A prognostic nomogram to predict overall survival in patients with platinum-sensitive recurrent ovarian cancer

A methylomics-associated nomogram predicts the overall survival risk of stage III to IV ovarian cancer

Accumulating studies demonstrated that DNA methylation may be potential prognostic hallmarks of various cancers. However, few studies have focused on the power of DNA methylation for prognostic prediction in patients with stage III to IV ovarian cancer (OC). Therefore, constructing a methylomics-related indicator to predict overall survival (OS) of stage III to IV OC was urgently required. A total of 520 OC patients with 485,577 DNA methylation sites from TCGA database were selected to develop a robust DNA methylation signature. The 520 patients were clustered into a training group (70%, n = 364 samples) and an internal validation group (30%, n = 156). The training group was used for digging a prognostic predictor based on univariate Cox proportional hazard analysis, least absolute shrinkage and selection operator (LASSO) as well as multivariate Cox regression analysis. The internal and external validation group (ICGC OV-AU project) were used for validating the predictive robustness of the predictor based on receiver operating characteristic (ROC) analysis and Kaplan-Meier survival analysis. We identified a 21-DNA methylation signature-based classifier for stage III-IV OC patients' OS. According to ROC analysis in the internal validation, external validation and entire TCGA set, we proved the high power of the 21-DNA methylation signature for predicting OS (area under the curve [AUC] at 1, 3, 5 years in internal validation set (0.782, 0.739, 0.777, respectively), external validation set (0.828, 0.760, 0.741, respectively), entire TCGA set (0.741, 0.748, 0.781, respectively). Besides, a nomogram was developed via methylation risk score as well as a few clinical variables, and the result showed a high ability of the predictive nomogram. In summary, we used integrated bioinformatics approaches to successfully identified a DNA methylation-associated nomogram, which can predict effectively the OS of patients with stage III to IV OC.

Prognostic nomogram that predicts progression-free survival and overall survival of patients with ovarian clear cell carcinoma

Objectives

We aims to develop nomograms to predict progression-free survival (PFS) and overall survival (OS) in patients with ovarian clear cell carcinoma (OCCC) after primary treatment and compare the predictive accuracy with the currently used International Federation of Gynecology and Obstetrics (FIGO) system.

Methods

We collected data from 358 Chinese patients diagnosed with OCCC and who underwent standard treatment at our hospital. Patients diagnosed from 1982-9 to 2011-12 were classified as the training group and patients diagnosed from 2012-1 to 2016-11 were classified as the validation group. Nomograms were developed based on the training group and was validated in the validation group. The predictive performance was determined by concordance index and calibration curve.

Results

The most predictive nomogram for PFS was constructed using variables: thrombosis, the FIGO staging, residual of the tumor and distant metastasis, with a concordance index of 0.738. While the nomogram for OS consisted of thrombosis, lymph node metastasis, residual of the tumor, malignant ascites/washing, and platinum resistance, with a concordance index of 0.835. The nomograms were internally validated by concordance indexes of 0.775 and 0.807 for predicting PFS and OS, respectively. In comparison, the concordance statistics for OS based on the FIGO staging was significantly lower (P<0.05).

Conclusion

We have established two prognostic nomograms for recurrence and long-term survival in patients with OCCC after primary treatment in a large Chinese center and validated them in patients from the same center. This tool used variables specifically related to OCCC and was more accurate than the FIGO system. It is relatively easy to use in clinic for patient counseling, postoperative management, and follow-up for individual patients.

Ovarian cancer recurrence: is the definition of platinum resistance modified by PARPi and other intervening treatments? The evolving landscape in the management of platinum-resistant ovarian cancer

Definitions of platinum resistance have been questioned and changed over the last five years, even though no predictive biomarker of resistance exists. These have sculpted how we approach platinum retreatment and, consequently, how we devise new treatment strategies for those patients with tumour progression on platinum therapy. Platinum-non-eligible ovarian cancer is treated with single-agent non-platinum drugs. When bevacizumab can be added to chemotherapy, progression-free survival improves significantly. For patients with a BRCA mutation, PARP inhibitor monotherapy is an option compared to chemotherapy. There is currently no clearly identified role for immune-checkpoint inhibition in this patient population. This review describes some of the challenges in treating patients with platinum resistance and suggests refinements in the selection of patients most likely to benefit from targeting a DNA damage response, angiogenesis or immune modulation. It also describes novel agents of interest and possible mechanisms of the synergy of therapeutic combinations.

FOXA1 can be modulated by HDAC3 in the progression of epithelial ovarian carcinoma

FOXA1 is associated with malignant tumors, but the function of FOXA1 in EOC is unclear. HDAC3 can influence the proliferation, migration and invasion ability of EOC. In this study, we wanted to explore the function of FOXA1 in ovarian cancer and the relationship between HDAC3 and FOXA1.The expression of HDAC3 and FOXA1 was detected by immunohistochemical staining of primary lesions from 127 epithelial ovarian carcinoma patients. A proliferation assay, a Transwell assay, an apoptosis assay and animal experiments were used to assess the proliferation, invasion and apoptosis abilities of ovarian cancer cells before and after transfection with FOXA1. The relevance of the in vitro findings was confirmed in xenografts. The H-scores for FOXA1 and HDAC3 staining in FIGO stage III-IV were noticeably higher and predicted adverse clinical outcomes in patients with ovarian cancer. The expression level of HDAC3 was significantly correlated with the expression level of FOXA1. Invasion, proliferation and apoptosis capacity and tumor formation were decreased in the FOXA1-knockdown cells. Experiments in xenografts confirmed that HDAC3 mediated tumor formation. In conclusion, FOXA1 can be modulated by HDAC3 through the Wnt/β-catenin signaling pathway, and FOXA1 plays essential roles in the proliferation, apoptosis and invasion of EOC cell lines and xenograft experiments.

