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Purpose <p>To develop and validate a predictive model for stent patency following a palliative self-expandable metallic stent (SEMS) for primary malignant colonic obstruction.</p> Methods <p>Patients with primary malignant colonic obstruction who underwent SEMS treatment were included in this study. One retrospective set (<i>N</i> = 121) was used to develop and validate the predictive model. The clinical features were collected and subjected to Cox regression analyses. The final predictive model was displayed as a nomogram, which was validated in an independent set (<i>N</i> = 36).</p> Results <p>The clinical prognostic model was composed of pre-chemotherapy (<i>P</i> &lt; 0.001), time of obstruction (<i>P</i> = 0.005), and post-chemotherapy (<i>P</i> &lt; 0.001). The time-dependent area under the curve were 0.898 at 30-day, 0.778 at 90-day, 0.728 at 180-day, and 0.844 at 360-day in the training set; and 0.654 at 30-day, 0.745 at 90-day, 0.777 at 180-day, and 0.740 at 360-day in the validation set. Moreover, this easy-to-use and individualized nomogram was exclusively applied to predict stent patency and showed a favorable prognostic performance in the training and validation sets.</p> Conclusion <p>The nomogram developed in this study accurately predicts stent patency and shows promise for personalized SEMS management. However, external validation must be prioritized before clinical implementation to ensure generalizability and safety.</p>

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Individualized prediction of stent patency in malignant colonic obstruction: development and validation of a prognostic model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月11日

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  • Yuan Wan,
  • Meng-sha Zou,
  • Zhao-fei Zeng,
  • Xiao-zheng Cao,
  • Huan-hua Wu,
  • Bo Zhang

摘要

Purpose

To develop and validate a predictive model for stent patency following a palliative self-expandable metallic stent (SEMS) for primary malignant colonic obstruction.

Methods

Patients with primary malignant colonic obstruction who underwent SEMS treatment were included in this study. One retrospective set (N = 121) was used to develop and validate the predictive model. The clinical features were collected and subjected to Cox regression analyses. The final predictive model was displayed as a nomogram, which was validated in an independent set (N = 36).

Results

The clinical prognostic model was composed of pre-chemotherapy (P < 0.001), time of obstruction (P = 0.005), and post-chemotherapy (P < 0.001). The time-dependent area under the curve were 0.898 at 30-day, 0.778 at 90-day, 0.728 at 180-day, and 0.844 at 360-day in the training set; and 0.654 at 30-day, 0.745 at 90-day, 0.777 at 180-day, and 0.740 at 360-day in the validation set. Moreover, this easy-to-use and individualized nomogram was exclusively applied to predict stent patency and showed a favorable prognostic performance in the training and validation sets.

Conclusion

The nomogram developed in this study accurately predicts stent patency and shows promise for personalized SEMS management. However, external validation must be prioritized before clinical implementation to ensure generalizability and safety.