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Landy R, Gomez I, Caverly TJ, Kawamoto K, Rivera MP, Robbins HA, Young CD, Chaturvedi AK, Cheung LC, Katki HA. Methods for Using Race and Ethnicity in Prediction Models for Lung Cancer Screening Eligibility. JAMA Netw Open 2023; 6:e2331155. [PMID: 37721755 PMCID: PMC10507484 DOI: 10.1001/jamanetworkopen.2023.31155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 07/20/2023] [Indexed: 09/19/2023] Open
Abstract
Importance Using race and ethnicity in clinical prediction models can reduce or inadvertently increase racial and ethnic disparities in medical decisions. Objective To compare eligibility for lung cancer screening in a contemporary representative US population by refitting the life-years gained from screening-computed tomography (LYFS-CT) model to exclude race and ethnicity vs a counterfactual eligibility approach that recalculates life expectancy for racial and ethnic minority individuals using the same covariates but substitutes White race and uses the higher predicted life expectancy, ensuring that historically underserved groups are not penalized. Design, Setting, and Participants The 2 submodels composing LYFS-CT NoRace were refit and externally validated without race and ethnicity: the lung cancer death submodel in participants of a large clinical trial (recruited 1993-2001; followed up until December 31, 2009) who ever smoked (n = 39 180) and the all-cause mortality submodel in the National Health Interview Survey (NHIS) 1997-2001 participants aged 40 to 80 years who ever smoked (n = 74 842, followed up until December 31, 2006). Screening eligibility was examined in NHIS 2015-2018 participants aged 50 to 80 years who ever smoked. Data were analyzed from June 2021 to September 2022. Exposure Including and removing race and ethnicity (African American, Asian American, Hispanic American, White) in each LYFS-CT submodel. Main Outcomes and Measures By race and ethnicity: calibration of the LYFS-CT NoRace model and the counterfactual approach (ratio of expected to observed [E/O] outcomes), US individuals eligible for screening, predicted days of life gained from screening by LYFS-CT. Results The NHIS 2015-2018 included 25 601 individuals aged 50 to 80 years who ever smoked (2769 African American, 649 Asian American, 1855 Hispanic American, and 20 328 White individuals). Removing race and ethnicity from the submodels underestimated lung cancer death risk (expected/observed [E/O], 0.72; 95% CI, 0.52-1.00) and all-cause mortality (E/O, 0.90; 95% CI, 0.86-0.94) in African American individuals. It also overestimated mortality in Hispanic American (E/O, 1.08, 95% CI, 1.00-1.16) and Asian American individuals (E/O, 1.14, 95% CI, 1.01-1.30). Consequently, the LYFS-CT NoRace model increased Hispanic American and Asian American eligibility by 108% and 73%, respectively, while reducing African American eligibility by 39%. Using LYFS-CT with the counterfactual all-cause mortality model better maintained calibration across groups and increased African American eligibility by 13% without reducing eligibility for Hispanic American and Asian American individuals. Conclusions and Relevance In this study, removing race and ethnicity miscalibrated LYFS-CT submodels and substantially reduced African American eligibility for lung cancer screening. Under counterfactual eligibility, no one became ineligible, and African American eligibility increased, demonstrating the potential for maintaining model accuracy while reducing disparities.
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Affiliation(s)
- Rebecca Landy
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Isabel Gomez
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
- Biostatistics Department, University of Michigan, Ann Arbor
| | - Tanner J. Caverly
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - M. Patricia Rivera
- Division of Pulmonary and Critical Care Medicine and Wilmot Cancer Institute, University of Rochester, Rochester, New York
| | - Hilary A. Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Corey D. Young
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
- Department of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia
| | - Anil K. Chaturvedi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Li C. Cheung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
| | - Hormuzd A. Katki
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland
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Barta JA, Erkmen CP, Shusted CS, Myers RE, Saia C, Cohen S, Wainwright J, Zeigler-Johnson C, Dako F, Wender R, Kane GC, Vachani A, Rendle KA. The Philadelphia Lung Cancer Learning Community: a multi-health-system, citywide approach to lung cancer screening. JNCI Cancer Spectr 2023; 7:pkad071. [PMID: 37713466 PMCID: PMC10588937 DOI: 10.1093/jncics/pkad071] [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: 03/09/2023] [Revised: 06/16/2023] [Accepted: 09/13/2023] [Indexed: 09/17/2023] Open
Abstract
BACKGROUND Lung cancer screening uptake for individuals at high risk is generally low across the United States, and reporting of lung cancer screening practices and outcomes is often limited to single hospitals or institutions. We describe a citywide, multicenter analysis of individuals receiving lung cancer screening integrated with geospatial analyses of neighborhood-level lung cancer risk factors. METHODS The Philadelphia Lung Cancer Learning Community consists of lung cancer screening clinicians and researchers at the 3 largest health systems in the city. This multidisciplinary, multi-institutional team identified a Philadelphia Lung Cancer Learning Community study cohort that included 11 222 Philadelphia residents who underwent low-dose computed tomography for lung cancer screening from 2014 to 2021 at a Philadelphia Lung Cancer Learning Community health-care system. Individual-level demographic and clinical data were obtained, and lung cancer screening participants were geocoded to their Philadelphia census tract of residence. Neighborhood characteristics were integrated with lung cancer screening counts to generate bivariate choropleth maps. RESULTS The combined sample included 37.8% Black adults, 52.4% women, and 56.3% adults who currently smoke. Of 376 residential census tracts in Philadelphia, 358 (95.2%) included 5 or more individuals undergoing lung cancer screening, and the highest counts were geographically clustered around each health system's screening sites. A relatively low percentage of screened adults resided in census tracts with high tobacco retailer density or high smoking prevalence. CONCLUSIONS The sociodemographic characteristics of lung cancer screening participants in Philadelphia varied by health system and neighborhood. These results suggest that a multicenter approach to lung cancer screening can identify vulnerable areas for future tailored approaches to improving lung cancer screening uptake. Future directions should use these findings to develop and test collaborative strategies to increase lung cancer screening at the community and regional levels.
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Affiliation(s)
- Julie A Barta
- Department of Medicine, The Jane and Leonard Korman Respiratory Institute, Division of Pulmonary and Critical Care Medicine, Thomas Jefferson University, Philadelphia, PA, USA
| | - Cherie P Erkmen
- Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
| | - Christine S Shusted
- Department of Medicine, The Jane and Leonard Korman Respiratory Institute, Division of Pulmonary and Critical Care Medicine, Thomas Jefferson University, Philadelphia, PA, USA
| | - Ronald E Myers
- Department of Medical Oncology, Division of Population Science, Thomas Jefferson University, Philadelphia, PA, USA
| | - Chelsea Saia
- Department of Family & Community Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah Cohen
- Department of Family & Community Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jocelyn Wainwright
- Department of Family & Community Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charnita Zeigler-Johnson
- Department of Medical Oncology, Division of Population Science, Thomas Jefferson University, Philadelphia, PA, USA
- Cancer Prevention and Control Program, Fox Chase Cancer Center, Philadelphia, PA, USA
| | - Farouk Dako
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Richard Wender
- Department of Family & Community Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gregory C Kane
- Department of Medicine, The Jane and Leonard Korman Respiratory Institute, Division of Pulmonary and Critical Care Medicine, Thomas Jefferson University, Philadelphia, PA, USA
| | - Anil Vachani
- Department of Medicine, Division of Pulmonary, Allergy and Critical Care, University of Pennsylvania, Philadelphia, PA, USA
| | - Katharine A Rendle
- Department of Family & Community Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Fantin A, Castaldo N, Tirone C, Sartori G, Crisafulli E, Patrucco F, Vetrugno L, Patruno V. Endobronchial ultrasound: a pictorial essay. ACTA BIO-MEDICA : ATENEI PARMENSIS 2023; 94:e2023113. [PMID: 37539612 PMCID: PMC10440771 DOI: 10.23750/abm.v94i4.14090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 03/13/2023] [Indexed: 08/05/2023]
Abstract
BACKGROUND AND AIM endobronchial ultrasound has gained widespread popularity in the last decade, becoming the primary technique for minimally invasive evaluation of the mediastinum and staging of lung cancer. Several tertiary and quaternary care institutes use this method, performed by trained and accredited specialists. Its main indications are (I) diagnosis and staging of lung cancer, (II) mediastinal lymphadenopathy diagnosis (III) sampling peripheral pulmonary lesions. CONCLUSIONS this manuscript aims to describe the operational potential of both convex endobronchial ultrasound probe and radial endobronchial ultrasound probe technology, focusing on lung cancer. This narrative review is complemented with by the description of peculiar clinical cases in which endobronchial ultrasound played a pivotal role in reaching the diagnosis.
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Affiliation(s)
- Alberto Fantin
- Department of Pulmonology, Azienda Sanitaria Universitaria Integrata di Udine, Udine, Italy.
| | - Nadia Castaldo
- Department of Pulmonology, S. Maria della Misericordia University Hospital, Udine, Italy.
| | - Chiara Tirone
- Department of Medicine, Respiratory Medicine Unit, University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy.
| | - Giulia Sartori
- Department of Medicine, Respiratory Medicine Unit, University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy.
| | - Ernesto Crisafulli
- Department of Medicine, Respiratory Medicine Unit, University of Verona and Azienda Ospedaliera Universitaria Integrata of Verona, Verona, Italy.
| | - Filippo Patrucco
- Division of Respiratory Diseases, Department of Medicine, Maggiore della Carità University Hospital, Novara, Italy.
| | - Luigi Vetrugno
- Department of Medical, Oral and Biotechnological Sciences, University of Chieti-Pescara, Chieti, Italy.
| | - Vincenzo Patruno
- Department of Pulmonology, S. Maria della Misericordia University Hospital, Udine, Italy.
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Borg M, Wen SWC, Andersen RF, Timm S, Hansen TF, Hilberg O. Methylated Circulating Tumor DNA in Blood as a Tool for Diagnosing Lung Cancer: A Systematic Review and Meta-Analysis. Cancers (Basel) 2023; 15:3959. [PMID: 37568774 PMCID: PMC10417522 DOI: 10.3390/cancers15153959] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 07/24/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023] Open
Abstract
Lung cancer is the leading cause of cancer-related deaths, and early detection is crucial for improving patient outcomes. Current screening methods using computed tomography have limitations, prompting interest in non-invasive diagnostic tools such as methylated circulating tumor DNA (ctDNA). The PRISMA guidelines for systematic reviews were followed. The electronic databases MEDLINE, Embase, Web of Science, and Cochrane Library were systematically searched for articles. The search string contained three main topics: Lung cancer, blood, and methylated ctDNA. The extraction of data and quality assessment were carried out independently by the reviewers. In total, 33 studies were eligible for inclusion in this systematic review and meta-analysis. The most frequently studied genes were SHOX2, RASSF1A, and APC. The sensitivity and specificity of methylated ctDNA varied across studies, with a summary sensitivity estimate of 46.9% and a summary specificity estimate of 92.9%. The area under the hierarchical summary receiver operating characteristics curve was 0.81. The included studies were generally of acceptable quality, although they lacked information in certain areas. The risk of publication bias was not significant. Based on the findings, methylated ctDNA in blood shows potential as a rule-in tool for lung cancer diagnosis but requires further research, possibly in combination with other biomarkers.
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Affiliation(s)
- Morten Borg
- Department of Medicine, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark; (M.B.)
| | - Sara Witting Christensen Wen
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
- Department of Regional Health Research, University of Southern Denmark, 5000 Odense, Denmark
| | - Rikke Fredslund Andersen
- Department of Biochemistry and Immunology, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
| | - Signe Timm
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
- Department of Regional Health Research, University of Southern Denmark, 5000 Odense, Denmark
| | - Torben Frøstrup Hansen
- Department of Oncology, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark
- Department of Regional Health Research, University of Southern Denmark, 5000 Odense, Denmark
| | - Ole Hilberg
- Department of Medicine, Vejle Hospital, University Hospital of Southern Denmark, 7100 Vejle, Denmark; (M.B.)
- Department of Regional Health Research, University of Southern Denmark, 5000 Odense, Denmark
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Pritchett MA, Sigal B, Bowling MR, Kurman JS, Pitcher T, Springmeyer SC. Assessing a biomarker's ability to reduce invasive procedures in patients with benign lung nodules: Results from the ORACLE study. PLoS One 2023; 18:e0287409. [PMID: 37432960 DOI: 10.1371/journal.pone.0287409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 06/05/2023] [Indexed: 07/13/2023] Open
Abstract
A blood-based integrated classifier (IC) has been clinically validated to improve accuracy in assessing probability of cancer risk (pCA) for pulmonary nodules (PN). This study evaluated the clinical utility of this biomarker for its ability to reduce invasive procedures in patients with pre-test pCA ≤ 50%. This was a propensity score matching (PSM) cohort study comparing patients in the ORACLE prospective, multicenter, observational registry to control patients treated with usual care. This study enrolled patients meeting the intended use criteria for IC testing: pCA ≤ 50%, age ≥40 years, nodule diameter 8-30 mm, and no history of lung cancer and/or active cancer (except for non-melanomatous skin cancer) within 5 years. The primary aim of this study was to evaluate invasive procedure use on benign PNs of registry patients as compared to control patients. A total of 280 IC tested, and 278 control patients met eligibility and analysis criteria and 197 were in each group after PSM (IC and control groups). Patients in the IC group were 74% less likely to undergo an invasive procedure as compared to the control group (absolute difference 14%, p <0.001) indicating that for every 7 patients tested, one unnecessary invasive procedure was avoided. Invasive procedure reduction corresponded to a reduction in risk classification, with 71 patients (36%) in the IC group classified as low risk (pCA < 5%). The proportion of IC group patients with malignant PNs sent to surveillance were not statistically different than the control group, 7.5% vs 3.5% for the IC vs. control groups, respectively (absolute difference 3.91%, p 0.075). The IC for patients with a newly discovered PN has demonstrated valuable clinical utility in a real-world setting. Use of this biomarker can change physicians' practice and reduce invasive procedures in patients with benign pulmonary nodules. Trial registration: Clinical trial registration: ClinicalTrials.gov NCT03766958.
