Lung cancer screening, version 1.2015: featured updates to the NCCN guidelines

Application of artificial intelligence in lung cancer screening: A real-world study in a Chinese physical examination population

BACKGROUND

With the rapid increase of chest computed tomography (CT) images, the workload faced by radiologists has increased dramatically. It is undeniable that the use of artificial intelligence (AI) image-assisted diagnosis system in clinical treatment is a major trend in medical development. Therefore, in order to explore the value and diagnostic accuracy of the current AI system in clinical application, we aim to compare the detection and differentiation of benign and malignant pulmonary nodules between AI system and physicians, so as to provide a theoretical basis for clinical application.

METHODS

Our study encompassed a cohort of 23 336 patients who underwent chest low-dose spiral CT screening for lung cancer at the Health Management Center of West China Hospital. We conducted a comparative analysis between AI-assisted reading and manual interpretation, focusing on the detection and differentiation of benign and malignant pulmonary nodules.

RESULTS

The AI-assisted reading exhibited a significantly higher screening positive rate and probability of diagnosing malignant pulmonary nodules compared with manual interpretation (p < 0.001). Moreover, AI scanning demonstrated a markedly superior detection rate of malignant pulmonary nodules compared with manual scanning (97.2% vs. 86.4%, p < 0.001). Additionally, the lung cancer detection rate was substantially higher in the AI reading group compared with the manual reading group (98.9% vs. 90.3%, p < 0.001).

CONCLUSIONS

Our findings underscore the superior screening positive rate and lung cancer detection rate achieved through AI-assisted reading compared with manual interpretation. Thus, AI exhibits considerable potential as an adjunctive tool in lung cancer screening within clinical practice settings.

Machine Learning for Early Discrimination Between Lung Cancer and Benign Nodules Using Routine Clinical and Laboratory Data

BACKGROUND

Lung cancer poses a global health threat necessitating early detection and precise staging for improved patient outcomes. This study focuses on developing and validating a machine learning-based risk model for early lung cancer screening and staging, using routine clinical data.

METHODS

Two medical center, observational, retrospective studies were conducted, involving 2312 lung cancer patients and 653 patients with benign nodules. Machine learning techniques, including differential analysis and feature selection, were employed to identify key factors for modeling. The study focused on variables such as nodule density, carcinoembryonic antigen (CEA), age, and lifestyle habits. The Logistic Regression model was utilized for early diagnoses, and the XGBoost model was utilized for staging based on selected features.

RESULTS

For early diagnoses, the Logistic Regression model achieved an area under the curve (AUC) of 0.716 (95% confidence interval [CI] 0.607-0.826), with 0.703 sensitivity and 0.654 specificity. The XGBoost model excelled in distinguishing late-stage from early-stage lung cancer, exhibiting an AUC of 0.913 (95% CI 0.862-0.963), with 0.909 sensitivity and 0.814 specificity. These findings highlight the model's potential for enhancing diagnostic accuracy and staging in lung cancer.

CONCLUSION

This study introduces a novel machine learning-based risk model for early lung cancer screening and staging, leveraging routine clinical information and laboratory data. The model shows promise in enhancing accuracy, mitigating overdiagnosis, and improving patient outcomes.

Screening for lung cancer using thin-slice low-dose computed tomography in southwestern China: a population-based real-world study

OBJECTIVES

Lung cancer is one of the most common malignant tumors threatening human life and health. At present, low-dose computed tomography (LDCT) screening for the high-risk population to achieve early diagnosis and treatment of lung cancer has become the first choice recommended by many authoritative international medical organizations. To further optimize the lung cancer screening method, we conducted a real-world study of LDCT lung cancer screening in a large sample of a healthy physical examination population, comparing differences in lung nodules and lung cancer detection between thin and thick-slice LDCT scanning.

METHODS

A total of 29 296 subjects who underwent low-dose thick-slice CT scanning (5 mm thickness) from January 2015 to December 2015 and 28 058 subjects who underwent low-dose thin-slice CT scanning (1 mm thickness) from January 2018 to December 2018 in West China Hospital were included. The positive detection rate, detection rate of lung cancer, pathological stage of lung cancer, and mortality rate of lung cancer were analyzed and compared between the two groups.

RESULTS

The positive rate of LDCT screening in the thin-slice scanning group was significantly higher than that in the thick-slice scanning group (20.1% vs. 14.4%, p < 0.001). In addition, the lung cancer detection rate in the thin-slice LDCT screening positive group was significantly higher than that in the thick-slice scanning group (78.0% vs. 52.9%, p < 0.001).

CONCLUSIONS

The screening positive rate of low-dose thin-slice CT scanning is higher and more early-stage lung cancer (IA1 stage) can be detected in the screen-positive group.

Proactively tailoring implementation: the case of shared decision-making for lung cancer screening across the VA New England Healthcare Network

BACKGROUND

Shared Decision-Making to discuss how the benefits and harms of lung cancer screening align with patient values is required by the US Centers for Medicare and Medicaid and recommended by multiple organizations. Barriers at organizational, clinician, clinical encounter, and patient levels prevent SDM from meeting quality standards in routine practice. We developed an implementation plan, using the socio-ecological model, for Shared Decision-Making for lung cancer screening for the Department of Veterans Affairs (VA) New England Healthcare System. Because understanding the local context is critical to implementation success, we sought to proactively tailor our original implementation plan, to address barriers to achieving guideline-concordant lung cancer screening.

METHODS

We conducted a formative evaluation using an ethnographic approach to proactively identify barriers to Shared Decision-Making and tailor our implementation plan. Data consisted of qualitative interviews with leadership and clinicians from seven VA New England medical centers, regional meeting notes, and Shared Decision-Making scripts and documents used by providers. Tailoring was guided by the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS).

RESULTS

We tailored the original implementation plan to address barriers we identified at the organizational, clinician, clinical encounter, and patient levels. Overall, we removed two implementation strategies, added five strategies, and modified the content of two strategies. For example, at the clinician level, we learned that past personal and clinical experiences predisposed clinicians to focus on the benefits of lung cancer screening. To address this barrier, we modified the content of our original implementation strategy Make Training Dynamic to prompt providers to self-reflect about their screening beliefs and values, encouraging them to discuss both the benefits and potential harms of lung cancer screening.

CONCLUSIONS

Formative evaluations can be used to proactively tailor implementation strategies to fit local contexts. We tailored our implementation plan to address unique barriers we identified, with the goal of improving implementation success. The FRAME-IS aided our team in thoughtfully addressing and modifying our original implementation plan. Others seeking to maximize the effectiveness of complex interventions may consider using a similar approach.

Correlation analysis of clinical, pathological, imaging and genetic features of ground-glass nodule featured lung adenocarcinomas between high-risk and non-high-risk individuals

BACKGROUND

Early stage lung adenocarcinomas manifested as ground-glass nodules (GGNs) are increasingly being detected, but screening and diagnosis for GGN-featured lung adenocarcinomas in different risk populations reach no agreement.

OBJECTIVES

To analyze the clinical, pathological, imaging and genetic features of GGN-featured lung adenocarcinomas on high-resolution computed tomography (HRCT) in different risk groups.

METHODS

Include patients with GGNs on HRCT surgically diagnosed as lung adenocarcinoma in the West China Hospital, Sichuan University from 2009 to 2021, and their clinical, pathological, imaging and gene sequencing data.

RESULTS

According to Chinese Expert Consensus on Screening and Management of Lung Cancer, 1,800 patients with GGN-featured lung adenocarcinoma, 545 males (incl. 269 smokers) and 1,255 females (incl. 16 smokers), were divided into high-risk (509) and non-high-risk (1,291) groups. Among them, 1,095 were detected via physical examination. The mean age at diagnosis was 54.78 (23-84) and the mean time from detection to diagnosis was 9.59 months. There were more males than females in the high-risk group [288 (56.58%) vs 221 (43.42%)], just the opposite in the non-high-risk group [1,034 (80.09%) vs 257 (19.91%)] (both P < 0.001). No statistical difference was found in GGN detection way (P > 0.05). The frequency of invasive adenocarcinoma was higher in the high-risk group, while those of precursor lesions and minimally invasive adenocarcinoma were higher in the non-high-risk group (all P < 0.001). The preoperative follow-up time in the non-high-risk group was shorter (P < 0.05). A total of 711 gene mutations were observed in 473 patients with a ratio of non-high-risk to high-risk of 494:217. The incidence of EGFR mutation was not statistically significant (P = 0.824), while those of TP53 and KRAS mutations were higher in the high-risk group (P < 0.05).

CONCLUSIONS

GGN-featured lung adenocarcinoma is dominated by non-high-risk female patients. Shorter preoperative follow-up in the non-high-risk group and no statistical difference in GGN detection way suggests the existing screening criteria for high-risk population may not suit GGN-featured lung cancer. In addition, the incidences of KRAS and TP53 mutations are higher in the high-risk group.

