A new lymph node ratio-based staging system for rectosigmoid cancer: a retrospective study with external validation.

BACKGROUND

This study evaluated the clinical value of a new American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging prediction model based on lymph node ratio (LNR) in rectosigmoid cancer (RSC).

METHODS

The analysis included 1444 patients with nonmetastatic RSC diagnosed pathologically between 2010 and 2016 who were collected from the National Cancer Institute Surveillance, Epidemiology, and Results database. The AJCC N-stage was redefined according to the LNR cutoff point, and the ability of the new staging system to predict prognosis was compared with that of the AJCC TNM staging system. Data from 739 patients from our hospital were used for external validation.

RESULTS

According to the number of examined lymph nodes and LNR, the N stage was divided into five groups (LNR0-5). The 5-year OS of patients divided according to the new T lymph node ratio M (TLNRM) staging into stage I (T1LNR1, T1LNR2), IIA (T1LNR3, T2LNR1, T2LNR2, T2LNR3, T1LNR4, T3LNR1), IIB (T2LNR4), IIC (T3LNR2, T4a LNR1, T1LNR5), IIIA (T3LNR3, T2LNR5, T4b LNR1, T4a LNR2, T3LNR4), IIIB (T3LNR5, T4a LNR3, T4a LNR4, T4b LNR2), and IIIC (T4b LNR3, T4a LNR5, T4b LNR4, T4b LNR5) was significantly different ( P <0.05). Decision curve analysis showed that the net income of the new TLNRM staging system for different decision thresholds was higher than the prediction line of the traditional eighth TNM staging system. The smaller Akaike information criterion and Bayesian information suggested that the new staging system had a higher sensitivity for predicting prognosis than the traditional staging system. TLNRM II and III patients benefited from adjuvant chemotherapy, while adjuvant chemotherapy did not improve the prognosis of TNM II patients. These findings were confirmed by the external validation data.

CONCLUSION

The new TLNRM staging system was superior to the eighth edition AJCC staging system for staging and predicting the prognosis of patients with RSC and may become an effective tool in clinical practice.