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Optimizing patient selection for secondary cytoreductive surgery in recurrent endometrial cancer.
Vargiu, Virginia; Rosati, Andrea; Tortorella, Lucia; Giannarelli, Diana; Capozzi, Vito Andrea; Gallotta, Valerio; Gioè, Alessandro; Di Stefano, Ettore; Corrado, Martina; Berretta, Roberto; Cosentino, Francesco; Scambia, Giovanni; Fanfani, Francesco.
Afiliação
  • Vargiu V; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Rosati A; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Tortorella L; Università Cattolica del Sacro Cuore, Rome, Italy.
  • Giannarelli D; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Capozzi VA; Facility of Epidemiology and Biostatistics, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Gallotta V; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Gioè A; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Di Stefano E; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
  • Corrado M; Università Cattolica del Sacro Cuore, Rome, Italy.
  • Berretta R; Università Cattolica del Sacro Cuore, Rome, Italy.
  • Cosentino F; Department of Medicine and Surgery, University of Parma, Parma, Italy.
  • Scambia G; Department of Medicine and Health Sciences "Vincenzo Tiberio", Università degli Studi del Molise, Campobasso, Italy.
  • Fanfani F; Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy.
Int J Gynecol Cancer ; 2024 Jun 14.
Article em En | MEDLINE | ID: mdl-38876787
ABSTRACT

OBJECTIVE:

This retrospective, multicenter, observational study aimed to refine patient selection criteria for secondary cytoreductive surgery in recurrent endometrial cancer. The objective was to identify preoperative predictors of complete cytoreduction, assess surgical complexity, and propose a preoperative predictive scoring system to identify suitable candidates for secondary cytoreductive surgery.

METHODS:

Data from 331 women with recurrent endometrial cancer were analyzed across three Italian centers from January 2010 to December 2021. Patients were categorized based on treatment received (medical treatment, diagnostic laparoscopy/examination under anesthesia, or secondary cytoreductive surgery). Preoperative predictors, surgical complexity, complications, and a predictive scoring system were assessed. Logistic regression and receiver operating characteristic analysis were used for statistical evaluation.

RESULTS:

Of the cohort, 56.2% underwent debulking surgery, 17.2% had diagnostic laparoscopy, and 26.6% received medical treatment. Patients undergoing secondary cytoreductive surgery were younger, with a lower body mass index, better performance status, and fewer comorbidities. Single site locoregional relapse was common in secondary cytoreductive surgery patients. Age <65 years, single site relapse, lymph node, and hematogenous relapse were independent predictors of complete cytoreduction. A predictive scoring system demonstrated a clear relationship between the score and the likelihood of complete cytoreduction.

CONCLUSION:

This study identified age <65 years, single site recurrence, as well as nodal and hematogenous recurrence, as predictive factors for achieving optimal cytoreduction. A predictive scoring system incorporating these factors has been proposed to identify optimal candidates for secondary cytoreductive surgery in recurrent endometrial cancer. The scoring system showed promising predictive accuracy and could aid in refining the decision making process, ensuring appropriate patient selection for secondary cytoreductive surgery. Further prospective studies are warranted to validate and enhance the predictive model.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article