in clinical practice.

A radiomics nomogram for invasiveness prediction in lung adenocarcinoma manifesting as part-solid nodules with solid components smaller than 6 mm

Objective

To investigate whether radiomics can help radiologists and thoracic surgeons accurately predict invasive adenocarcinoma (IAC) manifesting as part-solid nodules (PSNs) with solid components <6 mm and provide a basis for rational clinical decision-making.

Materials and Methods

In total, 1,210 patients (mean age ± standard deviation: 54.28 ± 11.38 years, 374 men and 836 women) from our hospital and another hospital with 1,248 PSNs pathologically diagnosed with adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or IAC were enrolled in this study. Among them, 1,050 cases from our hospital were randomly divided into a derivation set (n = 735) and an internal validation set (n = 315), 198 cases from another hospital were used for external validation. Each labeled nodule was segmented, and 105 radiomics features were extracted. Least absolute shrinkage and selection operator (LASSO) was used to calculate Rad-score and build the radiomics model. Multivariable logistic regression was conducted to identify the clinicoradiological predictors and establish the clinical-radiographic model. The combined model and predictive nomogram were developed based on identified clinicoradiological independent predictors and Rad-score using multivariable logistic regression analysis. The predictive performances of the three models were compared via receiver operating characteristic (ROC) curve analysis. Decision curve analysis (DCA) was performed on both the internal and external validation sets to evaluate the clinical utility of the nomogram.

Results

The radiomics model showed superior predictive performance than the clinical-radiographic model in both internal and external validation sets (Az values, 0.884 vs. 0.810, p = 0.001; 0.924 vs. 0.855, p < 0.001, respectively). The combined model showed comparable predictive performance to the radiomics model (Az values, 0.887 vs. 0.884, p = 0.398; 0.917 vs. 0.924, p = 0.271, respectively). The clinical application value of the nomogram developed based on the Rad-score, maximum diameter, and lesion shape was confirmed, and DCA demonstrated that application of the Rad-score would be beneficial for radiologists predicting invasive lesions.

Conclusions

Radiomics has the potential as an independent diagnostic tool to predict the invasiveness of PSNs with solid components <6 mm.

Association between long non‑coding RNA HOTAIR polymorphism and lung cancer risk: A systematic review and meta‑analysis

Single nucleotide polymorphism (SNP) of long noncoding RNA (lnc)RNA has been reported to be an important factor in cancer development. Recently, lncRNA homeobox transcript antisense intergenic RNA (HOTAIR) was indicated to induce tumorigenesis of several cancer types, but the association between the SNP of lncRNA HOTAIR and lung cancer susceptibility has remained undetermined. The present meta-analysis aimed to investigate the effect of HOTAIR polymorphism on susceptibility to lung cancer. The PubMed, Ovid Medline, Embase and Cochrane Library databases were thoroughly searched. Studies containing data on the incidence of lung cancer in patients with different HOTAIR SNPs were included. The Hardy-Weinberg equilibrium was analyzed to determine genotype distribution and allele frequencies. The odds ratio (OR) was pooled to evaluate the association of different SNPs with the susceptibility to lung cancer. A total of six studies comprising 1,715 patients with lung cancer and 2,745 healthy controls were finally included. A total of 4 SNPs (rs12826786, rs1899663, rs920778 and rs4759314) were reported. Analyses for all of these SNPs individually indicated that the lncRNA HOTAIR rs1899663 C>A polymorphism was a risk factor for lung cancer (dominant mode, AA+CA vs. CC: OR=0.816, 95% CI=0.707-0.942, P=0.005). The present study was the first meta-analysis investigating the association between lncRNA HOTAIR and lung cancer susceptibility. The results indicated that the lncRNA HOTAIR rs1899663 C>A polymorphism is a risk factor for lung cancer. LncRNA HOTAIR may be of value in lung cancer screening, particularly for populations with high-risk factors, as well as prognosis prediction. Future investigations are required to further clarify the intrinsic mechanism of the role of HOTAIR in the oncogenesis of lung cancer.

A Multi-Omics Study of Familial Lung Cancer: Microbiome and Host Gene Expression Patterns

Background

Inherited susceptibility and environmental carcinogens are crucial players in lung cancer etiology. The lung microbiome is getting rising attention in carcinogenesis. The present work sought to investigate the microbiome in lung cancer patients affected by familial lung cancer (FLC) and indoor air pollution (IAP); and further, to compare host gene expression patterns with their microbiome for potential links.

Methods

Tissue sample pairs (cancer and adjacent nonmalignant tissue) were used for 16S rRNA (microbiome) and RNA-seq (host gene expression). Subgroup microbiome diversities and their matched gene expression patterns were analyzed. Significantly enriched taxa were screened out, based on different clinicopathologic characteristics.

Results

Our FLC microbiome seemed to be smaller, low-diversity, and inactive to change; we noted microbiome differences in gender, age, blood type, anatomy site, histology type, TNM stage as well as IAP and smoking conditions. We also found smoking and IAP dramatically decreased specific-OTU biodiversity, especially in normal lung tissue. Intriguingly, enriched microbes were in three categories: opportunistic pathogens, probiotics, and pollutant-detoxication microbes; this third category involved Sphingomonas, Sphingopyxis, etc. which help degrade pollutants, but may also cause epithelial damage and chronic inflammation. RNA-seq highlighted IL17, Ras, MAPK, and Notch pathways, which are associated with carcinogenesis and compromised immune system.

Conclusions

The lung microbiome can play vital roles in carcinogenesis. FLC and IAP subjects were affected by fragile lung epithelium, vulnerable host-microbes equilibrium, and dysregulated immune surveillance and response. Our findings provided useful information to study the triple interplay among environmental carcinogens, population genetic background, and diversified lung microbiome.

Radiomics in Early Lung Cancer Diagnosis: From Diagnosis to Clinical Decision Support and Education

Lung cancer is the most frequent cause of cancer-related death around the world. With the recent introduction of low-dose lung computed tomography for lung cancer screening, there has been an increasing number of smoking- and non-smoking-related lung cancer cases worldwide that are manifesting with subsolid nodules, especially in Asian populations. However, the pros and cons of lung cancer screening also follow the implementation of lung cancer screening programs. Here, we review the literature related to radiomics for early lung cancer diagnosis. There are four main radiomics applications: the classification of lung nodules as being malignant/benign; determining the degree of invasiveness of the lung adenocarcinoma; histopathologic subtyping; and prognostication in lung cancer prediction models. In conclusion, radiomics offers great potential to improve diagnosis and personalized risk stratification in early lung cancer diagnosis through patient–doctor cooperation and shared decision making.

Molecular typing of lung adenocarcinoma with computed tomography and CT image-based radiomics: a narrative review of research progress and prospects

Objective

The purpose of this paper was to perform a narrative review of current research evidence on conventional computed tomography (CT) imaging features and CT image-based radiomic features for predicting gene mutations in lung adenocarcinoma and discuss how to translate the research findings to guide future practice.

Background

Lung cancer, especially lung adenocarcinoma, is the leading cause of cancer-related deaths. With advances in the diagnosis and treatment of lung adenocarcinoma with the emergence of molecular testing, the prediction of oncogenes and even drug resistance gene mutations have become key to individualized and precise clinical treatment in order to prolong survival and improve quality of life. The progress of imageological examination includes the development of CT and radiomics are promising quantitative methods for predicting different gene mutations in lung adenocarcinoma, especially common mutations, such as epidermal growth factor receptor (EGFR) mutation, anaplastic lymphoma kinase (ALK) mutation and Kirsten rat sarcoma viral oncogene (KRAS) mutation.

