Pre-treatment thrombocytosis and ovarian cancer survival: A meta-analysis

An association between thrombocytosis and cancer progression and decreased survival has been observed for various forms of cancer. The aim of this study was to evaluate the impact of pre-treatment thrombocytosis on ovarian cancer survival. Medline, Scopus, Clinicaltrials.gov, Cochrane Central Register of Controlled Trials CENTRAL and Google Scholar were searched systematically for studies that compared survival outcomes of patients with ovarian cancer who had pre-treatment thrombocytosis with survival outcomes of patients with normal platelet counts. Fourteen articles were retrieved, with a total of 5414 patients with ovarian cancer. The methodological quality of included studies ranged between moderate and high. Patients with advanced stage disease were more likely to have pre-treatment thrombocytosis, and this was associated with lower rates of optimal debulking. Thrombocytosis was also associated with increased likelihood of recurrence of ovarian cancer [hazard ratio (HR) 2.01, 95 % confidence interval (CI) 1.34-3.01] and increased risk of death from ovarian cancer (HR 2.29, 95 % CI 1.35-3.90). The incidence of deep vein thrombosis was comparable in both groups (odds ratio 1.62, 95 % CI 0.48-5.46). Considering these findings, it is evident that pre-treatment thrombocytosis in patients with ovarian cancer is associated with increased risk of recurrence and death. Pre-treatment thrombocytosis is a potential sign of advanced stage disease, and may be predictive of suboptimal tumour debulking during surgery. Its association with other factors that affect survival, including platinum resistance and response to targeted therapy, remains poorly explored, although preliminary data suggest a potential correlation.

Development and Internal Validation of Nomograms for Survival of Advanced Epithelial Ovarian Cancer Based on Established Prognostic Factors and Hematologic Parameters

Objective: To assess the association between pretreatment thrombocytosis, anemia, and leukocytosis and overall survival (OS) of advanced-stage EOC. Furthermore, to develop nomograms using established prognostic factors and pretreatment hematologic parameters to predict the OS of advanced EOC patients. Methods: Advanced-stage EOC patients treated between January 1996 and January 2010 in eastern Netherlands were included. Survival outcomes were compared between patients with and without pretreatment thrombocytosis (≥450,000 platelets/µL), anemia (hemoglobin level of <7.5 mmol/L), or leukocytosis (≥11.0 × 109 leukocytes/L). Three nomograms (for ≤3-, ≥5-, and ≥10-year OS) were developed. Candidate predictors were fitted into multivariable logistic regression models. Multiple imputation was conducted. Model performance was assessed on calibration, discrimination, and Brier scores. Bootstrap validation was used to correct for model optimism. Results: A total of 773 advanced-stage (i.e., FIGO stages IIB-IV) EOC patients were included. The median [interquartile range, IQR] OS was 2.3 [1.3-4.2] and 3.0 [1.4-7.0] years for patients with and without pretreatment thrombocytosis (p < 0.01). The median OS was not notably different for patients with and without pretreatment leukocytosis (p = 0.58) or patients with and without pretreatment anemia (p = 0.07). The final nomograms comprised established predictors with either pretreatment leukocyte or platelet count. The ≥5- and ≥10-year OS models demonstrated good calibration and adequate discrimination with optimism-corrected c-indices [95%-CI] of 0.76 [0.72-0.80] and 0.78 [0.73-0.83], respectively. The ≤3-year OS model demonstrated suboptimal performance with an optimism-corrected c-index of 0.71 [0.66-0.75]. Conclusions: Pretreatment thrombocytosis is associated with poorer EOC survival. Two well-performing models predictive of ≥5-year and ≥10-year OS in advanced-stage EOC were developed and internally validated.

Incidence and predictors for chemotherapy modifications and their impact on the outcome of ovarian cancer patients

PURPOSE

Chemotherapy (CTX) is an important part of the treatment strategy of stage II-IV ovarian cancer. CTX modifications, such as delays, dose reductions or premature terminations might have a negative impact on overall survival (OS) and progression free survival (PFS). The goal of this study was to determine the incidence and predictors of CTX modifications and their influence on survival.

METHODS

An observational retrospective cohort analysis of 192 ovarian cancer patients who were treated at the Department of Obstetrics and Gynaecology, Technical University Munich, Germany, according to international guidelines was performed including from 2009 to 2013. A potential association between patient and disease characteristics and CTX modifications was tested with multivariate logistic regression. OS and PFS were estimated by Kaplan-Meier analysis.

RESULTS

44.8% (86/192) received a modification of CTX. 34 (17.7%) women discontinued CTX prematurely, 17 (8.9%) underwent a dose reduction, 16 (8.3%) experienced a CTX delay and 10 (5.2%) had both a delay and a dose modification. In nine (4.7%) patients, the dose needed to be divided. Leukopenia (p < 0.001) and anaemia (p = 0.003) were significantly more common in patients with CTX modifications. Significant predictors for CTX modifications were a history of thrombosis or embolism (p < 0.001) and residual tumour postoperatively (p = 0.003). Patients with CTX modifications showed a significantly lower OS as well as PFS (p < 0.001), even after adjustment for prognostic factors such as age, body-mass-index, residual tumour, histology, FIGO stage and grading (p = 0.005 for OS and p = 0.001 for PFS).

CONCLUSION

CTX modifications have a negative impact on survival. Significant predictors for such modifications are a history of thrombosis or embolism and the presence of residual postoperative tumour. Further studies are needed to avoid CTX modifications and to improve survival of ovarian cancer patients.

The Use of Artificial Intelligence for Complete Cytoreduction Prediction in Epithelial Ovarian Cancer: A Narrative Review

INTRODUCTION

In patients affected by epithelial ovarian cancer (EOC) complete cytoreduction (CC) has been associated with higher survival outcomes. Artificial intelligence (AI) systems have proved clinical benefice in different areas of healthcare.

OBJECTIVE

To systematically assemble and analyze the available literature on the use of AI in patients affected by EOC to evaluate its applicability to predict CC compared to traditional statistics.

MATERIAL AND METHODS

Data search was carried out through PubMed, Scopus, Ovid MEDLINE, Cochrane Library, EMBASE, international congresses and clinical trials. The main search terms were: Artificial Intelligence AND surgery/cytoreduction AND ovarian cancer. Two authors independently performed the search by October 2022 and evaluated the eligibility criteria. Studies were included when data about Artificial Intelligence and methodological data were detailed.

