Journal: Scientific reports
This study developed and validated a postoperative risk prediction model for recurrence and metastasis in early-stage cervical cancer by integrating circulating tumor cell (CTC) counts and tumor fibrosis distance (TFD).
A retrospective analysis of 148 patients identified the following independent predictors of poor prognosis:
- CTCs ≥ 28/5 mL
- TFD ≤ 5.7 mm
The combined model demonstrated strong predictive performance:
- AUC: 0.91
- Sensitivity: 90.6%
- Specificity: 84.5%
- Negative Predictive Value (NPV): 94.7%
This model allowed stratification into low-, intermediate-, and high-risk groups with tailored management recommendations.
Complementary animal experiments showed that high-risk groups had:
- Increased CTC release
- Immune imbalance
- Elevated inflammatory markers (IL-6, TNF-α)
- Increased oxidative stress
These findings support the model’s biological basis.
This integrative approach surpasses traditional clinicopathological models, offering a promising tool for personalized postoperative surveillance and treatment planning in cervical cancer.