Accuracy of volatile urine biomarkers for the detection and characterization of lung cancer.

BACKGROUND: The mixture of volatile organic compounds in the headspace gas of urine may be able to distinguish lung cancer patients from relevant control populations. METHODS: Subjects with biopsy confirmed untreated lung cancer, and others at risk for developing lung cancer, provided a urine sample. A colorimetric sensor array was exposed to the headspace gas of neat and pre-treated urine samples. Random forest models were trained from the sensor output of 70% of the study subjects and were tested against the remaining 30%. Models were developed to separate cancer and cancer subgroups from control, and to characterize the cancer. An additional model was developed on the largest clinical subgroup. RESULTS: 90 subjects with lung cancer and 55 control subjects participated. The accuracies, reported as C-statistics, for models of cancer or cancer subgroups vs. control ranged from 0.795 - 0.917. A model of lung cancer vs. control built using only subjects from the largest available clinical subgroup (30 subjects) had a C-statistic of 0.970. Models developed and tested to characterize cancer histology, and to compare early to late stage cancer, had C-statistics of 0.849 and 0.922 respectively. CONCLUSIONS: The colorimetric sensor array signature of volatile organic compounds in the urine headspace may be capable of distinguishing lung cancer patients from clinically relevant controls. The incorporation of clinical phenotypes into the development of this biomarker may optimize its accuracy.

Preoperative evaluation of the patient with lung cancer being considered for lung resection.

PURPOSE OF REVIEW: This review summarizes the general approach to evaluating the cardiopulmonary fitness of a patient with lung cancer being considered for lung resection. Many patients have a high risk for morbidity and mortality from lung resection owing to severe comorbidities or low cardiopulmonary reserve. A comprehensive and individualized assessment is essential to identify the factors that may impact operative outcome. RECENT FINDINGS: Identification of comorbid conditions related to cigarette smoking, particularly cardiovascular diseases, is essential because they need to be managed in advance. In those with low predicted postoperative forced expiratory volume during first second (FEV(1)) or carbon monoxide diffusing capacity (DL(CO)), or impaired performance on a low-technology exercise test, cardiopulmonary exercise testing should be considered. SUMMARY: Preoperative assessment requires an understanding of the relative benefits and harms of available treatment options and consideration of patients' values. A balance between the potential to cure one's cancer and the short-term and long-term risks of the selected treatment needs to be reached. All patients should have a baseline FEV(1) and DL(CO) measured, and predicted postoperative FEV(1) and DL(CO) calculated to assist with risk prediction. Measures of exercise performance can help to further risk stratify patients. Means of modifying the risks should be considered for all patients.

Lung Cancer Screening.

Lung cancer screening with low-dose computed tomography (LDCT) reduces lung cancer deaths by early detection. The United States Preventive Services Task Force recommends lung cancer screening with LDCT in adults of age 50 years to 80 years who have at least a 20 pack-year smoking history and are currently smoking or have quit within the past 15 years. The implementation of a lung-cancer-screening program is complex. High-quality screening requires the involvement of a multidisciplinary team. The aim of a screening program is to find balance between mortality reduction and avoiding potential harms related to false-positive findings, overdiagnosis, invasive procedures, and radiation exposure. Components and processes of a high-quality lung-cancer-screening program include the identification of eligible individuals, shared decision-making, performing and reporting LDCT results, management of screen-detected lung nodules and non-nodule findings, smoking cessation, ensuring adherence, data collection, and quality improvement.

The current state of tobacco cessation treatment.

Nicotine addiction and dependence is a chronic relapsing disease driven by addiction to nicotine. Proactive treatment for all tobacco users, regardless of their readiness to quit, is recommended. First-line tobacco cessation medications include nicotine replacement therapy, bupropion, and varenicline. Comprehensive treatment with behavioral interventions and pharmacologic therapy increases success rates of smoking cessation. Although there are many popular alternative treatments, they should not replace or delay the use of known effective therapies.

Preoperative Pulmonary Risk Assessment.

