scholarly journals Predicting Factors Affecting the First Recurrence of Epithelial Ovarian Cancer Using Random Survival Forest

2021 ◽  
Author(s):  
Maryam Deldar ◽  
Robab Anbiaee ◽  
Kourosh Sayehmiri
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Survival Data ◽  
Prediction Error ◽  
Life Quality ◽  
Metastatic Tumor ◽  
Relative Importance ◽  
Factors Affecting ◽  
First Recurrence ◽  
Random Survival Forest

Predicting survival time has many Effective implications in life quality management for the remainder of the patient's life. Also, survival data are highly variable and make accurate predictions difficult or impossible. Random Survival Forest by repeated tree construction on Bootstrap samples and averaging on the results of these trees reduce the prediction error and cause further generalization of these results. In this retrospective study, the records of 141 patients with epithelial ovarian cancer who were referred to the oncology and radiotherapy ward of Imam Hossein Hospital in Tehran from 2007 to 2018 were used. Random Survival Forest was fitted to the data to investigate the key factors affecting the first recurrence of epithelial ovarian cancer. The mean age of the patients in our study was 52 (23-82) years and the median time to the first recurrence in these was 17 (0.5-127) months, respectively. According to RSF results, using variable importance criterion (VIMP) metastatic tumor with relative importance 2.665 and also using minimal (MD) by depth 2.349, tumor stage with relative importance 1.993 and depth 2.678, and maximum platelet count with relative importance 2.132 and depth 2.683 were the most important variables affecting in the first recurrence of Epithelial Ovarian Cancer. One of the disadvantages of classical methods is the inappropriate fitting of many variables and the need for specific assumptions. More advanced methods such as RSF without the need for any specific assumptions with less prediction error can well explain event variations when exposed to high-dimensional data.

scholarly journals Predicting Epithelial Ovarian Cancer First Recurrence with Random Survival Forest: Comparison Parametric, Semi-Parametric, and Random Survival Forest Methods

2021 ◽  
Author(s):  
Maryam Deldar ◽  
Robab Anbiaee ◽  
Kourosh Sayehmiri
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Prediction Error ◽  
Cox Model ◽  
Brier Score ◽  
Factors Affecting ◽  
Technological Advances ◽  
Weibull Models ◽  
First Recurrence ◽  
Random Survival Forest

Objective: Rapid technological advances in the last century and the large amount of information have made it difficult to analyze a large number of independent variables. In such circumstances, the existence of interactions of different degrees in the model is expected, in this case, the Cox model cannot be useful and the nonparametric method of random survival forest can be a useful alternative. This study compares the prediction error of random survival forest with Cox and Weibull models in predicting the time to the first recurrence in patients with epithelial ovarian cancer. Method: In this retrospective study, the records of patients with epithelial ovarian cancer who referred to Imam Hossein Hospital in Tehran from 2007 to 2018 were used. To investigate the factors affecting the first recurrence of these patients, RSF was fitted to the data. Finally, prediction error of Cox, Weibull and RSF were compared using C-Index and Brier score. Results: Brier score was calculated 0.16 for RSF, and 0.24 for Cox, also C-Index was calculated 0.34 for RSF and 0.42 for Cox. Brier score was calculated 0.092 for Cox and 0.089 for Weibull, so the prediction error of RSF was lower than both Cox and Weibull models. Conclusion: Random survival forest with a suitable fit on many variables and without the need for a special default with a prediction error less than the Weibull and Cox methods can predict the response variable when confronted with high-dimensional data.

scholarly journals Comparison of Cox’s Regression Model and Weibull’ Parametric Model in Evaluating Factors Affecting in First Recurrence of Epithelial Ovarian Cancer

2020 ◽  
Author(s):  
Maryam Deldar ◽  
Robab Anbiaee ◽  
Anahita Jalilian ◽  
Kourosh Sayehmiri ◽  
Shima Azimi
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Cox Regression ◽  
Cancer Recurrence ◽  
Metastatic Tumor ◽  
Tumor Stage ◽  
Weibull Analysis ◽  
Factors Affecting ◽  
Screening Programs ◽  
First Recurrence

Ovarian cancer is one of the most deadly women's gynecological malignancies in the world, and despite the low prevalence, it accounts for about 5% of all cancer deaths in women. Survival analysis is a regression relationship between a set of variables with a specific outcome, which is considered disease survival or recurrence in medical studies. The aim of this study is to determine the important factors in the first recurrence of patients with epithelial ovarian cancer with two statistics methods. In this study, we review medical records of patients with epithelial ovarian cancer who referred to the oncology and radiotherapy department of Imam Hossein Hospital of Tehran from the beginning of 2007 to the end of 2018. Univariate and multivariate Cox regression, as well as the parametric Weibull method, were used to investigate the factors affecting patients' first recurrence. We perform all calculations with Stata Ver14. Of the 141 patients, 58 patients (41%) had a first recurrence during our follow-up. The mean time to the first recurrence was 24.88 months. Univariate Cox regression and univariate Weibull analysis showed that metastatic tumor and tumor stage had highly significant effects in the first recurrence of epithelial ovarian cancer. In multivariate Cox and multivariate Weibull analysis, the metastatic tumor had a significant effect in the first recurrence of epithelial ovarian cancer. One of the causes of ovarian cancer recurrence may be diagnosis happened at late stages. Therefore, screening programs are needed to reduce illness and death from ovarian cancer.