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Affiliation(s)
- Michael A Pritchett
- Department of Pulmonary Medicine, FirstHealth of the Carolinas & Pinehurst Medical Clinic, Pinehurst, North Carolina, United States of America
| | - Barry Sigal
- Southeastern Research Center, Winston-Salem, North Carolina, United States of America
| | - Mark R Bowling
- Division of Pulmonary, Critical Care, and Sleep Medicine, Brody School of Medicine, Eastern Carolina University, Greenville, North Carolina, United States of America
| | - Jonathan S Kurman
- Division of Critical Care Medicine, Interventional Pulmonology, Pulmonary Disease, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America
| | - Trevor Pitcher
- Medical Affairs, Biodesix, Inc., Boulder, Colorado, United States of America
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Chen Y, Ma S, Lin C, Zhu Z, Bai J, Yin Z, Sun Y, Mao F, Xue L, Ma S. Integrative analysis of DNA methylomes reveals novel cell-free biomarkers in lung adenocarcinoma. Front Genet 2023; 14:1175784. [PMID: 37396036 PMCID: PMC10311559 DOI: 10.3389/fgene.2023.1175784] [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: 02/28/2023] [Accepted: 06/07/2023] [Indexed: 07/04/2023] Open
Abstract
Lung cancer is a leading cause of cancer-related deaths worldwide, with a low 5-year survival rate due in part to a lack of clinically useful biomarkers. Recent studies have identified DNA methylation changes as potential cancer biomarkers. The present study identified cancer-specific CpG methylation changes by comparing genome-wide methylation data of cfDNA from lung adenocarcinomas (LUAD) patients and healthy donors in the discovery cohort. A total of 725 cell-free CpGs associated with LUAD risk were identified. Then XGBoost algorithm was performed to identify seven CpGs associated with LUAD risk. In the training phase, the 7-CpGs methylation panel was established to classify two different prognostic subgroups and showed a significant association with overall survival (OS) in LUAD patients. We found that the methylation of cg02261780 was negatively correlated with the expression of its representing gene GNA11. The methylation and expression of GNA11 were significantly associated with LAUD prognosis. Based on bisulfite PCR, the methylation levels of five CpGs (cg02261780, cg09595050, cg20193802, cg15309457, and cg05726109) were further validated in tumor tissues and matched non-malignant tissues from 20 LUAD patients. Finally, validation of the seven CpGs with RRBS data of cfDNA methylation was conducted and further proved the reliability of the 7-CpGs methylation panel. In conclusion, our study identified seven novel methylation markers from cfDNA methylation data which may contribute to better prognosis for LUAD patients.
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Affiliation(s)
- Yifan Chen
- Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
- Biobank, Peking University Third Hospital, Beijing, China
| | - Shanwu Ma
- Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China
| | - Chutong Lin
- Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China
| | - Zhipeng Zhu
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
| | - Jie Bai
- Department of Thoracic Surgery, Peking University Third Hospital, Beijing, China
| | - Zhongnan Yin
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
- Biobank, Peking University Third Hospital, Beijing, China
| | - Yan Sun
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
- Biobank, Peking University Third Hospital, Beijing, China
| | - Fengbiao Mao
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
| | - Lixiang Xue
- Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, China
- Cancer Center of Peking University Third Hospital, Peking University Third Hospital, Beijing, China
- Biobank, Peking University Third Hospital, Beijing, China
| | - Shaohua Ma
- Beijing Cancer Hospital and Institute, Peking University School of Oncology, Beijing, China
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Kallavus K, Laisaar KT, Rätsep A, Kiudma T, Takker U, Poola A, Makke V, Frik M, Viiklepp P, Taur M, Laisaar T. National lung cancer screening program feasibility study in Estonia. INTERDISCIPLINARY CARDIOVASCULAR AND THORACIC SURGERY 2023; 36:ivad041. [PMID: 36807427 PMCID: PMC10279650 DOI: 10.1093/icvts/ivad041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 01/30/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES The main aim of the lung cancer screening (LCS) feasibility study was to investigate the plausibility of and bottlenecks to systematic enrolment in family physician practices by evaluating all their patients. METHODS In 3 family physician practices, for each individual born in 1947-1966 (target age group 55-74 years), information on ever smoking was gathered by a family physician/nurse. All current and ex-smokers were invited to an 'LCS visit'. In parallel, 2 inclusion criteria were used: (1) current smoker (≥20 pack-years) or ex-smoker (quit <15 years ago and smoking history ≥20 pack-years) and (2) PLCOm2012noRace risk score >1.5. All individuals with elevated lung cancer risk were assigned low-dose computed tomography. RESULTS Among the total 7035 individuals in the 3 family physician practices, the LCS target age group comprised 1208 individuals, including 649 (46.3-57.1%) males and 559 (42.9-53.7%) females. Of the 1208 applicable age group individuals, 395 (all current or ex-smokers) were invited to the 'LCS visit'. According to either 1 or both the LCS inclusion criteria, 206 individuals were referred to low-dose computed tomography, and 201 (97.6% of those referred) ended up taking it. The estimated participation rate in LCS, based on data from our feasibility study, would have been 87.4%. CONCLUSIONS In LCS, systematic enrolment of individuals by family physicians results in high uptake, and thus, effectiveness of the LCS in the setting of a well-functioning family physician system like in Estonia. Also, the feasibility study provided excellent input to the currently ongoing regional LCS pilot study in Estonia.
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Affiliation(s)
- Kadi Kallavus
- Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Kaja-Triin Laisaar
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
| | - Anneli Rätsep
- Institute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia
- Ränilinna Health Centre, Tartu, Estonia
| | | | - Urmas Takker
- Family Physicians Takker and Sarapuu, Tartu, Estonia
| | - Anneli Poola
- Radiology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Vahur Makke
- Radiology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Marianna Frik
- Radiology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Piret Viiklepp
- Head of Department of Registries, National Institute for Health Development, Tallinn, Estonia
| | - Merily Taur
- Lung Clinic, Tartu University Hospital, Tartu, Estonia
| | - Tanel Laisaar
- Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Lung Clinic, Tartu University Hospital, Tartu, Estonia
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Peterson MW, Jain R, Hildebrandt K, Carson WK, Fayed MA. Differentiating Lung Nodules Due to Coccidioides from Those Due to Lung Cancer Based on Radiographic Appearance. J Fungi (Basel) 2023; 9:641. [PMID: 37367577 DOI: 10.3390/jof9060641] [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: 03/20/2023] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 06/28/2023] Open
Abstract
BACKGROUND Coccidioidomycosis (cocci) is an endemic fungal disease that can cause asymptomatic or post-symptomatic lung nodules which are visible on chest CT scanning. Lung nodules are common and can represent early lung cancer. Differentiating lung nodules due to cocci from those due to lung cancer can be difficult and lead to invasive and expensive evaluations. MATERIALS AND METHODS We identified 302 patients with biopsy-proven cocci or bronchogenic carcinoma seen in our multidisciplinary nodule clinic. Two experienced radiologists who were blinded to the diagnosis read the chest CT scans and identified radiographic characteristics to determine their utility in differentiating lung cancer nodules from those due to cocci. RESULTS Using univariate analysis, we identified several radiographic findings that differed between lung cancer and cocci infection. We then entered these variables along with age and gender into a multivariate model and found that age, nodule diameter, nodule cavitation, presence of satellite nodules and radiographic presence of chronic lung disease differed significantly between the two diagnoses. Three findings, cavitary nodules, satellite nodules and chronic lung disease, have sufficient discrimination to potentially be useful in clinical decision-making. CONCLUSIONS Careful evaluation of the three obtained radiographic findings can significantly improve our ability to differentiate benign coccidioidomycosis infection from lung cancer in an endemic region for the fungal disease. Using these data may significantly reduce the cost and risk associated with distinguishing the cause of lung nodules in these patients by preventing unnecessary invasive studies.
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Affiliation(s)
- Michael W Peterson
- Fresno Department of Medicine, University of California (San Francisco), San Francisco, CA 93701, USA
- UCSF Fresno/Community Medical Centers' Multidisciplinary Lung Nodule Clinic, Fresno, CA 93701, USA
| | - Ratnali Jain
- Fresno Department of Medicine, University of California (San Francisco), San Francisco, CA 93701, USA
| | - Kurt Hildebrandt
- Community Medical Imaging Radiology Group, Fresno, CA 93721, USA
| | | | - Mohamed A Fayed
- Fresno Department of Medicine, University of California (San Francisco), San Francisco, CA 93701, USA
- UCSF Fresno/Community Medical Centers' Multidisciplinary Lung Nodule Clinic, Fresno, CA 93701, USA
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Rustagi AS, Byers AL, Brown JK, Purcell N, Slatore CG, Keyhani S. Lung Cancer Screening Among U.S. Military Veterans by Health Status and Race and Ethnicity, 2017-2020: A Cross-Sectional Population-Based Study. AJPM FOCUS 2023; 2:100084. [PMID: 37790642 PMCID: PMC10546514 DOI: 10.1016/j.focus.2023.100084] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
Introduction Veterans are at high risk for lung cancer and are an important group for lung cancer screening. Previous research suggests that lung cancer screening may not be reaching healthier and/or non-White individuals, who stand to benefit most from lung cancer screening. We sought to test whether lung cancer screening is associated with poor health and/or race and ethnicity among veterans. Methods This cross-sectional, population-based study included veterans eligible for lung cancer screening (aged 55-79 years, ≥30 pack-year smoking history, current smokers or quit within 15 years, no previous lung cancer) in the 2017-2020 Behavioral Risk Factor Surveillance System surveys. Exposures were (1) poor health, defined as fair/poor health status and difficulty walking or climbing stairs, aligning with eligibility criteria for a pivotal lung cancer screening trial, and (2) race/ethnicity. The outcome was a receipt of lung cancer screening. All variables were self-reported. Results Of 3,376 lung cancer screening-eligible veterans representing an underlying population of 866,000 individuals, 20.3% (95% CI=17.3, 23.6) had poor health, and 13.7% (95% CI=10.6, 17.5) identified as non-White. Poor health was strongly associated with lung cancer screening (adjusted RR=1.64, 95% CI=1.06, 2.27); one third of veterans screened for lung cancer would not qualify for a pivotal lung cancer screening trial in terms of health. Marked racial disparities were observed among veterans: after adjustment, non-White veterans were 67% less likely to report lung cancer screening than White veterans (adjusted RR=0.33, 95% CI=0.11, 0.66). Conclusions Lung cancer screening is correlated with poorer health and White race/ethnicity among veterans, which may undermine its population-level effectiveness. These results highlight the need to promote lung cancer screening, especially for healthier and/or non-White veterans, an important group of Americans for lung cancer screening.
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Affiliation(s)
- Alison S. Rustagi
- Division of General Internal Medicine, Medical Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Medicine, University of California, San Francisco, California
| | - Amy L. Byers
- Department of Medicine, University of California, San Francisco, California
- Research Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California
- Weill Institute for Neurosciences, University of California, San Francisco, California
| | - James K. Brown
- Department of Medicine, University of California, San Francisco, California
- Division of Pulmonary, Critical Care, and Sleep Medicine, Medical Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
| | - Natalie Purcell
- Integrative Health, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Social Behavioral Health Sciences, School of Nursing, University of California, San Francisco, California
| | - Christopher G. Slatore
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, District of Columbia
- Division of Pulmonary and Critical Care Medicine, VA Portland Health Care System, Portland, Oregon
- Division of Pulmonary & Critical Care Medicine, Department of Medicine, Oregon Health & Science University School of Medicine, Portland, Oregon
| | - Salomeh Keyhani
- Division of General Internal Medicine, Medical Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Medicine, University of California, San Francisco, California
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Galang K, Polychronopoulou E, Sharma G, Nishi SP. A Closer Look-Who Are We Screening for Lung Cancer? Mayo Clin Proc Innov Qual Outcomes 2023; 7:171-177. [PMID: 37293510 PMCID: PMC10244365 DOI: 10.1016/j.mayocpiqo.2023.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 03/31/2023] [Accepted: 04/05/2023] [Indexed: 06/10/2023] Open
Abstract
Objective To evaluate the characteristics of individuals receiving lung cancer screening (LCS) and identify those with potentially limited benefit owing to coexisting chronic illnesses and/or comorbidities. Patients and Methods In this retrospective study in the United States, patients were selected from a large clinical database who received LCS from January 1, 2019, through December 31, 2019, with at least 1 year of continuous enrollment. We assessed for potentially limited benefit in LCS defined strictly as not meeting the traditional risk factor inclusion criteria (age <55 years or >80 years, previous computed tomography scan within 11 months before an LCS examination, or a history of nonskin cancer) or liberally as having the potential exclusion criteria related to comorbid life-limiting conditions, such as cardiac and/or respiratory disease. Results A total of 51,551 patients were analyzed. Overall, 8391 (16.3%) individuals experienced a potentially limited benefit from LCS. Among those who did not meet the strict traditional inclusion criteria, 317 (3.8%) were because of age, 2350 (28%) reported a history of nonskin malignancy, and 2211 (26.3%) underwent a previous computed tomography thorax within 11 months before an LCS examination. Of those with potentially limited benefit owing to comorbidity, 3680 (43.9%) were because of severe respiratory comorbidity (937 [25.5%] with any hospitalization for coronary obstructive pulmonary disease, interstitial lung disease, or respiratory failure; 131 [3.6%] with hospitalization for respiratory failure requiring mechanical ventilation; or 3197 [86.9%] with chronic obstructive disease/interstitial lung disease requiring outpatient oxygen) and 721 (8.59%) with cardiac comorbidity. Conclusion Up to 1 of 6 low-dose computed tomography examinations may have limited benefit from LCS.
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Affiliation(s)
- Kristine Galang
- Department of Internal Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
| | | | - Gulshan Sharma
- Department of Internal Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
- Sealy Center on Aging, University of Texas Medical Branch–Galveston, Galveston, TX
| | - Shawn P.E. Nishi
- Department of Internal Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Texas Medical Branch–Galveston, Galveston, TX
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Lowenstein LM, Shih YCT, Minnix J, Lopez-Olivo MA, Maki KG, Kypriotakis G, Leal VB, Shete SS, Fox J, Nishi SP, Cinciripini PM, Volk RJ. A protocol for a cluster randomized trial of care delivery models to improve the quality of smoking cessation and shared decision making for lung cancer screening. Contemp Clin Trials 2023; 128:107141. [PMID: 36878389 PMCID: PMC10164095 DOI: 10.1016/j.cct.2023.107141] [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: 08/03/2022] [Revised: 02/16/2023] [Accepted: 03/01/2023] [Indexed: 03/07/2023]
Abstract
BACKGROUND Patients eligible for lung cancer screening (LCS) are those at high risk of lung cancer due to their smoking histories and age. While screening for LCS is effective in lowering lung cancer mortality, primary care providers are challenged to meet beneficiary eligibility for LCS from the Centers for Medicare & Medicaid Services, including a patient counseling and shared decision-making (SDM) visit with the use of patient decision aid(s) prior to screening. METHODS We will use an effectiveness-implementation type I hybrid design to: 1) identify effective, scalable smoking cessation counseling and SDM interventions that are consistent with recommendations, can be delivered on the same platform, and are implemented in real-world clinical settings; 2) examine barriers and facilitators of implementing the two approaches to delivering smoking cessation and SDM for LCS; and 3) determine the economic implications of implementation by assessing the healthcare resources required to increase smoking cessation for the two approaches by delivering smoking cessation within the context of LCS. Providers from different healthcare organizations will be randomized to usual care (providers delivering smoking cessation and SDM on site) vs. centralized care (smoking cessation and SDM delivered remotely by trained counselors). The primary trial outcomes will include smoking abstinence at 12-weeks and knowledge about LCS measured at 1-week after baseline. CONCLUSION This study will provide important new evidence about the effectiveness and feasibility of a novel care delivery model for addressing the leading cause of lung cancer deaths and supporting high-quality decisions about LCS. CLINICALTRIALS GOV PROTOCOL REGISTRATION NCT04200534 TRIAL REGISTRATION: ClinicalTrials.govNCT04200534.
