Feller-Kopman DJ, Liu S, Garner AM, Decamp M, Pietzsch JB. Cost-effectiveness of the Percepta bronchial genomic classifier for the diagnostic evaluation of lung cancer: an analytical framework based on the AEGIS studies. Presentation at the 2016 annual meeting of the American Thoracic Society. Am J Respir Crit Care Med. 2016;193:A6182.

Objectives. Percepta is a bronchial genomic classifier that has been clinically validated to improve diagnostic accuracy for suspected cases of lung cancer. When bronchoscopy is inconclusive for lung cancer, the classifier genomically identifies patients who have a low probability of disease, and may therefore be considered for monitoring instead of an invasive biopsy procedure. The AEGIS-1 and AEGIS-2 studies have demonstrated an overall improvement in diagnostic sensitivity when bronchoscopy is not used by itself, but is used in conjunction with a genomic classifier. Our objective was to develop a health-economic framework for assessing the clinical and economic value proposition for using a bronchial genomic classifier as part of the diagnostic workup for suspected lung cancer.

Methods. We developed a decision-analytic Markov modeling framework comparing bronchoscopy only to bronchoscopy plus a bronchial genomic classifier. The model was developed from the third-party payer perspective, considering both U.S. Medicare and private-payer perspectives. Test performance for the initial diagnostic strategies was based on recently published AEGIS results (Silvestri et al., NEJM 2015). Diagnostic accuracy of noninvasive versus invasive follow-up, as well as associated adverse event rates, were derived from a review of the published literature. Procedure costs were based on an analysis of Medicare claims data and 2015 inpatient and outpatient reimbursement amounts. Because the commercial price of the classifier is not yet fully established, we used sensitivity analysis to explore the effect of changes in this parameter. All costs and outcomes were discounted at 3% per annum, in line with health-economic guidelines.

Results. In a patient cohort at intermediate risk for lung cancer (with a pretest probability of 10% to 60%), bronchoscopy plus the classifier was found to be associated with improved diagnostic accuracy compared to bronchoscopy alone (negative predictive value of 91%, and sensitivity of 93% versus 41%). If patients with negative classifier results did not undergo invasive biopsy procedures but were followed with computed tomography surveillance, they would realize an associated reduction in procedure-related adverse events, disutility, and costs. The bronchial genomic classifier strategy was found to be either dominant or cost-effective across the range of test costs examined, when considering commonly accepted thresholds of willingness to pay.

Conclusions. Bronchoscopy augmented by the use of a bronchial genomic classifier is a new diagnostic approach that promises to improve diagnostic performance for the detection of lung cancer and reduce unnecessary and invasive procedures, at a favorable health-economic profile ranging from overall cost-saving to cost-effective. Confirmatory analyses are needed once bronchial genomic classifier costs are fully established.