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Bhalla S, Yi S, Gerber DE. Emerging Strategies in Lung Cancer Screening: Blood and Beyond. Clin Chem 2024; 70:60-67. [PMID: 38175587 PMCID: PMC11161198 DOI: 10.1093/clinchem/hvad137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/02/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND Although low dose computed tomography (LDCT)-based lung cancer screening (LCS) can decrease lung cancer-related mortality among high-risk individuals, it remains an imperfect and substantially underutilized process. LDCT-based LCS may result in false-positive findings, which can lead to invasive procedures and potential morbidity. Conversely, current guidelines may fail to capture at-risk individuals, particularly those from under-represented minority populations. To address these limitations, numerous biomarkers have emerged to complement LDCT and improve early lung cancer detection. CONTENT This review focuses primarily on blood-based biomarkers, including protein, microRNAs, circulating DNA, and methylated DNA panels, in current clinical development for LCS. We also examine other emerging biomarkers-utilizing airway epithelia, exhaled breath, sputum, and urine-under investigation. We highlight challenges and limitations of biomarker testing, as well as recent strategies to integrate molecular strategies with imaging technologies. SUMMARY Multiple biomarkers are under active investigation for LCS, either to improve risk-stratification after nodule detection or to optimize risk-based patient selection for LDCT-based screening. Results from ongoing and future clinical trials will elucidate the clinical utility of biomarkers in the LCS paradigm.
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Affiliation(s)
- Sheena Bhalla
- Department of Internal Medicine (Division of Hematology-Oncology), UT Southwestern Medical Center, Dallas, TX, United States
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, United States
| | - Sofia Yi
- School of Medicine, UT Southwestern Medical Center, Dallas, TX, United States
| | - David E Gerber
- Department of Internal Medicine (Division of Hematology-Oncology), UT Southwestern Medical Center, Dallas, TX, United States
- Harold C. Simmons Comprehensive Cancer Center, UT Southwestern Medical Center, Dallas, TX, United States
- Peter O'Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX, United States
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2
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van den Broek D, Groen HJM. Screening approaches for lung cancer by blood-based biomarkers: Challenges and opportunities. Tumour Biol 2024; 46:S65-S80. [PMID: 37393461 DOI: 10.3233/tub-230004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/03/2023] Open
Abstract
Lung cancer (LC) is one of the leading causes for cancer-related deaths in the world, accounting for 28% of all cancer deaths in Europe. Screening for lung cancer can enable earlier detection of LC and reduce lung cancer mortality as was demonstrated in several large image-based screening studies such as the NELSON and the NLST. Based on these studies, screening is recommended in the US and in the UK a targeted lung health check program was initiated. In Europe lung cancer screening (LCS) has not been implemented due to limited data on cost-effectiveness in the different health care systems and questions on for example the selection of high-risk individuals, adherence to screening, management of indeterminate nodules, and risk of overdiagnosis. Liquid biomarkers are considered to have a high potential to address these questions by supporting pre- and post- Low Dose CT (LDCT) risk-assessment thereby improving the overall efficacy of LCS. A wide variety of biomarkers, including cfDNA, miRNA, proteins and inflammatory markers have been studied in the context of LCS. Despite the available data, biomarkers are currently not implemented or evaluated in screening studies or screening programs. As a result, it remains an open question which biomarker will actually improve a LCS program and do this against acceptable costs. In this paper we discuss the current status of different promising biomarkers and the challenges and opportunities of blood-based biomarkers in the context of lung cancer screening.
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Affiliation(s)
- Daniel van den Broek
- Department of laboratory Medicine, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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3
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Feng X, Wu WYY, Onwuka JU, Haider Z, Alcala K, Smith-Byrne K, Zahed H, Guida F, Wang R, Bassett JK, Stevens V, Wang Y, Weinstein S, Freedman ND, Chen C, Tinker L, Nøst TH, Koh WP, Muller D, Colorado-Yohar SM, Tumino R, Hung RJ, Amos CI, Lin X, Zhang X, Arslan AA, Sánchez MJ, Sørgjerd EP, Severi G, Hveem K, Brennan P, Langhammer A, Milne RL, Yuan JM, Melin B, Johansson M, Robbins HA, Johansson M. Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools. J Natl Cancer Inst 2023; 115:1050-1059. [PMID: 37260165 PMCID: PMC10483263 DOI: 10.1093/jnci/djad071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 04/05/2023] [Accepted: 04/08/2023] [Indexed: 06/02/2023] Open
Abstract
BACKGROUND We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test. METHODS We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. RESULTS The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. CONCLUSION Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.