Value of peripheral blood circulating tumor cell detection in the diagnosis of thoracic diseases and the prediction of severity

Circulating tumor cell (CTC) detection, as a noninvasive liquid biopsy method, has been used in the diagnosis, prognostic indication, and monitoring of a variety of cancers. In this study, we aimed to investigate whether CTC detection could be used in the early diagnosis and prediction of severity of thoracic diseases. We enrolled 168 thoracic disease patients, all of whom underwent pathological biopsy. Carcinoembryonic antigen (CEA) and neuron-specific enolase (NSE) measurement was also performed in 146 patients. There were 131 cases of malignant thoracic diseases and 37 cases of benign lesions. We detected CTCs in a 5 ml peripheral blood sample with the CTCBiopsy® system and analyzed the value of CTC count for predicting disease severity. Of 131 patients with a diagnosis of thoracic malignancy, CTCs were found in blood samples from 122 patients. However, only 2 out of 37 patients with benign thoracic disease had no detectable CTCs. There was no significant correlation between CTC count and benign and malignant lesions (P = 0.986). However, among 131 patients who had been diagnosed with malignant lesions, 33 had lymph node metastasis or distant metastasis. The presence of CTCs was significantly correlated with metastasis (P = 0.016 OR = 1.14). The area under the receiver operating characteristic (ROC) curve was 0.625 (95% confidence interval (CI), 0.519 to 0.730 P = 0.032). In addition, with stage IA1 as the cutoff, all patients were further divided into an early-stage group and a late-stage group. CTC count was significantly correlated with disease progression (P = 0.031 OR = 1.11), with an area under the curve (AUC) of 0.599 (95% CI, 0.506-0.692 P = 0.47). The sensitivity and specificity of CTC detection for the diagnosis of disease stage were 72.3% and 45.5%, respectively. In addition, the cutoff of 2.5 CTCs was the same when predicting disease metastasis and staging. Furthermore, the combination of CTC count, demographic characteristics and tumor markers had better predictive significance for disease staging. CTC count can effectively indicate the stages and metastasis of thoracic diseases, but it cannot differentiate benign and malignant diseases.

A Novel Urine Test Biosensor Platform for Early Lung Cancer Detection

Lung cancer is the leading cause of cancer-related mortality worldwide. Early detection is essential to achieving a better outcome and prognosis. Volatile organic compounds (VOCs) reflect alterations in the pathophysiology and body metabolism processes, as shown in various types of cancers. The biosensor platform (BSP) urine test uses animals' unique, proficient, and accurate ability to scent lung cancer VOCs. The BSP is a testing platform for the binary (negative/positive) recognition of the signature VOCs of lung cancer by trained and qualified Long-Evans rats as biosensors (BSs). The results of the current double-blind study show high accuracy in lung cancer VOC recognition, with 93% sensitivity and 91% specificity. The BSP test is safe, rapid, objective and can be performed repetitively, enabling periodic cancer monitoring as well as an aid to existing diagnostic methods. The future implementation of such urine tests as routine screening and monitoring tools has the potential to significantly increase detection rate as well as curability rates with lower healthcare expenditure. This paper offers a first instructive clinical platform utilizing VOC's in urine for detection of lung cancer using the innovative BSP to deal with the pressing need for an early lung cancer detection test tool.

Patient and Clinician Recommendations to Improve Communication and Understanding of Lung Cancer Screening Results

BACKGROUND

Patient understanding of chest low-dose CT (LDCT) scan results for lung cancer screening (LCS) may impact outcomes.

RESEARCH QUESTION

What are patient- and clinician-identified gaps in understanding and communication of LCS results and how might communication be improved through a patient-oriented tool?

STUDY DESIGN AND METHODS

We performed a mixed-methods study of participants recruited from a multisite LCS program to understand knowledge gaps after receiving LCS results and to guide development of a commonly asked questions (CAQ) after LCS information sheet. Initial patient surveys assessed understanding and reactions to LCS results (n = 190). We then conducted patient interviews and focus group discussions (n = 31) to understand experiences receiving LDCT scan results and reactions to results letters and the proposed CAQ; we also interviewed clinicians (n = 6) for feedback on these resources. We summarized survey responses and used thematic analysis to identify major themes in focus groups and interviews.

RESULTS

Of 190 survey respondents (43% response rate), although 88% agreed that they "understood" their LCS results, only 55% reported understanding what a lung nodule is. Approximately two-thirds thought it was "very important" to receive more information regarding lung nodules and incidental lung and heart disease. In interviews and focus groups, although patients believed that brief results letters for normal LDCT scan results generally were acceptable, most found letters explaining abnormal LDCT scan and incidental findings to be concerning and not a substitute for discussion with their clinician. Nearly all patients expressed that the CAQ sheet provided helpful information on nodules, results reporting and incidental findings, and helped them form questions to ask their clinicians.

INTERPRETATION

We identified patient-reported information needs regarding LCS results and developed a CAQ information sheet that was refined with patient and clinician input. The CAQ may represent a simple and feasible way to improve LCS results reporting and to augment clinician-patient discussions.

The usefulness of liquid-based cytology of bronchoalveolar lavage fluid combined with bronchial brush specimens in lung cancer diagnosis

Objective

To explore the diagnostic value of liquid-based cytology (LBC) of bronchoalveolar lavage fluid (BALF) combined with bronchial brushing (BB).

Methods

One hundred patients with pulmonary masses or nodules found by chest computed tomography (CT) or X-ray before bronchoscopy or other diagnostic biopsy examinations were selected consecutively for this retrospective study. BALF and BB were performed for all patients. After conventional smear via BB, we mixed the BALF and BB samples in a prepared thin-layer bottle.

Results

The sensitivity of LBC of BALF combined with BB was noticeably higher than that of BB alone in the total sample group (65.15% vs. 32.84%, respectively). Similarly, in both the bronchoscopically visible group and invisible group, a higher sensitivity for LBC of BALF with BB vs BB alone (68.89% vs. 39.13%, respectively; 57.14% vs. 19.05%, respectively) was observed. Additionally, the negative predictive value of LBC of BALF with BB was higher than that with BB alone (58.56% vs. 42.31%; 61.29% vs. 44.73%; 53.47% vs. 37.83%; total sample vs visible vs invisible groups, respectively).

Conclusion

Regardless of whether lesions or nodules are bronchoscopically visible or invisible, LBC of BALF combined with BB may increase the diagnostic value over BB alone in lung cancer diagnosis.

From COPD to Lung Cancer: Mechanisms Linking, Diagnosis, Treatment, and Prognosis

Many studies have proved that the pathogenesis of the chronic obstructive pulmonary disease (COPD) and lung cancer is related, and may cause and affect each other to a certain extent. In fact, the change of chronic airway obstruction will continue to have an impact on the screening, treatment, and prognosis of lung cancer.In this comprehensive review, we outlined the links and heterogeneity between COPD and lung cancer and finds that factors such as gene expression and genetic susceptibility, epigenetics, smoking, epithelial mesenchymal transformation (EMT), chronic inflammation, and oxidative stress injury may all play a role in the process. Although the relationship between these two diseases have been largely determined, the methods to prevent lung cancer in COPD patients are still limited. Early diagnosis is still the key to a better prognosis. Thus, it is necessary to establish more intuitive screening evaluation criteria and find suitable biomarkers for lung cancer screening in high-risk populations with COPD. Some studies have indicated that COPD may change the efficacy of anti-tumor therapy by affecting the response of lung cancer patients to immune checkpoint inhibitors (ICIs). And for lung cancer patients with COPD, the standardized management of COPD can improve the prognosis. The treatment of lung cancer patients with COPD is an individualized, comprehensive, and precise process. The development of new targets and new strategies of molecular targeted therapy may be the breakthrough for disease treatment in the future.

Impact of CT screening in lung cancer: Scientific evidence and literature review

The treatment of lung cancer has improved significantly in recent years however, lung cancer remains as a leading cause of cancer-related mortality worldwide. Lung cancer screening has been explored, over the past several decades, as a means of reducing lung cancer mortality, to identify asymptomatic disease when it is potentially curable. The National Lung Screening Trial (NLST) established that low-dose computed tomography (LDCT) scans of the chest can be instrumental in reducing lung cancer mortality but the criteria for screening implemented in this trial may not be equitably sensitive across racial and sex subpopulations. Furthermore, the high false detection rate reported in this trial has raised concerns regarding overdiagnosis with LDCT alone. The aim of this review is to summarize the history of lung cancer screening trials, limitations of lung cancer screening, the impact of alternative risk prediction models in reducing disparities, and the use of biomarkers in conjunction with imaging to improve diagnostic authenticity.

Start of an era: circulating cell-free DNA for early detection of cancers

Effective screening modalities are currently available for only a small subset of cancers, and they generally have suboptimal performance with complicated procedures. Therefore, there is an urgent need to develop simple, accurate, and non-invasive methods for early detection of cancers. Genetic and epigenetic alterations in plasma circulating cell-free DNA (cfDNA) have shown the potential to revolutionize methods of early detection of cancers and facilitate subsequent diagnosis to improve survival of patients. The medical interest in cfDNA assays has been inspired by emerging single- and multi-early detection of cancers studies. This review summarizes current technological and clinical advances, in the hopes of providing insights into the development and applications of cfDNA assays in various cancers and clinical scenarios. The key phases of clinical development of biomarkers are highlighted, and the future developments of cfDNA-based liquid biopsies in early detection of cancers are outlined. It is hoped that this study can boost the potential integration of cfDNA-based early detection of cancers into the current clinical workflow.

