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Haaf KT, de Nijs K, Simoni G, Alban A, Cao P, Sun Z, Yong J, Jeon J, Toumazis I, Han SS, Gazelle GS, Kong CY, Plevritis SK, Meza R, de Koning HJ. The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations. Med Decis Making 2024; 44:497-511. [PMID: 38738534 PMCID: PMC11281869 DOI: 10.1177/0272989x241249182] [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: 05/14/2024]
Abstract
BACKGROUND Recommendations regarding personalized lung cancer screening are being informed by natural-history modeling. Therefore, understanding how differences in model assumptions affect model-based personalized screening recommendations is essential. DESIGN Five Cancer Intervention and Surveillance Modeling Network (CISNET) models were evaluated. Lung cancer incidence, mortality, and stage distributions were compared across 4 theoretical scenarios to assess model assumptions regarding 1) sojourn times, 2) stage-specific sensitivities, and 3) screening-induced lung cancer mortality reductions. Analyses were stratified by sex and smoking behavior. RESULTS Most cancers had sojourn times <5 y (model range [MR]; lowest to highest value across models: 83.5%-98.7% of cancers). However, cancer aggressiveness still varied across models, as demonstrated by differences in proportions of cancers with sojourn times <2 y (MR: 42.5%-64.6%) and 2 to 4 y (MR: 28.8%-43.6%). Stage-specific sensitivity varied, particularly for stage I (MR: 31.3%-91.5%). Screening reduced stage IV incidence in most models for 1 y postscreening; increased sensitivity prolonged this period to 2 to 5 y. Screening-induced lung cancer mortality reductions among lung cancers detected at screening ranged widely (MR: 14.6%-48.9%), demonstrating variations in modeled treatment effectiveness of screen-detected cases. All models assumed longer sojourn times and greater screening-induced lung cancer mortality reductions for women. Models assuming differences in cancer epidemiology by smoking behaviors assumed shorter sojourn times and lower screening-induced lung cancer mortality reductions for heavy smokers. CONCLUSIONS Model-based personalized screening recommendations are primarily driven by assumptions regarding sojourn times (favoring longer intervals for groups more likely to develop less aggressive cancers), sensitivity (higher sensitivities favoring longer intervals), and screening-induced mortality reductions (greater reductions favoring shorter intervals). IMPLICATIONS Models suggest longer screening intervals may be feasible and benefits may be greater for women and light smokers. HIGHLIGHTS Natural-history models are increasingly used to inform lung cancer screening, but causes for variations between models are difficult to assess.This is the first evaluation of these causes and their impact on personalized screening recommendations through easily interpretable metrics.Models vary regarding sojourn times, stage-specific sensitivities, and screening-induced lung cancer mortality reductions.Model outcomes were similar in predicting greater screening benefits for women and potentially light smokers. Longer screening intervals may be feasible for women and light smokers.
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Affiliation(s)
- Kevin ten Haaf
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Koen de Nijs
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Giulia Simoni
- Department of Biomedical Data Sciences, Stanford University, Stanford, California
| | - Andres Alban
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, Massachusetts
| | - Pianpian Cao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Zhuolu Sun
- Canadian Partnership Against Cancer, Toronto, ON, Canada
| | - Jean Yong
- Canadian Partnership Against Cancer, Toronto, ON, Canada
| | - Jihyoun Jeon
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Iakovos Toumazis
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Summer S. Han
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, California
| | - G. Scott Gazelle
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Chung Ying Kong
- Division of General Internal Medicine, Department of Medicine, Mount Sinai Hospital, New York, New York
| | - Sylvia K. Plevritis
- Department of Biomedical Data Sciences, Stanford University, Stanford, California
| | - Rafael Meza
- Department of Integrative Oncology, BC Cancer Research Institute, British Columbia, Canada
- School of Population and Public Health, University of British Columbia, British Columbia Canada
| | - Harry J. de Koning
- Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
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Benitez DA, Cumplido-Laso G, Olivera-Gómez M, Del Valle-Del Pino N, Díaz-Pizarro A, Mulero-Navarro S, Román-García A, Carvajal-Gonzalez JM. p53 Genetics and Biology in Lung Carcinomas: Insights, Implications and Clinical Applications. Biomedicines 2024; 12:1453. [PMID: 39062026 PMCID: PMC11274425 DOI: 10.3390/biomedicines12071453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Revised: 06/20/2024] [Accepted: 06/26/2024] [Indexed: 07/28/2024] Open
Abstract
The TP53 gene is renowned as a tumor suppressor, playing a pivotal role in overseeing the cell cycle, apoptosis, and maintaining genomic stability. Dysregulation of p53 often contributes to the initiation and progression of various cancers, including lung cancer (LC) subtypes. The review explores the intricate relationship between p53 and its role in the development and progression of LC. p53, a crucial tumor suppressor protein, exists in various isoforms, and understanding their distinct functions in LC is essential for advancing our knowledge of this deadly disease. This review aims to provide a comprehensive literature overview of p53, its relevance to LC, and potential clinical applications.
