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Kalva S, Ginzberg SP, Passman JE, Soegaard Ballester JM, Finn CB, Fraker DL, Kelz RR, Wachtel H. Sex differences and racial/ethnic disparities in the presentation and treatment of medullary thyroid cancer. Am J Surg 2024; 234:19-25. [PMID: 38365554 PMCID: PMC11223966 DOI: 10.1016/j.amjsurg.2024.02.009] [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: 10/15/2023] [Revised: 01/03/2024] [Accepted: 02/05/2024] [Indexed: 02/18/2024]
Abstract
BACKGROUND This study assessed for disparities in the presentation and management of medullary thyroid cancer (MTC). METHODS Patients with MTC (2010-2020) were identified from the National Cancer Database. Differences in disease presentation and likelihood of guideline-concordant surgical management (total thyroidectomy and resection of ≥1 lymph node) were assessed by sex and race/ethnicity. RESULTS Of 6154 patients, 68.2% underwent guideline-concordant surgery. Tumors >4 cm were more likely in men (vs. women: OR 2.47, p < 0.001) and Hispanic patients (vs. White patients: OR 1.52, p = 0.001). Non-White patients were more likely to have distant metastases (Black: OR 1.63, p = 0.002; Hispanic: OR 1.44, p = 0.038) and experienced longer time to surgery (Black: HR 0.66, p < 0.001; Hispanic: HR 0.71, p < 0.001). Black patients were less likely to undergo guideline-concordant surgery (OR 0.70, p = 0.022). CONCLUSIONS Male and non-White patients with MTC more frequently present with advanced disease, and Black patients are less likely to undergo guideline-concordant surgery.
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Affiliation(s)
- Saiesh Kalva
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Sara P Ginzberg
- Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA; Penn Center for Cancer Care Innovation, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, 3641 Locust Walk #210, Philadelphia, PA 19104, USA.
| | - Jesse E Passman
- Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, 3641 Locust Walk #210, Philadelphia, PA 19104, USA
| | - Jacqueline M Soegaard Ballester
- Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA
| | - Caitlin B Finn
- Department of Surgery, Weill Cornell Medicine, 525 E. 68th Street, New York, NY, 10065, USA
| | - Douglas L Fraker
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA; Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA
| | - Rachel R Kelz
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA; Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA; Leonard Davis Institute of Health Economics, University of Pennsylvania, 3641 Locust Walk #210, Philadelphia, PA 19104, USA
| | - Heather Wachtel
- Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA; Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce Street, 4 Silverstein Building, Philadelphia, PA, 19104, USA
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Meyer ML, Hirsch FR, Bunn PA, Ujhazy P, Fredrickson D, Berg CD, Carbone DP, Halmos B, Singh H, Borghaei H, Ferris A, Langer C, Dacic S, Mok TS, Peters S, Johnson BE. Calls to action on lung cancer management and research. Oncologist 2024:oyae169. [PMID: 39002167 DOI: 10.1093/oncolo/oyae169] [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: 03/18/2024] [Accepted: 05/24/2024] [Indexed: 07/15/2024] Open
Abstract
Lung cancer, the leading cause of cancer-related deaths globally, remains a pressing health issue despite significant medical advances. The New York Lung Cancer Foundation brought together experts from academia, the pharmaceutical and biotech industries as well as organizational leaders and patient advocates, to thoroughly examine the current state of lung cancer diagnosis, treatment, and research. The goal was to identify areas where our understanding is incomplete and to develop collaborative public health and scientific strategies to generate better patient outcomes, as highlighted in our "Calls to Action." The consortium prioritized 8 different calls to action. These include (1) develop strategies to cure more patients with early-stage lung cancer, (2) investigate carcinogenesis leading to lung cancers in patients without a history of smoking, (3) harness precision medicine for disease interception and prevention, (4) implement solutions to deliver prevention measures and effective therapies to individuals in under-resourced countries, (5) facilitate collaborations with industry to collect and share data and samples, (6) create and maintain open access to big data repositories, (7) develop new immunotherapeutic agents for lung cancer treatment and prevention, and (8) invest in research in both the academic and community settings. These calls to action provide guidance to representatives from academia, the pharmaceutical and biotech industries, organizational and regulatory leaders, and patient advocates to guide ongoing and planned initiatives.
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Affiliation(s)
- May-Lucie Meyer
- Hematology and Oncology Department, Tisch Cancer Institute at Mount Sinai, Icahn School of Medicine and Thoracic Oncology Center, New York, NY, United States
| | - Fred R Hirsch
- Hematology and Oncology Department, Tisch Cancer Institute at Mount Sinai, Icahn School of Medicine and Thoracic Oncology Center, New York, NY, United States
| | - Paul A Bunn
- Division of Medical Oncology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Peter Ujhazy
- Translational Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Rockville, MD, United States
| | | | | | - David P Carbone
- Division of Medical Oncology, The Ohio State University-James Comprehensive Cancer Center, Columbus, OH, United States
| | - Balazs Halmos
- Department of Oncology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Harpreet Singh
- US Food and Drug Administration (FDA), Washington, DC, United States
| | | | | | - Corey Langer
- Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanja Dacic
- Department of Pathology, Yale School of Medicine, New Haven, CT, United States
| | - Tony S Mok
- State Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong, People's Republic of China
| | - Solange Peters
- Department of Oncology, University Hospital CHUV, Lausanne, Switzerland
| | - Bruce E Johnson
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States
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Yan L, Su H, Liu J, Wen X, Luo H, Yin Y, Guo X. Rapid detection of lung cancer based on serum Raman spectroscopy and a support vector machine: a case-control study. BMC Cancer 2024; 24:791. [PMID: 38956551 PMCID: PMC11220989 DOI: 10.1186/s12885-024-12578-y] [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: 05/25/2023] [Accepted: 06/28/2024] [Indexed: 07/04/2024] Open
Abstract
BACKGROUND Early screening and detection of lung cancer is essential for the diagnosis and prognosis of the disease. In this paper, we investigated the feasibility of serum Raman spectroscopy for rapid lung cancer screening. METHODS Raman spectra were collected from 45 patients with lung cancer, 45 with benign lung lesions, and 45 healthy volunteers. And then the support vector machine (SVM) algorithm was applied to build a diagnostic model for lung cancer. Furthermore, 15 independent individuals were sampled for external validation, including 5 lung cancer patients, 5 benign lung lesion patients, and 5 healthy controls. RESULTS The diagnostic sensitivity, specificity, and accuracy were 91.67%, 92.22%, 90.56% (lung cancer vs. healthy control), 92.22%,95.56%,93.33% (benign lung lesion vs. healthy) and 80.00%, 83.33%, 80.83% (lung cancer vs. benign lung lesion), repectively. In the independent validation cohort, our model showed that all the samples were classified correctly. CONCLUSION Therefore, this study demonstrates that the serum Raman spectroscopy analysis technique combined with the SVM algorithm has great potential for the noninvasive detection of lung cancer.
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Affiliation(s)
- Linfang Yan
- Guang'an People's Hospital, Guang'an, Sichuan Province, China
| | - Huiting Su
- Guang'an People's Hospital, Guang'an, Sichuan Province, China.
| | - Jiafei Liu
- Guang'an People's Hospital, Guang'an, Sichuan Province, China
| | - Xiaozheng Wen
- Guang'an People's Hospital, Guang'an, Sichuan Province, China
| | - Huaichao Luo
- Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Chengdu, China
| | - Yu Yin
- Sichuan Institute for Brain Science and Brain-Inspired Intelligence, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaoqiang Guo
- Guang'an People's Hospital, Guang'an, Sichuan Province, China
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Caverly TJ, Wiener RS, Kumbier K, Lowery J, Fagerlin A. Prediction-Augmented Shared Decision-Making and Lung Cancer Screening Uptake. JAMA Netw Open 2024; 7:e2419624. [PMID: 38949809 DOI: 10.1001/jamanetworkopen.2024.19624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/02/2024] Open
Abstract
Importance Addressing poor uptake of low-dose computed tomography lung cancer screening (LCS) is critical, especially for those having the most to gain-high-benefit persons with high lung cancer risk and life expectancy more than 10 years. Objective To assess the association between LCS uptake and implementing a prediction-augmented shared decision-making (SDM) tool, which enables clinicians to identify persons predicted to be at high benefit and encourage LCS more strongly for these persons. Design, Setting, and Participants Quality improvement interrupted time series study at 6 Veterans Affairs sites that used a standard set of clinical reminders to prompt primary care clinicians and screening coordinators to engage in SDM for LCS-eligible persons. Participants were persons without a history of LCS who met LCS eligibility criteria at the time (aged 55-80 years, smoked ≥30 pack-years, and current smoking or quit <15 years ago) and were not documented to be an inappropriate candidate for LCS by a clinician during October 2017 through September 2019. Data were analyzed from September to November 2023. Exposure Decision support tool augmented by a prediction model that helps clinicians personalize SDM for LCS, tailoring the strength of screening encouragement according to predicted benefit. Main outcome and measure LCS uptake. Results In a cohort of 9904 individuals, the median (IQR) age was 64 (57-69) years; 9277 (94%) were male, 1537 (16%) were Black, 8159 (82%) were White, 5153 (52%) were predicted to be at intermediate (preference-sensitive) benefit and 4751 (48%) at high benefit, and 1084 (11%) received screening during the study period. Following implementation of the tool, higher rates of LCS uptake were observed overall along with an increase in benefit-based LCS uptake (higher screening uptake among persons anticipated to be at high benefit compared with those at intermediate benefit; primary analysis). Mean (SD) predicted probability of getting screened for a high-benefit person was 24.8% (15.5%) vs 15.8% (11.8%) for a person at intermediate benefit (mean absolute difference 9.0 percentage points; 95% CI, 1.6%-16.5%). Conclusions and Relevance Implementing a robust approach to personalized LCS, which integrates SDM, and a decision support tool augmented by a prediction model, are associated with improved uptake of LCS and may be particularly important for those most likely to benefit. These findings are timely given the ongoing poor rates of LCS uptake.
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Affiliation(s)
- Tanner J Caverly
- Center for Clinical Management Research, Department of Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor
| | - Renda S Wiener
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
- Center for Healthcare Organization and Implementation Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts
| | - Kyle Kumbier
- Center for Clinical Management Research, Department of Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Julie Lowery
- Center for Clinical Management Research, Department of Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, Michigan
| | - Angela Fagerlin
- University of Utah School of Medicine, Salt Lake City
- Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, Department of Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah
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Potter AL, Xu NN, Senthil P, Srinivasan D, Lee H, Gazelle GS, Chelala L, Zheng W, Fintelmann FJ, Sequist LV, Donington J, Palmer JR, Yang CFJ. Pack-Year Smoking History: An Inadequate and Biased Measure to Determine Lung Cancer Screening Eligibility. J Clin Oncol 2024; 42:2026-2037. [PMID: 38537159 PMCID: PMC11191064 DOI: 10.1200/jco.23.01780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/21/2023] [Accepted: 02/02/2024] [Indexed: 05/03/2024] Open
Abstract
PURPOSE Pack-year smoking history is an imperfect and biased measure of cumulative tobacco exposure. The use of pack-year smoking history to determine lung cancer screening eligibility in the current US Preventive Services Task Force (USPSTF) guideline may unintentionally exclude many high-risk individuals, especially those from racial and ethnic minority groups. It is unclear whether using a smoking duration cutoff instead of a smoking pack-year cutoff would improve the selection of individuals for screening. METHODS We analyzed 49,703 individuals with a smoking history from the Southern Community Cohort Study (SCCS) and 22,126 individuals with a smoking history from the Black Women's Health Study (BWHS) to assess eligibility for screening under the USPSTF guideline versus a proposed guideline that replaces the ≥20-pack-year criterion with a ≥20-year smoking duration criterion. RESULTS Under the USPSTF guideline, only 57.6% of Black patients with lung cancer in the SCCS would have qualified for screening, whereas a significantly higher percentage of White patients with lung cancer (74.0%) would have qualified (P < .001). Under the proposed guideline, the percentage of Black and White patients with lung cancer who would have qualified for screening increased to 85.3% and 82.0%, respectively, eradicating the disparity in screening eligibility between the groups. In the BWHS, using a 20-year smoking duration cutoff instead of a 20-pack-year cutoff increased the percentage of Black women with lung cancer who would have qualified for screening from 42.5% to 63.8%. CONCLUSION Use of a 20-year smoking duration cutoff instead of a 20-pack-year cutoff greatly increases the proportion of patients with lung cancer who would qualify for screening and eliminates the racial disparity in screening eligibility between Black versus White individuals; smoking duration has the added benefit of being easier to calculate and being a more precise assessment of smoking exposure compared with pack-year smoking history.
