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Grant Details

Grant Number: 5R01CA260889-02 Interpret this number
Primary Investigator: Kong, Chung
Organization: Icahn School Of Medicine At Mount Sinai
Project Title: Optimizing Lung Cancer Screening Nodule Evaluation
Fiscal Year: 2022


SUMMARY The goal of this project is to optimize the management of screen-detected pulmonary nodules thus maximizing the benefits of lung cancer screening. Lung cancer is the most common cause of cancer death in the US. To curb the burden of this disease, multiple national organizations recommend lung cancer screening with low- dose computed tomography (LDCT). However, up to one third of screening LDCTs identify pulmonary nodules but only 1-3% of these are cancers. Screen-detected pulmonary nodules are then followed-up with additional imaging tests and, in some cases, invasive and potentially harmful procedures. Follow-up and subsequent work-up procedures account for a large portion of screening-associated unnecessary harms and costs. An optimal nodule management algorithm should substantially reduce these harms and provide early cancer detection benefits. However, the optimal management of pulmonary nodules detected during lung cancer screening is currently unknown. There are differing major guidelines for LDCT screen-detected lung nodule management. Most widely implemented guidelines focus on nodule characteristics to decide the need for and type of follow-up. These guidelines fail to incorporate other key patient factors such as age, sex, smoking history, and comorbidities. Furthermore, additional factors can heavily impact the diagnostic accuracy and harms of nodule management strategies and ultimately, the benefits of lung cancer screening. These include: 1) risk of lung cancer based on participant and nodule characteristics; 2) cancer aggressiveness; 3) type, sequence and timing of nodule follow-up; 4) follow-up and biopsy related complications; 5) competing risks of death (non-lung cancer mortality); and 6) impact of evaluation on quality of life. Furthermore, differences in smoking patterns, lung cancer risk, and comorbidities among diverse race and ethnic groups are not incorporated in current nodule management guidelines. In this project, we will use simulation modeling to efficiently determine optimal algorithms that consider all the issues listed above. We will build a simulation model, the Multi-Racial and Ethnic Lung Cancer Model (MELCAM), based on a previous modeling framework used by our team to extensively study various aspects of lung cancer control. The project Specific Aims are to: 1) Derive and validate MELCAM to simulate the management and subsequent outcomes of screening participants from diverse racial and ethnic backgrounds; 2) Use MELCAM to compare existing nodule management protocols in terms of overall and quality-adjusted life-year gains and harms; 3) Use MELCAM to generate nodule management algorithm(s) that consider the impact of both nodule and patient factors on cancer risk, screening harms, and life expectancy to optimize the types and timing of follow-up procedures; and 4) Determine the cost-effectiveness of existing and novel follow-up algorithms. Our study is innovative in applying state-of-the-art modeling techniques and personalized approaches to the optimization of pulmonary nodule management maximizing the benefits of lung cancer screening in diverse populations.


Clinical Outcomes of Resected Pure Ground-Glass, Heterogeneous Ground-Glass, and Part-Solid Pulmonary Nodules.
Authors: Sun J.D. , Sugarbaker E. , Byrne S.C. , Gagné A. , Leo R. , Swanson S.J. , Hammer M.M. .
Source: AJR. American journal of roentgenology, 2024 May; 222(5), p. e2330504.
EPub date: 2024-05-15.
PMID: 38323785
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Comparison of Lung-RADS Version 1.1 and Lung-RADS Version 2022 in Classifying Airway Nodules Detected at Lung Cancer Screening CT.
Authors: DeSimone A.K. , Byrne S.C. , Hammer M.M. .
Source: Radiology. Cardiothoracic imaging, 2024 Feb; 6(1), p. e230149.
PMID: 38300115
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Rate of benign nodule resection in a lung cancer screening program.
Authors: El Alam R. , Byrne S.C. , Hammer M.M. .
Source: Clinical imaging, 2023 Dec; 104, p. 109984.
EPub date: 2023-09-16.
PMID: 37832324
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Risk and Time to Diagnosis of Lung Cancer in Incidental Pulmonary Nodules.
Authors: Hammer M.M. .
Source: Journal of thoracic imaging, 2023-11-27; , .
EPub date: 2023-11-27.
PMID: 38095275
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Volume Doubling Times of Benign and Malignant Nodules in Lung Cancer Screening.
Authors: Hammer M.M. , Gupta S. , Byrne S.C. .
Source: Current problems in diagnostic radiology, 2023 Nov-Dec; 52(6), p. 515-518.
EPub date: 2023-07-02.
PMID: 37451949
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Growth Rates of Pulmonary Carcinoid Tumors and Hamartomas.
Authors: Ryan J.W. , Hammer M.M. .
Source: Journal of computer assisted tomography, 2023 May-Jun 01; 47(3), p. 396-401.
EPub date: 2023-01-14.
PMID: 37185002
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Malignant Nodules Detected on Lung Cancer Screening CT: Yield of Short-Term Follow-Up CT in Showing Nodule Growth.
Authors: Byrne S.C. , Hammer M.M. .
Source: AJR. American journal of roentgenology, 2022 Nov; 219(5), p. 735-741.
EPub date: 2022-06-08.
PMID: 35674352
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Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data.
Authors: Hammer M.M. , Hunsaker A.R. .
Source: AJR. American journal of roentgenology, 2022 Sep; 219(3), p. 397-405.
EPub date: 2022-03-23.
PMID: 35319912
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COVID-19 in the Radiology Literature: A Look Back.
Authors: Hammer M.M. , Raptis C.A. , Henry T.S. , Bhalla S. .
Source: Radiology. Cardiothoracic imaging, 2022 Aug; 4(4), p. e220102.
EPub date: 2022-07-14.
PMID: 35935812
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Cancer Risk in Nodules Detected at Follow-Up Lung Cancer Screening CT.
Authors: Hammer M.M. , Byrne S.C. .
Source: AJR. American journal of roentgenology, 2022 Apr; 218(4), p. 634-641.
EPub date: 2021-11-10.
PMID: 34755524
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Factors Influencing the False Positive Rate in CT Lung Cancer Screening.
Authors: Hammer M.M. , Byrne S.C. , Kong C.Y. .
Source: Academic radiology, 2022 Feb; 29 Suppl 2(Suppl 2), p. S18-S22.
EPub date: 2020-09-03.
PMID: 32893112
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