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Affiliation(s)
- Lisa M Lowenstein
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Ya-Chen Tina Shih
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Jennifer Minnix
- Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Maria A Lopez-Olivo
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Kristin G Maki
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - George Kypriotakis
- Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Viola B Leal
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sanjay S Shete
- Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - James Fox
- Pulmonary & Critical Care Medicine, The University of Texas Health East Texas, Tyler, TX, USA.
| | - Shawn P Nishi
- Pulmonary & Critical Care Medicine, The University of Texas Medical Branch, Galveston, TX, USA.
| | - Paul M Cinciripini
- Behavioral Science, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| | - Robert J Volk
- Departments of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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Hirsch EA, Studts JL. Using User-Centered Design to Facilitate Adherence to Annual Lung Cancer Screening: Protocol for a Mixed Methods Study for Intervention Development. JMIR Res Protoc 2023; 12:e46657. [PMID: 37058339 PMCID: PMC10162485 DOI: 10.2196/46657] [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: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 04/15/2023] Open
Abstract
BACKGROUND Lung cancer is the leading cause of cancer-related death in the United States, with the majority of lung cancer occurrence diagnosed after the disease has already metastasized. Lung cancer screening (LCS) with low-dose computed tomography can diagnose early-stage disease, especially when eligible individuals participate in screening on a yearly basis. Unfortunately, annual adherence has emerged as a challenge for academic and community screening programs, endangering the individual and population health benefits of LCS. Reminder messages have effectively increased adherence rates in breast, colorectal, and cervical cancer screenings but have not been tested with LCS participants who experience unique barriers to screening associated with the stigma of smoking and social determinants of health. OBJECTIVE This research aims to use a theory-informed, multiphase, and mixed methods approach with LCS experts and participants to develop a set of clear and engaging reminder messages to support LCS annual adherence. METHODS In aim 1, survey data informed by the Cognitive-Social Health Information Processing model will be collected to assess how LCS participants process health information aimed at health protective behavior to develop content for reminder messages and pinpoint options for message targeting and tailoring. Aim 2 focuses on identifying themes for message imagery through a modified photovoice activity that asks participants to identify 3 images that represent LCS and then participate in an interview about the selection, likes, and dislikes of each photo. A pool of candidate messages for multiple delivery platforms will be developed in aim 3, using results from aim 1 for message content and aim 2 for imagery selection. The refinement of message content and imagery combinations will be completed through iterative feedback from LCS experts and participants. RESULTS Data collection began in July 2022 and will be completed by May 2023. The final reminder message candidates are expected to be completed by June 2023. CONCLUSIONS This project proposes a novel approach to facilitate adherence to annual LCS through the development of reminder messages that embrace content and imagery representative of the target population directly in the design process. Developing effective strategies to increase LCS adherence is instrumental in achieving optimal LCS outcomes at individual and population health levels. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/46657.
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Affiliation(s)
- Erin A Hirsch
- Division of Medical Oncology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- University of Colorado Cancer Center, Aurora, CO, United States
| | - Jamie L Studts
- Division of Medical Oncology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States
- University of Colorado Cancer Center, Aurora, CO, United States
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Scapicchio C, Chincarini A, Ballante E, Berta L, Bicci E, Bortolotto C, Brero F, Cabini RF, Cristofalo G, Fanni SC, Fantacci ME, Figini S, Galia M, Gemma P, Grassedonio E, Lascialfari A, Lenardi C, Lionetti A, Lizzi F, Marrale M, Midiri M, Nardi C, Oliva P, Perillo N, Postuma I, Preda L, Rastrelli V, Rizzetto F, Spina N, Talamonti C, Torresin A, Vanzulli A, Volpi F, Neri E, Retico A. A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia. Eur Radiol Exp 2023; 7:18. [PMID: 37032383 PMCID: PMC10083148 DOI: 10.1186/s41747-023-00334-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 02/27/2023] [Indexed: 04/11/2023] Open
Abstract
BACKGROUND The role of computed tomography (CT) in the diagnosis and characterization of coronavirus disease 2019 (COVID-19) pneumonia has been widely recognized. We evaluated the performance of a software for quantitative analysis of chest CT, the LungQuant system, by comparing its results with independent visual evaluations by a group of 14 clinical experts. The aim of this work is to evaluate the ability of the automated tool to extract quantitative information from lung CT, relevant for the design of a diagnosis support model. METHODS LungQuant segments both the lungs and lesions associated with COVID-19 pneumonia (ground-glass opacities and consolidations) and computes derived quantities corresponding to qualitative characteristics used to clinically assess COVID-19 lesions. The comparison was carried out on 120 publicly available CT scans of patients affected by COVID-19 pneumonia. Scans were scored for four qualitative metrics: percentage of lung involvement, type of lesion, and two disease distribution scores. We evaluated the agreement between the LungQuant output and the visual assessments through receiver operating characteristics area under the curve (AUC) analysis and by fitting a nonlinear regression model. RESULTS Despite the rather large heterogeneity in the qualitative labels assigned by the clinical experts for each metric, we found good agreement on the metrics compared to the LungQuant output. The AUC values obtained for the four qualitative metrics were 0.98, 0.85, 0.90, and 0.81. CONCLUSIONS Visual clinical evaluation could be complemented and supported by computer-aided quantification, whose values match the average evaluation of several independent clinical experts. KEY POINTS We conducted a multicenter evaluation of the deep learning-based LungQuant automated software. We translated qualitative assessments into quantifiable metrics to characterize coronavirus disease 2019 (COVID-19) pneumonia lesions. Comparing the software output to the clinical evaluations, results were satisfactory despite heterogeneity of the clinical evaluations. An automatic quantification tool may contribute to improve the clinical workflow of COVID-19 pneumonia.
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Affiliation(s)
- Camilla Scapicchio
- Physics Department, University of Pisa, Pisa, Italy.
- Pisa Division, National Institute for Nuclear Physics, Pisa, Italy.
| | - Andrea Chincarini
- Genova Division, National Institute for Nuclear Physics, Genova, Italy
| | - Elena Ballante
- Department of Political and Social Sciences, University of Pavia, Pavia, Italy
- Pavia Division, National Institute for Nuclear Physics, Pavia, Italy
| | - Luca Berta
- Department of Medical Physics, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Milano Division, National Institute for Nuclear Physics, Milan, Italy
| | - Eleonora Bicci
- Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence-Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Chandra Bortolotto
- Unit of Imaging and Radiotherapy, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy
- Institute of Radiology, Department of Diagnostic and Imaging Services, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Francesca Brero
- Pavia Division, National Institute for Nuclear Physics, Pavia, Italy
| | - Raffaella Fiamma Cabini
- Pavia Division, National Institute for Nuclear Physics, Pavia, Italy
- Department of Mathematics, University of Pavia, Pavia, Italy
| | - Giuseppe Cristofalo
- Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | | | - Maria Evelina Fantacci
- Physics Department, University of Pisa, Pisa, Italy
- Pisa Division, National Institute for Nuclear Physics, Pisa, Italy
| | - Silvia Figini
- Department of Political and Social Sciences, University of Pavia, Pavia, Italy
- Pavia Division, National Institute for Nuclear Physics, Pavia, Italy
| | - Massimo Galia
- Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Pietro Gemma
- Post-graduate School in Radiodiagnostics, University of Milan, Milan, Italy
| | - Emanuele Grassedonio
- Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | | | - Cristina Lenardi
- Milano Division, National Institute for Nuclear Physics, Milan, Italy
- Department of Physics "Aldo Pontremoli", University of Milan, Milan, Italy
| | - Alice Lionetti
- Unit of Imaging and Radiotherapy, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy
| | - Francesca Lizzi
- Physics Department, University of Pisa, Pisa, Italy
- Pisa Division, National Institute for Nuclear Physics, Pisa, Italy
| | - Maurizio Marrale
- Department of Physics and Chemistry "Emilio Segrè", University of Palermo, Palermo, Italy
- Catania Division, National Institute for Nuclear Physics, Catania, Italy
| | - Massimo Midiri
- Department of Biomedicine, Neuroscience and Advanced Diagnostic (BiND), University of Palermo, Palermo, Italy
| | - Cosimo Nardi
- Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence-Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Piernicola Oliva
- Cagliari Division, National Institute for Nuclear Physics, Monserrato, Cagliari, Italy
- Department of Chemical, Physical, Mathematical and Natural Sciences, University of Sassari, Sassari, Italy
| | - Noemi Perillo
- Post-graduate School in Radiodiagnostics, University of Milan, Milan, Italy
| | - Ian Postuma
- Pavia Division, National Institute for Nuclear Physics, Pavia, Italy
| | - Lorenzo Preda
- Unit of Imaging and Radiotherapy, Department of Clinical-Surgical, Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy
- Institute of Radiology, Department of Diagnostic and Imaging Services, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Vieri Rastrelli
- Department of Experimental and Clinical Biomedical Sciences, Radiodiagnostic Unit n. 2, University of Florence-Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Francesco Rizzetto
- Department of Radiology, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Postgraduate School of Diagnostic and Interventional Radiology, University of Milan, Milan, Italy
| | - Nicola Spina
- Department of Translational Research, Academic Radiology, University of Pisa, Pisa, Italy
| | - Cinzia Talamonti
- Department Biomedical Experimental and Clinical Science "Mario Serio", University of Florence, Florence, Italy
- Florence Division, National Institute for Nuclear Physics, Sesto Fiorentino, Firenze, Italy
| | - Alberto Torresin
- Department of Medical Physics, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Milano Division, National Institute for Nuclear Physics, Milan, Italy
- Department of Physics "Aldo Pontremoli", University of Milan, Milan, Italy
| | - Angelo Vanzulli
- Department of Medical Physics, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Federica Volpi
- Department of Translational Research, Academic Radiology, University of Pisa, Pisa, Italy
| | - Emanuele Neri
- Department of Translational Research, Academic Radiology, University of Pisa, Pisa, Italy
- Italian Society of Medical and Interventional Radiology, SIRM Foundation, Milan, Italy
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Henderson LM, Chiles C, Perera P, Durham DD, Lamb D, Lane LM, Rivera MP. Variability in Reporting of Incidental Findings Detected on Lung Cancer Screening. Ann Am Thorac Soc 2023; 20:617-620. [PMID: 36538683 PMCID: PMC10112412 DOI: 10.1513/annalsats.202206-486rl] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
| | | | | | | | - Derek Lamb
- University of North CarolinaChapel Hill, North Carolina
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Pasello G, Scattolin D, Bonanno L, Caumo F, Dell'Amore A, Scagliori E, Tinè M, Calabrese F, Benati G, Sepulcri M, Baiocchi C, Milella M, Rea F, Guarneri V. Secondary prevention and treatment innovation of early stage non-small cell lung cancer: Impact on diagnostic-therapeutic pathway from a multidisciplinary perspective. Cancer Treat Rev 2023; 116:102544. [PMID: 36940657 DOI: 10.1016/j.ctrv.2023.102544] [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: 11/28/2022] [Revised: 03/06/2023] [Accepted: 03/13/2023] [Indexed: 03/18/2023]
Abstract
Lung cancer (LC) is the leading cause of cancer-related death worldwide, mostly because the lack of a screening program so far. Although smoking cessation has a central role in LC primary prevention, several trials on LC screening through low-dose computed tomography (LDCT) in a high risk population showed a significant reduction of LC related mortality. Most trials showed heterogeneity in terms of selection criteria, comparator arm, detection nodule method, timing and intervals of screening and duration of the follow-up. LC screening programs currently active in Europe as well as around the world will lead to a higher number of early-stage Non Small Cell Lung Cancer (NSCLC) at the diagnosis. Innovative drugs have been recently transposed from the metastatic to the perioperative setting, leading to improvements in terms of resection rates and pathological responses after induction chemoimmunotherapy, and disease free survival with targeted agents and immune checkpoint inhibitors. The present review summarizes available evidence about LC screening, highlighting potential pitfalls and benefits and underlining the impact on the diagnostic therapeutic pathway of NSCLC from a multidisciplinary perspective. Future perspectives in terms of circulating biomarkers under evaluation for patients' risk stratification as well as a focus on recent clinical trials results and ongoing studies in the perioperative setting will be also presented.
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Affiliation(s)
- Giulia Pasello
- Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy.
| | - Daniela Scattolin
- Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
| | - Laura Bonanno
- Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Francesca Caumo
- Radiology Unit, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Andrea Dell'Amore
- Department of Cardiac, Thoracic, Vascular sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Elena Scagliori
- Radiology Unit, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Mariaenrica Tinè
- Department of Cardiac, Thoracic, Vascular sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Fiorella Calabrese
- Department of Cardiac, Thoracic, Vascular sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Gaetano Benati
- Azienda Unità Locale Socio-Sanitaria (AULSS 9) Scaligera, Verona, Italy
| | - Matteo Sepulcri
- Radiation Therapy Unit, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy
| | - Cristina Baiocchi
- Radiation Oncology Unit, San Bortolo Hospital, Azienda Unità Locale Socio-Sanitaria (AULSS 8) Berica, Vicenza, Italy
| | - Michele Milella
- Section of Oncology, University of Verona - School of Medicine, Verona University Hospital Trust, Italy
| | - Federico Rea
- Department of Cardiac, Thoracic, Vascular sciences and Public Health, University Hospital of Padova, Padova, Italy
| | - Valentina Guarneri
- Medical Oncology 2, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy; Department of Surgery, Oncology and Gastroenterology, University of Padova, Padova, Italy
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Walder JR, Faiz SA, Sandoval M. Lung cancer in the emergency department. EMERGENCY CANCER CARE 2023; 2:3. [PMID: 38799792 PMCID: PMC11116267 DOI: 10.1186/s44201-023-00018-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/13/2023] [Indexed: 05/29/2024]
Abstract
Background Though decreasing in incidence and mortality in the USA, lung cancer remains the deadliest of all cancers. For a significant number of patients, the emergency department (ED) provides the first pivotal step in lung cancer prevention, diagnosis, and management. As screening recommendations and treatments advance, ED providers must stay up-to-date with the latest lung cancer recommendations. The purpose of this review is to identify the many ways that emergency providers may intersect with the disease spectrum of lung cancer and provide an updated array of knowledge regarding detection, management, complications, and interdisciplinary care. Findings Lung cancer, encompassing 10-12% of cancer-related emergency department visits and a 66% admission rate, is the most fatal malignancy in both men and women. Most patients presenting to the ED have not seen a primary care provider or undergone screening. Ultimately, half of those with a new lung cancer diagnosis in the ED die within 1 year. Incidental findings on computed tomography are mostly benign, but emergency staff must be aware of the factors that make them high risk. Radiologic presentations range from asymptomatic nodules to diffuse metastatic lesions with predominately pulmonary symptoms, and some may present with extra-thoracic manifestations including neurologic. The short-term prognosis for ED lung cancer patients is worse than that of other malignancies. Screening offers new hope through earlier diagnosis but is underutilized which may be due to racial and socioeconomic disparities. New treatments provide optimism but lead to new complications, some long-term. Multidisciplinary care is essential, and emergency medicine is responsible for the disposition of patients to the appropriate specialists at inpatient and outpatient centers. Conclusion ED providers are intimately involved in all aspects of lung cancer care. Risk factor modification and referral for lung cancer screening are opportunities to further enhance patient care. In addition, with the advent of newer cancer therapies, ED providers must stay vigilant and up-to-date with all aspects of lung cancer including disparities, staging, symptoms of disease, prognosis, treatment, and therapy-related complications.