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Affiliation(s)
- Alexandra L. Potter
- Division of Thoracic Surgery, Department of Surgery, Massachusetts General Hospital, Boston, MA
| | - Nuo N. Xu
- Slone Epidemiology Center at Boston University, Boston, MA
| | - Priyanka Senthil
- Division of Thoracic Surgery, Department of Surgery, Massachusetts General Hospital, Boston, MA
| | - Deepti Srinivasan
- Division of Thoracic Surgery, Department of Surgery, Massachusetts General Hospital, Boston, MA
| | - Hang Lee
- Biostatistics Center, Massachusetts General Hospital, Boston, MA
| | - G. Scott Gazelle
- Department of Radiology, Massachusetts General Hospital, Boston, MA
- Institute for Technology Assessment, Massachusetts General Hospital, Boston, MA
| | - Lydia Chelala
- Department of Radiology, University of Chicago Pritzker School of Medicine, Chicago, IL
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Nashville, TN
- Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | | | - Lecia V. Sequist
- Mass General Cancer Center, Massachusetts General Hospital, Boston, MA
| | - Jessica Donington
- Section of Thoracic Surgery, Department of Surgery, University of Chicago Hospital, Chicago, IL
| | | | - Chi-Fu Jeffrey Yang
- Division of Thoracic Surgery, Department of Surgery, Massachusetts General Hospital, Boston, MA
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Kukhareva PV, Li H, Caverly TJ, Fagerlin A, Del Fiol G, Hess R, Zhang Y, Butler JM, Schlechter C, Flynn MC, Reddy C, Choi J, Balbin C, Warner IA, Warner PB, Nanjo C, Kawamoto, K. Lung Cancer Screening Before and After a Multifaceted Electronic Health Record Intervention: A Nonrandomized Controlled Trial. JAMA Netw Open 2024; 7:e2415383. [PMID: 38848065 PMCID: PMC11161845 DOI: 10.1001/jamanetworkopen.2024.15383] [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: 11/16/2023] [Accepted: 03/24/2024] [Indexed: 06/10/2024] Open
Abstract
Importance Lung cancer is the deadliest cancer in the US. Early-stage lung cancer detection with lung cancer screening (LCS) through low-dose computed tomography (LDCT) improves outcomes. Objective To assess the association of a multifaceted clinical decision support intervention with rates of identification and completion of recommended LCS-related services. Design, Setting, and Participants This nonrandomized controlled trial used an interrupted time series design, including 3 study periods from August 24, 2019, to April 27, 2022: baseline (12 months), period 1 (11 months), and period 2 (9 months). Outcome changes were reported as shifts in the outcome level at the beginning of each period and changes in monthly trend (ie, slope). The study was conducted at primary care and pulmonary clinics at a health care system headquartered in Salt Lake City, Utah, among patients aged 55 to 80 years who had smoked 30 pack-years or more and were current smokers or had quit smoking in the past 15 years. Data were analyzed from September 2023 through February 2024. Interventions Interventions in period 1 included clinician-facing preventive care reminders, an electronic health record-integrated shared decision-making tool, and narrative LCS guidance provided in the LDCT ordering screen. Interventions in period 2 included the same clinician-facing interventions and patient-facing reminders for LCS discussion and LCS. Main Outcome and Measure The primary outcome was LCS care gap closure, defined as the identification and completion of recommended care services. LCS care gap closure could be achieved through LDCT completion, other chest CT completion, or LCS shared decision-making. Results The study included 1865 patients (median [IQR] age, 64 [60-70] years; 759 female [40.7%]). The clinician-facing intervention (period 1) was not associated with changes in level but was associated with an increase in slope of 2.6 percentage points (95% CI, 2.4-2.7 percentage points) per month in care gap closure through any means and 1.6 percentage points (95% CI, 1.4-1.8 percentage points) per month in closure through LDCT. In period 2, introduction of patient-facing reminders was associated with an immediate increase in care gap closure (2.3 percentage points; 95% CI, 1.0-3.6 percentage points) and closure through LDCT (2.4 percentage points; 95% CI, 0.9-3.9 percentage points) but was not associated with an increase in slope. The overall care gap closure rate was 175 of 1104 patients (15.9%) at the end of the baseline period vs 588 of 1255 patients (46.9%) at the end of period 2. Conclusions and Relevance In this study, a multifaceted intervention was associated with an improvement in LCS care gap closure. Trial Registration ClinicalTrials.gov Identifier: NCT04498052.
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Affiliation(s)
| | - Haojia Li
- Study Design and Biostatistics Center, University of Utah, Salt Lake City
| | - Tanner J. Caverly
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, Michigan
- Department of Learning Health Sciences, University of Michigan, Ann Arbor
- Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Angela Fagerlin
- Department of Population Health Sciences, University of Utah, Salt Lake City
- Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences Center for Innovation, Salt Lake City, Utah
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Rachel Hess
- Department of Population Health Sciences, University of Utah, Salt Lake City
- Department of Internal Medicine, University of Utah, Salt Lake City
| | - Yue Zhang
- Study Design and Biostatistics Center, University of Utah, Salt Lake City
| | - Jorie M. Butler
- Department of Biomedical Informatics, University of Utah, Salt Lake City
- Department of Internal Medicine, University of Utah, Salt Lake City
- Geriatrics Research and Education Center, George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah
| | - Chelsey Schlechter
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | - Michael C. Flynn
- Department of Internal Medicine, University of Utah, Salt Lake City
- Department of Pediatrics, University of Utah, Salt Lake City
- Community Physicians Group, University of Utah Health, Salt Lake City
| | - Chakravarthy Reddy
- Study Design and Biostatistics Center, University of Utah, Salt Lake City
| | - Joshua Choi
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Christian Balbin
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Isaac A. Warner
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Phillip B. Warner
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Claude Nanjo
- Department of Biomedical Informatics, University of Utah, Salt Lake City
| | - Kensaku Kawamoto,
- Department of Biomedical Informatics, University of Utah, Salt Lake City
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Jhala K, Byrne SC, Hammer MM. Interpreting Lung Cancer Screening CTs: Practical Approach to Lung Cancer Screening and Application of Lung-RADS. Clin Chest Med 2024; 45:279-293. [PMID: 38816088 DOI: 10.1016/j.ccm.2023.08.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024]
Abstract
Lung cancer screening via low-dose computed tomography (CT) reduces mortality from lung cancer, and eligibility criteria have recently been expanded to include patients aged 50 to 80 with at least 20 pack-years of smoking history. Lung cancer screening CTs should be interepreted with use of Lung Imaging Reporting and Data System (Lung-RADS), a reporting guideline system that accounts for nodule size, density, and growth. The revised version of Lung-RADS includes several important changes, such as expansion of the definition of juxtapleural nodules, discussion of atypical pulmonary cysts, and stepped management for suspicious nodules. By using Lung-RADS, radiologists and clinicians can adopt a uniform approach to nodules detected during CT lung cancer screening and reduce false positives.
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Affiliation(s)
- Khushboo Jhala
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Suzanne C Byrne
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA
| | - Mark M Hammer
- Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02215, USA.
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8
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Fernandes C, Campbell-Scherer D, Lofters A, Grunfeld E, Aubrey-Bassler K, Cheung H, Latko K, Tink W, Lewanczuk R, Shea-Budgell M, Heisey R, Wong T, Yang H, Walji S, Wilson M, Holmes E, Lang-Robertson K, DeLonghi C, Manca DP. Harmonization of clinical practice guidelines for primary prevention and screening: actionable recommendations and resources for primary care. BMC PRIMARY CARE 2024; 25:153. [PMID: 38711031 PMCID: PMC11071261 DOI: 10.1186/s12875-024-02388-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 04/12/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND Clinical practice guidelines (CPGs) synthesize high-quality information to support evidence-based clinical practice. In primary care, numerous CPGs must be integrated to address the needs of patients with multiple risks and conditions. The BETTER program aims to improve prevention and screening for cancer and chronic disease in primary care by synthesizing CPGs into integrated, actionable recommendations. We describe the process used to harmonize high-quality cancer and chronic disease prevention and screening (CCDPS) CPGs to update the BETTER program. METHODS A review of CPG databases, repositories, and grey literature was conducted to identify international and Canadian (national and provincial) CPGs for CCDPS in adults 40-69 years of age across 19 topic areas: cancers, cardiovascular disease, chronic obstructive pulmonary disease, diabetes, hepatitis C, obesity, osteoporosis, depression, and associated risk factors (i.e., diet, physical activity, alcohol, cannabis, drug, tobacco, and vaping/e-cigarette use). CPGs published in English between 2016 and 2021, applicable to adults, and containing CCDPS recommendations were included. Guideline quality was assessed using the Appraisal of Guidelines for Research and Evaluation (AGREE) II tool and a three-step process involving patients, health policy, content experts, primary care providers, and researchers was used to identify and synthesize recommendations. RESULTS We identified 51 international and Canadian CPGs and 22 guidelines developed by provincial organizations that provided relevant CCDPS recommendations. Clinical recommendations were extracted and reviewed for inclusion using the following criteria: 1) pertinence to primary prevention and screening, 2) relevance to adults ages 40-69, and 3) applicability to diverse primary care settings. Recommendations were synthesized and integrated into the BETTER toolkit alongside resources to support shared decision-making and care paths for the BETTER program. CONCLUSIONS Comprehensive care requires the ability to address a person's overall health. An approach to identify high-quality clinical guidance to comprehensively address CCDPS is described. The process used to synthesize and harmonize implementable clinical recommendations may be useful to others wanting to integrate evidence across broad content areas to provide comprehensive care. The BETTER toolkit provides resources that clearly and succinctly present a breadth of clinical evidence that providers can use to assist with implementing CCDPS guidance in primary care.
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Affiliation(s)
- Carolina Fernandes
- Department of Family Medicine, University of Alberta, Edmonton, AB, Canada.
| | - Denise Campbell-Scherer
- Department of Family Medicine, University of Alberta, Edmonton, AB, Canada
- Office of Lifelong Learning and the Physician Learning Program, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
| | - Aisha Lofters
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
- Peter Gilgan Centre for Women's Cancers, Women's College Hospital, Toronto, ON, Canada
| | - Eva Grunfeld
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Kris Aubrey-Bassler
- Discipline of Family Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
- Newfoundland and Labrador Centre for Health Information, St. John's, NL, Canada
| | - Heidi Cheung
- Department of Family Medicine, University of Alberta, Edmonton, AB, Canada
| | - Katherine Latko
- College of Physicians and Surgeons of Ontario, Toronto, ON, Canada
| | - Wendy Tink
- Department of Family Medicine, University of Calgary, Calgary, AB, Canada
| | - Richard Lewanczuk
- Alberta Health Services, Alberta, AB, Canada
- Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | | | - Ruth Heisey
- Peter Gilgan Centre for Women's Cancers, Women's College Hospital, Toronto, ON, Canada
- Family and Community Medicine, Women's College Hospital, Toronto, ON, Canada
| | - Tracy Wong
- Strategic Clinical Networks, Alberta Health Services, Calgary, AB, Canada
| | | | - Sakina Walji
- Department of Family Medicine, Mount Sinai Hospital, Sinai Health System, Toronto, ON, Canada
| | - Margo Wilson
- Discipline of Emergency Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | | | | | | | - Donna Patricia Manca
- Department of Family Medicine, University of Alberta, Edmonton, AB, Canada
- Office of Lifelong Learning and the Physician Learning Program, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
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9
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Till BM, Grenda T, Tidwell T, Wickes B, Shusted C, Ruane B, Okusanya O, Evans NR, Barta JA. Brief Report: Nonmalignant Surgical Resection Among Individuals with Screening-Detected Versus Incidental Lung Nodules. Clin Lung Cancer 2024; 25:e129-e132.e4. [PMID: 38185612 DOI: 10.1016/j.cllc.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 12/01/2023] [Accepted: 12/13/2023] [Indexed: 01/09/2024]
Affiliation(s)
- Brian M Till
- Division of Thoracic Surgery, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Tyler Grenda
- Division of Thoracic Surgery, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Taylor Tidwell
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Baylor Wickes
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Christine Shusted
- Division of Pulmonary and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA
| | - Brooke Ruane
- Division of Pulmonary and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA
| | - Olugbenga Okusanya
- Division of Thoracic Surgery, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Nathaniel R Evans
- Division of Thoracic Surgery, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA; Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA
| | - Julie A Barta
- Sidney Kimmel Medical College at Thomas Jefferson University, Philadelphia, PA; Division of Pulmonary and Critical Care Medicine, Jane and Leonard Korman Respiratory Institute, Thomas Jefferson University, Philadelphia, PA.
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Wang Z, Xue F, Sui X, Han W, Song W, Jiang J. Personalised follow-up and management schema for patients with screen-detected pulmonary nodules: A dynamic modelling study. Pulmonology 2024:S2531-0437(24)00040-0. [PMID: 38614860 DOI: 10.1016/j.pulmoe.2024.02.010] [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: 07/23/2023] [Revised: 02/28/2024] [Accepted: 02/29/2024] [Indexed: 04/15/2024] Open
Abstract
BACKGROUND Selecting the time target for follow-up testing in lung cancer screening is challenging. We aim to devise dynamic, personalized lung cancer screening schema for patients with pulmonary nodules detected through low-dose computed tomography. METHODS We developed and validated dynamic models using data of pulmonary nodule patients (aged 55-74 years) from the National Lung Screening Trial. We predicted patient-specific risk profiles at baseline (R0) and updated the risk evaluation results in repeated screening rounds (R1 and R2). We used risk cutoffs to optimize time-dependent sensitivity at an early decision point (3 months) and time-dependent specificity at a late decision point (1 year). RESULTS In validation, area under receiver operating characteristic curve for predicting 12-month lung cancer onset was 0.867 (95 % confidence interval: 0.827-0.894) and 0.807 (0.765-0.948) at R0 and R1-R2, respectively. The personalized schema, compared with National Comprehensive Cancer Network (NCCN) guideline and Lung-RADS, yielded lower rates of delayed diagnosis (1.7% vs. 1.7% vs. 6.9 %) and over-testing (4.9% vs. 5.6% vs. 5.6 %) at R0, and lower rates of delayed diagnosis (0.0% vs. 18.2% vs. 18.2 %) and over-testing (2.6% vs. 8.3% vs. 7.3 %) at R2. Earlier test recommendation among cancer patients was more frequent using the personalized schema (vs. NCCN: 29.8% vs. 20.9 %, p = 0.0065; vs. Lung-RADS: 33.2% vs. 22.8 %, p = 0.0025), especially for women, patients aged ≥65 years, and part-solid or non-solid nodules. CONCLUSIONS The personalized schema is easy-to-implement and more accurate compared with rule-based protocols. The results highlight value of personalized approaches in realizing efficient nodule management.
