Spots Global Cancer Trial Database for Response and Toxicity Prediction by Microbiome Analysis After Concurrent Chemoradiotherapy

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Trial Identification

Brief Title: Response and Toxicity Prediction by Microbiome Analysis After Concurrent Chemoradiotherapy

Official Title: Response and Toxicity Prediction by Microbiome Analysis After Concurrent Chemo RT in Locally Advanced NSCLC Treated With IO (Durvalumab)

Study ID: NCT04711330

Conditions

Non Small Cell Lung Cancer Stage III

Immunotherapy

Interventions

Study Description

Brief Summary: The predictive value of the microbiome (throat swabs, stool and of bronchial samples) to identify patients who will relapse during durvalumab treatment after CRT (False negative Rate) at 6 months. Exploratory endpoints include the effects of antibiotic therapy before and during IO treatment on toxicity and response rate. The role of exhaled breath analysis in prediction of response and toxicity will also be investigated.

Detailed Description: In this observational study we aim to investigate the predictive value of the microbiome (throat swabs and stool) to identify patients who will relapse during durvalumab treatment after CRT (False negative Rate) at 6 months. Collection of stool and throat swipe before start of durvalumab treatment; sampling of blood and exhaled air for analysis of volatile organic compounds. Improved clinical outcomes after adjuvant treatment with durvalumab following concurrent chemoradiotherapy (CCRT) for locally advanced NSCLC (PACIFIC trial), led to the rapid adoption of this treatment strategy as standard of care. However, despite the improved progression free survival and overall survival, recurrence rate remains high. Approximately 45% of patients will relapse within 1 year, despite adjuvant durvalumab therapy. To date no performant biomarker predicting treatment response or failure nor toxicity exists and the number of prospective studies addressing this issue is limited. Both PD-L1 TPS and TMB should be considered 'enriching' parameters improving response-chances, but they are far from an ideal biomarker. Non-invasive biomarkers are essential in the future for better patient selection and therapy allocation. One of the potential non-invasive biomarkers of interest is the microbiome.