Role of CT scan-based and clinical evaluation in the preoperative prediction of optimal cytoreduction in advanced ovarian cancer: a prospective trial. Br J Cancer. 2009;101:1066-1073. [PMID: 19738608 PMCID: PMC2768100 DOI: 10.1038/sj.bjc.6605292]

Radiomics combined with clinical and MRI features may provide preoperative evaluation of suboptimal debulking surgery for serous ovarian carcinoma

PURPOSE

To develop and validate a model for predicting suboptimal debulking surgery (SDS) of serous ovarian carcinoma (SOC) using radiomics method, clinical and MRI features.

METHODS

228 patients eligible from institution A (randomly divided into the training and internal validation cohorts) and 45 patients from institution B (external validation cohort) were collected and retrospectively analyzed. All patients underwent abdominal pelvic enhanced MRI scan, including T2-weighted imaging fat-suppressed fast spin-echo (T2FSE), T1-weighted dual-echo magnetic resonance imaging (T1DEI), diffusion weighted imaging (DWI), and T1 with contrast enhancement (T1CE). We extracted, selected and eliminated highly correlated radiomic features for each sequence. Then, Radiomic models were made by each single sequence, dual-sequence (T1CE + T2FSE), and all-sequence, respectively. Univariate and multivariate analyses were performed to screen the clinical and MRI independent predictors. The radiomic model with the highest area under the curve (AUC) was used to combine the independent predictors as a combined model.

RESULTS

The optimal radiomic model was based on dual sequences (T2FSE + T1CE) among the five radiomic models (AUC = 0.720, P < 0.05). Serum carbohydrate antigen 125, the relationship between sigmoid colon/rectum and ovarian mass or mass implanted in Douglas' pouch, diaphragm nodules, and peritoneum/mesentery nodules were considered independent predictors. The AUC of the radiomic-clinical-radiological model was higher than either the optimal radiomic model or the clinical-radiological model in the training cohort (AUC = 0.908 vs. 0.720/0.854).

CONCLUSIONS

The radiomic-clinical-radiological model has an overall algorithm reproducibility and may help create individualized treatment programs and improve the prognosis of patients with SOC.

Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC) Applied to Platinum-Resistant Recurrence of Ovarian Tumor: A Single-Institution Experience (ID: PARROT Trial)

BACKGROUND

We aimed to investigate the therapeutic efficacy and safety of Pressurized IntraPeritoneal Aerosol Chemotherapy (PIPAC) in platinum-resistant recurrence of ovarian cancer and peritoneal carcinomatosis, while our secondary endpoint was to establish any changes in quality of life estimated via the EORTC QLQ-30 and QLQ-OV28 questionnaires.

METHODS

In this monocentric, single-arm, phase II trial, women were prospectively recruited and every 28-42 days underwent courses of PIPAC with doxorubicin 2.1 mg/m2 followed by cisplatin 10.5 mg/m2 via sequential laparoscopy.

RESULTS

Overall, 98 PIPAC procedures were performed on 43 women from January 2016 to January 2020; three procedures were aborted due to extensive intra-abdominal adhesions. The clinical benefit rate (CBR) was reached in 82% of women. Three cycles of PIPAC were completed in 18 women (45%), and 13 (32.5%) and 9 (22.5%) patients were subjected to one and two cycles, respectively. During two PIPAC procedures, patients experienced an intraoperative intestinal perforation. There were no treatment-related deaths. Nineteen patients showed no response according to the Peritoneal Regression Grading Score (PRGS) and 8 patients showed minor response according to the PRGS. Median time from ovarian cancer relapse to disease progression was 12 months (95% confidence interval [CI] 6.483-17.517), while the median overall survival was 27 months (95% CI 20.337-33.663). The EORTC QLQ-28 and EORTC QLQ-30 scores did not worsen during therapy.

CONCLUSIONS

PIPAC seems a feasible approach for the treatment of this subset of patients, without any impact on their quality of life. Since this study had a small sample size and a single-center design, future research is mandatory, such as its application in addition to systemic chemotherapy.

Neglected Anatomical Areas in Ovarian Cancer: Significance for Optimal Debulking Surgery

Ovarian cancer (OC), the most lethal gynecological malignancy, usually presents in advanced stages. Characterized by peritoneal and lymphatic dissemination, OC necessitates a complex surgical approach usually involving the upper abdomen with the aim of achieving optimal cytoreduction without visible macroscopic disease (R0). Failures in optimal cytoreduction, essential for prognosis, often stem from overlooking anatomical neglected sites that harbor residual tumor. Concealed OC metastases may be found in anatomical locations such as the omental bursa; Morison's pouch; the base of the round ligament and hepatic bridge; the splenic hilum; and suprarenal, retrocrural, cardiophrenic and inguinal lymph nodes. Hence, mastery of anatomy is crucial, given the necessity for maneuvers like liver mobilization, diaphragmatic peritonectomy and splenectomy, as well as dissection of suprarenal, celiac, and cardiophrenic lymph nodes in most cases. This article provides a meticulous anatomical description of neglected anatomical areas during OC surgery and describes surgical steps essential for the dissection of these "neglected" areas. This knowledge should equip clinicians with the tools needed for safe and complete cytoreduction in OC patients.

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

Maximal-effort upfront or interval debulking surgery is the recommended approach for advanced-stage ovarian cancer. The role of diagnostic imaging is to provide a systematic and structured report on tumour dissemination with emphasis on key sites for resectability. Imaging methods, such as pelvic and abdominal ultrasound, contrast-enhanced computed tomography, whole-body diffusion-weighted magnetic resonance imaging and positron emission tomography, yield high diagnostic performance for diagnosing bulky disease, but they are less accurate for depicting small-volume carcinomatosis, which may lead to unnecessary explorative laparotomies. Diagnostic laparoscopy, on the other hand, may directly visualize intraperitoneal involvement but has limitations in detecting tumours beyond the gastrosplenic ligament, in the lesser sac, mesenteric root or in the retroperitoneum. Laparoscopy has its place in combination with imaging in cases where ima-ging results regarding resectability are unclear. Different imaging models predicting tumour resectability have been developed as an adjunctional objective tool. Incorporating results from tumour quantitative analyses (e.g., radiomics), preoperative biopsies and biomarkers into predictive models may allow for more precise selection of patients eligible for extensive surgery. This review will discuss the ability of imaging and laparoscopy to predict non-resectable disease in patients with advanced ovarian cancer.

