Yichen Zhang, Lizheng Shi, Michael J Simoff, Oliver J Wagner, James Lavin
Objective: This study aimed to describe the frequency and distribution of biopsy procedures for patients diagnosed and treated for primary lung cancer.
Study design: Retrospective cohort study within an administrative database.
Materials & methods: This observational study used data from the IBM MarketScan® Databases between 2013 and 2015.
Results: The total number of lung biopsies performed among eligible subjects was 32,814; an average of 1.7 biopsies per patient. Bronchoscopy and percutaneous approaches accounted for 95% of all procedures. Complication rates by procedure are remarkably similar irrespective of biopsy frequency.
Conclusion: Nearly half (46%) of patients in this population experienced multiple biopsies prior to diagnosis. Further, biopsy choice or sequence in patients receiving multiple procedures was unpredictable.
{"title":"Biopsy frequency and complications among lung cancer patients in the United States.","authors":"Yichen Zhang, Lizheng Shi, Michael J Simoff, Oliver J Wagner, James Lavin","doi":"10.2217/lmt-2020-0022","DOIUrl":"10.2217/lmt-2020-0022","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to describe the frequency and distribution of biopsy procedures for patients diagnosed and treated for primary lung cancer.</p><p><strong>Study design: </strong>Retrospective cohort study within an administrative database.</p><p><strong>Materials & methods: </strong>This observational study used data from the IBM MarketScan<sup>®</sup> Databases between 2013 and 2015.</p><p><strong>Results: </strong>The total number of lung biopsies performed among eligible subjects was 32,814; an average of 1.7 biopsies per patient. Bronchoscopy and percutaneous approaches accounted for 95% of all procedures. Complication rates by procedure are remarkably similar irrespective of biopsy frequency.</p><p><strong>Conclusion: </strong>Nearly half (46%) of patients in this population experienced multiple biopsies prior to diagnosis. Further, biopsy choice or sequence in patients receiving multiple procedures was unpredictable.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/77/e8/lmt-09-40.PMC7729592.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38709410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Palliative care (PC) is the care of patients and their families with serious illness and is rapidly becoming an important part of the care of cancer patients. Patients with advanced lung cancer are a highly symptomatic population of patients and clearly experience benefits in quality of life and potentially benefits in overall survival when PC is incorporated early on after diagnosis. However, referrals to PC are still reliant on clinical judgment of patient prognosis and symptom burden. Moving forward, improving the integration of PC and lung cancer care will require more efficient real-time screening of patient symptoms, which may be accomplished through the use of patient-reported outcomes.
姑息治疗(Palliative care, PC)是对患有严重疾病的患者及其家属的护理，正迅速成为癌症患者护理的重要组成部分。晚期肺癌患者是一个高度症状化的患者群体，如果在诊断后早期合并PC，显然会在生活质量和总生存期方面获益。然而，转介到PC仍依赖于临床对患者预后和症状负担的判断。展望未来，改善PC和肺癌治疗的整合将需要更有效地实时筛查患者症状，这可以通过使用患者报告的结果来实现。
{"title":"The role of palliative care in the management of patients with lung cancer.","authors":"Irena Tan, Kavitha Ramchandran","doi":"10.2217/lmt-2020-0016","DOIUrl":"https://doi.org/10.2217/lmt-2020-0016","url":null,"abstract":"<p><p>Palliative care (PC) is the care of patients and their families with serious illness and is rapidly becoming an important part of the care of cancer patients. Patients with advanced lung cancer are a highly symptomatic population of patients and clearly experience benefits in quality of life and potentially benefits in overall survival when PC is incorporated early on after diagnosis. However, referrals to PC are still reliant on clinical judgment of patient prognosis and symptom burden. Moving forward, improving the integration of PC and lung cancer care will require more efficient real-time screening of patient symptoms, which may be accomplished through the use of patient-reported outcomes.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0016","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38709409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Combination platinum-based therapy has been the standard of care for the treatment of advanced non-small-cell lung cancer (NSCLC). Immunotherapy has emerged and demonstrated to show benefit in the treatment of patients with advanced NSCLC. In this review, we discuss the pivotal trials that led to the US FDA approval of specific immunotherapy regimens in particular patient populations. We discuss the optimal use of immunotherapy as monotherapy based on the KEYNOTE-024, KEYNOTE-042 and IMpower110 trials, chemo-immunotherapy based on KEYNOTE-189, KEYNOTE-407, IMpower150 and IMpower130 trials, and as doublet immunotherapy based on CheckMate-227. We also discuss the role and limitations of PD-L1 expression and tumor mutational burden as predictive biomarkers in response to single-agent immunotherapy and combination chemoimmunotherapy. Furthermore, we discuss emerging resistance markers such as STK11 and KEAP1 mutations in immunotherapy response and briefly discuss the role of immunotherapy in elderly patients and in patients with actionable mutations.