Methods

The PubMed electronic database was searched along with a set of terms specific to lung adenocarcinoma, radiomics (including texture analysis), CT, computed tomography, EGFR, ALK, KRAS, rearranging transfection (RET) rearrangement and c-ros oncogene 1 (ROS-1), v-raf murine sarcoma viral oncogene homolog B1 (BRAF), and human epidermal growth factor receptor 2 (HER2) mutations et al. This review has been reported in compliance with the Narrative Review checklist guidelines. From each full-text article, information was extracted regarding a set of terms above.

Conclusions

Research on the application of conventional CT features and CT image-based radiomic features for predicting the gene mutation status of lung adenocarcinoma is still in a preliminary stage. Noninvasively determination of mutation status in lung adenocarcinoma before targeted therapy with conventional CT features and CT image-based radiomic features remains both hopes and challenges. Before radiomics could be applied in clinical practice, more work needs to be done.

Effect of four or more antenatal care visits on facility delivery and early postnatal care services utilization in Uganda: a propensity score matched analysis

Introduction

Maternal mortality remains a global public health issue, more predominantly in developing countries, and is associated with poor maternal health services utilization. Antenatal care (ANC) visits are positively associated with facility delivery and postnatal care (PNC) utilization. However, ANC in itself may not lead to such association but due to differences that exist among users (women). The purpose of this study, therefore, is to examine the effect of four or more ANC visits on facility delivery and early PNC and also the effect of facility-based delivery on early PNC using Propensity Score Matched Analysis (PSMA).

Methods

The present study utilized the 2016 Uganda Demographic and Health Survey (UDHS) dataset. Women aged 15 – 49 years who had given birth three years preceding the survey were considered for this study. Propensity score-matched analysis was used to analyze the effect of four or more ANC visits on facility delivery and early PNC and also the effect of facility-based delivery on early PNC.

Results

The results revealed a significant and positive effect of four or more ANC visits on facility delivery [ATT (Average Treatment Effect of the Treated) = 0.118, 95% CI: 0.063 – 0.173] and early PNC [ATT = 0.099, 95% CI: 0.076 – 0.121]. It also found a positive and significant effect of facility-based delivery on early PNC [ATT = 0.518, 95% CI: 0.489 – 0.547].

Conclusion

Policies geared towards the provision of four or more ANC visits are an effective intervention towards improved facility-based delivery and early PNC utilisation in Uganda.

Impact of Smoking Status on Lung Cancer Characteristics and Mortality Rates between Screened and Non-Screened Lung Cancer Cohorts: Real-World Knowledge Translation and Education

This was a retrospective hospital-based cohort study of participants diagnosed with lung cancer in the lung cancer register database, and our goal was to evaluate the impact of smoking and screening status on lung cancer characteristics and clinical outcomes. According to the hospital-based lung cancer register database, a total of 2883 lung cancers were diagnosed in 2883 patients between January 2007 and September 2017, which were divided into four groups according to smoking and screening status. A comparison was performed in terms of clinical characteristics and outcomes of lung cancer between the four groups. For non-smokers, age, gender, screened status, tumor size, targeted therapy, and curative surgery were independent prognostic factors of overall survival for lung cancer subjects. However, screened status and gender were not significant prognostic factors for lung cancer survival in smokers with lung cancer. For the non-smoker group, about 4.9% of lung cancer subjects (N = 81) were detected by screening. However, only 0.97% of lung cancer subjects (N = 12) were detected by screening in smokers. This could be attributed to smokers' negative attitudes and low socioeconomic status preventing LDCT lung cancer screening. In summary, our real-world data suggest that effectively encouraging smokers to be more willing to participate in lung cancer screening programs with screening allowance and educational training in the future is an important issue.

Satisfaction With Patient Engagement and Self-Reported Depression Among Hospitalized Patients: A Propensity-Score Matching Analysis

BACKGROUND

Depression is common among hospitalized patients and poses a significant threat to their quality of life. Patient engagement (PE) in healthcare has been shown to be associated with positive health outcomes. However, the relationship between PE and depression among hospitalized patients, with and without chronic conditions, has not yet been explored. This study aimed to investigate the association between patients' satisfaction with PE and self-reported depression in Chinese public hospitals.

METHOD

A multi-centered, cross-sectional survey was conducted in seven tertiary-level public hospitals in Guangdong province, China. Twelve items from a patient-centered care questionnaire and the Patient Health Questionnaire 2-item version were used were used to assess patients' satisfaction with PE and self-reported depression, respectively. Propensity score matching (PSM) approach was used to reduce selection bias and potential baseline differences between patients with and without chronic conditions. The relationship between satisfaction with PE and depression was assessed, using univariate and multivariate logistic regression analyses, respectively.

RESULTS

A total of 1,974 hospitalized patients participated in the survey. After the PSM procedure, 604 patients were assigned to the chronic condition group, and another 604 patients were successfully matched in the comparison group with no differences in sex, age, educational level, and PE-related characteristics. Univariate logistic regression analysis indicated that high satisfaction with PE-related approaches significantly decreased the probability of developing depressive status. Multivariate logistic regression analysis further indicated that, after adjusting all PE-related approaches, "patient education" and "involvement in discharge planning" could significantly decrease the probability of patients developing depression.

CONCLUSIONS

Our results indicate that encouraging PE and improving patients' satisfaction with PE interventions in clinical practice led to improved mental health outcomes among hospitalized patients in China.

Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model

Background

Patients with consistent lung pure ground-glass nodules (pGGNs) have a high incidence of lung adenocarcinoma that can be classified as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), or invasive adenocarcinoma (IAC). Regular follow-up is recommended for AIS and MIA, while surgical resection should be considered for IAC. This study sought to develop a multi-parameter prediction model to increase the diagnostic accuracy in discriminating between IAC and AIS or MIA.

Methods

The training data set comprised consecutive patients with lung pGGNs who underwent resection from January to December 2017 at the Zhongshan Hospital. Of the 370 resected pGGNs, 344 were pathologically confirmed to be AIS, MIA, or IAC and were included in the study. The 26 benign pGGNs were excluded. We compared differences in the clinical features (e.g., age and gender), the content of serum tumor biomarkers, the computed tomography (CT) parameters (e.g., nodule size and the maximal CT value), and the morphologic characteristics of nodules (e.g., lobulation, spiculation, pleura indentation, vacuole sign, and normal vessel penetration or abnormal vessel) between the pathological subtypes of AIS, MIA, and IAC. An abnormal vessel was defined as “vessel curve” or “vessel enlargement”. Statistical analyses were performed using the chi-square test, analysis of variance (ANOVA), and rank test. The IAC prediction model was constructed via a multivariate logistical regression. Our prediction model for lung pGGNs was further validated in a data set comprising consecutive patients from multiple medical centers in China from July to December 2018. In total, 345 resected pGGNs were pathologically diagnosed as lung adenocarcinoma in the validation data set.