Development and Validation of 18F-FDG PET/CT-Based Models for Predicting Successful Complete Cytoreduction During Primary Cytoreductive Surgery for Advanced Ovarian cancer

PURPOSE

The aim of this study was to develop an 18F-FDG PET/CT-based model to predict complete cytoreduction during primary cytoreductive surgery (CRS) for ovarian cancer (OC).

PATIENTS AND METHODS

We retrospectively identified patients with stage III-IV OC who underwent primary CRS between June 2013 and February 2020 at 2 tertiary centers. Patients from each hospital were assigned to training and test sets. The abdominal cavity was divided into 3 sections, and data for the PET/CT-derived parameters were collected through image analysis. Various prediction models were constructed by combining clinicopathologic characteristics and PET/CT-derived parameters. The performance of the model with the highest area under the receiver operating characteristic curve (AUC) was externally validated.

RESULTS

The training and test sets included 159 and 166 patients, respectively. The median age of patients in the test set was 55 years; 72.3% of them had stage III tumors, and 65.4% underwent complete cytoreduction. Metabolic tumor volume, total lesion glycolysis, and the number of metastatic lesions above the upper margin of the renal vein (area A) were selected among the PET/CT parameters. The best predictive multivariable model consisted of CA-125 (<750 or ≥750 IU/mL), number of metastatic lesions (<2 or ≥2), and metabolic tumor volume of area A, predicting complete cytoreduction with an AUC of 0.768. The model was validated using a test set. Its predictive performance yielded an AUC of 0.771.

CONCLUSIONS

We successfully developed and validated a preoperative model to predict complete cytoreduction in advanced OC. This model can facilitate patient selection for primary CRS in clinical practice.

Concordance of Radiological, Laparoscopic and Laparotomic Scoring to Predict Complete Cytoreduction in Women with Advanced Ovarian Cancer

OBJECTIVE

To identify the best method among the radiologic, laparoscopic and laparotomic scoring assessment to predict the outcomes of cytoreductive surgery in patients with advanced ovarian cancer (AOC).

METHODS

Patients with AOC who underwent pre-operative computed tomography (CT) scan, laparoscopic evaluation, and cytoreductive surgery between August 2016 and February 2021 were retrospectively reviewed. Predictive Index (PI) score and Peritoneal Cancer Index (PCI) scores were used to estimate the tumor load and predict the residual disease in the primary debulking surgery (PDS) and interval debulking surgery (IDS) after neoadjuvant chemotherapy (NACT) groups. Concordance percentages were calculated between the two scores.

RESULTS

Among 100 eligible patients, 69 underwent PDS, and 31 underwent NACT and IDS. Complete cytoreduction was achieved in 72.5% of patients in the PDS group and 77.4% in the IDS. In patients undergoing PDS, the laparoscopic PI and the laparotomic PCI had the best accuracies for complete cytoreduction (R0) [area under the curve (AUC) = 0.78 and AUC = 0.83, respectively]. In the IDS group, the laparotomic PI (AUC = 0.75) and the laparoscopic PCI (AUC= 0.87) were associated with the best accuracy in R0 prediction. Furthermore, radiological assessment, through PI and PCI, was associated with the worst accuracy in either PDS or IDS group (PI in PDS: AUC = 0.64; PCI in PDS: AUC = 0.64; PI in IDS: AUC = 0.46; PCI in IDS: AUC = 0.47).

CONCLUSION

The laparoscopic score assessment had high accuracy for optimal cytoreduction in AOC patients undergoing PDS or IDS. Integrating diagnostic laparoscopy in the decision-making algorithm to accurately triage AOC patients to different treatment strategies seems necessary.

The BUMPy road of peritoneal metastases in ovarian cancer

Ovarian cancer is the most common cause of death due to gynecologic malignancies, with more than 70% of patients presenting with advanced stage disease at the time of diagnosis. The extent and distribution of tumor guide primary treatment selection and clinical management. While primary cytoreductive surgery with complete tumor resection improves survival, patients with extensive peritoneal disease may benefit from neoadjuvant chemotherapy first to reduce tumor burden followed by interval cytoreductive surgery. Imaging plays an essential role in triaging patients including selecting patients who may benefit from neoadjuvant chemotherapy before cytoreductive surgery. Interestingly, there are no universally established criteria to predict resectability and local practices depend on local guidelines and surgeon preferences. Nevertheless, certain anatomical tumor locations are known to be difficult to resect and are associated with suboptimal cytoreduction or require special surgical considerations. This review discusses the recent advances in the initial management of patients with ovarian cancer, a practical approach to the assessment and communication of peritoneal metastases locations on CT and MRI. It also explores recent advances in genomics profiling and radiomics that may influence the initial management of these patients.

Preoperative CT-based deep learning model for predicting overall survival in patients with high-grade serous ovarian cancer

Purpose

High-grade serous ovarian cancer (HGSOC) is aggressive and has a high mortality rate. A Vit-based deep learning model was developed to predicting overall survival in HGSOC patients based on preoperative CT images.

Methods

734 patients with HGSOC were retrospectively studied at Qilu Hospital of Shandong University with preoperative CT images and clinical information. The whole dataset was randomly split into training cohort (n = 550) and validation cohort (n = 184). A Vit-based deep learning model was built to output an independent prognostic risk score, afterward, a nomogram was then established for predicting overall survival.

Results

Our Vit-based deep learning model showed promising results in predicting survival in the training cohort (AUC = 0.822) and the validation cohort (AUC = 0.823). The multivariate Cox regression analysis indicated that the image score was an independent prognostic factor in the training (HR = 9.03, 95% CI: 4.38, 18.65) and validation cohorts (HR = 9.59, 95% CI: 4.20, 21.92). Kaplan-Meier survival analysis indicates that the image score obtained from model yields promising prognostic significance to refine the risk stratification of patients with HGSOC, and the integrative nomogram achieved a C-index of 0.74 in the training cohort and 0.72 in the validation cohort.

Conclusions

Our model provides a non-invasive, simple, and feasible method to predicting overall survival in patients with HGSOC based on preoperative CT images, which could help predicting the survival prognostication and may facilitate clinical decision making in the era of individualized and precision medicine.