Postoperative pulmonary complications have a significant impact on perioperative morbidity and mortality and contribute substantially to health care costs. Surgical stress and anesthesia lead to changes in respiratory physiology, altering lung volumes, respiratory drive, and muscle function that can cumulatively increase the risk of postoperative pulmonary complications. Preoperative medical evaluation requires a structured approach to identify patient-, procedure-, and anesthesia-related risk factors for postoperative pulmonary complications. Validated risk prediction models can be used for risk stratification and to help tailor the preoperative investigation. Optimization of pulmonary comorbidities, smoking cessation, and correction of anemia are risk-mitigation strategies. Lung-protective ventilation, moderate PEEP application, and conservative use of neuromuscular blocking drugs are intra-operative preventive strategies. Postoperative early mobilization, chest physiotherapy, oral care, and appropriate analgesia speed up recovery. High-risk patients should receive inspiratory muscle training prior to surgery, and there should be a focus to minimize surgery time.

Electronic Cigarettes and Alternative Methods of Vaping.

Vaping, the inhalation of heated aerosols, received widespread attention during the outbreak of electronic-cigarette (e-cigarette) or vaping-associated acute lung injury cases in 2019. E-cigarette use is now widely recognized as a potential cause of acute lung injury. Vaping is often perceived by physicians as referring exclusively to the use of e-cigarette devices. However, inhalation of nicotine or tetrahydrocannabinol-containing aerosol through alternate methods such as "dabbing" and "dripping" are increasingly common. However, the health impact of these alternate methods remains poorly understood. The use of alternate methods and devices may go unrecognized because of lack of clinician familiarity with them. In this review, we discuss e-cigarettes devices, electronic-liquid components, the expanded spectrum of methods used to consume aerosolized substances, and the potential for lung injury.

A prognostic and predictive computational pathology image signature for added benefit of adjuvant chemotherapy in early stage non-small-cell lung cancer.

BACKGROUND: We developed and validated a prognostic and predictive computational pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage non-small cell lung cancer (ES-NSCLC). METHODS: 1330 patients with ES-NSCLC were acquired from 3 independent sources and divided into four cohorts D1-4. D1 comprised 100 surgery treated patients and was used to identify prognostic features via an elastic-net Cox model to predict overall and disease-free survival. CoRiS was constructed using the Cox model coefficients for the top features. The prognostic performance of CoRiS was evaluated on D2 (N=331), D3 (N=657) and D4 (N=242). Patients from D2 and D3 which comprised surgery + chemotherapy were used to validate CoRiS as predictive of added benefit to adjuvant chemotherapy (ACT) by comparing survival between different CoRiS defined risk groups. FINDINGS: CoRiS was found to be prognostic on univariable analysis, D2 (hazard ratio (HR) = 1.41, adjusted (adj.) P = .01) and D3 (HR = 1.35, adj. P < .001). Multivariable analysis showed CoRiS was independently prognostic, D2 (HR = 1.41, adj. P < .001) and D3 (HR = 1.35, adj. P < .001), after adjusting for clinico-pathologic factors. CoRiS was also able to identify high-risk patients who derived survival benefit from ACT D2 (HR = 0.42, adj. P = .006) and D3 (HR = 0.46, adj. P = .08). INTERPRETATION: CoRiS is a tissue non-destructive, quantitative and low-cost tool that could potentially help guide management of ES-NSCLC patients. FUNDING: Data collection, anlaysis, and computation resources of the research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers: 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01 CA216579-01A1, R01 CA220581-01A1, 1U01 CA239055-01. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award (W81XWH-15-1-0558), the DOD Lung Cancer Investigator-Initiated Translational Research Award (W81XWH-18-1-0440), the DOD Peer Reviewed Cancer Research Program (W81XWH-16-1-0329), the Ohio Third Frontier Technology Validation Fund, the Wallace H. Coulter Foundation Program in the Department of Biomedical Engineering and the Clinical and Translational Science Award Program (CTSA) at Case Western Reserve University.

Predicting Lymph Node Metastasis in Non-small Cell Lung Cancer: Prospective External and Temporal Validation of the HAL and HOMER Models.