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Affiliation(s)
- Z Wang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China; Peking University People's Hospital, Peking University Hepatology Institute, Beijing Key Laboratory of Hepatitis C and Immunotherapy for Liver Diseases. No. 11 Xizhimen South Street, Beijing, China
| | - F Xue
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China
| | - X Sui
- Department of Radiology, Peking Union Medical College Hospital. No.1 Shuaifuyuan Street, Dongcheng District, Beijing, China
| | - W Han
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China
| | - W Song
- Department of Radiology, Peking Union Medical College Hospital. No.1 Shuaifuyuan Street, Dongcheng District, Beijing, China
| | - J Jiang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College. No. 5 Dongdansantiao Street, Dongcheng District, Beijing, China.
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Poghosyan H, Richman I, Sarkar S, Presley CJ. Lung cancer screening use among screening-eligible adults with disabilities. J Am Geriatr Soc 2024; 72:1155-1165. [PMID: 38357789 PMCID: PMC11018473 DOI: 10.1111/jgs.18795] [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: 05/31/2023] [Revised: 01/10/2024] [Accepted: 01/15/2024] [Indexed: 02/16/2024]
Abstract
BACKGROUND Lung cancer screening (LCS) use among adults with disabilities has not been well characterized. We estimated the prevalence of LCS use by disability types and counts and investigated the association between disability counts and LCS utilization among LCS-eligible adults. METHODS We used cross-sectional data from the 2019 Behavioral Risk Factor Surveillance System, Lung Cancer Screening Module. Based on the 2013 US Preventive Services Task Force criteria for LCS, the sample included 4407 LCS-eligible adults, aged 55-79 years, with current or former (quit smoking in the past 15 years) tobacco use history of at least 30 pack-years. Disability types included limitations in hearing, vision, cognition, mobility, self-care, and independent living. We also categorized respondents by number of disabilities (no disability, 1 disability, 2 disabilities, 3+ disabilities). We utilized descriptive statistics and multivariable logistic regression analyses to determine the association between disability counts and the receipt of LCS (yes/no) in the past 12 months. RESULTS In 2019, 16.4% of LCS-eligible adults were screened for lung cancer. Overall, 49.6% of participants had no disability, and 14.5% had >3 disabilities. Mobility was the most prevalent disability type (35.4%), followed by cognitive impairment (18.2%) and hearing (16.6%). LCS was more prevalent in adults with disability in self-care versus no disability in self-care (24.0% vs. 15.5%, p = 0.01), disability in independent living versus no disability in independent living (22.2% vs. 15.4%, p = 0.02), and cognitive impairment disability versus no cognitive impairment (22.1% vs. 15.3%, p = 0.03). The prevalence rates of LCS among groups of LCS-eligible adults with different disability counts were not significant (p = 0.17). CONCLUSIONS Despite the lack of clinical guidelines on LCS among individuals with disabilities, some individuals with disabilities are being screened for lung cancer. Future research should address this knowledge gap to determine clinical benefit versus harm of LCS among those with disabilities.
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Affiliation(s)
- Hermine Poghosyan
- Yale School of Nursing, New Haven, Connecticut, USA
- Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Ilana Richman
- Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) Center, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | | | - Carolyn J. Presley
- Division of Medical Oncology, Department of Internal Medicine, The Ohio State University, Columbus, Ohio, USA
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12
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Cartmel B, Fucito LM, Bold KW, Neveu S, Li F, Rojewski AM, Gueorguieva R, O'Malley SS, Herbst RS, Toll BA. Effect of a Personalized Tobacco Treatment Intervention on Smoking Abstinence in Individuals Eligible for Lung Cancer Screening. J Thorac Oncol 2024; 19:643-649. [PMID: 37977486 PMCID: PMC10999350 DOI: 10.1016/j.jtho.2023.11.012] [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: 02/10/2023] [Revised: 11/07/2023] [Accepted: 11/13/2023] [Indexed: 11/19/2023]
Abstract
INTRODUCTION To determine whether personalized gain-framed messaging and biomarker feedback related to tobacco cessation or reduction decrease smoking behavior in patients undergoing or eligible for lung cancer screening. METHODS Between 2016 and 2020, 188 patients were enrolled in a two-phase, sequential, randomized controlled trial. Phase 1 evaluated whether standard of care (SC) (five in-person counseling sessions and 8 weeks of nicotine patch) plus gain-framed messaging (GFM) versus SC would increase 8-week biochemically verified smoking cessation rates. In 143 participants randomized in phase 2, we tested whether feedback on smoking-related biomarkers would reduce 6-month self-reported number of cigarettes smoked per day compared with a no feedback control. Chi-square test and mixed effects repeated measures analyses were used to evaluate group differences. RESULTS Participants were 62.5 ± 5.6 (mean ± SD) years of age, had a 50.3 ± 21 pack-year smoking history, and were smoking 16.9 ± 9.9 cigarettes per day. At 8 weeks, there was no difference in quit rates between those randomized to SC plus GFM (n = 15 of 93, 16.1%) and those randomized to SC (n = 16 of 95, 16.8%), with p equals to 0.90. At the 6-month post-randomization follow-up, number of cigarettes smoked per day was similar in the feedback (least-squares mean = 7.5, 95% confidence interval: 6.0-9.1) and no feedback arms (7.7, 95% confidence interval: 6.2-9.3), with p equals to 0.87. CONCLUSIONS Gain-framed messaging and health feedback did not significantly improve quit rates relative to comprehensive standard of care. Nevertheless, the overall program achieved clinically meaningful smoking quit rates in this older high pack-year cohort, highlighting the importance of intensive tobacco treatment for patients undergoing lung cancer screening. CLINICAL TRIAL REGISTERED WITH CLINICALTRIALS.GOV: NCT02658032.
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Affiliation(s)
- Brenda Cartmel
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut; Yale Cancer Center, New Haven, Connecticut.
| | - Lisa M Fucito
- Yale Cancer Center, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Smilow Cancer Hospital at Yale-New Haven, New Haven, Connecticut
| | - Krysten W Bold
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Susan Neveu
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Fangyong Li
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - Alana M Rojewski
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina
| | - Ralitza Gueorguieva
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut
| | - Stephanie S O'Malley
- Yale Cancer Center, New Haven, Connecticut; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Roy S Herbst
- Yale Cancer Center, New Haven, Connecticut; Department of Internal Medicine, Section of Medical Oncology, Yale University School of Medicine, New Haven, Connecticut
| | - Benjamin A Toll
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Department of Public Health Sciences, Medical University of South Carolina, Charleston, South Carolina; MUSC Hollings Cancer Center, Medical University of South Carolina, Charleston, South Carolina
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13
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Slatore CG, Hooker ER, Shull S, Golden SE, Melzer AC. Association of patient and health care organization factors with incidental nodule guidelines adherence: A multi-system observational study. Lung Cancer 2024; 190:107526. [PMID: 38452601 PMCID: PMC10999337 DOI: 10.1016/j.lungcan.2024.107526] [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: 08/09/2023] [Revised: 02/01/2024] [Accepted: 02/26/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Health care organizations are increasingly developing systems to ensure patients with pulmonary nodules receive guideline-adherent care. Our goal was to determine patient and organization factors that are associated with radiologist adherence as well as clinician and patient concordance to 2005 Fleischner Society guidelines for incidental pulmonary nodule follow-up. MATERIALS Trained researchers abstracted data from the electronic health record from two Veterans Affairs health care systems for patients with incidental pulmonary nodules as identified by interpreting radiologists from 2008 to 2016. METHODS We classified radiology reports and patient follow-up into two categories. Radiologist-Fleischner Adherence was the agreement between the radiologist's recommendation in the computed tomography report and the 2005 Fleischner Society guidelines. Clinician/Patient-Fleischner Concordance was agreement between patient follow-up and the guidelines. We calculated multivariable-adjusted predicted probabilities for factors associated with Radiologist-Fleischner Adherence and Clinician/Patient-Fleischner Concordance. RESULTS Among 3150 patients, 69% of radiologist recommendations were adherent to 2005 Fleischner guidelines, 4% were more aggressive, and 27% recommended less aggressive follow-up. Overall, only 48% of patients underwent follow-up concordant with 2005 Fleischner Society guidelines, 37% had less aggressive follow-up, and 15% had more aggressive follow-up. Radiologist-Fleischner Adherence was associated with Clinician/Patient-Fleischner Concordance with evidence for effect modification by health care system. CONCLUSION Clinicians and patients seem to follow radiologists' recommendations but often do not obtain concordant follow-up, likely due to downstream differential processes in each health care system. Health care organizations need to develop comprehensive and rigorous tools to ensure high levels of appropriate follow-up for patients with pulmonary nodules.
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Affiliation(s)
- Christopher G Slatore
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, USA; Section of Pulmonary & Critical Care Medicine, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, USA; Division of Pulmonary & Critical Care Medicine, Department of Medicine, and Department of Radiation Medicine, Knight Cancer Institute, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239, USA.
| | - Elizabeth R Hooker
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, USA
| | - Sarah Shull
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, USA
| | - Sara E Golden
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, 3710 SW US Veterans Hospital Rd, Portland, OR 97239, USA
| | - Anne C Melzer
- Section of Pulmonary & Critical Care Medicine, VA Minneapolis Health Care System, 1 Veterans Dr, Minneapolis, MN 55417, USA
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Pereira LFF, dos Santos RS, Bonomi DO, Franceschini J, Santoro IL, Miotto A, de Sousa TLF, Chate RC, Hochhegger B, Gomes A, Schneider A, de Araújo CA, Escuissato DL, Prado GF, Costa-Silva L, Zamboni MM, Ghefter MC, Corrêa PCRP, Torres PPTES, Mussi RK, Muglia VF, de Godoy I, Bernardo WM. Lung cancer screening in Brazil: recommendations from the Brazilian Society of Thoracic Surgery, Brazilian Thoracic Association, and Brazilian College of Radiology and Diagnostic Imaging. J Bras Pneumol 2024; 50:e20230233. [PMID: 38536982 PMCID: PMC11095927 DOI: 10.36416/1806-3756/e20230233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 12/13/2023] [Indexed: 05/18/2024] Open
Abstract
Although lung cancer (LC) is one of the most common and lethal tumors, only 15% of patients are diagnosed at an early stage. Smoking is still responsible for more than 85% of cases. Lung cancer screening (LCS) with low-dose CT (LDCT) reduces LC-related mortality by 20%, and that reduction reaches 38% when LCS by LDCT is combined with smoking cessation. In the last decade, a number of countries have adopted population-based LCS as a public health recommendation. Albeit still incipient, discussion on this topic in Brazil is becoming increasingly broad and necessary. With the aim of increasing knowledge and stimulating debate on LCS, the Brazilian Society of Thoracic Surgery, the Brazilian Thoracic Association, and the Brazilian College of Radiology and Diagnostic Imaging convened a panel of experts to prepare recommendations for LCS in Brazil. The recommendations presented here were based on a narrative review of the literature, with an emphasis on large population-based studies, systematic reviews, and the recommendations of international guidelines, and were developed after extensive discussion by the panel of experts. The following topics were reviewed: reasons for screening; general considerations about smoking; epidemiology of LC; eligibility criteria; incidental findings; granulomatous lesions; probabilistic models; minimum requirements for LDCT; volumetric acquisition; risks of screening; minimum structure and role of the multidisciplinary team; practice according to the Lung CT Screening Reporting and Data System; costs versus benefits of screening; and future perspectives for LCS.
