Key points are not available for this paper at this time.
PURPOSE: Personalized medicine presents new opportunities for patients with cancer. However, many patients do not receive the most effective personalized treatments because of challenges associated with integrating predictive biomarker testing into clinical care. Patients are lost at various steps along the precision oncology pathway because of operational inefficiencies, limited understanding of biomarker strategies, inappropriate testing result usage, and access barriers. We examine the impact of various clinical practice gaps associated with diagnostic testing-informed personalized medicine strategies on the treatment of advanced non-small-cell lung cancer (aNSCLC). METHODS: Using Diaceutics' Data Repository, a multisource database including commercial and Medicare claims and laboratory data from over 500,000 patients with non-small-cell lung cancer in the United States, we analyzed the number of patients with newly diagnosed aNSCLC who could have, but did not, benefit from a personalized treatment. The analysis focuses on the independent and cumulative impacts of gaps occurring during seven steps of the precision oncology pathway, from diagnosis to treatment. RESULTS: For every 1,000 patients in the study cohort, 497 (49.7%) are lost to precision oncology because of factors associated with getting biomarker test results. Among the 503 of 1,000 patients who did receive results from a biomarker test, 147 (29.2%) did not receive appropriate targeted treatments. Thus, approximately 64% of potentially eligible patients with aNSCLC are not benefiting from precision oncology therapies appropriate for their disease. CONCLUSION: Most patients with aNSCLC eligible for precision oncology treatments do not benefit from them because of clinical practice gaps. This finding is likely reflective of similar gaps in other cancer types. An increased understanding of the impact of each practice gap can inform strategies to improve the delivery of precision oncology, helping to fully realize the promise of personalized medicine.
Sadik et al. (Sat,) studied this question.