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Affiliation(s)
- Dixan A. Benitez
- Departamento de Bioquímica, Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06006 Badajoz, Spain; (G.C.-L.); (M.O.-G.); (N.D.V.-D.P.); (A.D.-P.); (S.M.-N.); (A.R.-G.)
| | | | | | | | | | | | | | - Jose Maria Carvajal-Gonzalez
- Departamento de Bioquímica, Biología Molecular y Genética, Facultad de Ciencias, Universidad de Extremadura, 06006 Badajoz, Spain; (G.C.-L.); (M.O.-G.); (N.D.V.-D.P.); (A.D.-P.); (S.M.-N.); (A.R.-G.)
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3
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Yang DW, Miller JA, Xue WQ, Tang M, Lei L, Zheng Y, Diao H, Wang TM, Liao Y, Wu YX, Zheng XH, Zhou T, Li XZ, Zhang PF, Chen XY, Yu X, Li F, Ji M, Sun Y, He YQ, Jia WH. Polygenic risk-stratified screening for nasopharyngeal carcinoma in high-risk endemic areas of China: a cost-effectiveness study. Front Public Health 2024; 12:1375533. [PMID: 38756891 PMCID: PMC11097958 DOI: 10.3389/fpubh.2024.1375533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 04/18/2024] [Indexed: 05/18/2024] Open
Abstract
Background Nasopharyngeal carcinoma (NPC) has an extremely high incidence rate in Southern China, resulting in a severe disease burden for the local population. Current EBV serologic screening is limited by false positives, and there is opportunity to integrate polygenic risk scores for personalized screening which may enhance cost-effectiveness and resource utilization. Methods A Markov model was developed based on epidemiological and genetic data specific to endemic areas of China, and further compared polygenic risk-stratified screening [subjects with a 10-year absolute risk (AR) greater than a threshold risk underwent EBV serological screening] to age-based screening (EBV serological screening for all subjects). For each initial screening age (30-34, 35-39, 40-44, 45-49, 50-54, 55-59, 60-64, and 65-69 years), a modeled cohort of 100,000 participants was screened until age 69, and then followed until age 79. Results Among subjects aged 30 to 54 years, polygenic risk-stratified screening strategies were more cost-effective than age-based screening strategies, and almost comprised the cost-effectiveness efficiency frontier. For men, screening strategies with a 1-year frequency and a 10-year absolute risk (AR) threshold of 0.7% or higher were cost-effective, with an incremental cost-effectiveness ratio (ICER) below the willingness to pay (¥203,810, twice the local per capita GDP). Specifically, the strategies with a 10-year AR threshold of 0.7% or 0.8% are the most cost-effective strategies, with an ICER ranging from ¥159,752 to ¥201,738 compared to lower-cost non-dominated strategies on the cost-effectiveness frontiers. The optimal strategies have a higher probability (29.4-35.8%) of being cost-effective compared to other strategies on the frontier. Additionally, they reduce the need for nasopharyngoscopies by 5.1-27.7% compared to optimal age-based strategies. Likewise, for women aged 30-54 years, the optimal strategy with a 0.3% threshold showed similar results. Among subjects aged 55 to 69 years, age-based screening strategies were more cost-effective for men, while no screening may be preferred for women. Conclusion Our economic evaluation found that the polygenic risk-stratified screening could improve the cost-effectiveness among individuals aged 30-54, providing valuable guidance for NPC prevention and control policies in endemic areas of China.
