The American Society of Clinical Oncology (ASCO) and the National Comprehensive Cancer Network (NCCN) recommend molecular testing to guide treatment for non–small cell lung cancer (NSCLC).1,2 Known gene alterations can help physicians identify “potentially efficacious targeted therapies,” notes the NCCN panel.1 The ASCO panel suggests that providers identify “appropriate gene targets on either primary or metastatic lung lesions to guide initial treatment selection.”2
What’s missing, said Benjamin Djulbegovic, MD, PhD, professor of hematology and hematopoietic cell transplantation and medical director of evidence-based analytics at City of Hope, Duarte, California, is a framework to assess whether omics-based management strategies correlate with patient survival. “Despite decades of investment in precision medicine/targeted therapy,” Dr Djulbegovic explained, “evidence that such an approach reliably improves patients’ outcomes has been lacking. Our study fills that void.”
In a recent paper, principal investigator Dr Djulbegovic and colleagues demonstrated that the use of genomics data — coupled with a particular type of flowchart called a fast-and-frugal decision tree (FFT) — helped improve overall survival (OS) and progression-free survival (PFS) compared with standard/nontargeted treatment in patients with advanced lung cancer.3
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The study authors described the FFT model as a simple series of cues/questions (eg, Driver mutation?) accompanied by 2 decisions (eg, Other mutation? or Nontargeted therapy) to which the user answers yes or no, essentially moving through if-then scenarios. “The binary (yes or no) responses” the authors explained, “determine the ratio between false-negative and false-positive recommendations, which, in turn, allow the application of Bayesian methods to calculate the accuracy of the entire FFT (ie, the entire clinical management strategy).”3
Dr Djulbegovic’s retrospective study was conducted at a single institution, City of Hope, where 4 academic thoracic-oncology specialists treated 798 patients with stage IV NSCLC between 2008 and 2016; chart review occurred between 2016 and 2018. Among the study cohort, 56% were female, 50% had a history of smoking, a majority were white (60%) and a third were Asian, and median patient age was 65 years.3
A total of 83% of patients received molecular testing to interrogate for alterations in the genes EGFR, ALK, ROS1, KRAS, BRAF, MET, and RET. Based on those results, 55% of patients received targeted therapy with tyrosine kinase inhibitors (TKIs). The FFT model was applied to the omics-informed treatment decisions, and OS and PFS were measured “as a function of the management driven by targeted versus nontargeted therapy,” the authors wrote.3
Results showed that the FFT model was highly predictive of a decision to use targeted therapy with TKIs — overall positive predictive value was 88%; negative predictive value was 96%. The investigators reported that the management strategy for advanced lung cancer was driven almost exclusively by the availability of a targeted therapy, whereas clinical characteristics played a lesser role in treatment decision making.3
