Scholarlink

Background <p>Aberrant expression of p53 and elevated Ki-67 proliferation index have been associated with tumor progression and recurrence; however, their prognostic value in postoperative early gastric cancer (EGC) remains to be fully established. This study aimed to develop and internally validate a nomogram integrating these biomarkers for individualized recurrence risk prediction.</p> Methods <p>We retrospectively analyzed 536 EGC patients from a single institution between January 2017 and October 2018, with follow-up through June 2025. Patients were randomly divided into training (n = 375) and validation (n = 161) cohorts. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic predictors. Model performance was assessed using time-dependent AUC, integrated Brier score, calibration curves, and decision curve analysis.</p> Results <p>Five independent factors were identified: Helicobacter pylori infection (HR = 1.83), Ki-67 &gt; 30% (HR = 4.28), lymphovascular invasion (HR = 1.91), perineural invasion (HR = 4.37), and p53 (reference: mutant, HR = 0.37). The nomogram achieved good discriminative ability (1-year AUC: 0.861 training, 0.878 validation; 5-year AUC: 0.808, 0.788). Nomogram-based risk stratification demonstrated significant differences in survival outcomes (log-rank <i>P</i> &lt; 0.001).</p> Conclusion <p>This nomogram demonstrates potential utility for recurrence risk stratification in postoperative EGC patients. However, the model requires external validation in independent, multi-center cohorts before clinical implementation. The single-center retrospective design and relatively short follow-up represent important limitations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A nomogram integrating p53 and Ki-67 expression for predicting recurrence risk in postoperative early gastric cancer

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月19日

查看全文
  • Jinming Yan,
  • Zexue Qi,
  • Ruming Zhang

摘要

Background

Aberrant expression of p53 and elevated Ki-67 proliferation index have been associated with tumor progression and recurrence; however, their prognostic value in postoperative early gastric cancer (EGC) remains to be fully established. This study aimed to develop and internally validate a nomogram integrating these biomarkers for individualized recurrence risk prediction.

Methods

We retrospectively analyzed 536 EGC patients from a single institution between January 2017 and October 2018, with follow-up through June 2025. Patients were randomly divided into training (n = 375) and validation (n = 161) cohorts. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify independent prognostic predictors. Model performance was assessed using time-dependent AUC, integrated Brier score, calibration curves, and decision curve analysis.

Results

Five independent factors were identified: Helicobacter pylori infection (HR = 1.83), Ki-67 > 30% (HR = 4.28), lymphovascular invasion (HR = 1.91), perineural invasion (HR = 4.37), and p53 (reference: mutant, HR = 0.37). The nomogram achieved good discriminative ability (1-year AUC: 0.861 training, 0.878 validation; 5-year AUC: 0.808, 0.788). Nomogram-based risk stratification demonstrated significant differences in survival outcomes (log-rank P < 0.001).

Conclusion

This nomogram demonstrates potential utility for recurrence risk stratification in postoperative EGC patients. However, the model requires external validation in independent, multi-center cohorts before clinical implementation. The single-center retrospective design and relatively short follow-up represent important limitations.