A laparoscopy-based score to predict surgical outcome in patients with advanced ovarian carcinoma: a pilot study

Abstract

Background: Our objective was to set up a more objective quantitative laparoscopy-based model in predicting the chances of optimal cytoreductive surgery in advanced ovarian cancer patients.

Methods: Sixty-four advanced ovarian cancer patients were submitted to both laparoscopy and standard longitudinal laparotomy sequentially, to define the chances of optimal debulking surgery (residual disease < or = 1 cm). Three patients could not be evaluated by laparoscopy because of the presence of multiple and tenacious adherences. Sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy were calculated for each laparoscopic parameter. On the basis of the statistical probability of each factor to predict surgical outcome, seven laparoscopic features were selected for inclusion in the final model. Each parameter was assigned a numerical score based on the strength of statistical association, and a total predictive index value was tabulated for each patient. Receiver operating characteristic curve analysis was used to assess the ability of the model to predict surgical outcome.

Results: After debulking surgery, 41 (67.2%) of 61 patients were left with optimal residual disease. The presence of omental cake, peritoneal carcinosis, diaphragmatic carcinosis, mesenteric retraction, bowel and/or stomach infiltration, and liver metastases satisfied the basic inclusion criteria and were assigned a final predictive index value of 2. In the final model, a predictive index score > or = 8 identified patients undergoing suboptimal surgery with a specificity of 100%. The positive predictive value was 100%, and the negative predictive value was 70%.

Conclusions: The reliability of laparoscopy in assessing the chance of optimal cytoreduction can be improved by using a simple scoring system.