New PCR-Based Assay Better Predicts Lung Cancer Survival

Assay identifies which early-stage NSCLC patients are at high risk of death after surgical resection

FRIDAY, Jan. 27 (HealthDay News) -- A new quantitative polymerase chain reaction (PCR)-based assay can better identify which patients with early-stage non-small-cell lung cancer (NSCLC) are at higher risk of mortality after surgical resection, according to a study published online Jan. 27 in The Lancet.

To stratify mortality risk after surgery for patients with early-stage NSCLC, Johannes R. Kratz, M.D., from the University of California San Francisco, and colleagues developed a 14-gene expression assay which uses quantitative PCR, runs on formalin-fixed paraffin-embedded tissue samples, and differentiates patients with heterogeneous statistical prognoses. The assay was developed in a cohort of 361 patients and then validated in two cohorts: 433 patients in Kaiser Permanente Northern California hospitals with stage I non-squamous NSCLC, and 1,006 patients in China with stage I to III non-squamous NSCLC.

The researchers found that the assay strongly predicted five-year overall survival in both validation groups. In the California group, five-year overall survival was 71.4 percent for low-risk patients, 58.3 percent for intermediate-risk patients, and 49.2 percent for high-risk patients. In the China group, survival was 74.1, 57.4, and 44.6 percent for low-, intermediate-, and high-risk patients, respectively. The assay predicted survival better than standard clinical risk factors, and improved prognostic accuracy beyond the National Comprehensive Cancer Network criteria for stage I high-risk tumors.

"This assay provides prognostic differentiation of patients with early-stage disease and might be helpful in the identification of the most appropriate application of treatment guidelines to improve clinical outcomes," Kratz and colleagues write.

Several authors disclosed financial ties to Pinpoint Genomics Inc., which developed the molecular assay based on UCSF technology, and partially funded the study.

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