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Liquid biopsy, characterized by minimal invasiveness and user friendliness, can identify multiple cancers at the early stage and localize the tissue of origin

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The state-of-the-art technology facilitates the application of circulating cell-free DNA (cfDNA) assays in the early detection of cancers

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cfDNA assays are expected to be integrated into the clinical workflow after technological refinement and clinical trial validation

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The development and application strategies of cfDNA assays in various cancers and clinical scenarios can vary, and the harm-and-benefit should be balanced carefully

Wedge Resection vs. Stereotactic Body Radiation Therapy for Clinical Stage I Non-small Cell Lung Cancer: A Systematic Review and Meta-Analysis

Background

Whether wedge resection or stereotactic body radiation therapy (SBRT) has better effectiveness in treatment of clinical stage I non-small cell lung cancer (NSCLC) patients remains unclear. Here we conducted the first meta-analysis to directly compare the survival outcomes of clinical stage I NSCLCs treated with wedge resection and SBRT.

Methods

We systematically searched studies from PubMed, Embase, and Corchrane Library up to October 1, 2021. Data for analysis mainly included overall survival (OS) and disease-free survival (DFS), which were obtained directly from the text results or calculated from the Kaplan–Meier survival curve. We used the standard random-effect model test (DerSimonian and Laird method) to analyze the pooled hazard ratios (HRs) and 95% confidence intervals (CIs). The Q-test and I2-test were used to assess heterogeneity. The stability of pooled HRs was examined by sensitivity analysis.

Results

Six retrospective studies with a total of 11,813 clinical stage I NSCLCs who received wedge resection or SBRT were included. The results showed that patients receiving wedge resection had a significantly better OS (HR = 1.20, 95% CI = [1.07, 1.34], P = 0.002) than those with SBRT, but no significant difference of DFS (HR 1.53, 95% CI = [0.83–2.83], P = 0.17) was observed. There was no significant heterogeneity during our analysis, but there may be potential publication bias among these studies.

Conclusions

Our meta-analysis showed that clinical stage I NSCLCs treated with wedge resection had superior OS than those treated with SBRT. However, more prospective clinical trials should be well-designed to evaluate the optimal treatment modality of early-stage NSCLCs.

Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge

Lung cancer is by far the leading cause of cancer death in the US. Recent studies have demonstrated the effectiveness of screening using low dose CT (LDCT) in reducing lung cancer related mortality. While lung nodules are detected with a high rate of sensitivity, this exam has a low specificity rate and it is still difficult to separate benign and malignant lesions. The ISBI 2018 Lung Nodule Malignancy Prediction Challenge, developed by a team from the Quantitative Imaging Network of the National Cancer Institute, was focused on the prediction of lung nodule malignancy from two sequential LDCT screening exams using automated (non-manual) algorithms. We curated a cohort of 100 subjects who participated in the National Lung Screening Trial and had established pathological diagnoses. Data from 30 subjects were randomly selected for training and the remaining was used for testing. Participants were evaluated based on the area under the receiver operating characteristic curve (AUC) of nodule-wise malignancy scores generated by their algorithms on the test set. The challenge had 17 participants, with 11 teams submitting reports with method description, mandated by the challenge rules. Participants used quantitative methods, resulting in a reporting test AUC ranging from 0.698 to 0.913. The top five contestants used deep learning approaches, reporting an AUC between 0.87 - 0.91. The team's predictor did not achieve significant differences from each other nor from a volume change estimate (p =.05 with Bonferroni-Holm's correction).

Molecular Mechanisms and Cellular Contribution from Lung Fibrosis to Lung Cancer Development

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, fibrosing interstitial lung disease (ILD) of unknown aetiology, with a median survival of 2-4 years from the time of diagnosis. Although IPF has unknown aetiology by definition, there have been identified several risks factors increasing the probability of the onset and progression of the disease in IPF patients such as cigarette smoking and environmental risk factors associated with domestic and occupational exposure. Among them, cigarette smoking together with concomitant emphysema might predispose IPF patients to lung cancer (LC), mostly to non-small cell lung cancer (NSCLC), increasing the risk of lung cancer development. To this purpose, IPF and LC share several cellular and molecular processes driving the progression of both pathologies such as fibroblast transition proliferation and activation, endoplasmic reticulum stress, oxidative stress, and many genetic and epigenetic markers that predispose IPF patients to LC development. Nintedanib, a tyrosine-kinase inhibitor, was firstly developed as an anticancer drug and then recognized as an anti-fibrotic agent based on the common target molecular pathway. In this review our aim is to describe the updated studies on common cellular and molecular mechanisms between IPF and lung cancer, knowledge of which might help to find novel therapeutic targets for this disease combination.

Patient Identification of Lung Cancer Screening Follow-up Recommendations and the Association with Adherence

RATIONALE

Adherence to follow-up lung cancer screening (LCS) in real-world settings is suboptimal. Patient understanding of screening results and anticipated follow-up may be crucial to adherence.

OBJECTIVE

To determine patient-factors associated with identification of follow-up recommendations as a measure of patient understanding of screening results after LCS , and to determine whether misidentification of follow-up is associated with lower adherence to recommendations.

METHODS

We performed a prospective study of patients in the University of Washington/Seattle Cancer Care Alliance LCS registry who underwent an initial LCS exam between June 2017- September 2019. We mailed potential participants a survey following initial LCS exam, with additional data abstracted from the electronic health record and LCS registry. Participants were asked to identify the timing and next step for their follow-up, with answers corresponding to Lung-RADS recommendations. We examined associations between incorrect identification of recommended follow-up and patient-level characteristics, self-perceived benefit/harm of LCS, LCS knowledge, Lung-RADS score, and patient-reported method of LCS results communication (letter, telephone or in-person). We used multivariable logistic regression to evaluate associations with incorrect identification of recommendations and assessed incorrect identification of recommendations as a potential mechanism for poor adherence in a separate regression model.

RESULTS

One-hundred eighty-eight participants completed the survey (response rate 44%); 47% misidentified their follow-up recommendation. Those with lung-RADS scores ≥3 had higher odds of incorrectly identifying follow-up recommendations compared to those with scores <3, as did those with lower educational attainment. However, there was no significant association between incorrect identification of follow-up and ultimate adherence to follow-up.

CONCLUSION

Understanding of LCS follow-up appears to be poor, especially among those with lower education levels and positive findings. Among survey responders, incorrect identification of follow-up was not associated with poor adherence, suggesting other factors, such as provider interventions, may be driving adherence behavior. These results can inform efforts to target improved patient education regarding follow-up for LCS. Primary sources of funding. American Lung Association and American Thoracic Society.

Implementing Shared Decision-Making for Lung Cancer Screening across a Veterans Health Administration Hospital Network

Shared-decision making (SDM) for lung cancer screening (LCS) is recommended by multiple organizations, reflecting a larger movement towards patient-centered care. Yet SDM for LCS does not routinely occur due to barriers at multiple levels. Moreover, how best to implement SDM into routine clinical practice remains unknown. There is a need for a novel approach to overcome multi-level barriers and ensure high-quality SDM for LCS is integrated into routine practice. We present the protocol for our US Department of Veteran Affairs (VA) funded study. Our protocol is designed to implement and evaluate a multi-level, tailored approach to SDM for LCS in routine clinical practice within the VA New England Health Care Network, comprising eight medical centers. In this prospective, pragmatic hybrid implementation-effectiveness study, we will first conduct a formative evaluation of barriers to SDM for LCS at each level of the socioecological model, which will inform our tailored implementation plan. We will then sequentially introduce components of our tailored, multi-level approach to implementing SDM for LCS across VA New England. Finally, using mixed methods, we will evaluate the implementation and its impact on Effectiveness (primary outcome, defined as patient-centeredness of SDM), as well as implementation outcomes informed by the RE-AIM implementation science framework (i.e., Reach to patients, Adoption by providers, Implementation fidelity). Tailored implementation will address identified challenges to achieving policy recommendations for SDM for LCS in VA New England, inform nationwide implementation of SDM for LCS, and address stakeholder interests in promoting more patient-centered interactions across the VA.

Prediction Model for Lung Cancer in High-Risk Nodules Being Considered for Resection: Development and Validation in a Chinese Population

Background

Determining benign and malignant nodules before surgery is very difficult when managing patients with pulmonary nodules, which further makes it difficult to choose an appropriate treatment. This study aimed to develop a lung cancer risk prediction model for predicting the nature of the nodule in patients’ lungs and deciding whether to perform a surgical intervention.

Methods

This retrospective study included patients with pulmonary nodules who underwent lobectomy or sublobectomy at Tianjin Medical University General Hospital between 2017 and 2020. All subjects were further divided into training and validation sets. Multivariable logistic regression models with backward selection based on the Akaike information criterion were used to identify independent predictors and develop prediction models.

Results

To build and validate the model, 503 and 260 malignant and benign nodules were used. Covariates predicting lung cancer in the current model included female sex, age, smoking history, nodule type (pure ground-glass and part-solid), nodule diameter, lobulation, margin (smooth, or spiculated), calcification, intranodular vascularity, pleural indentation, and carcinoembryonic antigen. The final model of this study showed excellent discrimination and calibration with a concordance index (C-index) of 0.914 (0.890–0.939). In an independent sample used for validation, the C-index for the current model was 0.876 (0.825–0.927) compared with 0.644 (0.559–0.728) and 0.681 (0.605–0.757) for the Mayo and Brock models. The decision curve analysis showed that the current model had higher discriminatory power for malignancy than the Mayo and the Brock models.