Results

In the training data set, patients with pGGNs ≥10 mm in size had a high incidence (74.5%) of IAC. The maximal CT value of IAC [–416.1±121.2 Hounsfield unit (HU)] was much higher than that of MIA (–507.7±138.0 HU) and AIS (–602.6±93.3 HU) (P<0.001). IAC was more common in pGGNs that displayed any of the following CT manifestations: lobulation, spiculation, pleura indentation, vacuole sign, and vessel abnormality. The IAC prediction model was constructed using the parameters that were assessed as risk factors (i.e., the nodule size, maximal CT value, and CT signs). The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) of this model for diagnosing IAC was 0.910, which was higher than that of the AUC for nodule size alone (0.891) or the AUC for the maximal CT value alone (0.807) (P<0.05, respectively). A multicenter validation data set was used to validate the performance of our prediction model in diagnosing IAC, and our model was found to have an AUC of 0.883, which was higher than that of the AUC of 0.827 for the module size alone model or the AUC of 0.791 for the maximal CT value alone model (P<0.05, respectively).

Conclusions

Our multi-parameter prediction model was more accurate at diagnosing IAC than models that used only nodule size or the maximal CT value alone. Thus, it is an efficient tool for identifying the IAC of malignant pGGNs and deciding if surgery is needed.

Clinical Characteristics and Molecular Profiles of Lung Cancer in Ethiopia

Introduction

Lung cancer is the most common cause of cancer deaths worldwide, accounting for 1.8 million deaths each year. Only 20% of lung cancer cases are reported to occur in low- and middle-income countries. An estimated 1.5% of all Ethiopian cancers involved the lung; however, no nationwide cancer registry exists in Ethiopia. Thus, accurate data on clinical history, histopathology, molecular characteristics, and risk factors for lung cancer are not available. The aim of this study was to describe the clinical, radiologic, and pathologic characteristics, including available molecular profiles, for lung cancer at Tikur Anbessa Specialized Hospital (TASH), the main tertiary referral center in Addis Ababa, Ethiopia.

Methods

A cross-sectional study was conducted at TASH among 146 patients with pathologically confirmed primary lung cancer, diagnosed from 2015 to 2019 and recorded in the Addis Ababa Cancer Registry at TASH. Clinical data were extracted from patient medical records, entered into a Research Electronic Data Capture database, and analyzed using Statistical Package for the Social Sciences statistical software. Variables collected included sociodemographics, personal exposures, comorbidities, clinical manifestations at presentation, chest imaging results, diagnostic procedures performed, histopathological classification, cancer staging, and type of treatment (if any). A subset of lung biopsies fixed in formalin for 2 to 7 days, which could be retrieved from the files of the Pathology Department of TASH, were reviewed, and molecular analysis was performed using next-generation sequencing to identify the tumor-oncogenic drivers.

Results

Among the 146 patients studied, the mean (SD) age was 54 plus or minus 13 years; 61.6% (n = 90) were male and 25.3% (n = 37) had a history of tobacco use. The most common clinical manifestations included cough (88.4%, n = 129), chest pain (60.3%, n = 88), and dyspnea (53.4%, n = 78). The median duration of any symptoms was 6 months (interquartile range: 3-12 mo). The most common radiologic features were lung mass (84.9%, n = 129) and pleural effusion (52.7%, n = 77). Adenocarcinoma accounted for 35.7% of lung cancers (n = 52) and squamous cell carcinoma 19.2% (n = 28) from those specimens was reported. Among patients on whom staging of lung cancer was documented, 92.2% (n = 95) of the subjects presented at advanced stages (stages III and IV). EGFR mutation, exons 19 and 20, was found in 7 of 14 tissue blocks analyzed. No specific risk factors were identified, possibly reflecting the relatively small sample size and limited exposures.

Conclusions

There are marked differences in the presentation, risk factors, and molecular characteristics of lung cancer in Ethiopia as compared with other African and non-African countries. Adenocarcinoma was the most common histologic type of lung cancer detected in our study, similar to findings from other international studies. Nevertheless, compared with high-income countries, lung cancer in Ethiopia presents at a younger age, a later stage, and without considerable personal tobacco use. The relatively higher prevalence of EGFR mutation, from the limited molecular analyses, suggests that factors other than smoking history, such as exposure to biomass fuel, may be a more important risk factor. Country-specific screening guidelines and treatment protocols, in addition to a national tumor registry and greater molecular mutation analyses, are needed to improve prevention and management of lung cancer in Ethiopia.

Impact of low-dose computed tomography for lung cancer screening on lung cancer surgical volume: The urgent need in health workforce education and training

This study aimed to investigate the time trend variation in the surgical volume and prognostic outcome of patients with lung cancer after the gradual prolonged implementation of a low-dose computed tomography (LDCT) lung cancer screening program.Using the hospital-based cancer registry data on number of patients with lung cancer and deaths from 2008 to 2017, we conducted a retrospective study using a hospital-based cohort to investigate the relationship between changes in lung cancer surgical volume, the proportion of lung-sparing surgery, and prolonged prognostic outcomes after the gradual implementation of the LDCT lung cancer screening program in recent years.From 2008 to 2017, 3251 patients were diagnosed with lung cancer according to the hospital-based cancer registry. The 5-year mortality rate decreased gradually from 83.54% to 69.44% between 2008 and 2017. The volume of total lung cancer surgical procedures and proportion of lung-sparing surgery performed gradually increased significantly from 2008 to 2017, especially from 2014 to 2017 after implementation of a large volume of LDCT lung cancer screening examinations. In conclusion, our real-world data suggest that there will be an increase in cases of operable early-stage lung cancers, which in turn will increase the surgical volume and proportion of lung-sparing surgery, after the gradual implementation of the LDCT lung cancer screening program in recent years. These findings suggest the importance of a successful national policy regarding LDCT screening programs, regulation of shortage of thoracic surgeons, thoracic radiologist workforce training positions, and education programs.

The role of gender in non-small cell lung cancer: a narrative review

The role of gender in the development, treatment and prognosis of thoracic malignancies has been underappreciated and understudied. While most research has been grounded in tobacco-related malignancies, the incidence of non-smoking related lung cancer is on the rise and disproportionately affecting women. Recent research studies have unveiled critical differences between men and women with regard to risk factors, timeliness of diagnosis, incongruent screening practices, molecular and genetic mechanisms, as well as response to treatment and survival. These studies also highlight the increasingly recognized need for targeted therapies that account for variations in the response and complications as a function of gender. Similarly, screening recommendations continue to evolve as the role of gender is starting to be ellucidated. As women have been underrepresented in clinical trials until recently, the data regarding optimal care and outcomes is still lagging behind. Understanding the underlying similarities and differences between men and women is paramount to providing adequate care and prognostication to patients of either gender. This review provides an overview of the critical role that gender plays in the care of patients with non-small cell lung cancer and other thoracic malignancies, with an emphasis on the need for increased awareness and further research to continue elucidating these disparities.

