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Triplet chemotherapy combined with anti Epidermal Growth Factor Receptor treatment in RAS wild-type colorectal cancer: a network metanalysis

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BACKGROUND: The optimal first-line treatment for Rat Sarcorma Virus (RAS) wild-type metastatic colorectal cancer remains undetermined. Several studies have compared the efficacy of different first-line regimens, including doublet- or triplet-chemotherapy (CT) alone or in combination with targeted therapies (anti-EGFR/anti-VEGF), without conclusive results. METHODS: We conducted a systematic review and meta-analysis of phase II/III randomized clinical trials (RCT) comparing triplet-CT+anti-EGFRs with alternative first-line regimens in RAS wild-type patients. Pairwise- and network-meta-analyses were performed to assess overall response rate (ORR). Furthermore, we evaluated PFS and OS with pairwise-metanalyses. RESULTS: A total of 1283 patients across seven RCT were included. Four treatment arms were analyzed: Arm A (triplet-CT+anti-EGFR), Arm B (doublet-CT+anti-EGFR), Arm C (triplet al.ne), and Arm D (triplet+anti-VEGF). Arms A, B, and D demonstrated higher ORR compared to Arm C, while no significant differences were found among Arms A, B, and D (OR 1.05, 95% CI 0.73-1.49; P = .804, for Arm B in comparison to Arm A; OR 0.80, 95% CI 0.52-1.25; P = .328, for Arm D in comparison to Arm A). Pairwise-meta-analysis revealed significantly lower ORR for Arm C compared to Arm A (OR 4.23, 95% CI 2.06-8.68, P = .002). P-scores ranked Arm B highest for effectiveness (0.808), followed by Arm A (0.746), then Arm D (0.444) and lastly Arm C (0.002). The pooled Hazard ratios (HRs) for OS demonstrated a superiority for arm A (0.82, 95% CI 0.70-0.97, P = .022). CONCLUSIONS: Triplet-CT+anti-EGFR demonstrated no clear ORR advantage over other targeted regimens but was superior to triplet-CT alone. Preliminary data indicate a potential OS benefit. Due to increased toxicity, routine use of triplet-CT+anti-EGFR should be carefully evaluated.

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Colorectal Cancer Treatments and StudiesColorectal Cancer Surgical TreatmentsRadiomics and Machine Learning in Medical Imaging

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