Conclusions

The current model can be used in estimating the probability of lung cancer in nodules requiring surgical intervention. It may reduce unnecessary procedures for benign nodules and prompt diagnosis and treatment of malignant nodules.

Non-small-cell lung cancer with epidermal growth factor receptor L861Q-L833F compound mutation benefits from both afatinib and osimertinib: A case report

BACKGROUND

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have been adopted as the standard of care for non-small cell lung cancer (NSCLC) patients harboring EGFR sensitizing mutations. Besides the two common mutations exon 19 deletion and L858R, which together comprise approximately 85% of EGFR mutations in NSCLC, rare EGFR mutations also exist, including point mutations, deletions, and insertions spanning EGFR exons 18-25. However, the responsiveness of uncommon EGFR mutations to EGFR TKIs remains elusive and attracts increasing interest.

CASE SUMMARY

Herein, we report a 55-year-old male patient with stage IV NSCLC harboring a rare EGFR L833F-L861Q compound mutation in cis. The patient achieved a partial response to first-line treatment with afatinib and a progression-free survival of 10 mo. After afatinib failure, the patient received multiple line treatments with chemotherapy. Upon disease progression, the heavily pretreated patient was treated with osimertinib and bevacizumab, and both lung lesion and brain metastases were stable for more than 3 mo. He had an overall survival of 25 mo.

CONCLUSION

Our case revealed that both afatinib and the osimertinib + bevacizumab combination demonstrated clinical efficacy in NSCLC harboring an EGFR L833F-L861Q compound mutation. The results provide more therapeutic options for patients with rare compound mutations.

Early Diagnosis of Lung Cancer in the United Arab Emirates: Challenges and Strategic Recommendations

In the United Arab Emirates (UAE), lung cancer (LC) was the third leading cause of deaths due to cancer in 2017. Around 80% of the patients in the UAE are diagnosed at a late stage, rendering the treatment less effective in improving survival outcomes. Lack of awareness of disease symptomatology, deficient screening initiatives, misdiagnosis, and delayed referral to the specialist are contributing factors for delayed diagnosis. Effective screening at a primary care setting can be crucial for early diagnosis, referral to specialists, and enhancing patient outcomes. It is important to establish screening and referral guidelines through which each suspected case can be identified and provided timely intervention. Although the international screening and referral pathway framework are comprehensive, several regional barriers need to be addressed before they can be adapted at the national level. A group of LC experts from the UAE deliberated on issues like delayed diagnosis of LC and strategic recommendations for overcoming the challenges. The discussion was based on the review of the published evidence, international and regional guidelines for screening and early diagnosis of LC. Herein, we present a guideline, endorsed by the esteemed panel of experts, for aiding early diagnosis and optimizing the management of LC in the UAE.

2020 Innovation-Based Optimism for Lung Cancer Outcomes

Lung cancer is the leading cause of cancer death in both males and females in the U.S. and worldwide. Owing to advances in prevention, screening/early detection, and therapy, lung cancer mortality rates are decreasing and survival rates are increasing. These innovations are based on scientific discoveries in imaging, diagnostics, genomics, molecular therapy, and immunotherapy. Outcomes have improved in all histologies and stages. This review provides information on the clinical implications of these innovations that are practical for the practicing physicians, especially oncologists of all specialities who diagnose and treat patients with lung cancer. IMPLICATIONS FOR PRACTICE: Lung cancer survival rates have improved because of new prevention, screening, and therapy methods. This work provides a review of current standards for each of these areas, including targeted and immunotherapies. Treatment recommendations are provided for all stages of lung cancer.

Improvement in Follow-up Imaging With a Patient Tracking System and Computerized Registry for Lung Nodule Management

PURPOSE

Despite established guidelines, radiologists' recommendations and timely follow-up of incidental lung nodules remain variable. To improve follow-up of nodules, a system using standardized language (tracker phrases) recommending time-based follow-up in chest CT reports, coupled with a computerized registry, was created.

MATERIALS AND METHODS

Data were obtained from the electronic health record and a facility-built electronic lung nodule registry. We evaluated two randomly selected patient cohorts with incidental nodules on chest CT reports: before intervention (September 2008 to March 2011) and after intervention (August 2011 to December 2016). Multivariable logistic regression was used to compare the cohorts for the main outcome of timely follow-up, defined as a subsequent report within 13 months of the initial report.

RESULTS

In all, 410 patients were included in the pretracker cohort versus 626 in the tracker cohort. Before system inception, 30% of CT reports lacked an explicit time-based recommendation for nodule follow-up. The proportion of patients with timely follow-up increased from 46% to 55%, and the proportion of those with no documented follow-up or follow-up beyond 24 months decreased from 48% to 31%. The likelihood of timely follow-up increased 41%, adjusted for high risk for lung cancer and age 65 years or older. After system inception, reports missing a tracker phrase for nodule recommendation averaged 6%, without significant interyear variation.

CONCLUSIONS

Standardized language added to CT reports combined with a computerized registry designed to identify and track patients with incidental lung nodules was associated with improved likelihood of follow-up imaging.

Shared Decision-Making for Lung Cancer Screening: How Well Are We "Sharing"?

BACKGROUND

Lung cancer screening (LCS) reduces lung cancer mortality, but it also carries a range of risks. Shared decision-making (SDM) is a process of engaging patients in their health care decisions and is a vital component of LCS.

RESEARCH QUESTION

What is the quality of SDM among patients recently assessed for LCS?

STUDY DESIGN AND METHODS

Cross-sectional study of screened patients recruited from two academic tertiary care centers in the South Central Region of the United States. Self-reported surveys assessed patient demographics, values related to outcomes of LCS, knowledge, SDM components including receipt of educational materials, and decisional conflict.

RESULTS

Recently screened patients (n = 266) possessed varied LCS knowledge, answering an average of 41.4% of questions correctly. Patients valued finding cancer early over concerns about harms. Patients indicated that LCS benefits were presented to them by a health care provider far more often than harms (68.3% vs 20.8%, respectively), and 30.7% reported they received educational materials about LCS during the screening process. One-third of patients had some decisional conflict (33.6%) related to their screening decisions, whereas most patients (86.6%) noted that they were involved in the screening decision as much as they wanted. In multivariate models, non-White race and having less education were related to lower knowledge scores. Non-White patients and former smokers were more likely to be conflicted about the screening decision. Most patients (n = 227 [85.3%]) indicated that a health care provider had discussed smoking cessation or abstinence with them.

INTERPRETATION

Among recently screened patients, the quality of decision-making about LCS is highly variable. The low use of educational materials including decision aids and imbalance of conveying benefit vs risk information to patients is concerning. A structured approach using decision aids may assist with providing a balanced presentation of information and may improve the quality of SDM.

Screening rate and influential factors of lung cancer with low-dose computed tomography in Asian population: a systematic review and meta-analysis

BACKGROUND

There are currently no studies synthesizing the screening rate and influential factors of low-dose computed tomography (LDCT)-screened lung cancer in Asian population.

METHODS

A systematic review was conducted, using both English and Chinese language databases on March, 2019. The pooled screening rate and estimated odds ratios (ORs) of influential factors were analyzed using random effects models. Subgroup and meta-regression analyses were also employed to explore the heterogeneity.

RESULTS

The pooled LDCT lung cancer screening rate was 1.12% (95% confidence interval (CI): 0.94%, 1.32%), and increased with age. Adenocarcinoma and stage I lung cancer had higher screening rates. Analysis of influential factors in the general population showed that female and elder age (≥50 years) were significantly influencing LDCT lung cancer screening rate (for female, OR = 1.32, 95% CI: 1.15-1.52; for adults ≥ 50 years, OR = 1.94, 95% CI: 1.52-2.49). Meta-regression analysis indicated that the heterogeneity maybe significantly correlated with the sample size, risk population and source of population.

CONCLUSIONS

Unlike European and American populations, female and adults > 50 years rather than smoking adults were positively associated with screening rate in Asian populations. It is important to further study the benefits of lung cancer screening with LDCT in Asian populations.

Diagnostic role of liquid-based cytology of bronchial lavage fluid in addition to bronchial brushing specimens in lung cancer

BACKGROUND

Liquid-based cytology (LBC) tests, including the liquid-based thin layer method, have demonstrated the highest potential for reducing false-negatives and improving sample quality.

METHOD

This study aimed to evaluate the diagnostic role of LBC of bronchial brushing specimens in lung cancer. A total of 249 patients were analyzed in our study, involving 155 patients with combined bronchial brushing and bronchoalveolar lavage (BAL) and 94 patients with BAL alone.

RESULTS

The sensitivity in the combined bronchial brushing and BAL group was 61.4% in the diagnosis of lung cancer, which is much higher than with BAL alone. Rates of positive predictive values and negative predictive values in the combined group compared with the BALF alone group were 98.6% vs 100% and 47.6% vs 37.4%, respectively. Sensitivity in the BALF alone group was 12.5% in bronchoscopically invisible pulmonary lesions and as high as 52.1% in the combined group.

