Sign in Subscribe
Machine learning

Machine Learning Algorithm-Based Tumor-Stroma Ratio Improves Cholangiocarcinoma Prognosis

Strategic Insights

— 1 min read

A study published in the Journal of Surgical Research has demonstrated the efficacy of a machine learning algorithm-based tumor-stroma ratio in stratifying the prognosis of intrahepatic cholangiocarcinoma (iCCA) patients after radical surgery. The research, conducted by a team of scientists from Sun Yat-Sen University, aimed to quantify tumor components and explore effective biomarkers to predict the prognosis of iCCA patients.

Key Takeaways:

  • The study recruited a cohort of 237 iCCA patients who underwent radical resection and analyzed the tumor microenvironment components using a semiautomated pipeline.
  • The research found that high-stroma and low-tumor-infiltrated lymphocytes ratio % were associated with shorter disease-free survival (DFS) and overall survival (OS) in iCCA patients.
  • The multivariable Cox analysis verified the prognosis values of iCCA, including DFS (hazard ratio: 1.59, 95% confidence interval: 1.10-2.30, P = 0.015) and OS (hazard ratio: 1.92, 95% confidence interval: 1.27-4.17, P = 0.011).
  • The machine learning-based tumor-stroma ratio could serve as an effective prognostic biomarker for iCCA after radical surgery and potentially predict the therapeutic response of adjuvant chemotherapy.

Statistics:

  • 237 iCCA patients were recruited for the study.
  • The tumor microenvironment components were analyzed in 237 patients.
  • The overall survival (OS) and disease-free survival (DFS) were compared to evaluate their prognostic values.
  • The hazard ratio for DFS was 1.59 (95% confidence interval: 1.10-2.30, P = 0.015).
  • The hazard ratio for OS was 1.92 (95% confidence interval: 1.27-4.17, P = 0.011).

Sources:

  • "Machine Learning Algorithm-Based Tumor-Stroma Ratio Can Stratify the Prognosis of Intrahepatic Cholangiocarcinoma." Journal of Surgical Research, vol. 315, 2025, pp. 184-193.
  • Sun Yat-Sen University, Dept. of Pancreato-Biliary Surgery, First Affiliated Hospital. Journal of Surgical Research, Academic Press Inc Elsevier Science, 525 B St, Ste 1900, San Diego, CA 92101-4495, USA.
  • Elsevier, www.elsevier.com; Journal of Surgical Research, www.journals.elsevier.com/journal-of-surgical-research/.

Read more