Management Of Lung Cancer Patients Research Articles

Food, Nutrition, Physical Activity and Microbiota: Which Impact on Lung Cancer?

Lung cancer still represents the leading cause of cancer-related death, globally. Likewise, malnutrition and inactivity represent a major risk for loss of functional pulmonary capacities influencing overall lung cancer severity. Therefore, the adhesion to an appropriate health lifestyle is crucial in the management of lung cancer patients despite the subtype of cancer. This review aims to summarize the available knowledge about dietary approaches as well as physical activity as the major factors that decrease the risk towards lung cancer, and improve the response to therapies. We discuss the most significant dietary schemes positively associated to body composition and prognosis of lung cancer and the main molecular processes regulated by specific diet schemes, functional foods and physical activity, i.e., inflammation and oxidative stress. Finally, we report evidence demonstrating that dysbiosis of lung and/or gut microbiome, as well as their interconnection (the gut–lung axis), are strictly related to dietary patterns and regular physical activity playing a key role in lung cancer formation and progression, opening to the avenue of modulating the microbiome as coadjuvant therapy. Altogether, the evidence reported in this review highlights the necessity to consider non-pharmacological interventions (nutrition and physical activity) as effective adjunctive strategies in the management of lung cancer.

Association Rules of Comorbidities in Patients Hospitalized for Lung Cancer

Objectives: The purpose of this study is to find out how the accompanying diseases of lung cancer patients are related. Through this, we aim to provide implications for the management of lung cancer patients and the national cancer policy. Methods: The subjects of this study were the Korean National Hospital Discharge in-depth Injury Survey, which was surveyed from 2006 to 2016, and among them, patients with lung cancer were selected. The major variable, comorbidities, were grouped based on the middle classification of the KCD-7 revision. The general characteristics were analyzed by frequency, and χ2-test was performed to test the difference in the distribution for the presence of comorbidity. In order to analyze the association rules of comorbidities, the support, confidence, and improvement of the association rules were presented and visualized using the arules package and apriori algorithm of the R program. Results: As a result of the analysis, the proportion of patients with comorbid diseases out of 21,882 discharged patients was 82.86%, and an average of 2.48±2.19 comorbidities was diagnosed. As a result of applying the association rules criteria of support (>0.01), confidence (>0.1), and lift (>1), 33 comorbidity patterns were found. The high association rules were “hypertensive diseases (I10-I15)” and “malignant neoplasms of ill-defined, secondary and unspecified sites (C76-C80)”, “diabetes mellitus (E10-E14)” and “hypertensive diseases (I10-I15)”, “malignant neoplasms of ill-defined, secondary and unspecified sites (C76-C80)” and “diabetes mellitus (E10-E14)”, “influenza and pneumonia (J09-J18)” and “hypertensive diseases (I10-I15)”, and so on. Conclusions: This study provides the rules related to comorbidities of lung cancer patients in Korean. It is used for the diagnosis and treatment of lung cancer patients, and it provides implications for effectively improving cancer policy. Future research on the effect on medical use or treatment results is needed, focusing on major comorbidities.

Lung Cancer, Covid-19 Infections and Chemotherapy.

The Covid-19 epidemic has severely strained health care systems across the globe. The impacts are multiple especially for patients cared for cancer. The Covid-19 epidemic has several impacts on the management of lung cancer patients. The aim of this work was to summarize the available epidemiological data on patients diagnosed with lung cancer infected with Covid-19 and describe the different strategies to improve the management of these patients by summarizing the recommendations in this area. The Teravolt cohort is an observational multicenter registry, including patients with non-small cell cancer, small cell cancer or mesothelioma but also epithelial tumors and a diagnosis of Covid-19. The Theravolt registry indicates an unexpectedly high mortality rate in patients with thoracic malignancies with COVID-19. Between March 26 and April 12, 2020, 200 patients treated in 8 countries were included. They had a performance status (PS) of 0-1 in 72% of cases, were smokers or ex-smokers in 81% of cases, had non-small cell cancer (76% of cases), were under treatment in 74% of cases, and the majority were first-line cases (57%). The hospitalization rate was 76% and the mortality rate 33%; only 10% of patients with criteria for intensive care hospitalization were admitted to the intensive care. Data presented in this registry suggest a high mortality in patients with thoracic cancer and Covid-19. Therofere, the importance to create a safe healthcare system during Covid-19 pandemic is underlined along with the need for essential effective clinical service delivery to patients with lung cancer.

