Materiały źródłowe

• #1

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Ovarian cancer is the eighth most common cancer among women, accounting for 4.7% of all cancer-related deaths. […] Some established prognostic factors are clinical, such as age, ECOG, and Body Mass Index. Histological subtype, stage and grade are also prognostic factors, and optimal surgery is one of the main factors. Furthermore, the presence of ascites at diagnosis and cancer Antigen 125 assessment could help to predict patient outcomes. Nevertheless, median survival is less than 5 years. […] Despite the poor prognosis in this pathology, some patients are still alive 10 years after diagnosis. A better understanding of this populations characteristics could help to anticipate patient outcomes and thus adapt their management. […] The amount of residual disease after cytoreductive surgery plays a critical role in patients prognosis. Even minimal residual disease is associated with significantly reduced overall survival, optimal surgery (no macroscopic residual disease), also characterized by the completeness of cytoreduction score of 0 (CC-0), is widely recognized as associated with a good prognostic factor in EOCs.

• #2 DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315924

  Ovarian cancer is a malignant tumor with different clinicopathological and molecular characteristics. Due to its nonspecific early symptoms, the majority of patients are diagnosed with local or extensive metastasis, severely affecting treatment and prognosis. […] Integrating multiple types of omics data aids in predicting the survival rate of ovarian cancer patients. […] Experimental results demonstrate that compared to existing methods, the DFASGCNS model exhibits significant advantages in ovarian cancer prognosis prediction and survival analysis. Kaplan-Meier curve analysis results indicate significant differences in the survival subgroups predicted by the DFASGCNS model, contributing to a deeper understanding of the pathogenesis of ovarian cancer and providing more reliable auxiliary diagnostic information for the prognosis assessment of ovarian cancer patients.

• #3 Tumour gene test could help to predict ovarian cancer prognosis

  https://www.unsw.edu.au/newsroom/news/2020/08/tumour-gene-test-could-help-to-predict-ovarian-cancer-prognosis

  A global team of medical researchers led by UNSW have developed a test that could help to predict survival for women diagnosed with ovarian cancer, and pave the way towards personalised treatment. […] A tumour test could help to identify ovarian cancer patients with predicted poor survival, and down the track inform new therapeutical approaches, the results of a major international collaboration have shown. […] Ovarian cancer is the eighth most commonly occurring cancer in women, with nearly 300,000 global new cases in 2018. […] We conducted an analysis of 3769 tumour samples from women with ovarian cancer and found we were able to reliably use a piece of tumour to determine how good a womans survival chances would be five years after diagnosis, says lead author Professor Susan Ramus from UNSW Medicine.

• #4 :: JGO :: Journal of Gynecologic Oncology

  https://ejgo.org/DOIx.php?id=10.3802/jgo.2021.32.e18

  Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients. The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p0.001) had higher OVRS than those without. OVRS 10 (hazard ratio=3.29; 95% confidence interval=1.945.58; p0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. 60 months) of patients with OVRS 10 were significantly shorter than those of patients with OVRS 10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046). Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer. The overall 5-year relative survival rate generally ranges between 30%40% worldwide and has seen only very modest increases (2%4%) since the 1990s. More than 75% of affected patients are diagnosed at an advanced stage (stages III and IV). Early diagnosis of EOC is difficult due to the lack of obvious initial symptoms and accurate biomarkers: ovarian cancer patients are usually diagnosed at an advanced stage and have a poor prognosis. The 5-year survival rate was around 80% for patients with early stage EOCs (stages I and II), but less than 30% for those with advanced stage (stages III and IV) disease. Patients with refractory disease or recurrence within 6 months of cessation of chemotherapy (chemotherapy resistance) had poor prognosis and short expected survival, usually 12 months. Currently known factors affecting prognosis in ovarian cancer include cancer stage, histological type, tumor grade, residual tumor size after surgery, and chemosensitivity or chemoresistance. However, these factors present an incomplete picture of the tumor biology and are frequently interrelated. The OVRS was validated using the TCGA database of ovarian cancer patients. Our results found that patients with high OVRS were chemoresistant, and worse prognosis. Therefore, the OVRS can be a useful biomarker to predict chemoresistance and outcomes of epithelial ovarian carcinoma patients. The OVRS has excellent correlation with chemoresistance and outcome for both our studied cohort and the patients in the TCGA database. Therefore, the OVRS can serve as a useful biomarker in clinically predicting the chemoresistance and outcomes of EOC patients.

• #5 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  If you have ovarian cancer, you may have questions about your prognosis. The prognosis is the doctors best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type, grade, stage and other features of your cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis. […] Stage is the most important prognostic factor for most types of ovarian cancer. Women diagnosed with early stage ovarian cancer have a better prognosis than women diagnosed with cancer at a later stage. […] The grade of the tumour is an important prognostic factor for ovarian cancer. Low-grade tumours are associated with a better prognosis than high-grade tumours.

• #6

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Ovarian cancer is the eighth most common cancer among women, accounting for 4.7% of all cancer-related deaths. […] Some established prognostic factors are clinical, such as age, ECOG, and Body Mass Index. Histological subtype, stage and grade are also prognostic factors, and optimal surgery is one of the main factors. Furthermore, the presence of ascites at diagnosis and cancer Antigen 125 assessment could help to predict patient outcomes. Nevertheless, median survival is less than 5 years. […] Despite the poor prognosis in this pathology, some patients are still alive 10 years after diagnosis. A better understanding of this populations characteristics could help to anticipate patient outcomes and thus adapt their management. […] The amount of residual disease after cytoreductive surgery plays a critical role in patients prognosis. Even minimal residual disease is associated with significantly reduced overall survival, optimal surgery (no macroscopic residual disease), also characterized by the completeness of cytoreduction score of 0 (CC-0), is widely recognized as associated with a good prognostic factor in EOCs.

• #7 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  If you have ovarian cancer, you may have questions about your prognosis. The prognosis is the doctors best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type, grade, stage and other features of your cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis. […] Stage is the most important prognostic factor for most types of ovarian cancer. Women diagnosed with early stage ovarian cancer have a better prognosis than women diagnosed with cancer at a later stage. […] The grade of the tumour is an important prognostic factor for ovarian cancer. Low-grade tumours are associated with a better prognosis than high-grade tumours.