Integrated Clinical and Genomic Models to Predict Optimal Cytoreduction in High-Grade Serous Ovarian Cancer

Simple Summary

Approximately 30% of patients with advanced, high-grade serous ovarian cancer who undergo surgery will have a suboptimal result, resulting in decreased overall survival. Improving the ability to predict a successful surgery would improve survival. We aimed to use tumor genomics to create prediction models, which would predict an optimal or complete cytoreduction prior to entering the operating room. We created two sets of models, one for optimal and one for complete cytoreduction. We then validated those models using the TCGA database as well as statistical learning. We developed 21 models for optimal cytoreduction and 37 models for complete cytoreduction, which have the potential to improve our ability to predict these surgical results in patients with ovarian cancer before taking them to the operating room. Improving our pre-operative decision-making will result in more patients having the desired surgical results and, therefore, improved survival.

Abstract

Advanced high-grade serous (HGSC) ovarian cancer is treated with either primary surgery followed by chemotherapy or neoadjuvant chemotherapy followed by interval surgery. The decision to proceed with surgery primarily or after chemotherapy is based on a surgeon’s clinical assessment and prediction of an optimal outcome. Optimal and complete cytoreductive surgery are correlated with improved overall survival. This clinical assessment results in an optimal surgery approximately 70% of the time. We hypothesize that this prediction can be improved by using biological tumor data to predict optimal cytoreduction. With access to a large biobank of ovarian cancer tumors, we obtained genomic data on 83 patients encompassing gene expression, exon expression, long non-coding RNA, micro RNA, single nucleotide variants, copy number variation, DNA methylation, and fusion transcripts. We then used statistical learning methods (lasso regression) to integrate these data with pre-operative clinical information to create predictive models to discriminate which patient would have an optimal or complete cytoreductive outcome. These models were then validated within The Cancer Genome Atlas (TCGA) HGSC database and using machine learning methods (TensorFlow). Of the 124 models created and validated for optimal cytoreduction, 21 performed at least equal to, if not better than, our historical clinical rate of optimal debulking in advanced-stage HGSC as a control. Of the 89 models created to predict complete cytoreduction, 37 have the potential to outperform clinical decision-making. Prospective validation of these models could result in improving our ability to objectively predict which patients will undergo optimal cytoreduction and, therefore, improve our ovarian cancer outcomes.

Multidetector computed tomography in diagnosing peritoneal metastases in ovarian carcinoma

Multidetector computed tomography (MDCT) of the abdomen is currently the imaging examination of choice for the staging and follow-up of ovarian carcinoma (OC). Peritoneal metastases (PMs) represent the most common pathway for the metastatic spread of OC. MDCT scanners, due to several advantages-including increased volume coverage, reduced scanning time, acquisition of thin slices and creation of multiplanar reformations, and three-dimensional reconstructions-provide useful information regarding the early and accurate detection of PMs. Detailed mapping of peritoneal carcinomatosis is feasible, with improved detection of sub-centimeter peritoneal implants and thorough evaluation of curved peritoneal surfaces.

CT imaging of peritoneal carcinomatosis with surgical correlation: a pictorial review

Cytoreductive surgery in combination with hyperthermic intraperitoneal chemotherapy has revolutionized the survival and the quality of life in selected patients with peritoneal carcinomatosis. Preoperative CT is important for the selection of patients that may benefit from cytoreductive surgery and is useful for surgical planning. There are several tasks for the radiologist during CT interpretation: to describe cancerous implants on a "site-by-site" basis in the peritoneum, ligaments, mesenteries and visceral surfaces, to analyze patterns of involvement and to estimate the disease burden. Knowledge of the correlation between the CT and the surgical findings enhances the understanding of the disease and facilitates the communication between radiologists and surgeons.

Ascites volume at the time of primary debulking and overall survival of patients with advanced epithelial ovarian cancer

OBJECTIVES

To investigate the impact of malignant ascites volume on the outcomes of patients with advanced epithelial ovarian carcinoma who undergo primary debulking surgery.

METHODS

Patients diagnosed with stage III-IV epithelial ovarian carcinoma and bulky intra-abdominal (TIIIC) disease between 2010 and 2015, who underwent primary debulking surgery followed by multi-agent chemotherapy and known status of residual disease, were drawn from the National Cancer Database. Based on available information, the presence and volume of malignant ascites was categorized as absent, low (<980 mL), and high (>980 mL) volume. Median overall survival was determined from Kaplan-Meier curves and compared with the log rank test. A multivariate Cox model was constructed to control for confounders.

RESULTS

2493 patients were identified; 31.9% (n=795) had no ascites, 40.2% (n=1001) had low, and 28% (n=697) had high volume malignant ascites. Rate of complete gross resection was higher for patients with no ascites (65.9%) compared with those with low (35.6%) and high (23%) volume ascites (p<0.001). After controlling for stage, histology, grade, age, and comorbidities, compared with those with no ascites, patients with low (odds ratio (OR) 3.49, 95% confidence intervals (CI) 2.89 to 4.26) and high (OR 6.40, 95% CI 5.07 to 8.06) volume ascites were more likely to have gross residual disease. For patients who achieved complete gross resection after controlling for confounders compared with patients with no ascites, those with low (hazard ratio (HR) 1.37, 95% CI 1.09 to 1.72) and high volume ascites (HR 1.94, 95% CI 1.47 to 2.55) had worse overall survival. Similarly, patients with low volume ascites had better survival compared with those with high volume ascites (HR 0.71 95% CI 0.54 to 0.93).

CONCLUSIONS

The presence and volume of malignant ascites at the time of primary debulking surgery was associated with the likelihood of achieving a complete gross resection and worse overall survival.

Preoperative CT or PET/CT to Assess Pelvic and Para-Aortic Lymph Node Status in Epithelial Ovarian Cancer? A Systematic Review and Meta-Analysis

Background: In advanced epithelial ovarian cancer (EOC), the LION trial restricted lymphadenectomy indication to patients with suspect lymph nodes before and during surgery. Preoperative imaging is used to assess lymph node status, and particularly CT and PET/CT. The aim of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of preoperative CT and PET/CT to detect lymph node metastasis (LNM) in patients with EOC; Methods: Databases were searched from January 1990 to May 2019 for studies that evaluated the diagnostic accuracy of preoperative CT and PET/CT to detect LNM in patients with EOC with histology as the gold standard. Pooled diagnostic accuracy was calculated using bivariate random-effects models and hierarchical summary receiver operating curve (HSROC). This study is registered with PROSPERO number CRD42020179214; Results: A total of five studies were included in the meta-analysis: four articles concerned preoperative CT and four articles concerned preoperative PET/CT, involving 106 and 138 patients, respectively. For preoperative CT, pooled sensitivity was 0.47 95% CI [0.20–0.76], pooled specificity was 0.99 95% CI [0.75–1.00] and area under the curve (AUC) of the HSROC was 0.91 95% CI [0.88–0.93]. For preoperative PET/CT, pooled sensitivity was 0.81 95% CI [0.61–0.92], pooled specificity was 0.96 95% CI [0.91–0.99] and AUC of the HSROC was 0.97 95% CI [0.95–0.98]; Conclusions: PET/CT has a very high diagnostic accuracy, especially for specificity, to detect LNM in EOC and should be realized systematically, additionally to CT recommended to evaluate peritoneal spread, in the preoperative staging of patients with an advanced disease.