Narrative review of lung cancer treatment at the time of COVID-19 pandemia: pitfall and issues.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for coronavirus disease 2019 (COVID-19) pandemic, has caused disruption in cancer care and research, changing daily management approach of cancer patients, above all for those affected by lung cancer disease. Unfortunately, its length and severity beyond today is still uncertain. This emerged viral pandemic has produced severe illness to overwhelm healthcare infrastructure, with worse impact on public health system and on providers of essential community services, and needing to ration medical equipment and interventions. Several data from across the world highlighted the susceptibility of patients affected by tumors to high severe infection and mortality from COVID-19. Lung cancer patients emerged as “frail” subgroup, mainly attributable to their immunosuppression, co-existing medical conditions and underlying pulmonary compromise. So, the lung cancer care was confounded by urgent need for intervention for most patients and the competing risk of life-threatening COVID-19 infection, and also influenced by competing needs for personnel, beds and equipment for urgent COVID-19 care. Clearly, no one model of care is possible during all pandemic phases or in all medical environments. In this review we will discuss on available data and their impact on prioritizing the individual management for lung cancer patients, with aim to protect them from COVID-19.

Challenges in Advanced Lung Cancer Diagnosis During the COVID-19 Pandemic.

A pandemic of coronavirus diseases 2019 (COVID-19) outbreak is a major public health emergency that has spread in the fastest speed, and caused the most extensive infection world widely. Transbronchial biopsy (TBB) and computed tomography guided percutaneous needle biopsy (CTPNB) is the most common and significant method for the diagnosis of lung cancer. During the COVID-19 pandemic, the indications of TBB and CTPNB must be managed strictly. Therefore, it is extremely indispensable to perform meticulous and individualized management for lung cancer patients to protect the patients from COVID-19.

Image-guided EBUS bronchoscopy system for lung-cancer staging.

The staging of the central-chest lymph nodes is a major step in the management of lung-cancer patients. For this purpose, the physician uses a device that integrates videobronchoscopy and an endobronchial ultrasound (EBUS) probe. To biopsy a lymph node, the physician first uses videobronchoscopy to navigate through the airways and then invokes EBUS to localize and biopsy the node. Unfortunately, this process proves difficult for many physicians, with the choice of biopsy site found by trial and error. We present a complete image-guided EBUS bronchoscopy system tailored to lymph-node staging. The system accepts a patient’s 3D chest CT scan, an optional PET scan, and the EBUS bronchoscope’s video sources as inputs. System workflow follows two phases: (1) procedure planning and (2) image-guided EBUS bronchoscopy. Procedure planning derives airway guidance routes that facilitate optimal EBUS scanning and nodal biopsy. During the live procedure, the system’s graphical display suggests a series of device maneuvers to perform and provides multimodal visual cues for locating suitable biopsy sites. To this end, the system exploits data fusion to drive a multimodal virtual bronchoscope and other visualization tools that lead the physician through the process of device navigation and localization. A retrospective lung-cancer patient study and follow-on prospective patient study, performed within the standard clinical workflow, demonstrate the system’s feasibility and functionality. For the prospective study, 60/60 selected lymph nodes (100%) were correctly localized using the system, and 30/33 biopsied nodes (91%) gave adequate tissue samples. Also, the mean procedure time including all user interactions was 6 min 43 s All of these measures improve upon benchmarks reported for other state-of-the-art systems and current practice. Overall, the system enabled safe, efficient EBUS-based localization and biopsy of lymph nodes.

