It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Circulating tumor DNA (ctDNA) provides valuable tumor-related information without invasive biopsies, yet consensus is lacking on optimal parameters for predicting clinical outcomes. Utilizing longitudinal ctDNA data from the large phase 3 IMpower150 study (NCT02366143) of atezolizumab in combination with chemotherapy with or without bevacizumab in patients with stage IV non-squamous Non-Small Cell Lung Cancer (NSCLC), here we report that post-treatment ctDNA response correlates significantly with radiographic response. However, only modest concordance is identified, revealing that ctDNA response is likely not a surrogate for radiographic response; both provide distinct information. Various ctDNA metrics, especially early ctDNA nadirs, emerge as primary predictors for progression-free survival and overall survival, potentially better assessing long-term benefits for chemoimmunotherapy in NSCLC. Integrating radiographic and ctDNA assessments enhances prediction of survival outcomes. We also identify optimal cutoff values for risk stratification and key assessment timepoints, notably Weeks 6–9, for insights into clinical outcomes. Overall, our identified optimal ctDNA parameters can enhance the prediction of clinical outcomes, refine trial designs, and inform therapeutic decisions for first-line NSCLC patients.
Circulating tumor DNA (ctDNA) is emerging as a minimally invasive biomarker for cancer diagnosis and prognosis assessment. Here, using longitudinal ctDNA data from the phase 3 IMpower150 trial, the authors analyse ctDNA parameters for predicting outcomes after first-line immunotherapy in patients with non-small cell lung cancer.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details


1 University of Science and Technology of China, Department of Statistics and Finance, School of Management, Hefei, China (GRID:grid.59053.3a) (ISNI:0000 0001 2167 9639)
2 Anhui Medical University, Department of Health Data Science, Hefei, China (GRID:grid.186775.a) (ISNI:0000 0000 9490 772X)
3 Genmab Inc., Clinical Pharmacology and Quantitative Science, Princeton, USA (GRID:grid.492734.f) (ISNI:0000 0004 6079 3997)