CHEST Guidelines-Using-a-Blood-Biomarker-to-Distinguish-Benign-From

Using-a-Blood-Biomarker-to-Distinguish-Benign-From

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This study investigates the use of a proteomic integrated classifier (IC) combining two plasma proteins (LG3BP and C163A) with clinical and imaging factors to improve the identification of benign pulmonary nodules, potentially reducing unnecessary invasive procedures. The IC was assessed through two large multi-center cohort studies, PANOPTIC and ORACLE, which included a combined total of 430 patients. These patients had nodules ranging from 8 to 30 mm in diameter, with malignancy confirmed via histopathology and benign status inferred from radiographic resolution or stability over a year.<br /><br />The prevalence of malignancy among participants was 14%. In examining differences across subgroups based on screen detection, sex, smoking status, and nodule size, the IC maintained a high Negative Predictive Value (NPV), notably 98%. No significant disparity in performance was observed when comparing screen-detected versus incidental nodules, or across sex lines. However, a greater sensitivity and lower specificity were evident for individuals who had ever used tobacco compared to those who never smoked.<br /><br />Interestingly, the IC showed variation based on nodule size; sensitivity remained similar across sizes, but specificity was higher for smaller nodules (57% for nodules ≤11 mm). Nonetheless, the high NPV supports that negative test results can confidently guide surveillance, potentially reducing invasive procedures by reclassifying likely benign nodules typically subjected to further testing.<br /><br />The study highlights the utility of the IC in broad populations, suggesting consistent efficacy across different patient demographics. Despite some limitations, such as the smaller subgroup sizes and the decision to define benign status after 12 rather than the standard 24 months, the IC presents a promising tool for enhancing nodule assessment efficiency and accuracy. Thus, it offers a potential advance in lung cancer screening initiatives, specifically by lowering unnecessary escalations to invasive testing when monitoring pulmonary nodules.

Keywords

proteomic integrated classifier

plasma proteins

benign pulmonary nodules

PANOPTIC study

ORACLE study

negative predictive value

lung cancer screening

nodule size

smoking status

invasive procedures