Chu Liang, Wang Han, Ling Tao, Feng Shuhan, Ding Yucheng, Zhang Yan, Pan Ying, Wang Cenzhu, Wang Xiaohong, Liu Lei
Department of Surgery, The Affiliated Yixing Hospital of Jiangsu University, Yixing, Jiangsu, China.
Clinical Laboratory, Hainan Medical University, Haikou, Hainan, China.
Front Mol Biosci. 2025 Aug 1;12:1617787. doi: 10.3389/fmolb.2025.1617787. eCollection 2025.
The aim of this study was to assess the prognostic significance of positive lymph node ratio (LNR), tumor deposits (TD), and perineural invasion (PNI) in advanced colorectal signet-ring cell carcinoma (SRCC).
A multicenter retrospective cohort analysis was conducted involving 677 patients with advanced colorectal SRCC. The associations of variables with CSS and OS were analyzed using the Kaplan-Meier method and multivariable Cox proportional hazards models. A nomogram model was developed to predict outcomes.
High-LNR, TD-positive, and PNI-positive were associated with poorer CSS and OS in both the training and validation cohorts. Multivariate Cox analysis identified T stage, M stage, TD, CEA, chemotherapy, and LNR as independent prognostic factors. A prognostic nomogram model incorporating these variables demonstrated excellent calibration and satisfactory predictive accuracy. Survival curves generated from individualized nomogram scores effectively discriminated prognostic outcomes ( < 0.001). The combined variable of LNR, TD, and PNI significantly enhanced the predictive performance. Specifically, the combined variable exhibited the highest relative contribution to OS at 23.4%, surpassing that of T and M stages. For CSS, its relative contribution was 21.4%, ranking second only to T and M stages.
LNR, TD, and PNI served as prognostic factors for advanced colorectal SRCC. The combined analysis demonstrated a higher prognostic predictive value.
本研究旨在评估阳性淋巴结比率(LNR)、肿瘤结节(TD)和神经周围侵犯(PNI)在晚期结直肠癌印戒细胞癌(SRCC)中的预后意义。
进行了一项多中心回顾性队列分析,纳入677例晚期结直肠癌SRCC患者。使用Kaplan-Meier法和多变量Cox比例风险模型分析变量与CSS和OS的相关性。开发了一个列线图模型来预测预后。
在训练队列和验证队列中,高LNR、TD阳性和PNI阳性均与较差的CSS和OS相关。多变量Cox分析确定T分期、M分期、TD、CEA、化疗和LNR为独立预后因素。纳入这些变量的预后列线图模型显示出良好的校准和令人满意的预测准确性。根据个体化列线图评分生成的生存曲线有效区分了预后结果(<0.001)。LNR、TD和PNI的联合变量显著提高了预测性能。具体而言,联合变量对OS的相对贡献最高,为23.4%,超过了T和M分期。对于CSS,其相对贡献为21.4%,仅次于T和M分期。
LNR、TD和PNI是晚期结直肠癌SRCC的预后因素。联合分析显示出更高的预后预测价值。