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Affiliation(s)
- Xiaoshuang Feng
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Wendy Yi-Ying Wu
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | | | - Zahra Haider
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | - Karine Alcala
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | | | - Hana Zahed
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Florence Guida
- Environment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
| | - Julie K Bassett
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Victoria Stevens
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Ying Wang
- American Cancer Society, Atlanta, GA, USA
| | - Stephanie Weinstein
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Neal D Freedman
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Chu Chen
- Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Lesley Tinker
- Women’s Health Initiative Clinical Coordinating Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Therese Haugdahl Nøst
- Department of Community Medicine, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A*STAR), Singapore, Singapore
| | - David Muller
- Division of Genetic Medicine, Imperial College London School of Public Health, London, UK
| | - Sandra M Colorado-Yohar
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research, AIRE ONLUS Ragusa, Ragusa, Italy
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | - Xuehong Zhang
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Alan A Arslan
- Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - Maria-Jose Sánchez
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria ib, Granada, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Elin Pettersen Sørgjerd
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | | | - Kristian Hveem
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, VIC, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC, Australia
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatrice Melin
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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Khodayari Moez E, Warkentin MT, Brhane Y, Lam S, Field JK, Liu G, Zulueta JJ, Valencia K, Mesa-Guzman M, Nialet AP, Atkar-Khattra S, Davies MPA, Grant B, Murison K, Montuenga LM, Amos CI, Robbins HA, Johansson M, Hung RJ. Circulating proteome for pulmonary nodule malignancy. J Natl Cancer Inst 2023; 115:1060-1070. [PMID: 37369027 PMCID: PMC10483334 DOI: 10.1093/jnci/djad122] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 05/29/2023] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules. METHODS Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated. RESULTS We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001). CONCLUSIONS Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.
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Affiliation(s)
- Elham Khodayari Moez
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Matthew T Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Yonathan Brhane
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Stephen Lam
- Integrative Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada
| | - John K Field
- Molecular & Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Geoffrey Liu
- Computational Biology and Medicine Program, Princess Margaret Cancer Center, Toronto, ON, Canada
| | - Javier J Zulueta
- Division of Pulmonary, Critical Care and Sleep Medicine, Mount Sinai Morningside Hospital, Icahn School of Medicine, New York, NY, USA
| | - Karmele Valencia
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | - Miguel Mesa-Guzman
- Thoracic Surgery Department, Clínica Universidad de Navarra, Pamplona, Spain
| | - Andrea Pasquier Nialet
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | | | - Michael P A Davies
- Molecular & Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
| | - Benjamin Grant
- Computational Biology and Medicine Program, Princess Margaret Cancer Center, Toronto, ON, Canada
| | - Kiera Murison
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
| | - Luis M Montuenga
- Center of Applied Medical Research (CIMA) and Schools of Sciences and Medicine, University of Navarra, Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
- Centro de Investigacion Biomedica en Red de Cancer (CIBERONC), Madrid, Spain
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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5
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Wu WYY, Haider Z, Feng X, Heath AK, Tjønneland A, Agudo A, Masala G, Robbins HA, Huerta MJ, Guevara M, Schulze MB, Rodriguez-Barranco M, Vineis P, Tumino R, Kaaks R, Fortner RT, Sieri S, Panico S, Nøst TH, Sandanger TM, Braaten T, Johansson M, Melin B, Johansson M. Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts. Int J Cancer 2023; 152:2002-2010. [PMID: 36305647 PMCID: PMC10157531 DOI: 10.1002/ijc.34340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 09/30/2022] [Accepted: 10/05/2022] [Indexed: 11/11/2022]
Abstract
The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.