BACKGROUND: Two models, the Help with the Assessment of Adenopathy in Lung cancer (HAL) and Help with Oncologic Mediastinal Evaluation for Radiation (HOMER), were recently developed to estimate the probability of nodal disease in patients with non-small cell lung cancer (NSCLC) as determined by endobronchial ultrasound-transbronchial needle aspiration (EBUS-TBNA). The objective of this study was to prospectively externally validate both models at multiple centers. RESEARCH QUESTION: Are the HAL and HOMER models valid across multiple centers? STUDY DESIGN AND METHODS: This multicenter prospective observational cohort study enrolled consecutive patients with PET-CT clinical-radiographic stages T1-3, N0-3, M0 NSCLC undergoing EBUS-TBNA staging. HOMER was used to predict the probability of N0 vs N1 vs N2 or N3 (N2|3) disease, and HAL was used to predict the probability of N2|3 (vs N0 or N1) disease. Model discrimination was assessed using the area under the receiver operating characteristics curve (ROC-AUC), and calibration was assessed using the Brier score, calibration plots, and the Hosmer-Lemeshow test. RESULTS: Thirteen centers enrolled 1,799 patients. HAL and HOMER demonstrated good discrimination: HAL ROC-AUC = 0.873 (95%CI, 0.856-0.891) and HOMER ROC-AUC = 0.837 (95%CI, 0.814-0.859) for predicting N1 disease or higher (N1|2|3) and 0.876 (95%CI, 0.855-0.897) for predicting N2|3 disease. Brier scores were 0.117 and 0.349, respectively. Calibration plots demonstrated good calibration for both models. For HAL, the difference between forecast and observed probability of N2|3 disease was +0.012; for HOMER, the difference for N1|2|3 was -0.018 and for N2|3 was +0.002. The Hosmer-Lemeshow test was significant for both models (P = .034 and .002), indicating a small but statistically significant calibration error. INTERPRETATION: HAL and HOMER demonstrated good discrimination and calibration in multiple centers. Although calibration error was present, the magnitude of the error is small, such that the models are informative.

Vaping-related pulmonary granulomatous disease.

The use of electronic cigarettes, or "vaping," has garnered significant popularity and attention in recent years. Its pulmonary and systemic effects have yet to be fully studied and quantified, and recent reports of vaping-related illnesses and deaths have brought the clinical consequences of vaping into the public spotlight. This report describes the case of a 34 year old woman who presented to clinic with new-onset cough and dyspnea, shortly after beginning to use electronic cigarettes. Imaging demonstrated new micronodular opacities and mediastinal lymphadenopathy, while pathology confirmed granulomatous disease. After she received counseling and successfully quit vaping, her symptoms resolved and repeat imaging demonstrated resolution of parenchymal findings and lymphadenopathy. This case report therefore presents a longitudinal narrative of reversible vaping-related pulmonary granulomatous disease.

Lung Cancer Screening.

Lung cancer is the leading cause of US cancer-related deaths. Lung cancer screening with a low radiation dose chest computed tomography scan is now standard of care for a high-risk eligible population. It is imperative for clinicians and surgeons to evaluate the trade-offs of benefits and harms, including the identification of many benign lung nodules, overdiagnosis, and complications. Integration of smoking cessation interventions augments the clinical benefits of screening. Screening programs must develop strategies to manage screening-detected findings to minimize potential harms. Further research should focus on how to improve patient selection, minimize harms, and facilitate access to screening.

Radiologic Review With Pathology Correlation of E-Cigarette or Vaping Product Use-associated Lung Injury.

More than 2000 cases of vaping-associated lung injury have been reported in a recent outbreak, including >40 deaths. Although chest imaging is integral in the evaluation of these patients and is often abnormal, the spectrum of findings and the role of imaging in the diagnosis are not widely appreciated. The aim of this review is to highlight the imaging findings of vaping-associated lung injury. Basilar-predominant ground-glass opacities and/or consolidations, often with areas of subpleural or lobular sparing, are the most common pattern, and many other patterns are known to occur. Radiologists are encouraged to become familiar with the different imaging patterns of vaping-associated lung injury. The diagnosis should be considered in patients who have vaped within 90 days of onset of symptoms and present with bilateral lung opacities.

e-Cigarette or Vaping Product Use-Associated Lung Injury: Clinical, Radiologic, and Pathologic Findings of 15 Cases.

Since mid-2019, > 2,000 cases of e-cigarette or vaping product use-associated lung injury (EVALI) have been reported. Although initial reports suggested that this entity may be a form of inhalation-related lipoid pneumonia, subsequent studies indicate that EVALI represents various patterns of acute lung injury. Cases of EVALI continue to be reported, and public awareness of the epidemic is increasingly high. However, evidence surrounding optimal management of EVALI remains limited. In this case series, we report 15 cases of EVALI across a spectrum of severity, highlighting key radiologic, pathologic, and cytologic findings, and discuss management implications. In line with national findings, most patients with EVALI in the series vaped liquids containing tetrahydrocannabinol. Our imaging and pathologic findings support the notion that EVALI is a form of acute lung injury.