CONCLUSION

The results from our study demonstrated that LBC of brushing samples could be used as an important complement of bronchoscopy and could have the potential to be widely applied.

Patient vs Clinician Perspectives on Communication About Results of Lung Cancer Screening: A Qualitative Study

BACKGROUND

In the incidental pulmonary nodule and breast cancer screening settings, high-quality patient-centered communication can improve adherence to evaluation and mitigate patient distress. Although guidelines emphasize shared decision-making before lung cancer screening, little is known about patient-clinician communication after lung cancer screening.

RESEARCH QUESTION

How do patients and clinicians perceive communication and results notification after lung cancer screening, and are there approaches that may mitigate or exacerbate distress?

STUDY DESIGN AND METHODS

We conducted interviews and focus groups with 49 patients who underwent lung cancer screening in the prior year and 36 clinicians who communicate screening results (primary care providers, pulmonologists, nurses), recruited from lung cancer screening programs at 4 hospitals. We analyzed transcripts using conventional content analysis.

RESULTS

Clinicians and patients diverged in their impressions of the quality of communication after lung cancer screening. Clinicians recognized the potential for patient distress and tailored their approach to disclosure based on how clinically concerning they perceived results to be. Disclosure of normal or low-risk findings usually occurred by letter; clinicians believed this process was efficient and well received by patients. Yet many patients were dissatisfied: several could not recall receiving results at all, and others reported that receiving results by letter left them confused and concerned, with little opportunity to ask questions. By contrast, patients with larger nodules typically received results during an immediate phone call or clinic visit, and both patients and clinicians agreed that these conversations represented high-quality communication that met patient needs. Regardless of their cancer risk, patients who learned their results in a conversation appreciated the opportunity to discuss both the meaning of the nodule and the evaluation plan, and to have their concerns addressed, preempting distress.

INTERPRETATION

Tension exists between clinicians' interest in efficiency of results notification by letter in low-risk cases and patients' need to understand and be reassured about screening results, their implications, and the plan for subsequent screening or nodule evaluation-even when clinicians did not perceive results as concerning. Brief conversations to discuss lung cancer screening results may improve patient understanding and satisfaction while reducing distress.

Convolutional Neural Network ensembles for accurate lung nodule malignancy prediction 2 years in the future

Convolutional Neural Networks (CNNs) have been utilized for to distinguish between benign lung nodules and those that will become malignant. The objective of this study was to use an ensemble of CNNs to predict which baseline nodules would be diagnosed as lung cancer in a second follow up screening after more than one year. Low-dose helical computed tomography images and data were utilized from the National Lung Screening Trial (NLST). The malignant nodules and nodule positive controls were divided into training and test cohorts. T0 nodules were used to predict lung cancer incidence at T1 or T2. To increase the sample size, image augmentation was performed using rotations, flipping, and elastic deformation. Three CNN architectures were designed for malignancy prediction, and each architecture was trained using seven different seeds to create the initial weights. This enabled variability in the CNN models which were combined to generate a robust, more accurate ensemble model. Augmenting images using only rotation and flipping and training with images from T0 yielded the best accuracy to predict lung cancer incidence at T2 from a separate test cohort (Accuracy = 90.29%; AUC = 0.96) based on an ensemble 21 models. Images augmented by rotation and flipping enabled effective learning by increasing the relatively small sample size. Ensemble learning with deep neural networks is a compelling approach that accurately predicted lung cancer incidence at the second screening after the baseline screen mostly 2 years later.

Development of a machine learning-based multimode diagnosis system for lung cancer

As an emerging technology, artificial intelligence has been applied to identify various physical disorders. Here, we developed a three-layer diagnosis system for lung cancer, in which three machine learning approaches including decision tree C5.0, artificial neural network (ANN) and support vector machine (SVM) were involved. The area under the curve (AUC) was employed to evaluate their decision powers. In the first layer, the AUCs of C5.0, ANN and SVM were 0.676, 0.736 and 0.640, ANN was better than C5.0 and SVM. In the second layer, ANN was similar with SVM but superior to C5.0 supported by the AUCs of 0.804, 0.889 and 0.825. Much higher AUCs of 0.908, 0.910 and 0.849 were identified in the third layer, where the highest sensitivity of 94.12% was found in C5.0. These data proposed a three-layer diagnosis system for lung cancer: ANN was used as a broad-spectrum screening subsystem basing on 14 epidemiological data and clinical symptoms, which was firstly adopted to screen high-risk groups; then, combining with additional 5 tumor biomarkers, ANN was used as an auxiliary diagnosis subsystem to determine the suspected lung cancer patients; C5.0 was finally employed to confirm lung cancer patients basing on 22 CT nodule-based radiomic features.

Hybrid models for lung nodule malignancy prediction utilizing convolutional neural network ensembles and clinical data

Purpose: Due to the high incidence and mortality rates of lung cancer worldwide, early detection of a precancerous lesion is essential. Low-dose computed tomography is a commonly used technique for screening, diagnosis, and prognosis of non-small-cell lung cancer. Recently, convolutional neural networks (CNN) had shown great potential in lung nodule classification. Clinical information (family history, gender, and smoking history) together with nodule size provide information about lung cancer risk. Large nodules have greater risk than small nodules. Approach: A subset of cases from the National Lung Screening Trial was chosen as a dataset in our study. We divided the nodules into large and small nodules based on different clinical guideline thresholds and then analyzed the groups individually. Similarly, we also analyzed clinical features by dividing them into groups. CNNs were designed and trained over each of these groups individually. To our knowledge, this is the first study to incorporate nodule size and clinical features for classification using CNN. We further made a hybrid model using an ensemble with the CNN models of clinical and size information to enhance malignancy prediction. Results: From our study, we obtained 0.9 AUC and 83.12% accuracy, which was a significant improvement over our previous best results. Conclusions: In conclusion, we found that dividing the nodules by size and clinical information for building predictive models resulted in improved malignancy predictions. Our analysis also showed that appropriately integrating clinical information and size groups could further improve risk prediction.

Evaluation of Prediction Models for Identifying Malignancy in Pulmonary Nodules Detected via Low-Dose Computed Tomography

IMPORTANCE

Malignancy prediction models based on participant-related characteristics and imaging parameters from low-dose computed tomography (CT) may improve decision-making regarding nodule management and diagnosis in lung cancer screening.

OBJECTIVE

To externally validate 5 malignancy prediction models that were developed in screening settings, compared with 3 models that were developed in clinical settings, in terms of discrimination and absolute risk calibration among participants in the German Lung Cancer Screening Intervention trial.

DESIGN, SETTING, AND PARTICIPANTS

In this population-based diagnostic study, malignancy probabilities were estimated by applying 8 prediction models to data from 1159 participants in the intervention arm of the Lung Cancer Screening Intervention trial, a randomized clinical trial conducted from October 23, 2007, to April 30, 2016, with ongoing follow-up. This analysis considers end points up to 1 year after individuals' last screening visit. Inclusion criteria for participants were at least 1 noncalcified pulmonary nodule detected on any of 5 annual screening visits, receiving a lung cancer diagnosis within the active screening phase of the Lung Cancer Screening Intervention trial, and an unequivocal identification of the malignant nodules. Data analysis was performed from February 1, 2019, through December 5, 2019.

INTERVENTIONS

Five annual rounds of low-dose multislice CT.

MAIN OUTCOMES AND MEASURES

Discrimination ability and calibration of malignancy probabilities estimated by 5 models developed in data from screening studies (4 Pan-Canadian Early Detection of Lung Cancer Study [PanCan] models using a parsimonious approach including nodule spiculation [PanCan-1b] or a comprehensive approach including nodule spiculation [PanCan-2b], and PanCan-2b replacing the nodule diameter variable with mean diameter [PanCan-MD] or volume [PanCan-VOL], as well as a model developed by the UK Lung Cancer Screening trial) and 3 models developed in clinical settings (US Department of Veterans Affairs, Mayo Clinic, and Peking University People's Hospital).

RESULTS

A total of 1159 participants (median [range] age, 57.63 [50.34-71.89] years; 763 [65.8%] men) with 3903 pulmonary nodules were included in this study. For nodules detected in the prevalence round of CT, the PanCan models showed excellent discrimination (PanCan-1b: area under the curve [AUC], 0.93 [95% CI, 0.87-0.99]; PanCan-2b: AUC, 0.94 [95% CI, 0.89-0.99]; PanCan-MD: AUC, 0.94 [95% CI, 0.91-0.98]; PanCan-VOL: AUC, 0.94 [95% CI, 0.90-0.98]), and all of the screening models except PanCan-MD and PanCan-VOL showed acceptable calibration (PanCan-1b: Spiegelhalter z = -1.081; P = .28; PanCan-2b: Spiegelhalter z = 0.436; P = .67; PanCan-MD: Spiegelhalter z = 3.888; P < .001; PanCan-VOL: Spiegelhalter z = 1.978; P = .05; UK Lung Cancer Screening trial: Spiegelhalter z = -1.076; P = .28), whereas the other models showed worse discrimination and calibration, from an AUC of 0.58 (95% CI, 0.46-0.70) for the UK Lung Cancer Screening trial model to an AUC of 0.89 (95% CI, 0.82-0.97) for the Mayo Clinic model.