• #8 :: JGO :: Journal of Gynecologic Oncology

  https://ejgo.org/DOIx.php?id=10.3802/jgo.2021.32.e18

  Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients. The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p0.001) had higher OVRS than those without. OVRS 10 (hazard ratio=3.29; 95% confidence interval=1.945.58; p0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. 60 months) of patients with OVRS 10 were significantly shorter than those of patients with OVRS 10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046). Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer. The overall 5-year relative survival rate generally ranges between 30%40% worldwide and has seen only very modest increases (2%4%) since the 1990s. More than 75% of affected patients are diagnosed at an advanced stage (stages III and IV). Early diagnosis of EOC is difficult due to the lack of obvious initial symptoms and accurate biomarkers: ovarian cancer patients are usually diagnosed at an advanced stage and have a poor prognosis. The 5-year survival rate was around 80% for patients with early stage EOCs (stages I and II), but less than 30% for those with advanced stage (stages III and IV) disease. Patients with refractory disease or recurrence within 6 months of cessation of chemotherapy (chemotherapy resistance) had poor prognosis and short expected survival, usually 12 months. Currently known factors affecting prognosis in ovarian cancer include cancer stage, histological type, tumor grade, residual tumor size after surgery, and chemosensitivity or chemoresistance. However, these factors present an incomplete picture of the tumor biology and are frequently interrelated. The OVRS was validated using the TCGA database of ovarian cancer patients. Our results found that patients with high OVRS were chemoresistant, and worse prognosis. Therefore, the OVRS can be a useful biomarker to predict chemoresistance and outcomes of epithelial ovarian carcinoma patients. The OVRS has excellent correlation with chemoresistance and outcome for both our studied cohort and the patients in the TCGA database. Therefore, the OVRS can serve as a useful biomarker in clinically predicting the chemoresistance and outcomes of EOC patients.

• #9 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  If you have ovarian cancer, you may have questions about your prognosis. The prognosis is the doctors best estimate of how cancer will affect someone and how it will respond to treatment. Prognosis and survival depend on many factors. Only a doctor familiar with your medical history, the type, grade, stage and other features of your cancer, the treatments chosen and the response to treatment can put all of this information together with survival statistics to arrive at a prognosis. […] Stage is the most important prognostic factor for most types of ovarian cancer. Women diagnosed with early stage ovarian cancer have a better prognosis than women diagnosed with cancer at a later stage. […] The grade of the tumour is an important prognostic factor for ovarian cancer. Low-grade tumours are associated with a better prognosis than high-grade tumours.

• #10 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #11 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  Maximal-effort debulking surgery is the recommended approach for advanced-stage ovarian cancer. […] The outcomes of surgical treatment of ovarian cancer are divided into three prognostic groups based on the residual disease: (1) complete cytoreduction without macroscopic disease; (2) optimal cytoreduction with residual macroscopic disease up to 1 cm; and (3) suboptimal cytoreduction with macroscopic disease greater than 1 cm. […] Residual disease, along with the type of systemic therapy, are the most important prognostic factors that can be influenced by the treating physician. […] The 3-year overall survival for patients according to cytoreduction status was 72.4% (complete resection), 65.8% (residual tumour ≤ 1 cm) and 45.2% (residual tumour > 1cm), respectively, in a combined analysis of three multicentre phase III trials (AGO-OVAR 3, 5, and 7).

• #12 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #13 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #14 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #15

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Ovarian cancer is the eighth most common cancer among women, accounting for 4.7% of all cancer-related deaths. […] Some established prognostic factors are clinical, such as age, ECOG, and Body Mass Index. Histological subtype, stage and grade are also prognostic factors, and optimal surgery is one of the main factors. Furthermore, the presence of ascites at diagnosis and cancer Antigen 125 assessment could help to predict patient outcomes. Nevertheless, median survival is less than 5 years. […] Despite the poor prognosis in this pathology, some patients are still alive 10 years after diagnosis. A better understanding of this populations characteristics could help to anticipate patient outcomes and thus adapt their management. […] The amount of residual disease after cytoreductive surgery plays a critical role in patients prognosis. Even minimal residual disease is associated with significantly reduced overall survival, optimal surgery (no macroscopic residual disease), also characterized by the completeness of cytoreduction score of 0 (CC-0), is widely recognized as associated with a good prognostic factor in EOCs.

• #16

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #17 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  Ovarian cancer is a lethal reproductive tumour affecting women worldwide. The advancement in presentation and occurrence of chemoresistance are the key factors for poor survival among ovarian cancer women. […] Thus, there is a great need to identify biomarkers to predict platinum resistance before enrolment into chemotherapy, which would facilitate individualized targeted therapy for these subgroups of patients to ensure better survival and an improved quality of life and overall outcome. […] Despite the improvement in treatment for ovarian cancer, survival trends remained poor due to chemoresistance and a lack of biomarkers to detect the disease early. […] The heterogeneity of EOC, which consists of several tumour subtypes with greatly divergent clinicopathologic characteristics and behaviour, poses a major challenge to understanding the pathophysiology of the disease. Various patient and tumour parameters, such as age, genetic makeup, and tumour traits including stage, grade, histologic subtype, and chemotherapy sensitivity, therefore, have an impact on the prognosis of ovarian cancer.

• #18 Creation and validation of models to predict response to primary treatment in serous ovarian cancer | Scientific Reports

  https://www.nature.com/articles/s41598-021-85256-9

  Nearly a third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial therapy and have an overall poor prognosis. However, there are no validated tools that accurately predict which patients will not respond. Our objective is to create and validate accurate models of prediction for treatment response in HGSC. […] By integrating clinical and genomic variables, we achieved prediction performances of over 95% in AUC. […] The majority of these patients with suboptimal response to initial treatment (termed non-responders herein) will die from their disease within two years and are typically treated in the second-line setting with alternative therapies that do not contain platinum. […] The performance of these prediction models ranges from 75-85% (measured as the area under the receiver operator curve (AUC)). Adding clinical characteristics to serum markers increases the performance of the model to an AUC of 90%.

• #19 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  The goal of upfront cytoreduction should always be complete resection, especially in mucinous and clear-cell carcinoma where no benefit has been shown for residual disease ≤1 cm. […] However, small residual disease (i.e., ≤1 cm) may be acceptable in low-grade serous carcinoma, and possibly in tumours highly responsive to systemic treatment, such as high-grade serous tubo-ovarian carcinoma. […] In contrast to upfront debulking surgery, patients who underwent neoadjuvant chemotherapy appeared to benefit from subsequent interval debulking surgery only if complete cytoreduction was achieved; a small-volume residual disease at the end of surgery did not improve survival. […] Ovarian cancer is predominantly a peritoneal disease, and therefore its non-resectability is based on the evaluation of abdominal sites critical for cytoreduction (disease location).

• #20 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  The goal of upfront cytoreduction should always be complete resection, especially in mucinous and clear-cell carcinoma where no benefit has been shown for residual disease ≤1 cm. […] However, small residual disease (i.e., ≤1 cm) may be acceptable in low-grade serous carcinoma, and possibly in tumours highly responsive to systemic treatment, such as high-grade serous tubo-ovarian carcinoma. […] In contrast to upfront debulking surgery, patients who underwent neoadjuvant chemotherapy appeared to benefit from subsequent interval debulking surgery only if complete cytoreduction was achieved; a small-volume residual disease at the end of surgery did not improve survival. […] Ovarian cancer is predominantly a peritoneal disease, and therefore its non-resectability is based on the evaluation of abdominal sites critical for cytoreduction (disease location).