Retrospective analysis of the role of cyclin E1 overexpression as a predictive marker for the efficacy of bevacizumab in platinum-sensitive recurrent ovarian cancer

The relative benefit of bevacizumab in ovarian cancer (OC) patients is greater the more the disease becomes platinum-resistant. Among other mechanisms of action, antiangiogenic agents may induce homologous recombination deficiency. Cyclin E1 (CCNE1) overexpression is a proposed marker of platinum resistance and is mutually exclusive with deficiency in homologous recombination. In this study, we evaluated the predictive value of CCNE1 expression with regard to the efficacy of bevacizumab. We retrospectively evaluated data from patients with platinum-sensitive recurrent OC who were treated with chemotherapy (CT) plus bevacizumab (Bev group) or CT alone (CT group) at a tertiary cancer centre from 2005 to 2017. The two groups were paired according to histology, platinum-free interval (PFI) and number of previous treatment lines. Progression-free survival (PFS) was compared between groups by log rank test and Cox regression. A total of 124 patients were included, with 62 in each group. The groups were well balanced regarding histology, PFI and number of previous treatment lines. Median PFS (mPFS) was 19.5 months for the Bev group versus 16.0 months for CT group (p = 0.150). By multivariate analysis, the HR for PFS was 2.25 (95% CI: 1.10–4.60) for CCNE1 overexpression. The benefit of bevacizumab was larger in the subgroups of patients with PFI 6–12 months (mPFS 18.6 versus 10.4 months, p = 0.002) and CCNE1 overexpression (mPFS 16.3 versus 7.0 months, p = 0.010). In conclusion, CCNE1 overexpression and PFI may suggest which patients will receive the greatest benefit from bevacizumab. These data, if confirmed by other studies, could help better select patients for antiangiogenic therapy.

Single-Cell RNA-Sequencing Portraying Functional Diversity and Clinical Implications of IFI6 in Ovarian Cancer

Ovarian cancer (OC) is one of the most lethal gynecologic malignancies. Most patients die of metastasis due to a lack of other treatments aimed at improving the prognosis of OC patients. In the present study, we use multiple methods to identify prognostic S1 as the dominant subtype in OC, possessing the most ligand-receptor pairs with other cell types. Based on markers of S1, the consensus clustering algorithm is used to explore the clinical treatment subtype in OC. As a result, we identify two clusters associated with distinct survival and drug response. Notably, IFI6 contributes to the cluster classification and seems to be a vital gene in OC carcinogenesis. Functional enrichment analysis demonstrates that its functions involve G2M and cisplatin resistance, and downregulation of IFI6 suppresses proliferation capabilities and significantly potentiates cisplatin-induced apoptosis of OC cells in vitro. To explore possible mechanisms of IFI6 influencing OC proliferation and cisplatin resistance, GSEA is conducted and shows that IFI6 is positively correlated with the NF-κB pathway, which is validated by RT-qPCR. Significantly, we develop a prognostic model including IFI6, RiskScore, which is an independent prognostic factor and presents encouraging prognostic values. Our findings provide novel insights into elucidating the biology of OC based on single-cell RNA-sequencing. Moreover, this approach is potentially helpful for personalized anti-cancer strategies and predicting outcomes in the setting of OC.

Prognostic nomogram for progression-free survival in patients with BRCA mutations and platinum-sensitive recurrent ovarian cancer on maintenance olaparib therapy following response to chemotherapy

BACKGROUND

The impact of maintenance therapy with PARP inhibitors (PARPi) on progression-free survival (PFS) in patients with BRCA mutations and platinum-sensitive recurrent ovarian cancer (PSROC) varies widely. Individual prognostic factors do not reliably distinguish patients who progress early from those who have durable benefit. We developed and validated a prognostic nomogram to predict PFS in these patients.

METHODS

The nomogram was developed using data from a training patient cohort with BRCA mutations and high-grade serous PSROC on the placebo arm of two maintenance therapy trials, Study 19 and SOLO2/ENGOT-ov21. We performed multivariable Cox regression analysis based on pre-treatment characteristics to develop a nomogram that predicts PFS. We assessed the discrimination and validation of the nomogram in independent validation patient cohorts treated with maintenance olaparib.

RESULTS

The nomogram includes four PFS predictors: CA-125 at randomisation, platinum-free interval, presence of measurable disease and number of prior lines of platinum therapy. In the training (placebo) cohort (internal validation C-index 0.64), median PFS in the model-predicted good, intermediate and poor-risk groups was: 7.7 (95% CI 5.3-11.3), 5.4 (4.8-5.8) and 2.9 (2.8-4.4) months, respectively. In the validation (olaparib) cohort (C-index 0.71), median PFS in the model-predicted good, intermediate and poor-risk groups was: not reached, 16.6 (13.1-22.4) and 8.3 (7.1-10.8) months, respectively. The nomogram showed good calibration in the validation cohort (calibration plot).

