scholarly journals Bevacizumab improves overall survival in platinum refractory ovarian cancer patients: A retrospective study

2018 ◽  
Vol 57 (6) ◽  
pp. 819-824 ◽  
Author(s):  
Kenro Chikazawa ◽  
Sachiho Netsu ◽  
Tomoyuki Kuwata ◽  
Ryo Konno
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Retrospective Study ◽  
Cancer Patients ◽  
Platinum Refractory

scholarly journals Effects of neoadjuvant chemotherapy in ovarian cancer patients with different germline BRCA1/2 mutational status: A retrospective study

2021 ◽  
Author(s):  
Mengdi Fu ◽  
Chengjuan Jin ◽  
Jingying Chen ◽  
Shuai Feng ◽  
Lekai Nie ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Retrospective Study ◽  
Neoadjuvant Chemotherapy ◽  
Cancer Patients ◽  
Cancer Susceptibility ◽  
Debulking Surgery ◽  
Cancer Susceptibility Genes ◽  
Gynecology And Obstetrics ◽  
Mutational Status

Abstract Background Whether neoadjuvant chemotherapy (NAC) followed by interval debulking surgery (IDS) against primary debulking surgery (PDS) has a differential effect on prognosis due to Breast Cancer Susceptibility Genes (BRCA)1/2 mutations has not been confirmed by current studies. Methods All patients included in this retrospective study were admitted to Qilu Hospital of Shandong University between January 2009 and June 2020, and germline BRCA1/2 mutation were tested. Patients in stage IIIB, IIIC, and IV, re-staged by International Federation of Gynecology and Obstetrics (FIGO) 2014, were selected for analysis. All patients with NAC received 1–3 cycles of platinum-containing (carboplatin, cisplatin, or nedaplatin) chemotherapy. Patients who received maintenance therapy after chemotherapy were not eligible for this study. All relevant medical records were collected. Results A total of 308 patients were enrolled in the study, including 108 patients with BRCA1/2 mutations (BRCAmut), and 200 patients with BRCA1/2 wild-type (BRCAwt). In the two groups, 36 BRCAmut patients (33.3%) and 59 BRCAwt patients (29.5%) received neoadjuvant chemotherapy. The progression-free survival (PFS) of BRCAmut patients was significantly reduced after NAC (median: 15.0 vs. 19.0 months, HR = 0.59; p = 0.03); however, there was no statistical difference in overall survival (OS) (median: 75.1 vs. 68.5 months, HR = 0.90; p = 0.72). Whether BRCAwt patients received NAC had no significant effect on PFS (median: 13.5 vs. 14.6 months, HR = 1.02; p = 0.90) or OS (median: 54.0 vs. 56.4 months, HR = 1.23; p = 0.34). Multivariate analyses showed that the independent predictors of prolonged survival were PDS (p = 0.003), the absence of residual tumor after surgery (p = 0.010), and FIGO III stage (p = 0.011). Conclusions For advanced-stage ovarian cancer patients treated with NAC followed by IDS, PFS and OS were not significantly affected in BRCAwt patients. In BRCAmut patients, NAC-IDS resulted in a shortened PFS, but had no further effect on overall survival.

scholarly journals Potential Prognostic Immune Biomarkers of Overall Survival in Ovarian Cancer Through Comprehensive Bioinformatics Analysis: A Novel Artificial Intelligence Survival Prediction System

2021 ◽  
Vol 8 ◽  
Author(s):  
Tingshan He ◽  
Liwen Huang ◽  
Jing Li ◽  
Peng Wang ◽  
Zhiqiao Zhang
Keyword(s):  
Artificial Intelligence ◽  
Ovarian Cancer ◽  
Overall Survival ◽  
Transcription Factors ◽  
Cancer Patients ◽  
Prognostic Model ◽  
Cox Regression ◽  
Differentially Expressed ◽  
Immune Genes ◽  
Immune Biomarkers