{"title":"Choosing the best first-line therapy: NSCLC with no actionable oncogenic driver.","authors":"So Yeon Kim, Balazs Halmos","doi":"10.2217/lmt-2020-0003","DOIUrl":"https://doi.org/10.2217/lmt-2020-0003","url":null,"abstract":"<p><p>Combination platinum-based therapy has been the standard of care for the treatment of advanced non-small-cell lung cancer (NSCLC). Immunotherapy has emerged and demonstrated to show benefit in the treatment of patients with advanced NSCLC. In this review, we discuss the pivotal trials that led to the US FDA approval of specific immunotherapy regimens in particular patient populations. We discuss the optimal use of immunotherapy as monotherapy based on the KEYNOTE-024, KEYNOTE-042 and IMpower110 trials, chemo-immunotherapy based on KEYNOTE-189, KEYNOTE-407, IMpower150 and IMpower130 trials, and as doublet immunotherapy based on CheckMate-227. We also discuss the role and limitations of PD-L1 expression and tumor mutational burden as predictive biomarkers in response to single-agent immunotherapy and combination chemoimmunotherapy. Furthermore, we discuss emerging resistance markers such as <i>STK11</i> and <i>KEAP1</i> mutations in immunotherapy response and briefly discuss the role of immunotherapy in elderly patients and in patients with actionable mutations.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38245942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rahul Ladwa, Kate E Roberts, Connor O'Leary, Nicole Maggacis, Kenneth J O'Byrne, Kenneth Miles
Objectives: Assess computed tomography texture analysis of patients likely to benefit from nivolumab.
Materials & methods: Texture analysis was used to quantify heterogeneity within the largest tumor before immunotherapy. Histogram analysis was classified as hyperdense (positive skewness) or hypodense (negative skewness) and subclassified on median standard deviation value or entropy measurement.
Results: 47 patients were included. At a median follow-up of 18 months, statistical significant differences in progression-free survival were observed when stratified by positive skewness with low entropy, hazard ratio: 0.43 (0.19-0.95); p = 0.036, and positive skewness with low standard deviation, hazard ratio: 0.42 (0.18-0.96); p = 0.04.
Conclusion: Patients who derive a clinical benefit to Nivolumab show a computed tomography texture of a hyperdense yet homogenous tumor.
{"title":"Computed tomography texture analysis of response to second-line nivolumab in metastatic non-small cell lung cancer.","authors":"Rahul Ladwa, Kate E Roberts, Connor O'Leary, Nicole Maggacis, Kenneth J O'Byrne, Kenneth Miles","doi":"10.2217/lmt-2020-0002","DOIUrl":"https://doi.org/10.2217/lmt-2020-0002","url":null,"abstract":"<p><strong>Objectives: </strong>Assess computed tomography texture analysis of patients likely to benefit from nivolumab.</p><p><strong>Materials & methods: </strong>Texture analysis was used to quantify heterogeneity within the largest tumor before immunotherapy. Histogram analysis was classified as hyperdense (positive skewness) or hypodense (negative skewness) and subclassified on median standard deviation value or entropy measurement.</p><p><strong>Results: </strong>47 patients were included. At a median follow-up of 18 months, statistical significant differences in progression-free survival were observed when stratified by positive skewness with low entropy, hazard ratio: 0.43 (0.19-0.95); p = 0.036, and positive skewness with low standard deviation, hazard ratio: 0.42 (0.18-0.96); p = 0.04.</p><p><strong>Conclusion: </strong>Patients who derive a clinical benefit to Nivolumab show a computed tomography texture of a hyperdense yet homogenous tumor.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38246384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bernardo L Rapoport, Annette J Theron, Daniel A Vorobiof, Lizanne Langenhoven, Jacqueline M Hall, Ronwyn I Van Eeden, Teresa Smit, Sze-Wai Chan, Michael C Botha, Johann I Raats, Margriet De Necker, Ronald Anderson
Aim: We investigated the prognostic potential of pretherapy measurement of the neutrophil/lymphocyte ratio (NLR) in patients (n = 56) with non-small-cell lung cancer deemed suitable for treatment with nivolumab.