CONCLUSIONS

This nomogram can be used to predict PFS and counsel patients with BRCA mutations and PSROC prior to maintenance olaparib and for stratification of patients in trials of maintenance therapies.

Identification of a Novel Tumor Microenvironment Prognostic Signature for Advanced-Stage Serous Ovarian Cancer

Simple Summary

The expression of tumor microenvironment-related genes is known to be correlated with ovarian cancer patients’ prognosis. Immunotherapeutic targets are in part located in this complex cluster of cells and soluble factors. In our study, we constructed a prognostic 11-gene signature for advanced serous ovarian cancer from tumor microenvironment-related genes through lasso regression. The established risk score can quantify the prognosis of ovarian cancer patients more accurately and is able to predict the putative biological response of cancer samples to a programmed death ligand 1 blocking immunotherapy. This might empower the role of immunotherapy in ovarian cancer through its usage in future study protocols.

Abstract

(1) Background: The tumor microenvironment is involved in the growth and proliferation of malignant tumors and in the process of resistance towards systemic and targeted therapies. A correlation between the gene expression profile of the tumor microenvironment and the prognosis of ovarian cancer patients is already known. (2) Methods: Based on data from The Cancer Genome Atlas (379 RNA sequencing samples), we constructed a prognostic 11-gene signature (SNRPA1, CCL19, CXCL11, CDC5L, APCDD1, LPAR2, PI3, PLEKHF1, CCDC80, CPXM1 and CTAG2) for Fédération Internationale de Gynécologie et d’Obstétrique stage III and IV serous ovarian cancer through lasso regression. (3) Results: The established risk score was able to predict the 1-, 3- and 5-year prognoses more accurately than previously known models. (4) Conclusions: We were able to confirm the predictive power of this model when we applied it to cervical and urothelial cancer, supporting its pan-cancer usability. We found that immune checkpoint genes correlate negatively with a higher risk score. Based on this information, we used our risk score to predict the biological response of cancer samples to an anti-programmed death ligand 1 immunotherapy, which could be useful for future clinical studies on immunotherapy in ovarian cancer.

Impact of health-related quality of life (HRQoL) on short-term mortality in patients with recurrent ovarian, fallopian or peritoneal carcinoma (the NOGGO-AGO QoL Prognosis-Score-Study): results of a meta-analysis in 2209 patients

Objective

Recurrent ovarian cancer is an incurable disease with variable but poor prognosis. Health-related quality of life (HRQoL) is a patient-reported outcome measure generally applied to measure effects of therapies. Our aim was the development and validation of a risk score for the prediction of short-term mortality using the combination of sociodemographic and clinical factors and HRQoL.

Methods

For exploratory and validation analysis, the North-Eastern German Society of Gynecological Oncology (NOGGO) and Working Group Gynecological Oncology (AGO) study databases were screened for trials. Only trials which obtained defined HRQoL measurements were included in the final analysis. Multivariable logistic regression analyses were used to identify risk factors and their weighting for the risk score. Modulation with cubic regression analyses revealed median survival and short-term mortality defined as 1-year mortality for each value.

Results

For exploration, 974 patients from three clinical studies of the NOGGO and for validation, 1235 patients from several clinical studies of the AGO were eligible. The risk score included platinum-free interval, performance status, age, global QoL and nausea/vomiting. Receiver operating characteristic analysis showed a good predictive value with an area under the curve of 0.81 for model 1 in the exploration and 0.74 in the validation. Short-term mortality in model 1 was 8.2%, 23.5% and 58.4% in the exploration sample, and 19.7%, 38.1% and 63.4% in the validation sample for patients under low, medium and high risk, respectively.

Conclusions

This risk score discriminates well between recurrent ovarian cancer patients under low, medium and high risk of short-term mortality. It may help to identify a risk group under high risk for short-term mortality that can be used for randomization in clinical trials and may support decision making for palliative chemotherapy.

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This newly developed NOGGO-AGO QoL prognosis score clearly discriminates recurrent ovarian cancer (rOC) patients under low, medium and high risk for short-term survival (<1 year).

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The risk score included platinum-free interval, performance status, age, global QoL and nausea/vomiting.

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NOGGO-AGO QoL score can be used for stratification or randomization in clinical trials and for identification of a group under high risk for short-term mortality.

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It may also help the decision making for chemotherapy and provide more precise information of further life expectation for rOC patients.

The systemic treatment of recurrent ovarian cancer revisited

Treatment approaches for relapsed ovarian cancer have evolved over the past decade from a calendar-based decision tree to a patient-oriented biologically driven algorithm. Nowadays, platinum-based chemotherapy should be offered to all patients with a reasonable chance of responding to this therapy. The treatment-free interval for platinum is only one of many factors affecting patients' eligibility for platinum re-treatment. Bevacizumab increases the response to chemotherapy irrespective of the cytotoxic regimen and can be valuable in patients with an urgent need for symptom relief (e.g. pleural effusion, ascites). For patients with recurrent high-grade ovarian cancer, which responds to platinum-based treatment, maintenance therapy with a poly(ADP-ribose) polymerase inhibitor can be offered, regardless of the BRCA mutation status. Here we review contemporary decision-making processes in the systemic treatment of relapsed ovarian cancer.

