Explore the vast range of titles available.

Background Efficacy of 2nd line treatment in advanced gastric or gastro-esophageal junction (GEJ) adenocarcinoma remains limited with no identified strong predictor of treatment efficacy. We evaluated the prognostic value of circulating tumor DNA (ctDNA) in predicting the efficacy of immune checkpoint inhibitors (ICI) plus chemotherapy in the randomized PRODIGE 59-FFCD 1707-DURIGAST trial. Methods ctDNA was evaluated before treatment (baseline) and at 4 weeks (before the third cycle of treatment, C3) using droplet-digital PCR assays based on the detection of CpG methylation. Results Progression-free survival (PFS) and overall survival (OS) were shorter in patients with a high (>1.1 ng/mL) versus low (<1.1 ng/mL) ctDNA concentration at baseline (2.3 vs. 5.8 months; HR = 2.19; 95% CI, 1.09–4.41; p  = 0.03 and 4.5 vs. 12.9 months; HR = 2.73; 95% CI, 1.29–5.75; p  < 0.01), respectively, after adjustment for identified prognostic variables. Patients with a ctDNA decrease ≤75% between baseline and C3 versus a ctDNA decrease >75% had a worse objective response rate ( p  = 0.007), shorter PFS (2.2 vs. 7.4 months, HR = 1.90; 95% CI, 1.03–3.51; p = 0.04) and OS (6.6 vs 16.0 months; HR = 2.18; 95% CI, 1.09–4.37; p  = 0.03). Conclusions An early decrease in ctDNA concentration is a strong predictor of the therapeutic efficacy of ICI plus chemotherapy in advanced gastric/GEJ adenocarcinoma. Clinical Trial Information NCT03959293 (DURIGAST). Plain language summary Some patients with advanced gastric cancer receive immunotherapy (treatments that help one’s own immune system recognize and attack cancer cells) in addition to other treatments. We measured circulating tumor DNA (ctDNA) in patient’s blood samples and looked at associations with treatment outcome. We found that survival was shorter in patients receiving immunotherapy plus chemotherapy, when the levels of ctDNA in the blood were high at the start of treatment and when they did not decrease over time. Our results suggest that ctDNA could be used as a predictor of how well this specific treatment will work in advanced gastric cancer patients. Tougeron et al. evaluate the prognostic value of circulating tumor DNA (ctDNA) in predicting the efficacy of immune checkpoint inhibitors (ICI) plus chemotherapy in advanced gastric adenocarcinoma. An early decrease in ctDNA concentration is associated with a worse objective response rate, shorter progression free survival and overall survival.

Background Efficacy of 2nd line treatment in advanced gastric or gastro-esophageal junction (GEJ) adenocarcinoma remains limited with no identified strong predictor of treatment efficacy. We evaluated the prognostic value of circulating tumor DNA (ctDNA) in predicting the efficacy of immune checkpoint inhibitors (ICI) plus chemotherapy in the randomized PRODIGE 59-FFCD 1707-DURIGAST trial. Methods ctDNA was evaluated before treatment (baseline) and at 4 weeks (before the third cycle of treatment, C3) using droplet-digital PCR assays based on the detection of CpG methylation.Results Progression-free survival (PFS) and overall survival (OS) were shorter in patients with a high (>1.1 ng/mL) versus low (<1.1 ng/mL) ctDNA concentration at baseline (2.3 vs. 5.8 months; HR = 2.19; 95% CI, 1.09-4.41; p = 0.03 and 4.5 vs. 12.9 months; HR = 2.73; 95% CI, 1.29-5.75; p < 0.01), respectively, after adjustment for identified prognostic variables. Patients with a ctDNA decrease ≤75% between baseline and C3 versus a ctDNA decrease >75% had a worse objective response rate (p = 0.007), shorter PFS (2.2 vs. 7.4 months, HR = 1.90; 95% CI, 1.03-3.51; p = 0.04) and OS (6.6 vs 16.0 months; HR = 2.18; 95% CI, 1.09-4.37; p = 0.03). Conclusions An early decrease in ctDNA concentration is a strong predictor of the therapeutic efficacy of ICI plus chemotherapy in advanced gastric/GEJ adenocarcinoma. Clinical Trial Information NCT03959293 (DURIGAST).The prognosis of advanced gastric and gastro-esophageal junction (GEJ) adenocarcinoma remains poor, with overall survival (OS) ranging from 10% to 15% at 5 years 1 . In Human Epidermal Growth Factor Receptor-2 (HER2) negative unresectable advanced/metastatic tumors, the most frequently used first-line palliative chemotherapy is a doublet of fluoropyrimidine (5fluorouracil (5FU) or capecitabine) plus a platinum salt (cisplatin or oxaliplatin) 2,3 . Recently, the addition of docetaxel (TFOX regimen), immune checkpoint inhibitors (ICI, in PD-L1 positive tumors) and anti-claudin 18.

Renal cell carcinoma (RCC) is most often diagnosed at a localized stage, where surgery is the standard of care. Existing prognostic scores provide moderate predictive performance, leading to challenges in establishing follow-up recommendations after surgery and in selecting patients who could benefit from adjuvant therapy. In this study, we developed a model for individual postoperative disease-free survival (DFS) prediction using machine learning (ML) on real-world prospective data. Using the French kidney cancer research network database, UroCCR, we analyzed a cohort of surgically treated RCC patients. Participating sites were randomly assigned to either the training or testing cohort, and several ML models were trained on the training dataset. The predictive performance of the best ML model was then evaluated on the test dataset and compared with the usual risk scores. In total, 3372 patients were included, with a median follow-up of 30 months. The best results in predicting DFS were achieved using Cox PH models that included 24 variables, resulting in an iAUC of 0.81 [IC95% 0.77–0.85]. The ML model surpassed the predictive performance of the most commonly used risk scores while handling incomplete data in predictors. Lastly, patients were stratified into four prognostic groups with good discrimination (iAUC = 0.79 [IC95% 0.74–0.83]). Our study suggests that applying ML to real-world prospective data from patients undergoing surgery for localized or locally advanced RCC can provide accurate individual DFS prediction, outperforming traditional prognostic scores.