• #21 A nomogram based on SEER database | IJWH

  https://www.dovepress.com/a-nomogram-based-on-seer-database-for-predicting-prognosis-in-patients-peer-reviewed-fulltext-article-IJWH

  Mucinous ovarian cancer (MOC) is a rare histological type of EOC. In order to guide the clinical diagnosis and management of MOC patients, we constructed and verified a nomogram for the estimation of overall survival in patients with MOC. […] Cox hazard regression analysis revealed that age, grade, FIGO stage and log odds of positive lymph nodes stage were independent risk factors for patients with MOC. […] The C-index of the nomogram was 0.827 (95% CI: 0.791 0.863) and the areas under the curve (AUC) predicting the 1-, 3- and 5-year survival rate were 0.853 (95% CI: 0.791 0.915), 0.886 (95% CI: 0.852 0.920) and 0.815 (95% CI: 0.766 0.864), respectively. […] Patients with high risk had a poorer prognosis than those with low risk. […] The nomogram was constructed to predict overall survival in patients with MOC, which had the significance for clinical evaluation.

• #22 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  Patients undergo platinum chemotherapy are classified into platinum-sensitive or platinum-resistant according to the time from the end of treatment to the recurrence of the disease (platinum-free interval). Platinum resistance, defined as disease recurrence within 6 months of completion of first-line platinum-based chemotherapy, occurs in approximately 25% of cases and the median progression-free survival (PFS) is only 912 months on average. […] The tumour microenvironment in ovarian cancer tissues is associated with altered protein expression patterns, making it conceivably a site of interest to decipher protein profile patterns and alteration in disease development and treatment intervention. […] The identification of molecular signatures is becoming more important for individualized targeted ovarian cancer treatment. From a therapeutic standpoint, the discovery of biomarkers has a significant role in predicting the results of chemotherapy treatment, which is essential in assisting clinicians in weighing the possibility of chemotherapy resistance and predicting the quality of life after chemotherapy.

• #23

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #24 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #25

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #26 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  This narrative review discusses the relevance of IHC-based biomarkers in predicting chemotherapy resistance and prognosis in ovarian cancer while also outlining the drawbacks of using IHC in clinical practice. […] High levels of VEGF are linked with primary resistance to platinum-based chemotherapy, and the immunohistochemical level of VEGF expression is highly associated with platinum sensitivity and overall patient survival. […] The presence of HNF1-binding sites at numerous OCCC-specific hypomethylated genes further supports this notion. […] The over-expression of HNF-1 was found to be in OCCC subtypes and have been associated with significantly longer PFS and OS. […] In this review, we found that the Ki-67 antigen/MIB-1 antibody immunostaining can be employed as a diagnostic and predictive tool to direct the clinical care of ovarian cancer. Glypican-3, ALDH1A1, TNFR2, STAT3, FOXP3, and TIM3 are increasingly recognised biomarkers to predict chemoresistance in women with ovarian cancer.

• #27 Prediction of ovarian cancer prognosis and response to chemotherapy by a serum-based multiparametric biomarker panel | British Journal of Cancer

  https://www.nature.com/articles/6604630

  Higher values of baseline measures of CA125, KLK5, KLK6, KLK10, B7-H4 and Spondin-2 were all significantly associated with worse overall survival. […] In particular, rc1 of KLK6 significantly predicted time to survival in the univariate Cox regression models (HR=1.77, 95% CI (1.07, 2.95), P=0.028); however, none of the subsequent measurements remained a significant independent predictor in the multivariate model (with the exception of KLK6 rc1/rc2 ratio). […] The unadjusted HRs for progression-free survival are listed in Table 3. Higher values of baseline measures of CA125, KLK5, KLK6, KLK10, KLK11, B7-H4 and Spondin-2 were all significantly associated with worse progression-free survival. […] Notably, thirty-one of the patients included in this study had a baseline serum CA125 concentration that was close to or below the cutoff point of 30Uml1 and remained non-informative (no significant change) over the course of chemotherapy. […] These data suggest that some markers may be superior or complement CA125 for predicting response to chemotherapy treatment.

• #28 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  This narrative review discusses the relevance of IHC-based biomarkers in predicting chemotherapy resistance and prognosis in ovarian cancer while also outlining the drawbacks of using IHC in clinical practice. […] High levels of VEGF are linked with primary resistance to platinum-based chemotherapy, and the immunohistochemical level of VEGF expression is highly associated with platinum sensitivity and overall patient survival. […] The presence of HNF1-binding sites at numerous OCCC-specific hypomethylated genes further supports this notion. […] The over-expression of HNF-1 was found to be in OCCC subtypes and have been associated with significantly longer PFS and OS. […] In this review, we found that the Ki-67 antigen/MIB-1 antibody immunostaining can be employed as a diagnostic and predictive tool to direct the clinical care of ovarian cancer. Glypican-3, ALDH1A1, TNFR2, STAT3, FOXP3, and TIM3 are increasingly recognised biomarkers to predict chemoresistance in women with ovarian cancer.

• #29 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  This narrative review discusses the relevance of IHC-based biomarkers in predicting chemotherapy resistance and prognosis in ovarian cancer while also outlining the drawbacks of using IHC in clinical practice. […] High levels of VEGF are linked with primary resistance to platinum-based chemotherapy, and the immunohistochemical level of VEGF expression is highly associated with platinum sensitivity and overall patient survival. […] The presence of HNF1-binding sites at numerous OCCC-specific hypomethylated genes further supports this notion. […] The over-expression of HNF-1 was found to be in OCCC subtypes and have been associated with significantly longer PFS and OS. […] In this review, we found that the Ki-67 antigen/MIB-1 antibody immunostaining can be employed as a diagnostic and predictive tool to direct the clinical care of ovarian cancer. Glypican-3, ALDH1A1, TNFR2, STAT3, FOXP3, and TIM3 are increasingly recognised biomarkers to predict chemoresistance in women with ovarian cancer.

• #30 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  This narrative review discusses the relevance of IHC-based biomarkers in predicting chemotherapy resistance and prognosis in ovarian cancer while also outlining the drawbacks of using IHC in clinical practice. […] High levels of VEGF are linked with primary resistance to platinum-based chemotherapy, and the immunohistochemical level of VEGF expression is highly associated with platinum sensitivity and overall patient survival. […] The presence of HNF1-binding sites at numerous OCCC-specific hypomethylated genes further supports this notion. […] The over-expression of HNF-1 was found to be in OCCC subtypes and have been associated with significantly longer PFS and OS. […] In this review, we found that the Ki-67 antigen/MIB-1 antibody immunostaining can be employed as a diagnostic and predictive tool to direct the clinical care of ovarian cancer. Glypican-3, ALDH1A1, TNFR2, STAT3, FOXP3, and TIM3 are increasingly recognised biomarkers to predict chemoresistance in women with ovarian cancer.

• #31 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  It was also shown that Chk2, PGD2, and NOTCH 3 are promising biomarkers for the prediction of chemoresistance in HGSOC women. […] Continuous understanding of these molecular mechanisms has the potential to pave the way for the creation of pharmaceutical treatments for cancer that are more precisely targeted.

