Predictors of lymph node count in colorectal cancer resections: data from US nationwide prospective cohort studies

Abstract

Objective: To identify factors that influence the total and negative lymph node counts in colorectal cancer resection specimens independent of pathologists and surgeons.

Design: We used multivariate negative binomial regression. Covariates included age, sex, body mass index, family history of colorectal carcinoma, year of diagnosis, hospital setting, tumor location, resected colorectal length (specimen length), tumor size, circumferential growth, TNM stage, lymphocytic reactions and other pathological features, and tumor molecular features (microsatellite instability, CpG island methylator phenotype, long interspersed nucleotide element 1 [LINE-1] methylation, and BRAF, KRAS, and PIK3CA mutations).

Setting: Two US nationwide prospective cohort studies.

Patients: Patients with rectal and colon cancer (N=918).

Main outcome measures: The negative and total node counts (continuous).

Results: Specimen length, tumor size, ascending colon location, T3N0M0 stage, and year of diagnosis were positively associated with the negative node count (all P.002). Mutation of KRAS might also be positively associated with the negative node count (P=.03; borderline significance considering multiple hypothesis testing). Among node-negative (stages I and II) cases, specimen length, tumor size, and ascending colon location remained significantly associated with the node count (all P.002), and PIK3CA and KRAS mutations might also be positively associated (P=.03 and P=.049, respectively, with borderline significance).

Conclusions: This molecular pathological epidemiology study shows that specimen length, tumor size, tumor location, TNM stage, and year of diagnosis are operator-independent predictors of the lymph node count. These crucial variables should be examined in any future evaluation of the adequacy of lymph node harvest and nodal staging when devising individualized treatment plans for patients with colorectal cancer.

Figure 1

Number of cases analyzed in this study by State. Our patients were distributed throughout the U.S., and our results would not have been influenced by any particular surgeon or pathologist, thus increasing generalizability of our findings.

Figure 2

Lymph node counts in 918 colorectal cancers in our two U.S. nationwide prospective cohort studies. (A) Distribution of the negative node count. (B) Distribution of the total node count. Both negative and total node counts approximately follow a Gamma-Poisson-like distribution. (C) Correlation between the negative node count and specimen length. (D) Correlation between the negative node count and tumor size.