65 % of Eligible Lung Cancer Patients Do Not Receive the Most Appropriate Targeted Therapies, Diaceutics Report Finds

Why It Matters

The shift from diagnostic to decision‑making failures threatens the value of precision‑medicine investments and could delay life‑extending therapies for a majority of lung‑cancer patients.

Key Takeaways

• 65% of US aNSCLC patients lack optimal targeted therapy
• Treatment decision loss rose to 43.3% in 2023
• 86% of oncologists plan treatment before full biomarker results
• Only 43% wait for biomarker data before starting first‑line therapy
• Real‑time decision support needed to close precision‑medicine gap

Pulse Analysis

The latest Diacritics Clinical Practice Gaps report underscores a paradox in American lung‑cancer care. While biomarker testing for advanced non‑small cell lung cancer (aNSCLC) has expanded dramatically since 2019, the overall proportion of patients missing the most appropriate targeted therapy has barely moved, staying at roughly 65% in 2023. The study examined real‑world outcomes for more than 35,800 newly diagnosed patients, confirming that diagnostic uptake is no longer the primary bottleneck. Yet the promise of precision medicine remains unrealized for the majority of those who could benefit.

The report pinpoints a new choke point: treatment‑decision loss, which climbed from 29.2% in 2019 to 43.3% in 2023. Survey data reveal that 86% of oncologists devise a treatment plan before receiving complete biomarker panels, and only 43% consistently wait for those results before initiating first‑line therapy. More than half of clinicians do not act on the specific recommendations embedded in biomarker reports. This downstream gap reflects time pressure, growing test complexity, and a lack of actionable decision‑support tools at the point of care. Without timely alignment, patients risk receiving suboptimal regimens that diminish therapeutic benefit.

Closing this translation gap will require a systemic redesign of precision‑medicine workflows. Industry players are urged to embed real‑time analytics, interoperable electronic health‑record alerts, and physician‑focused education into the treatment pathway. Diagnostic‑enabled, data‑driven operating models can surface the most actionable targets instantly, reducing reliance on clinician memory and mitigating delays. If adopted at scale, such solutions could shrink the 65% loss rate, improve survival outcomes, and justify the billions invested in lung‑cancer biomarker platforms.