A prognosis-predictive nomogram of ovarian cancer with two immune-related genes: CDC20B and PNPLA5

Ovarian carcinoma (OV) is one of the most lethal gynecological malignancies globally, and the overall 5-year survival rate of OV was 47% in 2018 according to American data. To increase the survival rate of patients with OV, many researchers have sought to identify biomarkers that act as both prognosis-predictive markers and therapy targets. However, most of these have not been suitable for clinical application. The present study aimed at constructing a predictive prognostic nomogram of OV using the genes identified by combining The Cancer Genome Atlas (TCGA) dataset for OV with the immune score calculated by the Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data algorithm. Firstly, the algorithm was used to calculate the immune score of patients with OV in the TCGA-OV dataset. Secondly, differentially expressed genes (DEGs) between low and high immune score tissues were identified, and Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis was performed to predict the functions of these DEGs. Thirdly, univariate, multivariate and Lasso Cox's regression analyses were carried out step by step, and six prognosis-related DEGs were identified. Then, Kaplan-Myer survival curves were generated for these genes and validated by comparing their expression levels to further narrow the range of DEGs and to calculate the risk score. Two genes were identified, cell division cycle 20B and patatin-like phospholipase domain containing 5, which were both shown to have higher expression levels in OV tissues and to be significantly associated with the prognosis of OV. Next, a nomogram was created using these two genes and age, and using the receiver operating characteristic (ROC) curve and calibration curve, the effectiveness of the nomogram was validated. Finally, an external validation was conducted for this nomogram. The ROC showed that the areas under the curve (AUCs) of the 3- and 5-year overall survival predictions for the nomogram were 0.678 and 0.62, respectively. Moreover, the ROC of the external validation model showed that the AUCs of the 3- and 5-year were 0.699 and 0.643, respectively, demonstrating the effectiveness of the generated nomogram. In conclusion, the present study has identified two immune-related genes as biomarkers that reliably predict overall survival in OV. These biomarkers might also be potential molecular targets of immune therapy to treat patients with OV.

Prognostic impact of platinum sensitivity in ovarian carcinoma patients with brain metastasis

Background

Brain metastasis (BM) is a rare event in ovarian cancer patients. The current prognostic scores that have been used for other tumors do not account for specific characteristics of ovarian cancer, such as platinum sensitivity.

Methods

This retrospective cohort study examined patients with ovarian carcinoma and BM who were treated at a single institution from January 2007 to December 2017. Clinical data on the diagnosis of BM and follow-up were collected. Cox regression was used to evaluate prognostic factors for overall survival (OS).

Results

Of 560 patients, 26 presented with BM. Eight patients were treated with surgery, 15 with whole-brain radiotherapy (RT), and 5 with stereotactic RT, and 4 patients received systemic treatment at the diagnosis of BM. The median OS was 10.8 months. The following factors were associated with OS: platinum-sensitive recurrence (HR 0.34, 95% CI 0.12–0.99; p = 0.049), higher number of previous treatment lines (HR 1.57, 95% CI 1.12–2.19; p = 0.008), ECOG performance status (HR 2.52, 95% CI 1.24–5.09; p = 0.010), and longer interval from initial diagnosis to BM (p = 0.025). Notably, the number of brain metastasis, the largest tumor size, and progression outside of the CNS were not related to survival. Platinum sensitivity was not associated with any of the classic prognostic factors in brain metastasis patients such as number or size of brain metastasis or disease progression outside the CNS strengthening the hypothesis of the importance of platinum sensitivity to the prognosis of ovarian cancer patients with BM.

Conclusions

The factors related to the biological behavior of the ovarian cancer such as platinum sensitivity at the time of BM diagnosis, fewer number of previous treatment lines and interval from initial diagnosis were associated with survival in ovarian cancer patients with BM, while factors that are usually related to survival in BM in other cancers were not associated with survival in this cohort of ovarian cancer patients. The small number of patients did not allow us to exclude the prognostic role of these former factors that were not associated with survival in the present cohort.

Development and validation of a prognostic nomogram for overall survival in patients with platinum-resistant ovarian cancer treated with chemotherapy

BACKGROUND

Platinum-resistant ovarian cancer (PROC) is associated with a variable prognosis and unpredictable survival times. We have developed and validated a prognostic nomogram with the objective of improving the prediction of overall survival (OS) in patients treated with chemotherapy.

METHODS

The nomogram was developed using data from a training cohort of patients from two trials, including the chemotherapy-only arm in AURELIA and all randomised patients in CARTAXHY. Multivariable proportional hazards models were generated based on pretreatment characteristics to develop a nomogram that classifies patients based on OS. We subsequently assessed the performance of the nomogram in terms of discrimination and calibration in independent validation patient cohorts: PENELOPE and the bevacizumab-chemotherapy arm of AURELIA.