• #32 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  Patients undergo platinum chemotherapy are classified into platinum-sensitive or platinum-resistant according to the time from the end of treatment to the recurrence of the disease (platinum-free interval). Platinum resistance, defined as disease recurrence within 6 months of completion of first-line platinum-based chemotherapy, occurs in approximately 25% of cases and the median progression-free survival (PFS) is only 912 months on average. […] The tumour microenvironment in ovarian cancer tissues is associated with altered protein expression patterns, making it conceivably a site of interest to decipher protein profile patterns and alteration in disease development and treatment intervention. […] The identification of molecular signatures is becoming more important for individualized targeted ovarian cancer treatment. From a therapeutic standpoint, the discovery of biomarkers has a significant role in predicting the results of chemotherapy treatment, which is essential in assisting clinicians in weighing the possibility of chemotherapy resistance and predicting the quality of life after chemotherapy.

• #33 :: JGO :: Journal of Gynecologic Oncology

  https://ejgo.org/DOIx.php?id=10.3802/jgo.2021.32.e18

  Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients. The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p0.001) had higher OVRS than those without. OVRS 10 (hazard ratio=3.29; 95% confidence interval=1.945.58; p0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. 60 months) of patients with OVRS 10 were significantly shorter than those of patients with OVRS 10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046). Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer. The overall 5-year relative survival rate generally ranges between 30%40% worldwide and has seen only very modest increases (2%4%) since the 1990s. More than 75% of affected patients are diagnosed at an advanced stage (stages III and IV). Early diagnosis of EOC is difficult due to the lack of obvious initial symptoms and accurate biomarkers: ovarian cancer patients are usually diagnosed at an advanced stage and have a poor prognosis. The 5-year survival rate was around 80% for patients with early stage EOCs (stages I and II), but less than 30% for those with advanced stage (stages III and IV) disease. Patients with refractory disease or recurrence within 6 months of cessation of chemotherapy (chemotherapy resistance) had poor prognosis and short expected survival, usually 12 months. Currently known factors affecting prognosis in ovarian cancer include cancer stage, histological type, tumor grade, residual tumor size after surgery, and chemosensitivity or chemoresistance. However, these factors present an incomplete picture of the tumor biology and are frequently interrelated. The OVRS was validated using the TCGA database of ovarian cancer patients. Our results found that patients with high OVRS were chemoresistant, and worse prognosis. Therefore, the OVRS can be a useful biomarker to predict chemoresistance and outcomes of epithelial ovarian carcinoma patients. The OVRS has excellent correlation with chemoresistance and outcome for both our studied cohort and the patients in the TCGA database. Therefore, the OVRS can serve as a useful biomarker in clinically predicting the chemoresistance and outcomes of EOC patients.

• #34 A risk model of gene signatures for predicting platinum response and survival in ovarian cancer | Journal of Ovarian Research | Full Text

  https://ovarianresearch.biomedcentral.com/articles/10.1186/s13048-022-00969-3

  Identification of nonresponders is an important step toward greater life expectancy for OC patients. […] The prognostic value of PS was then evaluated by the Kaplan-Meier survival curve using log-rank test in the training set and then validated in the GSE63885 dataset. […] The expression level of these genes detected by IHC in the FUSCC cohort indicates that PNLDC1 expresses higher in the resistant group, whereas overexpression of the SLC5A1 and SYNM were detected in the sensitive patients. […] The prognosis predicted by the prognostic model is significantly correlated with the prognosis that depends on the platinum response state.

• #35 :: JGO :: Journal of Gynecologic Oncology

  https://ejgo.org/DOIx.php?id=10.3802/jgo.2021.32.e18

  Cytoreductive surgery followed by adjuvant chemotherapy is a standard frontline treatment for epithelial ovarian cancer (EOC). We aimed to develop an ovarian cancer risk score (OVRS) based on the expression of 10 ovarian-cancer-related genes to predict the chemoresistance, and outcomes of EOC patients. The chemosensitive group had lower OVRS than the chemoresistant group (5 vs. 15, p0.001, Mann-Whitney U test). Patients with disease relapse (13 vs. 5, p0.001, Mann-Whitney U test) or disease-related death (13.5 vs. 6, p0.001) had higher OVRS than those without. OVRS 10 (hazard ratio=3.29; 95% confidence interval=1.945.58; p0.001) was the only predictor for chemoresistance in multivariate analysis. The median DFS (5 months vs. 24 months) and OS (39 months vs. 60 months) of patients with OVRS 10 were significantly shorter than those of patients with OVRS 10). The high OVRS group also had significantly shorter median OS than the low OVRS group in 255 patients in the TCGA database (39 vs. 49 months, p=0.046). Specific genes panel can be clinically applied in predicting the chemoresistance and outcome, and decision-making of epithelial ovarian cancer. The overall 5-year relative survival rate generally ranges between 30%40% worldwide and has seen only very modest increases (2%4%) since the 1990s. More than 75% of affected patients are diagnosed at an advanced stage (stages III and IV). Early diagnosis of EOC is difficult due to the lack of obvious initial symptoms and accurate biomarkers: ovarian cancer patients are usually diagnosed at an advanced stage and have a poor prognosis. The 5-year survival rate was around 80% for patients with early stage EOCs (stages I and II), but less than 30% for those with advanced stage (stages III and IV) disease. Patients with refractory disease or recurrence within 6 months of cessation of chemotherapy (chemotherapy resistance) had poor prognosis and short expected survival, usually 12 months. Currently known factors affecting prognosis in ovarian cancer include cancer stage, histological type, tumor grade, residual tumor size after surgery, and chemosensitivity or chemoresistance. However, these factors present an incomplete picture of the tumor biology and are frequently interrelated. The OVRS was validated using the TCGA database of ovarian cancer patients. Our results found that patients with high OVRS were chemoresistant, and worse prognosis. Therefore, the OVRS can be a useful biomarker to predict chemoresistance and outcomes of epithelial ovarian carcinoma patients. The OVRS has excellent correlation with chemoresistance and outcome for both our studied cohort and the patients in the TCGA database. Therefore, the OVRS can serve as a useful biomarker in clinically predicting the chemoresistance and outcomes of EOC patients.

• #36 A risk model of gene signatures for predicting platinum response and survival in ovarian cancer | Journal of Ovarian Research | Full Text

  https://ovarianresearch.biomedcentral.com/articles/10.1186/s13048-022-00969-3

  Ovarian cancer (OC) is the deadliest tumor in the female reproductive tract. And increased resistance to platinum-based chemotherapy represents the major obstacle in the treatment of OC currently. Robust and accurate gene expression models are crucial tools in distinguishing platinum therapy response and evaluating the prognosis of OC patients. […] A 10-gene classifier was constructed which could discriminate platinum-sensitive samples precisely with an AUC of 0.971 in the training set and of 0.926 in the GEO dataset (GSE638855). […] These findings reveal a specific risk model that could serve as effective biomarkers to identify patients platinum response status and predict survival outcomes for OC patients. […] The five-year overall survival rate of epithelial OC patients ranges from 20% at stage IV to 89% at stage I, however, 80% of OC cases can not be diagnosed timely until the tumor has progressed to advanced stages with severe clinical outcomes due to its insidious onset without specific clinical manifestations and the lack of mature early diagnosis methods.