RESULTS

A total of 1899 cases were analyzed. Survival data were reported in 2 articles: 92% of 5-years overall survival (OS) and 73% of 2-years OS. The median area under the curve (AUC) resulted 0,62. The model accuracy for surgical resection reported in two articles reported was 77,7% and 65,8% respectively while the median AUC was 0,81. On average 8 variables were inserted in the algorithms. The most used parameters were age and Ca125.

DISCUSSION

AI revealed greater accuracy compared against the logistic regression models data. Survival predictive accuracy and AUC were lower for advanced ovarian cancers. One study analyzed the importance of factors predicting CC in recurrent epithelial ovarian cancer and disease free interval, retroperitoneal recurrence, residual disease at primary surgery and stage represented the main influencing factors. Surgical Complexity Scores resulted to be more useful in the algorithms than pre-operating imaging.

CONCLUSION

AI showed better prognostic accuracy if compared to conventional algorithms. However further studies are needed to compare the impact of different AI methods and variables and to provide survival informations.

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&lt;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.

Feature Selection is Critical for 2-Year Prognosis in Advanced Stage High Grade Serous Ovarian Cancer by Using Machine Learning

Introduction

Accurate prediction of patient prognosis can be especially useful for the selection of best treatment protocols. Machine Learning can serve this purpose by making predictions based upon generalizable clinical patterns embedded within learning datasets. We designed a study to support the feature selection for the 2-year prognostic period and compared the performance of several Machine Learning prediction algorithms for accurate 2-year prognosis estimation in advanced-stage high grade serous ovarian cancer (HGSOC) patients.

Methods

The prognosis estimation was formulated as a binary classification problem. Dataset was split into training and test cohorts with repeated random sampling until there was no significant difference (p = 0.20) between the two cohorts. A ten-fold cross-validation was applied. Various state-of-the-art supervised classifiers were used. For feature selection, in addition to the exhaustive search for the best combination of features, we used the-chi square test of independence and the MRMR method.

Results

Two hundred nine patients were identified. The model's mean prediction accuracy reached 73%. We demonstrated that Support-Vector-Machine and Ensemble Subspace Discriminant algorithms outperformed Logistic Regression in accuracy indices. The probability of achieving a cancer-free state was maximised with a combination of primary cytoreduction, good performance status and maximal surgical effort (AUC 0.63). Standard chemotherapy, performance status, tumour load and residual disease were consistently predictive of the mid-term overall survival (AUC 0.63–0.66). The model recall and precision were greater than 80%.

Conclusion

Machine Learning appears to be promising for accurate prognosis estimation. Appropriate feature selection is required when building an HGSOC model for 2-year prognosis prediction. We provide evidence as to what combination of prognosticators leads to the largest impact on the HGSOC 2-year prognosis.

Predictors of Survival Outcomes After Primary Treatment of Epithelial Ovarian Cancer in Lagos, Nigeria

PURPOSE

This study was designed to investigate the clinicopathologic predictors of progression-free survival (PFS) and overall survival (OS) in patients with epithelial ovarian cancer (EOC) following primary treatment in Lagos, Nigeria.

MATERIALS AND METHODS

Using data from a retrospective cohort of 126 patients who received treatment for EOC between 2010 and 2018, we identified 83 patients with a complete clinical record for subsequent data analysis. Patients' demographics and updated 2-year follow-up status were abstracted from medical records. Kaplan-Meier survival curves were compared using the log-rank test, and Cox proportional hazard models were used for multivariate analysis to identify independent predictors of survivals following treatment in EOC patients.

RESULTS

The median PFS and OS were 12 and 24 months, respectively. After adjusting for covariates in the multivariate analysis, younger age ≤ 55 years (hazard ratio [HR] = 0.40; 95% CI, 0.22 to 0.74; P = .01) and International Federation of Gynecology and Obstetrics (FIGO) stage I/II (HR = 0.02; 95% CI, 0.01 to 0.08; P = .01) were independent predictors of improved PFS, whereas being premenopausal (HR = 2.34; 95% CI, 1.16 to 4.75; P = .02) was an independent predictor of reduced OS after 2-year follow-up.

CONCLUSION

PFS could be predicted by the age and FIGO stage of the disease, whereas menopausal status was predictive of OS in patients with EOC. This knowledge should form the basis for counseling patients with ovarian cancer during their primary treatment and lend support to the importance of aggressive follow-up and monitoring for the older, premenopausal patients and those with an advanced stage of epithelial ovarian cancer. However, robust longitudinal research should be carried out to provide additional reliable insight to this information.

Development of Machine Learning Models to Predict Platinum Sensitivity of High-Grade Serous Ovarian Carcinoma

To support the implementation of individualized disease management, we aimed to develop machine learning models predicting platinum sensitivity in patients with high-grade serous ovarian carcinoma (HGSOC). We reviewed the medical records of 1002 eligible patients. Patients' clinicopathologic characteristics, surgical findings, details of chemotherapy, treatment response, and survival outcomes were collected. Using the stepwise selection method, based on the area under the receiver operating characteristic curve (AUC) values, six variables associated with platinum sensitivity were selected: age, initial serum CA-125 levels, neoadjuvant chemotherapy, pelvic lymph node status, involvement of pelvic tissue other than the uterus and tubes, and involvement of the small bowel and mesentery. Based on these variables, predictive models were constructed using four machine learning algorithms, logistic regression (LR), random forest, support vector machine, and deep neural network; the model performance was evaluated with the five-fold cross-validation method. The LR-based model performed best at identifying platinum-resistant cases with an AUC of 0.741. Adding the FIGO stage and residual tumor size after debulking surgery did not improve model performance. Based on the six-variable LR model, we also developed a web-based nomogram. The presented models may be useful in clinical practice and research.

