Development and validation of a predictive model for postoperative complications in elderly patients with locally advanced esophageal squamous cell carcinoma utilizing the POSSUM system and inflammatory markers - Summary - MDSpire

Development and validation of a predictive model for postoperative complications in elderly patients with locally advanced esophageal squamous cell carcinoma utilizing the POSSUM system and inflammatory markers

  • By

  • Ying Zhang

  • Haifang Zhu

  • Fujuan Yang

  • Lei Yang

  • January 27, 2026

  • 0 min

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Objective:

To develop a predictive model for postoperative complications in elderly patients with locally advanced esophageal squamous cell carcinoma by integrating the POSSUM system with inflammatory markers, enhancing predictive accuracy.

Key Findings:
  • The integration of inflammatory markers with the POSSUM system improved the predictive accuracy for postoperative complications, potentially leading to better patient management.
  • Common postoperative complications included pulmonary infection, anastomotic leakage, cardiac arrhythmia, and respiratory failure.
  • Age-related declines in organ reserve and the role of inflammation were significant factors in predicting complications.
Interpretation:

The study highlights the importance of considering both physiological and inflammatory factors in predicting postoperative outcomes in elderly patients with esophageal cancer, which could lead to improved clinical decision-making.

Limitations:
  • The study was conducted at a single institution, which may limit generalizability.
  • A formal power calculation was not performed, potentially affecting the robustness of the findings.
  • Exclusion of certain inflammatory markers may overlook additional risk factors, suggesting a need for broader studies in the future.
Conclusion:

The developed predictive model can aid clinicians in better managing surgical risks and improving postoperative outcomes for elderly patients with locally advanced esophageal squamous cell carcinoma, ultimately enhancing patient care.

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