• #37 Prediction of ovarian cancer prognosis and response to chemotherapy by a serum-based multiparametric biomarker panel | British Journal of Cancer

  https://www.nature.com/articles/6604630

  Currently, there are no effective biomarkers for ovarian cancer prognosis or prediction of therapeutic response. […] The levels of several markers at baseline (c0), or after the first chemotherapy cycle (rc1), predicted chemotherapy response and overall or progression-free survival in univariate analysis. […] A multiparametric model (c0 of CA125, KLK5, KLK7 and rc1 of CA125) provided predictive accuracy with area under the ROC curve (AUC) of 0.82 (0.62 after correction for overfitting). […] Another marker combination (c0 of KLK7, KLK10, B7-H4, Spondin-2) was useful in predicting short-term (1-year) survival with an AUC of 0.89 (0.74 after correction for overfitting). […] All markers examined, except KLK7 and regenerating protein IV, were powerful predictors of time to progression (TTP) among chemotherapy responders.

• #38

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  HRD is a predictive biomarker of PARPi response and platin-based CT, with mutation screening conducted at the start of care. […] The KELIM score aims to predict chemosensitivity using a modeled CA125 elimination rate. […] Some patients have been reported to have a long-life expectancy, even exceeding 10 years after diagnosis. […] These statistics warrant a search for reliable predictive factors. […] Even though LTSs often present many known factors for good prognosis, some of them have factors generally described as linked to poor prognosis, such as age over 50, advanced stage and grade or serous histology. […] By monitoring ctDNA as a reliable predictive and prognostic factor, a personalized and more adapted therapeutic strategy could probably be offered to patients with ovarian cancer.

• #39 Ovarian Cancer Staging – Ovarian Cancer Research Alliance

  https://ocrahope.org/for-patients/gynecologic-cancers/ovarian-cancer/ovarian-cancer-staging/

  If you or a loved one is diagnosed with ovarian cancer, questions about treatment and prognosis are natural. Knowing the stages of ovarian cancer and their meanings can help you understand what to expect. […] In order to plan treatment and predict prognosis, a doctor determines a persons cancer stage using the results of diagnostic tests, imaging scans, and samples taken from surgery. […] Generally, ovarian cancer stage refers to its pathological stage (surgical stage), determined by tissue samples surgically removed and biopsied. If surgery is not possible, a clinical stage is assigned based on imaging and physical exams. Subsequent surgical biopsy results can update the pathological stage classification. […] Survival rates vary by cancer stage. Early-stage disease generally has a better prognosis than advanced-stage disease. Survival rates are based on large studies and cannot predict individual outcomes.

• #40 Ovarian Cancer Staging – Ovarian Cancer Research Alliance

  https://ocrahope.org/for-patients/gynecologic-cancers/ovarian-cancer/ovarian-cancer-staging/

  Most women with Stage 1 ovarian cancer have an excellent prognosis, with an average 5-year survival rate of 93%. Survival rates are further determined by type of ovarian cancer. […] Stage 2 ovarian cancer is typically considered to be regional spread, which has a general 5-year relative survival rate of about 74%. […] The average five-year survival rate for Stage 3 ovarian cancer is 41%. […] The average relative 5-year survival rate for those diagnosed with distant spread ovarian cancer, which includes Stage 4 ovarian cancer, is about 31%.

• #41 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  Maximal-effort debulking surgery is the recommended approach for advanced-stage ovarian cancer. […] The outcomes of surgical treatment of ovarian cancer are divided into three prognostic groups based on the residual disease: (1) complete cytoreduction without macroscopic disease; (2) optimal cytoreduction with residual macroscopic disease up to 1 cm; and (3) suboptimal cytoreduction with macroscopic disease greater than 1 cm. […] Residual disease, along with the type of systemic therapy, are the most important prognostic factors that can be influenced by the treating physician. […] The 3-year overall survival for patients according to cytoreduction status was 72.4% (complete resection), 65.8% (residual tumour ≤ 1 cm) and 45.2% (residual tumour > 1cm), respectively, in a combined analysis of three multicentre phase III trials (AGO-OVAR 3, 5, and 7).

• #42 Application of machine learning techniques for predicting survival in ovarian cancer | BMC Medical Informatics and Decision Making | Full Text

  https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-02087-y

  Ovarian cancer is the fifth leading cause of mortality among women in the United States. The survival of ovarian cancer patients depends on several factors, including the treatment process and the prognosis. […] Ovarian cancer has a poor prognosis in most women since it is diagnosed at advanced stages. This cancer is called forgotten cancer and is sometimes misdiagnosed. Ovarian cancer has the fifth highest mortality rate among women living in the United States (US). […] Prognosis and survival prediction estimate the likelihood of recovery from a disease based on a patients clinical condition. Determining a disease prognosis plays an important role, especially in malignant diseases such as cancer. It is one of the most important elements that help clinicians decide on more appropriate treatments. Survival prediction helps patients be informed about treatment decisions and reduce their anxiety.

• #43 Application of machine learning techniques for predicting survival in ovarian cancer | BMC Medical Informatics and Decision Making | Full Text

  https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-02087-y

  Ovarian cancer is the fifth leading cause of mortality among women in the United States. The survival of ovarian cancer patients depends on several factors, including the treatment process and the prognosis. […] Ovarian cancer has a poor prognosis in most women since it is diagnosed at advanced stages. This cancer is called forgotten cancer and is sometimes misdiagnosed. Ovarian cancer has the fifth highest mortality rate among women living in the United States (US). […] Prognosis and survival prediction estimate the likelihood of recovery from a disease based on a patients clinical condition. Determining a disease prognosis plays an important role, especially in malignant diseases such as cancer. It is one of the most important elements that help clinicians decide on more appropriate treatments. Survival prediction helps patients be informed about treatment decisions and reduce their anxiety.

• #44 Application of machine learning techniques for predicting survival in ovarian cancer | BMC Medical Informatics and Decision Making | Full Text

  https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-022-02087-y

  Our results show that RF (Accuracy=88.72%, AUC=82.38%) and XGBoost (Root Mean Squad Error (RMSE))=20.61%, R2=0.4667) have the best performance for classification and regression approaches, respectively. […] To the best of our knowledge, our study is the first study that develops various ML models to predict ovarian cancer patients survival on the SEER database in both classification and regression approaches. […] The results showed that RF and XGBoost had the best performance for predicting the survival of ovarian cancer patients in classification and regression approaches, respectively.