Development and validation for prognostic nomogram of epithelial ovarian cancer recurrence based on circulating tumor cells and epithelial-mesenchymal transition

We aimed to determine the prognosis value of circulating tumor cells (CTCs) undergoing epithelial–mesenchymal transition in epithelial ovarian cancer (EOC) recurrence. We used CanPatrol CTC-enrichment technique to detect CTCs from blood samples and classify subpopulations into epithelial, mesenchymal, and hybrids. To construct nomogram, prognostic factors were selected by Cox regression analysis. Risk stratification was performed through Kaplan–Meier analysis among the training group (n = 114) and validation group (n = 38). By regression screening, both CTC counts (HR 1.187; 95% CI 1.098–1.752; p = 0.012) and M-CTC (HR 1.098; 95% CI 1.047–1.320; p = 0.009) were demonstrated as independent factors for recurrence. Other variables including pathological grade, FIGO stage, lymph node metastasis, ascites, and CA-125 were also selected (p < 0.005) to construct nomogram. The C-index of internal and external validation for nomogram was 0.913 and 0.874. We found significant predictive values for the nomogram with/without CTCs (AUC 0.8705 and 0.8097). Taking CTC counts and M-CTC into separation, the values were 0.8075 and 0.8262. Finally, survival curves of risk stratification based on CTC counts (p = 0.0241), M-CTC (p = 0.0107), and the nomogram (p = 0.0021) were drawn with significant differences. In conclusion, CTCs could serve as a novel factor for EOC prognosis. Nomogram model constructed by CTCs and other clinical parameters could predict EOC recurrence and perform risk stratification for clinical decision-making.

Trial registration Chinese Clinical Trial Registry, ChiCTR-DDD-16009601, October 25, 2016.

The Prevalence, Associated Factors for Lung Metastases Development and Prognosis in Ovarian Serous Cancer Based on SEER Database

Ovarian carcinoma (OC) is one of the 3 most common gynecological malignancies, and the prognosis of patients with lung metastasis was the worst. SEER documented OC patients, diagnosed between 2010 and 2016, were included in the study. Univariable and multivariable logistic regression analyses were performed to identify associated factors for lung metastases (LM) development. Kaplan–Meier analysis was used to estimate the overall survival for OC patients with LM. A total of 10146 eligible serous ovarian cancer (SOC) patients were included, the prevalence of LM was 3.77% (N = 378). Patients with T4 stage (χ² = 128.515; P = 0.000), N1 stage (χ² = 49.536; P = 0.000), right laterality (χ² = 18.756; P = 0.000) (compared with left side), undifferentiated grade (χ² = 36.174; P = 0.000), bone metastasis (χ² = 183.529); P = 0.000), brain metastasis (χ² = 117.539; P = 0.000), liver metastasis (χ² = 442.472; P = 0.000) had a larger probability of LM than other groups. Results showed that T3/N1 stage, bone metastases, liver metastases, chemotherapy, surgery were positively correlated with LM. Multivariable cox analysis showed that age, bone metastasis, no chemotherapy, no surgery were independent risk factors in SOC-LM patients. This study provided new research insights on the prevalent LM in patients with SOC. The factors associated with LM development and prognosis can be potentially used for LM early screening and professional care.

Low Red Blood Cell Count as an Early Indicator for Myometrial Invasion in Women with Endometrioid Endometrial Carcinoma with Metabolic Syndrome

Purpose

We investigated the relationship between metabolic syndrome (MetS) and its components and erythrocyte parameters such as red blood cell count (RBC) and hemoglobin (Hb) levels, and their association with the risk of deep myometrial invasion in endometrioid endometrial carcinoma (EEC).

Patients and Methods

A total of 473 women diagnosed with EEC between January 2012 and December 2018 were included in the study. MetS was diagnosed using a modified version of the Chinese Diabetes Society 2004 criteria. Demographic and clinical characteristics were stratified by MetS and compared. Logistic regression analyses were performed to calculate the odds ratios (ORs) of myometrial invasion.

Results

The prevalence of MetS was 18.8% (89/473). RBC and Hb levels were significantly higher in EEC patients with MetS. RBC and Hb values increased linearly with the number of MetS components. The OR of the MetS risk increased across the RBC quartiles (OR=2.212, 95% confidence interval [Cl]=1.125-4.350, P˂0.05). Among EEC patients with MetS, the OR of deep myometrial invasion increased with the decrease of the RBC quartiles (P=0.037). Similarly, in EEC patients with obesity and hyperglycemia or with ≥2 MetS criteria, the lowest RBC level (Q1) was a risk factor for deep myometrial invasion compared with the reference RBC group (Q4, P˂0.05). However, this trend was not evident in EEC patients without MetS and its components.

Conclusion

EEC with MetS and its components had higher RBC and Hb levels. The association between the erythrocyte parameters and myometrial invasion differed with MetS. RBC was identified as a risk factor of myometrial invasion in EEC patients with MetS and its components.

Platelets, Thrombocytosis, and Ovarian Cancer Prognosis: Surveying the Landscape of the Literature

Platelets are critical components of a number of physiologic processes, including tissue remodeling after injury, wound healing, and maintenance of vascular integrity. Increasing evidence suggests that platelets may also play important roles in cancer. In ovarian cancer, thrombocytosis, both at the time of initial diagnosis and at recurrence, has been associated with poorer prognosis. This review describes current evidence for associations between thrombocytosis and ovarian cancer prognosis and discusses the clinical relevance of platelet count thresholds and timing of assessment. In addition, we discuss several mechanisms from in vitro, in vivo, and clinical studies that may underlie these associations and recommend potential approaches for novel therapeutic targets for this lethal disease.

Thrombocytosis as a Biomarker in Type II, Non-Endometrioid Endometrial Cancer

Thrombocytosis (platelets ≥ 400K) is a common hematologic finding in gynecologic malignancies and associated with worse outcomes. Limited data exist on the prognostic capability of thrombocytosis in women with high-grade endometrial cancer (EC). Our objective was to describe the associations between elevated platelets at diagnosis, clinicopathologic features, and survival outcomes among women with high-grade, non-endometrioid EC. A review of the institutional cancer registry was performed to identify these women treated between 2005 and 2017. Sociodemographic, clinical, and outcomes data were collected. Analyses were performed using chi-square tests, Cox proportional hazards models, and the Kaplan–Meier method. A total of 271 women were included in the analysis. A total of 19.3% of women had thrombocytosis at diagnosis. Thrombocytosis was associated with reduced median overall survival (OS) compared with those not displaying thrombocytosis (29.4 months vs. 60 months, p < 0.01). This finding was most pronounced in uterine serous carcinoma (16.4 months with thrombocytosis vs. 34.4 months without, p < 0.01). While non-White women had shorter median OS for the whole cohort in the setting of thrombocytosis (29.4 months vs. 39.6 months, p < 0.01), among those with uterine serous carcinoma (USC), this finding was reversed, with decreased median OS in White women (22.1 vs. 16.4 months, p = 0.01). Thrombocytosis is concluded to have negative associations with OS and patient race.

