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112 Invasion depth based on MRI as a new prognostic predictor for I-IIIB cervical cancer patients with radiotherapy
  1. Linying Liu,
  2. Jie Lin,
  3. Ning Xie,
  4. Sufang Deng,
  5. Haijuan Yu and
  6. Yang Sun
  1. Department of Gynecology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China

Abstract

Introduction/Background There was still controversy about the FIGO staging system of cervical cancer (CC), which was confirmed according to the gynecological examination. The tumor invasion depth (ID) in pathology has been proven to be closely associated with the prognosis of postoperative CC patients. This study aimed to use ID based on MRI to verify if it can be regarded as a predictive indicator of CC patients with radiotherapy.

Methodology 218 CC patients from stage I-IIIB (FIGO 2018) who received radiotherapy in 2019 were studied. ID was defined as the farthest distance of tumor invasion to the center of the cervical canal based on MRI. Factors including ID, vaginal invasion, and radiotherapy were identified as independent risk factors and were incorporated to build a nomogram to predict the 1-, 2- and 3-year OS. Patients were divided into low-, middle- and high-risk groups based on nomogram points.

Results Lower ID was a good indicator of CC patients with longer OS, PFS, LRFS, and DMFS (all P < 0.05).

The nomogram based on ID showed good discrimination and calibration (concordance index of 0.739). Compared with the FIGO 2018 staging system, the DCA curve showed that the new risk stratification had a better net benefit. CC patients in the low-risk group were the most prone to get longer OS (high- vs. middle- vs. low-risk group: P < 0.05), and patients in low- and middle-risk groups were more prone to get longer PFS, LRFS, and DMFS (high- vs. low-risk group, high- vs. middle-risk group: P < 0.05).

Conclusion Our study was the first to verify ID as a new prognostic predictor for CC patients of I-IIIB stage with radiotherapy. We developed a multifactorial prognostic model of CC patients. The new risk stratification was superior to the current 2018 FIGO staging system.

Disclosures The authors declare that they have no competing interests.

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