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Affiliation(s)
- Luiz Fernando Ferreira Pereira
- . Serviço de Pneumologia, Hospital das Clínicas, Faculdade de Medicina, Universidade Federal de Minas Gerais - UFMG - Belo Horizonte (MG) Brasil
| | - Ricardo Sales dos Santos
- . Serviço de Cirurgia Torácica, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
| | - Daniel Oliveira Bonomi
- . Departamento de Cirurgia Torácica, Faculdade de Medicina, Universidade Federal de Minas Gerais - UFMG - Belo Horizonte (MG) Brasil
| | - Juliana Franceschini
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
- . Fundação ProAR, Salvador (BA) Brasil
| | - Ilka Lopes Santoro
- . Disciplina de Pneumologia, Departamento de Medicina, Escola Paulista de Medicina, Universidade Federal de São Paulo - UNIFESP - São Paulo (SP) Brasil
| | - André Miotto
- . Disciplina de Cirurgia Torácica, Departamento de Cirurgia, Escola Paulista de Medicina, Universidade Federal de São Paulo - UNIFESP - São Paulo (SP) Brasil
| | - Thiago Lins Fagundes de Sousa
- . Serviço de Pneumologia, Hospital Universitário Alcides Carneiro, Universidade Federal de Campina Grande - UFCG - Campina Grande (PB) Brasil
| | - Rodrigo Caruso Chate
- . Serviço de Radiologia, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
| | - Bruno Hochhegger
- . Department of Radiology, University of Florida, Gainesville (FL) USA
| | - Artur Gomes
- . Serviço de Cirurgia Torácica, Santa Casa de Misericórdia de Maceió, Maceió (AL) Brasil
| | - Airton Schneider
- . Serviço de Cirurgia Torácica, Hospital São Lucas, Escola de Medicina, Pontifícia Universidade Católica do Rio Grande do Sul - PUCRS - Porto Alegre (RS) Brasil
| | - César Augusto de Araújo
- . Programa ProPulmão, SENAI CIMATEC e SDS Healthline, Salvador (BA) Brasil
- . Departamento de Radiologia, Faculdade de Medicina da Bahia - UFBA - Salvador (BA) Brasil
| | - Dante Luiz Escuissato
- . Departamento de Clínica Médica, Universidade Federal Do Paraná - UFPR - Curitiba (PR) Brasil
| | | | - Luciana Costa-Silva
- . Serviço de Diagnóstico por Imagem, Instituto Hermes Pardini, Belo Horizonte (MG) Brasil
| | - Mauro Musa Zamboni
- . Instituto Nacional de Câncer José Alencar Gomes da Silva, Rio de Janeiro (RJ) Brasil
- . Centro Universitário Arthur Sá Earp Neto/Faculdade de Medicina de Petrópolis -UNIFASE - Petrópolis (RJ) Brasil
| | - Mario Claudio Ghefter
- . Serviço de Cirurgia Torácica, Hospital Israelita Albert Einstein, São Paulo (SP) Brasil
- . Serviço de Cirurgia Torácica, Hospital do Servidor Público Estadual, São Paulo (SP) Brasil
| | | | | | - Ricardo Kalaf Mussi
- . Serviço de Cirurgia Torácica, Hospital das Clínicas, Universidade Estadual de Campinas - UNICAMP - Campinas (SP) Brasil
| | - Valdair Francisco Muglia
- . Departamento de Imagens Médicas, Oncologia e Hematologia, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo - USP - Ribeirão Preto (SP) Brasil
| | - Irma de Godoy
- . Disciplina de Pneumologia, Departamento de Clínica Médica, Faculdade de Medicina de Botucatu, Universidade Estadual Paulista, Botucatu (SP) Brasil
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Lin X, Lei F, Lin J, Li Y, Chen Q, Arbing R, Chen WT, Huang F. Promoting Lung Cancer Screen Decision-Making and Early Detection Behaviors: A Systematic Review and Meta-analysis. Cancer Nurs 2024:00002820-990000000-00227. [PMID: 38498799 DOI: 10.1097/ncc.0000000000001334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/20/2024]
Abstract
BACKGROUND Promoting lung cancer screening (LCS) is complex. Previous studies have overlooked that LCS behaviors are stage based and thus did not identify the characteristics of LCS interventions at different screening stages. OBJECTIVE The aims of this study were to explore the characteristics and efficacy of interventions in promoting LCS decision making and behaviors and to evaluate these interventions. METHODS We conducted a study search from the inception of each bibliographic database to April 8, 2023. The precaution adoption process model was used to synthesize and classify the evidence. The RE-AIM framework was used to evaluate the effectiveness of LCS programs. Heterogeneity tests and meta-analysis were performed using RevMan 5.4 software. RESULTS We included 31 studies that covered 4 LCS topics: knowledge of lung cancer, knowledge of LCS, value clarification exercises, and LCS supportive resources. Patient decision aids outperformed educational materials in improving knowledge and decision outcomes with a significant reduction in decision conflict (standardized mean difference, 0.81; 95% confidence interval, -1.15 to -0.47; P < .001). Completion rates of LCS ranged from 3.6% to 98.8%. Interventions that included screening resources outperformed interventions that used patient decision aids alone in improving LCS completion. The proportions of reported RE-AIM indicators were highest for reach (69.59%), followed by adoption (43.87%), effectiveness (36.13%), implementation (33.33%), and maintenance (9.68%). CONCLUSION Evidence from 31 studies identified intervention characteristics and effectiveness of LCS interventions based on different stages of decision making. IMPLICATIONS FOR PRACTICE It is crucial to develop targeted and systematic interventions based on the characteristics of each stage of LCS to maximize intervention effectiveness and reduce the burden of lung cancer.
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Affiliation(s)
- Xiujing Lin
- Author Affiliations: School of Nursing, Fujian Medical University (Mss X Lin, J Lin, Li, and Q Chen, and Dr Huang), Fuzhou, China; School of Nursing, University of Minnesota (Dr Lei), Twin Cities, Minneapolis; and School of Nursing, University of California Los Angeles (Dr W-T Chen and Ms Arbing)
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16
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Hu N, Wang M, Yang M, Chen X, Wang J, Xie C, Zhang B, Wang Z, Chen X. Bone mineral density in lower thoracic vertebra for osteoporosis diagnosis in older adults during CT lung cancer screening. BMC Geriatr 2024; 24:237. [PMID: 38448801 PMCID: PMC10918915 DOI: 10.1186/s12877-024-04737-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 01/22/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Quantitative computed tomography (QCT)-based lumbar bone mineral density (LBMD) has been used to diagnose osteoporosis. This study explored the value of lower thoracic BMD (TBMD) in diagnosing osteoporosis in older adults during CT lung cancer screening. METHODS This study included 751 subjects who underwent QCT scans with both LBMD and TBMD. 141 of them was selected for a validation. Osteoporosis was diagnosed based on LBMD using the ACR criteria (gold standard). TBMD thresholds were obtained using receiver operating characteristic curve. TBMD was also translated into LBMD (TTBMD) and osteoporosis was defined based on TTBMD using ACR criteria. The performance of TBMD and TTBMD in identifying osteoporosis was determined by Kappa test. The associations between TBMD- and TTBMD-based osteoporosis and fracture were tested in 227 subjects with followed up status of spine fracture. RESULTS The performance of TBMD in identifying osteoporosis was low (kappa = 0.66) if using the ACR criteria. Two thresholds of TBMD for identifying osteopenia (128 mg/cm3) and osteoporosis (91 mg/cm3) were obtained with areas under the curve of 0.97 and 0.99, respectively. The performance of the identification of osteoporosis/osteopenia using the two thresholds or TTBMD both had good agreement with the gold standard (kappa = 0.78, 0.86). Similar results were observed in validation population. Osteoporosis identified using the thresholds (adjusted hazard ratio (HR) = 18.72, 95% confidence interval (CI): 5.13-68.36) or TTBMD (adjusted HR = 10.28, 95% CI: 4.22-25.08) were also associated with fractures. CONCLUSION Calculating the threshold of TBMD or normalizing TBMD to LBMD are both useful in identifying osteoporosis in older adults during CT lung cancer screening.
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Affiliation(s)
- Nandong Hu
- Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong road, 210029, Nanjing, China
| | - Miaomiao Wang
- Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong road, 210029, Nanjing, China
- Department of Radiology, the Second Affiliated Hospital of Soochow University, 1055 Sanxiang road, 215004, Suzhou, China
| | - Meng Yang
- Bengbu Medical College, 2600 Donghai road, 233030, Bengbu, China
| | - Xin Chen
- Department of Radiology, Shanghai Longhua Hospital, 200032, Shanghai, China
| | - Jiangchuan Wang
- Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong road, 210029, Nanjing, China
| | - Chao Xie
- Department of Orthopaedics, University of Rochester School of Medicine, 14642, Rochester, NY, USA
| | - Bin Zhang
- Department of Thoracic surgery, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Zhongqiu Wang
- Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong road, 210029, Nanjing, China
| | - Xiao Chen
- Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, 155 Hanzhong road, 210029, Nanjing, China.
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Udelsman BV, Detterbeck F, Tanoue L, Mase V, Boffa D, Blasberg J, Dhanasopon A, Ely S, Mazzarelli LJ, Bader A, Woodard G. Impact of the COVID-19 Pandemic on Lung Cancer Screening Processes in a Northeast Tertiary Health Care Network. J Comput Assist Tomogr 2024; 48:222-225. [PMID: 37832536 DOI: 10.1097/rct.0000000000001549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
ABSTRACT The coronavirus disease 2019 (COVID-19) pandemic disrupted health care systems, including implementation of lung cancer screening programs. The impact and recovery from this disruption on screening processes is not well appreciated. Herein, the radiology database of a Northeast tertiary health care network was reviewed before and during the pandemic (2013-2022). In the 3 months before the pandemic, an average of 77.3 lung cancer screening with computed tomography scans (LCS-CT) were performed per month. The average dropped to 23.3 between April and June of 2020, whereas COVID-19 hospitalizations peaked at 1604. By July, average hospitalizations dropped to 50, and LCS-CTs rose to >110 per month for the remaining year. LCS-CTs did not decline during COVID-19 surges in December of 2021 and 2022. The LCS-CT performance grew by 4.5% in 2020, 69.6% in 2021, and 27.0% in 2022, exceeding projected growth by 722 examinations. This resiliency indicates a potentially smaller impact of COVID-19 on lung cancer diagnoses than initially feared.
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Affiliation(s)
- Brooks V Udelsman
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Frank Detterbeck
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Lynn Tanoue
- Department of Internal Medicine, Yale University School of Medicine, New Haven, CT
| | - Vincent Mase
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Daniel Boffa
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Justin Blasberg
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Andrew Dhanasopon
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | - Sora Ely
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
| | | | - Anna Bader
- Department of Radiology, Yale University School of Medicine, New Haven, CT
| | - Gavitt Woodard
- From the Division of Thoracic Surgery, Department of Surgery, Yale University School of Medicine, New Haven, CT
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Ren Y, Zhang Z, She Y, He Y, Li D, Shi Y, He C, Yang Y, Zhang W, Chen C. A Highly Sensitive and Specific Non-Invasive Test through Genome-Wide 5-Hydroxymethylation Mapping for Early Detection of Lung Cancer. SMALL METHODS 2024; 8:e2300747. [PMID: 37990399 DOI: 10.1002/smtd.202300747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 10/04/2023] [Indexed: 11/23/2023]
Abstract
Low-dose computed tomography screening can increase the detection for non-small-cell lung cancer (NSCLC). To improve the diagnostic accuracy of early-stage NSCLC detection, ultrasensitive methods are used to detect cell-free DNA (cfDNA) 5-hydroxymethylcytosine (5hmC) in plasma. Genome-wide 5hmC is profiled in 1990 cfDNA samples collected from patients with non-small cell lung cancer (NSCLC, n = 727), healthy controls (HEA, n = 1,092), as well as patients with small cell lung cancer (SCLC, n = 41), followed by sample randomization, differential analysis, feature selection, and modeling using a machine learning approach. Differentially modified features reflecting tissue origin. A weighted diagnostic model comprised of 105 features is developed to compute a detection score for each individual, which showed an area under the curve (AUC) range of 86.4%-93.1% in the internal and external validation sets for distinguishing lung cancer from HEA controls, significantly outperforming serum biomarkers (p < 0.001). The 5hmC-based model detected high-risk pulmonary nodules (AUC: 82%)and lung cancer of different subtypes with high accuracy as well. A highly sensitive and specific blood-based test is developed for detecting lung cancer. The 5hmC biomarkers in cfDNA offer a promising blood-based test for lung cancer.
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Affiliation(s)
- Yijiu Ren
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Zhou Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Yunlang She
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Yayi He
- Department of Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Dongdong Li
- Shanghai Epican Genetech, Co., Ltd., Shanghai, China
| | - Yixiang Shi
- Bionova (Shanghai) Medical Technology Co., Ltd, Shanghai, China
| | - Chuan He
- Department of Chemistry, The University of Chicago, Chicago, IL, 60637, USA
- The Howard Hughes Medical Institute, The University of Chicago, Chicago, IL, 60637, USA
| | - Yang Yang
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
| | - Wei Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Chang Chen
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, 200433, China
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19
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Núñez ER, Bolton RE, Boudreau JH, Sliwinski SK, Herbst AN, Kearney LE, Caverly TJ, Wiener RS. "It Can't Hurt!": Why Many Patients With Limited Life Expectancy Decide to Accept Lung Cancer Screening. Ann Fam Med 2024; 22:95-102. [PMID: 38527813 PMCID: PMC11237214 DOI: 10.1370/afm.3081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 11/01/2023] [Accepted: 11/13/2023] [Indexed: 03/27/2024] Open
Abstract
PURPOSE Lung cancer screening (LCS) has less benefit and greater potential for iatrogenic harm among people with multiple comorbidities and limited life expectancy. Yet, such individuals are more likely to undergo screening than healthier LCS-eligible people. We sought to understand how patients with marginal LCS benefit conceptualize their health and make decisions regarding LCS. METHODS We interviewed 40 people with multimorbidity and limited life expectancy, as determined by high Care Assessment Need scores, which predict 1-year risk of hospitalization or death. Patients were recruited from 6 Veterans Health Administration facilities after discussing LCS with their clinician. We conducted a thematic analysis using constant comparison to explore factors that influence LCS decision making. RESULTS Patients commonly held positive beliefs about screening and perceived LCS to be noninvasive. When posed with hypothetical scenarios of limited benefit, patients emphasized the nonlongevity benefits of LCS (eg, peace of mind, planning for the future) and generally did not consider their health status or life expectancy when making decisions regarding LCS. Most patients were unaware of possible additional evaluations or treatment of screen-detected findings, but when probed further, many expressed concerns about the potential need for multiple evaluations, referrals, or invasive procedures. CONCLUSIONS Patients in this study with multimorbidity and limited life expectancy were unaware of their greater risk of potential harm when accepting LCS. Given patient trust in clinician recommendations, it is important that clinicians engage patients with marginal LCS benefit in shared decision making, ensuring that their values of desiring more information about their health are weighed against potential harms from further evaluations.
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Affiliation(s)
- Eduardo R Núñez
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
- Department of Healthcare Delivery and Population Sciences, University of Massachusetts Chan Medical School-Baystate, Springfield, Massachusetts
| | - Rendelle E Bolton
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
- The Heller School for Social Policy and Management, Brandeis University, Waltham, Massachusetts
| | - Jacqueline H Boudreau
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
| | - Samantha K Sliwinski
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
| | - Abigail N Herbst
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
| | - Lauren E Kearney
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
| | - Tanner J Caverly
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan
- University of Michigan School of Medicine, Ann Arbor, Michigan
| | - Renda Soylemez Wiener
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, Massachusetts and VA Bedford Healthcare System, Bedford, Massachusetts
- The Pulmonary Center, Boston University School of Medicine, Boston, Massachusetts
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
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20
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Park H, Hwang EJ, Goo JM. Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality. Invest Radiol 2024; 59:278-286. [PMID: 37428617 DOI: 10.1097/rli.0000000000001003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/12/2023]
Abstract
OBJECTIVES The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality. MATERIALS AND METHODS This retrospective study investigated LDCTs obtained from asymptomatic individuals aged 60 years or older during health checkups between February 2009 and December 2016. These LDCTs were reconstructed using a 1- or 1.25-mm slice thickness alongside high-frequency kernels. A deep learning algorithm, capable of generating CT images that resemble standard-dose and low-frequency kernel images, was applied to these LDCTs. To quantify emphysema, the lung volume percentage with an attenuation value less than or equal to -950 Hounsfield units (LAA-950) was gauged before and after kernel adaptation. Low-dose chest CTs with LAA-950 exceeding 6% were deemed emphysema-positive according to the Fleischner Society statement. Survival data were sourced from the National Registry Database at the close of 2021. The risk of nonaccidental death, excluding causes such as injury or poisoning, was explored according to the emphysema quantification results using multivariate Cox proportional hazards models. RESULTS The study comprised 5178 participants (mean age ± SD, 66 ± 3 years; 3110 males). The median LAA-950 (18.2% vs 2.6%) and the proportion of LDCTs with LAA-950 exceeding 6% (96.3% vs 39.3%) saw a significant decline after kernel adaptation. There was no association between emphysema quantification before kernel adaptation and the risk of nonaccidental death. Nevertheless, after kernel adaptation, higher LAA-950 (hazards ratio for 1% increase, 1.01; P = 0.045) and LAA-950 exceeding 6% (hazards ratio, 1.36; P = 0.008) emerged as independent predictors of nonaccidental death, upon adjusting for age, sex, and smoking status. CONCLUSIONS The application of deep learning for kernel adaptation proves instrumental in quantifying pulmonary emphysema on LDCTs, establishing itself as a potential predictive tool for long-term nonaccidental mortality in asymptomatic individuals.
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Affiliation(s)
- Hyungin Park
- From the Department of Radiology, Seoul National University Hospital, Seoul, South Korea (H.P., E.J.H., J.M.G.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.G.)
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21
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Kale MS, Morgan O, Wisnivesky J, Schnur J, Diefenbach MA. Challenges Addressing Lung Cancer Screening for Patients With Multimorbidity in Primary Care: A Qualitative Study. Ann Fam Med 2024; 22:103-112. [PMID: 38527820 PMCID: PMC11237206 DOI: 10.1370/afm.3080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 11/27/2023] [Accepted: 11/28/2023] [Indexed: 03/27/2024] Open
Abstract
PURPOSE Many individuals who are eligible for lung cancer screening have comorbid conditions complicating their shared decision-making conversations with physicians. The goal of our study was to better understand how primary care physicians (PCPs) factor comorbidities into their evaluation of the risks and benefits of lung cancer screening and into their shared decision-making conversations with patients. METHODS We conducted semistructured interviews by videoconference with 15 PCPs to assess the extent of shared decision-making practices and explore their understanding of the intersection of comorbidities and lung cancer screening, and how that understanding informed their clinical approach to this population. RESULTS We identified 3 themes. The first theme was whether to discuss or not to discuss lung cancer screening. PCPs described taking additional steps for individuals with complex comorbidities to decide whether to initiate this discussion and used subjective clinical judgment to decide whether the conversation would be productive and beneficial. PCPs made mental assessments that factored in the patient's health, life expectancy, quality of life, and access to support systems. The second theme was that shared decision making is not a simple discussion. When PCPs did initiate discussions about lung cancer screening, although some believed they could provide objective information, others struggled with personal biases. The third theme was that ultimately, the decision to be screened was up to the patient. Patients had the final say, even if their decision was discordant with the PCP's advice. CONCLUSIONS Shared decision-making conversations about lung cancer screening differed substantially from the standard for patients with complex comorbidities. Future research should include efforts to characterize the risks and benefits of LCS in patients with comorbidities to inform guidelines and clinical application.
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Affiliation(s)
- Minal S Kale
- Division of General Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Orly Morgan
- Division of Medical Education, University of Miami Miller School of Medicine, Miami, Florida
| | - Juan Wisnivesky
- Division of Medical Education, University of Miami Miller School of Medicine, Miami, Florida
| | - Julie Schnur
- Department of Population Health Science and Policy, Center for Behavioral Oncology, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Michael A Diefenbach
- Institute of Health System Science, Feinstein Institutes for Medical Research, Manhasset, New York
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22
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Sano H, Okoshi EN, Tachibana Y, Tanaka T, Lami K, Uegami W, Ohta Y, Brcic L, Bychkov A, Fukuoka J. Machine-Learning-Based Classification Model to Address Diagnostic Challenges in Transbronchial Lung Biopsy. Cancers (Basel) 2024; 16:731. [PMID: 38398122 PMCID: PMC10886691 DOI: 10.3390/cancers16040731] [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: 01/05/2024] [Revised: 01/29/2024] [Accepted: 02/07/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND When obtaining specimens from pulmonary nodules in TBLB, distinguishing between benign samples and mis-sampling from a tumor presents a challenge. Our objective is to develop a machine-learning-based classifier for TBLB specimens. METHODS Three pathologists assessed six pathological findings, including interface bronchitis/bronchiolitis (IB/B), plasma cell infiltration (PLC), eosinophil infiltration (Eo), lymphoid aggregation (Ly), fibroelastosis (FE), and organizing pneumonia (OP), as potential histologic markers to distinguish between benign and malignant conditions. A total of 251 TBLB cases with defined benign and malignant outcomes based on clinical follow-up were collected and a gradient-boosted decision-tree-based machine learning model (XGBoost) was trained and tested on randomly split training and test sets. RESULTS Five pathological changes showed independent, mild-to-moderate associations (AUC ranging from 0.58 to 0.75) with benign conditions, with IB/B being the strongest predictor. On the other hand, FE emerged to be the sole indicator of malignant conditions with a mild association (AUC = 0.66). Our model was trained on 200 cases and tested on 51 cases, achieving an AUC of 0.78 for the binary classification of benign vs. malignant on the test set. CONCLUSION The machine-learning model developed has the potential to distinguish between benign and malignant conditions in TBLB samples excluding the presence or absence of tumor cells, thereby improving diagnostic accuracy and reducing the burden of repeated sampling procedures for patients.
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Affiliation(s)
- Hisao Sano
- Department of Pathology Informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8588, Nagasaki, Japan; (H.S.); (E.N.O.); (Y.T.); (K.L.)
- Department of Diagnostic Pathology, Izumi City General Hospital, Izumi 594-0073, Osaka, Japan; (T.T.); (Y.O.)
- Department of Pathology, Kameda Medical Center, Kamogawa 296-8602, Chiba, Japan; (W.U.); (A.B.)
| | - Ethan N. Okoshi
- Department of Pathology Informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8588, Nagasaki, Japan; (H.S.); (E.N.O.); (Y.T.); (K.L.)
| | - Yuri Tachibana
- Department of Pathology Informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8588, Nagasaki, Japan; (H.S.); (E.N.O.); (Y.T.); (K.L.)
- Department of Pathology, Kameda Medical Center, Kamogawa 296-8602, Chiba, Japan; (W.U.); (A.B.)
| | - Tomonori Tanaka
- Department of Diagnostic Pathology, Izumi City General Hospital, Izumi 594-0073, Osaka, Japan; (T.T.); (Y.O.)
- Department of Pathology, Kobe University Graduate School of Medicine, Kobe 650-0017, Hyogo, Japan
| | - Kris Lami
- Department of Pathology Informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8588, Nagasaki, Japan; (H.S.); (E.N.O.); (Y.T.); (K.L.)
| | - Wataru Uegami
- Department of Pathology, Kameda Medical Center, Kamogawa 296-8602, Chiba, Japan; (W.U.); (A.B.)
| | - Yoshio Ohta
- Department of Diagnostic Pathology, Izumi City General Hospital, Izumi 594-0073, Osaka, Japan; (T.T.); (Y.O.)
| | - Luka Brcic
- Diagnostic and Research Institute of Pathology, Medical University of Graz, 8010 Graz, Austria;
| | - Andrey Bychkov
- Department of Pathology, Kameda Medical Center, Kamogawa 296-8602, Chiba, Japan; (W.U.); (A.B.)
| | - Junya Fukuoka
- Department of Pathology Informatics, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki 852-8588, Nagasaki, Japan; (H.S.); (E.N.O.); (Y.T.); (K.L.)
- Department of Pathology, Kameda Medical Center, Kamogawa 296-8602, Chiba, Japan; (W.U.); (A.B.)
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23
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Núñez ER, Zhang S, Glickman ME, Qian SX, Boudreau JH, Lindenauer PK, Slatore CG, Miller DR, Caverly TJ, Wiener RS. What Goes into Patient Selection for Lung Cancer Screening? Factors Associated with Clinician Judgments of Suitability for Screening. Am J Respir Crit Care Med 2024; 209:197-205. [PMID: 37819144 PMCID: PMC10806423 DOI: 10.1164/rccm.202301-0155oc] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 10/11/2023] [Indexed: 10/13/2023] Open
Abstract
Rationale: Achieving the net benefit of lung cancer screening (LCS) depends on optimizing patient selection. Objective: To identify factors associated with clinician assessments that a patient was unlikely to benefit from LCS ("LCS-inappropriate") because of comorbidities or limited life expectancy. Methods: Retrospective analysis of patients assessed for LCS at 30 Veterans Health Administration facilities from January 1, 2015 to February 1, 2021. We conducted hierarchical mixed-effects logistic regression analyses to determine factors associated with clinicians' designations of LCS inappropriateness (primary outcome), accounting for 3-year predicted probability (i.e., competing risk) of non-lung cancer death. Measurements and Main Results: Among 38,487 LCS-eligible patients, 1,671 (4.3%) were deemed LCS-inappropriate by clinicians, whereas 4,383 (11.4%) had an estimated 3-year competing risk of non-lung cancer death greater than 20%. Patients with higher competing risks of non-lung cancer death were more likely to be deemed LCS-inappropriate (odds ratio [OR], 2.66; 95% confidence interval [CI], 2.32-3.05). Older patients (ages 75-80; OR, 1.45; 95% CI, 1.18-1.78) and those with interstitial lung disease (OR, 1.98; 95% CI, 1.51-2.59) were more likely to be deemed LCS-inappropriate than would be explained by competing risk of non-lung cancer death, whereas patients currently smoking (OR, 0.65; 95% CI, 0.58-0.73) were less likely to be deemed LCS-inappropriate, suggesting that clinicians over- or underweighted these factors. The probability of being deemed LCS-inappropriate varied from 0.4% to 74%, depending on the clinician making the assessment (median OR, 3.07; 95% CI, 2.89-3.25). Conclusion: Concerningly, the likelihood that a patient is deemed LCS-inappropriate is more strongly associated with the clinician making the assessment than with patient characteristics. Patient selection may be optimized by providing decision support to help clinicians assess net LCS benefit.
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Affiliation(s)
- Eduardo R. Núñez
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- The Pulmonary Center, School of Medicine, Boston University, Boston, Massachusetts
- Department of Healthcare Delivery and Population Sciences, Chan Medical School-Baystate, University of Massachusetts, Springfield, Massachusetts
| | - Sanqian Zhang
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- Department of Statistics, Harvard University, Cambridge, Massachusetts
| | - Mark E. Glickman
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- Department of Statistics, Harvard University, Cambridge, Massachusetts
| | - Shirley X. Qian
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
| | - Jacqueline H. Boudreau
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
| | - Peter K. Lindenauer
- Department of Healthcare Delivery and Population Sciences, Chan Medical School-Baystate, University of Massachusetts, Springfield, Massachusetts
| | - Christopher G. Slatore
- Center to Improve Veteran Involvement in Care, VA Portland Health Care System, Portland Oregon
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
- Division of Pulmonary and Critical Care Medicine, Oregon Health and Science University, Portland, Oregon
| | - Donald R. Miller
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- Zuckerberg College of Health Sciences, University of Massachusetts, Lowell, Massachusetts
| | - Tanner J. Caverly
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
- VA Ann Arbor Healthcare System, Ann Arbor, Michigan; and
- School of Medicine, University of Michigan, Ann Arbor, Michigan
| | - Renda Soylemez Wiener
- Center for Healthcare Organization and Implementation Research, VA Boston and Bedford Healthcare Systems, Boston, Massachusetts
- VA Bedford Healthcare System, Bedford, Massachusetts
- The Pulmonary Center, School of Medicine, Boston University, Boston, Massachusetts
- National Center for Lung Cancer Screening, Veterans Health Administration, Washington, DC
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24
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Zhao Z, Gu S, Yang Y, Wu W, Du L, Wang G, Dong H. A cost-effectiveness analysis of lung cancer screening with low-dose computed tomography and a polygenic risk score. BMC Cancer 2024; 24:73. [PMID: 38218803 PMCID: PMC10787978 DOI: 10.1186/s12885-023-11800-7] [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: 10/06/2023] [Accepted: 12/26/2023] [Indexed: 01/15/2024] Open
Abstract
INTRODUCTION Several studies have proved that Polygenic Risk Score (PRS) is a potential candidate for realizing precision screening. The effectiveness of low-dose computed tomography (LDCT) screening for lung cancer has been proved to reduce lung cancer specific and overall mortality, but the cost-effectiveness of diverse screening strategies remained unclear. METHODS The comparative cost-effectiveness analysis used a Markov state-transition model to assess the potential effect and costs of the screening strategies incorporating PRS or not. A hypothetical cohort of 300,000 heavy smokers entered the study at age 50-74 years and were followed up until death or age 79 years. The model was run with a cycle length of 1 year. All the transition probabilities were validated and the performance value of PRS was extracted from published literature. A societal perspective was adopted and cost parameters were derived from databases of local medical insurance bureau. Sensitivity analyses and scenario analyses were conducted. RESULTS The strategy incorporating PRS was estimated to obtain an ICER of CNY 156,691.93 to CNY 221,741.84 per QALY gained compared with non-screening with the initial start age range across 50-74 years. The strategy that screened using LDCT alone from 70-74 years annually could obtain an ICER of CNY 80,880.85 per QALY gained, which was the most cost-effective strategy. The introduction of PRS as an extra eligible criteria was associated with making strategies cost-saving but also lose the capability of gaining more LYs compared with LDCT screening alone. CONCLUSION The PRS-based conjunctive screening strategy for lung cancer screening in China was not cost-effective using the willingness-to-pay threshold of 1 time Gross Domestic Product (GDP) per capita, and the optimal screening strategy for lung cancer still remains to be LDCT screening for now. Further optimization of the screening modality can be useful to consider adoption of PRS and prospective evaluation remains a research priority.
