A combination of blood proteins was able to differentiate between benign lung nodules and early-stage lung cancer with 90% probability, thereby providing a diagnostic tool to avoid invasive biopsy on benign nodules.

Only an estimated 20% of patients with lung nodules who undergo biopsy or surgery actually have a cancerous nodule, as noted in a statement from Science Translational Medicine, in which the study was published (2013;5[207]:207ra142).

Paul Kearney, PhD, and fellow investigators established the group of 13 blood-based proteins, known as a classifier, after identifying and creating a multiple reaction monitoring (MRM) assay for 371 protein candidates. Kearney is the president and chief science officer of Indi (Integrated Diagnostics), the molecular diagnostics company in Seattle, Washington, whose researchers helped develop the classifier by collecting plasma samples from 143 persons across three study sites. All of the samples came from persons with benign or stage 1A lung cancer.

To evaluate the diagnostic value of various combinations of biomarkers, the investigative team applied the MRM assays to the plasma samples. The 13-protein classifier that emerged was validated on an independent set of 104 plasma samples, exhibiting a negative predictive value (NPV) of 90%. Validation performance on samples from a fourth clinical site showed an NPV of 94%, which was indicative of the general effectiveness of the classifier.

The classifier score was independent of patient nodule size, smoking history, and age, all of which are risk factors used for clinical management of pulmonary nodules. These findings led Kearney and colleagues to conclude that this molecular test provides a potential complementary tool to help clinicians in lung cancer diagnosis.