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| Home > Publications database > Deep Learning-Derived Sarcopenia Marker Predicts Benefit from Anti-EGFR Therapy in Patients with RAS Wild-type Metastatic Colorectal Cancer. |
| Home > Publications database > Deep Learning-Derived Sarcopenia Marker Predicts Benefit from Anti-EGFR Therapy in Patients with RAS Wild-type Metastatic Colorectal Cancer. |
| Journal Article | DKFZ-2026-00534 |
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2026
AACR
Philadelphia, Pa. [u.a.]
Abstract: The benefit of treatment intensification in metastatic colorectal cancer (mCRC) may be influenced by host-related factors that are not accounted for in clinical trials or standard care. We investigated the prognostic and predictive value of the muscle/bone ratio (MBR), a sarcopenia marker automatically derived from computed tomography (CT) images, in patients with mCRC from the prospective PanaMa study and a real-world validation cohort.PanaMa (AIO KRK 0212; NCT01991873) randomized patients with RAS wild-type mCRC, following induction therapy, to maintenance therapy with fluorouracil and folinic acid (FU/FA) with or without panitumumab (Pmab). MBR was automatically calculated from baseline CT images using a validated deep learning model, and patients were stratified by MBR tertiles. Associations with progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analyses. A retrospective real-world cohort of patients with mCRC treated with cetuximab was used for validation.Premaintenance CT images were available for 189 of 248 randomized patients (76.2%) from PanaMa. In patients receiving FU/FA + Pmab, high MBR was associated with longer PFS [HR, 0.43; 95% confidence interval (CI), 0.25-0.73; P = 0.002] and OS (HR, 0.41; 95% CI, 0.21-0.77; P = 0.006), whereas no association was observed in patients receiving FU/FA alone. Pmab provided a PFS benefit only in patients with high MBR (HR, 0.42; 95% CI, 0.24-0.73; P = 0.002). The association of high MBR with superior PFS (P = 0.002) and OS (P < 0.001) was confirmed in the real-world cohort.The benefit of anti-EGFR therapy in mCRC is confined to patients with a high MBR. Automated sarcopenia assessment holds promise for personalized treatment intensification in mCRC.
Keyword(s): Humans (MeSH) ; Male (MeSH) ; Female (MeSH) ; Sarcopenia: diagnosis (MeSH) ; Sarcopenia: pathology (MeSH) ; Sarcopenia: etiology (MeSH) ; Colorectal Neoplasms: drug therapy (MeSH) ; Colorectal Neoplasms: pathology (MeSH) ; Colorectal Neoplasms: genetics (MeSH) ; Colorectal Neoplasms: mortality (MeSH) ; Colorectal Neoplasms: complications (MeSH) ; ErbB Receptors: antagonists & inhibitors (MeSH) ; Aged (MeSH) ; Middle Aged (MeSH) ; Antineoplastic Combined Chemotherapy Protocols: therapeutic use (MeSH) ; Antineoplastic Combined Chemotherapy Protocols: adverse effects (MeSH) ; Deep Learning (MeSH) ; Prognosis (MeSH) ; Panitumumab: administration & dosage (MeSH) ; Leucovorin: administration & dosage (MeSH) ; Cetuximab: administration & dosage (MeSH) ; Retrospective Studies (MeSH) ; Biomarkers, Tumor (MeSH) ; Fluorouracil: administration & dosage (MeSH) ; ras Proteins: genetics (MeSH) ; Tomography, X-Ray Computed (MeSH) ; Prospective Studies (MeSH) ; Neoplasm Metastasis (MeSH) ; ErbB Receptors ; EGFR protein, human ; Panitumumab ; Leucovorin ; Cetuximab ; Biomarkers, Tumor ; Fluorouracil ; ras Proteins
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