S Tuminello, R Flores, M Untalan, T Ivic-Pavlicic, C I Henschke, R Yip, D F Yankelevitz, Emanuela Taioli
{"title":"偶然发现肺结节对非小细胞肺癌死亡率的预测影响。","authors":"S Tuminello, R Flores, M Untalan, T Ivic-Pavlicic, C I Henschke, R Yip, D F Yankelevitz, Emanuela Taioli","doi":"10.1016/j.jtho.2024.11.009","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>Despite the reduction in mortality by low-dose computed tomography lung cancer screening, the uptake is still low. Patients undergo chest imaging for several other medical reasons, and this is a unique opportunity to detect lung nodules.</p><p><strong>Methods: </strong>In a cohort of patients with NSCLC from the Surveillance, Epidemiology, and End Results-Medicare-linked data, tumor size at previous imaging was calculated as follows: volume doubling time = [(T<sub>2</sub>-T<sub>1</sub>)·ln2]/ln(V<sub>2</sub>/V<sub>1</sub>), solving for the diameter of V<sub>1</sub>. V<sub>1</sub> and V<sub>2</sub> are tumor volume at times T<sub>1</sub> (previous imaging) and T<sub>2</sub> (diagnostic procedure) according to three different growth models. The 10-year lung cancer-specific mortality was calculated as follows: lung cancer survival rate = (-0.0098 × maximum tumor diameter) + 1.</p><p><strong>Results: </strong>A total of 1007 patients who had a chest imaging performed up to 1 year before lung cancer diagnosis were included in this study. The median size of the tumor at diagnosis was 25 mm, and the predicted median tumor size at previous imaging was 12.16 mm, 17.3 mm, and 20.42 mm under the fast, medium, and slow growth model, respectively. Under the fast growth model, a detection of the nodule at previous imaging would have yield a decrease in mortality of 7.79%; the corresponding value for the medium growth model is 4.5% and for the slow growth model 2.45%.</p><p><strong>Conclusions: </strong>Identifying malignant lung nodules in imaging performed for other clinical reasons can help decrease the burden of NSCLC, especially for patients not eligible for low-dose computed tomography and the medically vulnerable. We reveal here that clinical benefits, especially among patients with aggressive disease, can be considerable.</p>","PeriodicalId":17515,"journal":{"name":"Journal of Thoracic Oncology","volume":" ","pages":""},"PeriodicalIF":21.0000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Predicted Effect of Incidental Pulmonary Nodule Findings on NSCLC Mortality.\",\"authors\":\"S Tuminello, R Flores, M Untalan, T Ivic-Pavlicic, C I Henschke, R Yip, D F Yankelevitz, Emanuela Taioli\",\"doi\":\"10.1016/j.jtho.2024.11.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Despite the reduction in mortality by low-dose computed tomography lung cancer screening, the uptake is still low. Patients undergo chest imaging for several other medical reasons, and this is a unique opportunity to detect lung nodules.</p><p><strong>Methods: </strong>In a cohort of patients with NSCLC from the Surveillance, Epidemiology, and End Results-Medicare-linked data, tumor size at previous imaging was calculated as follows: volume doubling time = [(T<sub>2</sub>-T<sub>1</sub>)·ln2]/ln(V<sub>2</sub>/V<sub>1</sub>), solving for the diameter of V<sub>1</sub>. V<sub>1</sub> and V<sub>2</sub> are tumor volume at times T<sub>1</sub> (previous imaging) and T<sub>2</sub> (diagnostic procedure) according to three different growth models. The 10-year lung cancer-specific mortality was calculated as follows: lung cancer survival rate = (-0.0098 × maximum tumor diameter) + 1.</p><p><strong>Results: </strong>A total of 1007 patients who had a chest imaging performed up to 1 year before lung cancer diagnosis were included in this study. The median size of the tumor at diagnosis was 25 mm, and the predicted median tumor size at previous imaging was 12.16 mm, 17.3 mm, and 20.42 mm under the fast, medium, and slow growth model, respectively. Under the fast growth model, a detection of the nodule at previous imaging would have yield a decrease in mortality of 7.79%; the corresponding value for the medium growth model is 4.5% and for the slow growth model 2.45%.</p><p><strong>Conclusions: </strong>Identifying malignant lung nodules in imaging performed for other clinical reasons can help decrease the burden of NSCLC, especially for patients not eligible for low-dose computed tomography and the medically vulnerable. We reveal here that clinical benefits, especially among patients with aggressive disease, can be considerable.</p>\",\"PeriodicalId\":17515,\"journal\":{\"name\":\"Journal of Thoracic Oncology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":21.0000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Thoracic Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.jtho.2024.11.009\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Thoracic Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.jtho.2024.11.009","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Predicted Effect of Incidental Pulmonary Nodule Findings on NSCLC Mortality.
Introduction: Despite the reduction in mortality by low-dose computed tomography lung cancer screening, the uptake is still low. Patients undergo chest imaging for several other medical reasons, and this is a unique opportunity to detect lung nodules.
Methods: In a cohort of patients with NSCLC from the Surveillance, Epidemiology, and End Results-Medicare-linked data, tumor size at previous imaging was calculated as follows: volume doubling time = [(T2-T1)·ln2]/ln(V2/V1), solving for the diameter of V1. V1 and V2 are tumor volume at times T1 (previous imaging) and T2 (diagnostic procedure) according to three different growth models. The 10-year lung cancer-specific mortality was calculated as follows: lung cancer survival rate = (-0.0098 × maximum tumor diameter) + 1.
Results: A total of 1007 patients who had a chest imaging performed up to 1 year before lung cancer diagnosis were included in this study. The median size of the tumor at diagnosis was 25 mm, and the predicted median tumor size at previous imaging was 12.16 mm, 17.3 mm, and 20.42 mm under the fast, medium, and slow growth model, respectively. Under the fast growth model, a detection of the nodule at previous imaging would have yield a decrease in mortality of 7.79%; the corresponding value for the medium growth model is 4.5% and for the slow growth model 2.45%.
Conclusions: Identifying malignant lung nodules in imaging performed for other clinical reasons can help decrease the burden of NSCLC, especially for patients not eligible for low-dose computed tomography and the medically vulnerable. We reveal here that clinical benefits, especially among patients with aggressive disease, can be considerable.
期刊介绍:
Journal of Thoracic Oncology (JTO), the official journal of the International Association for the Study of Lung Cancer,is the primary educational and informational publication for topics relevant to the prevention, detection, diagnosis, and treatment of all thoracic malignancies.The readship includes epidemiologists, medical oncologists, radiation oncologists, thoracic surgeons, pulmonologists, radiologists, pathologists, nuclear medicine physicians, and research scientists with a special interest in thoracic oncology.