CONCLUSIONS AND RELEVANCE

This diagnostic study found that PanCan models showed excellent discrimination and calibration in prevalence screenings, confirming their ability to improve nodule management in screening settings, although calibration to nodules detected in follow-up scans should be improved. The models developed by the Mayo Clinic, Peking University People's Hospital, Department of Veterans Affairs, and UK Lung Cancer Screening Trial did not perform as well.

Effect of a Patient Decision Aid on Lung Cancer Screening Decision-Making by Persons Who Smoke: A Randomized Clinical Trial

IMPORTANCE

Lung cancer screening with low-dose computed tomography lowers lung cancer mortality but has potential harms. Current guidelines support patients receiving information about the benefits and harms of lung cancer screening during decision-making.

OBJECTIVE

To examine the effect of a patient decision aid (PDA) about lung cancer screening compared with a standard educational material (EDU) on decision-making outcomes among smokers.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial was conducted using 13 state tobacco quitlines. Current and recent tobacco quitline clients who met age and smoking history eligibility for lung cancer screening were enrolled from March 30, 2015, to September 12, 2016, and followed up for 6 months until May 5, 2017. Data analysis was conducted between May 5, 2017, and September 30, 2018.

INTERVENTIONS

Participants were randomized to the PDA video Lung Cancer Screening: Is It Right for Me? (n = 259) or to EDU (n = 257).

MAIN OUTCOMES AND MEASURES

The primary outcomes were preparation for decision-making and decisional conflict measured at 1 week. Secondary outcomes included knowledge, intentions, and completion of screening within 6 months of receiving the intervention measured by patient report.

RESULTS

Of 516 quit line clients enrolled, 370 (71.7%) were younger than 65 years, 320 (62.0%) were female, 138 (26.7%) identified as black, 47 (9.1%) did not have health insurance, and 226 (43.8%) had a high school or lower educational level. Of participants using the PDA, 153 of 227 (67.4%) were well prepared to make a screening decision compared with 108 of 224 participants (48.2%) using EDU (odds ratio [OR], 2.31; 95% CI, 1.56-3.44; P < .001). Feeling informed about their screening choice was reported by 117 of 234 participants (50.0%) using a PDA compared with 66 of 233 participants (28.3%) using EDU (OR, 2.56; 95% CI, 1.72-3.79; P < .001); 159 of 234 participants (68.0%) using a PDA compared with 110 of 232 (47.4%) participants using EDU reported being clear about their values related to the harms and benefits of screening (OR, 2.37; 95% CI, 1.60-3.51; P < .001). Participants using a PDA were more knowledgeable about lung cancer screening than participants using EDU at each follow-up assessment. Intentions to be screened and screening behaviors did not differ between groups.

CONCLUSIONS AND RELEVANCE

In this study, a PDA delivered to clients of tobacco quit lines improved informed decision-making about lung cancer screening. Many smokers eligible for lung cancer screening can be reached through tobacco quit lines.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02286713.

Significant function and research progress of biomarkers in gastric cancer

Gastric cancer is one of the most common gastrointestinal tumor types, and the incidence and mortality rates are higher in men compared with women. Various studies have revealed that gastric cancer is a spectrum of tumor types, which have biological and genetic diversity. It has proven to be difficult to improve the overall survival and disease-free survival of patients with gastric cancer through the use of traditional surgery and chemoradiation, as gastric cancer is usually identified at an advanced stage. In consequence, the outcome is frequently poor. Thus, novel biomarkers and anticancer targets are required to improve the outcome. As the identification of biomarkers has increased due to advances in research and the greater availability of bioinformatics and functional genomics, the potential therapeutic regimens available have also increased concurrently. These advances have also improved the ability to predict responses to chemotherapy, targeted therapy and immunotherapy, whilst other biomarkers predict post-treatment survival and recurrence based on their expression. This review focuses closely on the important functions of biomarkers in the timely diagnosis and treatment of gastric cancer, in addition to the advances in the study of certain novel markers in gastric cancer.

Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology

Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. Early detection of lung cancer is an important opportunity for decreasing mortality. Data support using low-dose computed tomography (LDCT) of the chest to screen select patients who are at high risk for lung cancer. Lung screening is covered under the Affordable Care Act for individuals with high-risk factors. The Centers for Medicare & Medicaid Services (CMS) covers annual screening LDCT for appropriate Medicare beneficiaries at high risk for lung cancer if they also receive counseling and participate in shared decision-making before screening. The complete version of the NCCN Guidelines for Lung Cancer Screening provides recommendations for initial and subsequent LDCT screening and provides more detail about LDCT screening. This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for LDCT of the chest and on evaluating initial screening findings.

Risk factors and clinical characteristics of lung cancer in idiopathic pulmonary fibrosis: a retrospective cohort study

Background

Lung cancer is a common comorbidity of idiopathic pulmonary fibrosis (IPF) and has poor outcomes. The incidence and clinical factors related to development of lung cancer in idiopathic pulmonary fibrosis (IPF) are unclear. The aim of this study was to elucidate the cumulative incidence, risk factors, and clinical characteristics of lung cancer in IPF.

Methods

In this retrospective study, we analyzed clinical data for 938 patients who were diagnosed with IPF without lung cancer between 1998 and 2013. Demographic, physiologic, radiographic, and histologic characteristics were reviewed. Cumulative incidence of lung cancer and survival were estimated by the Kaplan-Meier method. Risk factors of lung cancer development were determined by Cox proportional hazard analysis.

Results

Among 938 IPF patients without lung cancer at initial diagnosis, lung cancer developed in 135 (14.5%) during the follow-up period. The cumulative incidences of lung cancer were 1.1% at 1 year, 8.7% at 3, 15.9% at 5, and 31.1% at 10 years. Risk factors of lung cancer were male gender, current smoking at IPF diagnosis, and rapid annual decline of 10% or more in forced vital capacity (FVC). Patients who developed lung cancer were mostly elderly men with smoking history. Squamous cell carcinoma followed by adenocarcinoma was the most common histologic type. Lung cancer was frequently located in areas abutting or within fibrosis. Survival was significantly worse in patients with lung cancer compared to patients with IPF alone.

Conclusion

Lung cancer frequently developed in patients with IPF and was common in current-smoking men with rapid decline of FVC.

Electronic supplementary material

The online version of this article (10.1186/s12890-019-0905-8) contains supplementary material, which is available to authorized users.

Increased Incidence of Lung Cancer Among Patients With Superficial Transitional Cell Carcinoma: A Potential Risk Cohort for Lung Cancer Screening

BACKGROUND

Smoking is a major risk factor for lung cancer (LC) and transitional cell carcinoma of the bladder (TCC). Current recommendations for LC screening do not include TCC as a risk factor for determining screening eligibility. In this study we aimed to evaluate whether TCC patients constitute a population who might benefit from LC screening.

PATIENTS AND METHODS

The Surveillance, Epidemiology, and End Results 18 database was used to determine the incidence, standardized incidence ratio (SIR), and the average time to diagnosis of LC in patients with localized TCC of the bladder (American Joint Committee on Cancer, sixth edition, stages 0-1).

RESULTS

On the basis of 91,606 patients with localized TCC, The SIR for LC in men was 1.89 (95% confidence interval [CI], 1.8-1.97), significantly different from the risk for all solid tumors. The SIR for LC in women was 2.43 (95% CI, 2.22-2.65), significantly higher than for men. The 5-year incidence of LC was 3.2%, and the 10-year incidence was 5.94%. The average time to diagnosis of LC was 3.4 years, with >80% of LC cases occurring within 5 years of TCC diagnosis.

CONCLUSION

Patients with localized TCC have a higher incidence of LC than the general population. The risk is significantly increased among women compared with men. Considering this increased risk, patients with early stage TCC might stand to benefit from LC screening. Additional differences were noted between male and female TCC patients, which bear further study.

Quantitative Imaging features Improve Discrimination of Malignancy in Pulmonary nodules

Pulmonary nodules are frequently detected radiological abnormalities in lung cancer screening. Nodules of the highest- and lowest-risk for cancer are often easily diagnosed by a trained radiologist there is still a high rate of indeterminate pulmonary nodules (IPN) of unknown risk. Here, we test the hypothesis that computer extracted quantitative features (“radiomics”) can provide improved risk-assessment in the diagnostic setting. Nodules were segmented in 3D and 219 quantitative features are extracted from these volumes. Using these features novel malignancy risk predictors are formed with various stratifications based on size, shape and texture feature categories. We used images and data from the National Lung Screening Trial (NLST), curated a subset of 479 participants (244 for training and 235 for testing) that included incident lung cancers and nodule-positive controls. After removing redundant and non-reproducible features, optimal linear classifiers with area under the receiver operator characteristics (AUROC) curves were used with an exhaustive search approach to find a discriminant set of image features, which were validated in an independent test dataset. We identified several strong predictive models, using size and shape features the highest AUROC was 0.80. Using non-size based features the highest AUROC was 0.85. Combining features from all the categories, the highest AUROC were 0.83.