Background: The tumour immune microenvironment plays an important role in the biological mechanisms of tumorigenesis and progression. Artificial intelligence medicine studies based on big data and advanced algorithms are helpful for improving the accuracy of prediction models of tumour prognosis. The current research aims to explore potential prognostic immune biomarkers and develop a predictive model for the overall survival of ovarian cancer (OC) based on artificial intelligence algorithms.Methods: Differential expression analyses were performed between normal tissues and tumour tissues. Potential prognostic biomarkers were identified using univariate Cox regression. An immune regulatory network was constructed of prognostic immune genes and their highly related transcription factors. Multivariate Cox regression was used to identify potential independent prognostic immune factors and develop a prognostic model for ovarian cancer patients. Three artificial intelligence algorithms, random survival forest, multitask logistic regression, and Cox survival regression, were used to develop a novel artificial intelligence survival prediction system.Results: The current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes between tumour samples and normal samples. Further univariate Cox regression identified 84 prognostic immune gene biomarkers for ovarian cancer patients in the model dataset (GSE32062 dataset and GSE53963 dataset). An immune regulatory network was constructed involving 63 immune genes and 5 transcription factors. Fourteen immune genes (PSMB9, FOXJ1, IFT57, MAL, ANXA4, CTSH, SCRN1, MIF, LTBR, CTSD, KIFAP3, PSMB8, HSPA5, and LTN1) were recognised as independent risk factors by multivariate Cox analyses. Kaplan-Meier survival curves showed that these 14 prognostic immune genes were closely related to the prognosis of ovarian cancer patients. A prognostic nomogram was developed by using these 14 prognostic immune genes. The concordance indexes were 0.760, 0.733, and 0.765 for 1-, 3-, and 5-year overall survival, respectively. This prognostic model could differentiate high-risk patients with poor overall survival from low-risk patients. According to three artificial intelligence algorithms, the current study developed an artificial intelligence survival predictive system that could provide three individual mortality risk curves for ovarian cancer.Conclusion: In conclusion, the current study identified 1,307 differentially expressed genes and 337 differentially expressed immune genes in ovarian cancer patients. Multivariate Cox analyses identified fourteen prognostic immune biomarkers for ovarian cancer. The current study constructed an immune regulatory network involving 63 immune genes and 5 transcription factors, revealing potential regulatory associations among immune genes and transcription factors. The current study developed a prognostic model to predict the prognosis of ovarian cancer patients. The current study further developed two artificial intelligence predictive tools for ovarian cancer, which are available at https://zhangzhiqiao8.shinyapps.io/Smart_Cancer_Survival_Predictive_System_17_OC_F1001/ and https://zhangzhiqiao8.shinyapps.io/Gene_Survival_Subgroup_Analysis_17_OC_F1001/. An artificial intelligence survival predictive system could help improve individualised treatment decision-making.

Impact of pleural effusion in ovarian cancer: A retrospective study in Lleida, Spain.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e17534-e17534
Author(s):  
Eleonor Paola Murata ◽  
Silvia Bielsa ◽  
Marina Pardina ◽  
Antonieta Salud Salvia ◽  
Laura Porcel ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Retrospective Study ◽  
Pleural Effusion ◽  
Median Overall Survival ◽  
Serous Carcinoma ◽  
Stage Iiic ◽  
Disease Evolution ◽  
Medical Reports ◽  
Stage Ivb

e17534 Background: The presence of pleural effusion in the evolution of patients with ovarian cancer is not uncommon. In one series of 123 patients, malignant pleural effusion at the diagnoses was observed in 29%, and 70% during the course of the disease. Methods: This observational, retrospective study included patients with ovarian cancer and pleural effusion between July 2007 and December 2019 in Lleida, province of Catalonia, Spain. Data were collected from electronic medical reports. This study analyzed the clinical features of ovarian cancer patients with pleural effusion and its impact on their survival. Results: Data from 189 patients with ovarian cancer were collected. The median age was 63 years old. Pleural effusion was observed in 81 patients, 55 at the diagnosis and 26 in the disease evolution. Fifty five percent were confirmed as malignant etiology. Most of the patients were diagnosed with an advanced stage (38.3% stage IIIC, 12.3% stage IVA, 40.7% stage IVB), and 74.1% were high-grade serous carcinoma. When the pleural effusion was observed at the diagnosis, the median overall survival was 20.8 vs 69.3 months in the absence of it (p < 0.001). When the pleural effusion was observed at any time of the disease, the median overall survival was 26.7 vs 90.4 months without it (p < 0.001). Conclusions: In this study, patients with ovarian cancer and pleural effusion, at diagnosis or in the course of the disease, experienced reduced survival compared with the absence of it.