Infections and Immunotherapy in Lung Cancer: A Bad Relationship?

Infectious diseases represent a relevant issue in lung cancer patients. Bacterial and viral infections might influence the patients’ prognosis, both directly affecting the immune system and indirectly impairing the outcome of anticancer treatments, mainly immunotherapy. In this analysis, we aimed to review the current evidence in order to clarify the complex correlation between infections and lung cancer. In detail, we mainly explored the potential impact on immunotherapy outcome/safety of (1) bacterial infections, with a detailed focus on antibiotics; and (2) viral infections, discriminating among (a) human immune-deficiency virus (HIV), (b) hepatitis B/C virus (HBV-HCV), and (c) Sars-Cov-2. A series of studies suggested the prognostic impact of antibiotic therapy administration, timing, and exposure ratio in patients treated with immune checkpoint inhibitors, probably through an antibiotic-related microbiota dysbiosis. Although cancer patients with HIV, HBV, and HCV were usually excluded from clinical trials evaluating immunotherapy, some retrospective and prospective trials performed in these patient subgroups reported similar results compared to those described in not-infected patients, with a favorable safety profile. Moreover, patients with thoracic cancers are particularly at risk of COVID-19 severe outcomes and mortality. Few reports speculated about the prognostic implications of anticancer therapy, including immunotherapy, in lung cancer patients with concomitant Sars-Cov-2 infection, showing, to date, inconsistent results. The correlation between infectious diseases and immunotherapy remains to be further explored and clarified in the context of dedicated trials. In clinical practice, the accurate and prompt multidisciplinary management of lung cancer patients with infections should be encouraged in order to select the best treatment options for these patients, avoiding unexpected toxicities, while maintaining the anticancer effect.

Dealing with lung cancer in the COVID-19 scenario (A review).

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused the coronavirus disease 2019 (COVID-19), first appeared in December 2019 in Wuhan (China) and quickly spread worldwide and has since been assigned a pandemic status. This affected the worlds' social interactions, including within medical practices, thus interfering with routine treatments for a variety of diseases including cancer. Different studies have addressed the fact that patients with cancer are often immunocompromised, making them more susceptible to infections. Since COVID-19 frequently causes respiratory distress, patients with lung cancer are considered to be a high-risk group. Genes that have been indicated to mediate viral entry into host cells such as angiotensin-converting enzyme 2 and transmembrane protease serine 2 are expressed in the lung tissue, a fact that could partially explain COVID-19 pathogenesis and lung involvement. Therefore, the current study offers a disease overview including molecular aspects behind the infection and provide a perspective on already published Chinese data plus recommendations for the management of lung cancer patients according to the two main lung cancer types and stages: non-small cell lung cancer and small cell lung cancer. This review aimed to add to the collective effort of selecting the most appropriate guidelines to follow for the treatment of these patients.

The Role of the Liquid Biopsy in Decision-Making for Patients with Non-Small Cell Lung Cancer.

Liquid biopsy is a rapidly emerging tool of precision oncology enabling minimally invasive molecular diagnostics and longitudinal monitoring of treatment response. For the clinical management of advanced stage lung cancer patients, detection and quantification of circulating tumor DNA (ctDNA) is now widely adopted into clinical practice. Still, interpretation of results and validation of ctDNA-based treatment decisions remain challenging. We report here our experience implementing liquid biopsies into the clinical management of lung cancer. We discuss advantages and limitations of distinct ctDNA assay techniques and highlight our approach to the analysis of recurrent molecular alterations found in lung cancer. Moreover, we report three exemplary clinical cases illustrating the complexity of interpreting liquid biopsy results in clinical practice. These cases underscore the potential and current limitations of liquid biopsy, focusing on the difficulty of interpreting discordant findings. In our view, despite all current limitations, the analysis of ctDNA in lung cancer patients is an essential and highly versatile complementary diagnostic tool for the clinical management of lung cancer patients in the era of precision oncology.