Materials & methods: This was a multicenter, noninterventional, retrospective data analysis, involving five oncology centers.
Results: Patients with prenivolumab NLR values of <5 and ≥5 had respective median overall survival (OS) values of 14.5 and 7.02 months (p = 0.0026). Patients with ≤2 and >2 metastatic sites had median OS values of 11.4 and 6.1 months, respectively (p = 0.0174). A Cox multiple regression model revealed baseline NLR ≥5 as the only variable significantly associated with decreased OS (p < 0.0447).
Conclusion: Pretreatment elevated NLR values are associated with poor outcomes in patients with recurrent metastatic non-small-cell lung cancer treated with nivolumab.
{"title":"Prognostic significance of the neutrophil/lymphocyte ratio in patients undergoing treatment with nivolumab for recurrent non-small-cell lung cancer.","authors":"Bernardo L Rapoport, Annette J Theron, Daniel A Vorobiof, Lizanne Langenhoven, Jacqueline M Hall, Ronwyn I Van Eeden, Teresa Smit, Sze-Wai Chan, Michael C Botha, Johann I Raats, Margriet De Necker, Ronald Anderson","doi":"10.2217/lmt-2020-0014","DOIUrl":"https://doi.org/10.2217/lmt-2020-0014","url":null,"abstract":"<p><strong>Aim: </strong>We investigated the prognostic potential of pretherapy measurement of the neutrophil/lymphocyte ratio (NLR) in patients (n = 56) with non-small-cell lung cancer deemed suitable for treatment with nivolumab.</p><p><strong>Materials & methods: </strong>This was a multicenter, noninterventional, retrospective data analysis, involving five oncology centers.</p><p><strong>Results: </strong>Patients with prenivolumab NLR values of <5 and ≥5 had respective median overall survival (OS) values of 14.5 and 7.02 months (p = 0.0026). Patients with ≤2 and >2 metastatic sites had median OS values of 11.4 and 6.1 months, respectively (p = 0.0174). A Cox multiple regression model revealed baseline NLR ≥5 as the only variable significantly associated with decreased OS (p < 0.0447).</p><p><strong>Conclusion: </strong>Pretreatment elevated NLR values are associated with poor outcomes in patients with recurrent metastatic non-small-cell lung cancer treated with nivolumab.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0014","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38245943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lung cancer is the second most common cause of cancer worldwide and the leading cause of cancer death in the USA [1]. The American Cancer Society (NY, USA) estimated a total of 228,150 new cases of lung cancer with 142,670 deaths from lung cancer in the USA for 2019 [1]. Smoking is the main cause of lung cancer and contributes to 80% of lung cancer deaths in women and 90% in men [2]. Lung cancer is typically diagnosed at advanced stages and carries a high mortality rate, with a 5-year survival rate of only 18% [3]. Randomized controlled trials targeted toward lung cancer screening started in the 1970s when the US National Cancer Institute (NCI; MD, USA) sponsored several clinical trials to evaluate the benefit of adding sputum cytology to annual chest radiography (CXR) [4,5]. However, none of the trials showed a reduction in lung cancer mortality (Supplementary Table 1). Decades later, the NCI initiated the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO), a large randomized controlled trial that aimed to reduce disease-specific cancer mortality by evaluating the use of CXR for screening [6]. The study found that 2% of participants that had a positive radiographic findings were diagnosed with lung cancer within 12 months of the screen, 44% of whom were diagnosed with stage I disease [6]. Pertinent findings that paved the road for future guidelines included the discovery that high incidences of lung cancer were noted in active smokers or those that had quit within 15 years of randomization [6]. In the 2000s, prospective studies were created throughout the world to evaluate the role of low-dose computed tomography (LDCT) for screening. The Lung Screening Study compared LDCT and CXR as screening modalities and revealed that LDCT was twice as effective as CXR in detecting lung cancer [7]. It also showed that 48% of lung cancers detected by LDCT screening were diagnosed at stage I [7]. Inspired by the Lung Screening Study, a large scale study called the National Lung Screening Trial (NLST), which enrolled 53,456 participants, was created. Participants were randomized to LDCT or CXR at a 1:1 ratio. The study demonstrated a 20% relative