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Affiliation(s)
- Jeremy R. Walder
- Divisions of Critical Care, Pulmonary and Sleep Medicine, McGovern Medical School at UTHealth, 6431 Fannin St., Ste. MSB 1.282, Houston, TX 77030 USA
| | - Saadia A. Faiz
- Department of Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1462, Houston, TX 77030 USA
| | - Marcelo Sandoval
- Department of Emergency Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1468, Houston, TX 77030 USA
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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: 102] [Impact Index Per Article: 102.0] [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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Pan Z, Zhang R, Shen S, Lin Y, Zhang L, Wang X, Ye Q, Wang X, Chen J, Zhao Y, Christiani DC, Li Y, Chen F, Wei Y. OWL: an optimized and independently validated machine learning prediction model for lung cancer screening based on the UK Biobank, PLCO, and NLST populations. EBioMedicine 2023; 88:104443. [PMID: 36701900 PMCID: PMC9881220 DOI: 10.1016/j.ebiom.2023.104443] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 12/27/2022] [Accepted: 01/06/2023] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND A reliable risk prediction model is critically important for identifying individuals with high risk of developing lung cancer as candidates for low-dose chest computed tomography (LDCT) screening. Leveraging a cutting-edge machine learning technique that accommodates a wide list of questionnaire-based predictors, we sought to optimize and validate a lung cancer prediction model. METHODS We developed an Optimized early Warning model for Lung cancer risk (OWL) using the XGBoost algorithm with 323,344 participants from the England area in UK Biobank (training set), and independently validated it with 93,227 participants from UKB Scotland and Wales area (validation set 1), as well as 70,605 and 66,231 participants in the Prostate, Lung, Colorectal, and Ovarian cancer screening trial (PLCO) control and intervention subpopulations, respectively (validation sets 2 & 3) and 23,138 and 18,669 participants in the United States National Lung Screening Trial (NLST) control and intervention subpopulations, respectively (validation sets 4 & 5). By comparing with three competitive prediction models, i.e., PLCO modified 2012 (PLCOm2012), PLCO modified 2014 (PLCOall2014), and the Liverpool Lung cancer Project risk model version 3 (LLPv3), we assessed the discrimination of OWL by the area under receiver operating characteristic curve (AUC) at the designed time point. We further evaluated the calibration using relative improvement in the ratio of expected to observed lung cancer cases (RIEO), and illustrated the clinical utility by the decision curve analysis. FINDINGS For general population, with validation set 1, OWL (AUC = 0.855, 95% CI: 0.829-0.880) presented a better discriminative capability than PLCOall2014 (AUC = 0.821, 95% CI: 0.794-0.848) (p < 0.001); with validation sets 2 & 3, AUC of OWL was comparable to PLCOall2014 (AUCPLCOall2014-AUCOWL < 1%). For ever-smokers, OWL outperformed PLCOm2012 and PLCOall2014 among ever-smokers in validation set 1 (AUCOWL = 0.842, 95% CI: 0.814-0.871; AUCPLCOm2012 = 0.792, 95% CI: 0.760-0.823; AUCPLCOall2014 = 0.791, 95% CI: 0.760-0.822, all p < 0.001). OWL remained comparable to PLCOm2012 and PLCOall2014 in discrimination (AUC difference from -0.014 to 0.008) among the ever-smokers in validation sets 2 to 5. In all the validation sets, OWL outperformed LLPv3 among the general population and the ever-smokers. Of note, OWL showed significantly better calibration than PLCOm2012, PLCOall2014 (RIEO from 43.1% to 92.3%, all p < 0.001), and LLPv3 (RIEO from 41.4% to 98.7%, all p < 0.001) in most cases. For clinical utility, OWL exhibited significant improvement in average net benefits (NB) over PLCOall2014 in validation set 1 (NB improvement: 32, p < 0.001); among ever smokers of validation set 1, OWL (average NB = 289) retained significant improvement over PLCOm2012 (average NB = 213) (p < 0.001). OWL had equivalent NBs with PLCOm2012 and PLCOall2014 in PLCO and NLST populations, while outperforming LLPv3 in the three populations. INTERPRETATION OWL, with a high degree of predictive accuracy and robustness, is a general framework with scientific justifications and clinical utility that can aid in screening individuals with high risks of lung cancer. FUNDING National Natural Science Foundation of China, the US NIH.
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Affiliation(s)
- Zoucheng Pan
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yunzhi Lin
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Longyao Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xiang Wang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Qian Ye
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Xuan Wang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - Yang Zhao
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China
| | - David C Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, 211166, China; Peking University Center for Public Health and Epidemic Preparedness & Response, Xueyuan Road, Haidian District, Beijing 100191, China.
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Sanchez R, Vaughan Sarrazin MS, Hoffman RM. Timely Curative Treatment and Overall Mortality Among Veterans With Stage I NSCLC. JTO Clin Res Rep 2023; 4:100455. [PMID: 36908685 PMCID: PMC9995692 DOI: 10.1016/j.jtocrr.2022.100455] [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: 10/15/2022] [Revised: 12/25/2022] [Accepted: 12/27/2022] [Indexed: 12/29/2022] Open
Abstract
Introduction Early stage lung cancer (LC) outcomes depend on the receipt of timely therapy. We aimed to determine the proportions of Veterans with stage I NSCLC in the age group eligible for LC screening (LCS) receiving timely curative treatment (≤12 wk after diagnosis), the factors associated with timely treatment and modality, and the factors associated with overall mortality. Methods Retrospective cohort study in Veterans aged 55 to 80 years when diagnosed with stage I NSCLC during 2011 to 2015. We used multivariate logistic regression models to determine factors associated with receiving timely therapy and receiving surgery versus stereotactic body radiation therapy (SBRT). We used multivariate Cox proportional hazards regression analysis to determine factors associated with overall mortality. Results We identified 4796 Veterans with stage I NSCLC; the cohort was predominantly older, White males, current or former smokers, and living in urban areas. Overall, 84% underwent surgery and 16% underwent SBRT. The median time to treatment was 63 days (61 d for surgery; 71 d for SBRT), with 30% treated more than 12 weeks. Unmarried Veterans with higher social deprivation index were less likely to receive timely therapy. Black race, female sex, and never smoking were associated with lower overall mortality. Older Veterans receiving treatment >12 wk, with higher comorbidity index, and squamous cell carcinoma had higher overall mortality. Conclusions A total of 30% of the Veterans with stage I NSCLC in the age group eligible for LCS received curative treatment more than 12 weeks after diagnosis, which was associated with higher overall mortality. Delays in LC treatment could decrease the mortality benefits of LCS among the Veterans.
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Affiliation(s)
- Rolando Sanchez
- Division of Pulmonary-Critical Care Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
- VA Iowa City Healthcare System, Iowa City, Iowa
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
| | - Mary S. Vaughan Sarrazin
- VA Iowa City Healthcare System, Iowa City, Iowa
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
- Center for Access and Delivery Research and Evaluation (CADRE) at the Iowa City VHA, Iowa City, Iowa
- Division of General Internal Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
| | - Richard M. Hoffman
- VA Iowa City Healthcare System, Iowa City, Iowa
- Holden Comprehensive Cancer Center, University of Iowa, Iowa City, Iowa
- Division of General Internal Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
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Williams BM, McAllister M, Erkmen C, Mody GN. Disparities in thoracic surgical oncology. J Surg Oncol 2023; 127:329-335. [PMID: 36630104 DOI: 10.1002/jso.27180] [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: 11/13/2022] [Revised: 12/07/2022] [Accepted: 12/07/2022] [Indexed: 01/12/2023]
Abstract
Disparities in access and outcomes of thoracic surgical oncology are long standing. This article examines the patient, population, and systems-level factors that contribute to these disparities and inequities. The need for research and policy to identify and solve these problems is apparent. As leaders in the field of thoracic oncology, surgeons will be instrumental in narrowing these gaps and moving the discipline forward.
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Affiliation(s)
- Brittney M Williams
- Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Miles McAllister
- Department of Surgery, Division of Thoracic Surgery, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Cherie Erkmen
- Department of Thoracic Surgery, Temple University Health System, Philadelphia, Pennsylvania, USA
| | - Gita N Mody
- Department of Surgery, Division of Cardiothoracic Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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71
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Endoscopic Technologies for Peripheral Pulmonary Lesions: From Diagnosis to Therapy. Life (Basel) 2023; 13:life13020254. [PMID: 36836612 PMCID: PMC9959751 DOI: 10.3390/life13020254] [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: 12/13/2022] [Revised: 01/07/2023] [Accepted: 01/09/2023] [Indexed: 01/18/2023] Open
Abstract
Peripheral pulmonary lesions (PPLs) are frequent incidental findings in subjects when performing chest radiographs or chest computed tomography (CT) scans. When a PPL is identified, it is necessary to proceed with a risk stratification based on the patient profile and the characteristics found on chest CT. In order to proceed with a diagnostic procedure, the first-line examination is often a bronchoscopy with tissue sampling. Many guidance technologies have recently been developed to facilitate PPLs sampling. Through bronchoscopy, it is currently possible to ascertain the PPL's benign or malignant nature, delaying the therapy's second phase with radical, supportive, or palliative intent. In this review, we describe all the new tools available: from the innovation of bronchoscopic instrumentation (e.g., ultrathin bronchoscopy and robotic bronchoscopy) to the advances in navigation technology (e.g., radial-probe endobronchial ultrasound, virtual navigation, electromagnetic navigation, shape-sensing navigation, cone-beam computed tomography). In addition, we summarize all the PPLs ablation techniques currently under experimentation. Interventional pulmonology may be a discipline aiming at adopting increasingly innovative and disruptive technologies.
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Guerra M. Predicting lung nodules malignancy. Pulmonology 2023:S2531-0437(22)00263-X. [PMID: 36639330 DOI: 10.1016/j.pulmoe.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 11/18/2022] [Accepted: 11/21/2022] [Indexed: 01/13/2023] Open
Affiliation(s)
- M Guerra
- Thoracic Surgery, Centro Hospitalar de Vila Nova de Gaia, Portugal; Faculty of Medicine of Oporto, Portugal.
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Chao HS, Tsai CY, Chou CW, Shiao TH, Huang HC, Chen KC, Tsai HH, Lin CY, Chen YM. Artificial Intelligence Assisted Computational Tomographic Detection of Lung Nodules for Prognostic Cancer Examination: A Large-Scale Clinical Trial. Biomedicines 2023; 11:biomedicines11010147. [PMID: 36672655 PMCID: PMC9856020 DOI: 10.3390/biomedicines11010147] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 12/23/2022] [Accepted: 12/29/2022] [Indexed: 01/11/2023] Open
Abstract
Low-dose computed tomography (LDCT) has emerged as a standard method for detecting early-stage lung cancer. However, the tedious computer tomography (CT) slide reading, patient-by-patient check, and lack of standard criteria to determine the vague but possible nodule leads to variable outcomes of CT slide interpretation. To determine the artificial intelligence (AI)-assisted CT examination, AI algorithm-assisted CT screening was embedded in the hospital picture archiving and communication system, and a 200 person-scaled clinical trial was conducted at two medical centers. With AI algorithm-assisted CT screening, the sensitivity of detecting nodules sized 4−5 mm, 6~10 mm, 11~20 mm, and >20 mm increased by 41%, 11.2%, 10.3%, and 18.7%, respectively. Remarkably, the overall sensitivity of detecting varied nodules increased by 20.7% from 67.7% to 88.4%. Furthermore, the sensitivity increased by 18.5% from 72.5% to 91% for detecting ground glass nodules (GGN), which is challenging for radiologists and physicians. The free-response operating characteristic (FROC) AI score was ≥0.4, and the AI algorithm standalone CT screening sensitivity reached >95% with an area under the localization receiver operating characteristic curve (LROC-AUC) of >0.88. Our study demonstrates that AI algorithm-embedded CT screening significantly ameliorates tedious LDCT practices for doctors.
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Affiliation(s)
- Heng-Sheng Chao
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Chiao-Yun Tsai
- Division of Thoracic Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
- Institute of Medicine, College of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Chung-Wei Chou
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Tsu-Hui Shiao
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
| | - Hsu-Chih Huang
- Division of Thoracic Surgery, Department of Surgery, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
- Institute of Medicine, College of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Kun-Chieh Chen
- Division of Pulmonary Medicine, Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
- Department of Applied Chemistry, National Chi Nan University, Nantou 545301, Taiwan
| | - Hao-Hung Tsai
- Institute of Medicine, College of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung 40201, Taiwan
- School of Medicine, College of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan
| | - Chin-Yu Lin
- Institute of New Drug Development, College of Medicine, China Medical University, Taichung 40402, Taiwan
- Tsuzuki Institute for Traditional Medicine, College of Pharmacy, China Medical University, Taichung 40402, Taiwan
- Department for Biomedical Engineering, Collage of Biomedical Engineering, China Medical University, Taichung 40402, Taiwan
| | - Yuh-Min Chen
- Department of Chest Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan
- Faculty of Medicine, School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Correspondence: ; Tel.: +886-2-28712121 (ext. 7865)
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Blood-based DNA methylation signatures in cancer: A systematic review. Biochim Biophys Acta Mol Basis Dis 2023; 1869:166583. [PMID: 36270476 DOI: 10.1016/j.bbadis.2022.166583] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 09/30/2022] [Accepted: 10/11/2022] [Indexed: 11/07/2022]
Abstract
DNA methylation profiles are in dynamic equilibrium via the initiation of methylation, maintenance of methylation and demethylation, which control gene expression and chromosome stability. Changes in DNA methylation patterns play important roles in carcinogenesis and primarily manifests as hypomethylation of the entire genome and the hypermethylation of individual loci. These changes may be reflected in blood-based DNA, which provides a non-invasive means for cancer monitoring. Previous blood-based DNA detection objects primarily included circulating tumor DNA/cell-free DNA (ctDNA/cfDNA), circulating tumor cells (CTCs) and exosomes. Researchers gradually found that methylation changes in peripheral blood mononuclear cells (PBMCs) also reflected the presence of tumors. Blood-based DNA methylation is widely used in early diagnosis, prognosis prediction, dynamic monitoring after treatment and other fields of clinical research on cancer. The reversible methylation of genes also makes them important therapeutic targets. The present paper summarizes the changes in DNA methylation in cancer based on existing research and focuses on the characteristics of the detection objects of blood-based DNA, including ctDNA/cfDNA, CTCs, exosomes and PBMCs, and their application in clinical research.