Relationship between Oral Health Status and Postoperative Fever among Patients with Lung Cancer Treated by Surgery: A Retrospective Cohort Study.

A retrospective observational study using an oral bacteria counter was conducted to evaluate the trends in the number of oral bacteria in the perioperative period of lung cancer patients and to verify the relationship between oral health status and postoperative fever. All patients received perioperative oral management (POM) by oral specialists between April 2012 and December 2018 at Kagawa Prefectural Central Hospital, Kagawa, Japan prior to lung cancer surgery. Bacteria counts from the dorsum of the tongue were measured on the day of pre-hospitalization, pre-operation, and post-operation, and background data were also collected retrospectively. In total, 441 consecutive patients were enrolled in the study. Bonferroni’s multiple comparison test showed significantly higher oral bacteria counts at pre-hospitalization compared to pre- and post-operation (p < 0.001). Logistic regression analysis showed that body mass index, performance status, number of housemates, number of teeth, and white blood cell count at pre-operation were significantly associated with postoperative fever. The study showed that POM can reduce the level of oral bacterial counts, that the risk of postoperative complications is lower with dentulous patients, and that appropriate POM is essential for prevent of complications. Therefore, POM may play an important role in perioperative management of lung cancer patients.

Inflection of Akt/mTOR/STAT-3 cascade in TNF-α induced protein 8 mediated human lung carcinogenesis

Lung cancer is the leading cause of cancer-related death across the globe. Despite the marked advances in detection and therapeutic approaches, management of lung cancer patients remains a major challenge to oncologists which can be mainly attributed to late stage diagnosis, tumor recurrence and chemoresistance. Therefore, to overthrow these limitations, there arises a vital need to develop effective biomarkers for the successful management of this aggressive cancer type. Notably, TNF-alpha induced protein 8 (TIPE), a nuclear factor-kappa B (NF-κB)-inducible, oncogenic molecule and cytoplasmic protein which is involved in the regulation of T lymphocyte-mediated immunity and different processes in tumor cells such as proliferation, cell death and evasion of growth suppressors, might serve as one such biomarker which would facilitate effective management of lung cancer. Expression studies revealed this protein to be significantly upregulated in different lung cancer types, pathological conditions, stages and grades of lung tumor compared to normal human lung tissues. In addition, knockout of TIPE led to the reduced proliferation, survival, invasion and migration of lung cancer cells. Furthermore, TIPE was found to function through modulation of Akt/mTOR/STAT-3 signaling cascade. This is the first report which shows the involvement of TIPE in tobacco induced lung carcinogenesis. It positively regulated nicotine, NNK, NNN, and BaP induced proliferation, survival and migration of lung cancer cells possibly via Akt/STAT-3 signaling. Thus, this protein possesses important role in the pathogenesis of lung tumor and hence it can be targeted for developing newer therapeutic interventions for the clinico-management of lung cancer.

Developing and Assessing the Effectiveness of a Nurse-Led Home-Based Educational Programme for Managing Breathlessness in Lung Cancer Patients. A Feasibility Study.