Clinical Utility of Preoperative Assessment in Ovarian Cancer Cytoreduction

Ovarian cancer is the deadliest gynecologic cancer, in part due to late presentation. Many women have vague early symptoms and present with disseminated disease. Cytoreductive surgery can be extensive, involving multiple organ systems. Novel therapies and recent clinical trials have provided evidence that, compared to primary cytoreduction, neoadjuvant chemotherapy has equivalent survival outcomes with less morbidity. There is increasing need for validated tools and mechanisms for clinicians to determine the optimal management of ovarian cancer patients.

Can we predict who lives long with ovarian cancer?

Women with ovarian cancer benefit from individualized management that incorporates advanced imaging technologies, sophisticated cytoreductive surgery integrated with combination chemotherapy, genetic risk assessment, and tumor molecular profiling. However, advanced ovarian cancer remains a highly lethal disease because of early peritoneal dissemination, rapid development of resistance to key therapeutic agents, and evasion of the host immune response. Over the last 15 years, several models and nomograms have been developed to predict surgical outcomes, progression-free survival, or overall survival on the basis of clinical and pathologic data available at the primary diagnosis and recurrence. Each of these models has its strengths and limitations, and they provide a basis for future models that will incorporate functional imaging and molecular characteristics.

Prechemotherapy Hemoglobin Levels as a Predictive Factor of Ovarian Cancer Survival: A Systematic Review and Meta-Analysis

OBJECTIVES

The impact of anemia on cancer survival has been previously mentioned in various oncological fields. To date, however, it remains unknown whether prechemotherapy hemoglobin (Hgb) levels are predictive of ovarian cancer survival (OC). The purpose of the present systematic review is to accumulate evidence in this field.

MATERIALS AND METHODS

We used the Medline, Scopus, Clinicaltrials.gov, EMBASE, Cochrane Central Register of Controlled Trials CENTRAL, and Google Scholar databases in our primary search. The date of our last search was set for July 30, 2018. Statistical meta-analysis was performed with the RevMan 5.3 software.

RESULTS

Overall, 11 articles were included that recruited 1816 women with OC. Five articles that involved 856 OC patients were included in the meta-analysis. Compared with patients with anemia, patients with Hgb levels >12 g/dL had increased odds of overall survival (odds ratio, 1.72; 95% confidence interval: 1.41, 2.10). Similarly, the progression-free survival of patients was significantly affected, although the available data could not be accumulated in a meta-analysis because of the heterogeneity in outcome reporting measures.

CONCLUSIONS

Current evidence suggests that prechemotherapy Hgb levels below the threshold of 12 g/dL can potentially predict worse overall survival of OC patients. Future research is required in the field to elucidate whether several independent variables such as the stage and histology of disease and rates of optimal debulking affect the clinical significance of this association.

Hematologic Markers as Prognostic Factors in Nonmetastatic Esophageal Cancer Patients under Concurrent Chemoradiotherapy

Nonmetastatic esophageal cancer can demonstrate a high local recurrence rate even under the standard treatment. We evaluated platelet counts before and after concurrent chemoradiotherapy (CCRT), neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio for predicting esophageal cancer prognosis under CCRT. Newly diagnosed patients with esophageal cancer (stages IA–IIIC) who underwent CCRT during January 2013–December 2017 were enrolled. The data were collected retrospectively. Overall survival (OS), time to progressive disease (TPD), and time to metastasis (TM) were recorded for indicating prognosis. Kaplan–Meier curves were plotted and univariate and multivariate analyses were performed. In total, 105 patients were enrolled. The stages of esophageal cancer and surgery were associated with prognosis (i.e., OS, TPD, and TM). Based on TPD and TM, women had better prognosis than men. In the univariate analysis, high pre- and post-CCRT platelet counts (>300,000/μL), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) as well as low lymphocyte percentage were significantly associated with poor prognosis. However, in the multivariate analysis, only post-CCRT high platelet count (>300,000/μL) remained significantly associated with poor prognosis (P = .041, .045, and .023 for OS, TPD, and TM, respectively). Poor prognosis was observed in patients with high platelet counts, PLR, NLR, and low lymphocyte percentage. Surgery was an independent factor predicting better prognosis. Our findings may have clinical significance with regard to therapeutic decision-making.

[Perioperative care of epithelial ovarian cancer: Article drafted from the French Guidelines in oncology entitled "Initial management of patients with epithelial ovarian cancer" developed by FRANCOGYN, CNGOF, SFOG, GINECO-ARCAGY under the aegis of CNGOF and endorsed by INCa]

The following recommendations cover the perioperative management of ovarian, Fallopian tube and primary peritoneal cancers. Five questions related to pre-habilitation and enhanced recovery after surgery were evaluated. The conclusions and recommendations are based on an analysis of the level of evidence available in the literature. These recommendations are part of the overall recommendations for improving the management of ovarian, fallopian or primary peritoneal cancer, made with the support of INCa (Institut National du Cancer). The main preoperative measures are screening for nutritional deficiencies (Grade B) and for anaemia (GradeC) in patients with ovarian cancer. It is not possible to make recommendations on the correction of malnutrition and/or anemia or on the contribution of pre-operative immuno-nutrition due to the absence of data in ovarian cancer, tube cancer or primary peritoneum cancer. For the same reasons, no recommendation can be made on the value of preoperative digestive preparation in ovarian, fallopian tube or primary peritoneum cancer. During surgery, goal-directed fluid therapy for patients with advanced ovarian cancer is recommended (Grade B). A single dose infusion of tranexamic acid is recommended for patients with ovarian, fallopian tube or primary peritoneal cancer (GradeC). For postoperative analgesia, epidural analgesia is recommended for patients undergoing cyto-reduction surgery by laparotomy (Grade B). In the absence of epidural analgesia, patient controlled analgesia with morphine without continuous infusion (Grade B) is recommended. No recommendation can be given regarding intravenous administration of lidocaine and/or ketamine during surgery, or, regarding peri-operatively prescription of gabapentin or pregabalin. In the absence of studies on the impact of different non-opiate analgesic combinations for ovarian cancer surgery, no recommendations can be made. Early oral feeding is recommended, including in cases of digestive resection (Grade B). The implementation of enhanced recovery programs, including early mobilization, is recommended (GradeC).