Primary cytoreductive surgery for advanced stage endometrial cancer: a systematic review and meta-analysis

OBJECTIVE

Endometrial cancer uncommonly presents at an advanced stage and little prospective evidence exists to guide the management thereof. We aimed to summarize the evidence about primary cytoreductive surgery in the treatment of advanced stage endometrial cancer.

DATA SOURCES

MEDLINE, Embase, and Scopus databases were searched from inception to September 11, 2020, using search terms representing the themes "endometrial cancer," "advanced stage," and "primary cytoreductive surgery."

STUDY ELIGIBILITY CRITERIA

We included full-text, English reports that included ≥10 patients undergoing primary cytoreductive surgery for advanced stage endometrial cancer and that reported on the outcomes of primary cytoreductive surgery and survival rates based on the residual disease burden.

METHODS

Two reviewers independently screened the studies and with disagreements between the reviewers resolved by a third reviewer. Data were extracted using a standardized form. The percentage of cases reaching maximal (no gross residual disease) and optimal (<1 cm or <2 cm residual disease) cytoreduction were assessed by summing binomials proportions, and the association with survival was assessed using an inverse variance-weighted meta-analysis of logarithmic hazard ratios.

RESULTS

From 1219 unique records identified, 34 studies were selected for inclusion. Studies consisted of single or multi-institutional cohorts of patients collected over a period of 6 to 24 years and included various mixes of histologies (endometrioid, serous, clear cell, and carcinosarcoma) and disease stages (III or IV). In a meta-analysis of the extent of residual disease after primary cytoreductive surgery, we found that 52.1% of cases reached no gross residual disease status (n=18 studies; 1329 patients) and 75% reached <1 cm residual disease status (n=27 studies; 2343 patients). The proportion of cytoreduction for both thresholds was lower for studies of stage IV vs stage III to IV disease (41.4% vs 69.8% for no gross residual disease; 63.2% vs 82.2% for <1 cm residual disease) but did not vary notably by histology. In a meta-analysis of the reported hazard ratios, submaximal (any gross residual disease vs no gross residual disease) and suboptimal (≥1 cm vs <1 cm) cytoreduction thresholds were associated with worse progression-free survival (submaximal hazard ratio, 2.16; 95% confidence interval, 1.45-3.21; I²=68%; suboptimal hazard ratio, 2.55; 95% confidence interval, 1.93-3.37; I²=63%) and overall survival rates (submaximal hazard ratio, 2.57; 95% confidence interval, 2.13-3.10; I²=1%; suboptimal hazard ratio, 2.62; 95% confidence interval, 2.20-3.11; I²=15%). Sensitivity analyses limited to high-quality studies demonstrated consistent results.

CONCLUSION

Among cases of advanced stage endometrial cancer undergoing primary cytoreductive surgery, a significant proportion of patients are left with residual disease, which is associated with worse survival outcomes. Further investigations about the roles of neoadjuvant chemotherapy and primary cytoreductive surgery in prospective trials is warranted in this population.

Factors associated with response to neoadjuvant chemotherapy in advanced stage ovarian cancer

OBJECTIVES

To evaluate the factors associated with response to neoadjuvant chemotherapy (NACT) and the ability to undergo interval tumor reductive surgery (iTRS) in patients with advanced ovarian cancer.

METHODS

We performed a retrospective review from April 2013 to March 2019 of patients with advanced stage ovarian cancer triaged to NACT based on our standard triage algorithm. Clinicopathologic and treatment data were analyzed for factors associated with response to NACT, outcomes at iTRS, and their impact on progression-free survival (PFS).

RESULTS

562 patients met inclusion criteria and triaged to NACT following laparoscopy (n = 132) or without laparoscopy (n = 430). 413 patients underwent iTRS (74%). Factors that correlated with a patient reaching iTRS included increasing age (p < 0.001), higher Charlson comorbidity index (p < 0.001), ECOG status 2 or 3 (<0.001), and laparoscopic assessment (<0.001). Patients with CA-125 ≤ 35 U/mL at iTRS had higher rates of complete gross resection (88% vs. 65%, p < 0.001) and improved PFS (16.8 vs. 12.7 months, p < 0.001). Patients receiving dose-dense paclitaxel (76% vs. 60%, p = 0.004) and CA-125 ≤ 35 U/mL at iTRS (85% vs. 66%, p < 0.001) had higher rates of complete radiographic response. On multivariate analysis, germline BRCA 1/2 mutation (p = 0.001), iTRS vs. no surgery (R0, p < 0.001; ≤1 cm, p < 0.001; >1 cm, p < 0.001), dose-dense chemotherapy (p = 0.01), and CA-125 ≤ 35 U/mL at iTRS (p = 0.001) were independent significant factors affecting PFS.

CONCLUSIONS

Normalization of CA-125 at the time of iTRS following NACT may serve as a surrogate marker for prognosis in this high-risk population. Our NACT cohort experienced improved response rates and PFS with dose-dense therapy compared to conventional dosing.

What can we learn from the 10 mm lymph node size cut-off on the CT in advanced ovarian cancer at the time of interval debulking surgery?

INTRODUCTION

The benefit of a systematic lymphadenectomy is still debated in patients undergoing neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) in ovarian cancer (OC). The objective of this study was to evaluate the predictive value of the pre-NACT and post-NACT CT in predicting definitive histological lymph node involvement. The prognostic value of a positive node on the CT was also assessed.