Introduction: Breathlessness is the most common and refractory symptom in lung cancer patients. Even though various educational programmes have been developed, only a few were intended for implementation in the home setting for its management.Aim: Feasibility of a study for implementing a nurse-led educational programme for breathlessness management of lung cancer patients at home.Method: A randomized feasibility study was undertaken between February 2017 and October 2018. Patients were recruited through referral from oncologists from two oncology centers in Cyprus under certain inclusion and exclusion criteria. Patients were randomized in the intervention or control group via a computer programme, and their named family caregivers (f.c.) were allocated in the same group. Participants were not blinded to group assignment. The intervention consisted of a PowerPoint presentation and implementation of three non-pharmacological interventions. The control group received usual care. Patients were assessed for breathlessness, anxiety, and depression levels, whereas f.c. were assessed for anxiety, depression, and burden levels. F.c. also assessed patients' dyspnea level. The duration of the study process for both the intervention and control group was over a period of 4 weeks.Results: Twenty-four patients and their f.c. (n = 24) were allocated equally in the intervention and control group. Five patients withdrew, and the final sample entered analysis was 19 patients and 19 family caregivers. In the intervention group n = 11 + 11, and in the control group n = 8 + 8. In the intervention group patients' breathlessness and anxiety levels showed improvement and their f.c.s in the anxiety and burden levels. Major consideration was the sample size and the recruitment of the patients by the referring oncologists. Attrition was minor during the study process. No harm was recorded by the participants of the study.Conclusions: The study provided evidence of the feasibility of the implementation of the educational programme. For the future definitive study major consideration should be patients' recruitment method in order to achieve adequate sample size. Moreover, qualitative data should be collected in relation to the intervention and the involvement of f.c. The feasibility study was registered to the Cyprus Bioethics Committee with the registration number 2016/16. There was no funding of the study.

Text {DRTOP}: deep learning-based radiomics for the time-to-event outcome prediction in lung cancer

Hand-crafted radiomics has been used for developing models in order to predict time-to-event clinical outcomes in patients with lung cancer. Hand-crafted features, however, are pre-defined and extracted without taking the desired target into account. Furthermore, accurate segmentation of the tumor is required for development of a reliable predictive model, which may be objective and a time-consuming task. To address these drawbacks, we propose a deep learning-based radiomics model for the time-to-event outcome prediction, referred to as DRTOP that takes raw images as inputs, and calculates the image-based risk of death or recurrence, for each patient. Our experiments on an in-house dataset of 132 lung cancer patients show that the obtained image-based risks are significant predictors of the time-to-event outcomes. Computed Tomography (CT)-based features are predictors of the overall survival (OS), with the hazard ratio (HR) of 1.35, distant control (DC), with HR of 1.06, and local control (LC), with HR of 2.66. The Positron Emission Tomography (PET)-based features are predictors of OS and recurrence free survival (RFS), with hazard ratios of 1.67 and 1.18, respectively. The concordance indices of 68%, 63%, and 64% for predicting the OS, DC, and RFS show that the deep learning-based radiomics model is as accurate or better in predicting predefined clinical outcomes compared to hand-crafted radiomics, with concordance indices of 51%, 64%, and 47%, for predicting the OS, DC, and RFS, respectively. Deep learning-based radiomics has the potential to offer complimentary predictive information in the personalized management of lung cancer patients.

Identification of PDL1-Related Biomarkers to Select Lung Adenocarcinoma Patients for PD1/PDL1 Inhibitors.

PD1/PDL1 inhibitors have been adopted for the treatment of advanced non-small-cell lung cancer, and PDL1 expression has been investigated as a predictive biomarker for PD1/PDL1 inhibitor therapy. However, PDL1 lacks diagnostic accuracy in differentiating patients who are likely or unlikely to benefit. So, it is urgent and clinically significant to identify other associated predictive biomarkers for PD1/PDL1 inhibitor therapy. Our work was to identify PDL1-related biomarkers that could improve the patient selection for PD1/PDL1 inhibitor treatment. We obtained 500 genes coexpressed with PDL1 in lung adenocarcinoma from the TCGA database. Then, we identified 125 out of 500 genes differentially expressed in lung adenocarcinoma. A total of 39 genes were distinguished with prognostic value and associated with overall survival. Median survival time analysis based on gene expression level, protein-protein interaction analysis, GO and KEGG enrichment analyses, and significant GO and KEGG function consistency analyses were conducted to screen candidate biomarkers. Three candidate genes, BRCA1, BRIP1, and EREG, were identified to be functionally significantly coexpressed with PDL1. Functional enrichment analysis and protein-protein interaction networks further showed that these genes mainly participated in immune response and cell activation. Additionally, to find potential adjuvant therapeutic targets in PD1/PDL1 inhibitor treatment, we performed transcription factor prediction analysis. A group of negative differential expression but PDL1-related biomarkers has been identified, which might help to assess the clinical management of lung cancer patients. A combination of potential biomarkers and adjuvant therapeutic targets with PDL1 will predict the response to PD1/PDL1 inhibitors more accurately and help with the patient selection for more personalized immune checkpoint inhibitor treatment.