A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules

This study aims to predict the histological invasiveness of pulmonary adenocarcinoma spectrum manifesting with subsolid nodules ≦ 3 cm using the preoperative CT-based radiomic approach. A total of 186 patients with 203 SSNs confirmed with surgically pathologic proof were retrospectively reviewed from February 2016 to March 2020 for training cohort modeling. The validation cohort included 50 subjects with 57 SSNs confirmed with surgically pathologic proof from April 2020 to August 2020. CT-based radiomic features were extracted using an open-source software with 3D nodular volume segmentation manually. The association between CT-based conventional features/selected radiomic features and histological invasiveness of pulmonary adenocarcinoma status were analyzed. Diagnostic models were built using conventional CT features, selected radiomic CT features and experienced radiologists. In addition, we compared diagnostic performance between radiomic CT feature, conventional CT features and experienced radiologists. In the training cohort of 203 SSNs, there were 106 invasive lesions and 97 pre-invasive lesions. Logistic analysis identified that a selected radiomic feature named GLCM_Entropy_log10 was the predictor for histological invasiveness of pulmonary adenocarcinoma spectrum (OR: 38.081, 95% CI 2.735–530.309, p = 0.007). The sensitivity and specificity for predicting histological invasiveness of pulmonary adenocarcinoma spectrum using the cutoff value of CT-based radiomic parameter (GLCM_Entropy_log10) were 84.8% and 79.2% respectively (area under curve, 0.878). The diagnostic model of CT-based radiomic feature was compared to those of conventional CT feature (morphologic and quantitative) and three experienced radiologists. The diagnostic performance of radiomic feature was similar to those of the quantitative CT feature (nodular size and solid component, both lung and mediastinal window) in prediction invasive pulmonary adenocarcinoma (IPA). The AUC value of CT radiomic feature was higher than those of conventional CT morphologic feature and three experienced radiologists. The c-statistic of the training cohort model was 0.878 (95% CI 0.831–0.925) and 0.923 (0.854–0.991) in the validation cohort. Calibration was good in both cohorts. The diagnostic performance of CT-based radiomic feature is not inferior to solid component (lung and mediastinal window) and nodular size for predicting invasiveness. CT-based radiomic feature and nomogram could help to differentiate IPA lesions from preinvasive lesions in the both independent training and validation cohorts. The nomogram may help clinicians with decision making in the management of subsolid nodules.

Clinical Value of 18F-FDG PET/CT in Prediction of Visceral Pleural Invasion of Subsolid Nodule Stage I Lung Adenocarcinoma

RATIONALE AND OBJECTIVES

This study investigated the utility of ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for predicting visceral pleural invasion (VPI) of subsolid nodule (SSN) stage I lung adenocarcinoma.

MATERIALS AND METHODS

A retrospective analysis of ¹⁸F-FDG PET/CT data from 65 postsurgical cases with surgical pathology-confirmed SSN lung adenocarcinoma identified significant VPI predictors using multivariate logistic regression.

RESULTS

Nodule and solid component sizes, solid component-to-tumor ratios, pleural indentations, distances between nodules and pleura, and maximum standardized uptake values (SUVmax) differed significantly between VPI-positive (n = 30) and VPI-negative (n = 35) cases on univariate analysis. The distance between the nodule and pleura and SUVmax were significant independent VPI predictors on multivariate analysis. Areas under the curve of the distance between the nodule and pleura and SUVmax on receiver operating characteristic curves were 0.76 and 0.79, respectively; both factors were 0.90. The area under the curve of combined predictors was significantly superior to the distance between the nodule and pleura only but not SUVmax alone. The threshold of the distance between the nodule and pleura, to predict VPI was 4.50 mm, with 96.67% sensitivity, and 57.14% specificity. The threshold of SUVmax to predict VPI was 1.05, with 100% sensitivity and 60% specificity. The sensitivity and specificity of model 2 using the independent predictive factors were 96.67%, and 71.43%, respectively.

CONCLUSION

Distance between the nodule and pleura and SUVmax are independent predictors of VPI in SSN stage I lung adenocarcinoma. Further, combining these factors improves their predictive ability.

Two types of lung cancer with situs inversus totalis: a case report and review of the literature

Situs inversus totalis (SIT) is a rare congenital anatomical variation. However, patients with SIT combined with cancer are rare and these patients with two types of lung cancer have not been reported. We report here a case of combined lung adenocarcinoma and solitary fibrous tumor of the pleura with SIT and discuss its clinicopathological features and outcomes. A 68-year-old asymptomatic woman was referred to the Affiliated Hospital of Qingdao University because of an abnormal shadow on chest radiography. Computed tomography showed SIT and an irregularly shaped nodule (measuring 38 × 27 mm in diameter) in the pleural area of the left lower lobe and a 5-mm nodule in the dorsal segment of the lower lobe of the left lung. Surgery was then performed. For such patients, we should eliminate anxiety in patients, perform regular reexaminations, focus on the individual features of these patients, and avoid misdiagnosis because of habitual thinking. At the same time, the lymph nodes should be completely removed and different parts of the tumor with different properties should be treated differently according to the situation.

Association of cancer screening and residing in a coal-polluted East Asian region with overall survival of lung cancer patients: a retrospective cohort study

Lung cancer is the leading cause of cancer death worldwide. The Xuanwei-Fuyuan (XF) region of Yunnan, China has a high incidence of lung cancer from coal-related pollution. Effort to raise public awareness screening for lung cancer has been ongoing. We retrospectively analyzed overall survival (OS) of lung cancer patients of a tertiary cancer center in Yunnan to investigate screening and regional residential status as predictive factors. Consecutive cases of newly diagnosed lung cancer were reviewed. The lung cancer cases diagnosed by screening were more likely to be early-staged and treated by surgery than those diagnosed not by screening. In patients diagnosed not by screening, XF residential status was a significant predictor of improved OS. Frailty model detected significant heterogeneity associated with region of residence in unscreened patients. Potential biases associated with screening were examined by Monte Carlo simulations and sensitivity analyses. Focused effort in cancer screening and increased public awareness of pollution-related lung cancer in XF might have led to early diagnosis and improved OS, and increased investment in health care resources in high risk areas may have produced additional unobserved factors that underlay the association of XF residential status with improved OS in patients diagnosed not by screening.

GABAergic but not Antidepressant Medications Increase Risk for Clostridioides difficile Infection in a National Cohort of Veterans

Background

Clostridioides difficile infection (CDI) is primarily mediated by alterations in the host gut ecosystem. While antibiotic use is the primary risk factor for CDI, other medications that modulate the gut ecosystem, particularly those targeting the gut-brain axis, could impact CDI risk. This study aimed to investigate the association between recent antidepressant and gamma-aminobutyric acid (GABA)-ergic medication use with CDI risk in a national cohort of United States veterans.

Methods

This was a retrospective case-control study of patients seen in Veterans Health Administration facilities from October 2002 to September 2014. CDI and non-CDI control patients were propensity score matched 1:1 using a maximum caliper of 0.0001. Antidepressant and GABAergic medication use 90 days before cohort inclusion were analyzed for CDI association using bivariable and multivariable logistic regression models.

Results

A total of 85 831 patients were included, and 9287 CDI and 9287 control patients were propensity score matched. Antidepressant use overall was not significantly associated with CDI risk (odds ratio [OR], 1.05; 95% CI, 0.98-1.12), although GABAergic medication use was associated with increased risk (OR, 1.81; 95% CI, 1.70-1.92). In multivariable models of individual medications/classes, benzodiazepines had the strongest CDI association (OR, 1.91; 95% CI, 1.77-2.07). SSRIs (OR, 0.88; 95% CI, 0.81-0.95) and bupropion (OR, 0.67; 95% CI, 0.57-0.78) were negatively associated with CDI.

Conclusions

In this national study of veterans, GABAergic medication use was a positive predictor of CDI risk, though antidepressant use was not. Further research is needed to understand biological mechanisms, and confirmatory studies are needed to validate these findings.