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Affiliation(s)
- Wendy Yi-Ying Wu
- Department of Radiation Sciences, Oncology, Umeå University, Sweden
| | - Zahra Haider
- Department of Radiation Sciences, Oncology, Umeå University, Sweden
| | - Xiaoshuang Feng
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Alicia K. Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Anne Tjønneland
- Diet, Cancer and Health, Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, University of Copenhagen, Denmark
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Catalan Institute of Oncology - ICO, L’Hospitalet de Llobregat, Spain
- Nutrition and Cancer Group; Epidemiology, Public Health, Cancer Prevention and Palliative Care Program; Bellvitge Biomedical Research Institute - IDIBELL, L’Hospitalet de Llobregat, Spain
| | - Giovanna Masala
- Institute for cancer research, prevention and clinical network (ISPRO) Florence, Italy
| | - Hilary A. Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - María-José Huerta
- Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
| | - Marcela Guevara
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
- Navarra Public Health Institute, 31003 Pamplona, Spain
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
| | - Matthias B. Schulze
- German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Miguel Rodriguez-Barranco
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, 18012 Granada, Spain
| | - Paolo Vineis
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, UK
| | - Rosario Tumino
- Hyblean Association for Epidemiological Research, AIRE ONLUS Ragusa, Italy
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
- Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Renée T. Fortner
- Division of Cancer Epidemiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano Via Venezian, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia Federico II Universioty, Naples, Italy
| | - Therese Haugdahl Nøst
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Torkjel M. Sandanger
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Tonje Braaten
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Beatrice Melin
- Department of Radiation Sciences, Oncology, Umeå University, Sweden
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Sweden
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Adams SJ, Stone E, Baldwin DR, Vliegenthart R, Lee P, Fintelmann FJ. Lung cancer screening. Lancet 2023; 401:390-408. [PMID: 36563698 DOI: 10.1016/s0140-6736(22)01694-4] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 07/26/2022] [Accepted: 08/25/2022] [Indexed: 12/24/2022]
Abstract
Randomised controlled trials, including the National Lung Screening Trial (NLST) and the NELSON trial, have shown reduced mortality with lung cancer screening with low-dose CT compared with chest radiography or no screening. Although research has provided clarity on key issues of lung cancer screening, uncertainty remains about aspects that might be critical to optimise clinical effectiveness and cost-effectiveness. This Review brings together current evidence on lung cancer screening, including an overview of clinical trials, considerations regarding the identification of individuals who benefit from lung cancer screening, management of screen-detected findings, smoking cessation interventions, cost-effectiveness, the role of artificial intelligence and biomarkers, and current challenges, solutions, and opportunities surrounding the implementation of lung cancer screening programmes from an international perspective. Further research into risk models for patient selection, personalised screening intervals, novel biomarkers, integrated cardiovascular disease and chronic obstructive pulmonary disease assessments, smoking cessation interventions, and artificial intelligence for lung nodule detection and risk stratification are key opportunities to increase the efficiency of lung cancer screening and ensure equity of access.
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Affiliation(s)
- Scott J Adams
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Emily Stone
- Faculty of Medicine, University of New South Wales and Department of Lung Transplantation and Thoracic Medicine, St Vincent's Hospital, Sydney, NSW, Australia
| | - David R Baldwin
- Respiratory Medicine Unit, David Evans Research Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | | | - Pyng Lee
- Division of Respiratory and Critical Care Medicine, National University Hospital and National University of Singapore, Singapore
| | - Florian J Fintelmann
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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7