2-[18F]FDG PET/CT radiomics in lung cancer: An overview of the technical aspect and its emerging role in management of the disease.

Lung cancer is the most common cancer, worldwide, and a major health issue with a remarkable mortality rate. 2-[18F]fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography (2-[18F]FDG PET/CT) plays an indispensable role in the management of lung cancer patients. Long-established quantitative parameters such as size, density, and metabolic activity have been and are being employed in the current practice to enhance interpretation and improve diagnostic and prognostic value. The introduction of radiomics analysis revolutionized the quantitative evaluation of medical imaging, revealing data within images beyond visual interpretation. The "big data" are extracted from high-quality images and are converted into information that correlates to relevant genetic, pathologic, clinical, or prognostic features. Technically advanced, diverse methods have been implemented in different studies. The standardization of image acquisition, segmentation and features analysis is still a debated issue. Importantly, a body of features has been extracted and employed for diagnosis, staging, risk stratification, prognostication, and therapeutic response. 2-[18F]FDG PET/CT-derived features show promising value in non-invasively diagnosing the malignant nature of pulmonary nodules, differentiating lung cancer subtypes, and predicting response to different therapies as well as survival. In this review article, we aimed to provide an overview of the technical aspects used in radiomics analysis in non-small cell lung cancer (NSCLC) and elucidate the role of 2-[18F]FDG PET/CT-derived radiomics in the diagnosis, prognostication, and therapeutic response.

Clinical recommendations on lung cancer management during the COVID-19 pandemic.

Coronavirus disease 2019 (COVID‐19) is spreading worldwide, and has been declared as an international public health concern. Patients with lung cancer are highly susceptible to infection compared to healthy individuals because of systemic immunosuppression induced by malignancy and anticancer therapy. Furthermore, patients with cancer demonstrate poorer outcomes following infection. Hence, patients with lung cancer should be considered a priority group for COVID‐19 prevention. Furthermore, the routine treatment of patients with cancer has been affected during the COVID‐19 pandemic, and patients may not have been able to undergo timely and effective antitumor treatment, thereby indicating a poor prognosis. Here, we provide some suggestions for early identification of COVID‐19 and differential diagnosis in patients with lung cancer who have fever and respiratory symptoms. Our medical team also provide clinical recommendations on lung cancer management during the COVID‐19 pandemic, for carrying out meticulous and individualized clinical management of lung cancer patients and maximum protection to effectively prevent COVID‐19.Key pointsSignificant findings of the studyThis article provides suggestions for early identification of COVID‐19 and differential diagnosis in patients with lung cancer with fever and respiratory symptoms.What this study addsThis article makes clinical recommendations on lung cancer management during the COVID‐19 pandemic.

Barriers to lung cancer referral, diagnosis, and treatment in Central America and the Caribbean: the health professionals' perspectives.