RESULTS

The nomogram included six significant OS predictors, in order of importance: performance status, ascites, size of the largest tumour, CA-125, platinum-free interval and primary platinum resistance (C-statistic 0.69). In the training cohort, the median OS in the good, intermediate and poor prognosis groups was 25.3, 15.2 and 7.4 months, respectively. In the PENELOPE validation cohort (C-statistic 0.59), the median OS in the good, intermediate and poor prognosis groups was 18.5, 10.3 and 5.8 months, respectively. In the AURELIA bevacizumab-chemotherapy validation cohort (C-statistic 0.67), the median OS in good, intermediate and poor prognosis groups was 26.7, 13.8 and 10.0 months, respectively.

CONCLUSIONS

This nomogram with six pretreatment characteristics allows prediction of OS in PROC and could be used for stratification of patients in clinical trials as well as for counselling patients about prognosis.

Development of Web-Based Nomograms to Predict Treatment Response and Prognosis of Epithelial Ovarian Cancer

Purpose

Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC.

Materials and Methods

We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016. Patients’ clinico-pathologic characteristics, details of primary treatment, intra-operative surgical findings, and survival outcomes were collected. To construct predictive nomograms for platinum sensitivity, 3-year progression-free survival (PFS), and 5-year overall survival (OS), we performed stepwise variable selection by measuring the area under the receiver operating characteristic curve (AUC) with leave-one-out cross-validation. For model validation, 10-fold cross-validation was applied.

Results

The median length of observation was 42.4 months (interquartile range, 25.7 to 69.9 months), during which 441 patients (50.9%) experienced disease recurrence. The median value of PFS was 32.6 months and 3-year PFS rate was 47.8% while 5-year OS rate was 68.4%. The AUCs of the newly developed nomograms predicting platinum sensitivity, 3-year PFS, and 5-year OS were 0.758, 0.841, and 0.805, respectively. We also developed predictive nomograms confined to the patients who underwent primary debulking surgery. The AUCs for platinum sensitivity, 3-year PFS, and 5-year OS were 0.713, 0.839, and 0.803, respectively.

Conclusion

We successfully developed nomograms predicting treatment response and prognosis of patients with EOC. These nomograms are expected to be useful in clinical practice and designing clinical trials.

Establishment and external validation of a prognostic model for predicting disease-free survival and risk stratification in breast cancer patients treated with neoadjuvant chemotherapy

Background

The eighth edition of the American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system for survival prediction and risk stratification in breast cancer (BC) patients after neoadjuvant chemotherapy (NCT) is of limited efficacy. This study aimed to establish a novel prognostic nomogram for predicting disease-free survival (DFS) in BC patients after NCT.

Patients and methods

A total of 567 BC patients treated with NCT, from two independent centers, were included in this study. Cox proportional-hazards regression (CPHR) analysis was conducted to identify the independent prognostic factors for DFS, in order to develop a model. Subsequently, the discrimination and calibration ability of the prognostic model were assessed in terms of its concordance index (C-index), risk group stratification, and calibration curve. The performance of the nomogram was compared with that of the eighth edition of the AJCC TNM staging system via C-index.

Results

Based on the CPHR model, eight prognostic predictors were screened and entered into the nomogram. The prognostic model showed better performance (p<0.01) in terms of DFS prediction (C-index: 0.738; 95% CI: 0.698-0.779) than the eighth edition of the AJCC TNM staging system (C-index: 0.644; 95% CI: 0.604-0.684). Stratification into three risk groups highlighted significant differences between the survival curves in the training cohort and those in the validation cohort. The calibration curves for likelihood of 3- and 5-year DFS indicated optimal agreement between nomogram predictions and actual observations.

Conclusion

We constructed and externally validated a novel nomogram scoring system for individualized DFS estimation in BC patients treated with NCT. This user-friendly predictive tool may help oncologists to make optimal clinical decisions.

Recurrent Ovarian Cancer: The Role of Radiation Therapy

OBJECTIVE

The aim of this review was to present the current radiation therapy status in recurrent ovarian cancer (OC) and explore potential solution to improve clinical outcomes in this setting of patients.

MATERIALS AND METHODS

PubMed search was performed. An attempt was made to include all relevant studies. Pertinent references cited in selected articles were also considered.

RESULTS

The role of radiation therapy in recurrent OC needs to be defined. This is the largest reported analysis of published data.

CONCLUSIONS

Chemotherapy is the mainstay of recurrent OC treatment but prognosis remains very poor, and novel therapies are required to be integrated into this consolidated treatment regimen. Radiation therapy represents a valid alternative approach, even if no clear guidelines are available concerning it.

Recurrent ovarian cancer

Recurrence still occurs in a majority of patients with advanced ovarian cancer. However, progress in the management has allowed a significant prolongation of survival for relapsing disease. These last years, the field of interest has moved from chemotherapy to targeted therapy which is dominated by anti-angiogenic and anti-PARP agents. It is assumed that platinum-free interval will not remain the main prognostic and predictive criterion in the future, and will be replaced by a multi-factorial approach. This trend for personalization of therapy has highlighted important neglected fields for clinical research such as multi-line (≥3) relapse, frail patients including elderly and symptomatic and supportive measures.

