LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Early [18]FDG PET/CT scan predicts tumor response in head and neck squamous cell cancer patients treated with erlotinib adjusted per smoking status

Photo from wikipedia

Translational Relevance Evaluation of targeted therapies is urgently needed for the majority of patients with metastatic/recurrent head and neck squamous cell carcinoma (HNSCC) who progress after immunochemotherapy. Erlotinib, a targeted… Click to show full abstract

Translational Relevance Evaluation of targeted therapies is urgently needed for the majority of patients with metastatic/recurrent head and neck squamous cell carcinoma (HNSCC) who progress after immunochemotherapy. Erlotinib, a targeted inhibitor of epidermal growth factor receptor pathway, lacks FDA approval in HNSCC due to inadequate tumor response. This study identifies two potential avenues to improve tumor response to erlotinib among patients with HNSCC. For the first time, this study shows that an increased erlotinib dose of 300 mg in smokers is well-tolerated and produces similar plasma drug concentration as the regular dose of 150 mg in non-smokers, with increased study-specific defined tumor response. The study also highlights the opportunity for improved patient selection for erlotinib treatment by demonstrating that early in-treatment [18]FDG PET/CT is a potential predictor of tumor response, with robust statistical correlations between metabolic changes on early in-treatment PET (4-7 days through treatment) and anatomic response measured by end-of-treatment CT. Purpose Patients with advanced HNSCC failing immunochemotherapy have no standard treatment options. Accelerating the investigation of targeted drug therapies is imperative. Treatment with erlotinib produced low response rates in HNSCC. This study investigates the possibility of improved treatment response through patient smoking status-based erlotinib dose optimization, and through early in-treatment [18]FDG PET evaluation to differentiate responders from non-responders. Experimental design In this window-of-opportunity study, patients with operable HNSCC received neoadjuvant erlotinib with dose determined by smoking status: 150 mg (E150) for non-smokers and 300 mg (E300) for active smokers. Plasma erlotinib levels were measured using mass spectrometry. Patients underwent PET/CT before treatment, between days 4-7 of treatment, and before surgery (post-treatment). Response was measured by diagnostic CT and was defined as decrease in maximum tumor diameter by ≥ 20% (responders), 10-19% (minimum-responders), and < 10% (non-responders). Results Nineteen patients completed treatment, ten of whom were smokers. There were eleven responders, five minimum-responders, and three non-responders. Tumor response and plasma erlotinib levels were similar between the E150 and E300 patient groups. The percentage change on early PET/CT and post-treatment PET/CT compared to pre-treatment PET/CT were significantly correlated with the radiologic response on post-treatment CTs: R=0.63, p=0.0041 and R=0.71, p=0.00094, respectively. Conclusion This pilot study suggests that early in-treatment PET/CT can predict response to erlotinib, and treatment with erlotinib dose adjusted according to smoking status is well-tolerated and may improve treatment response in HNSCC. These findings could help optimize erlotinib treatment in HNSCC and should be further investigated. Clinical Trial Registration https://clinicaltrials.gov/ct2/show/NCT00601913, identifier NCT00601913.

Keywords: tumor response; smoking status; erlotinib; treatment; response; study

Journal Title: Frontiers in Oncology
Year Published: 2022

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.