Abstract
ObjectiveThe aim of this study is to establish a noninvasive preoperative model for predicting primary optimal cytoreduction in advanced epithelial ovarian cancer by HE4 and CA125 combined with clinicopathological parameters.MethodsClinical data including preoperative serum HE4 and CA125 level of 83 patients with advanced epithelial ovarian cancer were collected. The sensitivity, specificity, positive predictive value, negative predictive value and overall accuracy of each clinical parameter were calculated. The Predictive Index score model and the logistic model were constructed to predict the primary optimal cytoreduction.ResultsOptimal surgical cytoreduction was achieved in 62.65% (52/83) patients. Cutoff values of preoperative serum HE4 and CA125 were 777.10 pmol/L and 313.60 U/ml. (1) Patients with PIV ≥ 6 may not be able to achieve optimal surgical cytoreduction. The diagnostic accuracy, NPV, PPV and specificity for diagnosing suboptimal cytoreduction were 71, 100, 68, and 100%, respectively. (2) The logistic model was: logit p = 0.12 age − 2.38 preoperative serum CA125 level − 1.86 preoperative serum HE4 level-2.74 histological type-3.37. AUC of the logistic model in the validation group was 0.71(95%CI 0.54–0.88, P = 0.025). Sensitivity and specificity were 1.00 and 0.44, respectively.ConclusionAge, preoperative serum CA125 level and preoperative serum HE4 level are important non-invasive predictors of primary optimal surgical cytoreduction in advanced epithelial ovarian cancer. Our PIV and logistic model can be used for assessment before expensive and complex predictive methods including laparoscopy and diagnostic imaging. Further future clinical validation is needed.
Highlights
Ovarian cancer is the most lethal gynecological malignancy
Our predictive index value (PIV) and logistic model can be used for assessment before expensive and complex predictive methods including laparoscopy and diagnostic imaging
Advanced ovarian cancer patients who are older, with increased comorbidities, and with a higher disease burden who cannot achieve primary optimal surgical debulking can obtain the similar overall survival rates and lower postoperative adverse events compared to patients with optimal cytoreduction when they choose
Summary
Ovarian cancer is the most lethal gynecological malignancy. More than 75% of ovarian cancer patients are in stage III-IV at the time of initial diagnosis. Residual lesions after primary surgery remain one of the most important prognostic factors in patients with advanced ovarian cancer [2,3,4,5]. Models predicting the primary optimal surgical debulking are important in guiding the initial treatment of patients with advanced ovarian cancer. Unsatisfactory primary debulking surgery (PDS) does not improve the prognosis, and may increase perioperative morbidity [6, 7]. Advanced ovarian cancer patients who are older, with increased comorbidities, and with a higher disease burden who cannot achieve primary optimal surgical debulking can obtain the similar overall survival rates and lower postoperative adverse events compared to patients with optimal cytoreduction when they choose
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