Prognostic effect of implementation of the mass low-dose computed tomography lung cancer screening program: a hospital-based cohort study

Low-dose computed tomography lung cancer screening aims to detect early-stage lung cancers in order to decrease the incidence of advanced-stage lung cancers and to reduce lung cancer mortality. We analyzed the time trends of lung cancer stage distribution and mortality rates after the gradual implementation of the low-dose computed tomography lung cancer screening in a hospital-based cohort. Using the hospital-based cancer registry data on lung cancer number and death from 2007 to 2014, we aim to evaluate the trends in stage distribution and mortality rate after the gradual implementation of low-dose computed tomography lung cancer screening program over recent years. From 2007 to 2014, overall 2542 cases of lung cancers were diagnosed according to hospital-based cancer registry. For the 1-year mortality rate, the mortality rate decreased gradually from 48.16 to 37.04% between 2007 and 2014. For the 5-year mortality rate, the mortality rate decreased gradually from 88.49 to 69.44% between 2007 and 2014. There was a gradual decrease in stage IV lung cancer with the corresponding sharp increase in stage I early lung cancer after following the implementation of the large volume of the low-dose computed tomography examination between the years 2011 and 2014. In conclusion, these results suggest that the gradual implementation of low-dose computed tomography lung screening program could lead to a remarkable decrease in lung cancer mortality and a remarkable stage shift in the trend over time in this hospital-based cohort.

Cancer Incidence Characteristic Evolution Based on the National Cancer Registry in Taiwan

Introduction

Taiwan has committed itself to cancer prevention. This study investigates the impact of cancer prevention on cancer incidence in Taiwan.

Objective

This study describes the secular trends and present status of cancer incidence in Taiwan during the years of 1988 to 2016.

Methods

Age-standardized incidence rates (ASRs), age-specific incidence, and sex ratios for all cancers were calculated using data from the Taiwan Cancer Registry System for the years 1988 to 2016. Results and Conclusions. ASRs of cancer for males increased from 150.93 per 10⁵ individuals in 1988 to 330.03 per 10⁵ individuals in 2016, and, for females, they increased from 124.18 per 10⁵ individuals in 1988 to 269.5 per 10⁵ individuals in 2016. We found that cancer incidence has begun at younger ages and that the rates of cancer incidence are increasing faster. This study shows that the incidence of cancer in males has decreased slightly in recent years, while the incidence of cancer in females has continued to increase. The continuous promotion of health literacy, lifestyle modification, HBV and HPV vaccination, and cancer early screening can improve the effectiveness of cancer prevention.

Causation between Pathway Completion and Reduced Hospital Stay in Patients with Lung Cancer: a Retrospective Cohort Study Using Propensity Score Matching

We have previously demonstrated that clinical pathway completion helps reduce hospital stays. However, our previous results showed only a correlation, not causation. Therefore, the current study’s aim was to analyze the causation between clinical pathway completion and reduced hospital stays for patients with lung cancer. Data were collected from April 2013 to March 2018 from the electronic medical records of the University of Miyazaki Hospital. We used propensity score matching to extract records from 227 patients. Patients were further divided into a pathway completed group and a pathway not completed group; 74 patients in each group were available for data analysis. Our main analysis involved estimating the discharge curve, which was comprised of the in-hospital rate and hospital stay. Additional analyzes were performed to compare the frequency of medical treatments registered in the clinical pathway but not implemented (termed deviated medical treatments). The occurrence of these treatments meant that the clinical pathway was not completed. The main results indicated a decrease in the in-hospital rate of the completion group, compared with the not completed group. The p value of the log-rank test was <0.001 for total patients and patients who underwent resection, and 0.017 for patients who did not undergo resection. Additional results indicated that a number of intravenous drips were not implemented, despite their registration on clinical pathways. Our results indicate that clinical pathway completion contributes to improved efficiency and safety. This simplified procedure is expected to be applicable to other diseases and clinical indicators.

Value of TSCT Features for Differentiating Preinvasive and Minimally Invasive Adenocarcinoma From Invasive Adenocarcinoma Presenting as Subsolid Nodules Smaller Than 3 cm

BACKGROUND

To distinguish preinvasive (adenocarcinoma in situ/atypical adenomatous hyperplasia) and minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IA) appearing as solitary subsolid nodules (SSNs) less than 3 cm based on thin-section computed tomography (TSCT) features to guide therapeutic approaches.

METHODS

A total of 154 lesions that were histopathologically confirmed to have pre/minimally invasive adenocarcinoma (hereafter pre/MIA) and IA presenting as part-solid nodules (PSNs) or pure ground-glass nodules (pGGNs) were retrospectively reviewed. The TSCT features, including diameter, area, CT value, shape, air bronchogram, margins, and location, were compared and assessed. Receiver operating characteristic analyses were conducted to determine the cut-off values for the qualitative variables and their diagnostic performances.

RESULTS

Of 154 nodules, 89 IA, 53 MIA, eight adenocarcinoma in situ, and four atypical adenomatous hyperplasia lesions were found. Univariate and multivariate logistic regression of the pre/MIA and IA lesions were compared and analyzed among PSNs and pGGNs. Among pGGNs, a significant difference was found in the area (p = 0.004, odds ratio [OR] = 0.124, 95% confidence interval [CI] = 0.300-0.515) between the pre/MIA and IA groups. In PSNs, significant differences were found in the diameter (p = 0.001, OR = 0.171, 95% CI = 0.063-0.467) and CT value (p = 0.001, OR = 0.996, 95% CI = 0.993-0.998) between the pre/MIA and IA groups. According to the corresponding receiver operating characteristic curves, the optimal cut-off tumor area in pGGNs to differentiate pre/MIA from IA was 0.595 cm². A higher CT value of the lesion (≥ -298.500 HU) and a larger diameter (≥1.450 cm) in PSNs were significantly associated with IA.

CONCLUSION

Imaging features from TSCT contribute to distinguishing pre/MIA from IA in solitary subsolid nodules and may contribute to guide the clinical management of these lesions.

Differences in lung cancer characteristics and mortality rate between screened and non-screened cohorts

Screening programs for lung cancer aim to allow diagnosis at the early stage, and therefore the decline in mortality rates. Thus, the aim of this retrospective cohort study was to the comparison of screened and non-screened lung cancer in terms of lung cancer characteristics, overdiagnosis and survival rate. A retrospective study in which 2883 patients with 2883 lung cancer diagnosed according to the hospital-based lung cancer register database between 2007 and 2017. A comparison was performed in term of clinical characteristics and outcomes of lung cancer between the screened and non-screening patient groups. 2883 subjects were identified (93 screened and 2790 non-screened). Screened group patients were younger (59.91 ± 8.14 versus 67.58 ± 12.95; p < 0.0001), and were more likely to be female than non-screened group (61.3% versus 36.8%; p < 0.0001). The screened group showed significantly better outcomes in overall mortality than the non-screened group (10.75% versus 79.06%; <0.0001). In a Cox proportional hazard model, lung cancer in the screened group proved to be an independent prognostic factor in lung cancer subjects. Our findings point to the improved survival outcome in the screened group and might underline the benefit of low-dose computed tomography (LDCT) screening program in Asian populations with the high prevalence of non-smoking-related lung cancer. Further study aimed at the LDCT mass screening program targeting at light smokers and non-smoker outside of existing screening criteria is warranted.

Qualitative and quantitative imaging features of pulmonary subsolid nodules: differentiating invasive adenocarcinoma from minimally invasive adenocarcinoma and preinvasive lesions

Background

To explore the role of qualitative and quantitative imaging features of pulmonary subsolid nodules (SSNs) in differentiating invasive adenocarcinoma (IAC) from minimally invasive adenocarcinoma (MIA) and preinvasive lesions.

Methods

We reviewed the clinical records of our institute from October 2010 to December 2015 and included 316 resected SSNs from 287 patients: 260 pure ground-glass nodules, 47 part-solid nodules with solid components ≤5 mm, and 9 ground-glass nodules (GGNs) with cystic airspaces. According to the pathologic review results, 307 SSNs in addition to nine GGNs with cystic airspaces were divided into two groups: A, including atypical adenomatous hyperplasia (AAH) (n=15), adenocarcinoma in situ (AIS) (n=56), and MIA (n=41); B, including 195 IACs. Univariate and binary logistic regression analyses were conducted to identify independent risk factors for IAC.