Lung Biopsy Findings in Severe Pulmonary Illness Associated With E-Cigarette Use (Vaping).

OBJECTIVES: The aim of this report is to describe the lung biopsy findings in vaping-associated pulmonary illness. METHODS: Lung biopsies from eight patients with vaping-associated pulmonary illness were reviewed. RESULTS: The biopsies were from eight men (aged 19-61 years) with respiratory symptoms following e-cigarette use (vaping). Workup for infection was negative in all cases, and there was no evidence for other etiologies. Imaging showed diffuse bilateral ground-glass opacities in all patients. Most recovered with corticosteroid therapy, while one died. Lung biopsies (seven transbronchial, one surgical) showed acute lung injury, including organizing pneumonia and/or diffuse alveolar damage. Common features were fibroblast plugs, hyaline membranes, fibrinous exudates, type 2 pneumocyte hyperplasia, and interstitial organization. Some cases featured a sparse interstitial chronic inflammatory infiltrate. Although macrophages were present within the airspaces in all cases, this feature was not prominent, and findings typical of exogenous lipoid pneumonia were absent. CONCLUSIONS: The histopathology of acute pulmonary illness related to e-cigarette use (vaping) is characterized by acute lung injury patterns, supporting the contention that vaping can cause severe lung damage.

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in Stage I, II resectable Non-Small Cell Lung Cancer: a retrospective multi-cohort study for outcome prediction.

Background: Development and validation of a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (ES-NSCLC) that is prognostic of disease-free survival (DFS) and predictive of the added benefit of adjuvant chemotherapy (ACT) following surgery. Methods: QuRiS was developed using radiomic texture features derived from within and outside the primary lung nodule on chest CT scans using a cohort D1 of 329 patients from the Cleveland Clinic. A LASSO-Cox regularization model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on D2(N=114; University of Pennsylvania) and D3(N=82; TCIA). QuRNom was constructed by integrating QuRiS with T-, N-Descriptors, and LVI. The added benefit of ACT using QuRiS and QuRNom was validated by comparing patients who received ACT against patients who underwent surgery alone in D1-D3. To explore the underlying morphologic basis of the QuRiS, we explored associations with corresponding whole-slide tissue scans (WSIs) and mRNA sequencing data using subsets of D1 and D3. Findings: QuRiS consisted three intra- and ten peri-tumoral CT-radiomic features and was found to be significantly associated with DFS (D1: HR=1.60 [1.10-2.20];p<·05; D2:HR=2.70 [1.40-5.10]; p<·01; D3:HR=2.70 [1.20-5.70];p<·01). Patients were partitioned into three risk groups (QH, QI, QL) based off their corresponding QuRiS score. High QuRiS group, QH, patients were observed to have significantly prolonged survival with ACT when compared to surgery alone (D1: HR=0·27[0.07-0.95],p<0.05; D2+D3: HR=0·08[0.01-0.42],p<0.01). For developed QuRNom, the actual efficacy of ACT was predictive of nomogram-estimated survival benefit (D1: HR= D1:0·25 [0·12-0·55], D3: HR=0·13 [0·004-0·99]). QuRiS features were found to be associated with the spatial arrangement of TILs and cancer nuclei on corresponding WSIs (D1: Rho=0·23,p<0·05, N=70). They were also observed to have an association with biological pathways implicated in chemotaxis (D3,p<0·05, N=86) and other immune specific biological pathways. Interpretation: QuRiS and QuRNom were validated as being prognostic of DFS and predictive of the added benefit of ACT.

CT derived radiomic score for predicting the added benefit of adjuvant chemotherapy following surgery in stage I, II resectable non-small cell lung cancer: a retrospective multicohort study for outcome prediction.