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Li X, Zhang G, Gao S, Xue Q, He J. Knowledge mapping visualization of the pulmonary ground-glass opacity published in the web of science. Front Oncol 2022; 12:1075350. [PMID: 36620580 PMCID: PMC9815441 DOI: 10.3389/fonc.2022.1075350] [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: 10/20/2022] [Accepted: 12/01/2022] [Indexed: 12/24/2022] Open
Abstract
Objectives With low-dose computed tomography(CT) lung cancer screening, many studies with an increasing number of patients with ground-glass opacity (GGO) are published. Hence, the present study aimed to analyze the published studies on GGO using bibliometric analysis. The findings could provide a basis for future research in GGO and for understanding past advances and trends in the field. Methods Published studies on GGO were obtained from the Web of Science Core Collection. A bibliometric analysis was conducted using the R package and VOSviewer for countries, institutions, journals, authors, keywords, and articles relevant to GGO. In addition, a bibliometric map was created to visualize the relationship. Results The number of publications on GGO has been increasing since 2011. China is ranked as the most prolific country; however, Japan has the highest number of citations for its published articles. Seoul National University and Professor Jin Mo Goo from Korea had the highest publications. Most top 10 journals specialized in the field of lung diseases. Radiology is a comprehensive journal with the greatest number of citations and highest H-index than other journals. Using bibliometric analysis, research topics on "prognosis and diagnosis," "artificial intelligence," "treatment," "preoperative positioning and minimally invasive surgery," and "pathology of GGO" were identified. Artificial intelligence diagnosis and minimally invasive treatment may be the future of GGO. In addition, most top 10 literatures in this field were guidelines for lung cancer and pulmonary nodules. Conclusions The publication volume of GGO has increased rapidly. The top three countries with the highest number of published articles were China, Japan, and the United States. Japan had the most significant number of citations for published articles. Most key journals specialized in the field of lung diseases. Artificial intelligence diagnosis and minimally invasive treatment may be the future of GGO.
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Affiliation(s)
| | | | | | - Qi Xue
- *Correspondence: Qi Xue, ; Jie He,
| | - Jie He
- *Correspondence: Qi Xue, ; Jie He,
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Rong F, Shi R, Hu L, Chen R, Wang D, Lv X, Zhao Y, Huang W, Yang Y, Zhou H, Hong K. Low-dose computed tomography for lung cancer screening in Anhui, China: A randomized controlled trial. Front Oncol 2022; 12:1059999. [PMID: 36591449 PMCID: PMC9795014 DOI: 10.3389/fonc.2022.1059999] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Accepted: 11/30/2022] [Indexed: 12/15/2022] Open
Abstract
Background Lung cancer is the leading cause of cancer-related death worldwide, with risk factors such as age and smoking. Low-dose computed tomography screening can reduce lung cancer mortality. However, its effectiveness in Asian populations remains unclear. Most Asian women with lung cancer are non-smokers who have not been screened. We conducted a randomized controlled trial to evaluate the performance of low-dose computed tomography screening in a Chinese population, including high-risk smokers and non-smokers exposed to passive smoking. The baseline data are reported in this study. Methods Between May and December 2019, eligible participants were randomized in a ratio of 1:1:1 to a screening (two arms) or control cohort. Non-calcified nodules/masses with a diameter >4 mm on low-dose computed tomography were considered positive findings. Results In total, 600 patients (mean age, 59.1 ± 6.9 years) underwent low-dose computed tomography. Women accounted for 31.5% (189/600) of patients; 89.9% (170/189) were non-smokers/passive smokers. At baseline, the incidence of lung cancer was 1.8% (11/600). The incidence of lung cancer was significantly lower in smokers than in female non-smokers/passive smokers (1.0% [4/415] vs. 4.1% [7/170], respectively; P=0.017). Stage 0-I lung cancer accounted for 90.9% (10/11) of cases. Conclusions We demonstrate the importance of including active smokers and female non-smokers/passive smokers in lung cancer screening programs. Further studies are needed to explore the risk factors, and long-term cost-benefit of screening Asian non-smoking women. Clinical trial registration http://chictr.org.cn/showproj.aspx?proj=39003, identifier ChiCTR1900023197.
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Takegami K, Hayashi H, Maeda T, Lee C, Nishigami R, Asahara T, Goto S, Kobayashi D, Ando M, Kanazawa Y, Yamashita K, Higashino K, Murakami S, Konishi T, Maki M. Thyroid dose reduction shield with the generation of less artifacts used for fast chest CT examination. Radiat Phys Chem Oxf Engl 1993 2022. [DOI: 10.1016/j.radphyschem.2022.110635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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Liu Y, Pan IWE, Tak HJ, Vlahos I, Volk R, Shih YCT. Assessment of Uptake Appropriateness of Computed Tomography for Lung Cancer Screening According to Patients Meeting Eligibility Criteria of the US Preventive Services Task Force. JAMA Netw Open 2022; 5:e2243163. [PMID: 36409492 PMCID: PMC9679877 DOI: 10.1001/jamanetworkopen.2022.43163] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2022] [Accepted: 09/30/2022] [Indexed: 11/23/2022] Open
Abstract
Importance Currently, computed tomography (CT) is used for lung cancer screening (LCS) among populations with various levels of compliance to the eligibility criteria from the US Preventive Services Task Force (USPSTF) recommendations and may represent suboptimal allocation of health care resources. Objective To evaluate the appropriateness of CT LCS according to the USPSTF eligibility criteria. Design, Setting, and Participants This cross-sectional study used the 2019 Behavioral Risk Factor Surveillance System (BRFSS) survey. Participants included individuals who responded to the LCS module administered in 20 states and had valid answers to questions regarding screening and smoking history. Data were analyzed between October 2021 and August 2022. Exposures Screening eligibility groups were categorized according to the USPSTF 2013 recommendations, and subgroups of individuals who underwent LCS were analyzed. Main Outcomes and Measures Main outcomes included LCS among the screening-eligible population and the proportions of the screened populations according to compliance categories established from the USPSTF 2013 and 2021 recommendations. In addition, the association between respondents' characteristics and LCS was evaluated for the subgroup who were screened despite not meeting any of the 3 USPSTF screening criteria: age, pack-year, and years since quitting smoking. Results A total of 96 097 respondents were identified for the full study cohort, and 2 subgroups were constructed: (1) 3374 respondents who reported having a CT or computerized axial tomography to check for lung cancer and (2) 33 809 respondents who did not meet any screening eligibility criteria. The proportion of participants who were under 50 years old was 53.1%; between 50 and 54, 9.1%; between 55 and 79, 33.8%; and over 80, 4.0%. A total of 51 536 (50.9%) of the participants were female. According to the USPSTF 2013 recommendation, 807 (12.8%) of the screening-eligible population underwent LCS. Among those who were screened, only 807 (20.9%) met all 3 screening eligibility criteria, whereas 538 (20.1%) failed to meet any criteria. Among respondents in subgroup 2, being of older age and having a history of stroke, chronic obstructive pulmonary disease, kidney disease, or diabetes were associated with higher likelihood of LCS. Conclusions and Relevance In this cross-sectional study of the BRFSS 2019 survey, the low uptake rate among screening-eligible patients undermined the goal of LCS of early detection. Suboptimal screening patterns could increase health system costs and add financial stress, psychological burden, and physical harms to low-risk patients, while failing to provide high-quality preventive services to individuals at high risk of lung cancer.
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Affiliation(s)
- Yu Liu
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston
| | - I-Wen Elaine Pan
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston
| | - Hyo Jung Tak
- Department of Health Services Research and Administration, University of Nebraska Medical Center, Omaha
| | - Ioannis Vlahos
- Thoracic Imaging Department, The University of Texas MD Anderson Cancer Center, Houston
| | - Robert Volk
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston
| | - Ya-Chen Tina Shih
- Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston
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He C, Liu J, Li Y, Lin L, Qing H, Guo L, Hu S, Zhou P. Quantitative parameters of enhanced dual-energy computed tomography for differentiating lung cancers from benign lesions in solid pulmonary nodules. Front Oncol 2022; 12:1027985. [PMID: 36276069 PMCID: PMC9582258 DOI: 10.3389/fonc.2022.1027985] [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: 08/25/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives This study aimed to investigate the ability of quantitative parameters of dual-energy computed tomography (DECT) and nodule size for differentiation between lung cancers and benign lesions in solid pulmonary nodules. Materials and Methods A total of 151 pathologically confirmed solid pulmonary nodules including 78 lung cancers and 73 benign lesions from 147 patients were consecutively and retrospectively enrolled who underwent dual-phase contrast-enhanced DECT. The following features were analyzed: diameter, volume, Lung CT Screening Reporting and Data System (Lung-RADS) categorization, and DECT-derived quantitative parameters including effective atomic number (Zeff), iodine concentration (IC), and normalized iodine concentration (NIC) in arterial and venous phases. Multivariable logistic regression analysis was used to build a combined model. The diagnostic performance was assessed by area under curve (AUC) of receiver operating characteristic curve, sensitivity, and specificity. Results The independent factors for differentiating lung cancers from benign solid pulmonary nodules included diameter, Lung-RADS categorization of diameter, volume, Zeff in arterial phase (Zeff_A), IC in arterial phase (IC_A), NIC in arterial phase (NIC_A), Zeff in venous phase (Zeff_V), IC in venous phase (IC_V), and NIC in venous phase (NIC_V) (all P < 0.05). The IC_V, NIC_V, and combined model consisting of diameter and NIC_V showed good diagnostic performance with AUCs of 0.891, 0.888, and 0.893, which were superior to the diameter, Lung-RADS categorization of diameter, volume, Zeff_A, and Zeff_V (all P < 0.001). The sensitivities of IC_V, NIC_V, and combined model were higher than those of IC_A and NIC_A (all P < 0.001). The combined model did not increase the AUCs compared with IC_V (P = 0.869) or NIC_V (P = 0.633). Conclusion The DECT-derived IC_V and NIC_V may be useful in differentiating lung cancers from benign lesions in solid pulmonary nodules.
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Affiliation(s)
| | | | | | | | | | | | | | - Peng Zhou
- Department of Radiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
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Cao W, Tan F, Liu K, Wu Z, Wang F, Yu Y, Wen Y, Qin C, Xu Y, Zhao L, Tang W, Li J, Dong X, Zheng Y, Yang Z, Su K, Li F, Shi J, Ren J, Liu Y, Yu L, Wei D, Dong D, Cao J, Zhang S, Yan S, Wang N, Du L, Chen W, Li N, He J. Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study. EClinicalMedicine 2022; 52:101594. [PMID: 35923428 PMCID: PMC9340538 DOI: 10.1016/j.eclinm.2022.101594] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 07/13/2022] [Accepted: 07/13/2022] [Indexed: 12/17/2022] Open
Abstract
Background Optimal uptake rates of low-dose computed tomography (LDCT) scans are essential for lung cancer screening (LCS) to confer mortality benefits. We aimed to outline the process model of the LCS programme in China, identify the high-risk individuals with low uptake based on a prospective multi-centre population-based cohort, and further explore associated structural characteristics. Methods A total of 221,955 individuals at high-risk for lung cancer from the National Lung Cancer Screening cohort were included. The logistic regression model was performed to identify the individual characteristics associated with the uptake of LCS, defined as whether the high-risk individual undertook LDCT scans in designated hospitals within six months following the initial risk assessment. The linear regression model was adopted to explore the structural characteristics associated with the uptake rates in 186 communities. Findings The overall uptake rate was 33·0%. The uptake rate was negatively correlated with the incidence of advanced-stage lung cancer (Pearson's coefficient -0·88, p-value 0·0007). Multivariable regression models found that lower uptake rates were associated with males (OR 0·88, 95%CI 0·85-0·91), current smokers (OR 0·93, 95%CI 0·90-0·96), individuals with depressive symptoms (OR 0·92, 95%CI 0·90-0·94), and the structural characteristics, including longer structural delays in initiating LDCT scans (30-90 days vs. ≤14 days: β -7·17, 95%CI -12·76∼ -1·57; >90 days vs. ≤14 days: β -13·69, 95%CI -24·61∼ -2·76), no media-assisted publicity (β -6·43, 95%CI -11·26∼ -1·60), and no navigation assistance (β -5·48, 95%CI -10·52∼ -0·44). Interpretation Multifaceted interventions are recommended, which focus on poor-uptake individuals and integrate the 'assessment-to-timely-screening' approach to minimise structural delays, media publicity, and a navigation assistance along the centralised screening pathway. Funding Ministry of Finance and National Health Commission of the People's Republic of China.