Results

Univariate analysis showed significant differences between groups regarding patient age, mean diameter, mean and relative computed tomography (CT) values, volume, mass (all P<0.001), and morphological features including lobulated sign (P<0.001), spiculated sign (P=0.028), vacuole sign/air bronchogram (P<0.001), and pleural retraction (P=0.017). Binary logistic regression and receiver operating characteristic analysis indicated the SSN mass as the only independent risk factor of IAC (odds ratio, 1.007; P<0.001), with an optimal cutoff value of 283.2 mg [area under curve (AUC): 0.859; sensitivity: 68.7%; specificity: 92.9%]. Among lepidic, acinar, and papillary adenocarcinomas, we found significant differences for the vacuole sign/air bronchogram (P=0.032) and mean and relative CT values (P<0.001). All nine GGNs with cystic airspaces were IACs.

Conclusions

The SSN mass with an optimal cutoff value of 283.2 mg may be reliable for differentiating IAC from MIA and preinvasive lesions.

MUC16 in non-small cell lung cancer patients affected by familial lung cancer and indoor air pollution: clinical characteristics and cell behaviors

Background

Inherited susceptibility and environmental carcinogens are crucial players in lung cancer etiology, and both exhibit population heterogeneity. MUC16 is overexpressed in various cancers and often associated with poor prognosis. Present work was to investigate the clinical significance of MUC16 in non-small cell lung cancer patients affected by familial lung cancer (FLC) and indoor air pollution caused by coal use.

Methods

Clinicopathologic characteristics and MUC16 expression were analyzed and evaluated in our subject population. Vectors were constructed for MUC16 gene knockout and overexpression, then we examined how MUC16 affected lung cancer cell behaviors, including proliferation, migration, invasion and chemoresistance.

Results

FLC showed significant association with early-onset (P<0.01) and later stage (P<0.01). Indoor air pollution was associated with younger age (P<0.01), later stage (P<0.05) and AD histology type (P<0.05). Interestingly, two age peaks were observed in our FLC and sporadic group respectively, possibly suggesting multiple major contributors to lung cancer in our subject population. MUC16 overexpression was significantly associated with FLC (P<0.05), indoor air pollution (P<0.01) and later stage (P<0.01), additionally more metastasis cases were observed in patients with up-regulated MUC16 (18.1% vs. 10.3%). Taken together, elevated MUC16 may potentially be one molecular character of FLC in local residents. Intriguingly, patients with more MUC16 up-regulation seemed to have a lower number of white blood cells, especially neutrophils, this reflected MUC16's role in immune regulation. In cell behavior experiments, high MUC16 level could contribute to lung cancer cell proliferation, migration, invasion and chemoresistance, but there were variations among cell lines.

Conclusions

MUC16 plays crucial roles in lung cancer pathogenesis, progression and chemoresistance. Interestingly, its association with FLC and indoor air pollution highlights the complexity of lung cancer etiology. Our findings provide useful information to study the intricate interaction between environmental carcinogens and population genetic background.

Comparison of clinical characteristics and overall survival between spirometrically diagnosed chronic obstructive pulmonary disease (COPD) and non-COPD never-smoking stage I-IV non-small cell lung cancer patients

Objectives: A significant proportion of non-small cell lung cancer (NSCLC) patients are never-smokers. However, the clinical impact of spirometrically diagnosed chronic obstructive pulmonary disease (COPD) on the prognosis of never-smoking NSCLC has not been evaluated in the context of treatment modalities and other cancer-related factors. In the present study, we evaluated the clinical impact of COPD in non-smoking NSCLC patients, and correlations between COPD and other previously unevaluated clinical variables.

Materials and methods: Lung cancer patients (stages I to IV) diagnosed with NSCLC between January 2008 and December 2015 at six university hospitals were enrolled in the study cohort and retrospectively evaluated. Clinical parameters were compared between spirometrically diagnosed COPD and non-COPD groups. Correlations between COPD status and other variables were evaluated. In order to reduce the effect of potential confounders and selection bias, we performed adjustment for differences in baseline parameters by using propensity score matching (PSM). After PSM, clinical variables were evaluated for their effects on overall survival (OS).

Results: Of the 345 patients enrolled in the study, 277 were categorized as non-COPD and 68 as COPD. Old age, male gender, and wild-type EGFR were significantly correlated with COPD. By univariate analysis of 218 patients in a propensity score matched cohort, not receiving active anticancer treatment, advanced stage, and COPD were significantly associated with shorter OS. Multivariate analysis showed that not receiving active anticancer treatment, advanced cancer stage, and COPD (P=0.044, HR: 1.526, 95% CI: 1.012–2.300) were significant predictors of shorter OS.

Conclusion: In the present study, never-smoker NSCLC patients with COPD had shorter OS times, compared to non-COPD never-smoker NSCLC patients.

Oxidative stress in lung cancer patients is associated with altered serum markers of lipid metabolism

In lung cancer (LC), alterations in redox balance are extensively observed and are a consequence of disease as well as co-occurrent with smoking. We previously demonstrated that metabolic disturbances such as trace element status and carbohydrate metabolism alterations are linked with redox status. The aim of this study was to evaluate relationships between the serum parameters of lipid metabolism and redox balance in LC patients. Serum parameters of lipid metabolism, i.e. total cholesterol (T-C), HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), triglycerides (TG), T-C:HDL-C ratio, non-HDL-C, apolipoprotein A1 (Apo-A1), apolipoprotein B (Apo-B) and Apo-B:Apo-A1 ratio, as well as systemic redox status, i.e. total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), vitamin E (VE), vitamin C (VC), malonyldialdehyde (MDA), conjugated dienes (CD), and 4-hydroxynonenal (4-HNE) were determined in 92 LC patients and 82 control subjects (CS). LC women had significantly lower T-C and LDL-C, and higher TG, while HDL-C, Apo-A1 and Apo-B were significantly decreased in LC patients regardless of sex, when compared to CS. LC men had alterations in the systemic total redox balance such as lower TAS and higher OSI than CS men. LC women had lower VC, but VE was decreased in LC patients, regardless of sex. We observed higher lipid peroxidation in LC patients expressed via higher 4-HNE and CD. Systemic redox disturbances were associated with serum lipid alterations: TOS and OSI were positively correlated with T-C:HDL-C ratio and Apo-B:Apo-A1 ratio and negatively with HDL-C. The parameters of lipid peroxidation CD and MDA were significantly associated with variables reflecting lipid disturbances. The observed correlations were strengthened by general overweight/obesity, abdominal obesity, hypertriglyceridemia and non-smoking status. In conclusion, parameters related to lipid alterations are associated with oxidative stress in LC patients. The largest contribution from lipid parameters was revealed for T-C:HDL-C ratio, HDL-C and Apo-B:Apo-A1 ratio, while the largest contribution from redox status was revealed for OSI and VE. Overweight, obesity, hypertriglyceridemia and non-smoking status intensified these relationships.