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.

Development of Peritoneal Carcinomatosis in Epithelial Ovarian Cancer: A Review

Epithelial ovarian cancer (EOC) metastasizes intra-abdominally with often numerous, superficial, small-sized lesions. This so-called peritoneal carcinomatosis is difficult to treat, and peritoneal recurrences are frequently observed, leading to a poor prognosis. Underlying mechanisms of interactions between EOC and peritoneal cells are incompletely understood. This review summarizes and discusses the development of peritoneal carcinomatosis from a cell-biological perspective, focusing on characteristics of EOC and peritoneal cells. We aim to provide insight into how peritoneum facilitates tumor adhesion but limits size of lesions and depth of invasion. The development of peritoneal carcinomatosis is a multistep process that requires adaptations of EOC and peritoneal cells. Mechanisms that enable tumor adhesion and growth involve cadherin restructuring on EOC cells, integrin-mediated adhesion, and mesothelial evasion by mechanical forces driven by integrin-ligand interactions. Clinical trials targeting these mechanisms, however, showed only limited effects. Other factors that inhibit tumor growth and deep invasion are virtually unknown. Future studies are needed to elucidate the exact mechanisms that underlie the development and limited growth of peritoneal carcinomatosis. This review on development of peritoneal carcinomatosis of EOC summarizes the current knowledge and its limitations. Clarification of the stepwise process may inspire future research to investigate new treatment approaches of peritoneal carcinomatosis.

Impact of prognostic factors on survival rates in patients with ovarian carcinoma

PURPOSE

The aim of the present study was to invesitigate the impact of significant clinico-pathological prognostic factors on survival rates and to identify factors predictive of poor outcome in patients with ovarian carcinoma.

MATERIALS AND METHODS

A retrospective chart review of 74 women with pathologically proven ovarian carcinoma who were treated between January 2006 and April 2011 was performed. Patients were investigated with respect to survival to find the possible effects of age, gravida, parity, menstruel condition, pre-operative Ca-125, treatment period, cytologic washings, presence of ascites, tumor histology, stage and grade, maximal tumor diameter, adjuvan chemotherapy and cytoreductive success. Also 55 ovarian carcinoma patients were investigated with respect to prognostic factors for early 2-year survival.

RESULTS

The two-year survival rate was 69% and the 5-year survival rate was 25.5% for the whole study population. Significant factors for 2-year survival were preoperative CA-125 level, malignant cytology and FIGO clinical stage. Significant factors for 5-year survival were age, preoperative CA-125 level, residual tumor, lymph node metastases, histologic type of tumor, malignant cytology and FIGO clinical stage. Logistic regression revealed that independent prognostic factors of 5-year survival were patient age, lymph node metastasis and malignant cytology.

CONCLUSIONS

We consider quality registries with prospectively collected data to be one important tool in monitoring treatment effects in population-based cancer research.

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.

Retrospective analysis of the impact of platinum dose reduction and chemotherapy delays on the outcomes of stage III ovarian cancer patients

Background

Ovarian cancer is a common gynaecological malignancy still remaining a challenge to treat. The objective of this study was to evaluate the impact of platinum dose reduction and chemotherapy delays on progression free survival and overall survival in patients with stage III ovarian cancer and to analyze reasons for such chemotherapy scheme modifications.

Methods

Medical records of patients with FIGO stage III ovarian cancer were reviewed. Inclusion criteria involved FIGO stage III epithelial ovarian carcinoma; cytoreductive surgery performed and 6 courses of platinum-based chemotherapy completed; no neoadjuvant chemotherapy applied; and no history of previous malignancies. Progression free survival and overall survival were analyzed using Kaplan-Meier and Cox proportional hazards models.

Results

Significant 3.3 times higher death risk in patients who experienced only chemotherapy delays compared with patients who did not experience any chemotherapy scheme modifications was established (HR = 3.3, 95% Cl: 1.2 – 8.5, p = 0.016). Increased death risk in patients who experienced only chemotherapy delays compared with patients who experienced both chemotherapy delays and platinum dose reduction was also established (HR = 2.3, 95% Cl: 1.1 – 4.8, p = 0.021). Main reasons for chemotherapy scheme modifications (in decreasing order) were the following: neutropenia, modifications with no objective medical reasons, renal disorders, anaemia, poor performance status, gastrointestinal symptoms and neuropathy. Overall survival in patients who experienced chemotherapy scheme modifications with no objective medical reasons was non-inferior than in patients who did not experience any chemotherapy scheme modifications.

Conclusions

Chemotherapy delays in patients with FIGO stage III ovarian cancer caused lower overall survival. The most common reason for chemotherapy scheme modifications was neutropenia.

Risk of Ovarian Cancer Relapse score: a prognostic algorithm to predict relapse following treatment for advanced ovarian cancer

OBJECTIVE

The aim of this study was to construct a prognostic index that predicts risk of relapse in women who have completed first-line treatment for ovarian cancer (OC).

METHODS

A database of OC cases from 2000 to 2010 was interrogated for International Federation of Gynecology and Obstetrics stage, grade and histological subtype of cancer, preoperative and posttreatment CA-125 level, presence or absence of residual disease after cytoreductive surgery and on postchemotherapy computed tomography scan, and time to progression and death. The strongest predictors of relapse were included into an algorithm, the Risk of Ovarian Cancer Relapse (ROVAR) score.

RESULTS

Three hundred fifty-four cases of OC were analyzed to generate the ROVAR score. Factors selected were preoperative serum CA-125, International Federation of Gynecology and Obstetrics stage and grade of cancer, and presence of residual disease at posttreatment computed tomography scan. In the validation data set, the ROVAR score had a sensitivity and specificity of 94% and 61%, respectively. The concordance index for the validation data set was 0.91 (95% confidence interval, 0.85-0.96). The score allows patient stratification into low (<0.33), intermediate (0.34-0.67), and high (>0.67) probability of relapse.

CONCLUSIONS

The ROVAR score stratifies patients according to their risk of relapse following first-line treatment for OC. This can broadly facilitate the appropriate tailoring of posttreatment care and support.