Computed Tomography-Based Radiomics Signature: A Potential Indicator of Epidermal Growth Factor Receptor Mutation in Pulmonary Adenocarcinoma Appearing as a Subsolid Nodule

BACKGROUND

Lung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer sensitive to EGFR-targeted tyrosine kinase inhibitors. We aimed to develop and validate a computed tomography (CT)-based radiomics signature for prediction of EGFR mutation status in LADC appearing as a subsolid nodule.

MATERIALS AND METHODS

A total of 467 eligible patients were divided into training and validation cohorts (n = 306 and 161, respectively). Radiomics features were extracted from unenhanced CT images by using Pyradiomics. A CT-based radiomics signature for distinguishing EGFR mutation status was constructed using the random forest (RF) method in the training cohort and then tested in the validation cohort. A combination of the radiomics signature with a clinical factors model was also constructed using the RF method. The performance of the model was evaluated using the area under the curve (AUC) of a receiver operating characteristic curve.

RESULTS

In this study, 64.2% (300/467) of the patients showed EGFR mutations. L858R mutation of exon 21 was the most common mutation type (185/301). We identified a CT-based radiomics signature that successfully discriminated between EGFR positive and EGFR negative in the training cohort (AUC = 0.831) and the validation cohort (AUC = 0.789). The radiomics signature combined with the clinical factors model was not superior to the simple radiomics signature in the two cohorts (p > .05).

CONCLUSION

As a noninvasive method, the CT-based radiomics signature can be used to predict the EGFR mutation status of LADC appearing as a subsolid nodule.

IMPLICATIONS FOR PRACTICE

Lung adenocarcinoma (LADC) with epidermal growth factor receptor (EGFR) mutation is considered a subgroup of lung cancer that is sensitive to EGFR-targeted tyrosine kinase inhibitors. However, some patients with inoperable subsolid LADC are unable to undergo tissue sampling by biopsy for molecular analysis in clinical practice. A computed tomography-based radiomics signature may serve as a noninvasive biomarker to predict the EGFR mutation status of subsolid LADCs when mutational profiling is not available or possible.

[Lung cancer screening among the smoker population]

CONTEXT

Lung cancer is the most common cancer in men and the leading cause of cancer death worldwide. This cancer, often diagnosed at an advanced stage, mainly affects smokers and survival could increase with early detection. Screening by chest x-ray has not shown its effectiveness, then several randomized trials have been carried out about screening by thoracic low-dose computed tomography in smokers.

METHODS

A systematic review of these trials was conducted according to the PRISMA criteria as well as a point of the difficulties of setting up screening following these trials.

RESULTS

Among five trials that published mortality results, only the US one, the National Lung Screening Trial (NLST) was showed a 20% decrease in lung cancer mortality in smokers screened by low-dose computed tomography compared to chest x-ray. However, besides the lack of power of the other trials, a great heterogeneity of the methods makes the synthesis of the results difficult. While many expert groups are in favor of testing, only the United States has implemented a screening program, whose adherence remains low.

CONCLUSION

Many persistent questions about the eligible population, the organization, the side effects, and finally the cost-benefit, need additional research around these issues.

Effects of probiotics on chemotherapy in patients with lung cancer

Chemotherapy damages the intestinal mucosa, causing adverse gastrointestinal reactions. Clostridium butyricum (C. butyricum) reduces the incidence of diarrhea in digestive diseases, including inflammatory bowel disease. Therefore, the aim of the present study was to investigate the role of C. butyricum in patients undergoing chemotherapy. A total of 41 participants with lung cancer were enrolled, and divided into the C. butyricum (CB) or placebo group using 1:1 randomization to obtain 20 CB and 21 placebo participants. On the first and last day of the 3-week intervention, blood and stool samples were collected and analyzed. To analyze stool flora, 16S ribosomal RNA sequencing was performed. The incidence of chemotherapy-induced diarrhea was lower in the CB group compared with the placebo group. The lymphocyte count and platelet/lymphocyte ratio (PLR) was markedly altered between the two groups. Neutrophil/lymphocyte ratio (NLR) and PLR decreased within the CB group. At week 3, the lymphocyte/monocyte ratio (LMR) was higher in the CB group compared with the placebo group. Alterations in lymphocyte subsets and immunoglobulin levels were not significantly different. Albumin (ALB) level and weight did not differ significantly between the two groups. At 3 weeks the total flora diversity did not decrease in either group. Phyla in the CB group varied slightly, while the proportion of Firmicutes in the placebo group decreased significantly. No statistically significant difference was observed between the two groups, though the genera producing short-chain fatty acids tended to increase, and the pathogenic genera tended to decrease in the CB group, which was almost the opposite of the observation in the placebo group. Operational taxonomy unit analysis revealed a notable increase in beneficial flora, including the Clostridium and Lactobacillus genera of the CB group, compared with the placebo group. The present study highlighted that C. butyricum reduced chemotherapy-induced diarrhea in patients with lung cancer, reduced the systemic inflammatory response system and encouraged homeostatic maintenance.

Delta radiomic features improve prediction for lung cancer incidence: A nested case-control analysis of the National Lung Screening Trial

Background

Current guidelines for lung cancer screening increased a positive scan threshold to a 6 mm longest diameter. We extracted radiomic features from baseline and follow‐up screens and performed size‐specific analyses to predict lung cancer incidence using three nodule size classes (<6 mm [small], 6‐16 mm [intermediate], and ≥16 mm [large]).

Methods

We extracted 219 features from baseline (T0) nodules and 219 delta features which are the change from T0 to first follow‐up (T1). Nodules were identified for 160 incidence cases diagnosed with lung cancer at T1 or second follow‐up screen (T2) and for 307 nodule‐positive controls that had three consecutive positive screens not diagnosed as lung cancer. The cases and controls were split into training and test cohorts; classifier models were used to identify the most predictive features.

Results

The final models revealed modest improvements for baseline and delta features when compared to only baseline features. The AUROCs for small‐ and intermediate‐sized nodules were 0.83 (95% CI 0.76‐0.90) and 0.76 (95% CI 0.71‐0.81) for baseline‐only radiomic features, respectively, and 0.84 (95% CI 0.77‐0.90) and 0.84 (95% CI 0.80‐0.88) for baseline and delta features, respectively. When intermediate and large nodules were combined, the AUROC for baseline‐only features was 0.80 (95% CI 0.76‐0.84) compared with 0.86 (95% CI 0.83‐0.89) for baseline and delta features.

Conclusions

We found modest improvements in predicting lung cancer incidence by combining baseline and delta radiomics. Radiomics could be used to improve current size‐based screening guidelines.

The prognostic effect of the epidermal growth factor receptor gene mutation on recurrence dynamics of lung adenocarcinoma

OBJECTIVES

The prognostic effects of epidermal growth factor receptor (EGFR) gene mutation on lung adenocarcinoma recurrence have not been well established. The relationship between EGFR gene mutation and recurrence dynamics of lung adenocarcinoma was investigated.

METHODS

A total of 527 patients with complete resection for adenocarcinoma were reviewed retrospectively. EGFR gene mutation was analysed by polymerase chain reaction followed by bidirectional direct sequencing in recurred patients. Patients were divided into the EGFR gene mutation group (M) or the wild-type EGFR gene group (W). Recurrence types and disease-free intervals (DFIs) of the 2 groups were compared. DFIs were calculated by the Kaplan-Meier method and compared using the log-rank test and Cox proportional hazard model.

RESULTS

EGFR gene sequencing was performed in 115 recurrent adenocarcinoma patients. Sixty-six patients had EGFR mutations and 49 patients had wild-type EGFR. The median DFI of the 2 groups were significantly different (M: 20.3 months, W: 15.1 months, P = 0.012). EGFR gene mutation was the only prognostic factor for DFI [hazard ratio (HR) = 0.639, 95% confidence interval (CI) = 0.428-0.954, P = 0.029]. The proportion of loco-regional recurrences and distant metastases of both groups were similar (P = 0.50). In subgroup analysis, EGFR gene mutation (HR = 0.534, 95% CI = 0.339-0.839, P = 0.007) was a significant prognostic factor for DFI of distant metastases.

CONCLUSIONS

Lung adenocarcinoma with EGFR gene mutations had longer DFI than those with wild-type EGFR gene, especially with regard to distant metastasis. EGFR gene mutation was a prognostic factor for lung adenocarcinoma.

Financial Analysis of Free Lung Cancer Screening Program Shows Profitability Using Broader NCCN Guidelines

BACKGROUND

Lung cancer screening with low-dose computed tomography (LDCT) chest scans in high-risk populations has been established as an effective measure of preventive medicine by the National Lung Screening Trial. However, the sustainability of funding a program is still controversial. We present a 2.5-year profitability analysis of our screening program by using the broader National Comprehensive Cancer Network criteria.

METHODS

Retrospective chart review was performed on the initial 2.5-year data set of a free LDCT chest scan program that targeted the underserved Southeastern United States. Patients were selected by the National Comprehensive Cancer Network high-risk criteria, screening twice as many patients compared with Centers for Medicare and Medicaid Services criteria. LDCT scans were performed during the off-service hours of our positron emission tomography CT scanner. Analysis of fiscal years 2015 to 2017 was done to evaluate indirect cost, direct cost, and adjusted net margin per case after factoring downstream revenue from positive scans and other findings.