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Affiliation(s)
- Zixuan Zhao
- Department of Public Administration, School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China
| | - Shuyan Gu
- Center for Health Policy and Management Studies, School of Government, Nanjing University, Nanjing, China
| | - Yi Yang
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Weijia Wu
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingbin Du
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of the University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Gaoling Wang
- Department of Public Administration, School of Health Economics and Management, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Hengjin Dong
- Department of Science and Education of the Fourth Affiliated Hospital, and Center for Health Policy Studies, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
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Liu J, Yang X, Li Y, Xu H, He C, Zhou P, Qing H. Predicting the Invasiveness of Pulmonary Adenocarcinomas in Pure Ground-Glass Nodules Using the Nodule Diameter: A Systematic Review, Meta-Analysis, and Validation in an Independent Cohort. Diagnostics (Basel) 2024; 14:147. [PMID: 38248024 PMCID: PMC10814052 DOI: 10.3390/diagnostics14020147] [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: 12/09/2023] [Revised: 12/30/2023] [Accepted: 01/05/2024] [Indexed: 01/23/2024] Open
Abstract
The nodule diameter was commonly used to predict the invasiveness of pulmonary adenocarcinomas in pure ground-glass nodules (pGGNs). However, the diagnostic performance and optimal cut-off values were inconsistent. We conducted a meta-analysis to evaluate the diagnostic performance of the nodule diameter for predicting the invasiveness of pulmonary adenocarcinomas in pGGNs and validated the cut-off value of the diameter in an independent cohort. Relevant studies were searched through PubMed, MEDLINE, Embase, and the Cochrane Library, from inception until December 2022. The inclusion criteria comprised studies that evaluated the diagnostic accuracy of the nodule diameter to differentiate invasive adenocarcinomas (IAs) from non-invasive adenocarcinomas (non-IAs) in pGGNs. A bivariate mixed-effects regression model was used to obtain the diagnostic performance. Meta-regression analysis was performed to explore the heterogeneity. An independent sample of 220 pGGNs (82 IAs and 128 non-IAs) was enrolled as the validation cohort to evaluate the performance of the cut-off values. This meta-analysis finally included 16 studies and 2564 pGGNs (761 IAs and 1803 non-IAs). The pooled area under the curve, the sensitivity, and the specificity were 0.85 (95% confidence interval (CI), 0.82-0.88), 0.82 (95% CI, 0.78-0.86), and 0.73 (95% CI, 0.67-0.78). The diagnostic performance was affected by the measure of the diameter, the reconstruction matrix, and patient selection bias. Using the prespecified cut-off value of 10.4 mm for the mean diameter and 13.2 mm for the maximal diameter, the mean diameter showed higher sensitivity than the maximal diameter in the validation cohort (0.85 vs. 0.72, p < 0.01), while there was no significant difference in specificity (0.83 vs. 0.86, p = 0.13). The nodule diameter had adequate diagnostic performance in differentiating IAs from non-IAs in pGGNs and could be replicated in a validation cohort. The mean diameter with a cut-off value of 10.4 mm was recommended.
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Affiliation(s)
| | | | | | | | | | - Peng Zhou
- Department of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China; (J.L.); (X.Y.); (Y.L.); (H.X.); (C.H.)
| | - Haomiao Qing
- Department of Radiology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu 610041, China; (J.L.); (X.Y.); (Y.L.); (H.X.); (C.H.)
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26
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Wolf AMD, Oeffinger KC, Shih TYC, Walter LC, Church TR, Fontham ETH, Elkin EB, Etzioni RD, Guerra CE, Perkins RB, Kondo KK, Kratzer TB, Manassaram-Baptiste D, Dahut WL, Smith RA. Screening for lung cancer: 2023 guideline update from the American Cancer Society. CA Cancer J Clin 2024; 74:50-81. [PMID: 37909877 DOI: 10.3322/caac.21811] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 09/14/2023] [Indexed: 11/03/2023] Open
Abstract
Lung cancer is the leading cause of mortality and person-years of life lost from cancer among US men and women. Early detection has been shown to be associated with reduced lung cancer mortality. Our objective was to update the American Cancer Society (ACS) 2013 lung cancer screening (LCS) guideline for adults at high risk for lung cancer. The guideline is intended to provide guidance for screening to health care providers and their patients who are at high risk for lung cancer due to a history of smoking. The ACS Guideline Development Group (GDG) utilized a systematic review of the LCS literature commissioned for the US Preventive Services Task Force 2021 LCS recommendation update; a second systematic review of lung cancer risk associated with years since quitting smoking (YSQ); literature published since 2021; two Cancer Intervention and Surveillance Modeling Network-validated lung cancer models to assess the benefits and harms of screening; an epidemiologic and modeling analysis examining the effect of YSQ and aging on lung cancer risk; and an updated analysis of benefit-to-radiation-risk ratios from LCS and follow-up examinations. The GDG also examined disease burden data from the National Cancer Institute's Surveillance, Epidemiology, and End Results program. Formulation of recommendations was based on the quality of the evidence and judgment (incorporating values and preferences) about the balance of benefits and harms. The GDG judged that the overall evidence was moderate and sufficient to support a strong recommendation for screening individuals who meet the eligibility criteria. LCS in men and women aged 50-80 years is associated with a reduction in lung cancer deaths across a range of study designs, and inferential evidence supports LCS for men and women older than 80 years who are in good health. The ACS recommends annual LCS with low-dose computed tomography for asymptomatic individuals aged 50-80 years who currently smoke or formerly smoked and have a ≥20 pack-year smoking history (strong recommendation, moderate quality of evidence). Before the decision is made to initiate LCS, individuals should engage in a shared decision-making discussion with a qualified health professional. For individuals who formerly smoked, the number of YSQ is not an eligibility criterion to begin or to stop screening. Individuals who currently smoke should receive counseling to quit and be connected to cessation resources. Individuals with comorbid conditions that substantially limit life expectancy should not be screened. These recommendations should be considered by health care providers and adults at high risk for lung cancer in discussions about LCS. If fully implemented, these recommendations have a high likelihood of significantly reducing death and suffering from lung cancer in the United States.
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Affiliation(s)
- Andrew M D Wolf
- University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Kevin C Oeffinger
- Department of Medicine, Duke University School of Medicine and Duke Cancer Institute Center for Onco-Primary Care, Durham, North Carolina, USA
| | - Tina Ya-Chen Shih
- David Geffen School of Medicine and Jonsson Comprehensive Cancer Center, University of California Los Angeles, Los Angeles, California, USA
| | - Louise C Walter
- Department of Medicine, University of California San Francisco and San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Timothy R Church
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Elizabeth T H Fontham
- Health Sciences Center, School of Public Health, Louisiana State University, New Orleans, Louisiana, USA
| | - Elena B Elkin
- Department of Health Policy and Management, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Ruth D Etzioni
- Fred Hutchinson Cancer Research Center, University of Washington, Seattle, Washington, USA
| | - Carmen E Guerra
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rebecca B Perkins
- Obstetrics and Gynecology, Boston University Chobanian and Avedisian School of Medicine, Boston, Massachusetts, USA
| | - Karli K Kondo
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia, USA
| | - Tyler B Kratzer
- Cancer Surveillance and Health Equity Science, American Cancer Society, Atlanta, Georgia, USA
| | | | | | - Robert A Smith
- Early Cancer Detection Science, American Cancer Society, Atlanta, Georgia, USA
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Landy R, Cheung LC, Young CD, Chaturvedi AK, Katki HA. Absolute lung cancer risk increases among individuals with >15 quit-years: Analyses to inform the update of the American Cancer Society lung cancer screening guidelines. Cancer 2024; 130:201-215. [PMID: 37909885 PMCID: PMC10938406 DOI: 10.1002/cncr.34758] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 12/16/2022] [Accepted: 01/05/2023] [Indexed: 11/03/2023]
Abstract
BACKGROUND This report quantifies counteracting effects of quit-years and concomitant aging on lung cancer risk, especially on exceeding 15 quit-years, when the US Preventive Services Task Force (USPSTF) recommends curtailing lung-cancer screening. METHODS Cox models were fitted to estimate absolute lung cancer risk among Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) and National Lung Screening Trial (NLST) participants who ever smoked. Absolute lung cancer risk and gainable years of life from screening for individuals aged 50 to 80 in the US-representative National Health Interview Survey (NHIS) 2015-2018 who ever smoked were projected. Relaxing USPSTF recommendations to 20/25/30 quit-years versus augmenting USPSTF criteria with individuals whose estimated gain in life expectancy from screening exceeded 16.2 days according to the Life Years From Screening-CT (LYFS-CT) prediction model was compared. RESULTS Absolute lung cancer risk increased by 8.7%/year (95% CI, 7.7%-9.7%; p < .001) as individuals aged beyond 15 quit-years in the PLCO, with similar results in NHIS and NLST. For example, mean 5-year lung cancer risk for those aged 65 years with 15 quit-years = 1.47% (95% CI, 1.35%-1.59%) versus 1.76% (95% CI, 1.62%-1.90%) for those aged 70 years with 20 quit-years in the PLCO. Removing the quit-year criterion would make 4.9 million more people eligible and increase the proportion of preventable lung cancer deaths prevented (sensitivity) from 63.7% to 74.2%. Alternatively, augmentation using LYFS-CT would make 1.7 million more people eligible while increasing the lung cancer death sensitivity to 74.0%. CONCLUSIONS Because of aging, absolute lung cancer risk increases beyond 15 quit-years, which does not support exemption from screening or curtailing screening once it has been initiated. Compared with relaxing the USPSTF quit-year criterion, augmentation using LYFS-CT could prevent most of the deaths at substantially superior efficiency, while also preventing deaths among individuals who currently smoke with low intensity or long duration.
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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, USA
| | - Li C. Cheung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Corey D. Young
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
- Department of Microbiology, Biochemistry and Immunology, Morehouse School of Medicine, Atlanta, Georgia, USA
| | - Anil K. Chaturvedi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Hormuzd A. Katki
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
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Kondo KK, Rahman B, Ayers CK, Relevo R, Griffin JC, Halpern MT. Lung cancer diagnosis and mortality beyond 15 years since quit in individuals with a 20+ pack-year history: A systematic review. CA Cancer J Clin 2024; 74:84-114. [PMID: 37909870 DOI: 10.3322/caac.21808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 07/20/2023] [Accepted: 07/21/2023] [Indexed: 11/03/2023] Open
Abstract
Current US lung cancer screening recommendations limit eligibility to adults with a pack-year (PY) history of ≥20 years and the first 15 years since quit (YSQ). The authors conducted a systematic review to better understand lung cancer incidence, risk and mortality among otherwise eligible individuals in this population beyond 15 YSQ. The PubMed and Scopus databases were searched through February 14, 2023, and relevant articles were searched by hand. Included studies examined the relationship between adults with both a ≥20-PY history and ≥15 YSQ and lung cancer diagnosis, mortality, and screening ineligibility. One investigator abstracted data and a second confirmed. Two investigators independently assessed study quality and certainty of evidence (COE) and resolved discordance through consensus. From 2636 titles, 22 studies in 26 articles were included. Three studies provided low COE of elevated lung cancer incidence beyond 15 YSQ, as compared with people who never smoked, and six studies provided moderate COE that the risk of a lung cancer diagnosis after 15 YSQ declines gradually, but with no clinically significant difference just before and after 15 YSQ. Studies examining lung cancer-related disparities suggest that outcomes after 15 YSQ were similar between African American/Black and White participants; increasing YSQ would expand eligibility for African American/Black individuals, but for a significantly larger proportion of White individuals. The authors observed that the risk of lung cancer not only persists beyond 15 YSQ but that, compared with individuals who never smoked, the risk may remain significantly elevated for 2 or 3 decades. Future research of nationally representative samples with consistent reporting across studies is needed, as are better data from which to examine the effects on health disparities across different populations.