To identify the perspectives from healthcare providers about the limitations in referral, diagnosis, and treatment of lung cancer (LC) patients. A cross-sectional study through an Internet-based survey was addressed to physicians of multidisciplinary teams in charge of LC patients from Cuba, Curacao, Costa Rica, Dominican Republic, El Salvador, Guatemala, Honduras, Jamaica, Panama, and Trinidad and Tobago. The questions focused on physicians' perspectives concerning waiting times and the availability of diagnostic and staging procedures in their settings, as well as the access to systemic therapies and continuous medical education (CME). A total of 152 physicians responded to the online questionnaire (response rate 24.9%). Delays in biopsy results were the main barrier for LC diagnosis as identified by 48.2% of the respondents, followed by patients not being referred in time (31.3%), delays for staging procedures (11.4%), and time taken for biopsy (9%). Almost one-half of physicians perceived that patients are diagnosed in advanced stages. A total of 29 respondent physicians (19.1%) reported limited access to immunohistochemical or genetic analysis for common mutations. Although 73 physicians (48.0%) confirmed that their centers provided radiotherapy and systemic therapy for their patients, immunotherapy was not available in the institutions of 30 physicians (19.7%). A total of 42 practitioners (27.6%) reported that they did not have access to CME on LC topics due to working or budget restrictions. This study revealed among respondents the main barriers for an appropriate management of LC patients in the Central American and Caribbean Region. Further studies must validate these findings.

IMAGING OF LUNG CANCER STAGING USING ADVANCED CT SCAN TECHNIQUES

Background: Lung cancer is one of leading death worldwide, it begins when cells in the lung grow out of control and formed mass or nodules which classified in two known major forms, non-small cell and small cell cancer. The accurate assessment of the disease extent is important in management approach and Computed tomography imaging in nodal staging remains the important tool for lung cancer diagnosis, particularly when assessing intra and extra thoracic spread of lung cancer.&#x0D; Objective: This is a quantitative cross-sectional study conducted in Sudanese lung cancer patients in period from November 2019 to February 2020 in Khartoum state hospital. The main aim of the study was to evaluate staging of lung cancer using computed tomography technology.&#x0D; Method: A group of 100 participants patients were selected randomly in different gender and in age group between (30-80) years old. The inclusion limited to patients diagnosed with lung cancer by computed tomography techniques and the normal cases and other abnormalities was being excluded. The data were collected using a special collection sheet and the data statistical analyzed using SPSS program.&#x0D; Result: The outcomes of this study showed that patients in age group between (60-70) years old do not have lung cancer in the first stage, while lung cancer in the second stage occurred in 10 patients only with 10 % percentage. The third stage is the most common type with a high incidence rate which occurred in 90 patients with 90 %. Percent.&#x0D; Conclusion: Advance imaging with CT scan techniques play a critical role in the diagnosis and management of lung cancer patients adding to accurately describing the radiological extent of the disease. Moreover, the important to understand the principles of staging description and their impact on treatment decisions.

Applications of cell-free circulating tumor DNA detection in EGFR mutant lung cancer.

Analyses of cell-free tumor DNA (ctDNA) have provided a non-invasive strategy for cancer diagnosis, the identification of molecular aberrations for treatment identification, and evaluation of tumor response. Sensitive and specific ctDNA sequencing strategies have allowed for implementation into clinical practice for the initial genotyping of patients and resistance monitoring. The specific need for EGFR mutation detection for the management of lung cancer patients has been an early imperative and has set the stage for non-invasive molecular profiling across other oncogenic drivers. Ongoing efforts are demonstrating the utility of ctDNA analyses in the initial genotyping of patients, the monitoring resistance clones, and the initial evaluation of response.

Diagnostic and therapeutic strategies of lung cancer patients during the outbreak of 2019 novel coronavirus disease (COVID-19)

With the increasing number of cases and widening geographical spread, the 2019 novel coronavirus disease (COVID-19) has been classified as one of the class B infectious diseases but prevented and controlled as class A infectious disease by the National Health Commission of China. The diagnosis and treatment of lung cancer patients have been challenged greatly because of extraordinary public health measures since the lung cancer patients are a high-risk population during the COVID-19 outbreak period. Strict protection for lung cancer patients is needed to avoid infection. Lung cancer patients are difficult to differentiate from patients with COVID-19 in terms of clinical symptoms, which will bring great trouble to the clinical work and physical and mental health of lung cancer patients. This review will demonstrate how to applicate appropriate and individual management for lung cancer patients to protect them from COVID-19.