• #45 DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315924

  Ovarian cancer is a malignant tumor with different clinicopathological and molecular characteristics. Due to its nonspecific early symptoms, the majority of patients are diagnosed with local or extensive metastasis, severely affecting treatment and prognosis. […] Integrating multiple types of omics data aids in predicting the survival rate of ovarian cancer patients. […] Experimental results demonstrate that compared to existing methods, the DFASGCNS model exhibits significant advantages in ovarian cancer prognosis prediction and survival analysis. Kaplan-Meier curve analysis results indicate significant differences in the survival subgroups predicted by the DFASGCNS model, contributing to a deeper understanding of the pathogenesis of ovarian cancer and providing more reliable auxiliary diagnostic information for the prognosis assessment of ovarian cancer patients.

• #46 DFASGCNS: A prognostic model for ovarian cancer prediction based on dual fusion channels and stacked graph convolution | PLOS One

  https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0315924

  Ovarian cancer is a heterogeneous disease characterized by molecular and omics diversity. While single omics data focus on specific molecular aspects of ovarian cancer, integrating different omics data can provide complementary information from different molecular perspectives. Comprehensive analysis of multi-omics data is crucial for understanding the pathogenesis of ovarian cancer and predicting patient prognosis. […] Therefore, ovarian cancer prognosis prediction based on multi-omics data not only improves prediction accuracy but also deepens researchers understanding of the biological characteristics and molecular mechanisms of ovarian cancer. […] The results demonstrate that learning feature representations of multiple omics data and the relationship graph between samples using a dual fusion channel can effectively learn high-dimensional feature representations of multiple omics data from different perspectives. The utilization of SGCN to capture the latent network structure of multiple omics data significantly improves the accuracy of ovarian cancer prognosis prediction.

• #47 Creation and validation of models to predict response to primary treatment in serous ovarian cancer | Scientific Reports

  https://www.nature.com/articles/s41598-021-85256-9

  Nearly a third of patients with high-grade serous ovarian cancer (HGSC) do not respond to initial therapy and have an overall poor prognosis. However, there are no validated tools that accurately predict which patients will not respond. Our objective is to create and validate accurate models of prediction for treatment response in HGSC. […] By integrating clinical and genomic variables, we achieved prediction performances of over 95% in AUC. […] The majority of these patients with suboptimal response to initial treatment (termed non-responders herein) will die from their disease within two years and are typically treated in the second-line setting with alternative therapies that do not contain platinum. […] The performance of these prediction models ranges from 75-85% (measured as the area under the receiver operator curve (AUC)). Adding clinical characteristics to serum markers increases the performance of the model to an AUC of 90%.

• #48 Prediction Tools for Ovarian Cancer | Memorial Sloan Kettering Cancer Center

  https://www.mskcc.org/cancer-care/types/ovarian/prediction-tools

  Our ovarian cancer nomogram is an online tool that can be used to help predict the chance that a patient will not survive five years after primary surgery for epithelial ovarian cancer. […] This nomogram was developed using information from women with any stage of epithelial ovarian cancer who had surgery to remove their tumor. Therefore, this nomogram should not be used for women who have not had surgical treatment. […] Doctors have traditionally relied on the International Federation of Gynecology and Obstetrics (FIGO) staging system to estimate survival for epithelial ovarian cancer. However, additional patient- and tumor-specific factors may be important in determining prognosis. […] This prediction tool takes those factors including age, tumor type, family history, and overall physical health into account. […] To better understand these results, patients who elect to use this tool should discuss the survival estimates provided by this nomogram with their doctors.

• #49 Prediction Tools for Ovarian Cancer | Memorial Sloan Kettering Cancer Center

  https://www.mskcc.org/cancer-care/types/ovarian/prediction-tools

  Our ovarian cancer nomogram is an online tool that can be used to help predict the chance that a patient will not survive five years after primary surgery for epithelial ovarian cancer. […] This nomogram was developed using information from women with any stage of epithelial ovarian cancer who had surgery to remove their tumor. Therefore, this nomogram should not be used for women who have not had surgical treatment. […] Doctors have traditionally relied on the International Federation of Gynecology and Obstetrics (FIGO) staging system to estimate survival for epithelial ovarian cancer. However, additional patient- and tumor-specific factors may be important in determining prognosis. […] This prediction tool takes those factors including age, tumor type, family history, and overall physical health into account. […] To better understand these results, patients who elect to use this tool should discuss the survival estimates provided by this nomogram with their doctors.

• #50 Prediction Tools for Ovarian Cancer | Memorial Sloan Kettering Cancer Center

  https://www.mskcc.org/cancer-care/types/ovarian/prediction-tools

  Our ovarian cancer nomogram is an online tool that can be used to help predict the chance that a patient will not survive five years after primary surgery for epithelial ovarian cancer. […] This nomogram was developed using information from women with any stage of epithelial ovarian cancer who had surgery to remove their tumor. Therefore, this nomogram should not be used for women who have not had surgical treatment. […] Doctors have traditionally relied on the International Federation of Gynecology and Obstetrics (FIGO) staging system to estimate survival for epithelial ovarian cancer. However, additional patient- and tumor-specific factors may be important in determining prognosis. […] This prediction tool takes those factors including age, tumor type, family history, and overall physical health into account. […] To better understand these results, patients who elect to use this tool should discuss the survival estimates provided by this nomogram with their doctors.

• #51 A nomogram based on SEER database | IJWH

  https://www.dovepress.com/a-nomogram-based-on-seer-database-for-predicting-prognosis-in-patients-peer-reviewed-fulltext-article-IJWH

  Mucinous ovarian cancer (MOC) is a rare histological type of EOC. In order to guide the clinical diagnosis and management of MOC patients, we constructed and verified a nomogram for the estimation of overall survival in patients with MOC. […] Cox hazard regression analysis revealed that age, grade, FIGO stage and log odds of positive lymph nodes stage were independent risk factors for patients with MOC. […] The C-index of the nomogram was 0.827 (95% CI: 0.791 0.863) and the areas under the curve (AUC) predicting the 1-, 3- and 5-year survival rate were 0.853 (95% CI: 0.791 0.915), 0.886 (95% CI: 0.852 0.920) and 0.815 (95% CI: 0.766 0.864), respectively. […] Patients with high risk had a poorer prognosis than those with low risk. […] The nomogram was constructed to predict overall survival in patients with MOC, which had the significance for clinical evaluation.

• #52 Tumour gene test could help to predict ovarian cancer prognosis

  https://www.unsw.edu.au/newsroom/news/2020/08/tumour-gene-test-could-help-to-predict-ovarian-cancer-prognosis

  A global team of medical researchers led by UNSW have developed a test that could help to predict survival for women diagnosed with ovarian cancer, and pave the way towards personalised treatment. […] A tumour test could help to identify ovarian cancer patients with predicted poor survival, and down the track inform new therapeutical approaches, the results of a major international collaboration have shown. […] Ovarian cancer is the eighth most commonly occurring cancer in women, with nearly 300,000 global new cases in 2018. […] We conducted an analysis of 3769 tumour samples from women with ovarian cancer and found we were able to reliably use a piece of tumour to determine how good a womans survival chances would be five years after diagnosis, says lead author Professor Susan Ramus from UNSW Medicine.