Association between Family History of Cancer and Lung Cancer Risk among Japanese Men and Women

Although cigarette smoking is a major risk factor for lung cancer, genetic susceptibility may also affect lung cancer risk. To explore the role of genetic risk, this case-control study investigated the association between family history of cancer at several sites and lung cancer risk. A total of 1,733 lung cancer cases and 6,643 controls were selected from patients aged 30 years and over admitted to a single hospital in Japan between 1997 and 2009. Information on family history of cancer was collected using a self-administered questionnaire and odds ratios (ORs) were estimated by unconditional logistic regression. Family history of lung cancer in first-degree relatives was associated with an increased risk of lung cancer among both sexes. According to histology and type of relatives, a parental history of lung cancer was significantly associated with an increased risk of female adenocarcinoma (OR = 1.72). Stratification by smoking status revealed that this significant positive association in women was limited to ever-smokers (OR = 4.13). In men, a history of lung cancer in siblings was significantly associated with an increased risk of small cell carcinoma (OR = 2.28) and adenocarcinoma (OR = 2.25). Otherwise, positive associations between history of breast (OR = 1.99) and total (OR = 1.71) cancers in siblings and the risk of male adenocarcinoma were observed. These results suggest that inherited genetic susceptibility may contribute to the development of lung cancer. In men, shared exposure to environmental factors among siblings may also be responsible for the increase in lung cancer risk.

Lung cancer family history and exposure to occupational/domestic coal combustion contribute to variations in clinicopathologic features and gene fusion patterns in non-small cell lung cancer

BACKGROUND

Both genetic and environmental factors contribute to the development of cancer and its mutant spectrum. Lung cancer has familial aggregation. Lung cancer caused by non-tobacco factors has unique pathological and molecular characteristics. The interaction between genetic lung cancer susceptibility and carcinogens from coal burning remains complex and understudied.

METHODS

We selected 410 non-small cell lung cancer (NSCLC) patients with a family history of lung cancer (FLC) and exposure to coal combustion between 2014 and 2017. Clinicopathologic parameters were analyzed. Reverse transcription-PCR was performed to detect ALK, ROS1, RET, and NTRK1 rearrangement.

RESULTS

Among the 410 NSCLC patients, 192 had FLC and 204 (49.8%) were exposed to occupational or domestic coal combustion. FLC patients had the same characteristics regardless of gender and coal exposure: younger age, high female ratio, adenocarcinoma, increased metastasis, later stage at diagnosis, and higher frequency of gene fusion. Sixty-seven patients (16.3%) had gene rearrangement: 51 (12.4%) harbored EML4-ALK fusions and 16 ROS1 fusions (3.9%). The highest gene fusion rate (35.1%, 33/94) occurred in patients with both FLC and high tobacco and coal exposure. ALK fusions and total gene rearrangement were closely associated with women, never smokers, younger age, FLC, and coal exposure.

CONCLUSION

FLC and exposure to coal combustion have an important impact on the clinicopathological characteristics and gene fusion mode of NSCLC, particularly in cases of higher levels of carcinogens, and genetic susceptibility has a greater impact. Our findings may help evaluate the effect of FLC and coal exposure on the pathogenesis of lung cancer.

Circulating high sensitivity C reactive protein concentrations and risk of lung cancer: nested case-control study within Lung Cancer Cohort Consortium

OBJECTIVES

To conduct a comprehensive analysis of prospectively measured circulating high sensitivity C reactive protein (hsCRP) concentration and risk of lung cancer overall, by smoking status (never, former, and current smokers), and histological sub-type.

DESIGN

Nested case-control study.

SETTING

20 population based cohort studies in Asia, Europe, Australia, and the United States.

PARTICIPANTS

5299 patients with incident lung cancer, with individually incidence density matched controls.

EXPOSURE

Circulating hsCRP concentrations in prediagnostic serum or plasma samples.

MAIN OUTCOME MEASURE

Incident lung cancer diagnosis.

RESULTS

A positive association between circulating hsCRP concentration and the risk of lung cancer for current (odds ratio associated with a doubling in hsCRP concentration 1.09, 95% confidence interval 1.05 to 1.13) and former smokers (1.09, 1.04 to 1.14) was observed, but not for never smokers (P<0.01 for interaction). This association was strong and consistent across all histological subtypes, except for adenocarcinoma, which was not strongly associated with hsCRP concentration regardless of smoking status (odds ratio for adenocarcinoma overall 0.97, 95% confidence interval 0.94 to 1.01). The association between circulating hsCRP concentration and the risk of lung cancer was strongest in the first two years of follow-up for former and current smokers. Including hsCRP concentration in a risk model, in addition to smoking based variables, did not improve risk discrimination overall, but slightly improved discrimination for cancers diagnosed in the first two years of follow-up.

CONCLUSIONS

Former and current smokers with higher circulating hsCRP concentrations had a higher risk of lung cancer overall. Circulating hsCRP concentration was not associated with the risk of lung adenocarcinoma. Circulating hsCRP concentration could be a prediagnostic marker of lung cancer rather than a causal risk factor.

Risk prediction models for lung cancer: Perspectives and dissemination

Objective

The objective was to systematically assess lung cancer risk prediction models by critical evaluation of methodology, transparency and validation in order to provide a direction for future model development.

Methods

Electronic searches (including PubMed, EMbase, the Cochrane Library, Web of Science, the China National Knowledge Infrastructure, Wanfang, the Chinese BioMedical Literature Database, and other official cancer websites) were completed with English and Chinese databases until April 30th, 2018. Main reported sources were input data, assumptions and sensitivity analysis. Model validation was based on statements in the publications regarding internal validation, external validation and/or cross-validation.

Results

Twenty-two studies (containing 11 multiple-use and 11 single-use models) were included. Original models were developed between 2003 and 2016. Most of these were from the United States. Multivariate logistic regression was widely used to identify a model. The minimum area under the curve for each model was 0.57 and the largest was 0.87. The smallest C statistic was 0.59 and the largest 0.85. Six studies were validated by external validation and three were cross-validated. In total, 2 models had a high risk of bias, 6 models reported the most used variables were age and smoking duration, and 5 models included family history of lung cancer.

Conclusions

The prediction accuracy of the models was high overall, indicating that it is feasible to use models for high-risk population prediction. However, the process of model development and reporting is not optimal with a high risk of bias. This risk affects prediction accuracy, influencing the promotion and further development of the model. In view of this, model developers need to be more attentive to bias risk control and validity verification in the development of models.

Characteristics of Familial Lung Cancer in Yunnan-Guizhou Plateau of China

Background: Lung cancer has inherited susceptibility and show familial aggregation, the characteristics of familial lung cancer exhibit population heterogeneity. Despite previous studies, familial lung cancer in China's Yunnan-Guizhou plateau remains understudied. Methods: Between 2015 and 2017, 1,023 lung cancer patients (residents of Yunnan-Guizhou plateau) were enrolled with no limitation on other parameters, 152 subjects had familial lung cancer. Clinicopathologic parameters were analyzed and compared, 4,754 lung cancer patients from NCI-GDC were used to represent a general population. Results: Familial lung cancer (FLC) subjects showed unique characters: early-onset; increased rate of female, adenocarcinoma, stage IV and other cancer history; unbalance in anatomic sites; all ruling out significant difference in smoking status. Unbalanced distribution of co-existing diseases or symptoms was also discovered. FLC patients were more likely to develop benign lesions (polyps, nodules, cysts) early in life, especially early-growth of multiple pulmonary nodules at higher frequency. Typical diseases with family history like diabetes and hypertension were also increased in FLC population. Compared to GDC data, our subject population was younger: the age peak of our FLC group was in 50-59; our sporadic group had an age peak around 60; while GDC patients' age peak was in 60-69. Importantly, the biggest difference happened in age 40-49: our FLC group and sporadic group had 3 times and 2 times higher ratio than GDC population, respectively. Moreover, the age peaks of our FLC males and FLC females were both in 50-59; while our sporadic females had the age peak in 50-59, much earlier than sporadic males (around 60-69); reflecting gender-specific or age-specific characters in our subject population. Conclusions: Familial lung cancer in China's Yunnan-Guizhou plateau showed unique clinicopathologic characters, differences were found in gender, age, histologic type, TNM stage and co-existing diseases or symptoms. Identification of hereditary factors which lead to increased lung cancer risk will be a challenge of both scientific and clinical significance.

