Preoperative fluorine 18 fluorodeoxyglucose tumoral uptake ratio between upper and lower abdomen in primary advanced-stage ovarian cancer

Preoperative PET/CT score can predict complete resection in advanced epithelial ovarian cancer: a prospective study

Background

To assess the ability of preoperative positron emission tomography/computed tomography (PET/CT) scans to predict postoperative residual disease in advanced epithelial ovarian cancer (AEOC).

Methods

Thirty-one women with suspected AEOC were enrolled in our prospective study before surgery from July 2016 to December 2017. Complete resection was determined as no residual disease (R0) after surgery. A PET/CT scan was obtained within 2 weeks before surgery in our hospital. The PET score was the sum of each score of the radiological criteria from Suidan's model. The correlations between the PET score and tumor burden and surgical complexity were evaluated by Pearson correlation analysis. T-test or Fisher's exact test was used to compare differences in the variables between the complete and incomplete resection groups. Receiver operating characteristic (ROC) curve analysis was performed to assess the accuracy of the PET score for predicting complete postoperative resection.

Results

The median [range] of PET score was 2 [0-8], and the PET score in 20 (65%) patients was less than 3. Complete resection was achieved in 11 (35.5%) patients after surgery, including 10 (90.91%) with low PET scores and only 1 (9.09%) with a high score. The PET score had a significant positive correlation with tumor burden [Eisenkop: r=0.603, P<0.001; peritoneal cancer index (PCI): r=0.522, P=0.003] but not with surgery complexity (Aletti: r=0.291, P=0.113). Patients with lower PET scores (P=0.046) and tumor burdens (Eisenkop: P=0.013; PCI: P=0.012) had higher rates of complete resection. The PET score and tumor burden were effective for predicting complete resection. The AUC_PET, AUC_Eisenkop, and AUC_PCI were 0.797 (95% CI: 0.633-0.961, P=0.01), 0.847 (95% CI: 0.707-0.988, P=0.003), and 0.811 (95% CI: 0.653-0.969, P=0.007), respectively. However, surgery complexity was not useful for assessing complete resection.

Conclusions

The preoperative PET score can noninvasively reflect tumor burden and helps predict complete resection after surgery in AEOC patients.

Blueberries inhibit cyclooxygenase-1 and cyclooxygenase-2 activity in human epithelial ovarian cancer

Ovarian cancer (OC) is the sixth and eighth leading cause of cancer mortality among women in developed and developing countries, respectively. Medical therapy is the main method for the treatment of OC. However, drug toxicity and the marked side effects of chemotherapy limit the usage and therapeutic results of the treatments. Therefore, the identification of multi-target agents with few side effects and high effectiveness is required. Traditional Chinese medicine has been used clinically to treat various types of cancer for thousands of years and is considered to possess multiple components and agents, which exert efficient therapeutic functions with few side effects. Although blueberries have previously been used to treat various types of cancer, the effect on OC and precise molecular mechanism of function of the fruit remains unknown. Cyclooxygenase (COX)-1 and COX-2 have been reported to be the biomarkers of OC. Blueberries may affect the progression of OC by affecting COX levels. To investigate the issue, COX-1 and COX-2 were overexpressed or silenced in ovarian cancer SKOV3 cells. The effect of blueberries on SKOV3 cell viability was determined by an MTT assay. Furthermore, a mouse model for OC was established. The results indicated that blueberries inhibited the proliferation of OC cells by downregulating the levels of COX-1 and COX-2. Blueberry (400 mg daily) consumption reduced tumor size significantly in mice with OC compared with the control without blueberry treatment (P<0.05). The results suggest that blueberries should be used to develop a potential non-pharmaceutical therapy for OC.

Preoperative Lymphocyte-Monocyte Ratio Is a Predictor of Suboptimal Cytoreduction in Stage III-IV Epithelial Ovarian Cancer

Objective: To determine whether the preoperative lymphocyte-monocyte ratio (LMR) is a predictor of suboptimal cytoreduction in advanced-stage epithelial ovarian cancer (EOC).

Methods: Preoperative clinico-pathologic and hematologic parameters were reviewed in a total of 154 patients with EOC submitted to primary cytoreductive surgery. Patients were categorized into two different groups according to the results of cytoreductive surgery: optimal and suboptimal cytoreduction. Continuous variables were categorized into two groups using the best cutoff points selected on the receiver operating characteristic (ROC) curve for suboptimal cytoreduction.

Results: Based on data collected from the 154 patients, 133 (86.4%) and 21 (13.6%) patients presented with stage III and IV disease, respectively. One hundred seventeen (76.0%) patients had serous adenocarcinoma, and 92 (59.7%) had histologic tumor grade 3. The optimal and suboptimal cytoreduction groups included 96 (62.3%) and 58 patients (37.7%), respectively. The best LMR cutoff point for suboptimal cytoreduction was 3.75. On multivariate logistic regression analysis, age, cancer antigen 125, white blood cell count, and LMR were found to be the strongest predictors for suboptimal cytoreduction (P=0.0037, 0.0249, 0.0062, and 0.0015, respectively).

Conclusion: Preoperative LMR is an independent predictor of suboptimal cytoreduction. It provides additional prognostic information beyond the biological parameters of the tumor.

Nomogram for predicting incomplete cytoreduction in advanced ovarian cancer patients

OBJECTIVE

Accurately predicting cytoreducibility in advanced-ovarian cancer is needed to establish preoperative plans, consider neoadjuvant chemotherapy, and improve clinical trial protocols. We aimed to develop a positron-emission tomography/computed tomography-based nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients.

METHODS

Between 2006 and 2012, 343 consecutive advanced-ovarian cancer patients underwent positron-emission tomography/computed tomography before primary cytoreduction: 240 and 103 patients were assigned to the model development or validation cohort, respectively. After reviewing the detailed surgical documentation, incomplete cytoreduction was defined as a remaining gross residual tumor. We evaluated each individual surgeon's surgical aggressiveness index (number of high-complex surgeries/total number of surgeries). Possible predictors, including surgical aggressiveness index and positron-emission tomography/computed tomography features, were analyzed using logistic regression modeling. A nomogram based on this model was developed and externally validated.

RESULTS

Complete cytoreduction was achieved in 120 patients (35%). Surgical aggressiveness index and five positron-emission tomography/computed tomography features were independent predictors of incomplete cytoreduction. Our nomogram predicted incomplete cytoreduction by incorporating these variables and demonstrated good predictive accuracy (concordance index = 0.881; 95% CI = 0.838-0.923). The predictive accuracy of our validation cohort was also good (concordance index = 0.881; 95% CI = 0.790-0.932) and the predicted probability was close to the actual observed outcome. Our model demonstrated good performance across surgeons with varying degrees of surgical aggressiveness.

CONCLUSION

We have developed and validated a nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients which may help stratify patients for clinical trials, establish meticulous preoperative plans, and determine if neoadjuvant chemotherapy is warranted.