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Affiliation(s)
- Wei Cao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Fengwei Tan
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Kuangyu Liu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, United States
| | - Zheng Wu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Fei Wang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yiwen Yu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yan Wen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Chao Qin
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yongjie Xu
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Liang Zhao
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Wei Tang
- Department of Diagnostic Radiology, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Panjiayuan Nanli, Chaoyang District, Beijing 100021, China
| | - Jiang Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Xuesi Dong
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yadi Zheng
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Zhuoyu Yang
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Kai Su
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Fang Li
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Jufang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Jiansong Ren
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yunyong Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen 518116, China
| | - Lianzheng Yu
- Liaoning Center for Disease Control and Prevention, Shenyang 110005, China
| | - Donghua Wei
- Office for Cancer Prevention and Control, Anhui Provincial Cancer Hospital, Hefei 230031, China
| | - Dong Dong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou 221000, China
| | - Ji Cao
- Cancer Prevention and Control Office, Affiliated Tumor Hospital of Guangxi Medical University, Nanning 530021, China
| | - Shaokai Zhang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou 450008, China
| | - Shipeng Yan
- Department of Cancer Prevention and Control, Hunan Cancer Hospital & The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410000, China
| | - Ning Wang
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Beijing Office for Cancer Prevention and Control, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Lingbin Du
- Department of Cancer Prevention, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital)/Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou 310022, China
| | - Wanqing Chen
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Ni Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
- Chinese Academy of Medical Sciences Key Laboratory for National Cancer Big Data Analysis and Implement, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Jie He
- Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Yuan J, Sun Y, Xu F, Li M, Fan M, Zhang C, Wang K, Li H, Bu X, Yan X, Wang J, Ma J, Zhang G, Chen M, Ren H. Cost-effectiveness of lung cancer screening combined with nurse-led smoking cessation intervention: A population-based microsimulation study. Int J Nurs Stud 2022; 134:104319. [DOI: 10.1016/j.ijnurstu.2022.104319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 05/17/2022] [Accepted: 06/25/2022] [Indexed: 10/17/2022]
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Xie M, Gao J, Ma X, Wu C, Zang X, Wang Y, Deng H, Yao J, Sun T, Yu Z, Liu S, Zhuang G, Xue X, Wu J, Wang J. Consolidation radiographic morphology can be an indicator of the pathological basis and prognosis of partially solid nodules. BMC Pulm Med 2022; 22:369. [PMID: 36171571 PMCID: PMC9520850 DOI: 10.1186/s12890-022-02165-x] [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: 05/21/2022] [Accepted: 09/14/2022] [Indexed: 11/10/2022] Open
Abstract
Background Part-solid nodules (PSNs) have gradually shifted to defining special clinical subtypes. Commonly, the solid portions of PSNs show various radiological morphologies, of which the corresponding pathological basis and prognosis are unclear. We conducted a radiological–pathological evaluation to determine the histopathologic basis of different consolidation radiographic morphologies related to prognosis. Materials and methods A cohort of 275 patients with a surgical pathological diagnosis of lung adenocarcinoma were enrolled. Preoperative computed tomography (CT) images of the PSNs were recorded and assessed. A panel of 103 patients with complete pathological specimens was selected to examine the radiological–pathological associations, and follow-up was performed to identify the prognosis. Results Of the 275 patients, punctate consolidation was observed radiologically in 43/275 (15.7%), stripe consolidation in 68/275 (24.7%), and irregular consolidation in 164/275 (59.6%) patients. The radiological morphology of the solid components was significantly associated with the histopathological subtypes (P < 0.001). Visual punctate solid components on CT correlated with tertiary lymphoid structures, stripe solid components on CT correlated with fibrotic scar, and irregular solid components on CT correlated with invasion. PSNs with regular consolidation had a better prognosis than those with irregular consolidation. Conclusion Radiological morphology of solid components in PSNs can indicate the pathological basis and is valuable for prognosis. In particular, irregular solid components in PSNs usually indicate serious invasive growth, which should be taken with caution during assessment.
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Affiliation(s)
- Mei Xie
- Department of Respiratory and Critical Care, Chinese PLA General Hospital, the First Medical Centre, Beijing, 100835, People's Republic of China.,Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China
| | - Jie Gao
- Department of Pathology, Chinese PLA General Hospital, Beijing, 100835, People's Republic of China
| | - Xidong Ma
- Department of Respiratory and Critical Care, Chinese PLA General Hospital, the First Medical Centre, Beijing, 100835, People's Republic of China
| | - Chongchong Wu
- Department of Radiology, Chinese PLA General Hospital, Beijing, 100835, People's Republic of China
| | - Xuelei Zang
- Center of Clinical Laboratory Medicine, First Medical Centre, Chinese PLA General Hospital, 100835, Beijing, People's Republic of China
| | - Yuanyong Wang
- Department of Thoracic Surgery, Tangdu Hospital of Air Force Military Medical University, Xi'an, 710038, Shanxi, People's Republic of China
| | - Hui Deng
- Department of Respiratory and Critical Care, Beijing Shijitan Hospital, Capital Medical University, 100038, Beijing, People's Republic of China
| | - Jie Yao
- Department of Respiratory and Critical Care, Beijing Shijitan Hospital, Capital Medical University, 100038, Beijing, People's Republic of China
| | - Tingting Sun
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China
| | - Zhaofeng Yu
- School of Medicine, Peking University, Beijing, 100871, People's Republic of China
| | - Sanhong Liu
- Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Guanglei Zhuang
- Shanghai Key Laboratory of Gynecologic Oncology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, 200000, Shanghai, People's Republic of China.
| | - Xinying Xue
- Department of Respiratory and Critical Care, Beijing Shijitan Hospital, Capital Medical University, 100038, Beijing, People's Republic of China.
| | - Jianlin Wu
- Department of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.
| | - Jianxin Wang
- Department of Respiratory and Critical Care, Chinese PLA General Hospital, the First Medical Centre, Beijing, 100835, People's Republic of China.
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Tang Y, Li Q, Zhang D, Ma Z, Yang J, Cui Y, Zhang A. Cuproptosis-related gene signature correlates with the tumor immune features and predicts the prognosis of early-stage lung adenocarcinoma patients. Front Genet 2022; 13:977156. [PMID: 36186452 PMCID: PMC9515444 DOI: 10.3389/fgene.2022.977156] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Although a majority of early-stage lung adenocarcinoma (es-LUAD) patients have a favorable prognosis, there are still some cases with a risk of recurrence and metastasis. Cuproptosis is a new form of death that differs from other programmed cell death. However, no study has been reported for setting a prognostic model of es-LUAD using cuproptosis pattern-related genes.Methods: Using multiple R packages, the data from the GEO database was processed, and es-LUAD patients was classified into two patterns based on cuproptosis-related genes. Key differentially expressed genes (DEGs) in the two patterns were screened to construct a prognostic signature to assess differences in biological processes and immunotherapy responses in es-LUAD. Tumor microenvironment (TME) in es-LUAD was analyzed using algorithms such as TIMER and ssGSEA. Then, a more accurate nomogram was constructed by combining risk scores with clinical factors.Results: Functional enrichment analysis revealed that DEGs in two patterns were correlated with organelle fission, nuclear division, chromosome segregation, and cycle-related pathways. Univariate Cox regression and Lasso-Cox regression analyses identified six prognostic genes: ASPM, CCNB2, CDC45, CHEK1, NCAPG, and SPAG5. Based on the constructed model, we found that the high-risk group patients had higher expression of immune checkpoints (CTLA4, LAG3, PD-L1, TIGIT and TIM3), and a lower abundance of immune cells. Lastly, the nomogram was highly accurate in predicting the 1-, 3-, and 5-year survival status of patients with es-LUAD based on risk scores and clinical factors.Conclusion: The cuproptosis pattern-related signature can serve as a potential marker for clinical decision-making. It has huge potential in the future to guide the frequency of follow-up and adjuvant therapy for es-LUAD patients.
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Affiliation(s)
- Yu Tang
- Department of Thoracic and Cardiovascular Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Qifan Li
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Daoqi Zhang
- Department of Internal Medicine Teaching and Research Section, Xuancheng Vocational and Technical College, Xuancheng, China
| | - Zijian Ma
- Department of Thoracic and Cardiovascular Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
| | - Jian Yang
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Aiping Zhang, ; Jian Yang, ; Yuan Cui,
| | - Yuan Cui
- Department of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- Institute of Thoracic Surgery, The First Affiliated Hospital of Soochow University, Suzhou, China
- *Correspondence: Aiping Zhang, ; Jian Yang, ; Yuan Cui,
| | - Aiping Zhang
- Department of Thoracic and Cardiovascular Surgery, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- *Correspondence: Aiping Zhang, ; Jian Yang, ; Yuan Cui,
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84
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Liu Z, Liu X, Ni L. Analysis of pulmonary nodules detected by annual low-dose computed tomography in the elderly during a 10-year follow-up. Geriatr Gerontol Int 2022; 22:865-869. [PMID: 36065163 DOI: 10.1111/ggi.14479] [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: 04/11/2022] [Revised: 08/08/2022] [Accepted: 08/17/2022] [Indexed: 11/29/2022]
Abstract
AIM To describe pulmonary nodules detected by annual low-dose computed tomography (LDCT) in the elderly during a 10-year follow-up, and to provide a basis for clinical decision-making in the elderly. METHODS In this retrospective study, patients who completed at least a 3-year follow-up visit with annual LDCT imaging data were eligible for inclusion. The evolution of pulmonary nodules was evaluated, including malignant, suspicious malignant, benign and undetermined nodules. Additionally, the nature and outcome of new nodules during the follow-up were analyzed. RESULTS For the 365 subjects included, 899 positive pulmonary nodules were detected in 286 patients. Among these there were 788 solid nodules, 20 part-solid nodules and 91 nonsolid nodules. The detection rate of positive nodules and of lung cancer was 78.4% and 5.5%, respectively. 99.7% (786/788) of solid nodules were benign, and 75% (15/20) of part-solid nodules and 28.6% (26/91) of nonsolid nodules were malignant or suspected malignant. 124 new positive nodules appeared during the annual follow-up, but 58.9% of them subsequently disappeared. Significant higher detection rates of 10-20-mm nodules (P = 0.0485) and suspicious malignant nodules (P = 0.017) were observed in subjects over 75 years old as compared with those under 75 years old. CONCLUSIONS Solid nodules accounted for the highest proportion of lung nodules screened at baseline, and most of them were benign. The malignant probability of part-solid nodules was the highest. Most newly appeared nodules disappeared during subsequent follow-up. The proportions of suspicious malignant nodules and 10-20-mm nodules in subjects over 75 years old were higher than in those under 75 years old. Geriatr Gerontol Int 2022; ••: ••-••.
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Affiliation(s)
- Zhonghui Liu
- The Geriatrics Department, Peking University First Hospital, Beijing, China
| | - Xinmin Liu
- The Geriatrics Department, Peking University First Hospital, Beijing, China
| | - Lianfang Ni
- The Geriatrics Department, Peking University First Hospital, Beijing, China
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Majeed A, Ruane B, Shusted CS, Austin M, Mirzozoda K, Pimpinelli M, Vojnika J, Ward L, Sundaram B, Lakhani P, Kane G, Lev Y, Barta JA. Frequency of Statin Prescription Among Individuals with Coronary Artery Calcifications Detected Through Lung Cancer Screening. Am J Med Qual 2022; 37:388-395. [PMID: 35302536 DOI: 10.1097/jmq.0000000000000053] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Individuals eligible for lung cancer screening (LCS) are at risk for atherosclerotic cardiovascular disease (ASCVD) due to smoking history. Coronary artery calcifications (CAC), a common incidental finding on low-dose CT (LDCT) for LCS, is a predictor of cardiovascular events. Despite findings of high ASCVD risk and CAC, a substantial proportion of LCS patients are not prescribed primary preventive statin therapy for ASCVD. We assessed the frequency of statin prescription in LCS patients with moderate levels of CAC. Among 259 individuals with moderate CAC, 95% had ASCVD risk ≥ 7.5%. Despite this, 27% of patients were statin-free prior to LDCT and 21.2% remained statin-free after LDCT showing moderate CAC. Illustratively, while a substantial proportion of LCS patients are statin-eligible, many lack a statin prescription, even after findings of CAC burden. CAC reporting should be standardized, and interdisciplinary communication should be optimized to ensure that LCS patients are placed on appropriate preventive therapy.
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Affiliation(s)
- Amry Majeed
- Sidney Kimmel Medical College at Thomas Jefferson University
| | - Brooke Ruane
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University
| | - Christine S Shusted
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University
| | - Melissa Austin
- Sidney Kimmel Medical College at Thomas Jefferson University
| | - Khulkar Mirzozoda
- Department of Medicine, Division of Internal Medicine, Thomas Jefferson University
| | | | - Jetmir Vojnika
- Department of Medicine, Division of Internal Medicine, Thomas Jefferson University
| | - Lawrence Ward
- Department of Medicine, Division of Internal Medicine, Thomas Jefferson University
| | | | - Paras Lakhani
- Department of Radiology, Thomas Jefferson University
| | - Gregory Kane
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University
| | - Yair Lev
- Division of Cardiology, Thomas Jefferson University
| | - Julie A Barta
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University
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Addressing Lung Cancer Screening Disparities: What Does It Mean to Be Centralized? Ann Am Thorac Soc 2022; 19:1457-1458. [PMID: 36048121 PMCID: PMC9447398 DOI: 10.1513/annalsats.202206-495ed] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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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: 17] [Impact Index Per Article: 8.5] [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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Núñez ER, Caverly TJ, Zhang S, Glickman ME, Qian SX, Boudreau JH, Miller DR, Wiener RS. Invasive Procedures and Associated Complications After Initial Lung Cancer Screening in a National Cohort of Veterans. Chest 2022; 162:475-484. [PMID: 35231480 PMCID: PMC9424329 DOI: 10.1016/j.chest.2022.02.031] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 01/21/2022] [Accepted: 02/13/2022] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Little is known about rates of invasive procedures and associated complications after lung cancer screening (LCS) in nontrial settings. RESEARCH QUESTION What are the frequency of invasive procedures, complication rates, and factors associated with complications in a national sample of veterans screened for lung cancer? STUDY DESIGN AND METHODS We conducted a retrospective cohort analysis of veterans who underwent LCS in any Veterans Health Administration (VA) facility between 2013 and 2019 and identified veterans who underwent invasive procedures within 10 months of initial LCS. The primary outcome was presence of a complication within 10 days after an invasive procedure. We conducted hierarchical mixed-effects logistic regression analyses to determine patient- and facility-level factors associated with complications resulting from an invasive procedure. RESULTS Our cohort of 82,641 veterans who underwent LCS was older, more racially diverse, and had more comorbidities than National Lung Screening Trial (NLST) participants. Overall, 1,741 veterans (2.1%) underwent an invasive procedure after initial screening, including 856 (42.3%) bronchoscopies, 490 (24.2%) transthoracic needle biopsies, and 423 (20.9%) thoracic surgeries. Among veterans who underwent procedures, 151 (8.7%) experienced a major complication (eg, respiratory failure, prolonged hospitalization) and an additional 203 (11.7%) experienced an intermediate complication (eg, pneumothorax, pleural effusion). Veterans who underwent thoracic surgery (OR, 7.70; 95% CI, 5.48-10.81), underwent multiple nonsurgical procedures (OR, 1.49; 95% CI, 1.15-1.92), or carried a dementia diagnosis (OR, 3.91; 95% CI, 1.79-8.52) were more likely to experience complications. Invasive procedures were performed less often than in the NLST (2.1% vs 4.2%), but veterans were more likely to experience complications after each type of procedure. INTERPRETATION These findings may reflect a higher threshold to perform procedures in veteran populations with multiple comorbidities and higher risks of complications. Future work should focus on optimizing the identification of patients whose chance of benefit likely outweighs the complication risks.