• #53 Tumour gene test could help to predict ovarian cancer prognosis

  https://www.unsw.edu.au/newsroom/news/2020/08/tumour-gene-test-could-help-to-predict-ovarian-cancer-prognosis

  A global team of medical researchers led by UNSW have developed a test that could help to predict survival for women diagnosed with ovarian cancer, and pave the way towards personalised treatment. […] A tumour test could help to identify ovarian cancer patients with predicted poor survival, and down the track inform new therapeutical approaches, the results of a major international collaboration have shown. […] Ovarian cancer is the eighth most commonly occurring cancer in women, with nearly 300,000 global new cases in 2018. […] We conducted an analysis of 3769 tumour samples from women with ovarian cancer and found we were able to reliably use a piece of tumour to determine how good a womans survival chances would be five years after diagnosis, says lead author Professor Susan Ramus from UNSW Medicine.

• #54 Tumour gene test could help to predict ovarian cancer prognosis

  https://www.unsw.edu.au/newsroom/news/2020/08/tumour-gene-test-could-help-to-predict-ovarian-cancer-prognosis

  The researchers found their gene expression test was substantively better at predicting survival than using a patients age and cancer stage. […] When women were divided into five groups, we found that the women whose tumour gene expression was associated with the best prognosis had nine years survival, whereas the women in the poorest survival group have two years survival, which is a very big difference, Professor Ramus says. […] Our vision is that clinicians could use our test at diagnosis to identify the group of patients who wouldn’t do well on the current treatments and potentially offer them alternatives for example, we may be able to put those patients into clinical trials and offer them different treatments that may improve their survival. […] The consortium is unique in this space because it has access to thousands of samples which is a lot of samples for a rare disease like ovarian cancer,” she says.

• #55 Tumour gene test could help to predict ovarian cancer prognosis

  https://www.unsw.edu.au/newsroom/news/2020/08/tumour-gene-test-could-help-to-predict-ovarian-cancer-prognosis

  At the moment, only patient age and stage are used to determine survival, so something like our tool is sorely needed. […] Some of the genes we identified as being predictors for good or poor survival may be potential targets for new treatments. […] So this is a way to stratify patients and potentially give more personalized treatment down the track. […] Potentially, we could incorporate it within a clinical trial so that the women who are predicted to have poor survival could get alternative treatments as rapidly as possible, Prof. Ramus says. […] The researchers hope their test will be ready for clinical use in the near future.

• #56 Genes | An Open Access Journal from MDPI

  https://www.mdpi.com/journal/genes

  Clinicopathological Characteristics of Ovarian and Breast Cancer in PALB2, RAD51C, and RAD51D Germline Pathogenic Variant Carriers […] Germline pathogenic variants (GPVs) in PALB2, RAD51C, and RAD51D increase breast cancer (BC) and ovarian cancer (OC) risk. Limited data on clinicopathological characteristics of BC and OC in women with these GPVs hamper guideline development. Therefore, this study aims to describe these characteristics in a consecutive series of female PALB2, RAD51C, and RAD51D GPV carriers. […] The median OC onset age was 66 (n = 4) and 56 years (n = 2) for RAD51C and RAD51D carriers, respectively, versus 67 years in the NCR. All RAD51D carriers had high-grade serous carcinoma, compared to 51.5% in the NCR. […] Differences in onset age and histological subtypes were observed between GPV carriers and national data. Further research on cancer characteristics is needed to optimize counseling and cancer prevention in these women.

• #57 Prognosis and survival in ovarian cancer | Canadian Cancer Society

  https://cancer.ca/en/cancer-information/cancer-types/ovarian/prognosis-and-survival

  The amount of cancer that remains after surgery is called residual disease. No residual disease has a better prognosis than if there is cancer remaining after surgery. […] Younger women who have ovarian cancer have a better prognosis than older women. […] A woman with a good performance status is more likely to respond to treatment, experience fewer and less severe side effects and have a better prognosis. […] If the treatment is having an effect on the cancer after the first cycle of chemotherapy, it is considered a good prognostic factor. […] A lowered level of CA125 after chemotherapy is a good prognostic factor.

• #58 Predicting Prognosis and Platinum Resistance in Ovarian Cancer: Role of Immunohistochemistry Biomarkers

  https://pmc.ncbi.nlm.nih.gov/articles/PMC9916805/

  Patients undergo platinum chemotherapy are classified into platinum-sensitive or platinum-resistant according to the time from the end of treatment to the recurrence of the disease (platinum-free interval). Platinum resistance, defined as disease recurrence within 6 months of completion of first-line platinum-based chemotherapy, occurs in approximately 25% of cases and the median progression-free survival (PFS) is only 912 months on average. […] The tumour microenvironment in ovarian cancer tissues is associated with altered protein expression patterns, making it conceivably a site of interest to decipher protein profile patterns and alteration in disease development and treatment intervention. […] The identification of molecular signatures is becoming more important for individualized targeted ovarian cancer treatment. From a therapeutic standpoint, the discovery of biomarkers has a significant role in predicting the results of chemotherapy treatment, which is essential in assisting clinicians in weighing the possibility of chemotherapy resistance and predicting the quality of life after chemotherapy.

• #59 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  Maximal-effort debulking surgery is the recommended approach for advanced-stage ovarian cancer. […] The outcomes of surgical treatment of ovarian cancer are divided into three prognostic groups based on the residual disease: (1) complete cytoreduction without macroscopic disease; (2) optimal cytoreduction with residual macroscopic disease up to 1 cm; and (3) suboptimal cytoreduction with macroscopic disease greater than 1 cm. […] Residual disease, along with the type of systemic therapy, are the most important prognostic factors that can be influenced by the treating physician. […] The 3-year overall survival for patients according to cytoreduction status was 72.4% (complete resection), 65.8% (residual tumour ≤ 1 cm) and 45.2% (residual tumour > 1cm), respectively, in a combined analysis of three multicentre phase III trials (AGO-OVAR 3, 5, and 7).

• #60 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  Maximal-effort debulking surgery is the recommended approach for advanced-stage ovarian cancer. […] The outcomes of surgical treatment of ovarian cancer are divided into three prognostic groups based on the residual disease: (1) complete cytoreduction without macroscopic disease; (2) optimal cytoreduction with residual macroscopic disease up to 1 cm; and (3) suboptimal cytoreduction with macroscopic disease greater than 1 cm. […] Residual disease, along with the type of systemic therapy, are the most important prognostic factors that can be influenced by the treating physician. […] The 3-year overall survival for patients according to cytoreduction status was 72.4% (complete resection), 65.8% (residual tumour ≤ 1 cm) and 45.2% (residual tumour > 1cm), respectively, in a combined analysis of three multicentre phase III trials (AGO-OVAR 3, 5, and 7).