Fifth Ovarian Cancer Consensus Conference of the Gynecologic Cancer InterGroup: recurrent disease

This manuscript reports the consensus statements regarding recurrent ovarian cancer (ROC), reached at the fifth Ovarian Cancer Consensus Conference (OCCC), which was held in Tokyo, Japan, in November 2015. Three important questions were identified: (i) What are the subgroups for clinical trials in ROC? The historical definition of using platinum-free interval (PFI) to categorise patients as having platinum-sensitive/resistant disease was replaced by therapy-free interval (TFI). TFI can be broken down into TFIp (PFI), TFInp (non-PFI) and TFIb (biological agent-free interval). Additional criteria to consider include histology, BRCA mutation status, number/type of previous therapies, outcome of prior surgery and patient reported symptoms. (ii) What are the control arms for clinical trials in ROC? When platinum is considered the best option, the control arm should be a platinum-based therapy with or without an anti-angiogenic agent or a poly (ADP-ribose) polymerase (PARP) inhibitor. If platinum is not considered the best option, the control arm could include a non-platinum drug, either as single agent or in combination. (iii) What are the endpoints for clinical trials in ROC? Overall survival (OS) is the preferred endpoint for patient cohorts with an expected median OS < or = 12 months. Progression-free survival (PFS) is an alternative, and it is the preferred endpoint when the expected median OS is > 12 months. However, PFS alone should not be the only endpoint and must be supported by additional endpoints including pre-defined patient reported outcomes (PROs), time to second subsequent therapy (TSST), or time until definitive deterioration of quality of life (TUDD).

A novel nomogram based on LODDS to predict the prognosis of epithelial ovarian cancer

BACKGROUND

To develop and validate a nomogram based on log of odds between the number of positive lymph node and the number of negative lymph node (LODDS) in predicting the overall survival (OS) and cancer specific survival (CSS) for epithelial ovarian cancer (EOC) patients.

MATERIALS AND METHODS

A total of 10,692 post-operative EOC patients diagnosed between 2004 and 2013 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly divided into training (n = 7,021) and validation (n = 3,671) cohorts. Multiple clinical pathological parameters were assessed and compared with outcomes. Parameters significantly correlating with outcomes were used to build a nomogram. Bootstrap validation was subsequently used to assess the predictive value of the model.

RESULTS

In the training set, age at diagnosis, race, marital status, tumor location, stage, grade and LODDS were correlated significantly with outcome in both the univariate and multivariate analyses and were used to develop a nomogram. The nomogram demonstrated good accuracy in predicting OS and CSS, with a bootstrap-corrected concordance index of 0.757 (95% CI, 0.746-0.768) for OS and 0.770 (95% CI, 0.759-0.782) for CSS. Notably, in this population our model performed favorably compared to the currently utilized Federation of Gynecology and Obstetrics (FIGO) model, with concordance indices of 0.699 (95% CI, 0.688-0.710, P < 0.05) and 0.719 (95% CI, 0.709- 0.730, P < 0.05) for OS and CSS, respectively. Using our nomogram in the validation cohort, the C-indices were 0.757 (95% CI, 0.741-0.773, P < 0.05, compared to FIGO) for OS and 0.762 (95% CI, 0.746-0.779, P < 0.05, compared to FIGO) for CSS.

CONCLUSIONS

LODDS works as an independent prognostic factor for predicting survival in patients with EOC regardless of the tumor stage. By incorporating LODDS, our nomogram may be superior to the currently utilized FIGO staging system in predicting OS and CSS among post-operative EOC patients.

Secondary cytoreductive surgery in recurrent epithelial ovarian cancer: A prognostic analysis with 103 cases

BACKGROUND

Due to satisfactory cytoreductive surgery combined with platinum-based chemotherapy in epithelial ovarian cancer has improved greatly, however, the relapse rate also high. In current study, we analyzed prognostic factors related to secondary cytoreductive surgery in patients with recurrent epithelial ovarian cancer.

METHODS

Clinical and follow-up data from 103 patients with recurrent epithelial ovarian cancer who received secondary cytoreductive surgery and were admitted to our hospital between January 2000 and December 2008 were analyzed.

RESULTS

Median survival after recurrence (RS) after the first relapse for the 103 patients was 36 months, and median overall survival (OS) was 60 months. Patients without visible residual tumors after secondary cytoreductive surgery had longer RS and OS compared to those with residual tumors ≥1 cm. The RS and OS of patients without visible residual tumors after secondary cytoreductive surgery were not significantly different compared to those with residual tumors between 0.1 and 1 cm. Patients with disease free interval (DFI) ≥ 12 months at secondary cytoreductive surgery had longer RS and OS compared to those with DFI < 12 months. Patients with one recurrent lesion had longer RS and OS compared to those with more than one lesion.

CONCLUSIONS

Residual tumor at secondary cytoreductive surgery, DFI and number of lesions were independent prognostic factors for secondary cytoreductive surgery in patients with epithelial ovarian cancer. Patients with DFI ≥12 months and a single lesion had better prognosis for achieving satisfactory cytoreduction, especially the absence of visible residual tumors.

Exploratory Analysis of TP53 Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study

BACKGROUND

Circulating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic TP53 mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP).

METHODS AND FINDINGS

We performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific TP53 assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The TP53 mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP. The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%-22%) compared to 0.7% (IQR 0.3%-2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson r = 0.59, p < 0.001), and this correlation improved when patients with ascites were excluded (r = 0.82). The ratio of TP53MAF to volume of disease was higher in relapsed patients (0.04% per cm3) than in untreated patients (0.0008% per cm3, p = 0.004). In nearly all relapsed patients with disease volume > 32 cm3, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28-54) compared with a median time to nadir of 84 d (IQR 42-116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07-0.67, p = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%-92%) and 88% specificity (95% CI 64%-99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort.

