Added value of a serum proteomic signature in the diagnostic evaluation of lung nodules.

BACKGROUND: Current management of lung nodules is complicated by nontherapeutic resections and missed chances for cure. We hypothesized that a serum proteomic signature may add diagnostic information beyond that provided by combined clinical and radiographic data. METHODS: Cohort A included 265 and cohort B 114 patients. Using multivariable logistic regression analysis we calculated the area under the receiver operating characteristic curve (AUC) and quantified the added value of a previously described serum proteomic signature beyond clinical and radiographic risk factors for predicting lung cancer using the integration discrimination improvement (IDI) index. RESULTS: The average computed tomography (CT) measured nodule size in cohorts A and B was 37.83 versus 23.15 mm among patients with lung cancer and 15.82 versus 17.18 mm among those without, respectively. In cohort A, the AUC increased from 0.68 to 0.86 after adding chest CT imaging variables to the clinical results, but the proteomic signature did not provide meaningful added value. In contrast, in cohort B, the AUC improved from 0.46 with clinical data alone to 0.61 when combined with chest CT imaging data and to 0.69 after adding the proteomic signature (IDI of 20% P = 0.0003). In addition, in a subgroup of 100 nodules between 5 and 20 mm in diameter, the proteomic signature added value with an IDI of 15% (P ≤ 0.0001). CONCLUSIONS: The results show that this serum proteomic biomarker signature may add value to the clinical and chest CT evaluation of indeterminate lung nodules. IMPACT: This study suggests a possible role of a blood biomarker in the evaluation of indeterminate lung nodules.

Diagnostic characteristics of a serum biomarker in patients with positron emission tomography scans.

BACKGROUND: Surgery for pulmonary nodules results in a benign diagnosis in 10% to 30% of cases. Computed tomography and fluorodeoxyglucose-positron emission tomography (FDG-PET) are highly sensitive but less specific. High-risk patients (age > 55 years and smoke > 15 pack-years) for lung cancer with negative FDG-PET scans, or low-risk patients (age < 55 years or smoke < 15 pack-years) with FDG-PET-avid lesions may have higher rates of benign nodules. We hypothesized that our serum biomarker improves diagnostic accuracy by providing greater specificity. METHODS: Fifty-eight patients with pulmonary nodules (< or = 3 cm) were prospectively enrolled. We tested the accuracy of our proteomic biomarker in the serum by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Malignancy rates, contingency tables, sensitivity, and specificity analyses were calculated for the entire group and in a subset of patients at high risk for benign disease. RESULTS: We identified 46 (79%) lung cancers and 12 (21%) benign lesions. Forty-five nodules were FDG-PET-avid. In 36 high-risk patients with FDG-PET-avid lesions, 32 (89%) had cancer. Of the remaining 22 lower-risk patients, 14 (64%) had cancer (p = 0.02). The serum biomarker sensitivity was 26.1%, specificity was 91.7%, positive predictive value was 92%, negative predictive value was 24%, and overall accuracy was 40%. The serum signature accurately predicted all eight benign nodules in this 22-patient subset. CONCLUSIONS: The serum protein biomarker has a high specificity. This biomarker has a high positive predictive value but low negative predictive value and may improve noninvasive evaluation of lung nodules. Validation in a larger population is warranted.