AIM: To select accurately good candidates of hepatic resection for colorectal liver metastasis. METHODS: Thirteen clinicopathological features, which were recognized only before or during surgery, were selected retrospectively in 81 consecutive patients in one hospital (Group I). These features were entered into a multivariate analysis to determine independent and significant variables affecting long-term prognosis after hepatectomy. Using selected variables, we created a scoring formula to classify patients with colorectal liver metastases to select good candidates for hepatic resection. The usefulness of the new scoring system was examined in a series of 92 patients from another hospital (Group II), comparing the number of selected variables. RESULTS: Among 81 patients of Group I, multivariate analysis, i.e. Cox regression analysis, showed that multiple tumors, the largest tumor greater than 5 cm in diameter, and resectable extrahepatic metastases were significant and independent prognostic factors for poor survival after hepatectomy (P < 0.05). In addition, these three factors: serosa invasion, local lymph node metastases of primary cancers, and post-operative disease free interval less than 1 year including synchronous hepatic metastasis, were not significant, however, they were selected by a stepwise method of Cox regression analysis (0.05 < P < 0.20). Using these six variables, we created a new scoring formula to classify patients with colorectal liver metastases. Finally, our new scoring system not only classified patients in Group I very well, but also that in Group II, according to long-term outcomes after hepatic resection. The positive number of these six variables also classified them well. CONCLUSION: Both, our new scoring system and the positive number of significant prognostic factors are useful to classify patients with colorectal liver metastases in the preoperative selection of good candidates for hepatic resection.
AIM: To select accurately good candidates of hepatic resection for colorectal liver metastasis. METHODS: Thirteen clinicopathological features, which were recognized only before or during surgery, were selected retrospectively in 81 consecutive patients in one hospital (Group I). These features were entered into a multivariate analysis to determine independent and significant variables affecting long-term prognosis after hepatectomy. Using selected variables, we created a scoring formula to classify patients with colorectal liver metastases to select good candidates for hepatic resection. The usefulness of the new scoring system was examined in a series of 92 patients from another hospital (Group II), comparing the number of selected variables. RESULTS: Among 81 patients of Group I, multivariate analysis, i.e. Cox regression analysis, showed that multiple tumors, the largest tumor greater than 5 cm in diameter, and resectable extrahepatic metastases were significant and independent prognostic factors for poor survival after hepatectomy (P < 0.05). In addition, these three factors: serosa invasion, local lymph node metastases of primary cancers, and post-operative disease free interval less than 1 year including synchronous hepatic metastasis, were not significant, however, they were selected by a stepwise method of Cox regression analysis (0.05 < P < 0.20). Using these six variables, we created a new scoring formula to classify patients with colorectal liver metastases. Finally, our new scoring system not only classified patients in Group I very well, but also that in Group II, according to long-term outcomes after hepatic resection. The positive number of these six variables also classified them well. CONCLUSION: Both, our new scoring system and the positive number of significant prognostic factors are useful to classify patients with colorectal liver metastases in the preoperative selection of good candidates for hepatic resection.
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Authors: Young Il Kim; In Ja Park; Jeong Eun Kim; So Yeon Kim; Jin-Hong Park; Jae Hoon Lee; Tae Yong Ha; Yong Sang Hong; Sun Young Kim; Tae Won Kim; Seok-Byung Lim; Chang Sik Yu; Jin Cheon Kim Journal: Ann Surg Treat Res Date: 2019-11-01 Impact factor: 1.859