CONCLUSIONS

In this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.

Exploratory Analysis of TP53 Mutations in Circulating Tumour DNA as Biomarkers of Treatment Response for Patients with Relapsed High-Grade Serous Ovarian Carcinoma: A Retrospective Study

BACKGROUND

Circulating tumour DNA (ctDNA) carrying tumour-specific sequence alterations may provide a minimally invasive means to dynamically assess tumour burden and response to treatment in cancer patients. Somatic TP53 mutations are a defining feature of high-grade serous ovarian carcinoma (HGSOC). We tested whether these mutations could be used as personalised markers to monitor tumour burden and early changes as a predictor of response and time to progression (TTP).

METHODS AND FINDINGS

We performed a retrospective analysis of serial plasma samples collected during routine clinical visits from 40 patients with HGSOC undergoing heterogeneous standard of care treatment. Patient-specific TP53 assays were developed for 31 unique mutations identified in formalin-fixed paraffin-embedded tumour DNA from these patients. These assays were used to quantify ctDNA in 318 plasma samples using microfluidic digital PCR. The TP53 mutant allele fraction (TP53MAF) was compared to serum CA-125, the current gold-standard response marker for HGSOC in blood, as well as to disease volume on computed tomography scans by volumetric analysis. Changes after one cycle of treatment were compared with TTP. The median TP53MAF prior to treatment in 51 relapsed treatment courses was 8% (interquartile range [IQR] 1.2%-22%) compared to 0.7% (IQR 0.3%-2.0%) for seven untreated newly diagnosed stage IIIC/IV patients. TP53MAF correlated with volumetric measurements (Pearson r = 0.59, p < 0.001), and this correlation improved when patients with ascites were excluded (r = 0.82). The ratio of TP53MAF to volume of disease was higher in relapsed patients (0.04% per cm3) than in untreated patients (0.0008% per cm3, p = 0.004). In nearly all relapsed patients with disease volume > 32 cm3, ctDNA was detected at ≥20 amplifiable copies per millilitre of plasma. In 49 treatment courses for relapsed disease, pre-treatment TP53MAF concentration, but not CA-125, was associated with TTP. Response to chemotherapy was seen earlier with ctDNA, with a median time to nadir of 37 d (IQR 28-54) compared with a median time to nadir of 84 d (IQR 42-116) for CA-125. In 32 relapsed treatment courses evaluable for response after one cycle of chemotherapy, a decrease in TP53MAF of >60% was an independent predictor of TTP in multivariable analysis (hazard ratio 0.22, 95% CI 0.07-0.67, p = 0.008). Conversely, a decrease in TP53MAF of ≤60% was associated with poor response and identified cases with TTP < 6 mo with 71% sensitivity (95% CI 42%-92%) and 88% specificity (95% CI 64%-99%). Specificity was improved when patients with recent drainage of ascites were excluded. Ascites drainage led to a reduction of TP53MAF concentration. The limitations of this study include retrospective design, small sample size, and heterogeneity of treatment within the cohort.

CONCLUSIONS

In this retrospective study, we demonstrated that ctDNA is correlated with volume of disease at the start of treatment in women with HGSOC and that a decrease of ≤60% in TP53MAF after one cycle of chemotherapy was associated with shorter TTP. These results provide evidence that ctDNA has the potential to be a highly specific early molecular response marker in HGSOC and warrants further investigation in larger cohorts receiving uniform treatment.

Nomograms Predicting Platinum Sensitivity, Progression-Free Survival, and Overall Survival Using Pretreatment Complete Blood Cell Counts in Epithelial Ovarian Cancer

Purpose

This study was conducted to evaluate the prognostic significance of pre-treatment complete blood cell count (CBC), including white blood cell (WBC) differential, in epithelial ovarian cancer (EOC) patients with primary debulking surgery (PDS) and to develop nomograms for platinum sensitivity, progression-free survival (PFS), and overall survival (OS).

Materials and Methods

We retrospectively reviewed the records of 757 patients with EOC whose primary treatment consisted of surgical debulking and chemotherapy at Samsung Medical Center from 2002 to 2012. We subsequently created nomograms for platinum sensitivity, 3-year PFS, and 5-year OS as prediction models for prognostic variables including age, stage, grade, cancer antigen 125 level, residual disease after PDS, and pre-treatment WBC differential counts. The models were then validated by 10-fold cross-validation (CV).

Results

In addition to stage and residual disease after PDS, which are known predictors, lymphocyte and monocyte count were found to be significant prognostic factors for platinum-sensitivity, platelet count for PFS, and neutrophil count for OS on multivariate analysis. The area under the curves of platinum sensitivity, 3-year PFS, and 5-year OS calculated by the 10-fold CV procedure were 0.7405, 0.8159, and 0.815, respectively.

Conclusion

Prognostic factors including pre-treatment CBC were used to develop nomograms for platinum sensitivity, 3-year PFS, and 5-year OS of patients with EOC. These nomograms can be used to better estimate individual outcomes.