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Affiliation(s)
- Da-Wei Yang
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Jacob A. Miller
- Department of Radiation Oncology, Cleveland Clinic, Cleveland, OH, United States
| | - Wen-Qiong Xue
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | | | - Lin Lei
- Shenzhen Center for Chronic Disease Control, Shenzhen, China
| | - Yuming Zheng
- Wuzhou Red Cross Hospital, Wuzhou, Guangxi, China
| | - Hua Diao
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
| | - Tong-Min Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Ying Liao
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yan-Xia Wu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiao-Hui Zheng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Ting Zhou
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xi-Zhao Li
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Pei-Fen Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xue-Yin Chen
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xia Yu
- Cancer Research Institute of Zhongshan City, Zhongshan Hospital of Sun Yat-sen University, Zhongshan, China
| | - Fugui Li
- Cancer Research Institute of Zhongshan City, Zhongshan Hospital of Sun Yat-sen University, Zhongshan, China
| | - Mingfang Ji
- Cancer Research Institute of Zhongshan City, Zhongshan Hospital of Sun Yat-sen University, Zhongshan, China
| | - Ying Sun
- Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Department of Radiation Oncology, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Yong-Qiao He
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Wei-Hua Jia
- School of Public Health, Sun Yat-Sen University, Guangzhou, China
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou, China
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Liu Y, Xu H, Lv L, Wang X, Kang R, Guo X, Wang H, Zheng L, Liu H, Guo L, Chen Q, Liu S, Qiao Y, Zhang S. Risk-based lung cancer screening in heavy smokers: a benefit-harm and cost-effectiveness modeling study. BMC Med 2024; 22:73. [PMID: 38369461 PMCID: PMC10875747 DOI: 10.1186/s12916-024-03292-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 02/09/2024] [Indexed: 02/20/2024] Open
Abstract
BACKGROUND Annual screening through low-dose computed tomography (LDCT) is recommended for heavy smokers. However, it is questionable whether all individuals require annual screening given the potential harms of LDCT screening. This study examines the benefit-harm and cost-effectiveness of risk-based screening in heavy smokers and determines the optimal risk threshold for screening and risk-stratified screening intervals. METHODS We conducted a comparative cost-effectiveness analysis in China, using a cohort-based Markov model which simulated a lung cancer screening cohort of 19,146 heavy smokers aged 50 ~ 74 years old, who had a smoking history of at least 30 pack-years and were either current smokers or had quit for < 15 years. A total of 34 risk-based screening strategies, varying by different risk groups for screening eligibility and screening intervals (1-year, 2-year, 3-year, one-off, non-screening), were evaluated and were compared with annual screening for all heavy smokers (the status quo strategy). The analysis was undertaken from the health service perspective with a 30-year time horizon. The willingness-to-pay (WTP) threshold was adopted as three times the gross domestic product (GDP) of China in 2021 (CNY 242,928) per quality-adjusted life year (QALY) gained. RESULTS Compared with the status quo strategy, nine risk-based screening strategies were found to be cost-effective, with two of them even resulting in cost-saving. The most cost-effective strategy was the risk-based approach of annual screening for individuals with a 5-year risk threshold of ≥ 1.70%, biennial screening for individuals with a 5-year risk threshold of 1.03 ~ 1.69%, and triennial screening for individuals with a 5-year risk threshold of < 1.03%. This strategy had the highest incremental net monetary benefit (iNMB) of CNY 1032. All risk-based screening strategies were more efficient than the status quo strategy, requiring 129 ~ 656 fewer screenings per lung cancer death avoided, and 0.5 ~ 28 fewer screenings per life-year gained. The cost-effectiveness of risk-based screening was further improved when individual adherence to screening improved and individuals quit smoking after being screened. CONCLUSIONS Risk-based screening strategies are more efficient in reducing lung cancer deaths and gaining life years compared to the status quo strategy. Risk-stratified screening intervals can potentially balance long-term benefit-harm trade-offs and improve the cost-effectiveness of lung cancer screenings.
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Affiliation(s)
- Yin Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Huifang Xu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Lihong Lv
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Xiaoyang Wang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Ruihua Kang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Xiaoli Guo
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Hong Wang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Liyang Zheng
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Hongwei Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Lanwei Guo
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Qiong Chen
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Shuzheng Liu
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China
| | - Youlin Qiao
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
- Center for Global Health, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China.