BACKGROUND: Use of adjuvant chemotherapy in patients with early-stage lung cancer is controversial because no definite biomarker exists to identify patients who would receive added benefit from it. We aimed to develop and validate a quantitative radiomic risk score (QuRiS) and associated nomogram (QuRNom) for early-stage non-small cell lung cancer (NSCLC) that is prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy following surgery. METHODS: We did a retrospective multicohort study of individuals with early-stage NSCLC (stage I and II) who either received surgery alone or surgery plus adjuvant chemotherapy. We selected patients for whom we had available pre-treatment diagnostic CT scans and corresponding survival information. We used radiomic texture features derived from within and outside the primary lung nodule on chest CT scans of patients from the Cleveland Clinic Foundation (Cleveland, OH, USA; cohort D1) to develop QuRiS. A least absolute shrinkage and selection operator-Cox regularisation model was used for data dimension reduction, feature selection, and QuRiS construction. QuRiS was independently validated on a cohort of patients from the University of Pennsylvania (Philadephia, PA, USA; cohort D2) and a cohort of patients whose CT scans were derived from The Cancer Imaging Archive (cohort D3). QuRNom was constructed by integrating QuRiS with tumour and node descriptors (according to the tumour, node, metastasis staging system) and lymphovascular invasion. The primary endpoint of the study was the assessment of the performance of QuRiS and QuRNom in predicting disease-free survival. The added benefit of adjuvant chemotherapy estimated using QuRiS and QuRNom was validated by comparing patients who received adjuvant chemotherapy versus patients who underwent surgery alone in cohorts D1-D3. FINDINGS: We included: 329 patients in cohort D1 (73 [22%] had surgery plus adjuvant chemotherapy and 256 (78%) had surgery alone); 114 patients in cohort D2 (33 [29%] had surgery plus adjuvant chemotherapy and 81 (71%) had surgery alone); and 82 patients in cohort D3 (24 [29%] had surgery plus adjuvant chemotherapy and 58 (71%) had surgery alone). QuRiS comprised three intratumoral and 10 peritumoral CT-radiomic features and was found to be significantly associated with disease-free survival (ie, prognostic validation of QuRiS; hazard ratio for predicted high-risk vs predicted low-risk groups 1·56, 95% CI 1·08-2·23, p=0·016 for cohort D1; 2·66, 1·24-5·68, p=0·011 for cohort D2; and 2·67, 1·39-5·11, p=0·0029 for cohort D3). To validate the predictive performance of QuRiS, patients were partitioned into three risk groups (high, intermediate, and low risk) on the basis of their corresponding QuRiS. Patients in the high-risk group were observed to have significantly longer survival with adjuvant chemotherapy than patients who underwent surgery alone (0·27, 0·08-0·95, p=0·042, for cohort D1; 0·08, 0·01-0·42, p=0·0029, for cohorts D2 and D3 combined). As concerns QuRNom, the nomogram-estimated survival benefit was predictive of the actual efficacy of adjuvant chemotherapy (0·25, 0·12-0·55, p<0·0001, for cohort D1; 0·13, <0·01-0·99, p=0·0019 for cohort D3). INTERPRETATION: QuRiS and QuRNom were validated as being prognostic of disease-free survival and predictive of the added benefit of adjuvant chemotherapy, especially in clinically defined low-risk groups. Since QuRiS is based on routine chest CT imaging, with additional multisite independent validation it could potentially be employed for decision management in non-invasive treatment of resectable lung cancer. FUNDING: National Cancer Institute of the US National Institutes of Health, National Center for Research Resources, US Department of Veterans Affairs Biomedical Laboratory Research and Development Service, Department of Defence, National Institute of Diabetes and Digestive and Kidney Diseases, Wallace H Coulter Foundation, Case Western Reserve University, and Dana Foundation.

A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study.