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Affiliation(s)
- Karli K Kondo
- Early Cancer Detection Science, American Cancer Society, Kennesaw, Georgia, USA
- Research Integrity, Oregon Health & Science University, Portland, Oregon, USA
| | - Basmah Rahman
- Early Cancer Detection Science, American Cancer Society, Kennesaw, Georgia, USA
| | - Chelsea K Ayers
- Center to Improve Veteran Involvement in Care, Portland Veterans Affairs Health Care System, Portland, Oregon, USA
| | - Rose Relevo
- Early Cancer Detection Science, American Cancer Society, Kennesaw, Georgia, USA
| | - Jessica C Griffin
- Early Cancer Detection Science, American Cancer Society, Kennesaw, Georgia, USA
| | - Michael T Halpern
- Division of Cancer Control & Population Sciences, National Cancer Institute, Bethesda, Maryland, USA
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Skurla SE, Leishman NJ, Fagerlin A, Wiener RS, Lowery J, Caverly TJ. Clinician Perceptions on Using Decision Tools to Support Prediction-Based Shared Decision Making for Lung Cancer Screening. MDM Policy Pract 2024; 9:23814683241252786. [PMID: 38779527 PMCID: PMC11110512 DOI: 10.1177/23814683241252786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024] Open
Abstract
Background Considering a patient's full risk factor profile can promote personalized shared decision making (SDM). One way to accomplish this is through encounter tools that incorporate prediction models, but little is known about clinicians' perceptions of the feasibility of using these tools in practice. We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS). Design We conducted a qualitative study based on field notes from academic detailing visits during a multisite quality improvement program. The detailer engaged one-on-one with 96 primary care clinicians across multiple Veterans Affairs sites (7 medical centers and 6 outlying clinics) to get feedback on 1) the rationale for prediction-based LCS and 2) how to use the DecisionPrecision (DP) encounter tool with eligible patients to personalize LCS discussions. Results Thematic content analysis from detailing visit data identified 6 categories of clinician willingness to use the DP tool to personalize SDM for LCS (adoption potential), varying from "Enthusiastic Potential Adopter" (n = 18) to "Definite Non-Adopter" (n = 16). Many clinicians (n = 52) articulated how they found the concept of prediction-based SDM highly appealing. However, to varying degrees, nearly all clinicians identified challenges to incorporating such an approach in routine practice. Limitations The results are based on the clinician's initial reactions rather than longitudinal experience. Conclusions While many primary care clinicians saw real value in using prediction to personalize LCS decisions, more support is needed to overcome barriers to using encounter tools in practice. Based on these findings, we propose several strategies that may facilitate the adoption of prediction-based SDM in contexts such as LCS. Highlights Encounter tools that incorporate prediction models promote personalized shared decision making (SDM), but little is known about clinicians' perceptions of the feasibility of using these tools in practice.We examined how clinicians react to using one such encounter tool for personalizing SDM about lung cancer screening (LCS).While many clinicians found the concept of prediction-based SDM highly appealing, nearly all clinicians identified challenges to incorporating such an approach in routine practice.We propose several strategies to overcome adoption barriers and facilitate the use of prediction-based SDM in contexts such as LCS.
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Affiliation(s)
- Sarah E. Skurla
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
| | | | - Angela Fagerlin
- University of Utah School of Medicine, Salt Lake City, UT, USA
- Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, VA Salt Lake City Healthcare System, Salt Lake City, UT, USA
| | - Renda Soylemez Wiener
- Center for Healthcare Organization & Implementation Research, VA Boston Healthcare System, Boston, MA, USA
- The Pulmonary Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Julie Lowery
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
| | - Tanner J. Caverly
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI, USA
- Department of Learning Health Sciences, University of Michigan School of Medicine, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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Wang L, Qi Y, Liu A, Guo X, Sun S, Zhang L, Ji H, Liu G, Zhao H, Jiang Y, Li J, Song C, Yu X, Yang L, Yu J, Feng H, Yang F, Xue F. Opportunistic Screening With Low-Dose Computed Tomography and Lung Cancer Mortality in China. JAMA Netw Open 2023; 6:e2347176. [PMID: 38085543 PMCID: PMC10716726 DOI: 10.1001/jamanetworkopen.2023.47176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/26/2023] [Indexed: 12/18/2023] Open
Abstract
Importance Despite the recommendations of lung cancer screening guidelines and the evidence supporting the effectiveness of population-based lung screening, a common barrier to effective lung cancer screening is that the participation rates of low-dose computed tomography (LDCT) screening among individuals with the highest risk are not large. There are limited data from clinical practice regarding whether opportunistic LDCT screening is associated with reduced lung-cancer mortality. Objective To evaluate whether opportunistic LDCT screening is associated with improved prognosis among adults with lung cancer in mainland China. Design, Setting, and Participants This cohort study included patients diagnosed with lung cancer at Weihai Municipal Hospital Healthcare Group, Weihai City, China, from 2016 to 2021. Data were analyzed from January 2022 to February 2023. Exposures Data collected included demographic indicators, tumor characteristics, comorbidities, blood indexes, and treatment information. Patients were classified into screened and nonscreened groups on the basis of whether or not their lung cancer diagnosis occurred through opportunistic screening. Main Outcomes and Measures Follow-up outcome indicators included lung cancer-specific mortality and all-cause mortality. Propensity score matching (PSM) was adopted to account for potential imbalanced factors between groups. The associations between LDCT screening and outcomes were analyzed using Cox regression models based on the matched data. Propensity score regression adjustment and inverse probability treatment weighting were used for sensitivity analysis. Results A total of 5234 patients (mean [SD] baseline age, 61.8 [9.8] years; 2518 [48.1%] female) with complete opportunistic screening information were included in the analytical sample, with 2251 patients (42.91%) receiving their lung cancer diagnosis through opportunistic screening. After 1:1 PSM, 2788 patients (1394 in each group) were finally included. The baseline characteristics of the matched patients were balanced between groups. Opportunistic screening with LDCT was associated with a 49% lower risk of lung cancer death (HR, 0.51; 95% CI, 0.42-0.62) and 46% lower risk of all-cause death (HR, 0.54; 95% CI, 0.45-0.64). Conclusions and Relevance In this cohort study of patients with lung cancer, opportunistic lung cancer screening with LDCT was associated with lower lung cancer mortality and all-cause mortality. These findings suggest that opportunistic screening is an important supplement to population screening to improve prognosis of adults with lung cancer.
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Affiliation(s)
- Lijie Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Healthcare Big Data Research Institute, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Department of Endocrinology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Yue Qi
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Ailing Liu
- Department of Pulmonary and Critical Care Medicine, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Xiaolei Guo
- Department for Chronic and Non-Communicable Disease Control and Prevention, Shandong Center for Disease Control and Prevention, Jinan, China
| | - Shanshan Sun
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Lanfang Zhang
- Department of Chemotherapy, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Huaijun Ji
- Department of Thoracic Surgery, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Guiyuan Liu
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Huan Zhao
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Yinan Jiang
- Department of Radiotherapy, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Jingyi Li
- Department of Radiotherapy, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Chengcun Song
- Department of Chemotherapy, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Xin Yu
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Liu Yang
- Department of Chemotherapy, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Jinchao Yu
- Department of Radiology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Hu Feng
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Fujun Yang
- Department of Oncology, Weihai Municipal Hospital, Cheeloo College of Medicine, Shandong University, Weihai, China
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Healthcare Big Data Research Institute, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China
- Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
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Wang Q, Song X, Zhao F, Chen Q, Xia W, Dong G, Xu L, Mao Q, Jiang F. Noninvasive diagnosis of pulmonary nodules using a circulating tsRNA-based nomogram. Cancer Sci 2023; 114:4607-4621. [PMID: 37770420 PMCID: PMC10728016 DOI: 10.1111/cas.15971] [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: 05/16/2023] [Revised: 07/20/2023] [Accepted: 08/31/2023] [Indexed: 09/30/2023] Open
Abstract
Evaluating the accuracy of pulmonary nodule diagnosis avoids repeated low-dose computed tomography (LDCT)/CT scans or invasive examination, yet remains a main clinical challenge. Screening for new diagnostic tools is urgent. Herein, we established a nomogram based on the diagnostic signature of five circulating tsRNAs and CT information to predict malignant pulmonary nodules. In total, 249 blood samples of patients with pulmonary nodules were selected from three different lung cancer centers. Five tsRNAs were identified in the discovery and training cohorts and the diagnostic signature was established by the randomForest algorithm (tRF-Ser-TGA-003, tRF-Val-CAC-005, tRF-Ala-AGC-060, tRF-Val-CAC-024, and tiRNA-Gln-TTG-001). A nomogram was developed by combining tsRNA signature and CT information. The high level of accuracy was identified in an internal validation cohort (n = 83, area under the receiver operating characteristic curve [AUC] = 0.930, sensitivity 100.0%, specificity 73.8%) and external validation cohort (n = 66, AUC = 0.943, sensitivity 100.0%, specificity 86.8%). Furthermore, the diagnostic ability of our model discriminating invasive malignant ones from noninvasive lesions was assessed. A robust performance was achieved in the diagnosis of invasive malignant lesions in both training and validation cohorts (discovery cohort: AUC = 0.850, sensitivity 86.0%, specificity 81.4%; internal validation cohort: AUC = 0.784, sensitivity 78.8%, specificity 78.1%; and external validation cohort: AUC = 0.837, sensitivity 85.7%, specificity 84.0%). This novel circulating tsRNA-based diagnostic model has potential significance in predicting malignant pulmonary nodules. Application of the model could improve the accuracy of pulmonary nodule diagnosis and optimize surgical plans.
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Affiliation(s)
- Qinglin Wang
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Xuming Song
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Feng Zhao
- Department of Thoracic SurgeryTaixing People's HospitalTaizhouChina
| | - Qiang Chen
- Department of Thoracic SurgeryXuzhou Central HospitalXuzhouChina
| | - Wenjie Xia
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Gaochao Dong
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Lin Xu
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Qixing Mao
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
| | - Feng Jiang
- Department of Thoracic Surgery, Jiangsu Cancer HospitalJiangsu Institute of Cancer Research, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
- Jiangsu Key Laboratory of Molecular and Translational Cancer ResearchCancer Institute of Jiangsu Province, Nanjing Medical University Affiliated Cancer HospitalNanjingChina
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Long KJ, Pitcher T, Kurman JS, Pritchett MA, Silvestri GA. Using a Blood Biomarker to Distinguish Benign From Malignant Pulmonary Nodules: A Subgroup Analysis Comparing Screen Detection, Sex, Smoking History, and Nodule Size. Chest 2023; 164:1572-1575. [PMID: 37414335 DOI: 10.1016/j.chest.2023.06.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 07/08/2023] Open
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Huber RM. [Early detection of lung cancer - current status and implementation scenarios]. Pneumologie 2023; 77:1016-1026. [PMID: 38092015 DOI: 10.1055/a-1531-0131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The prognosis of conventionally diagnosed lung cancer patients is still rather poor. Two large, randomized trials using screening by low dose CT could demonstrate that early detection in persons with smoking as risk factor can improve this prognosis. Early detection of lung cancer can be achieved by structured screening programs using low dose CT for persons at increased risk, but in addition also by consequent management of incidental pulmonary nodules, which are seen on imaging for other reasons. Integral part of these programs should be prevention measures, especially a consequent, repeated, low-threshold offer of a service for smoking cessation. Programs for lung cancer screening for persons at increased risk are only beneficial for the screenees and cost-effective, if the various parts of the program are optimally integrated and coordinated and all necessary disciplines (especially respiratory medicine, radiology, pathology, thoracic surgery, radiotherapy) are included in a multidisciplinary manner. For Germany the certified lung cancer centres in structured cooperation with physicians in private practice (respiratory physicians, radiologists, general practitioners) would be a good option. It is essential that there is a good perception for the need of early detection of lung cancer in politics and the public and that the persons at risk are reached, contacted and motivated by various methods.
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Steinberg MB, Young WJ, Miller Lo EJ, Bover-Manderski MT, Jordan HM, Hafiz Z, Kota KJ, Mukherjee R, Garthe NE, Sonnenberg FA, O'Dowd M, Delnevo CD. Electronic Health Record Prompt to Improve Lung Cancer Screening in Primary Care. Am J Prev Med 2023; 65:892-895. [PMID: 37306638 DOI: 10.1016/j.amepre.2023.05.016] [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: 01/25/2023] [Revised: 05/18/2023] [Accepted: 05/18/2023] [Indexed: 06/13/2023]
Abstract
INTRODUCTION Lung cancer is the leading cause of cancer death in the U.S. Combusted tobacco use, the primary risk factor, accounts for 90% of all lung cancers. Early detection of lung cancer improves survival, yet lung cancer screening rates are much lower than those of other cancer screening tests. Electronic health record (EHR) systems are an underutilized tool that could improve screening rates. METHODS This study was conducted in the Rutgers Robert Wood Johnson Medical Group, a university-affiliated network in New Brunswick, NJ. Two novel EHR workflow prompts were implemented on July 1, 2018. These prompts included fields to determine tobacco use and lung cancer screening eligibility and facilitated low-dose computed tomography ordering for eligible patients. The prompts were designed to improve tobacco use data entry, allowing for better lung cancer screening eligibility identification. Data were analyzed in 2022 retrospectively for the period July 1, 2017 to June 30, 2019. The analyses represented 48,704 total patient visits. RESULTS The adjusted odds of patient record completeness to determine eligibility for low-dose computed tomography (AOR=1.19, 95% CI=1.15, 1.23), eligibility for low-dose computed tomography (AOR=1.59, 95% CI=1.38, 1.82), and whether low-dose computed tomography was ordered (AOR=1.04, 95% CI=1.01, 1.07) all significantly increased after the electronic medical record prompts were implemented. CONCLUSIONS These findings show the utility and benefit of EHR prompts in primary care settings to increase identification for lung cancer screening eligibility as well as increased low-dose computed tomography ordering.