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Zhang R, Shen S, Wei Y, Zhu Y, Li Y, Chen J, Guan J, Pan Z, Wang Y, Zhu M, Xie J, Xiao X, Zhu D, Li Y, Albanes D, Landi MT, Caporaso NE, Lam S, Tardon A, Chen C, Bojesen SE, Johansson M, Risch A, Bickeböller H, Wichmann HE, Rennert G, Arnold S, Brennan P, McKay JD, Field JK, Shete SS, Le Marchand L, Liu G, Andrew AS, Kiemeney LA, Zienolddiny-Narui S, Behndig A, Johansson M, Cox A, Lazarus P, Schabath MB, Aldrich MC, Dai J, Ma H, Zhao Y, Hu Z, Hung RJ, Amos CI, Shen H, Chen F, Christiani DC. A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians. J Thorac Oncol 2022; 17:974-990. [PMID: 35500836 PMCID: PMC9512697 DOI: 10.1016/j.jtho.2022.04.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/13/2022] [Accepted: 04/20/2022] [Indexed: 01/12/2023]
Abstract
INTRODUCTION Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC). METHODS Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers. RESULTS With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification. CONCLUSIONS Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.
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Affiliation(s)
- Ruyang Zhang
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Sipeng Shen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yongyue Wei
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Ying Zhu
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Jiajin Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Jinxing Guan
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Zoucheng Pan
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yuzhuo Wang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Meng Zhu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Junxing Xie
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Xiangjun Xiao
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Dakai Zhu
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Yafang Li
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Demetrios Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Neil E Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland
| | - Stephen Lam
- Department of Medicine, British Columbia Cancer Agency, University of British Columbia, Vancouver, Canada
| | - Adonina Tardon
- Faculty of Medicine, University of Oviedo and CIBERESP, Oviedo, Spain
| | - Chu Chen
- Department of Epidemiology, University of Washington School of Public Health, Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Angela Risch
- Department of Biosciences and Cancer Cluster Salzburg, University of Salzburg, Salzburg, Austria
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg August University Göttingen, Göttingen, Germany
| | - H-Erich Wichmann
- Institute of Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians University, Munich, Germany
| | - Gadi Rennert
- Clalit National Cancer Control Center, Carmel Medical Center and Technion Faculty of Medicine, Carmel, Haifa, Israel
| | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, Kentucky
| | - Paul Brennan
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - James D McKay
- Section of Genetics, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - John K Field
- Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - Sanjay S Shete
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii
| | - Geoffrey Liu
- Princess Margaret Cancer Centre, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Angeline S Andrew
- Department of Epidemiology, Department of Community and Family Medicine, Dartmouth Geisel School of Medicine, Hanover, New Hampshire
| | - Lambertus A Kiemeney
- Department for Health Evidence, Department of Urology, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Annelie Behndig
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | | | - Angela Cox
- Department of Oncology and Metabolism, The Medical School, University of Sheffield, Sheffield, United Kingdom
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy, Washington State University, Spokane, Washington
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida
| | - Melinda C Aldrich
- Department of Thoracic Surgery and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Juncheng Dai
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Hongxia Ma
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Yang Zhao
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China
| | - Zhibin Hu
- China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Christopher I Amos
- The Institute for Clinical and Translational Research, Department of Medicine, Baylor College of Medicine, Houston, Texas
| | - Hongbing Shen
- China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Feng Chen
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, People's Republic of China; China International Cooperation Center (CICC) for Environment and Human Health, Nanjing Medical University, Nanjing, People's Republic of China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, People's Republic of China.
| | - David C Christiani
- Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
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Núñez ER, Caverly TJ, Zhang S, Glickman ME, Qian SX, Boudreau JH, Miller DR, Slatore CG, Wiener RS. Factors Associated With Declining Lung Cancer Screening After Discussion With a Physician in a Cohort of US Veterans. JAMA Netw Open 2022; 5:e2227126. [PMID: 35972738 PMCID: PMC9382440 DOI: 10.1001/jamanetworkopen.2022.27126] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 06/29/2022] [Indexed: 12/17/2022] Open
Abstract
Importance Lung cancer screening (LCS) is underused in the US, particularly in underserved populations, and little is known about factors associated with declining LCS. Guidelines call for shared decision-making when LCS is offered to ensure informed, patient-centered decisions. Objective To assess how frequently veterans decline LCS and examine factors associated with declining LCS. Design, Setting, and Participants This retrospective cohort study included LCS-eligible US veterans who were offered LCS between January 1, 2013, and February 1, 2021, by a physician at 1 of 30 Veterans Health Administration (VHA) facilities that routinely used electronic health record clinical reminders documenting LCS eligibility and veterans' decisions to accept or decline LCS. Data were obtained from the Veterans Affairs (VA) Corporate Data Warehouse or Medicare claims files from the VA Information Resource Center. Main Outcomes and Measures The main outcome was documentation, in clinical reminders, that veterans declined LCS after a discussion with a physician. Logistic regression analyses with physicians and facilities as random effects were used to assess factors associated with declining LCS compared with agreeing to LCS. Results Of 43 257 LCS-eligible veterans who were offered LCS (mean [SD] age, 64.7 [5.8] years), 95.9% were male, 84.2% were White, and 37.1% lived in a rural zip code; 32.0% declined screening. Veterans were less likely to decline LCS if they were younger (age 55-59 years: odds ratio [OR], 0.69; 95% CI, 0.64-0.74; age 60-64 years: OR, 0.80; 95% CI, 0.75-0.85), were Black (OR, 0.80; 95% CI, 0.73-0.87), were Hispanic (OR, 0.62; 95% CI, 0.49-0.78), did not have to make co-payments (OR, 0.92; 95% CI, 0.85-0.99), or had more frequent VHA health care utilization (outpatient: OR, 0.70; 95% CI, 0.67-0.72; emergency department: OR, 0.86; 95% CI, 0.80-0.92). Veterans were more likely to decline LCS if they were older (age 70-74 years: OR, 1.27; 95% CI, 1.19-1.37; age 75-80 years: OR, 1.93; 95% CI, 1.73-2.17), lived farther from a VHA screening facility (OR, 1.06; 95% CI, 1.03-1.08), had spent more days in long-term care (OR, 1.13; 95% CI, 1.07-1.19), had a higher Elixhauser Comorbidity Index score (OR, 1.04; 95% CI, 1.03-1.05), or had specific cardiovascular or mental health conditions (congestive heart failure: OR, 1.25; 95% CI, 1.12-1.39; stroke: OR, 1.14; 95% CI, 1.01-1.28; schizophrenia: OR, 1.87; 95% CI, 1.60-2.19). The physician and facility offering LCS accounted for 19% and 36% of the variation in declining LCS, respectively. Conclusions and Relevance In this cohort study, older veterans with serious comorbidities were more likely to decline LCS and Black and Hispanic veterans were more likely to accept it. Variation in LCS decisions was accounted for more by the facility and physician offering LCS than by patient factors. These findings suggest that shared decision-making conversations in which patients play a central role in guiding care may enhance patient-centered care and address disparities in LCS.
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Affiliation(s)
- Eduardo R. Núñez
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
| | - Tanner J. Caverly
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan Medical School, Ann Arbor
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
| | - Sanqian Zhang
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- Department of Statistics, Harvard University, Cambridge, Massachusetts
| | - Mark E. Glickman
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
| | - Shirley X. Qian
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
| | - Jacqueline H. Boudreau
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
| | - Donald R. Miller
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
| | - Christopher G. Slatore
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland, Oregon
- Division of Pulmonary and Critical Care Medicine, Oregon Health & Science University, Portland
| | - Renda Soylemez Wiener
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
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91
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Huo B, Manos D, Xu Z, Matheson K, Chun S, Fris J, Wallace AMR, French DG. Screening Criteria Evaluation for Expansion in Pulmonary Neoplasias (SCREEN). Semin Thorac Cardiovasc Surg 2022; 35:769-780. [PMID: 35878739 DOI: 10.1053/j.semtcvs.2022.06.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 06/06/2022] [Indexed: 12/14/2022]
Abstract
The SCREEN study investigated screening eligibility and survival outcomes between heavy smokers and light-or-never-smokers with lung cancer to determine whether expanded risk factor analysis is needed to refine screening criteria. SCREEN is a retrospective study of 917 lung cancer patients diagnosed between 2005 and 2018 in Nova Scotia, Canada. Screening eligibility was determined using the National Lung Screening Trial (NSLT) criteria. Mortality risk between heavy smokers and light-or-never-smokers was compared using proportional-hazards models. The median follow-up was 2.9 years. The cohort was comprised of 179 (46.1%) female heavy smokers and 306 (57.8%) female light-or-never-smokers. Light-or-never-smokers were more likely to have a diagnosis of adenocarcinoma [n=378 (71.6%)] compared to heavy smokers [n=234 (60.5%); P< 0.001]. Heavy smokers were more frequently diagnosed with squamous cell carcinoma [n=111 (28.7%)] compared to light-or-never-smokers, [n=100 (18.9%); P< 0.001]. Overall, 36.9% (338) of patients met NLST screening criteria. There was no difference in 5-year survival between light-or-never-smokers and heavy smokers [55.2% (338) vs 58.5% (529); P = 0.408; HR 1.06, 95% CI 0.80-1.40; P = 0.704]. Multivariate analysis showed that males had an increased mortality risk [HR 2.00 (95% CI 1.57-2.54); P< 0.001]. Half of lung cancer patients were missed with the conventional screening criteria. There were more curable, stage 1 tumors among light-or-never-smokers. Smoking status and age alone may be insufficient predictors of lung cancer risk and prognosis. Expanded risk factor analysis is needed to refine lung cancer screening criteria.
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Affiliation(s)
- Bright Huo
- Faculty of Medicine, Dalhousie University, Halifax, NS, Canada
| | - Daria Manos
- Department of Diagnostic Radiology, Dalhousie University, Halifax, NS, Canada
| | - Zhaolin Xu
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
| | - Kara Matheson
- Research Methods Unit, Nova Scotia Health Authority, Halifax, NS, Canada
| | - Samuel Chun
- Department of Urology, Dalhousie University, Halifax, NS, Canada
| | - John Fris
- Department of Pathology, Dalhousie University, Halifax, NS, Canada
| | - Alison M R Wallace
- Department of Pathology, Dalhousie University, Halifax, NS, Canada; Division of Thoracic Surgery, Department of Surgery, Dalhousie University, Halifax, NS, Canada
| | - Daniel G French
- Division of Thoracic Surgery, Department of Surgery, Dalhousie University, Halifax, NS, Canada.
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Bade B, Gwin M, Triplette M, Wiener RS, Crothers K. Comorbidity and life expectancy in shared decision making for lung cancer screening. Semin Oncol 2022; 49:S0093-7754(22)00057-4. [PMID: 35940959 DOI: 10.1053/j.seminoncol.2022.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/02/2022] [Accepted: 07/03/2022] [Indexed: 11/11/2022]
Abstract
Shared decision making (SDM) is an important part of lung cancer screening (LCS) that includes discussing the risks and benefits of screening, potential outcomes, patient eligibility and willingness to participate, tobacco cessation, and tailoring a strategy to an individual patient. More than other cancer screening tests, eligibility for LCS is nuanced, incorporating the patient's age as well as tobacco use history and overall health status. Since comorbidities and multimorbidity (ie, 2 or more comorbidities) impact the risks and benefits of LCS, these topics are a fundamental part of decision-making. However, there is currently little evidence available to guide clinicians in addressing comorbidities and an individual's "appropriateness" for LCS during SDM visits. Therefore, this literature review investigates the impact of comorbidities and multimorbidity among patients undergoing LCS. Based on available evidence and guideline recommendations, we identify comorbidities that should be considered during SDM conversations and review best practices for navigating SDM conversations in the context of LCS. Three conditions are highlighted since they concomitantly portend higher risk of developing lung cancer, potentially increase risk of screening-related evaluation and treatment complications and can be associated with limited life expectancy: chronic obstructive pulmonary disease, idiopathic pulmonary fibrosis, and human immunodeficiency virus infection.
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Affiliation(s)
- Brett Bade
- Veterans Affairs (VA) Connecticut Healthcare System, Section of Pulmonary, Critical Care, and Sleep Medicine, West Haven, CT, United States of America (USA); Yale University School of Medicine, Section of Pulmonary, Critical Care, and Sleep Medicine, New Haven, CT, USA.
| | - Mary Gwin
- University of Washington School of Medicine, Seattle, WA, USA
| | - Matthew Triplette
- University of Washington School of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Seattle, WA, USA; Fred Hutchinson Cancer Center, Clinical Research Division, Seattle, WA, USA
| | - Renda Soylemez Wiener
- Center for Healthcare Organization & Implementation Research and Medical Service, VA Boston Healthcare System, Boston, MA, USA; The Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
| | - Kristina Crothers
- University of Washington School of Medicine, Division of Pulmonary, Critical Care and Sleep Medicine, Seattle, WA, USA; VA Puget Sound Health Care System, Section of Pulmonary, Critical Care and Sleep Medicine, Seattle, WA, USA
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Rampariag R, Chernyavskiy I, Al-Ajam M, Tsay JCJ. Controversies and challenges in lung cancer screening. Semin Oncol 2022; 49:S0093-7754(22)00056-2. [PMID: 35907666 DOI: 10.1053/j.seminoncol.2022.07.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 07/01/2022] [Accepted: 07/01/2022] [Indexed: 11/11/2022]
Abstract
Two large randomized controlled trials have shown mortality benefit from lung cancer screening (LCS) in high-risk groups. Updated guidelines by the United State Preventative Service Task Force in 2020 will allow for inclusion of more patients who are at high risk of developing lung cancer and benefit from screening. As medical clinics and lung cancer screening programs around the country continue to work on perfecting the LCS workflow, it is important to understand some controversial issues surrounding LCS that should be addressed. In this article, we identify some of these issues, including false positive rates of low-dose CT, over-diagnosis, cost expenditure, LCS disparities in minorities, and utility of biomarkers. We hope to provide clarity, potential solutions, and future directions on how to address these controversies.
