ArticleWorld journal of surgical oncology2025
Predictive value of combined Albumin-Globulin score and psoas muscle index for postoperative prognosis in combined hepatocellular carcinoma and cholangiocarcinoma.
Article in World journal of surgical oncology, 2025. 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
backgroundNutrition and inflammation play vital roles in the prognosis of cancer patients. This study evaluated the impact of relevant indicators-albumin-globulin score (AGS), psoas muscle index (PMI), and the combination of AGS and PMI (CAP)- on postoperative outcomes in combined hepatocellular carcinoma and cholangiocarcinoma (cHCC-CC) patients.
methodsOne hundred forty one cHCC-CC patients treated surgically from 2010 to 2020 were retrospectively analyzed. Psoas muscle area was measured via abdominal CT scans. Albumin (ALB), globulin (GLB), and PMI cutoff values were established through receiver operating characteristic (ROC) curves. The influence of AGS, PMI, and CAP on cHCC-CC prognosis was evaluated using Time-dependent ROC curves. The predictive accuracy of nomograms were evaluated using calibration plots, the C-index value, and the area under the ROC curves (AUC).
resultsLower PMI and higher AGS indicated poorer OS and DFS. A lower CAP grade was linked to a more favorable prognosis, with CAP grade 1 showing the best and grade 3 the worst prognosis. The Td-ROC curve demonstrates that CAP grade outperforms PMI and AGS in terms of predictive ability at various time points. The predictive accuracy of nomograms was considered acceptable, with c-index values of 0.684 (95% CI: 0.632-0.731) and 0.684 (95% CI: 0.635-0.734) for OS and DFS, respectively.The corresponding AUC values for 1, 3, and 5-year OS were 0.731, 0.744, and 0.720, and for DFS were 0.768, 0.796, and 0.757.
conclusionsThe CAP grade, integrating AGS and PMI, significantly correlates with postoperative prognosis in cHCC-CC patients. It stands as a crucial indicator for optimizing treatment planning.
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