Biomarkers to help guide management of patients with pulmonary nodules.
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RATIONALE: Indeterminate pulmonary nodules are a common radiographic finding and require further evaluation because of the concern for lung cancer. OBJECTIVES: We developed an algorithm to assign patients to a low- or high-risk category for lung cancer, based on a combination of serum biomarker levels and nodule size. METHODS: For the serum biomarker assay, we determined levels of carcinoembryonic antigen, α1-antitrypsin, and squamous cell carcinoma antigen. Serum data and nodule size from a training set of 509 patients with (n = 298) and without (n = 211) lung cancer were subjected to classification and regression tree and logistic regression analyses. Multiple models were developed and tested in an independent, masked validation set for their ability to categorize patients with (n = 203) or without (n = 196) lung cancer as being low- or high-risk for lung cancer. MEASUREMENTS AND MAIN RESULTS: In all models, a large percentage of individuals in the validation study with small nodules (<1 cm) were assigned to the low-risk group, and a large percentage of individuals with large nodules (≥3 cm) were assigned to the high-risk group. In the validation study, the classification and regression tree algorithm had overall sensitivity, specificity, and positive and negative predictive values for determining lung cancer of 88%, 82%, 84%, and 87%, respectively. The logistic regression model had overall sensitivity, specificity, and positive and negative predictive values of 80%, 89%, 89%, and 81%, respectively. CONCLUSION: Integration of biomarkers with lung nodule size has the potential to help guide the management of patients with indeterminate pulmonary nodules.
Aged, 80 and over
Sensitivity and Specificity
Solitary Pulmonary Nodule
Published Version (Please cite this version)10.1164/rccm.201210-1760OC
Publication InfoCampa, Michael Joseph; Eisenberg, M; Gottlin, EB; Grant, RP; Herndon, James Emmett II; Kafader, D; ... Trotter, PR (2013). Biomarkers to help guide management of patients with pulmonary nodules. Am J Respir Crit Care Med, 188(4). pp. 461-465. 10.1164/rccm.201210-1760OC. Retrieved from https://hdl.handle.net/10161/11579.
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Associate Professor in Radiology
There is longstanding evidence that invasive lung cancer is the end result of a multi-step process in which progressive molecular changes herald and accompany cytomorphologic changes. Our knowledge of these molecular events and the specific markers associated with the evolution from initiation to invasion is only partial. A number of specific biomarkers involved in oncogene activation or inactivation of tumor suppressor genes have been identified, but no single marker to date has been show
Professor of Biostatistics and Bioinformatics
Current research interests have application to the design and analysis of cancer clinical trials. Specifically, interests include the use of time-dependent covariables within survival models, the design of phase II cancer clinical trials which minimize some of the logistical problems associated with their conduct, and the analysis of longitudinal studies with informative censoring (in particular, quality of life studies of patients with advanced cancer).
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