A laparoscopic risk-adjusted model to predict major complications after primary debulking surgery in ovarian cancer: A single-institution assessment

Francesco Fanfani, Giovanni Scambia, Anna Fagotti, Giuseppe Vizzielli, Barbara Costantini, Lucia Tortorella, Valerio Gallotta, Salvatore Gueli Alletti, Francesco Cosentino, Camilla Nero

Risultato della ricerca: Contributo in rivistaArticolo in rivista

22 Citazioni (Scopus)

Abstract

Objective To develop and validate a simple adjusted laparoscopic score to predict major postoperative complications after primary debulking surgery (PDS) in advanced epithelial ovarian cancer (AEOC). Methods From January 2006 to June 2015, preoperative, intraoperative, and post-operative outcome data from patients undergoing staging laparoscopy (S-LPS) before receiving PDS (n = 555) were prospectively collected in an electronic database and retrospectively analyzed. Major complications were defined as levels 3 to 5 of MSKCC classification. On the basis of a multivariate regression model, the score was developed using a random two-thirds of the population (n = 370) and was validated on the remaining one-third patients (n = 185). Results Major complication rate was 18.3% (102/555). Significant predictors included in the scoring system were: poor performance status, presence of ascites (> 500 cm3), CA125 serum level (> 1000 U/ml), and high laparoscopic tumor load (predictive index value, PIV ≥ 8). The mean risk of developing major postoperative complications was 3.7% in patients with score 0 to 2, 13.2% in patients with score 3 to 5, 37.1% in patients with score 6 to 8. In the validation population, the predicted risk of major complications was 17.8% (33/185) versus a 16.7% (31/185) observed risk (C-statistic index = 0.790). Conclusion This new score may accurately predict a patient's postoperative outcome. Early identification of high-risk patients could help the surgeon to adopt tailored strategies on individual basis.
Lingua originaleEnglish
pagine (da-a)19-24
Numero di pagine6
RivistaGynecologic Oncology
Volume142
DOI
Stato di pubblicazionePubblicato - 2016

Keywords

  • Laparoscopy
  • Obstetrics and Gynecology
  • Oncology
  • Ovarian cancer
  • Post-operative complications
  • Predictive model

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