| | - Shaokai Zhang
- Department of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
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5
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Tomonaga Y, de Nijs K, Bucher HC, de Koning H, Ten Haaf K. Cost-effectiveness of risk-based low-dose computed tomography screening for lung cancer in Switzerland. Int J Cancer 2024; 154:636-647. [PMID: 37792671 DOI: 10.1002/ijc.34746] [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: 03/16/2023] [Revised: 09/05/2023] [Accepted: 09/06/2023] [Indexed: 10/06/2023]
Abstract
Throughout Europe, computed tomography (CT) screening for lung cancer is in a phase of clinical implementation or reimbursement evaluation. To efficiently select individuals for screening, the use of lung cancer risk models has been suggested, but their incremental (cost-)effectiveness relative to eligibility based on pack-year criteria has not been thoroughly evaluated for a European setting. We evaluate the cost-effectiveness of pack-year and risk-based screening (PLCOm2012 model-based) strategies for Switzerland, which aided in informing the recommendations of the Swiss Cancer Screening Committee (CSC). We use the MISCAN (MIcrosimulation SCreening ANalysis)-Lung model to estimate benefits and harms of screening among individuals born 1940 to 1979 in Switzerland. We evaluate 1512 strategies, differing in the age ranges employed for screening, the screening interval and the strictness of the smoking requirements. We estimate risk-based strategies to be more cost-effective than pack-year-based screening strategies. The most efficient strategy compliant with CSC recommendations is biennial screening for ever-smokers aged 55 to 80 with a 1.6% PLCOm2012 risk. Relative to no screening this strategy is estimated to reduce lung cancer mortality by 11.0%, with estimated costs per Quality-Adjusted Life-Year (QALY) gained of €19 341, and a €1.990 billion 15-year budget impact. Biennial screening ages 55 to 80 for those with 20 pack-years shows a lower mortality reduction (10.5%) and higher cost per QALY gained (€20 869). Despite model uncertainties, our estimates suggest there may be cost-effective screening policies for Switzerland. Risk-based biennial screening ages 55 to 80 for those with ≥1.6% PLCOm2012 risk conforms to CSC recommendations and is estimated to be more efficient than pack-year-based alternatives.
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Affiliation(s)
- Yuki Tomonaga
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Koen de Nijs
- Department of Public Health, Erasmus MC: University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Heiner C Bucher
- Division of Clinical Epidemiology, Department of Clinical Research University Hospital Basel and University of Basel, Basel, Switzerland
| | - Harry de Koning
- Department of Public Health, Erasmus MC: University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Kevin Ten Haaf
- Department of Public Health, Erasmus MC: University Medical Center Rotterdam, Rotterdam, The Netherlands
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Resong PJ, Niu J, Duhon GF, Foxhall LE, Shete S, Volk RJ, Toumazis I. Acceptability of Personalized Lung Cancer Screening Program Among Primary Care Providers. Cancer Prev Res (Phila) 2024; 17:51-57. [PMID: 38212272 PMCID: PMC10926168 DOI: 10.1158/1940-6207.capr-23-0359] [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: 08/29/2023] [Revised: 12/05/2023] [Accepted: 01/10/2024] [Indexed: 01/13/2024]
Abstract
Current lung cancer screening (LCS) guidelines rely on age and smoking history. Despite its benefit, only 5%-15% of eligible patients receive LCS. Personalized screening strategies select individuals based on their lung cancer risk and may increase LCS's effectiveness. We assess current LCS practices and the acceptability of personalized LCS among primary care providers (PCP) in Texas. We surveyed 32,983 Texas-based PCPs on an existing network (Protocol 2019-1257; PI: Dr. Shete) and 300 attendees of the 2022 Texas Academy of Family Physicians (TAFP) conference. We analyzed the responses by subgroups of interest. Using nonparametric bootstrap, we derived an enriched dataset to develop logistic regression models to understand current LCS practices and acceptability of personalized LCS. Response rates were 0.3% (n = 91) and 15% (n = 60) for the 2019-1257 and TAFP surveys, respectively. Most (84%) respondents regularly assess LCS in their practice. Half of the respondents were interested in adopting personalized LCS. The majority (66%) of respondents expressed concerns regarding time availability with the personalized LCS. Most respondents would use biomarkers as an adjunct to assess eligibility (58%), or to help guide indeterminate clinical findings (63%). There is a need to enhance the engagement of Texas-based PCPs in LCS. Most of the respondents expressed interest in personalized LCS. Time availability was the main concern related to personalized LCS. Findings from this project highlight the need for better education of Texas-based PCPs on the benefits of LCS, and the development of efficient decision tools to ensure successful implementation of personalized LCS. PREVENTION RELEVANCE Personalized LCS facilitated by a risk model and/or a biomarker test is proposed as an alternative to existing programs. Acceptability of personalized approach among PCPs is unknown. The goal of this study is to assess the acceptability of personalized LCS among PCPs.
