Literature DB >> 27103179

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

G Vizzielli1, B Costantini2, L Tortorella2, I Pitruzzella3, V Gallotta2, F Fanfani4, S Gueli Alletti2, F Cosentino2, C Nero2, G Scambia2, A Fagotti5.   

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 (>500cm(3)), CA125 serum level (>1000U/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.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Laparoscopy; Ovarian cancer; Post-operative complications; Predictive model

Mesh:

Year:  2016        PMID: 27103179     DOI: 10.1016/j.ygyno.2016.04.020

Source DB:  PubMed          Journal:  Gynecol Oncol        ISSN: 0090-8258            Impact factor:   5.482


  10 in total

1.  Clinical Impact of a Surgical Energy Device in Advanced Ovarian Cancer Surgery Including Bowel Resection.

Authors:  Giuseppe Vizzielli; Carmine Conte; Massimo Romano; Anna Fagotti; Barbara Costantini; Claudio Lodoli; Salvatore Gueli Alletti; Khaled Gaballah; Fabio Pacelli; Alfredo Ercoli; Giovanni Scambia; Valerio Gallotta
Journal:  In Vivo       Date:  2018 Mar-Apr       Impact factor: 2.155

2.  Comparison of Survival Between Primary Debulking Surgery Versus Neoadjuvant Chemotherapy for Ovarian Cancers in a Personalized Treatment Cohort.

Authors:  Zheng Feng; Hao Wen; Ruimin Li; Shuai Liu; Yi Fu; Xiaojun Chen; Rui Bi; Xingzhu Ju; Xiaohua Wu
Journal:  Front Oncol       Date:  2021-02-10       Impact factor: 6.244

3.  RE: Pattern of and reason for postoperative residual disease in patients with advanced ovarian cancer following upfront radical debulking surgery.

Authors:  A Fagotti; G Vizzielli; M Petrillo; G Scambia
Journal:  Gynecol Oncol Rep       Date:  2016-11-10

4.  Predictive model for major complications after extensive abdominal surgery in primary advanced ovarian cancer.

Authors:  Antoni Llueca; Anna Serra; Karina Maiocchi; Katty Delgado; Rosa Jativa; Luis Gomez; Javier Escrig
Journal:  Int J Womens Health       Date:  2019-03-07

5.  Trends in bacterial resistance among perioperative infections in patients with primary ovarian cancer: A retrospective 20-year study at an affiliated hospital in South China.

Authors:  Yanlin Zhou; Tingting Zhang
Journal:  J Int Med Res       Date:  2020-06       Impact factor: 1.671

6.  A Prediction Model for Optimal Primary Debulking Surgery Based on Preoperative Computed Tomography Scans and Clinical Factors in Patients With Advanced Ovarian Cancer: A Multicenter Retrospective Cohort Study.

Authors:  Yu Gu; Meng Qin; Ying Jin; Jing Zuo; Ning Li; Ce Bian; Yu Zhang; Rong Li; Yu-Mei Wu; Chun-Yan Wang; Ke-Qiang Zhang; Ying Yue; Ling-Ying Wu; Ling-Ya Pan
Journal:  Front Oncol       Date:  2021-01-07       Impact factor: 6.244

Review 7.  The Role of Artificial Intelligence in Managing Multimorbidity and Cancer.

Authors:  Alfredo Cesario; Marika D'Oria; Riccardo Calvani; Anna Picca; Antonella Pietragalla; Domenica Lorusso; Gennaro Daniele; Franziska Michaela Lohmeyer; Luca Boldrini; Vincenzo Valentini; Roberto Bernabei; Charles Auffray; Giovanni Scambia
Journal:  J Pers Med       Date:  2021-04-19

8.  A Practical Nomogram to Predict Early Death in Advanced Epithelial Ovarian Cancer.

Authors:  Zixuan Song; Yangzi Zhou; Xue Bai; Dandan Zhang
Journal:  Front Oncol       Date:  2021-03-19       Impact factor: 6.244

9.  Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

Authors:  Camilla Nero; Luca Boldrini; Jacopo Lenkowicz; Maria Teresa Giudice; Alessia Piermattei; Frediano Inzani; Tina Pasciuto; Angelo Minucci; Anna Fagotti; Gianfranco Zannoni; Vincenzo Valentini; Giovanni Scambia
Journal:  Int J Mol Sci       Date:  2022-09-26       Impact factor: 6.208

10.  Surgical risk assessment for gynecological oncologic patients.

Authors:  Çağlayan Biçer; Jalal Raoufi; Serhan Can İşcan; Mehmet Güney; Evrim Erdemoğlu
Journal:  Turk J Obstet Gynecol       Date:  2019-10-10
  10 in total

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