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Affiliation(s)
- Michael B Steinberg
- The Department of Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey.
| | - William J Young
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Erin J Miller Lo
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Michelle T Bover-Manderski
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, New Jersey
| | - Heather M Jordan
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Zibran Hafiz
- Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, New Jersey
| | - Karthik J Kota
- The Department of Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Rohit Mukherjee
- The Department of Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, New Jersey
| | - Nicolette E Garthe
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, New Jersey
| | - Frank A Sonnenberg
- The Department of Medicine, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Mary O'Dowd
- Rutgers Biomedical Health Sciences, Rutgers, The State University of New Jersey, New Brunswick, New Jersey
| | - Cristine D Delnevo
- Rutgers Center for Tobacco Studies, Rutgers, The State University of New Jersey, New Brunswick, New Jersey; Rutgers School of Public Health, Rutgers, The State University of New Jersey, Piscataway, New Jersey
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Kukhareva PV, Li H, Caverly TJ, Del Fiol G, Fagerlin A, Butler JM, Hess R, Zhang Y, Taft T, Flynn MC, Reddy C, Martin DK, Warner IA, Rodriguez-Loya S, Warner PB, Kawamoto K. Implementation of Lung Cancer Screening in Primary Care and Pulmonary Clinics: Pragmatic Clinical Trial of Electronic Health Record-Integrated Everyday Shared Decision-Making Tool and Clinician-Facing Prompts. Chest 2023; 164:1325-1338. [PMID: 37142092 PMCID: PMC10792294 DOI: 10.1016/j.chest.2023.04.040] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 04/18/2023] [Accepted: 04/25/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND Although low-dose CT (LDCT) scan imaging lung cancer screening (LCS) can reduce lung cancer mortality, it remains underused. Shared decision-making (SDM) is recommended to assess the balance of benefits and harms for each patient. RESEARCH QUESTION Do clinician-facing electronic health record (EHR) prompts and an EHR-integrated everyday SDM tool designed to support routine incorporation of SDM into primary care improve LDCT scan imaging ordering and completion? STUDY DESIGN AND METHODS A preintervention and postintervention analysis was conducted in 30 primary care and four pulmonary clinics for visits with patients who met United States Preventive Services Task Force criteria for LCS. Propensity scores were used to adjust for covariates. Subgroup analyses were conducted based on the expected benefit from screening (high benefit vs intermediate benefit), pulmonologist involvement (ie, whether the patient was seen in a pulmonary clinic in addition to a primary care clinic), sex, and race and ethnicity. RESULTS In the 12-month preintervention phase among 1,090 eligible patients, 77 patients (7.1%) had LDCT scan imaging orders and 48 patients (4.4%) completed screenings. In the 9-month intervention phase among 1,026 eligible patients, 280 patients (27.3%) had LDCT scan imaging orders and 182 patients (17.7%) completed screenings. Adjusted ORs were 4.9 (95% CI, 3.4-6.9; P < .001) and 4.7 (95% CI, 3.1-7.1; P < .001) for LDCT imaging ordering and completion, respectively. Subgroup analyses showed increases in ordering and completion for all patient subgroups. In the intervention phase, the SDM tool was used by 23 of 102 ordering providers (22.5%) and for 69 of 274 patients (25.2%) for whom LDCT scan imaging was ordered and who needed SDM at the time of ordering. INTERPRETATION Clinician-facing EHR prompts and an EHR-integrated everyday SDM tool are promising approaches to improving LCS in the primary care setting. However, room for improvement remains. As such, further research is warranted. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT04498052; URL: www. CLINICALTRIALS gov.
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Affiliation(s)
- Polina V Kukhareva
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Haojia Li
- Study Design and Biostatistics Center, University of Utah, Salt Lake City, UT
| | - Tanner J Caverly
- Center for Clinical Management Research, Department of Veterans Affairs, Ann Arbor, MI; Department of Learning Health Sciences, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, University of Michigan, Ann Arbor, MI
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Angela Fagerlin
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT; Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, Salt Lake City, UT
| | - Jorie M Butler
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT; Department of Internal Medicine, University of Utah, Salt Lake City, UT; Geriatrics Research and Education Center, George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT
| | - Rachel Hess
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT; Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Yue Zhang
- Study Design and Biostatistics Center, University of Utah, Salt Lake City, UT
| | - Teresa Taft
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Michael C Flynn
- Department of Internal Medicine, University of Utah, Salt Lake City, UT; Department of Pediatrics, University of Utah, Salt Lake City, UT; Community Physicians Group, University of Utah Health, Salt Lake City, UT
| | | | - Douglas K Martin
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Isaac A Warner
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | | | - Phillip B Warner
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT.
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Stevens ER, Caverly T, Butler JM, Kukhareva P, Richardson S, Mann DM, Kawamoto K. Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening. J Biomed Inform 2023; 147:104525. [PMID: 37844677 PMCID: PMC11221602 DOI: 10.1016/j.jbi.2023.104525] [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: 05/30/2023] [Revised: 10/06/2023] [Accepted: 10/13/2023] [Indexed: 10/18/2023]
Abstract
Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.
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Affiliation(s)
- Elizabeth R Stevens
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States.
| | - Tanner Caverly
- University of Michigan Medical School, Ann Arbor, MI, United States
| | - Jorie M Butler
- Department of Biomedical Informatics, University of Utah Health, Salt Lake City, UT, United States
| | - Polina Kukhareva
- Department of Biomedical Informatics, University of Utah Health, Salt Lake City, UT, United States
| | - Safiya Richardson
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States
| | - Devin M Mann
- Department of Population Health, NYU Grossman School of Medicine, New York, NY, United States; Medical Center Information Technology, NYU Langone Health, New York, NY, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah Health, Salt Lake City, UT, United States
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Vu LH, Yu Lee-Mateus A, Edell ES, Hartley C, Vierkant RA, Fernandez-Bussy S, Reisenauer J. Accuracy of Preliminary Pathology for Robotic Bronchoscopic Biopsy. Ann Thorac Surg 2023; 116:1028-1034. [PMID: 36470566 DOI: 10.1016/j.athoracsur.2022.11.022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 10/24/2022] [Accepted: 11/11/2022] [Indexed: 12/11/2022]
Abstract
BACKGROUND Diagnosis and treatment of peripheral pulmonary lesions (PPLs) currently require at least 2 procedures. An all-in-1 approach would require diagnosing malignancy with preliminary cytology results. This study investigated the concordance between preliminary cytology and final pathology results in biopsies of PPLs obtained by shape-sensing robotic-assisted bronchoscopy (ssRAB). METHODS This study was a retrospective, consecutive, single-arm, single-center study of 110 ssRABs for PPLs. Concordance was defined as agreement between preliminary cytology and final pathology results. Accuracy, sensitivity, specificity, positive and negative predictive values, and safety outcomes were examined. RESULTS The concordance was 89% for needle biopsies, 85% for forceps biopsies, and 92% overall, with substantial agreement. There was no significant association of concordance with patients' demographics or lesion characteristics. Preliminary cytology resulted in a malignant diagnosis in 70%, a nonmalignant diagnosis in 4%, and a nondiagnostic result in 26%, with accuracy of 86% and sensitivity of 84%. The total complication rate was 3.6%, with a pneumothorax rate of 1.8%. CONCLUSIONS This study compared the concordance of preliminary pathology results with final pathology results for ssRAB biopsies in PPLs. The results showed that preliminary samples have a high concordance with final pathology results and may enable management of PPLs with a single anesthetic procedure including biopsy, staging, and treatment.
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Affiliation(s)
- Linh H Vu
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Alejandra Yu Lee-Mateus
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Jacksonville, Florida
| | - Eric S Edell
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | | | - Robert A Vierkant
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Sebastian Fernandez-Bussy
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Jacksonville, Florida
| | - Janani Reisenauer
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota; Division of Thoracic Surgery, Department of Surgery, Mayo Clinic, Rochester, Minnesota.
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Kang HR, Song JH, Chung KB, Lee BJ, Lee JH, Lee CT. Impact of lung cancer screening with low-dose chest computed tomography on an older population: a retrospective cohort study. Transl Lung Cancer Res 2023; 12:2068-2082. [PMID: 38025808 PMCID: PMC10654442 DOI: 10.21037/tlcr-23-266] [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: 04/22/2023] [Accepted: 09/26/2023] [Indexed: 12/01/2023]
Abstract
Background The older population is at high risk of lung cancer (LC). However, the importance of lung cancer screening (LCS) in this population is rarely investigated. Herein, we evaluated the effect of LCS with low-dose computed tomography (LDCT) in the older population. Methods This retrospective cohort study was conducted in a single center and included patients aged 70-80 years who had undergone LCS with LDCT. They were categorized into the early 70s (70-74 years) and late 70s (75-80 years) groups based on their age. Using propensity score matching, the control group included patients with non-screening-detected LC from an LC cohort. LC detection, characteristics, and treatment were compared between the early and late 70s groups and between screening-detected LC and non-screening-detected LC. Results The study included 1,281 participants who underwent LDCT for LCS, of whom 1,020 were in their early 70s and 261 in their late 70s. Among the screening groups, 87.7% of the patients were ever-smokers. The overall LC detection rate was 2.8%. Interestingly, the LC detection rate in the late 70s group was similar to that in the early 70s group (3.4% vs. 2.7%, P=0.485). Furthermore, the incidence of LC was 6.1 cases and 8.3 cases per 1,000 person-years in the early 70s and late 70s groups, respectively (P=0.428). When comparing LC characteristics, patients with screening-detected LC showed a higher proportion of stage I LC (52.8% vs. 30.6%, P=0.010) and a lower proportion of stage IV LC (19.4% vs. 42.2%, P=0.010) than those with non-screening-detected LC. Moreover, 80.6% of patients with screening-detected LC received appropriate tumor reduction treatment based on the cancer stage. Conclusions In the older population, LCS using LDCT showed remarkable detection of LC, with a higher proportion of cases detected at an early stage.
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Affiliation(s)
- Hye-Rin Kang
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Graduate School, Seoul, Republic of Korea
| | - Jin Hwa Song
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea
| | - Keun Bum Chung
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea
| | - Byoung-Jun Lee
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea
| | - Jae-Ho Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Graduate School, Seoul, Republic of Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Choon-Taek Lee
- Department of Internal Medicine, Seoul National University College of Medicine, Graduate School, Seoul, Republic of Korea
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
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Shusted CS, Juon HS, Ruane B, Till B, Zeigler-Johnson C, McIntire RK, Grenda T, Okusanya O, Evans NR, Kane GC, Barta JA. Individual- and neighborhood-level characteristics of lung cancer screening participants undergoing telemedicine shared decision making. BMC Health Serv Res 2023; 23:1179. [PMID: 37899430 PMCID: PMC10614340 DOI: 10.1186/s12913-023-10185-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 10/19/2023] [Indexed: 10/31/2023] Open
Abstract
BACKGROUND Although lung cancer screening (LCS) for high-risk individuals reduces lung cancer mortality in clinical trial settings, many questions remain about how to implement high-quality LCS in real-world programs. With the increasing use of telemedicine in healthcare, studies examining this approach in the context of LCS are urgently needed. We aimed to identify sociodemographic and other factors associated with screening completion among individuals undergoing telemedicine Shared Decision Making (SDM) for LCS. METHODS This retrospective study examined patients who completed Shared Decision Making (SDM) via telemedicine between May 4, 2020 - March 18, 2021 in a centralized LCS program. Individuals were categorized into Complete Screening vs. Incomplete Screening subgroups based on the status of subsequent LDCT completion. A multi-level, multivariate model was constructed to identify factors associated with incomplete screening. RESULTS Among individuals undergoing telemedicine SDM during the study period, 20.6% did not complete a LDCT scan. Bivariate analysis demonstrated that Black/African-American race, Medicaid insurance status, and new patient type were associated with greater odds of incomplete screening. On multi-level, multivariate analysis, individuals who were new patients undergoing baseline LDCT or resided in a census tract with a high level of socioeconomic deprivation had significantly higher odds of incomplete screening. Individuals with a greater level of education experienced lower odds of incomplete screening. CONCLUSIONS Among high-risk individuals undergoing telemedicine SDM for LCS, predictors of incomplete screening included low education, high neighborhood-level deprivation, and new patient type. Future research should focus on testing implementation strategies to improve LDCT completion rates while leveraging telemedicine for high-quality LCS.
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Affiliation(s)
- Christine S Shusted
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, 834 Walnut Street, Suite 650, Philadelphia, PA, 19107, USA
| | - Hee-Soon Juon
- Department of Medical Oncology, Division of Population Science, Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Brooke Ruane
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, 834 Walnut Street, Suite 650, Philadelphia, PA, 19107, USA
| | - Brian Till
- Division of Thoracic Surgery, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Charnita Zeigler-Johnson
- Department of Medical Oncology, Division of Population Science, Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Russell K McIntire
- Jefferson College of Population Health, Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Tyler Grenda
- Division of Thoracic Surgery, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Olugbenga Okusanya
- Division of Thoracic Surgery, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Nathaniel R Evans
- Division of Thoracic Surgery, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, Philadelphia, PA, 19107, USA
| | - Gregory C Kane
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, 834 Walnut Street, Suite 650, Philadelphia, PA, 19107, USA
| | - Julie A Barta
- Division of Pulmonary and Critical Care Medicine, The Jane and Leonard Korman Respiratory Institute at Thomas Jefferson University, 834 Walnut Street, Suite 650, Philadelphia, PA, 19107, USA.
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Bonney A, Steinfort D, Manser R. Are current lung cancer screening guidelines and programs racially biased? Transl Lung Cancer Res 2023; 12:1834-1837. [PMID: 37854162 PMCID: PMC10579830 DOI: 10.21037/tlcr-23-444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 08/07/2023] [Indexed: 10/20/2023]
Affiliation(s)
- Asha Bonney
- Department of Respiratory and Sleep Medicine, The Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, The University of Melbourne, Melbourne, Australia
| | - Daniel Steinfort
- Department of Respiratory and Sleep Medicine, The Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, The University of Melbourne, Melbourne, Australia
| | - Renee Manser
- Department of Respiratory and Sleep Medicine, The Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, The University of Melbourne, Melbourne, Australia
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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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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: 1] [Impact Index Per Article: 1.0] [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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49
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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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50
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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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