Qualitative CT Criterion for Subsolid Nodule Subclassification: Improving Interobserver Agreement and Pathologic Correlation in the Adenocarcinoma Spectrum

RATIONALE AND OBJECTIVES

The main aim of this study was to evaluate the clinical validity and correlation with pathologic invasiveness in the pulmonary adenocarcinoma spectrum based on the novel qualitative computed tomography criterion for subsolid nodule (SSN) classification, which classified SSN into pure ground-glass nodule, heterogeneous ground-glass nodule, and part-solid nodule. In addition, we compared the performance of the conventional and novel classifications.

MATERIALS AND METHODS

The computed tomography images of 41 SSN nodules were interpreted by six observers independently, and the SSN characteristics were classified according to both the conventional and the novel classification systems. Each observer assessed 41 nodules in two different classifications separated by a minimum of 8 weeks. The kappa (κ) coefficient test was used to determine the reliability. The correlation between pulmonary adenocarcinoma spectrum and the SSN classification was analyzed with Spearman correlation coefficients.

RESULTS

Interobserver agreement (κ) was 0.702 (range 0.42-0.89) and 0.707 (range 0.58-0.88) for the conventional and the novel classifications for SSN, respectively, and intraobserver agreement (κ) was 0.92 and 0.88 for the conventional and the novel classifications for SSN, respectively. The novel SSN classification (correlation coefficient range 0.622-0.732) is more strongly correlated with the pathologic invasiveness degree of lesions in adenocarcinoma spectrum than the conventional SSN classification (correlation coefficient range 0.458-0.644).

CONCLUSIONS

The agreement between observers on the novel SSN classification system was good and had better correlation with pathologic invasiveness than the conventional SSN classification. Further studies are needed to confirm these results on interobserver agreement.

Modified Lung-RADS Improves Performance of Screening LDCT in a Population with High Prevalence of Non-smoking-related Lung Cancer

OBJECTIVES

We proposed a modification of the ACR Lung Imaging Reporting and Data System (Lung-RADS) to clarify the characteristics of subsolid nodules with categories 1-11, and to compare the diagnostic accuracy with Lung-RADS and National Lung Screening Trial criteria in an Asian population with high prevalence of adenocarcinoma.

METHODS

We analyzed a retrospective cohort of 1978 consecutive healthy subjects (72.8% nonsmoker) who underwent low-dose computed tomography from August 2013 to October 2014 (1084 men, 894 women). Lung-RADS categories 2 and 3 were modified to include subcategories of 2A/2B/2C and 3A/3B/3C, respectively. Clinical information and nodule characteristics were recorded. Receiver operating characteristic curves were used to compare diagnostic accuracy at different cutoffs.

RESULTS

Thirty-two subjects (30 nonsmokers) had pathology-proven adenocarcinoma spectrum lesions in the follow-up period (1.6 ± 0.5 years). Modified Lung-RADS, using modified Lung-RADS category 2C as cutoff, had an area under the curve (AUC) of 0.973 in predicting adenocarcinoma spectrum lesions (sensitivity of 100%, specificity of 89.3%), which was significantly higher than that of Lung-RADS (AUC = 0.815, P < .001) and National Lung Screening Trial (AUC = 0.906, P < .001). Furthermore, modified Lung-RADS showed an AUC of 0.992 in predicting invasive adenocarcinoma (sensitivity of 95%, specificity of 97.8%) when category 3B was used as cutoff.

CONCLUSIONS

Modified Lung-RADS may substantially improve sensitivity while maintaining specificity for detection of adenocarcinoma spectrum lesions in an Asian population. Compared to Lung-RADS, it has enhanced ability to differentiate invasive from indolent adenocarcinoma by more refined subclassification of subsolid nodules using two cutoff values of category 2C and 3B. The effect of using modified Lung-RADS in clinical practice must be carefully studied in prospective large cohort studies.

Natural History of Persistent Pulmonary Subsolid Nodules: Long-Term Observation of Different Interval Growth

BACKGROUND

The long-term natural course and outcomes of subsolid nodules (SSNs) in terms of true growth, substantial growth, and stage shift need to be clarified.

METHODS

Between 2002 and 2016, 128 subjects with persistent SSNs of 3cm or smaller were enrolled. The baseline and interval changes in the series computed tomography (CT) findings during the follow-up period were subsequently reviewed.

RESULTS

The mean follow-up period was 3.57±2.93years. The cumulative percentage of growth nodules of the part-solid nodule (PSN) group was significantly higher than that of the ground-glass nodule (GGN) group by Kaplan-Meier estimation (all p<0.0001). For true SSN growth, GGNs usually take a median follow-up of 7 years to grow; PSNs usually take a median follow-up of 3 years to grow. For substantial SSN growth, GGNs usually take a median follow-up of 9 years to grow; PSNs usually take a median follow-up of 3 years to grow. For stage shift, GGNs usually take a median follow-up of 12 years to grow; PSNs usually take a median follow-up of 9 years to grow.

CONCLUSIONS

The natural course in terms of true growth, substantial growth, and stage shift differed significantly according to their nodule type, which could contribute to the development of follow-up guidelines and management strategy of pulmonary SSNs.

Semiquantative Visual Assessment of Sub-solid Pulmonary Nodules ≦3 cm in Differentiation of Lung Adenocarcinoma Spectrum

We aimed to analyze CT features of persistent subsolid nodules (SSN) ≦3 cm diagnosed pathologically as adenocarcinoma spectrum to investigate whether parameters enable distinction between invasive pulmonary adenocarcinomas (IPAs) and pre-invasive lesions. A total of 129 patients with 141 SSNs confirmed with surgically pathologic proof were retrospectively reviewed. Of 141 SSNs, there were 57 pure ground-glass nodules (GGNs), 22 heterogeneous GGNs, and 62 part-solid nodules. SSN subclassification showed a significant linear trend with invasive degree of the adenocarcinoma spectrum (pure GGNs 7%; heterogeneous GGNs 36.4%; part-solid nodules 85.5%, P for trend <0.0001). For IPA detection in 141 SSNs, a solid part of ≧3 mm was the most specificity (sensitivity, 76.9%; specificity, 94.7%), followed by air-bronchogram sign (sensitivity, 53.8%; specificity, 89.5%), SSN subclassification (sensitivity, 81.5%; specificity, 88.2%), and a lesion size ≧12 mm (sensitivity, 84.6%; specificity, 76.3%). For IPA detection in 79 pure or heterogeneous GGNs, the heterogeneous GGN sign was the most useful finding, with most specificity (sensitivity, 66.7%; specificity, 79.1%), followed by CT attenuation (HU) of ≧-493 (sensitivity, 75%; specificity, 74.6%) and a lesion size ≧10 mm (sensitivity, 83.3%; specificity, 70.1%). In conclusion, this simple combined visual and semiquantitative analysis of CT features helps distinguish IPAs from pre-invasive lesions.