ArticleThe journal of liquid biopsy2026
Minimal residual disease combined with radiological tumor volume as a tool for identification of resected NSCLC patients at high risk of recurrence.
Article in The journal of liquid biopsy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Circulating tumor DNA (ctDNA) is a valuable tool for assessing minimal residual disease (MRD) and predicting recurrence in resected non-small cell lung cancer (NSCLC) patients. Combining ctDNA-detection with radiological tumor volume may improve risk stratification. Methods: Patients with stage I-III resectable NSCLC were prospectively enrolled in the RESIDUAL study. Plasma samples were collected before surgery (T0), at landmark (10 days after surgery), during surveillance (T2, 20 days, T3, 1 months after surgery and every 3 months for the first year and then at the end of the second year after surgery), and at relapse. Samples were analyzed using Guardant Reveal, a tissue-free methylation-based ctDNA assay. Receiver operating characteristic analysis associated T1 ctDNA status with tumor volume; volume thresholds were calculated via Youden's J, and Cox regression analysis was performed. Results: Forty-eight patients were enrolled (median age 72 years; 64.6% male). Most had stage I disease (54.2%) and adenocarcinoma histology (79.2%). Median follow-up was 41.8 months, and 19 patients (39.6%) relapsed. Overall ctDNA detection rate was 15.2% across all timepoints. Pre-surgical ctDNA detection was higher in squamous histology and stage II-III disease and was associated with worse disease-free survival (DFS; p = 0.022). Landmark MRD detection was also associated with worse DFS (p = 0.024). Serial surveillance sampling anticipated radiologic recurrence by a median of 2.6 months (range 2.0-7.5). Patients with tumor volume >26,378 mm Conclusions: MRD detection in NSCLC resected patients predicts relapse and poor outcome; integrating ctDNA with tumor volume enhances identification of high-risk patients.
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