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Affiliation(s)
- Paul J Resong
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- University of Nevada, Reno School of Medicine
| | - Jiangong Niu
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Gabrielle F Duhon
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Lewis E Foxhall
- Department of Clinical Cancer Prevention, Division of OVP, Cancer Prevention and Population Sciences, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Sanjay Shete
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Robert J Volk
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Iakovos Toumazis
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
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Lam S, Bai C, Baldwin DR, Chen Y, Connolly C, de Koning H, Heuvelmans MA, Hu P, Kazerooni EA, Lancaster HL, Langs G, McWilliams A, Osarogiagbon RU, Oudkerk M, Peters M, Robbins HA, Sahar L, Smith RA, Triphuridet N, Field J. Current and Future Perspectives on Computed Tomography Screening for Lung Cancer: A Roadmap From 2023 to 2027 From the International Association for the Study of Lung Cancer. J Thorac Oncol 2024; 19:36-51. [PMID: 37487906 PMCID: PMC11253723 DOI: 10.1016/j.jtho.2023.07.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/13/2023] [Accepted: 07/18/2023] [Indexed: 07/26/2023]
Abstract
Low-dose computed tomography (LDCT) screening for lung cancer substantially reduces mortality from lung cancer, as revealed in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer, which focuses on the major themes pertinent to the successful global implementation of LDCT screening and develops a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year roadmap to advance the implementation of LDCT screening globally, including the following: (1) establish universal screening program quality indicators; (2) establish evidence-based criteria to identify individuals who have never smoked but are at high-risk of developing lung cancer; (3) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (4) Integrate artificial intelligence and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (5) standardize high-quality performance artificial intelligence protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (6) personalize CT screening intervals on the basis of an individual's lung cancer risk; (7) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (8) develop publicly accessible, easy-to-use geospatial tools to plan and monitor equitable access to screening services; and (9) establish a global shared education resource for lung cancer screening CT to ensure high-quality reading and reporting.
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Affiliation(s)
- Stephen Lam
- Department of Integrative Oncology, British Columbia Cancer Research Institute, Vancouver, British Columbia, Canada; Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.
| | - Chunxue Bai
- Shanghai Respiratory Research Institute and Chinese Alliance Against Cancer, Shanghai, People's Republic of China
| | - David R Baldwin
- Nottingham University Hospitals National Health Services (NHS) Trust, Nottingham, United Kingdom
| | - Yan Chen
- Digital Screening, Faculty of Medicine & Health Sciences, University of Nottingham Medical School, Nottingham, United Kingdom
| | - Casey Connolly
- International Association for the Study of Lung Cancer, Denver, Colorado
| | - Harry de Koning
- Department of Public Health, Erasmus MC University Medical Centre Rotterdam, The Netherlands
| | - Marjolein A Heuvelmans
- University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Ping Hu
- Division of Cancer Prevention, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Ella A Kazerooni
- Division of Cardiothoracic Radiology, Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan; Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Harriet L Lancaster
- University of Groningen, Groningen, The Netherlands; Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands; The Institute for Diagnostic Accuracy, Groningen, The Netherlands
| | - Georg Langs
- Computational Imaging Research Laboratory, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Annette McWilliams
- Department of Respiratory Medicine, Fiona Stanley Hospital, Murdoch, Western Australia, Australia; Australia University of Western Australia, Nedlands, Western Australia
| | | | - Matthijs Oudkerk
- Center for Medical Imaging and The Institute for Diagnostic Accuracy, Faculty of Medical Sciences, University of Groningen, Groningen, The Netherlands
| | - Matthew Peters
- Woolcock Institute of Respiratory Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Liora Sahar
- Data Science, American Cancer Society, Atlanta, Georgia
| | - Robert A Smith
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia
| | | | - John Field
- Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, Liverpool, United Kingdom
