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Development of a preoperative computed tomography score for the management of advanced epithelial ovarian cancer
  1. Luca Fuso1,
  2. Annamaria Ferrero1,
  3. Elena Vietti1,
  4. Massimo Petracchini2,
  5. Michela Mineccia3,
  6. Michela Villa1 and
  7. Guido Menato1
  1. 1 Gynaecology and Obstetrics Academic Department, University of Turin, A.O. Ordine Mauriziano, Turin, Italy
  2. 2 Radiology Department, A.O. Ordine Mauriziano, Turin, Italy
  3. 3 Surgical Oncology Department, A.O. Ordine Mauriziano, Turin, Italy
  1. Correspondence to Luca Fuso, Gynaecology and Obstetrics Academic Department, Universityof Turin, A.O. Ordine Mauriziano, Turin, Italy; luca.fuso1972{at}gmail.com

Abstract

Objective The main objective is to develop a model based on computed tomographic features to predict surgical outcome and establish cut-offs to rationalize clinical management in advanced epithelial ovarian carcinoma. The secondary purpose is to identify parameters that should be reported by radiologists to allow a correct pre-operative evaluation.

Methods This study evaluated the association between 17 radiologic parameters and surgical outcome through the review of 61 computed tomographic scans. Each parameter received a score according to the strength of statistical association and points were added to obtain a predictive index value. The absence of residual tumor was considered an optimal result. Receiver operating characteristic curves were applied to assess the ability to predict surgical outcome. The score was applied to the study population to verify if the therapeutic approach had been congruent with the predicted results and to define adequate cut-offs.

Results Analysis with a receiver operating characteristic curve demonstrated a statistical association with surgical outcome (area under curve=0.949). The clinical approach agreed with the predicted outcome. Patients with lower scores received primary debulking surgery (mean predictive index value 2.4) whereas those with higher scores (mean 14.1) were given neoadjuvant chemotherapy. Further surgical investigation (laparoscopy) was performed in patients with higher predictive index value variability (0–17.5). Different cut-offs were analysed to define the model applicability. The results show that surgery is appropriate for patients with a predictive index value <6 (failure rate 11.5%) while a predictive index value >8 should address to neoadjuvant chemotherapy (0% of inappropriately unexplored patients). In addition, patients with a predictive index value between 6 and 8 could benefit from diagnostic exploration with a good success rate (71.4%).

Conclusions The model correctly discerns patients who can benefit from surgery (predictive index value <6) from those who should undergo neoadjuvant chemotherapy (>8) and establishes a range (6–8) where surgical investigations may be helpful. This score is a flexible tool where cut-offs can be changed according to the desire to be surgically more aggressive or more conservative.

  • advanced ovarian carcinoma
  • computed tomography
  • debulking surgery
  • predictive score
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Footnotes

  • Patient consent Not required.

  • Ethics approval Study was approved by local ERB

  • Provenance and peer review Not commissioned; externally peer reviewed.

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