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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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Amicizia D, Piazza MF, Marchini F, Astengo M, Grammatico F, Battaglini A, Schenone I, Sticchi C, Lavieri R, Di Silverio B, Andreoli GB, Ansaldi F. Systematic Review of Lung Cancer Screening: Advancements and Strategies for Implementation. Healthcare (Basel) 2023; 11:2085. [PMID: 37510525 PMCID: PMC10379173 DOI: 10.3390/healthcare11142085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/12/2023] [Accepted: 07/12/2023] [Indexed: 07/30/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths in Europe, with low survival rates primarily due to late-stage diagnosis. Early detection can significantly improve survival rates, but lung cancer screening is not currently implemented in Italy. Many countries have implemented lung cancer screening programs for high-risk populations, with studies showing a reduction in mortality. This review aimed to identify key areas for establishing a lung cancer screening program in Italy. A literature search was conducted in October 2022, using the PubMed and Scopus databases. Items of interest included updated evidence, approaches used in other countries, enrollment and eligibility criteria, models, cost-effectiveness studies, and smoking cessation programs. A literature search yielded 61 scientific papers, highlighting the effectiveness of low-dose computed tomography (LDCT) screening in reducing mortality among high-risk populations. The National Lung Screening Trial (NLST) in the United States demonstrated a 20% reduction in lung cancer mortality with LDCT, and other trials confirmed its potential to reduce mortality by up to 39% and detect early-stage cancers. However, false-positive results and associated harm were concerns. Economic evaluations generally supported the cost-effectiveness of LDCT screening, especially when combined with smoking cessation interventions for individuals aged 55 to 75 with a significant smoking history. Implementing a screening program in Italy requires the careful consideration of optimal strategies, population selection, result management, and the integration of smoking cessation. Resource limitations and tailored interventions for subpopulations with low-risk perception and non-adherence rates should be addressed with multidisciplinary expertise.
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Affiliation(s)
- Daniela Amicizia
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
- Department of Health Sciences (DiSSal), University of Genoa, 16132 Genoa, Italy
| | - Maria Francesca Piazza
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Francesca Marchini
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Matteo Astengo
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Federico Grammatico
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
- Department of Health Sciences (DiSSal), University of Genoa, 16132 Genoa, Italy
| | - Alberto Battaglini
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Irene Schenone
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Camilla Sticchi
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Rosa Lavieri
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Bruno Di Silverio
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Giovanni Battista Andreoli
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
| | - Filippo Ansaldi
- Regional Health Agency of Liguria (ALiSa), 16121 Genoa, Italy; (D.A.); (F.M.); (M.A.); (F.G.); (A.B.); (I.S.); (C.S.); (R.L.); (B.D.S.); (G.B.A.); (F.A.)
- Department of Health Sciences (DiSSal), University of Genoa, 16132 Genoa, Italy
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Toumazis I, Cao P, de Nijs K, Bastani M, Munshi V, Hemmati M, Ten Haaf K, Jeon J, Tammemägi M, Gazelle GS, Feuer EJ, Kong CY, Meza R, de Koning HJ, Plevritis SK, Han SS. Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis. Ann Intern Med 2023; 176:320-332. [PMID: 36745885 PMCID: PMC11025620 DOI: 10.7326/m22-2216] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. OBJECTIVE To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. DESIGN Comparative modeling analysis. DATA SOURCES National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. TARGET POPULATION 1960 U.S. birth cohort. TIME HORIZON 45 years. PERSPECTIVE U.S. health care sector. INTERVENTION Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. OUTCOME MEASURES Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. RESULTS OF BASE-CASE ANALYSIS Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). RESULTS OF SENSITIVITY ANALYSES Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. LIMITATION Risk models were restricted to age, sex, and smoking-related risk predictors. CONCLUSION Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. PRIMARY FUNDING SOURCE National Cancer Institute (NCI).
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Affiliation(s)
- Iakovos Toumazis
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
| | - Pianpian Cao
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
| | - Koen de Nijs
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Mehrad Bastani
- Feinstein Institutes for Medical Research, Northwell Health, Manhasset, New York (M.B.)
| | - Vidit Munshi
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
| | - Mehdi Hemmati
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas (I.T., M.H.)
| | - Kevin Ten Haaf
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan (P.C., J.J.)
| | - Martin Tammemägi
- Department of Health Sciences, Brock University, St. Catharines, Ontario, Canada (M.T.)
| | - G Scott Gazelle
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts (V.M., G.S.G.)
| | - Eric J Feuer
- Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland (E.J.F.)
| | - Chung Yin Kong
- Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York (C.Y.K.)
| | - Rafael Meza
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, and Department of Integrative Oncology, BC Cancer Research Institute, British Columbia, Canada (R.M.)
| | - Harry J de Koning
- Erasmus MC-University Medical Center, Rotterdam, the Netherlands (K. de N., K. ten H., H.J. de K.)
| | - Sylvia K Plevritis
- Department of Biomedical Data Sciences, Stanford University, Stanford, California (S.K.P.)
| | - Summer S Han
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California (S.S.H.)
