Barbara Nemesure, PhD  Professor, Department of Family, Population and Preventive Medicine Division Head, Epidemiology and Biostatistics Director, Cancer Prevention and Control Program Director, Lung Cancer Program, Stony Brook Cancer Center Renaissance School of Medicine Stony Brook University  

Risk Prediction Nodule Helps Determine Cancer Risk of Pulmonary Nodule Found on CT Scan

MedicalResearch.com Interview with:

Barbara Nemesure, PhD  Professor, Department of Family, Population and Preventive Medicine Division Head, Epidemiology and Biostatistics Director, Cancer Prevention and Control Program Director, Lung Cancer Program, Stony Brook Cancer Center Renaissance School of Medicine Stony Brook University  

Dr. Nemesure

Barbara Nemesure, PhD
Professor, Department of Family, Population and Preventive Medicine
Division Head, Epidemiology and Biostatistics
Director, Cancer Prevention and Control Program
Director, Lung Cancer Program, Stony Brook Cancer Center
Renaissance School of Medicine
Stony Brook University   

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Lung cancer is the most common cause of cancer death, claiming the lives of more than 150,000 people in the United States each year. While lung nodules are not uncommon, it has remained a challenge to differentiate those that will progress to cancer and those that will remain benign. Although numerous risk prediction models for lung cancer have been developed over the past 2 decades, the majority have been based on retrospective analyses or high risk groups with a strong history of tobacco use. To date, there have been a limited number of large-scale, prospective studies evaluating risk that a nodule will convert to cancer in the general population.

This investigation aimed to construct a population-based risk prediction model of incident lung cancer for patients found to have a lung nodule on initial CT scan. The derived model was determined to have high accuracy for predicting nodule progression to cancer and identified a combination of clinical and radiologic predictors including age, smoking history (pack-years), a personal history of cancer, the presence of chronic obstructive pulmonary disease (COPD), and nodule features such as size, presence of spiculation and ground glass opacity type.

When compared to patients in the low risk category, those defined as high risk had more than 14 times the risk of developing lung cancer. Quantification of reliable risk scores has high clinical utility, enabling physicians to better stratify treatment plans for their patients.     

MedicalResearch.com: What should readers take away from your report?

Response: Accurate risk prediction models may reduce the burden of care in patients with very low risk, while ensuring more vigilant monitoring in those found to be at higher risk. Despite the fact that most lung nodules will not progress to cancer, it is important that patients seek follow up care if they are found to have a pulmonary nodule.

MedicalResearch.com: What recommendations do you have for future research as a result of this work? 

Response: Future studies are needed to validate this model in other populations and to develop corresponding risk prediction calculators for implementation into clinical practice.

No disclosures

Citation: 

Will That Pulmonary Nodule Become Cancerous? A Risk Prediction Model for Incident Lung Cancer

Barbara NemesureSean CloustonDenise AlbanoStephen Kuperberg and Thomas V. Bilfinger
Cancer Prevention Research

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Last Updated on June 28, 2019 by Marie Benz MD FAAD