Determination of Both TP53 Mutation Status and the Amount of p53 Protein Has Limited Diagnostic Importance for Patients with Ovarian Cancer

2022 ◽  
Vol 29 ◽  
Author(s):  
Sebastian M. Klein ◽  
Maria Bozko ◽  
Astrid Toennießen ◽  
Nisar P. Malek ◽  
Przemyslaw Bozko
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Tp53 Mutation ◽  
P53 Protein ◽  
Mutation Status ◽  
Tumor Tissues ◽  
Tp53 Status ◽  
Diagnostic Importance

Background: Ovarian cancer is one of the most aggressive types of gynecologic cancers. Many patients have a relapse within two years after diagnosis and subsequent therapy. Among different genetic changes generally believed to be important for the development of cancer, TP53 is the most common mutation in the case of ovarian tumors. Objective: Our work aims to compare the outcomes of different comparisons based on the overall survival of ovarian cancer patients, determination of TP53 status, and amount of p53 protein in tumor tissues. Methods: We analyzed and compared a collective of 436 ovarian patient’s data. Extracted data include TP53 mutation status, p53 protein level, and information on the overall survival. Values for p53 protein level in dependence of TP53 mutation status were compared using the Independent-Samples t-Test. Survival analyses were displayed by Kaplan-Meier plots, using the log-rank test to check for statistical significance. Results: We have not found any statistically significant correlations between determination of TP53 status, amount of p53 protein in tumor tissues, and overall survival of ovarian cancer patients. Conclusion: In ovarian tumors both determination of TP53 status as well as p53 protein amount has only limited diagnostic importance.

scholarly journals A descriptive report of outcomes of primary mucinous ovarian cancer patients receiving either an adjuvant gynecologic or gastrointestinal chemotherapy regimen

2019 ◽  
Vol 29 (5) ◽  
pp. 904-909
Author(s):  
Brooke A Schlappe ◽  
Qin C Zhou ◽  
Roisin O'Cearbhaill ◽  
Alexia Iasonos ◽  
Robert A Soslow ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Progression Free Survival ◽  
Categorical Variables ◽  
Continuous Variables ◽  
Free Survival ◽  
Exact Test ◽  
Clinical Criteria ◽  
Kaplan Meier

ObjectiveWe described progression-free survival and overall survival in patients with primary mucinous ovarian cancer receiving adjuvant gynecologic versus gastrointestinal chemotherapy regimens.MethodsWe identified all primary mucinous ovarian cancer patients receiving adjuvant gynecologic or gastrointestinal chemotherapy regimens at a single institution from 1994 to 2016. Gynecologic pathologists using strict pathologic/clinical criteria determined diagnosis. Adjuvant therapy was coded as gynecologic or gastrointestinal based on standard agents and schedules. Clinical/pathologic/treatment characteristics were recorded. Wilcoxon rank-sum test was used for continuous variables, and Fisher’s exact test for categorical variables. Progression-free and overall survival were calculated using the Kaplan-Meier method, applying landmark analysis.ResultsOf 62 patients identified, 21 received adjuvant chemotherapy: 12 gynecologic, 9 gastrointestinal. Median age (in years) at diagnosis: 58 (range 25–68) gynecologic cohort, 38 (range 32–68) gastrointestinal cohort (p=0.13). Median body mass index at first post-operative visit: 25 kg/m2(range 18–31) gynecologic cohort, 23 kg/m2(range 18–31) gastrointestinal cohort (p=0.23). History of smoking: 6/12 (50%) gynecologic cohort, 3/9 (33%) gastrointestinal cohort (p=0.66). Stage distribution in gynecologic and gastrointestinal cohorts, respectively: stage I: 9/12 (75%) and 3/9 (33%); stage II: 2/12 (17%) and 1/9 (11%); stage III: 1/12 (8%) and 5/9 (56%) (p=0.06). Grade distribution in gynecologic and gastrointestinal cohorts, respectively: grade 1: 8/12 (67%) and 1/9 (13%); grade 2/3: 4/12 (33%) and 7/9 (88%) (p=0.03). Three-year progression-free survival: 90.9% (95% CI 50.8% to 98.7 %) gynecologic, 53.3% (95% CI 17.7% to 79.6%) gastrointestinal. Three-year overall survival: 90.9% (95% CI 50.8% to 98.7%) gynecologic, 76.2% (95% CI 33.2% to 93.5%) gastrointestinal.ConclusionOngoing international collaborative research may further define associations between chemotherapy regimens and survival.

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