reduction in mortality in patients screened with LDCT compared with CXR [8]. Results from this trial were updated in 2013 and confirmed the benefit of LDCT for lung cancer screening in specific patient populations [9]. Similar results were showcased from The Dutch–Belgian Randomized Lung Cancer Screening Trial (NELSON) which began in Europe in 2003 [10]. More than 15,000 participants were enrolled and assigned to either computer tomography (CT) screening or to the control group with no screening [10]. The study reported a 41% positive predictive value with screening and 50% of the cancers diagnosed in the screening arm were found at early stages of the disease [10]. During a 10-year follow-up, there was a 26% mortality rate reduction in men and 39% in women [10]. Updated results published in the New E
{"title":"Lung cancer screening guidelines are clear but are they being followed?","authors":"Coral Olazagasti, Carolina Bernabe, Nagashree Seetharamu","doi":"10.2217/lmt-2020-0015","DOIUrl":"https://doi.org/10.2217/lmt-2020-0015","url":null,"abstract":"Lung cancer is the second most common cause of cancer worldwide and the leading cause of cancer death in the USA [1]. The American Cancer Society (NY, USA) estimated a total of 228,150 new cases of lung cancer with 142,670 deaths from lung cancer in the USA for 2019 [1]. Smoking is the main cause of lung cancer and contributes to 80% of lung cancer deaths in women and 90% in men [2]. Lung cancer is typically diagnosed at advanced stages and carries a high mortality rate, with a 5-year survival rate of only 18% [3]. Randomized controlled trials targeted toward lung cancer screening started in the 1970s when the US National Cancer Institute (NCI; MD, USA) sponsored several clinical trials to evaluate the benefit of adding sputum cytology to annual chest radiography (CXR) [4,5]. However, none of the trials showed a reduction in lung cancer mortality (Supplementary Table 1). Decades later, the NCI initiated the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO), a large randomized controlled trial that aimed to reduce disease-specific cancer mortality by evaluating the use of CXR for screening [6]. The study found that 2% of participants that had a positive radiographic findings were diagnosed with lung cancer within 12 months of the screen, 44% of whom were diagnosed with stage I disease [6]. Pertinent findings that paved the road for future guidelines included the discovery that high incidences of lung cancer were noted in active smokers or those that had quit within 15 years of randomization [6]. In the 2000s, prospective studies were created throughout the world to evaluate the role of low-dose computed tomography (LDCT) for screening. The Lung Screening Study compared LDCT and CXR as screening modalities and revealed that LDCT was twice as effective as CXR in detecting lung cancer [7]. It also showed that 48% of lung cancers detected by LDCT screening were diagnosed at stage I [7]. Inspired by the Lung Screening Study, a large scale study called the National Lung Screening Trial (NLST), which enrolled 53,456 participants, was created. Participants were randomized to LDCT or CXR at a 1:1 ratio. The study demonstrated a 20% relative reduction in mortality in patients screened with LDCT compared with CXR [8]. Results from this trial were updated in 2013 and confirmed the benefit of LDCT for lung cancer screening in specific patient populations [9]. Similar results were showcased from The Dutch–Belgian Randomized Lung Cancer Screening Trial (NELSON) which began in Europe in 2003 [10]. More than 15,000 participants were enrolled and assigned to either computer tomography (CT) screening or to the control group with no screening [10]. The study reported a 41% positive predictive value with screening and 50% of the cancers diagnosed in the screening arm were found at early stages of the disease [10]. During a 10-year follow-up, there was a 26% mortality rate reduction in men and 39% in women [10]. Updated results published in the New E","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/1b/3b/lmt-09-35.PMC7724650.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38709408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Meera V Ragavan*,1 & Manali I Patel2,3,4 1Department of Medicine, Stanford University School of Medicine, Stanford, 94305 CA 94305, USA 2Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA 3Division of Oncology, VA Palo Alto Healthcare System, Palo Alto, CA 94304, USA 4Center for Health Policy/Primary Care Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA *Author for correspondence: mragavan@stanford.edu
