Nomogram Predicting Lymph Node Metastasis in the Early-Stage Cervical Cancer

Area of Science:

• Oncology
• Radiology
• Medical Imaging

Background:

• Accurate prediction of lymph node metastasis is crucial for managing early-stage cervical cancer.
• ¹⁸F-FDG PET/CT imaging offers potential for risk stratification.
• Identifying high-risk patients aids in tailoring treatment strategies.

Purpose of the Study:

• To develop and validate a predictive nomogram for lymph node metastasis in early cervical cancer.
• To integrate ¹⁸F-FDG PET/CT findings with clinical characteristics.
• To improve pre-operative risk assessment for cervical cancer patients.

Main Methods:

• Retrospective review of 234 early-stage cervical cancer patients (FIGO 2018 IA-IIA) who underwent ¹⁸F-FDG PET/CT before surgery.
• Construction of a nomogram using predictors like SCCA, nSUVmax, uterine corpus invasion, and tumor size.
• Internal and external validation using a separate cohort of 191 patients.

Main Results:

• A nomogram incorporating squamous cell carcinoma antigen (SCCA), lymph node SUVmax (nSUVmax), uterine corpus invasion, and tumor size was developed.
• The nomogram achieved high predictive accuracy with an area under the ROC curve of 0.926 (primary) and 0.897 (validation).
• Calibration and decision curve analyses confirmed the nomogram's good agreement and clinical utility.

Conclusions:

• A simple and effective nomogram for predicting lymph node metastasis in cervical cancer has been established and validated.
• This tool can assist clinicians in pre-operative risk assessment for early-stage cervical cancer.
• The nomogram enhances personalized treatment planning by identifying metastasis risk.