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Duarte A, Corbett M, Melton H, Harden M, Palmer S, Soares M, Simmonds M. EarlyCDT Lung blood test for risk classification of solid pulmonary nodules: systematic review and economic evaluation. Health Technol Assess 2022; 26:1-184. [PMID: 36534989 PMCID: PMC9791464 DOI: 10.3310/ijfm4802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND EarlyCDT Lung (Oncimmune Holdings plc, Nottingham, UK) is a blood test to assess malignancy risk in people with solid pulmonary nodules. It measures the presence of seven lung cancer-associated autoantibodies. Elevated levels of these autoantibodies may indicate malignant disease. The results of the test might be used to modify the risk of malignancy estimated by existing risk calculators, including the Brock and Herder models. OBJECTIVES The objectives were to determine the diagnostic accuracy, clinical effectiveness and cost-effectiveness of EarlyCDT Lung; and to develop a conceptual model and identify evidence requirements for a robust cost-effectiveness analysis. DATA SOURCES MEDLINE (including Epub Ahead of Print, In-Process & Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE), EMBASE, Cochrane Central Register of Controlled Trials, Science Citation Index, EconLit, Cochrane Database of Systematic Reviews, Database of Abstracts of Reviews of Effects, Health Technology Assessment database, NHS Economic Evaluation Database ( NHS EED ) and the international Health Technology Assessment database were searched on 8 March 2021. REVIEW METHODS A systematic review was performed of evidence on EarlyCDT Lung, including diagnostic accuracy, clinical effectiveness and cost-effectiveness. Study quality was assessed with the quality assessment of diagnostic accuracy studies-2 tool. Evidence on other components of the pulmonary nodule diagnostic pathway (computerised tomography surveillance, Brock risk, Herder risk, positron emission tomography-computerised tomography and biopsy) was also reviewed. When feasible, bivariate meta-analyses of diagnostic accuracy were performed. Clinical outcomes were synthesised narratively. A simulation study investigated the clinical impact of using EarlyCDT Lung. Additional reviews of cost-effectiveness studies evaluated (1) other diagnostic strategies for lung cancer and (2) screening approaches for lung cancer. A conceptual model was developed. RESULTS A total of 47 clinical publications on EarlyCDT Lung were identified, but only five cohorts (695 patients) reported diagnostic accuracy data on patients with pulmonary nodules. All cohorts were small or at high risk of bias. EarlyCDT Lung on its own was found to have poor diagnostic accuracy, with a summary sensitivity of 20.2% (95% confidence interval 10.5% to 35.5%) and specificity of 92.2% (95% confidence interval 86.2% to 95.8%). This sensitivity was substantially lower than that estimated by the manufacturer (41.3%). No evidence on the clinical impact of EarlyCDT Lung was identified. The simulation study suggested that EarlyCDT Lung might potentially have some benefit when considering intermediate risk nodules (10-70% risk) after Herder risk analysis. Two cost-effectiveness studies on EarlyCDT Lung for pulmonary nodules were identified; none was considered suitable to inform the current decision problem. The conceptualisation process identified three core components for a future cost-effectiveness assessment of EarlyCDT Lung: (1) the features of the subpopulations and relevant heterogeneity, (2) the way EarlyCDT Lung test results affect subsequent clinical management decisions and (3) how changes in these decisions can affect outcomes. All reviewed studies linked earlier diagnosis to stage progression and stage shift to final outcomes, but evidence on these components was sparse. LIMITATIONS The evidence on EarlyCDT Lung among patients with pulmonary nodules was very limited, preventing meta-analyses and economic analyses. CONCLUSIONS The evidence on EarlyCDT Lung among patients with pulmonary nodules is insufficient to draw any firm conclusions as to its diagnostic accuracy or clinical or economic value. FUTURE WORK Prospective cohort studies, in which EarlyCDT Lung is used among patients with identified pulmonary nodules, are required to support a future assessment of the clinical and economic value of this test. Studies should investigate the diagnostic accuracy and clinical impact of EarlyCDT Lung in combination with Brock and Herder risk assessments. A well-designed cost-effectiveness study is also required, integrating emerging relevant evidence with the recommendations in this report. STUDY REGISTRATION This study is registered as PROSPERO CRD42021242248. FUNDING This project was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 49. See the NIHR Journals Library website for further project information.
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Affiliation(s)
- Ana Duarte
- Centre for Health Economics, University of York, York UK
| | - Mark Corbett
- Centre for Reviews and Dissemination, University of York, York UK
| | - Hollie Melton
- Centre for Reviews and Dissemination, University of York, York UK
| | - Melissa Harden
- Centre for Reviews and Dissemination, University of York, York UK
| | - Stephen Palmer
- Centre for Health Economics, University of York, York UK
| | - Marta Soares
- Centre for Health Economics, University of York, York UK
| | - Mark Simmonds
- Centre for Reviews and Dissemination, University of York, York UK
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He T, Wu Z, Xia P, Wang W, Sun H, Yu L, Lv W, Hu J. The combination of a seven-autoantibody panel with computed tomography scanning can enhance the diagnostic efficiency of non-small cell lung cancer. Front Oncol 2022; 12:1047019. [DOI: 10.3389/fonc.2022.1047019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 11/04/2022] [Indexed: 12/05/2022] Open
Abstract
BackgroundNon-small cell lung cancer (NSCLC) is still of concern in differentiating it from benign disease. This study aims to validate the diagnostic efficacy of a novel seven-autoantibody (7-AAB) panel for the diagnosis of NSCLC.MethodsWe retrospectively enrolled 2650 patients who underwent both the 7-AAB panel test and CT scanning. We compared the sensitivity, specificity, and PPV of 7-AAB, CT, and PET-CT in the diagnosis of NSCLC in different subgroups. Then, we established a nomogram based on CT image features and the 7-AAB panel to further improve diagnostic efficiency. Moreover, we compared the pathological and molecular results of NSCLC patients in the 7-AABs positive group and the negative group to verify the prognostic value of the 7-AAB panel.ResultsThe strategy of a “both-positive rule” combination of 7-AABs and CT had a specificity of 95.4% and a positive predictive value (PPV) of 95.8%, significantly higher than those of CT or PET-CT used alone (P<0.05). The nomogram we established has passed the calibration test (P=0.987>0.05) with an AUC of 0.791. Interestingly, it was found that the 7-AABs positive group was associated with higher proportion of EGFR mutations (P<0.001), lower pathological differentiation degrees (P=0.018), more advanced pathological stages (P=0.040) and higher Ki-67 indexes (P=0.011) in patients with adenocarcinoma.ConclusionThis study shows that combination of a 7-AAB panel with CT has can significantly enhance the diagnostic efficiency of lung cancer. Moreover, the 7-AAB panel also has potential prognostic value and has reference significance for the formulation of the treatment plan.
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Bonney A, Malouf R, Marchal C, Manners D, Fong KM, Marshall HM, Irving LB, Manser R. Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality. Cochrane Database Syst Rev 2022; 8:CD013829. [PMID: 35921047 PMCID: PMC9347663 DOI: 10.1002/14651858.cd013829.pub2] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT). OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening. SEARCH METHODS We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021. SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes. DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity. MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years. None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence). Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence). False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour. AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.
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Affiliation(s)
- Asha Bonney
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Reem Malouf
- National Perinatal Epidemiology Unit (NPEU), University of Oxford, Oxford, UK
| | | | - David Manners
- Respiratory Medicine, Midland St John of God Public and Private Hospital, Midland, Australia
| | - Kwun M Fong
- Thoracic Medicine Program, The Prince Charles Hospital, Brisbane, Australia
- UQ Thoracic Research Centre, School of Medicine, The University of Queensland, Brisbane, Australia
| | - Henry M Marshall
- School of Medicine, The University of Queensland, Brisbane, Australia
| | - Louis B Irving
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
| | - Renée Manser
- Department of Respiratory and Sleep Medicine, Royal Melbourne Hospital, Parkville, Australia
- Department of Haematology and Medical Oncology, Peter MacCallum Cancer Centre, Melbourne, Australia
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Li C, Wang H, Jiang Y, Fu W, Liu X, Zhong R, Cheng B, Zhu F, Xiang Y, He J, Liang W. Advances in lung cancer screening and early detection. Cancer Biol Med 2022; 19:j.issn.2095-3941.2021.0690. [PMID: 35535966 PMCID: PMC9196057 DOI: 10.20892/j.issn.2095-3941.2021.0690] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/03/2022] [Indexed: 11/18/2022] Open
Abstract
Lung cancer is associated with a heavy cancer-related burden in terms of patients' physical and mental health worldwide. Two randomized controlled trials, the US-National Lung Screening Trial (NLST) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON), indicated that low-dose CT (LDCT) screening results in a statistically significant decrease in mortality in patients with lung cancer, LDCT has become the standard approach for lung cancer screening. However, many issues in lung cancer screening remain unresolved, such as the screening criteria, high false-positive rate, and radiation exposure. This review first summarizes recent studies on lung cancer screening from the US, Europe, and Asia, and discusses risk-based selection for screening and the related issues. Second, an overview of novel techniques for the differential diagnosis of pulmonary nodules, including artificial intelligence and molecular biomarker-based screening, is presented. Third, current explorations of strategies for suspected malignancy are summarized. Overall, this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.
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Affiliation(s)
- Caichen Li
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Huiting Wang
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Yu Jiang
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Wenhai Fu
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
| | - Xiwen Liu
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Ran Zhong
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Bo Cheng
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
| | - Feng Zhu
- Department of Internal Medicine, Detroit Medical Center Sinai-Grace Hospital, Detroit, Michigan 48235, USA
| | - Yang Xiang
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
| | - Jianxing He
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
- Department of Thoracic Surgery, Nanfang Hospital of Southern Medical University, Guangzhou 510515, China
| | - Wenhua Liang
- Department of Thoracic Oncology and Surgery, the First Affiliated Hospital of Guangzhou Medical University, China National Center for Respiratory Medicine, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou 510120, China
- Dongguan Affiliated Hospital of Southern Medical University, Dongguan People Hospital, Dongguan 523059, China
- Department of Oncology, the First People’s Hospital of Zhaoqing, Zhaoqing 526020, China
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11
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Temporal reproducibility of IgG and IgM autoantibodies in serum from healthy women. Sci Rep 2022; 12:6192. [PMID: 35418192 PMCID: PMC9008031 DOI: 10.1038/s41598-022-10174-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 03/30/2022] [Indexed: 11/09/2022] Open
Abstract
Autoantibodies are present in healthy individuals and altered in chronic diseases. We used repeated samples collected from participants in the NYU Women's Health Study to assess autoantibody reproducibility and repertoire stability over a one-year period using the HuProt array. We included two samples collected one year apart from each of 46 healthy women (92 samples). We also included eight blinded replicate samples to assess laboratory reproducibility. A total of 21,211 IgG and IgM autoantibodies were interrogated. Of those, 86% of IgG (n = 18,303) and 34% of IgM (n = 7,242) autoantibodies showed adequate lab reproducibility (coefficient of variation [CV] < 20%). Intraclass correlation coefficients (ICCs) were estimated to assess temporal reproducibility. A high proportion of both IgG and IgM autoantibodies with CV < 20% (76% and 98%, respectively) showed excellent temporal reproducibility (ICC > 0.8). Temporal reproducibility was lower after using quantile normalization suggesting that batch variability was not an important source of error, and that normalization removed some informative biological information. To our knowledge this study is the largest in terms of sample size and autoantibody numbers to assess autoantibody reproducibility in healthy women. The results suggest that for many autoantibodies a single measurement may be used to rank individuals in studies of autoantibodies as etiologic markers of disease.
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12
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Wang Y, Jiao Y, Ding CM, Sun WZ. The role of autoantibody detection in the diagnosis and staging of lung cancer. ANNALS OF TRANSLATIONAL MEDICINE 2022; 9:1673. [PMID: 34988182 PMCID: PMC8667094 DOI: 10.21037/atm-21-5357] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 11/09/2021] [Indexed: 01/19/2023]
Abstract
Background Previously, the clinical value of seven autoantibodies (p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1, and CAGE) has been surveyed in our pilot observation and other published studies. Herein, we aimed to further investigate the role of these autoantibodies in the diagnosis and staging of LC. Methods We included a total of 135 individuals, who were divided into a Lung cancer (LC) group and a control group according to the final diagnosis. Seven autoantibody detection kits were used (ELISA method) for the expression measurement. The patients’ demographics information (e.g., age, gender, and smoking history) were also documented. Results Among the seven types of autoantibodies, only P53 and GBU4-5 were significantly increased in the LC group compared to the controls. Also, the P53 autoantibody was markedly different among the various subtype groups. Meanwhile, the GBU4-5 level was significantly higher in the small cell lung cancer (SCLC) patients compared to patients with adenocarcinoma (ADC). Autoantibodies against PGP9.5, SOX2, GBU4-5, and CAGE were found to be associated with stages. Their expressions were notably higher in the advanced stage (IV) versus early stages (I–II). Using logistic regression, the outcomes of LC prediction and stage prediction showed that the area under curve (AUCs) of the receiver operating characteristic (ROC) curves were 0.743 and 0.798, respectively. Conclusions In summary, our study confirmed the diagnostic value of tumor-associated autoantibodies, which may be useful as latent tumor markers to facilitate the detection of early LC. Single autoantibody testing is not yet sufficient in LC cancer screening, and the combined detection of autoantibodies can improve the sensitivity of detection compared with single antibody detection, especially for P53, PGP9.5, SOX2, GBU4-5, and CAGE autoantibodies.
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Affiliation(s)
- Yun Wang
- Department of Respiratory Medicine, the Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yang Jiao
- Hebei Medical University, Shijiazhuang, China
| | - Cui-Min Ding
- Department of Respiratory Medicine, the Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wu-Zhuang Sun
- Department of Respiratory Medicine, The First Hospital of Hebei Medical University, Shijiazhuang, China
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Chen P, Lu W, Chen T. Seven tumor-associated autoantibodies as a serum biomarker for primary screening of early-stage non-small cell lung cancer. J Clin Lab Anal 2021; 35:e24020. [PMID: 34555232 PMCID: PMC8605152 DOI: 10.1002/jcla.24020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 09/01/2021] [Accepted: 09/09/2021] [Indexed: 02/06/2023] Open
Abstract
Objective The purpose of this study was to analyze the levels of tumor‐associated autoantibodies (TAAbs) in lung diseases and determine their diagnostic efficiency in early‐stage non‐small cell lung cancer (NSCLC). Methods We retrospectively analyzed the levels of 7‐TAAbs in 177 newly diagnosed early‐stage NSCLC patients, 202 patients with lung benign diseases and 137 healthy cases. The levels of a panel of 7‐TAAbs, including p53, GAGE7, PGP9.5, CAGE, MAGE A1, SOX2, GBU4‐5, were measured by ELISA. Results The serum levels of p53, GAGE7, PGP9.5, CAGE, MAGE A1, SOX2, and GBU4‐5 were not statistically different among NSCLC, benign and healthy groups (p > 0.05). The area under the curve (AUC) of 7‐TAAbs was all lower than 0.70. The sensitivity of combined detection was the highest (23.73%), while the specificity was the lowest (88.79%). The positive rates of PGP9.5, SOX2, and combined detection were significantly different among the three groups (p < 0.05). Among them, PGP9.5 and combined detection were significantly different between the NSCLC and benign groups (p < 0.05), PGP9.5, SOX2 and combined detection were significantly different between the NSCLC and healthy groups (p < 0.05). Conclusions The diagnostic efficiency of 7‐TAAbs in early‐stage NSCLC was not high, so it cannot be used alone as a screening method for NSCLC.
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Affiliation(s)
- Ping Chen
- Medical Laboratory, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Wei Lu
- Medical Laboratory, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
| | - Tingting Chen
- Medical Laboratory, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Traditional Chinese Medicine), Hangzhou, China
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Borg M, Wen SWC, Nederby L, Hansen TF, Jakobsen A, Andersen RF, Weinreich UM, Hilberg O. Performance of the EarlyCDT® Lung test in detection of lung cancer and pulmonary metastases in a high-risk cohort. Lung Cancer 2021; 158:85-90. [PMID: 34130044 DOI: 10.1016/j.lungcan.2021.06.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 06/02/2021] [Accepted: 06/07/2021] [Indexed: 12/17/2022]
Abstract
OBJECTIVES Early detection of lung cancer is pivotal for an optimal prognosis. CT screening is currently implemented in USA. To decrease the amount of CT scans, the application of a blood-based biomarker as part of screening criteria is desirable. MATERIALS AND METHODS The EarlyCDT® Lung test was performed in a high-risk cohort composed 246 patients referred from their GP on suspicion of lung cancer. Blood samples were taken at first visit and patients underwent diagnostic workup on suspicion of lung cancer resulting in either a malignant diagnosis or ruled out cancer. Sensitivity and specificity of the EarlyCDT® Lung were calculated in the cohort and subgroups based on age, smoking history, sex and lung cancer stage. RESULTS Overall sensitivity in the cohort was 33 % for lung cancer and 31 % for primary lung cancer and lung metastases combined. Sensitivity in age groups was 11 % (60 years or below), 31 % (61-75 years) and 55 % (>75 years). In patients with at least 10 tobacco pack years, sensitivity was 33 % while the sensitivity in patients with at least 50 tobacco pack years was 44 %. The assay sensitivity in stage I-II lung cancer patients was 21 %, while this was 40 % in stage III-IV lung cancer patients. In a subgroup of patients that met current CT screening criteria (age 55-80 years and minimum 30 tobacco pack years) the sensitivity was 37 %. CONCLUSION The rationale of screening for lung cancer is to find patients in an early and resectable stage. However, the EarlyCDT® Lung test performed best in elderly, late stage lung cancer patients with a heavy smoking history. Based on these results, the current study finds insufficient sensitivity of the EarlyCDT® Lung test to be used as part of inclusion criteria in a low-dose CT program for detection of lung cancer.
