Purpose To develop a nomogram predicting the risks of distant metastasis following postoperative adjuvant radiation therapy for early stage cervical cancer. Materials and methods We reviewed the medical records of 1069 patients from ten participating institutions. Patients were divided into two cohorts: a training set (n = 748) and a validation set (n = 321). The demographic, clinical, and pathological variables were included in the univariate Cox proportional hazards analysis. Clinically established and statistically significant prognostic variables were utilized to develop a nomogram. Results The model was constructed using four variables: histologic type, pelvic lymph node involvement, depth of stromal invasion, and parametrial invasion. This model demonstrated good calibration and discrimination, with an internally validated concordance index of 0.71 and an externally validated c-index of 0.65. Compared to FIGO staging, which showed a broad range in terms of distant metastasis, the developed nomogram can accurately predict individualized risks based on individual risk factors. Conclusions The devised model offers a significantly accurate level of prediction and discrimination. In clinical practice it could be useful for counseling patients and selecting the patient group who could benefit from more intensive/further chemotherapy, once validated in a prospective patient cohort.
- Adjuvant radiotherapy
- Uterine cervical cancer
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging