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Gu B, Xia L, Ge H, Liu S. Preoperative PET/CT score can predict complete resection in advanced epithelial ovarian cancer: a prospective study. Quant Imaging Med Surg 2020; 10:743-753. [PMID: 32269933 DOI: 10.21037/qims.2020.02.19] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
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 AUCPET, AUCEisenkop, and AUCPCI 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.
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Affiliation(s)
- Bingxin Gu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Center for Biomedical Imaging, Fudan University, Shanghai 200032, China.,Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai 200032, China
| | - Lingfang Xia
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Gynecological Oncology, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Huijuan Ge
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Shuai Liu
- Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.,Center for Biomedical Imaging, Fudan University, Shanghai 200032, China.,Shanghai Engineering Research Center of Molecular Imaging Probes, Shanghai 200032, China
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Lin W, Li Z. Blueberries inhibit cyclooxygenase-1 and cyclooxygenase-2 activity in human epithelial ovarian cancer. Oncol Lett 2017; 13:4897-4904. [PMID: 28599493 DOI: 10.3892/ol.2017.6094] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Accepted: 10/19/2016] [Indexed: 11/06/2022] Open
Abstract
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.
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Affiliation(s)
- Wumei Lin
- Department of Gynecology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, P.R. China
| | - Zhigang Li
- Department of Gynecology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong 510080, P.R. China
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Eo W, Kim HB, Lee YJ, Suh DS, Kim KH, Kim H. Preoperative Lymphocyte-Monocyte Ratio Is a Predictor of Suboptimal Cytoreduction in Stage III-IV Epithelial Ovarian Cancer. J Cancer 2016; 7:1772-1779. [PMID: 27698915 PMCID: PMC5039359 DOI: 10.7150/jca.15724] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2016] [Accepted: 06/29/2016] [Indexed: 12/29/2022] Open
Abstract
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.
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Affiliation(s)
- Wankyu Eo
- Department of Internal Medicine, College of Medicine, Kyung Hee University, Seoul, Korea
| | - Hong-Bae Kim
- Department of Obstetrics and Gynecology, Kangnam Sacred Heart Hospital, Hallym University Medical Center, Hallym University College of Medicine, Seoul, Korea
| | - Yong Joo Lee
- Department of Medicine, Pusan National University Graduate School
| | - Dong Soo Suh
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine; Biomedical Research Institute, Pusan National University Hospital, Busan, Korea
| | - Ki Hyung Kim
- Department of Obstetrics and Gynecology, Pusan National University School of Medicine; Biomedical Research Institute, Pusan National University Hospital, Busan, Korea
| | - Heungyeol Kim
- Department of Obstetrics and Gynecology, College of Medicine, Kosin University, Busan, Korea
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Shim SH, Lee SJ, Kim SO, Kim SN, Kim DY, Lee JJ, Kim JH, Kim YM, Kim YT, Nam JH. Nomogram for predicting incomplete cytoreduction in advanced ovarian cancer patients. Gynecol Oncol 2014; 136:30-6. [PMID: 25448457 DOI: 10.1016/j.ygyno.2014.11.004] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2014] [Revised: 10/31/2014] [Accepted: 11/02/2014] [Indexed: 11/19/2022]
Abstract
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.
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Affiliation(s)
- Seung-Hyuk Shim
- Department of Obstetrics and Gynecology, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Sun Joo Lee
- Department of Obstetrics and Gynecology, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Seon-Ok Kim
- Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Soo-Nyung Kim
- Department of Obstetrics and Gynecology, Konkuk University School of Medicine, Seoul, Republic of Korea
| | - Dae-Yeon Kim
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
| | - Jong Jin Lee
- Department of Nuclear Medicine, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jong-Hyeok Kim
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Yong-Man Kim
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Young-Tak Kim
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Joo-Hyun Nam
- Department of Obstetrics and Gynecology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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