Patterns of Recurrence in Patients Treated With Bevacizumab in the Primary Treatment of Advanced Epithelial Ovarian Cancer

2013 ◽  
Vol 23 (7) ◽  
pp. 1219-1225 ◽  
Author(s):  
Jose Alejandro Rauh-Hain ◽  
Stephanie H. Guseh ◽  
Katharine M. Esselen ◽  
Whitfield B. Growdon ◽  
John O. Schorge ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Primary Treatment ◽  
Categorical Variables ◽  
First Line ◽  
Liver Recurrence ◽  
First Recurrence ◽  
Patterns Of Recurrence ◽  
First Line Treatment ◽  
Registry Database

ObjectiveThe purpose of this study was to compare the distribution of the first site of recurrence in patients with epithelial ovarian cancer (EOC) who received first-line treatment with bevacizumab compared with patients who did not receive bevacizumab.MethodsFrom the Cancer Registry database at our institutions, we identified a group of patients with recurrent EOC who underwent treatment from January 1, 2005, to December 31, 2010. Each patient record was evaluated to classify the site of first recurrence. Correlation between categorical variables was assessed with χ2test.ResultsTwo hundred ninety-two patients with advanced EOC (stage III or IV) who originally responded to chemotherapy and had a recurrence were identified. Of these, 37 (12.5%) had received postoperative chemotherapy bevacizumab, and 255 (87.5%) did not. Compared with those not treated with bevacizumab, there was a lower incidence of liver recurrence (0% vs 9%;P= 0.05) and a higher rate of lung and/or pleural recurrence (22% vs 5%;P= 0.001) and recurrence at distant sites (22% vs 9%;P= 0.03) in patients who received bevacizumab. There was no difference in the incidence of ascites at the time of recurrence between these groups.ConclusionsPatients who received bevacizumab as part of primary treatment for EOC had a higher rate of lung and/or pleural recurrence and a lower rate of liver recurrence. There was no difference in the rate of ascites at the time of recurrence.

Second-line Intraperitoneal Platinum-based Therapy Leads to an Increase in Second-line Progression-free Survival for Epithelial Ovarian Cancer

2016 ◽  
Vol 26 (4) ◽  
pp. 626-631 ◽  
Author(s):  
Michelle M. Boisen ◽  
Jamie L. Lesnock ◽  
Scott D. Richard ◽  
Sushil Beriwal ◽  
Joseph L. Kelley ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Gynecologic Oncology ◽  
Progression Free Survival ◽  
Primary Response ◽  
Published Data ◽  
Second Line ◽  
First Recurrence ◽  
Oncology Practice ◽  
Platinum Chemotherapy

ObjectiveOnly 3% of patients with epithelial ovarian cancer (EOC) have a longer treatment-free interval (TFI) after second-line intravenous (IV) platinum chemotherapy than with frontline IV therapy. We sought to examine what impact second-line combination IV/intraperitoneal (IV/IP) platinum therapy might have on the ratio of second-line to first-line TFI in patients treated with second-line IP platinum chemotherapy for first recurrence after front-line IV therapy.MethodsA retrospective analysis of women who received combination platinum-based IV/IP chemotherapy for recurrent EOC between January 2005 and March 2011 was conducted. Patients were identified from the tumor registry, and office records from a large gynecologic oncology practice and patient records were reviewed. The first and second TFIs were defined as the time from the end of previous platinum-based therapy to the start of next therapy.ResultsTwenty-five women received IV/IP chemotherapy for their first EOC recurrence after IV chemotherapy. In 10 patients (40%), we observed a longer TFI after IV/IP chemotherapy than after primary IV chemotherapy. For these 10 patients, the median TFI for primary response was 22 months (range, 15–28), whereas median TFI after IV/IP chemotherapy for recurrent disease was 37 months (range, 12–61).ConclusionsFor EOC patients with limited peritoneal recurrence, 40% of patients had a second-line IP-platinum TFI that exceeded their frontline IV-platinum TFI compared to published data. These data support the use of IV/IP chemotherapy as a treatment for recurrence.

Do metabolic factors impact time to first recurrence or survival in epithelial ovarian cancer?

2015 ◽  
Vol 139 (3) ◽  
pp. 600
Author(s):  
Christina Tierney ◽  
M. Craig Miller ◽  
Kevin M. Holcomb ◽  
Yue Wu ◽  
Sandeep Raj ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Metabolic Factors ◽  
Impact Time ◽  
First Recurrence

scholarly journals Association of Soluble B7-H4 and Circulating Tumor Cells in Blood of Advanced Epithelial Ovarian Cancer Patients

2021 ◽  
Vol 11 ◽  
Author(s):  
Pawel Mach ◽  
Rainer Kimmig ◽  
Sabine Kasimir-Bauer ◽  
Paul Buderath
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Tumor Cells ◽  
Circulating Tumor Cells ◽  
Survival Data ◽  
Liquid Biopsy ◽  
Therapy Response ◽  
Predictive Biomarkers ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints

IntroductionEpithelial ovarian cancer (EOC) is the deadliest gynecologic malignancy worldwide. Reliable predictive biomarkers are urgently needed to estimate the risk of relapse and to improve treatment management. Soluble immune-checkpoints in EOC are promising molecules serving as prognostic biomarkers accessible via liquid biopsy. We thus, aimed at elucidating the role of sB7-H4 in EOC.Material and MethodsWe analyzed soluble serum B7-H4 (sB7-H4) using ELISA and circulating tumor cells (CTCs) in blood applying the AdnaTest OvarianCancer in 85 patients suffering from advanced EOC. Findings were correlated with clinical parameters as well as survival data.ResultssB7-H4 was detectable in 14.1% patients, CTCs in 32.9% patients and simultaneous presence of CTCs and sB7-H4 was found in 7% patients, respectively. Although no association between sB7-H4 and CTC could be documented, each of them served as independent predictive factors for overall survival (OS).ConclusionsB7-H4 and CTCs are independent prognostic biomarkers for impaired survival in EOC. As they are easily accessible via liquid biopsy, they may be of potential benefit for the prediction of therapy response and survival for EOC patients.

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