MATERIEL AND METHODS

A retrospective, unicentric cohort study was performed including all patients with ovarian cancer who underwent NACT and IDS with a lymphadenectomy between 2005 and 2018. CT were analyzed blinded to pathology, and nodes with small axis ≥ 10 mm on CT were considered positive. Sensitivity (Se), specificity (Sp), and negative (NPV) and positive predictive values (PPV) and their CI95% were calculated. The 2-year recurrence free survival (RFS) and 5-year overall survival (OS) was compared.

RESULTS

158 patients were included, among which 92 (58%) had histologically positive lymph nodes. CT had a Se, Sp, NPV and PPV of 35%, 82%, 47% and 73% before NACT and 20%, 97%, 47% and 91% after NACT, respectively. Patients with nodes considered positive had a non-significant lower 2-year RFS and 5-year OS on the pre-NACT and post-NACT CT. Patients at 'high risk' (nodes stayed positive on the CT or became positive after NACT) also had a non-significant lower 2-year RFS and 5-year OS.

CONCLUSION

Presence of enlarged lymph nodes on CT is a weak indicator of lymph node involvement in patients with advanced ovarian cancer undergoing NACT. However, it could be used to assess prognosis.

CT-Based Fagotti Scoring System for Non-Invasive Prediction of Cytoreduction Surgery Outcome in Patients with Advanced Ovarian Cancer

Objective

To construct a CT-based Fagotti scoring system by analyzing the correlations between laparoscopic findings and CT features in patients with advanced ovarian cancer.

Materials and Methods

This retrospective cohort study included patients diagnosed with stage III/IV ovarian cancer who underwent diagnostic laparoscopy and debulking surgery between January 2010 and June 2018. Two radiologists independently reviewed preoperative CT scans and assessed ten CT features known as predictors of suboptimal cytoreduction. Correlation analysis between ten CT features and seven laparoscopic parameters based on the Fagotti scoring system was performed using Spearman's correlation. Variable selection and model construction were performed by logistic regression with the least absolute shrinkage and selection operator method using a predictive index value (PIV) ≥ 8 as an indicator of suboptimal cytoreduction. The final CT-based scoring system was internally validated using 5-fold cross-validation.

Results

A total of 157 patients (median age, 56 years; range, 27–79 years) were evaluated. Among 120 (76.4%) patients with a PIV ≥ 8, 105 patients received neoadjuvant chemotherapy followed by interval debulking surgery, and the optimal cytoreduction rate was 90.5% (95 of 105). Among 37 (23.6%) patients with PIV < 8, 29 patients underwent primary debulking surgery, and the optimal cytoreduction rate was 93.1% (27 of 29). CT features showing significant correlations with PIV ≥ 8 were mesenteric involvement, gastro-transverse mesocolon-splenic space involvement, diaphragmatic involvement, and para-aortic lymphadenopathy. The area under the receiver operating curve of the final model for prediction of PIV ≥ 8 was 0.72 (95% confidence interval: 0.62–0.82).

Conclusion

Central tumor burden and upper abdominal spread features on preoperative CT were identified as distinct predictive factors for high PIV on diagnostic laparoscopy. The CT-based PIV prediction model might be useful for patient stratification before cytoreduction surgery for advanced ovarian cancer.

A prospective study on the diagnostic pathway of patients with stage IIIC-IV ovarian cancer: Exploratory laparoscopy (EXL) + CT scan VS. CT scan

OBJECTIVE

To compare the diagnostic power of CT scan to a combination of exploratory laparoscopy (EXL) and CT scan in patients with stage IIIC-IV Ovarian Cancer (OC) by anatomic areas. To investigate if adding EXL to CT can reduce unnecessary laparotomy.

METHODS

In the period 2009-2017, 350 consecutive patients with FIGO Stage IIIC-IV OC underwent CT and EXL prior to Visceral-Peritoneal debulking (VPD) and were included in the study. Radiologist and surgeons filled an ad-hoc form to report CT scan and EXL of eleven key anatomic areas. The decision to proceed to EXL was based on the CT scan and the decision to proceed to laparotomy (LPT) on CT and EXL. Setting LPT findings as the gold standard, positive and negative predictive value (PPV/NPV), sensitivity, specificity, and accuracy of CT, EXL and CT + EXL were calculated. We broke down the diagnostic outcomes by anatomic areas and determined the rate of unnecessary laparotomy avoided with the findings of EXL.

RESULTS

Median time for the EXL was 14 min (SD +/- 3). No complication related to EXL occurred. At EXL, 325 out of 350 patients (93%) proceeded to LPT and 25 patients (7.1%) did not because of exclusion criteria. In 307 patients out of 325 (94.4%) EXL was followed by VPD. Eighteen patients had exclusion criteria found at LPT and had no VPD. EXL reduced the rate of unnecessary/futile laparotomy from 12.2% to 5.1%. CT + EXL showed a significantly higher sensitivity for all anatomic areas except for the lymph nodes. Specificity was not significantly improved. PPV was significantly improved for small bowel, porta hepatis and stomach. NPV displayed a statistical improvement in all anatomic areas except lymph nodes, stomach, and liver.

CONCLUSION

The combination CT + EXL has a higher diagnostic power than CT alone, particularly on diaphragm, small bowel serosa and mesentery. The rate of unnecessary laparotomy decreased by almost 60%.

A Prediction Model for Optimal Primary Debulking Surgery Based on Preoperative Computed Tomography Scans and Clinical Factors in Patients With Advanced Ovarian Cancer: A Multicenter Retrospective Cohort Study

Objective

This study assessed the predictive value of preoperative computed tomography (CT) scans and clinical factors for optimal debulking surgery (ODS) in patients with advanced ovarian cancer (AOC).

Methods

Patients with AOC in International Federation of Gynecology and Obstetrics (FIGO) stage III-IV who underwent primary debulking surgery (PDS) between 2016 and 2019 from nine tertiary Chinese hospitals were included. Large-volume ascites, diffuse peritoneal thickening, omental cake, retroperitoneal lymph node enlargement (RLNE) below and above the inferior mesenteric artery (IMA), and suspected pelvic bowel, abdominal bowel, liver surface, liver parenchyma and portal, spleen, diaphragm and pleural lesions were evaluated on CT. Preoperative factors included age, platelet count, and albumin and CA125 levels.

