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EP379 Prognosis-predicting model based on F-18 PET metabolic parameters in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy: multi-center retrospective study
  1. C-M Park1,
  2. YH Lee2,
  3. HJ Lee3,
  4. DG Hong2,
  5. DH Lee4,
  6. YS Choi5,
  7. YS Lee2 and
  8. GO Chong2
  1. 1Obsteterics and Gynecology, Jeju National University/Jeju National University Hospital
  2. 2Obstetrics and Gynecology, Kyungpook National University/Kyungpook National University Chilgok Hospital
  3. 3Obstetrics and Gynecology, Kyungpook National University/Kyungpook National University Hospital
  4. 4Obstetrics and Gynecology, Yeungnam University
  5. 5Obstetrics and Gynecology, Daegu Catholic University, Daegu, Republic of Korea

Abstract

Introduction/Background The aim of this study was to develop a prognosis-predicting model based on F-18-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (CCRT).

Methodology The medical records of 270 patients with locally advanced cervical cancer who were treated with CCRT were collected from three institutions and reviewed retrospectively. A nomogram for predicting disease-free survival (DFS) and overall survival (OS) was made using Cox proportional hazards regression. Predictor variables included nodal maximum standardized uptake value (SUVmax), primary tumor SUVmax, age, tumor size, stage, serum squamous cell carcinoma (SCC) antigen level, and human papillomavirus status. Internal validation of the nomogram was performed.

Results A nomogram for predicting the 2-year DFS and 5-year OS was constructed using 7 parameters. With a focus on 2-year DFS, our model found nodal SUVmax was the highest weighted negative prognostic factor. With a focus on 5-year OS, young age was the highest weighted negative prognostic factor. The concordance index was 0.75 for the 2-year DFS and 0.78 for the 5-year OS, respectively.

Conclusion This nomogram is a predictive tool that can be used to counsel patients in predicting survival outcomes. Moreover, our prognosis-predicting model may make it possible to personalize treatment.

Disclosure Nothing to disclose.

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