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Voigt W, Prosch H, Silva M. Clinical Scores, Biomarkers and IT Tools in Lung Cancer Screening-Can an Integrated Approach Overcome Current Challenges? Cancers (Basel) 2023; 15:cancers15041218. [PMID: 36831559 PMCID: PMC9954060 DOI: 10.3390/cancers15041218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 02/05/2023] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
As most lung cancer (LC) cases are still detected at advanced and incurable stages, there are increasing efforts to foster detection at earlier stages by low dose computed tomography (LDCT) based LC screening. In this scoping review, we describe current advances in candidate selection for screening (selection phase), technical aspects (screening), and probability evaluation of malignancy of CT-detected pulmonary nodules (PN management). Literature was non-systematically assessed and reviewed for suitability by the authors. For the selection phase, we describe current eligibility criteria for screening, along with their limitations and potential refinements through advanced clinical scores and biomarker assessments. For LC screening, we discuss how the accuracy of computerized tomography (CT) scan reading might be augmented by IT tools, helping radiologists to cope with increasing workloads. For PN management, we evaluate the precision of follow-up scans by semi-automatic volume measurements of CT-detected PN. Moreover, we present an integrative approach to evaluate the probability of PN malignancy to enable safe decisions on further management. As a clear limitation, additional validation studies are required for most innovative diagnostic approaches presented in this article, but the integration of clinical risk models, current imaging techniques, and advancing biomarker research has the potential to improve the LC screening performance generally.
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Affiliation(s)
- Wieland Voigt
- Medical Innovation and Management, Steinbeis University Berlin, Ernst-Augustin-Strasse 15, 12489 Berlin, Germany
- Correspondence:
| | - Helmut Prosch
- Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, General Hospital, 1090 Vienna, Austria
| | - Mario Silva
- Scienze Radiologiche, Department of Medicine and Surgery (DiMeC), University of Parma, 43121 Parma, Italy
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Desperito E, Schwartz L, Capaccione KM, Collins BT, Jamabawalikar S, Peng B, Patrizio R, Salvatore MM. Chest CT for Breast Cancer Diagnosis. Life (Basel) 2022; 12:life12111699. [PMID: 36362854 PMCID: PMC9695285 DOI: 10.3390/life12111699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 09/22/2022] [Accepted: 10/12/2022] [Indexed: 12/02/2022] Open
Abstract
Background: We report the results of our retrospective analysis of the ability of standard chest CT scans to correctly diagnose cancer in the breast. Methods: Four hundred and fifty-three consecutive women with chest CT scans (contrast and non-contrast) preceding mammograms within one year comprise the study population. All chest CT images were reviewed by an experienced fellowship-trained chest radiologist and mammograms by an experienced fellowship-trained mammographer without the benefit of prior or ancillary studies; only four mammographic views were included for analysis. The size, location, and shape of breast masses were documented; on CT, the average Hounsfield units were measured. On both imaging modalities, the presence of lymphadenopathy, architectural distortion, skin thickening, and microcalcifications were recorded. Ultimately, the interpreting radiologist was asked to decide if a biopsy was indicated, and these recommendations were correlated with the patient’s outcome. Findings: Nineteen of four hundred and fifty-three patients had breast cancer at the time of the mammography. Breast masses were the most common finding on chest CT, leading to the recommendation for biopsy. Hounsfield units were the most important feature for discerning benign from malignant masses. CT sensitivity, specificity, and accuracy of CT for breast cancer detection was 84.21%, 99.3%, and 98.68% compared to 78.95%, 93.78%, and 93.16% for four-view mammography. Chest CT scans with or without contrast had similar outcomes for specificity and accuracy, but sensitivity was slightly less without contrast. Chest CT alone, without the benefit of prior exams and patient recall, correctly diagnosed cancer with a p-value of <0.0001 compared to mammography with the same limitations. Conclusion: Chest CT accurately diagnosed breast cancer with few false positives and negatives and did so without the need for patient recall for additional imaging.
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Affiliation(s)
- Elise Desperito
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Lawrence Schwartz
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Kathleen M. Capaccione
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Brian T. Collins
- Department of Radiation Oncology, University of South Florida Tampa General Hospital, Tampa, FL 33612, USA
| | - Sachin Jamabawalikar
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Boyu Peng
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Rebecca Patrizio
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
| | - Mary M. Salvatore
- Department of Radiology, Columbia University Irving Medical Center, New York, NY 10032, USA
- Correspondence:
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Hung RJ, Khodayari Moez E, Kim SJ, Budhathoki S, Brooks JD. Considerations of Biomarker Application for Cancer Continuum in the Era of Precision Medicine. CURR EPIDEMIOL REP 2022; 9:200-211. [DOI: 10.1007/s40471-022-00295-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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7
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Hung RJ. Biomarker-Based Lung Cancer Screening Eligibility: Implementation Considerations. Cancer Epidemiol Biomarkers Prev 2022; 31:698-701. [PMID: 35373266 PMCID: PMC10689115 DOI: 10.1158/1055-9965.epi-22-0099] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 02/10/2022] [Accepted: 02/15/2022] [Indexed: 12/17/2022] Open
Abstract
With the convergence of promising biomarkers for lung cancer risk stratifications, and the increasing need for better eligibility assessment for lung cancer low-dose CT (LDCT) screening, the elephant in the room now is whether and how the implementation of biomarker-based lung cancer screening eligibility can be successfully achieved. This brief commentary provides an outline of key considerations for biomarker implementations for LDCT eligibility assessment and possible mitigation strategies. See related article by Jacobsen et al., p. 758.
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Affiliation(s)
- Rayjean J. Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health
- Dalla Lana School of Public Health, University of Toronto
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