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Affiliation(s)
- Ravindra Rampariag
- Section of Pulmonary, Critical Care and Sleep Medicine, Medical Service, Veterans Administration (VA) New York Harbor Healthcare System, NY, USA
| | - Igor Chernyavskiy
- Section of Pulmonary, Critical Care and Sleep Medicine, Medical Service, Veterans Administration (VA) New York Harbor Healthcare System, NY, USA; Section of Pulmonary, Critical Care and Sleep Medicine, Medical Service, Veterans Administration (VA) Northport Healthcare System, NY, USA
| | - Mohammad Al-Ajam
- Section of Pulmonary, Critical Care and Sleep Medicine, Medical Service, Veterans Administration (VA) New York Harbor Healthcare System, NY, USA; Division of Pulmonary, Critical Care, and Sleep, Department of Medicine, SUNY Downstate Medical Center, NY, USA
| | - Jun-Chieh J Tsay
- Section of Pulmonary, Critical Care and Sleep Medicine, Medical Service, Veterans Administration (VA) New York Harbor Healthcare System, NY, USA; Division of Pulmonary, Critical Care, and Sleep, Department of Medicine, New York University Grossman School of Medicine, NY, USA.
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94
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Sex disparity of lung cancer risk in non-smokers: a multicenter population-based prospective study based on China National Lung Cancer Screening Program. Chin Med J (Engl) 2022; 135:1331-1339. [PMID: 35830209 PMCID: PMC9433079 DOI: 10.1097/cm9.0000000000002161] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
Background: Non-smokers account for a large proportion of lung cancer patients, especially in Asia, but the attention paid to them is limited compared with smokers. In non-smokers, males display a risk for lung cancer incidence distinct from the females—even after excluding the influence of smoking; but the knowledge regarding the factors causing the difference is sparse. Based on a large multicenter prospective cancer screening cohort in China, we aimed to elucidate the interpretable sex differences caused by known factors and provide clues for primary and secondary prevention. Methods: Risk factors including demographic characteristics, lifestyle factors, family history of cancer, and baseline comorbidity were obtained from 796,283 Chinese non-smoking participants by the baseline risk assessment completed in 2013 to 2018. Cox regression analysis was performed to assess the sex difference in the risk of lung cancer, and the hazard ratios (HRs) that were adjusted for different known factors were calculated and compared to determine the proportion of excess risk and to explain the existing risk factors. Results: With a median follow-up of 4.80 years, 3351 subjects who were diagnosed with lung cancer were selected in the analysis. The lung cancer risk of males was significantly higher than that of females; the HRs in all male non-smokers were 1.29 (95% confidence interval [CI]: 1.20–1.38) after adjusting for the age and 1.38 (95% CI: 1.28–1.50) after adjusting for all factors, which suggested that known factors could not explain the sex difference in the risk of lung cancer in non-smokers. Known factors were 7% (|1.29–1.38|/1.29) more harmful in women than in men. For adenocarcinoma, women showed excess risk higher than men, contrary to squamous cell carcinoma; after adjusting for all factors, 47% ([1.30–1.16]/[1.30–1]) and 4% ([7.02–6.75]/[7.02–1])) of the excess risk was explainable in adenocarcinoma and squamous cell carcinoma. The main causes of gender differences in lung cancer risk were lifestyle factors, baseline comorbidity, and family history. Conclusions: Significant gender differences in the risk of lung cancer were discovered in China non-smokers. Existing risk factors did not explain the excess lung cancer risk of all non-smoking men, and the internal causes for the excess risk still need to be explored; most known risk factors were more harmful to non-smoking women; further exploring the causes of the sex difference would help to improve the prevention and screening programs and protect the non-smoking males from lung cancers.
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95
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Shih YCT, Sabik LM, Stout NK, Halpern MT, Lipscomb J, Ramsey S, Ritzwoller DP. Health Economics Research in Cancer Screening: Research Opportunities, Challenges, and Future Directions. J Natl Cancer Inst Monogr 2022; 2022:42-50. [PMID: 35788368 PMCID: PMC9255920 DOI: 10.1093/jncimonographs/lgac008] [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: 09/30/2021] [Accepted: 03/03/2022] [Indexed: 01/26/2023] Open
Abstract
Cancer screening has long been considered a worthy public health investment. Health economics offers the theoretical foundation and research methodology to understand the demand- and supply-side factors associated with screening and evaluate screening-related policies and interventions. This article provides an overview of health economic theories and methods related to cancer screening and discusses opportunities for future research. We review 2 academic disciplines most relevant to health economics research in cancer screening: applied microeconomics and decision science. We consider 3 emerging topics: cancer screening policies in national as well as local contexts, "choosing wisely" screening practices, and targeted screening efforts for vulnerable subpopulations. We also discuss the strengths and weaknesses of available data sources and opportunities for methodological research and training. Recommendations to strengthen research infrastructure include developing novel data linkage strategies, increasing access to electronic health records, establishing curriculum and training programs, promoting multidisciplinary collaborations, and enhancing research funding opportunities.
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Affiliation(s)
- Ya-Chen Tina Shih
- Section of Cancer Economics and Policy, Department of Health Services Research, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Lindsay M Sabik
- Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA
| | - Natasha K Stout
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Michael T Halpern
- Healthcare Delivery Research Program, National Cancer Institute, Bethesda, MD, USA
| | - Joseph Lipscomb
- Department of Health Policy and Management, Rollins School of Public Health, and the Winship Cancer Institute, Emory University, Atlanta, GA, USA
| | - Scott Ramsey
- Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Institute, Seattle, WA, USA
| | - Debra P Ritzwoller
- Institute for Health Research, Kaiser Permanente Colorado, Aurora, CO, USA
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96
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Tanoue LT, Sather P, Cortopassi I, Dicks D, Curtis A, Michaud G, Bader A, Gange C, Detterbeck F, Killam J. Standardizing the Reporting of Incidental, Non-Lung Cancer (Category S) Findings Identified on Lung Cancer Screening Low-Dose CT Imaging. Chest 2022; 161:1697-1706. [DOI: 10.1016/j.chest.2021.12.662] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 12/12/2022] Open
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97
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Stone E, Leong TL. Contemporary Concise Review 2021: Pulmonary nodules from detection to intervention. Respirology 2022; 27:776-785. [PMID: 35581532 DOI: 10.1111/resp.14296] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 05/02/2022] [Indexed: 12/11/2022]
Abstract
The US Preventive Task Force (USPSTF) has updated screening criteria by expanding age range and reducing smoking history required for eligibility; the International Lung Screen Trial (ILST) data have shown that PLCOM2012 performs better for eligibility than USPSTF criteria. Screening adherence is low (4%-6% of potential eligible candidates in the United States) and depends upon multiple system and patient/candidate-related factors. Smoking cessation in lung cancer improves survival (past prospective trial data, updated meta-analysis data); smoking cessation is an essential component of lung cancer screening. Circulating biomarkers are emerging to optimize screening and early diagnosis. COVID-19 continues to affect lung cancer treatment and screening through delays and disruptions; specific operational challenges need to be met. Over 70% of suspected malignant lesions develop in the periphery of the lungs. Bronchoscopic navigational techniques have been steadily improving to allow greater accuracy with target lesion approximation and therefore diagnostic yield. Fibre-based imaging techniques provide real-time microscopic tumour visualization, with potential diagnostic benefits. With significant advances in peripheral lung cancer localization, bronchoscopically delivered ablative therapies are an emerging field in limited stage primary and oligometastatic disease. In advanced stage lung cancer, small-volume samples acquired through bronchoscopic techniques yield material of sufficient quantity and quality to support clinically relevant biomarker assessment.
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Affiliation(s)
- Emily Stone
- Department of Thoracic Medicine and Lung Transplantation, St Vincent's Hospital Sydney, Sydney, New South Wales, Australia.,School of Clinical Medicine, UNSW, Sydney, New South Wales, Australia.,School of Public Health, University of Sydney, Sydney, New South Wales, Australia
| | - Tracy L Leong
- Department of Respiratory and Sleep Medicine, Austin Health, Melbourne, Victoria, Australia.,Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Victoria, Australia
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98
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Smoking Cessation Training and Treatment: Options for Cancer Centres. Curr Oncol 2022; 29:2252-2262. [PMID: 35448157 PMCID: PMC9032722 DOI: 10.3390/curroncol29040183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/18/2022] [Accepted: 03/21/2022] [Indexed: 11/16/2022] Open
Abstract
Patients who achieve smoking cessation following a cancer diagnosis can experience an improvement in treatment response and lower morbidity and mortality compared to individuals who continue to smoke. It is therefore imperative for publicly funded cancer centres to provide appropriate training and education for healthcare providers (HCP) and treatment options to support smoking cessation for their patients. However, system-, practitioner-, and patient-level barriers exist that hamper the integration of evidence-based cessation programs within publicly funded cancer centres. The integration of evidence-based smoking cessation counselling and pharmacotherapy into cancer care facilities could have a significant effect on smoking cessation and cancer treatment outcomes. The purpose of this paper is to describe the elements of a learning health system for smoking cessation, implemented and scaled up in community settings that can be adapted for ambulatory cancer clinics. The core elements include appropriate workflows enabled by technology, thereby improving both practitioner and patient experience and effectively removing practitioner-level barriers to program implementation. Integrating the smoking cessation elements of this program from primary care to cancer centres could improve smoking cessation outcomes in patients attending cancer clinics.
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99
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Guo X, Jia D, He L, Jia X, Zhang D, Dou Y, Shen S, Ji H, Zhang S, Chen Y. Evaluation of ultralow-dose computed tomography on detection of pulmonary nodules in overweight or obese adult patients. J Appl Clin Med Phys 2022; 23:e13589. [PMID: 35293673 PMCID: PMC8992951 DOI: 10.1002/acm2.13589] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 02/28/2022] [Accepted: 03/03/2022] [Indexed: 12/02/2022] Open
Abstract
Purpose To evaluate the accuracy of pulmonary nodule (PN) detection in overweight or obese adult patients using ultralow‐dose computed tomography (ULDCT) with tin filtration at 100 kV and advanced model‐based iterative reconstruction (ADMIRE). Methods Eighty‐one patients with body mass indices of ≥25 kg/m2 were enrolled. All patients underwent low‐dose chest CT (LDCT), followed by ULDCT. Two radiologists experienced in LDCT established the standard of reference (SOR) for PNs. The number, type, size, and location of PNs were identified in the SOR. Effective dose, objective image quality (IQ), and subjective IQ based on two radiologists’ scores were compared between ULDCT and LDCT. The detection performances of radiologists based on ULDCT were calculated according to the nodule analyses. Logistic regression was used to test for independent predictors of PN detection sensitivity. Results Both the effective dose and objective IQ were lower for ULDCT than for LDCT (both p < 0.001). Both radiologists rated the subjective IQ of the overall IQ on ULDCT to be diagnostically sufficient. In total, 234 nodules (mean diameter, 3.4 ± 1.9 mm) were classified into 32 subsolid, 149 solid, and 53 calcified nodules according to the SOR. The overall sensitivity of ULDCT for nodule detection was 93.6%. Based on multivariate analyses, the nodule types (p = 0.015) and sizes (p = 0.013) were independent predictors of nodule detection. Conclusions Compared with LDCT, ULDCT with tin filtration at 100 kV and ADMIRE could significantly reduce the radiation dose in overweight or obese patients while maintaining good sensitivity for nodule detection.
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Affiliation(s)
- Xiaowan Guo
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Dezhao Jia
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Lei He
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Xudong Jia
- Department of Urology, The Second Hospital of Hebei Medical University, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Danqing Zhang
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Yana Dou
- Siemens Healthcare Ltd., Chaoyang District, Beijing, China
| | - Shanshan Shen
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Hong Ji
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Shuqian Zhang
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
| | - Yingmin Chen
- Department of Radiology, Hebei General Hospital, Xinhua District, Shijiazhuang, Hebei Province, China
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100
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Rustagi AS, Byers AL, Keyhani S. Likelihood of Lung Cancer Screening by Poor Health Status and Race and Ethnicity in US Adults, 2017 to 2020. JAMA Netw Open 2022; 5:e225318. [PMID: 35357450 PMCID: PMC8972038 DOI: 10.1001/jamanetworkopen.2022.5318] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 02/12/2022] [Indexed: 12/17/2022] Open
Abstract
Importance Lung cancer screening (LCS) via low-dose chest computed tomography can prevent mortality through surgical resection of early-stage cancers, but it is unknown whether poor health is associated with screening. Though LCS may be associated with better outcomes for non-Hispanic Black individuals, it is unknown whether racial or ethnic disparities exist in LCS use. Objective To determine whether health status is associated with LCS and whether racial or ethnic disparities are associated with LCS independently of health status. Design, Setting, and Participants This cross-sectional, population-based study of community-dwelling US adults used data from Behavioral Risk Factor Surveillance System annual surveys, 2017 to 2020. Participants were aged 55 to 79 years, with a less than 30 pack-year smoking history, and were current smokers or those who quit within 15 years. Data were analyzed from August to November 2021. Exposures Self-reported health status and race and ethnicity. Main Outcomes and Measures Self-reported LCS in the last 12 months. Results Of 14 550 individuals (7802 men [55.5%]; 7527 [55.0%] aged 65-79 years [percentages are weighted]), representing 3.68 million US residents, 17.0% (95% CI, 15.1%-18.9%) reported undergoing LCS. The prevalence of LCS was lower among non-Hispanic Black than non-Hispanic White individuals but not to a significant degree (12.0% [95% CI, 4.3%-19.7%] vs 17.5% [95% CI, 15.6%-19.5%]; P = .57). Health status was associated with LCS: 468 individuals in poor health vs 96 individuals in excellent health reported LCS (25.2% [95% CI, 20.6%-29.9%] vs 7.6% [95% CI, 5.0%-10.3%]; P < .001), and those with difficulty climbing stairs were more likely to report LCS than those without this functional limitation. Adjusting for sociodemographic factors, functional status, and comorbidities, self-rated health status remained associated with LCS (adjusted odds ratio, 1.19 per each 1-step decline in health; 95% CI, 1.03-1.38), and non-Hispanic Black individuals were 53% less likely to report LCS than non-Hispanic White individuals (adjusted odds ratio, 0.47; 95% CI, 0.24-0.90). Results were robust in sensitivity analyses in which health was alternatively quantified as number of comorbidities. Conclusions and Relevance LCS in the US is more common among those who may be less likely to benefit from screening because of poor underlying health. Furthermore, racial or ethnic disparities were evident after accounting for health status, with non-Hispanic Black individuals nearly half as likely as non-Hispanic White individuals to report LCS despite the potential for greater benefit of screening this population.
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Affiliation(s)
- Alison S. Rustagi
- Medical Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Medicine, University of California, San Francisco
| | - Amy L. Byers
- Department of Medicine, University of California, San Francisco
- Research Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco
- Weill Institute for Neurosciences, University of California, San Francisco
| | - Salomeh Keyhani
- Medical Service, San Francisco Veterans Affairs Health Care System, San Francisco, California
- Department of Medicine, University of California, San Francisco
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