Background: Intratumoural heterogeneity has been previously shown to be related to clonal evolution and genetic instability and associated with tumour progression. Phenotypically, it is reflected in the diversity of appearance and morphology within cell populations. Computer-extracted features relating to tumour cellular diversity on routine tissue images might correlate with outcome. This study investigated the prognostic ability of computer-extracted features of tumour cellular diversity (CellDiv) from haematoxylin and eosin (H&E)-stained histology images of non-small cell lung carcinomas (NSCLCs). Methods: In this multicentre, retrospective study, we included 1057 patients with early-stage NSCLC with corresponding diagnostic histology slides and overall survival information from four different centres. CellDiv features quantifying local cellular morphological diversity from H&E-stained histology images were extracted from the tumour epithelium region. A Cox proportional hazards model based on CellDiv was used to construct risk scores for lung adenocarcinoma (LUAD; 270 patients) and lung squamous cell carcinoma (LUSC; 216 patients) separately using data from two of the cohorts, and was validated in the two remaining independent cohorts (comprising 236 patients with LUAD and 335 patients with LUSC). We used multivariable Cox regression analysis to examine the predictive ability of CellDiv features for 5-year overall survival, controlling for the effects of clinical and pathological parameters. We did a gene set enrichment and Gene Ontology analysis on 405 patients to identify associations with differentially expressed biological pathways implicated in lung cancer pathogenesis. Findings: For prognosis of patients with early-stage LUSC, the CellDiv LUSC model included 11 discriminative CellDiv features, whereas for patients with early-stage LUAD, the model included 23 features. In the independent validation cohorts, patients predicted to be at a higher risk by the univariable CellDiv model had significantly worse 5-year overall survival (hazard ratio 1·48 [95% CI 1·06-2·08]; p=0·022 for The Cancer Genome Atlas [TCGA] LUSC group, 2·24 [1·04-4·80]; p=0·039 for the University of Bern LUSC group, and 1·62 [1·15-2·30]; p=0·0058 for the TCGA LUAD group). The identified CellDiv features were also found to be strongly associated with apoptotic signalling and cell differentiation pathways. Interpretation: CellDiv features were strongly prognostic of 5-year overall survival in patients with early-stage NSCLC and also associated with apoptotic signalling and cell differentiation pathways. The CellDiv-based risk stratification model could potentially help to determine which patients with early-stage NSCLC might receive added benefit from adjuvant therapy. Funding: National Institue of Health and US Department of Defense.

Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study.

OBJECTIVES: To evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT). MATERIALS AND METHODS: CT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D1) and validation set (D2). 80 patients from The Cancer Genome Atlas Lung Adenocarcinoma and Squamous Cell Carcinoma and 195 patients from The Cancer Imaging Archive, were used as independent second (D3) and third (D4) validation sets. A linear discriminant analysis (LDA) classifier was built based on the most stable and discriminate features. In addition, a radiomic risk score (RRS) was generated by using least absolute shrinkage and selection operator, Cox regression model to predict time to progression (TTP) following surgery. RESULTS: A feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D2, AUC of 0.75 vs. 0.65; D3, 0.74 vs. 0.62; D4, 0.76 vs. 0.63). The RRS generated by most stable-discriminating features was significantly associated with TTP compared to discriminating alone criteria (HR = 1.66, C-index of 0.72 vs. HR = 1.04, C-index of 0.62). CONCLUSION: Accounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage NSCLC.

Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic: CHEST Expert Panel Report.

Background: The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. Materials and Methods: An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. Results: Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non-small cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non-small cell lung cancer. Conclusion: There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.© 2020 RSNA; The American College of Chest Physicians, published by Elsevier Inc; and The American College of Radiology, published by Elsevier Inc.

Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic: CHEST Expert Panel Report.

BACKGROUND: The risks from potential exposure to coronavirus disease 2019 (COVID-19), and resource reallocation that has occurred to combat the pandemic, have altered the balance of benefits and harms that informed current (pre-COVID-19) guideline recommendations for lung cancer screening and lung nodule evaluation. Consensus statements were developed to guide clinicians managing lung cancer screening programs and patients with lung nodules during the COVID-19 pandemic. METHODS: An expert panel of 24 members, including pulmonologists (n = 17), thoracic radiologists (n = 5), and thoracic surgeons (n = 2), was formed. The panel was provided with an overview of current evidence, summarized by recent guidelines related to lung cancer screening and lung nodule evaluation. The panel was convened by video teleconference to discuss and then vote on statements related to 12 common clinical scenarios. A predefined threshold of 70% of panel members voting agree or strongly agree was used to determine if there was a consensus for each statement. Items that may influence decisions were listed as notes to be considered for each scenario. RESULTS: Twelve statements related to baseline and annual lung cancer screening (n = 2), surveillance of a previously detected lung nodule (n = 5), evaluation of intermediate and high-risk lung nodules (n = 4), and management of clinical stage I non-small cell lung cancer (n = 1) were developed and modified. All 12 statements were confirmed as consensus statements according to the voting results. The consensus statements provide guidance about situations in which it was believed to be appropriate to delay screening, defer surveillance imaging of lung nodules, and minimize nonurgent interventions during the evaluation of lung nodules and stage I non-small cell lung cancer. CONCLUSIONS: There was consensus that during the COVID-19 pandemic, it is appropriate to defer enrollment in lung cancer screening and modify the evaluation of lung nodules due to the added risks from potential exposure and the need for resource reallocation. There are multiple local, regional, and patient-related factors that should be considered when applying these statements to individual patient care.