{"title":"Understanding sex disparities in lung cancer incidence: are women more at risk?","authors":"Meera V Ragavan, Manali I Patel","doi":"10.2217/lmt-2020-0013","DOIUrl":"https://doi.org/10.2217/lmt-2020-0013","url":null,"abstract":"Meera V Ragavan*,1 & Manali I Patel2,3,4 1Department of Medicine, Stanford University School of Medicine, Stanford, 94305 CA 94305, USA 2Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA 3Division of Oncology, VA Palo Alto Healthcare System, Palo Alto, CA 94304, USA 4Center for Health Policy/Primary Care Outcomes Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA *Author for correspondence: mragavan@stanford.edu","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0013","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38245941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).
Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan-Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.
Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.
Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.
{"title":"Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma.","authors":"Chuanli Ren, Weixiu Sun, Xu Lian, Chongxu Han","doi":"10.2217/lmt-2020-0009","DOIUrl":"https://doi.org/10.2217/lmt-2020-0009","url":null,"abstract":"<p><strong>Aim: </strong>To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).</p><p><strong>Materials & methods: </strong>We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan-Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.</p><p><strong>Results: </strong>Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.</p><p><strong>Conclusion: </strong>23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0009","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37882477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Checkpoint inhibitors are integral to non-small-cell lung cancer treatment. Existing data suggests that nutritional status may play a role in antitumor immunity.
Materials & methods: This retrospective study of 106 non-small-cell lung cancer patients who started checkpoint inhibitors between 2014 and 2017 at our institution assessed relationship of nutritional parameters to overall survival (OS) and progression-free survival.
Results: Mean age was 68.7 ± 9.2 years and 59.4% patients were male. On multivariate analysis for OS, hypoalbuminemia and significant weight loss were prognostic at p-values of 0.0005 and 0.0052, respectively. We noted a parabolic association between age and OS (p = 0.026, 0.0025).
Conclusion: In our study, some malnutrition parameters were associated with decreased OS. U-shape relationship between age and OS noted here warrants further evaluation.
{"title":"Pretreatment nutritional status and response to checkpoint inhibitors in lung cancer.","authors":"Chung-Shien Lee, Craig E Devoe, Xinhua Zhu, Joanna Stein Fishbein, Nagashree Seetharamu","doi":"10.2217/lmt-2020-0008","DOIUrl":"https://doi.org/10.2217/lmt-2020-0008","url":null,"abstract":"<p><strong>Background: </strong>Checkpoint inhibitors are integral to non-small-cell lung cancer treatment. Existing data suggests that nutritional status may play a role in antitumor immunity.</p><p><strong>Materials & methods: </strong>This retrospective study of 106 non-small-cell lung cancer patients who started checkpoint inhibitors between 2014 and 2017 at our institution assessed relationship of nutritional parameters to overall survival (OS) and progression-free survival.</p><p><strong>Results: </strong>Mean age was 68.7 ± 9.2 years and 59.4% patients were male. On multivariate analysis for OS, hypoalbuminemia and significant weight loss were prognostic at p-values of 0.0005 and 0.0052, respectively. We noted a parabolic association between age and OS (p = 0.026, 0.0025).</p><p><strong>Conclusion: </strong>In our study, some malnutrition parameters were associated with decreased OS. U-shape relationship between age and OS noted here warrants further evaluation.</p>","PeriodicalId":43551,"journal":{"name":"Lung Cancer Management","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2020-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2217/lmt-2020-0008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37882399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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