Assessment of published models and prognostic variables in epithelial ovarian cancer at Mayo Clinic

OBJECTIVES

Epithelial ovarian cancer (EOC) is an aggressive disease in which first line therapy consists of a surgical staging/debulking procedure and platinum based chemotherapy. There is significant interest in clinically applicable, easy to use prognostic tools to estimate risk of recurrence and overall survival. In this study we used a large prospectively collected cohort of women with EOC to validate currently published models and assess prognostic variables.

METHODS

Women with invasive ovarian, peritoneal, or fallopian tube cancer diagnosed between 2000 and 2011 and prospectively enrolled into the Mayo Clinic Ovarian Cancer registry were identified. Demographics and known prognostic markers as well as epidemiologic exposure variables were abstracted from the medical record and collected via questionnaire. Six previously published models of overall and recurrence-free survival were assessed for external validity. In addition, predictors of outcome were assessed in our dataset.

RESULTS

Previously published models validated with a range of c-statistics (0.587-0.827), though application of models containing variables which are not part of routine practice were somewhat limited by missing data; utilization of all applicable models and comparison of results are suggested. Examination of prognostic variables identified only the presence of ascites and ASA score to be independent predictors of prognosis in our dataset, albeit with marginal gain in prognostic information, after accounting for stage and debulking.

CONCLUSIONS

Existing prognostic models for newly diagnosed EOC showed acceptable calibration in our cohort for clinical application. However, modeling of prospective variables in our dataset reiterates that stage and debulking remains the most important predictors of prognosis in this setting.

Prognosis and conditional disease-free survival among patients with ovarian cancer

PURPOSE

Traditional disease-free survival (DFS) does not reflect changes in prognosis over time. Conditional DFS accounts for elapsed time since achieving remission and may provide more relevant prognostic information for patients and clinicians. This study aimed to estimate conditional DFS among patients with ovarian cancer and to evaluate the impact of patient characteristics.

PATIENTS AND METHODS

Patients were recruited as part of the Hormones and Ovarian Cancer Prediction case-control study and were included in the current study if they had achieved remission after a diagnosis of cancer of the ovary, fallopian tube, or peritoneum (N = 404). Demographic and lifestyle information was collected at enrollment; disease, treatment, and outcome information was abstracted from medical records. DFS was calculated using the Kaplan-Meier method. Conditional DFS estimates were computed using cumulative DFS estimates.

RESULTS

Median DFS was 2.54 years (range, 0.03-9.96 years) and 3-year DFS was 48.2%. The probability of surviving an additional 3 years without recurrence, conditioned on having already survived 1, 2, 3, 4, and 5 years after remission, was 63.8%, 80.5%, 90.4%, 97.0%, and 97.7%, respectively. Initial differences in 3-year DFS at time of remission between age, stage, histology, and grade groups decreased over time.

CONCLUSION

DFS estimates for patients with ovarian cancer improved dramatically over time, in particular among those with poorer initial prognoses. Conditional DFS is a more relevant measure of prognosis for patients with ovarian cancer who have already achieved a period of remission, and time elapsed since remission should be taken into account when making follow-up care decisions.

Prognostic Value of Serum HE4 Levels and Risk of Ovarian Malignancy Algorithm Scores at the Time of Ovarian Cancer Diagnosis

Objectives

The aim of this study is to assess whether the pretreatment serum HE4 levels or the Risk of Ovarian Malignancy Algorithm (ROMA) scores at the time of initial diagnosis are associated with progression-free survival (PFS) and disease-specific survival (DSS) in patients with ovarian cancer receiving either primary debulking surgery or neoadjuvant chemotherapy followed by interval debulking surgery.

Methods

A survival analysis of 101 cases of invasive ovarian cancer recruited in a previous diagnostic accuracy study was conducted from 2005 to 2009 at the University Hospital KU Leuven, Belgium. Serum HE4 levels (pM) and ROMA scores (%) were obtained before primary treatment. Dates of death were obtained by record linkage with patient hospital files. Progression was evaluated according to the Response Evaluation Criteria in Solid Tumors. Adjusted hazards ratios (HRs) were estimated using multivariable Cox regression.

Results

Eighty patients (79%) with invasive ovarian cancer underwent primary debulking surgery, whereas 21 (21%) received neoadjuvant chemotherapy. The median DSS was 3.72 years (95% confidence interval [CI], 3.19–4.07). Fifty-two patients (51%) died of disease, and 74 patients (73%) had progressive disease during follow-up. On univariable analysis, elevated pretreatment HE4 levels and ROMA scores were related to worse prognosis. However, after the adjustment for classic prognostic variables, HE4 levels (log2-transformed) and ROMA scores were unrelated to DSS (log-2 HE4: adjusted HR, 1.01; 95% CI, 0.84–1.21 and ROMA: adjusted HR per 10% increase, 0.96; 95% CI, 0.84–1.12) and PFS (log-2 HE4: adjusted HR, 0.98; 95% CI, 0.84–1.13 and ROMA: adjusted HR per 10% increase, 0.98; 95% CI, 0.88–1.11).

Conclusions

Pretreatment HE4 levels and ROMA scores are not independent prognostic factors for DSS and PFS after multivariable adjustment in patients with ovarian cancer.

Development and internal validation of a prognostic model for survival after debulking surgery for epithelial ovarian cancer

OBJECTIVE

Predicting survival of patients with epithelial ovarian cancer (EOC) is based on prognosis of the population. Combining prognostic factors could facilitate survival prediction on the level of the individual patient. The aim of this study was to develop a prognostic model to predict five-year disease specific survival in patients with EOC, and to evaluate whether this would add to prediction based on prognosis of the population.

PATIENTS AND METHODS

A retrospective cohort study was performed of all EOC patients treated with primary debulking and adjuvant chemotherapy or neo-adjuvant chemotherapy and interval debulking surgery in three gynaecological-oncologic centres between 1998 and 2010. Primary outcome was 5-year disease-specific survival. We developed a Cox proportional hazard model using the LASSO-method to select the best combination of characteristics from 12 potential predictors and to correct for overfitting. Performance of the model was expressed as calibration and discrimination (c-statistic). A nomogram was developed to increase the clinical applicability of the model.

RESULTS

Of 840 patients with EOC 462 (55%) died within 5 years due to the disease. A combination of FIGO stage, residual tumour after surgery, primary or interval surgery, histology, performance status, age, amount of ascites and a family history suggestive of breast/ovarian cancer best predicted 5-year survival. The final model showed accurate calibration and the c-statistic was 0.71 (95% CI 0.69-0.74).