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Meza R, Cao P, de Nijs K, Jeon J, Smith RA, ten Haaf K, de Koning H. Assessing the impact of increasing lung screening eligibility by relaxing the maximum years-since-quit threshold: A simulation modeling study. Cancer 2024; 130:244-255. [PMID: 37909874 PMCID: PMC11188688 DOI: 10.1002/cncr.34925] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 04/10/2023] [Accepted: 05/02/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND In 2021, the US Preventive Services Task Force expanded its lung screening recommendation to include persons aged 50-80 years who had ever smoked and had at least 20 pack-years of exposure and less than 15 years since quitting (YSQ). However, studies have suggested that screening persons who formerly smoked with longer YSQ could be beneficial. METHODS The authors used two validated lung cancer models to assess the benefits and harms of screening using various YSQ thresholds (10, 15, 20, 25, 30, and no YSQ) and the age at which screening was stopped. The impact of enforcing the YSQ criterion only at entry, but not at exit, also was evaluated. Outcomes included the number of screens, the percentage ever screened, screening benefits (lung cancer deaths averted, life-years gained), and harms (false-positive tests, overdiagnosed cases, radiation-induced lung cancer deaths). Sensitivity analyses were conducted to evaluate the effect of restricting screening to those who had at least 5 years of life expectancy. RESULTS As the YSQ criterion was relaxed, the number of screens and the benefits and harms of screening increased. Raising the age at which to stop screening age resulted in additional benefits but with more overdiagnosis, as expected, because screening among those older than 80 years increased. Limiting screening to those who had at least 5 years of life expectancy would maintain most of the benefits while considerably reducing the harms. CONCLUSIONS Expanding screening to persons who formerly smoked and have greater than 15 YSQ would result in considerable increases in deaths averted and life-years gained. Although additional harms would occur, these could be moderated by ensuring that screening is restricted to only those with reasonable life expectancy.
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Affiliation(s)
- Rafael Meza
- Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Pianpian Cao
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Koen de Nijs
- Erasmus MC–University Medical Center, Rotterdam, The Netherlands
| | - Jihyoun Jeon
- Department of Epidemiology, University of Michigan, Ann Arbor, MI
| | - Robert A. Smith
- Early Cancer Detection Science Department, American Cancer Society, Atlanta, GA
| | - Kevin ten Haaf
- Erasmus MC–University Medical Center, Rotterdam, The Netherlands
| | - Harry de Koning
- Erasmus MC–University Medical Center, Rotterdam, The Netherlands
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Skurla SE, Leishman NJ, Fagerlin A, Wiener RS, Lowery J, Caverly TJ. Clinician Perceptions on Using Decision Tools to Support Prediction-Based Shared Decision Making for Lung Cancer Screening. MDM Policy Pract 2024; 9:23814683241252786. [PMID: 38779527 PMCID: PMC11110512 DOI: 10.1177/23814683241252786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024] Open
Abstract
Background Considering a patient's full risk factor profile can promote personalized shared decision making (SDM). One way to accomplish this is through encounter tools that incorporate prediction models, but little is known about clinicians' perceptions of the feasibility of using these tools in practice. We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS). Design We conducted a qualitative study based on field notes from academic detailing visits during a multisite quality improvement program. The detailer engaged one-on-one with 96 primary care clinicians across multiple Veterans Affairs sites (7 medical centers and 6 outlying clinics) to get feedback on 1) the rationale for prediction-based LCS and 2) how to use the DecisionPrecision (DP) encounter tool with eligible patients to personalize LCS discussions. Results Thematic content analysis from detailing visit data identified 6 categories of clinician willingness to use the DP tool to personalize SDM for LCS (adoption potential), varying from "Enthusiastic Potential Adopter" (n = 18) to "Definite Non-Adopter" (n = 16). Many clinicians (n = 52) articulated how they found the concept of prediction-based SDM highly appealing. However, to varying degrees, nearly all clinicians identified challenges to incorporating such an approach in routine practice. Limitations The results are based on the clinician's initial reactions rather than longitudinal experience. Conclusions While many primary care clinicians saw real value in using prediction to personalize LCS decisions, more support is needed to overcome barriers to using encounter tools in practice. Based on these findings, we propose several strategies that may facilitate the adoption of prediction-based SDM in contexts such as LCS. Highlights Encounter tools that incorporate prediction models promote personalized shared decision making (SDM), but little is known about clinicians' perceptions of the feasibility of using these tools in practice.We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).While many clinicians found the concept of prediction-based SDM highly appealing, nearly all clinicians identified challenges to incorporating such an approach in routine practice.We propose several strategies to overcome adoption barriers and facilitate the use of prediction-based SDM in contexts such as LCS.