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Affiliation(s)
- Morten Borg
- Department of Respiratory Diseases, Aalborg University Hospital, Mølleparkvej 4, 9000 Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Søndre Skovvej 15, 9000 Aalborg, Denmark.
| | - Sara W C Wen
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark; Institute of Regional Health Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000 Odense C, Denmark.
| | - Line Nederby
- Department of Clinical Biochemistry, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark.
| | - Torben Frøstrup Hansen
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark; Institute of Regional Health Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000 Odense C, Denmark.
| | - Anders Jakobsen
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark; Institute of Regional Health Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000 Odense C, Denmark.
| | - Rikke Fredslund Andersen
- Department of Clinical Biochemistry, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark.
| | - Ulla Møller Weinreich
- Department of Respiratory Diseases, Aalborg University Hospital, Mølleparkvej 4, 9000 Aalborg, Denmark; Department of Clinical Medicine, Aalborg University, Søndre Skovvej 15, 9000 Aalborg, Denmark.
| | - Ole Hilberg
- Institute of Regional Health Research, University of Southern Denmark, J.B. Winsløws Vej 19, 3, 5000 Odense C, Denmark; Department of Internal Medicine, Vejle Hospital, University Hospital of Southern Denmark, Beriderbakken 4, 7100 Vejle, Denmark.
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Ten Haaf K, van der Aalst CM, de Koning HJ, Kaaks R, Tammemägi MC. Personalising lung cancer screening: An overview of risk-stratification opportunities and challenges. Int J Cancer 2021; 149:250-263. [PMID: 33783822 PMCID: PMC8251929 DOI: 10.1002/ijc.33578] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 03/04/2021] [Accepted: 03/12/2021] [Indexed: 12/17/2022]
Abstract
Randomised clinical trials have shown the efficacy of computed tomography lung cancer screening, initiating discussions on whether and how to implement population‐based screening programs. Due to smoking behaviour being the primary risk‐factor for lung cancer and part of the criteria for determining screening eligibility, lung cancer screening is inherently risk‐based. In fact, the selection of high‐risk individuals has been shown to be essential in implementing lung cancer screening in a cost‐effective manner. Furthermore, studies have shown that further risk‐stratification may improve screening efficiency, allow personalisation of the screening interval and reduce health disparities. However, implementing risk‐based lung cancer screening programs also requires overcoming a number of challenges. There are indications that risk‐based approaches can negatively influence the trade‐off between individual benefits and harms if not applied thoughtfully. Large‐scale implementation of targeted, risk‐based screening programs has been limited thus far. Consequently, questions remain on how to efficiently identify and invite high‐risk individuals from the general population. Finally, while risk‐based approaches may increase screening program efficiency, efficiency should be balanced with the overall impact of the screening program. In this review, we will address the opportunities and challenges in applying risk‐stratification in different aspects of lung cancer screening programs, as well as the balance between screening program efficiency and impact.
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Affiliation(s)
- Kevin Ten Haaf
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Carlijn M van der Aalst
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Harry J de Koning
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Translational Lung Research Center (TLRC) Heidelberg, Member of the German Center for Lung Research (DZL), Heidelberg, Germany
| | - Martin C Tammemägi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada
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