CONCLUSIONS

Five-year survival in all stage EOC patients can be predicted accurately using available characteristics. After external validation the model can be used for counselling of patients.

External validation of three prognostic models for overall survival in patients with advanced-stage epithelial ovarian cancer

Background:

For various malignancies, prognostic models have shown to be superior to traditional staging systems in predicting overall survival. The purpose of this study was to validate and compare the performance of three prognostic models for overall survival in patients with advanced-stage epithelial ovarian cancer.

Methods:

A multi-institutional epithelial ovarian cancer database was used to identify patients and to evaluate the predictive performance of two nomograms, a prognostic index and FIGO (International Federation of Obstetrics and Gynecology) stage. All patients were treated for advanced-stage epithelial ovarian cancer between January 1996 and January 2009 in 11 hospitals in the eastern part of The Netherlands.

Results:

In total, 542 patients were found to be eligible. Overall performance did not differ between the three prognostic models and FIGO stage. The discriminative performance for Chi's model was moderately good (c indices 0.65 and 0.68) and for the models of Gerestein and Teramukai reasonable (c indices between 0.60 and 0.62). The c indices of FIGO stage ranged between 0.54 and 0.62. After recalibration, the three models showed almost perfect calibration, whereas calibration of FIGO stage was reasonable.

Conclusion:

The three prediction models showed general applicability and a reasonably well-predictive performance, especially in comparison to FIGO stage. To date, there are no studies available that analyse the impact of these prognostic models on decision-making and patient outcome. Therefore, the usefulness of these models in daily clinical practice remains to be investigated.

Outcome of BRCA1- compared with BRCA2-associated ovarian cancer: a nationwide study in the Netherlands

BACKGROUND

Recent studies suggested an improved overall survival (OS) for BRCA2- versus BRCA1-associated epithelial ovarian cancer (EOC), whereas the impact of chemotherapy is not yet clear. In a nationwide cohort, we examined the results of primary treatment, progression-free survival (PFS), treatment-free interval (TFI), and OS of BRCA1 versus BRCA2 EOC patients.

METHODS

Two hundred and forty-five BRCA1- and 99 BRCA2-associated EOC patients were identified through all Dutch university hospitals. Analyses were carried out with the Pearson's Chi-square test, Kaplan-Meier, and Cox regression methods.

RESULTS

BRCA1 patients were younger at EOC diagnosis than BRCA2 patients (51 versus 55 years; P < 0.001), without differences regarding histology, tumor grade, and International Federation of Gynecology and Obstetrics (FIGO) stage. Complete response rates after primary treatment, including chemotherapy, did not differ between BRCA1 (86%) and BRCA2 patients (90%). BRCA1 versus BRCA2 patients had a shorter PFS (median 2.2 versus 3.9 years, respectively; P = 0.006), TFI (median 1.7 versus 2.8 years; P = 0.009), and OS (median 6.0 versus 9.7 years; P = 0.04). Differences could not be explained by age at diagnosis, FIGO stage or type of treatment.

CONCLUSIONS

PFS and OS were substantially longer in BRCA2- than in BRCA1-associated EOC patients. While response rates after primary treatment were similarly high in both groups, TFI, as surrogate for chemosensitivity, was significantly longer in BRCA2 patients.

Expression of CD40 and growth-inhibitory activity of CD40 agonist in ovarian carcinoma cells

The CD40 receptor is a member of the tumour necrosis factor receptor family and is widely expressed on various cell types. The antitumour activity of CD40 agonist antibody has been observed in B-cell-derived malignancies, but its activity on ovarian cancer remains unclear. However, in this paper, we first confirmed that the anti-CD40 agonist antibody could inhibit the growth of ovarian cancer cells and induce apoptosis. This study investigated the expression of CD40 by ovarian carcinoma tissues and cell lines, at the same time, we evaluated the effect of a recombinant soluble human CD40L (rshCD40L) and an anti-CD40 agonist antibody on cell growth and apoptosis. Flow cytometry and immunohistochemistry assay demonstrated that CD40 was expressed on ovarian carcinoma cell lines and primary ovarian carcinoma cells derived from ascites, as well as on ovarian carcinoma tissues. The growth inhibition of rshCD40L and the anti-CD40 agonist antibody on ovarian carcinoma cells was examined by MTT assay, and the proportion of apoptotic tumour cells was analysed by flow cytometry and Hoechst staining. Our study showed that CD40 was expressed on all ovarian carcinoma cell lines and was examined in 86.2% (162/188) of ovarian cancer tissue samples, but not in normal ovarian tissues (n = 20). Treatment with rshCD40L or anti-CD40 agonist antibody significantly inhibited ovarian carcinoma cell growth and induced apoptosis. Theses results suggest that CD40 is expressed on ovarian carcinoma cells, moreover, that rshCD40L and anti-CD40 agonist antibody have therapeutic potential to inhibit human ovarian cancer growth.

Tumor-platelet interaction in solid tumors

Elevated platelet counts in patients diagnosed with malignant tumors were first described more than 100 years ago. Today it is well known that in many types of solid tumors, thrombocytosis at the time of diagnosis is associated with shorter survival. From this well-documented clinical correlation between platelet count and prognosis of solid tumors, the following questions arise: (i) Are the increased platelet counts the reason for shortened survival as platelet-secreted cytokines might boost tumor growth and angiogenesis? (ii) Do platelets affect tumor metastasis thereby shortening survival time? or (iii) Are increased platelet counts simply an epiphenomenon of tumor growth with larger tumors resulting in higher platelet counts and shorter survival times? We address these three questions within our review of the current literature to provide a comprehensive overview of the current concepts in tumor-platelet interaction.

Laparoscopy to predict the result of primary cytoreductive surgery in advanced ovarian cancer patients (LapOvCa-trial): a multicentre randomized controlled study

BACKGROUND

Standard treatment of advanced ovarian cancer is surgery and chemotherapy. The goal of surgery is to remove all macroscopic tumour, as the amount of residual tumour is the most important prognostic factor for survival. When removal off all tumour is considered not feasible, neoadjuvant chemotherapy (NACT) in combination with interval debulking surgery (IDS) is performed. Current methods of staging are not always accurate in predicting surgical outcome, since approximately 40% of patients will have more than 1 cm residual tumour after primary debulking surgery (PDS). In this study we aim to assess whether adding laparoscopy to the diagnostic work-up of patients suspected of advanced ovarian carcinoma may prevent unsuccessful primary debulking surgery for ovarian cancer.