Incorporation of postoperative CT data into clinical models to predict 5-year overall and recurrence free survival after primary cytoreductive surgery for advanced ovarian cancer

PURPOSE

The use of multivariable clinical models to assess postoperative prognosis in ovarian cancer increased. All published models incorporate surgical debulking. However, postoperative CT can detect residual disease (CT-RD) in 40% of optimally resected patients. The aim of our study was to investigate the added value of incorporating CT-RD evaluation into clinical models for assessment of overall survival (OS) and progression free survival (PFS) in patients after primary cytoreductive surgery (PCS).

METHODS

212 women with PCS for advanced ovarian cancer between 01/1997 and 12/2011, and a contrast enhanced abdominal CT 1-7 weeks after surgery were included in this IRB approved retrospective study. Two radiologists blinded to clinical data, evaluated all CT for the presence of CT-RD, and Cohen's kappa assessed agreement. Cox proportional hazards regression with stepwise selection was used to develop OS and PFS models, with CT-RD incorporated afterwards. Model fit was assessed with bootstrapped Concordance Probability Estimates (CPE), accounting for over-fitting bias by correcting the initial estimate after repeated subsampling.

RESULTS

Readers agreed on the majority of cases (179/212, k=0.68). For OS and PFS, CT-RD was significant after adjusting for clinical factors with a CPE 0.663 (p=0.0264) and 0.649 (p=0.0008). CT-RD was detected in 37% of patients assessed as optimally debulked (RD<1cm) and increased the risk of death (HR: 1.58, 95% CI: 1.06-2.37%).

CONCLUSION

CT-RD is a significant predictor after adjusting for clinical factors for both OS and PFS. Incorporating CT-RD into the clinical model improved the prediction of OS and PFS in patients after PCS for advanced ovarian cancer.

A prognostic nomogram to predict overall survival in women with recurrent ovarian cancer treated with bevacizumab and chemotherapy

OBJECTIVE

To develop a nomogram to predict overall survival (OS) in women with recurrent ovarian cancer treated with bevacizumab and chemotherapy.

METHODS

A multicenter retrospective study was conducted. Potential prognostic variables included age; stage; grade; histology; performance status; residual disease; presence of ascites and/or pleural effusions; number of chemotherapy regimens, treatment-free interval (TFI) prior to bevacizumab administration, and platinum sensitivity. Multivariate analysis was performed using Cox proportional hazards regression. The predictive model was developed into a nomogram to predict five-year OS.

RESULTS

312 women with recurrent ovarian cancer treated with bevacizumab and chemotherapy were identified; median age was 59 (range: 19-85); 86% women had advanced stage (III-IV) disease. The majority had serous histology (74%), high grade cancers (93.5%), and optimal cytoreductions (69.5%). Fifty-one percent of women received greater than two prior chemotherapeutic regimens. TFI (AHR=0.98, 95% CI 0.97-1.00, p=0.022) was the only statistically significant predictor in a multivariate progression-free survival (PFS) analysis. In a multivariate OS analysis, prior number of chemotherapy regimens, TFI, platinum sensitivity, and presence of ascites were significant. A nomogram to predict five-year OS was constructed and internally validated (bootstrap-corrected concordance index=0.737).

CONCLUSION

Our multivariate model identified prior number of chemotherapy regimens, TFI, platinum sensitivity, and the presence of ascites as prognostic variables for OS in women with recurrent ovarian cancer treated with bevacizumab combined with chemotherapy. Our nomogram to predict five-year OS may be used to identify women who may benefit from bevacizumab and chemotherapy, but further validation is needed.

Cost-effectiveness of adding bevacizumab to first line therapy for patients with advanced ovarian cancer

OBJECTIVE

To evaluate, from a societal perspective, the cost-effectiveness of adding bevacizumab to first-line therapy based on outcomes from the GOG-218 and ICON-7 trials.

METHODS

A three-state Markov model was used. The time horizon was until the death of 99% of the initial cohort of 1000 individuals. Costs and quality-adjusted life-years (QALYs) were discounted at an annual rate of 3%. All costs were adjusted to 2013 USD. The incremental cost-effectiveness ratio (ICER) was reported as incremental cost per QALY gained. The robustness of the result was checked with one-way sensitivity analyses and for relevant clinical situations (i.e. varying the drug of choice to treat cancer recurrence). Subgroup analysis was conducted to identify subgroup of population for whom the strategy could be cost-effective. The potential impact of biosimilar bevacizumab was considered, using a 30% price reduction.

RESULTS

For the GOG-218 study protocol, widely followed in US, the addition of bevacizumab results in an ICER of $2,420,691/QALY. For the ICON-7 study protocol, the ICER is $225,515/QALY. The results of the model were sensitive to the quality of life (QoL) and the median progression free survival (PFS). Biosimilar bevacizumab didn't reduce cost sufficiently to change conclusions. First-line augmentation is cost-effective, with biosimilar bevacizumab, for stage IV patients ($126,169/QALY), ECOG PS1 patients ($116,575/QALY) and for patients with suboptimal residual disease ($122,822/QALY) as per the ICON-7 protocol.

CONCLUSION

Addition of bevacizumab, by in large, is cost-ineffective. It can become cost-effective with the ICON-7 protocol, in patients at high risk of progression using biosimilar bevacizumab.