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. 2010 May;251(5):872-81.
doi: 10.1097/SLA.0b013e3181c0e5b1.

Prognostic significance of the number of lymph nodes examined in colon cancer surgery: clinical application beyond simple measurement

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Prognostic significance of the number of lymph nodes examined in colon cancer surgery: clinical application beyond simple measurement

Yojiro Hashiguchi et al. Ann Surg. 2010 May.

Abstract

Objective: To identify an optimal cutoff value for the number of lymph node examined (NLNE) to distinguish the prognoses in patients following a curative resection for advanced colon cancer, to clarify the mechanism of the difference, and to suggest the integration of NLNE to colon cancer staging.

Patients and methods: A total of 859 patients who had undergone surgical treatment for localized colon cancer from 1980 to 2000 were reviewed. This was a cohort from a single institution with mean NLNE of 20.7 and more than 12 NLNE in 77% of the patients. The optimal breakpoint for NLNE was calculated by a receiver operating characteristic curve (ROC) analysis. The patients were stratified into groups based on various parameters and underwent univariate and multivariate analyses with respect to survival.

Results: The ROC analysis identified NLNE as a significant prognostic factor with cutoff value of 18 for node-negative and 20 for node-positive patients. A multivariate analysis with these cutoff values identified NLNE as a significant prognostic factor independent of tumor depth and the number of lymph nodes involved. The 5-year cause-specific survival of stage IIB patients was 96.5% with 18 or more NLNE and 67.5% with NLNE less than 18 (P[r]=0.0067). Similarly, a cutoff value of 20 NLNE for node-positive patients separated the 5-year cause-specific survival of stage IIIB patients into 79.3% with 20 or more NLNE and 63.3% with less than 20 NLNE (P=0.0052).

Conclusions: The clinical significance of NLNE is not limited to being a benchmark for quality care, but has a definite benefit as a prognostic indicator across the stages. Patients could be stratified more efficiently by the integration of NLNE to TNM staging.

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