Results

Overall, 296 patients were included, and 250 (84.5%) underwent ODS. The prediction model included age >60 years (P=0.016; prediction index value, PIV=1), a CA125 level >800 U/ml (P=0.033, PIV=1), abdominal bowel metastasis (P=0.034, PIV=1), spleen metastasis (P<0.001, PIV=2), diaphragmatic metastasis (P=0.014, PIV=2), and an RLNE above the IMA (P<0.001, PIV=2). This model had superior discrimination (AUC=0.788>0.750), and the Hosmer-Lemeshow test indicated its stable calibration (P=0.600>0.050). With the aim of maximizing the accuracy of prediction and minimizing the rate of inappropriate explorations, a total PIV ≥5 achieved the highest accuracy of 85.47% and identified patients who underwent suboptimal PDS with a specificity of 100%.

Conclusions

We developed a prediction model based on two preoperative clinical factors and four radiological criteria to predict unsatisfactory debulking surgery in patients with AOC. The accuracy of this prediction model needs to be validated and adjusted in further multicenter prospective studies.

A novel laparoscopy-based model for the prediction of optimal cytoreduction and prognosis of epithelial ovarian cancer in a Chinese population

OBJECTIVES

This study aimed to investigate the predictive value of laparoscopy for the prediction of optimal cytoreduction and prognosis of epithelial ovarian cancer (EOC) in a Chinese population.

STUDY DESIGN

This study enrolled 162 EOC patients in Obstetrics and Gynecology Hospital of Fudan University from January 2015 to December 2016. All patients underwent preoperative CT scans and laparoscopic assessments. Each patient was scored according to the CT-based predictive model by Bristow and laparoscopy-based predictive model by Fagotti. The specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV) and area under the curve (AUC) of each model were calculated. The predictive scores and clinicopathologic factors were all analyzed using the Kaplan-Meier method and multivariate Cox analysis. A prognostic predictive nomogram was formulated in R software.

RESULTS

The AUCs of the laparoscopy-based predictive model and CT-based predictive model was 0.955 and 0.755 respectively. At a laparoscopic score ≥ 10, the possibility of optimal cytoreduction was 0, and the risk of unnecessary explorative attempts was 6%. Additionally, laparoscopic score, independent of residual tumor size and FIGO stage, was an independent prognostic factor for both overall survival (OS) and recurrence-free survival (RFS) in EOC. Notably, the predictive nomogram that we established further confirmed the prognostic value of laparoscopy for prognostic predictions in EOC.

CONCLUSIONS

Laparoscopy has a better discriminating performance than CT in the prediction of optimal cytoreduction in EOC. Moreover, the laparoscopic score is directly correlated with the survival of EOC patients. The laparoscopic score-based nomogram we established showed good potential to predict the prognosis of EOC patients.

Correlation of surgeon radiology assessment with laparoscopic disease site scoring in patients with advanced ovarian cancer

BACKGROUND

Radiographic triage measures in patients with new advanced ovarian cancer have yielded inconsistent results.

OBJECTIVE

To determine the correlation between surgeon radiology assessment and laparoscopic scoring by disease sites in patients with newly diagnosed advanced stage ovarian cancer.

METHODS

Fourteen gynecologic oncology surgeons from a single institution performed a blinded review of pre-operative contrast-enhanced CT imaging from patients with advanced stage ovarian cancer. Each of the patients had also undergone laparoscopic scoring assessment, between April 2013 and December 2017, to determine primary resectability using the validated Fagotti scoring method, and assigned a predictive index value score. Surgeons were asked to provide expected predictive index value scores based on their blinded review of the antecedent CT imaging. Linear mixed models were conducted to calculate the correlation between radiologic and laparoscopic score for surgeons individually, and as a group. Once the model was fit, the inter-class correlation and 95% CI were calculated.

RESULTS

Radiology review was performed on 20 patients with advanced stage ovarian cancer who underwent laparoscopic scoring assessment. Surgeon faculty rank included assistant professor (n=5), associate professor (p=4), and professor (n=5). The kappa inter-rater agreement was -0.017 (95% CI -0.023 to -0.005), indicating low inter-rater agreement between radiology review and actual laparoscopic score. The inter-class correlation in this model was 0.06 (0.02-0.21), indicating that surgeons do not score the same across all the images. When using a clinical cut-off point for the predictive index value of 8, the probability of agreement between radiology and actual laparoscopic score was 0.56 (95% CI 0.49 to 0.73). Examination of disease site sub-scales showed that the probability of agreement was as follows: peritoneum 0.57 (95% CI 0.51 to 0.62), diaphragm 0.54 (95% CI 0.48 to 0.60), mesentery 0.51 (95% CI 0.45 to 0.57), omentum 0.61 (95% CI 0.55 to 0.67), bowel 0.54 (95% CI 0.44 to 0.64), stomach 0.71 (95% CI 0.65 to 0.76), and liver 0.36 (95% CI 0.31 to 0.42). The number of laparoscopic scoring cases, tumor reductive surgery cases, or faculty rank was not significantly associated with overall or sub-scale agreement.

CONCLUSIONS

Surgeon radiology review did not correlate highly with actual laparoscopic scoring assessment findings in patients with advanced stage ovarian cancer. Our study highlights the limited accuracy of surgeon radiographic assessment to determine resectability.

The Significance of Preoperative Computed Tomography for Predicting Optimal Cytoreduction in Advanced Ovarian Cancer

Introduction Optimal cytoreduction is the most important prognostic factor in advanced ovarian cancer. Although staging and assessment of operability are made by exploratory surgery, preoperative computed tomography (CT) of the abdomen is regarded as standard. The aim of this study was to examine various CT parameters with regard to prediction of optimal cytoreduction. Patients and Methods The retrospective study included 131 patients with ovarian cancer newly diagnosed between 2010 and 2014. Of these, n = 36 with FIGO stage I to IIB were excluded from the study. A preoperative abdominal CT was available for n = 75 of the 95 patients with FIGO stage IIC to IV. The CT scans underwent blinded review. The 11 evaluated CT parameters were examined by means of χ ² test and logistic regression analysis with regard to the endpoints of macroscopic residual tumour and residual tumour > 1 cm. Survival analyses used the Kaplan-Meier method and log rank test. Results Of 75 patients, 28 (37.3%) had complete tumour resection and 26 (34.7%) had residual tumour ≤ 1 cm. Residual tumours > 1 cm were found in 21 (28%) patients, five of which were not resectable. Overall survival with residual tumour > 1 cm differed significantly from the group with no macroscopic residual tumour (p = 0.003) and with residual tumour ≤ 1 cm (p = 0.04). The CT parameters tumour foci in the diaphragm, mesocolon, greater omentum and peritoneum as well as ascites correlated with macroscopic residual tumour. In the multivariate logistic regression analysis only the CT parameter intraparenchymal liver metastasis was statistically significant with regard to prediction of suboptimal tumour resection (> 1 cm) (OR 8.04; 95% CI 1.57 - 42.4; p = 0.0134). The sensitivity, specificity, PPV and NPV were 37.5, 89.7, 66.7 and 72.2%. Conclusion Although risk parameters for suboptimal tumour reduction can be identified by CT of the abdomen, surgical exploration with histological confirmation of the diagnosis is essential because of the poor diagnostic accuracy.