RESULTS

A total of 705 scans were performed with 418 patients referred for subsequent procedures or specialist evaluations. The mean overhead cost over total cost was 42.3%. The adjusted net margin per case was -$212 in the first year but turned positive to $177 in the third fiscal year. The total break-even point of adjusted net margin was between 6% and 7% of indirect cost as a function of charges. Of the 60 new patients introduced to the hospital system, a gross margin per case of $211 was found.

CONCLUSIONS

Free lung cancer screening can demonstrate profitability from downstream revenue with a lag time of 2 years.

[China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2018 version)]

BACKGROUND

Lung cancer is the leading cause of cancer-related death in China. The results from a randomized controlled trial using annual low-dose computed tomography (LDCT) in specific high-risk groups demonstrated a 20% reduction in lung cancer mortality. The aim of tihs study is to establish the China National lung cancer screening guidelines for clinical practice.

METHODS

The China lung cancer early detection and treatment expert group (CLCEDTEG) established the China National Lung Cancer Screening Guideline with multidisciplinary representation including 4 thoracic surgeons, 4 thoracic radiologists, 2 medical oncologists, 2 pulmonologists, 2 pathologist, and 2 epidemiologist. Members have engaged in interdisciplinary collaborations regarding lung cancer screening and clinical care of patients with at risk for lung cancer. The expert group reviewed the literature, including screening trials in the United States and Europe and China, and discussed local best clinical practices in the China. A consensus-based guidelines, China National Lung Cancer Screening Guideline (CNLCSG), was recommended by CLCEDTEG appointed by the National Health and Family Planning Commission, based on results of the National Lung Screening Trial, systematic review of evidence related to LDCT screening, and protocol of lung cancer screening program conducted in rural China.

RESULTS

Annual lung cancer screening with LDCT is recommended for high risk individuals aged 50-74 years who have at least a 20 pack-year smoking history and who currently smoke or have quit within the past five years. Individualized decision making should be conducted before LDCT screening. LDCT screening also represents an opportunity to educate patients as to the health risks of smoking; thus, education should be integrated into the screening process in order to assist smoking cessation.

CONCLUSIONS

A lung cancer screening guideline is recommended for the high-risk population in China. Additional research , including LDCT combined with biomarkers, is needed to optimize the approach to low-dose CT screening in the future.

Randomized trial of a patient-centered decision aid for promoting informed decisions about lung cancer screening: Implementation of a PCORI study protocol and lessons learned

PURPOSE

We describe the methods, stakeholder engagement, and lessons learned from a study comparing a video decision aid to standard educational materials on lung cancer screening decisions.

METHODS

The study followed rigorous methodology standards from the Patient-Centered Outcomes Research Institute. The importance of patient-centeredness and patient/stakeholder engagement are reflected across the study's conceptualization, execution, interpretation, and dissemination efforts. Advisory groups of current and former smokers, quitline service providers, clinicians, and patient advocates were formed for the project. The study used both retrospective and prospective recruitment strategies. Randomization of patients occurred within state-based quitlines, with aggressive tracking of participants. We collected data at baseline and 1-week, 3-month and 6-months after receiving the intervention. The patient-centered outcomes included whether patients' receiving the decision aid a) felt better prepared to make a decision, b) felt more informed about the screening decision, c) had more clarity on their values regarding the benefits and harms of lung cancer screening, and d) were more knowledgeable about lung cancer screening than patients receiving the standard education materials. Exploratory outcomes included making an appointment with a health care provider to discuss screening, scheduling and completing lung cancer screening.

RESULTS

We have enrolled and randomized 516 quitline patients and learned many lessons about executing the trial based on significant patient and stakeholder engagement.

CONCLUSIONS

Conducting patient-centered outcomes research requires new ways of thinking and continuously checking-in with patients/stakeholders. The engagement of quitline service providers and patient advisors has been key to successful recruitment and dissemination planning. PCORI- CER-1306-03385 ClinicalTrials.gov NCT ID: NCT02286713.

Cancer screening in the United States, 2018: A review of current American Cancer Society guidelines and current issues in cancer screening

Each year, the American Cancer Society publishes a summary of its guidelines for early cancer detection, data and trends in cancer screening rates from the National Health Interview Survey, and select issues related to cancer screening. In this 2018 update, we also summarize the new American Cancer Society colorectal cancer screening guideline and include a clarification in the language of the 2013 lung cancer screening guideline. CA Cancer J Clin 2018;68:297-316. © 2018 American Cancer Society.

Patient and Clinician Perspectives on Shared Decision-making in Early Adopting Lung Cancer Screening Programs: a Qualitative Study

BACKGROUND

Guidelines recommend, and Medicare requires, shared decision-making between patients and clinicians before referring individuals at high risk of lung cancer for chest CT screening. However, little is known about the extent to which shared decision-making about lung cancer screening is achieved in real-world settings.

OBJECTIVE

To characterize patient and clinician impressions of early experiences with communication and decision-making about lung cancer screening and perceived barriers to achieving shared decision-making.

DESIGN

Qualitative study entailing semi-structured interviews and focus groups.

PARTICIPANTS

We enrolled 36 clinicians who refer patients for lung cancer screening and 49 patients who had undergone lung cancer screening in the prior year. Participants were recruited from lung cancer screening programs at four hospitals (three Veterans Health Administration, one urban safety net).

APPROACH

Using content analysis, we analyzed transcripts to characterize communication and decision-making about lung cancer screening. Our analysis focused on the recommended components of shared decision-making (information sharing, deliberation, and decision aid use) and barriers to achieving shared decision-making.

KEY RESULTS

Clinicians varied in the information shared with patients, and did not consistently incorporate decision aids. Clinicians believed they explained the rationale and gave some (often purposely limited) information about the trade-offs of lung cancer screening. By contrast, some patients reported receiving little information about screening or its trade-offs and did not realize the CT was intended as a screening test for lung cancer. Clinicians and patients alike did not perceive that significant deliberation typically occurred. Clinicians perceived insufficient time, competing priorities, difficulty accessing decision aids, limited patient comprehension, and anticipated patient emotions as barriers to realizing shared decision-making.

CONCLUSIONS

Due to multiple perceived barriers, patient-clinician conversations about lung cancer screening may fall short of guideline-recommended shared decision-making supported by a decision aid. Consequently, patients may be left uncertain about lung cancer screening's rationale, trade-offs, and process.

A single-center experience of 100 image-guided video-assisted thoracoscopic surgery procedures

Background

The advent of image-guided video-assisted thoracoscopic surgery (iVATS) has allowed the simultaneous localization and removal of small lung nodules. The aim of this study is to detail, in a retrospective review, one institution's experience using iVATS in this clinical setting, with a special attention to efficacy, safety, and procedural details.

Methods

This study was a retrospective analysis of prospectively collected data. Between October 2016 and January 2018, a total of 95 patients with 100 small lung nodules underwent iVATS. All procedures were performed in a hybrid operating room (HOR) in which a cone-beam computed tomography (CT) apparatus and a laser navigation system were present.

Results

The mean size of the 100 lung nodules was 7.94 mm, with their mean depth from the visceral pleura being 10 mm. A total of 98 nodules were successfully localized; of them, 94 were resected through a marker-guided procedure. There were four resection failures [wire dislodgement (n=2) or dye spillage (n=2)]). A significant inverse association was found between localization time (mean: 21.19 min) and the surgeon's experience (Pearson's r=-0.632; P<0.001). The mean length of hospital stay was 4.87 days and there were no perioperative deaths.

Conclusions

In the current context of an increase in early diagnosis of lung cancer by screening programs, iVATS performed in a HOR offers a safe and efficient option for simultaneous localization and removal of small pulmonary nodules.

Risk factors for disseminated intravascular coagulation in patients with lung cancer

BACKGROUND

The mortality rate from disseminated intravascular coagulation (DIC) is higher in patients with lung cancer than in non-lung cancer patients. Moreover, the prevalence of DIC varies among the pathologic types of lung cancer. This study analyzed the relationship between coagulation factors and the pathologic types of lung cancer.

METHODS

Twenty-six patients with progressive, inoperable stage IIB or higher lung cancer (20 men, 6 women; mean age 71 years; 11 Adeno, 10 squamous cell carcinoma, and 5 small cell carcinoma) and five healthy volunteers without respiratory disease (3 men, 2 women; mean age 72 years) were enrolled in the study. Blood samples were collected at lung cancer diagnosis, before treatment.

RESULTS

White blood cell count, platelet count, serum C-reactive protein, fibrin/fibrinogen degradation products, fibrinogen, thrombin-antithrombin complex, and D-dimer levels differed significantly between lung cancer patients and the control group, but not among the pathologic types of lung cancer. Thrombomodulin levels were significantly higher in patients with Adeno and squamous cell carcinoma than in those with small cell carcinoma (P < 0.05 and P < 0.01, respectively). Antithrombin levels were significantly lower in patients with squamous cell carcinoma than in those with Adeno (P < 0.05).

CONCLUSION

Coagulation disorders may develop secondary to chronic inflammation in patients with progressive lung cancer. DIC in lung cancer may be attributed to changes in anticoagulation factors, such as thrombomodulin and antithrombin, but not in other coagulation factors.