METHODS

Multicentre randomized controlled trial, including all gynaecologic oncologic centres in the Netherlands and their affiliated hospitals. Patients are eligible when they are planned for PDS after conventional staging. Participants are randomized between direct PDS or additional diagnostic laparoscopy. Depending on the result of laparoscopy patients are treated by PDS within three weeks, followed by six courses of platinum based chemotherapy or with NACT and IDS 3-4 weeks after three courses of chemotherapy, followed by another three courses of chemotherapy. Primary outcome measure is the proportion of PDS's leaving more than one centimetre tumour residual in each arm. In total 200 patients will be randomized. Data will be analysed according to intention to treat.

DISCUSSION

Patients who have disease considered to be resectable to less than one centimetre should undergo PDS to improve prognosis. However, there is a need for better diagnostic procedures because the current number of debulking surgeries leaving more than one centimetre residual tumour is still high. Laparoscopy before starting treatment for ovarian cancer can be an additional diagnostic tool to predict the outcome of PDS. Despite the absence of strong evidence and despite the possible complications, laparoscopy is already implemented in many countries. We propose a randomized multicentre trial to provide evidence on the effectiveness of laparoscopy before primary surgery for advanced stage ovarian cancer patients.

TRIAL REGISTRATION

Netherlands Trial Register number NTR2644.

Nomogram for predicting 5-year disease-specific mortality after primary surgery for epithelial ovarian cancer

OBJECTIVE

To develop a nomogram based on established prognostic factors to predict the probability of 5-year disease-specific mortality after primary surgery for patients with all stages of epithelial ovarian cancer (EOC) and compare the predictive accuracy with the currently used International Federation of Gynecology and Obstetrics (FIGO) staging system.

METHODS

Using a prospectively kept database, we identified all patients with EOC who had their primary surgery at our institution between January 1996 and December 2004. Disease-specific mortality was estimated using the Kaplan-Meier method. Twenty-eight clinical and pathologic factors were analyzed. Significant factors on univariate analysis were included in the Cox proportional hazards regression model, which identified factors utilized in the nomogram. The concordance index (CI) was used as an accuracy measure, with bootstrapping to correct for optimistic bias. Calibration plots were constructed.

RESULTS

A total of 478 patients with EOC were included. The most predictive nomogram was constructed using seven variables: age, FIGO stage, residual disease status, preoperative albumin level, histology, family history suggestive of hereditary breast/ovarian cancer (HBOC) syndrome, and American Society of Anesthesiologists (ASA) status. This nomogram was internally validated using bootstrapping and shown to have excellent calibration with a bootstrap-corrected CI of 0.714. The CI for FIGO staging alone was significantly less at 0.62 (P=0.002).

CONCLUSION

We have developed an all-stage nomogram to predict 5-year disease-specific mortality after primary surgery for epithelial ovarian cancer. This tool is more accurate than FIGO staging and should be useful for patient counseling, clinical trial eligibility, postoperative management, and follow-up.

Effect of chemotherapy delays and dose reductions on progression free and overall survival in the treatment of epithelial ovarian cancer

INTRODUCTION

Hematologic, gastrointestinal, and neurologic complications are common side effects of the platinum and taxane-based chemotherapy used in the primary treatment of epithelial ovarian cancer (EOC). These side effects and the impact of the resultant chemotherapy dose modification on disease free interval have not been extensively studied. The goal of this study was to determine the effect of chemotherapy delays and dose reductions on progression free survival (PFS) and overall survival (OS).

METHODS

A review of patients with primary epithelial ovarian, peritoneal, and fallopian tube carcinoma treated between 1/2000 and 12/2007 was performed. Inclusion criteria were advanced stage disease and first line chemotherapy with a platinum and taxane regimen. Cox proportional hazard models were used to determine the effect of chemotherapy reductions and delays on PFS and OS.

RESULTS

One hundred and fifty seven patients met the inclusion criteria. Patients were divided into four groups: no delays or reductions (48%), delay only (27%), reduction only (8%), and both delay and reduction (18%). The mean number of delays/reductions per patient was 1.1 (range=0-5) and therapy was delayed a mean of 8 days. The most common reasons for delays/reductions were neutropenia (n=51), thrombocytopenia (n=45), and neuropathy (n=18). There were no differences detected in PFS or OS between groups.

CONCLUSIONS

There were no differences detected in survival between patients who required dose adjustments and treatment delays and those who did not. The lack of association between survival and chemotherapy alterations suggests that in specific circumstances patients with advanced ovarian cancer should have individualized treatment plans.

Significance of platelet count in esophageal carcinomas

BACKGROUND/AIM

Thrombocytosis is found to be associated with unfavorable prognosis in esophageal carcinoma. Platelets produce thymidine phosphorylase which is a platelet-derived endothelial cell growth factor with angiogenic activity. Increased platelet count may be translated into enhanced tumor growth. We examined the relation between platelet count and several prognostic variables in patients with esophageal cancer.

PATIENTS AND METHODS

Three hundred and eighty-one cases with esophageal cancer that underwent esophagectomy in a referral cancer institute during a 5-year period were studied retrospectively. The relation between preoperative platelet count and patient age, gender, site of tumor, presence of multiple cancers and clinicopathological characteristics including histological type, tumor size, depth of penetration (T), lymph node involvement (N), distant metastasis (M), degree of differentiation, presence of vascular, lymphatic and perineural invasion was examined.

RESULTS

Squamous cell carcinoma (SCC) constituted 93% and adenocarcinoma 7% of cases. Most of patients were in stage III, followed by stage II. The mean platelet count was 245±76 (Χ 10(9)/L). There was no statistically significant correlation between platelet counts with prognostic factors except a weak linear correlation between platelet count and and tumor size (P = 0.03, Pearson correlation coefficient: 0.16). Patients with adenocarcinoma had a higher platelet count than those with SCC (P = 0.003).

CONCLUSION

Platelet count does not correlate with prognostic factors in esophageal cancer. However, it is significantly different between SCC and adenocarcinoma of esophagus.