CT Scan in the Prediction of Lymph Node Involvement in Ovarian Cancer - a Retrospective Analysis of a Tertiary Gyneco-Oncological Unit

Background The prognostic value of lymph node removal in ovarian cancer varies depending on the tumor stage. While in the advanced stage the removal of clinically normal lymph nodes does not improve the prognosis, this is still unclear in the early stages. Evaluation of the lymph nodes based on preoperative imaging influences the surgical procedure.

Methods This retrospective analysis was performed by analyzing data from 114 patients with ovarian cancer, treated in our university hospital in the years 2000 – 2012. Diagnostic performance of imaging by computer tomography with respect to the correct prediction of lymph node status was analyzed in terms of sensitivity, specificity, positive predictive value and negative predictive value.

Results Imaging by computer tomography showed a rather limited diagnostic performance with regard to the detection of lymph node metastases in ovarian cancer, with a sensitivity of 40.7%, a specificity of 89.1%, a positive predictive value of 80.0%, and a negative predictive value of 58.3%. A separate analysis for pelvic and paraaortic lymph node involvement showed a better diagnostic performance of computer tomography for the detection of positive paraaortic lymph nodes (41.2, 93.1, 84.0, and 64.3% for sensitivity, specificity, positive predictive value and negative predictive value, respectively) as compared to the detection of positive pelvic lymph nodes (25.6, 91.8, 62.5, and 69.8%).

Conclusion The preoperative prediction of lymph node status by computer tomography is limited. A decision for or against lymphadenectomy should not be made solely on the basis of this approach.

Laparoscopic Surgical Algorithm to Triage the Timing of Tumor Reductive Surgery in Advanced Ovarian Cancer

OBJECTIVE

To estimate the effects of a laparoscopic scoring algorithm to triage patients with advanced ovarian cancer to immediate or delayed debulking to improve complete gross surgical resection rates and determine the resulting clinical outcomes.

METHODS

We prospectively performed laparoscopic assessment on patients with suspected advanced-stage ovarian cancer from April 2013 to December 2016 to determine primary resectability at tumor reductive surgery. Patients with medically inoperable or distant metastatic disease received neoadjuvant chemotherapy. Two-surgeon scoring was performed in a blinded fashion using a validated scoring method. Patients with predictive index value scores less than 8 were offered primary surgery and those with scores 8 or greater received neoadjuvant chemotherapy. Univariate and multivariate analysis was performed for effects on progression-free survival.

RESULTS

Six hundred twenty-one patients presenting with presumed advanced ovarian cancer were evaluated during the study period and 488 patients met inclusion criteria. Two hundred fifteen patients underwent laparoscopic scoring, of whom 125 had predictive index value scores less than 8 and 84 had predictive index value scores 8 or greater. Blinded two-surgeon predictive index value scoring resulted in bivariate discordance in only 2% of patients. Tumor cytoreduction led to no gross residual disease (R0 resection) in 88% of patients in the primary surgery group and 74% in the neoadjuvant chemotherapy group. Patients triaged to primary surgery had an improved progression-free survival of 21.4 months versus 12.9 months in those patients undergoing neoadjuvant chemotherapy (P<.001). Median progression-free survival by treatment group and residual disease status was as follows: primary surgery-R0 23.5 months; primary surgery-R1 (any gross residual disease) 17.6 months; neoadjuvant chemotherapy-R0 15.5 months; and neoadjuvant chemotherapy-R1 12.9 months (P<.001). On multivariate analysis for progression-free survival, baseline CA 125 (P=.001) and gross residual disease at tumor reductive surgery (P=.01) were significantly associated with progression-free survival.

CONCLUSION

Laparoscopic triage assessment allowed for a personalized approach to the management of patients with advanced ovarian cancer and resulted in high complete surgical resection rates at tumor reductive surgery.

Pre-operative prediction of residual disease after interval cytoreduction for epithelial ovarian cancer using HE4

BACKGROUND

Presence of residual disease after cytoreductive surgery is an important negative prognostic factor for patients with advanced stage epithelial ovarian cancer. Surgery is of limited benefit when the diameter of residual disease is >1 cm. Residual disease is difficult to predict before surgery. The multivariate model Cancer Ovarii Non-invasive Assessment of Treatment Strategy (CONATS) index, based on serum biomarker HE4, age, and World Health Organization performance status, predicted no visible residual disease in patients undergoing primary cytoreductive surgery with an area under the curve (AUC) of 0.85. The AUC of predicting residual disease >1 cm was not reported, although this can be of importance for pre-operative decision making, especially in fragile patients. We tested this model for predicting residual disease >1 cm in patients undergoing interval cytoreduction.

METHODS

We retrospectively included patients with advanced epithelial ovarian cancer who underwent interval cytoreduction between January 2010 and December 2017 in two tertiary centers in the Netherlands. HE4 was measured with electrochemiluminescence in pre-operative samples. The CONATS index was used to predict residual disease. AUCs were calculated to predict residual disease >1 cm.

RESULTS

A total of 273 patients were included. Mean (SD) age was 64 (11) years. Median number of cycles of neoadjuvant chemotherapy was 3 (range 3-6) and the most common regimen used consisted of carboplatin and paclitaxel. Before interval cytoreduction, 19 patients (7%) showed complete response to chemotherapy, 251 patients (92%) showed partial response, and 3 patients (1%) showed stable disease at imaging. Following surgery, 232 patients (85%) had residual disease ≤1 cm and 41 patients (15%) had residual disease >1 cm. The AUC was 0.80 for predicting residual disease >1 cm. In patients ≥70 years of age the AUC was 0.82.

CONCLUSION

The CONATS index predicts surgical outcome after interval cytoreduction and is useful in counseling patients about the chance of whether an optimal interval cytoreduction can be achieved. This could be especially helpful in counseling elderly patients in whom surgery has a high risk of complications.