• #61 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  The goal of upfront cytoreduction should always be complete resection, especially in mucinous and clear-cell carcinoma where no benefit has been shown for residual disease ≤1 cm. […] However, small residual disease (i.e., ≤1 cm) may be acceptable in low-grade serous carcinoma, and possibly in tumours highly responsive to systemic treatment, such as high-grade serous tubo-ovarian carcinoma. […] In contrast to upfront debulking surgery, patients who underwent neoadjuvant chemotherapy appeared to benefit from subsequent interval debulking surgery only if complete cytoreduction was achieved; a small-volume residual disease at the end of surgery did not improve survival. […] Ovarian cancer is predominantly a peritoneal disease, and therefore its non-resectability is based on the evaluation of abdominal sites critical for cytoreduction (disease location).

• #62 Prediction of Surgical Outcome in Advanced Ovarian Cancer by Imaging and Laparoscopy: A Narrative Review

  https://www.mdpi.com/2072-6694/15/6/1904

  The goal of upfront cytoreduction should always be complete resection, especially in mucinous and clear-cell carcinoma where no benefit has been shown for residual disease ≤1 cm. […] However, small residual disease (i.e., ≤1 cm) may be acceptable in low-grade serous carcinoma, and possibly in tumours highly responsive to systemic treatment, such as high-grade serous tubo-ovarian carcinoma. […] In contrast to upfront debulking surgery, patients who underwent neoadjuvant chemotherapy appeared to benefit from subsequent interval debulking surgery only if complete cytoreduction was achieved; a small-volume residual disease at the end of surgery did not improve survival. […] Ovarian cancer is predominantly a peritoneal disease, and therefore its non-resectability is based on the evaluation of abdominal sites critical for cytoreduction (disease location).

• #63 Frontiers | Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

  https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.645839/full

  Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis. Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies. Despite recent advances in OC treatment, most OC patients diagnosed at advanced stages and have poor prognoses, with a recurrence rate of 70% within 3 years and only 30% 5-year survival rate. Therefore, there is an urgent need to identify sufficient and reliable biomarkers with high specificity and sensitivity for OC patients to distinguish responsive patients are suited to immune checkpoint inhibitor therapy from OC patients. The hypoxic microenvironment plays a key role in tumorigenesis, radiotherapy, and chemotherapy resistance in OC. Hypoxia affects the tumor microenvironment and promotes tumor angiogenesis, the release of damage-associated pattern molecules, tumor immunosuppression, and immune escape. Our findings provide a theoretical basis for clinical applications. These results demonstrated that tumor antigen presentation defects, recruitment of inhibitory immune cells and immunosuppressive factors, and change in tumor microenvironment results in the evasion of the monitoring, recognition, and attack by the immune system in high-risk patients, thus promoting tumor escape. Our findings therefore not only offer reliable biomarkers for predicting the prognosis of OC, but also identify the responsiveness of patients to immunotherapy.

• #64

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #65

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #66

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #67 Frontiers | Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis

  https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2021.645839/full

  Multi-Omics Profiling Identifies Risk Hypoxia-Related Signatures for Ovarian Cancer Prognosis. Ovarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. In this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies. Despite recent advances in OC treatment, most OC patients diagnosed at advanced stages and have poor prognoses, with a recurrence rate of 70% within 3 years and only 30% 5-year survival rate. Therefore, there is an urgent need to identify sufficient and reliable biomarkers with high specificity and sensitivity for OC patients to distinguish responsive patients are suited to immune checkpoint inhibitor therapy from OC patients. The hypoxic microenvironment plays a key role in tumorigenesis, radiotherapy, and chemotherapy resistance in OC. Hypoxia affects the tumor microenvironment and promotes tumor angiogenesis, the release of damage-associated pattern molecules, tumor immunosuppression, and immune escape. Our findings provide a theoretical basis for clinical applications. These results demonstrated that tumor antigen presentation defects, recruitment of inhibitory immune cells and immunosuppressive factors, and change in tumor microenvironment results in the evasion of the monitoring, recognition, and attack by the immune system in high-risk patients, thus promoting tumor escape. Our findings therefore not only offer reliable biomarkers for predicting the prognosis of OC, but also identify the responsiveness of patients to immunotherapy.

• #68

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Stage, grade and histology at diagnosis are major prognostic factors. […] The cancer Antigen 125 (CA125) is a biological parameter that can be used easily and inexpensively. It has been proven that a high value is a sign of poorer prognosis even if it is not specific. […] New prognostic factors have recently emerged. […] The patient’s immune system participates in the fight against tumors. […] Regardless of the tumor stage, the presence of TILs in ovarian cancer is predictive of good prognosis. […] A high PLR is associated with significantly poorer survival for colorectal, gastro-esophageal, hepatocellular and pancreatic cancer, whereas a high NLR is positively correlated with OS mainly for mesothelioma, pancreatic cancer, renal cell carcinoma and colorectal cancer. […] Circulating tumor DNA is one of the most promising prognostic and predictive factors.

• #69

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  HRD is a predictive biomarker of PARPi response and platin-based CT, with mutation screening conducted at the start of care. […] The KELIM score aims to predict chemosensitivity using a modeled CA125 elimination rate. […] Some patients have been reported to have a long-life expectancy, even exceeding 10 years after diagnosis. […] These statistics warrant a search for reliable predictive factors. […] Even though LTSs often present many known factors for good prognosis, some of them have factors generally described as linked to poor prognosis, such as age over 50, advanced stage and grade or serous histology. […] By monitoring ctDNA as a reliable predictive and prognostic factor, a personalized and more adapted therapeutic strategy could probably be offered to patients with ovarian cancer.

• #70

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  HRD is a predictive biomarker of PARPi response and platin-based CT, with mutation screening conducted at the start of care. […] The KELIM score aims to predict chemosensitivity using a modeled CA125 elimination rate. […] Some patients have been reported to have a long-life expectancy, even exceeding 10 years after diagnosis. […] These statistics warrant a search for reliable predictive factors. […] Even though LTSs often present many known factors for good prognosis, some of them have factors generally described as linked to poor prognosis, such as age over 50, advanced stage and grade or serous histology. […] By monitoring ctDNA as a reliable predictive and prognostic factor, a personalized and more adapted therapeutic strategy could probably be offered to patients with ovarian cancer.

• #71

  https://link.springer.com/article/10.1007/s40944-025-00964-8

  Ovarian cancer is the eighth most common cancer among women, accounting for 4.7% of all cancer-related deaths. […] Some established prognostic factors are clinical, such as age, ECOG, and Body Mass Index. Histological subtype, stage and grade are also prognostic factors, and optimal surgery is one of the main factors. Furthermore, the presence of ascites at diagnosis and cancer Antigen 125 assessment could help to predict patient outcomes. Nevertheless, median survival is less than 5 years. […] Despite the poor prognosis in this pathology, some patients are still alive 10 years after diagnosis. A better understanding of this populations characteristics could help to anticipate patient outcomes and thus adapt their management. […] The amount of residual disease after cytoreductive surgery plays a critical role in patients prognosis. Even minimal residual disease is associated with significantly reduced overall survival, optimal surgery (no macroscopic residual disease), also characterized by the completeness of cytoreduction score of 0 (CC-0), is widely recognized as associated with a good prognostic factor in EOCs.

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