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Affiliation(s)
- Sarah E. Skurla
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
| | | | - Angela Fagerlin
- University of Utah School of Medicine, Salt Lake City, UT, USA
- Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, VA Salt Lake City Healthcare System, Salt Lake City, UT, USA
| | - Renda Soylemez Wiener
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, MA, USA
- The Pulmonary Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Julie Lowery
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
| | - Tanner J. Caverly
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
- Department of Learning Health Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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10
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Wu JTY, Wakelee HA, Han SS. Optimizing Lung Cancer Screening With Risk Prediction: Current Challenges and the Emerging Role of Biomarkers. J Clin Oncol 2023; 41:4341-4347. [PMID: 37540816 PMCID: PMC10522111 DOI: 10.1200/jco.23.01060] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 05/24/2023] [Accepted: 06/15/2023] [Indexed: 08/06/2023] Open
Abstract
The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.Lung cancer screening has been demonstrated to reduce lung cancer mortality, but its benefits must be weighed against the potential harms of unnecessary procedures, false-positive radiological findings, and overdiagnosis. Individuals at highest risk of lung cancer are more likely to maximize benefits while minimizing harm from screening. Although current lung cancer screening guidelines recommended by the US Preventive Services Task Force (USPSTF) only consider age and smoking history for screening eligibility, National Comprehensive Cancer Network and other society guidelines recommend screening on the basis of individualized risk assessment including family history, environmental exposures, and presence of chronic lung disease. Risk prediction models have been developed to integrate various risk factors into an individualized risk prediction score. Previous evidence showed that risk prediction model-based screening eligibility could improve sensitivity for detecting lung cancer cases without reducing specificity. Furthermore, recent advances in lung cancer biomarkers have enhanced the performance of risk prediction in identifying lung cancer cases relative to the USPSTF criteria. These risk prediction models can be used to guide shared decision-making discussions before proceeding with lung cancer screening. This study aims to provide a concise overview of these prediction models and the emerging role of biomarker testing in risk prediction to facilitate conversations with patients. The goal was to assist clinicians in assessing individual patient risk, leading to more informed decision making.
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Affiliation(s)
- Julie Tsu-yu Wu
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA
| | - Heather A. Wakelee
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
| | - Summer S. Han
- Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA
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11
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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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Vachani A, Caruso C. Impact of low-dose computed tomography screening on lung cancer incidence and outcomes. Curr Opin Pulm Med 2023; 29:232-238. [PMID: 37191171 PMCID: PMC10247528 DOI: 10.1097/mcp.0000000000000974] [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: 05/17/2023]
Abstract
PURPOSE OF REVIEW To review findings from clinical trials of lung cancer screening (LCS), assess contemporary issues with implementation in clinical practice, and review emerging strategies to increase the uptake and efficiency of LCS. RECENT FINDINGS In 2013, the USPSTF recommended annual screening for individuals aged 55-80 years and currently smoke or quit within the past 15 years based on reduced mortality from lung cancer with annual low-dose computed tomography (LDCT) screening in the National Lung Screening Trial. Subsequent trials have demonstrated similar mortality outcomes in individuals with lower pack-year smoking histories. These findings, coupled with evidence for disparities in screening eligibility by race, resulted in updated guidelines by USPSTF to broaden eligibility criteria for screening. Despite this body of evidence, implementation in the United States has been suboptimal with fewer than 20% of eligible individuals receiving a screen. Barriers to efficient implementation are multifactorial and include patient, clinician, and system-level factors. SUMMARY Multiple randomized trials have established that annual LCS reduces mortality from lung cancer; however, several areas of uncertainty exist on the effectiveness of annual LDCT. Ongoing research is examining approaches to improve the uptake and efficiency of LCS, such as the use of risk-prediction models and biomarkers for identification of high-risk individuals.
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Affiliation(s)
- Anil Vachani
- Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania Perelman School of Medicine
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania
| | - Christopher Caruso
- Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania Perelman School of Medicine
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13
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Wiener RS, Gould MK. Selecting Candidates for Lung Cancer Screening: Implications for Effectiveness, Efficiency, Equity, and Implementation. Ann Intern Med 2023; 176:413-414. [PMID: 36745888 DOI: 10.7326/m23-0230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Affiliation(s)
- Renda Soylemez Wiener
- Center for Health Organization and Implementation Research, VA Boston Healthcare System, Boston, and The Pulmonary Center, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Michael K Gould
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California
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