Port site resection after laparoscopy in advance ovarian cancer surgery: Time to abandon?

INTRODUCTION

The use of laparoscopy in the treatment and management of advanced ovarian cancer is increasing among the gynaecologic oncologists. The development of port site metastases after laparoscopy is a concern and a matter of debate due to theoretical iatrogenic disease spread. Port site resection (PSR) has been proposed as an option to avoid this scenario.

MATERIAL AND METHODS

One hundred and twenty-three patients with advanced ovarian cancer (FIGO III-IV) and with diagnostic laparoscopy were included and after cytoreductive surgery were classified into two groups: no port site resection (No-PSR) and port site resection (PSR). Based on the pathological results of all port site specimens, PSR was classified as positive port site metastasis (PSM+) and negative port site metastasis (PSM-).

RESULTS

In 82 cases, the laparoscopic port site access was resected in the debulking surgery. At the final specimen examination, 49% presented as PSM+. No statistical differences regarding survival were found, either between the No-PSR and PSR groups (p = 0.28) or between the PSM+ and PSM - groups (p = 0.92). A higher wound complication rate was found in the PSR group (17% vs. 34%; p = 0.047). The RR (Relative Risk) of wound events for PSR was 2.42 (95% CI 1.09-5.35; p = 0.0296).

CONCLUSIONS

To date, not only there is no data supporting PSR after laparoscopy in advanced ovarian cancer, but the role of PSM+ in prognosis also remains unclear. In patients in which laparoscopy is performed prior to the debulking procedure, the PSR may not be recommended in those cases of no macroscopic port site metastasis.

Optimization of surgical treatment of advanced ovarian cancer: a Spanish expert perspective

BACKGROUND

Optimal upfront treatment of patients with advanced ovarian cancer is complex and requires the adequate function of a multidisciplinary team. Specific standard of quality of care needs to be taken into consideration.

METHODS

A literature search in PubMed was performed using the following criteria: ("ovarian neoplasms"[MeSH Terms] OR ("ovarian"[All Fields] AND "neoplasms"[All Fields]) OR "ovarian neoplasms"[All Fields] OR ("ovarian"[All Fields] AND "cancer"[All Fields]) OR "ovarian cancer"[All Fields])"[Date - Publication]: "2018/01/14"[Date - Publication]).

RESULTS

This article describes how to optimize the surgical management of advanced ovarian cancer, to achieve the best results in terms of survival and quality of life. For this purpose, this document will cover aspects related to pre-, intra- and postoperative care of newly diagnosed advanced ovarian cancer patients.

CONCLUSION

Optimizing upfront treatment of patients with advanced ovarian cancer is complex and requires a structured quality management program including the wise judgment of a multidisciplinary team. Surgeries performed by gynecologic oncologists with formal training in cytoreductive techniques at referral centers are crucial factors to obtain better clinical and oncological outcomes. However, other factors such as the patient's clinical status, the hospital infrastructure and equipment, as well as the tumor biology of each individual patient should also be taken into account before deciding on an initial therapeutic strategy for advanced-stage ovarian cancer to offer patients the best quality of care.

Concordance of a laparoscopic scoring algorithm with primary surgery findings in advanced stage ovarian cancer

OBJECTIVES

To determine the concordance between the laparoscopic scoring assessment and extent of disease identified at primary tumor reductive surgery (TRS) in patients with advanced ovarian cancer.

METHODS

From April 2013 to June 2017, we prospectively triaged patients with stage IIA to IVB ovarian cancer to laparoscopic scoring assessment. A validated predictive index value (PIV) score (range: 0-14) was assigned. Patients with PIV scores <8 were offered primary surgery and those with score ≥8 received NACT. Patients who underwent primary TRS had a second PIV score based on laparotomy findings. Concordance percentages were calculated between the two scores. Positive predictive value (PPV) was calculated to reflect the performance of the laparoscopic PIV score to predict R0 (complete gross resection) at TRS.

RESULTS

226 patients underwent laparoscopic scoring assessment, of which 139 (61.5%) had a PIV score <8 and 81 (35.8%) had a PIV score ≥8. 6 patients (2.7%) were unscoreable. There was 96% overall concordance between PIV scores at laparoscopy and primary TRS. Concordance scores by location were: bowel infiltration 74.7%, mesenteric disease 84.6%, liver surface involvement 86.5%, omental disease 89.7%, diaphragm disease 92.9%, stomach infiltration 94.7%, peritoneal carcinomatosis 94.8%. A laparoscopic PIV score of <8 had a PPV of 85.4% at predicting R0 at primary TRS.

CONCLUSIONS

Laparoscopic assessment of tumor burden is a feasible tool to predict R0 cytoreduction in patients with advanced ovarian cancer. Concordance between PIV scores at laparoscopy and primary TRS varied by anatomic location, with the lowest concordance seen in predicting bowel infiltration.

Neoadjuvant chemotherapy followed by fast-track cytoreductive surgery plus short-course hyperthermic intraperitoneal chemotherapy (HIPEC) in advanced ovarian cancer: preliminary results of a promising all-in-one approach

Purpose

Hyperthermic intraperitoneal chemotherapy (HIPEC) has been considered a promising treatment option for advanced or recurrent ovarian cancer, but there is no clear evidence based on randomized controlled trials to advocate this approach as a standard therapy. In this study, we aim to present the early outcomes and insights after an interim analysis of a pioneering clinical trial in Brazil.

Methods

This study was a cross-sectional analysis of early data from our ongoing clinical trial – an open-label, double-center, single-arm trial on the safety and efficacy of using HIPEC for advanced ovarian cancer (ClinicalTrials.gov: NCT02249013). A fast-track recovery strategy was also applied to improve patient outcomes.

Results

Nine patients with stage IIIB (n=1) or IIIC (n=8) epithelial malignancies were enrolled until February 2017. The median (range) serum CA125 level at diagnosis was 692 (223.7–6550) U/mL. The median number of preoperative cycles of intravenous (i.v.) chemotherapy was 3 (2–4), resulting in peritoneal cancer index scores of 9 (3–18) at the time of HIPEC. Time of restarting i.v. chemotherapy was 37 (33–50) days with all patients completing 6 cycles as planned. The median operation time was 395 (235–760) minutes, the length of hospital stay was 4 (3–10) days, and all the patients left the ICU on the morning after the procedure. Two patients experienced no postoperative complications, whereas 91% of the complications were minor G1/G2 events. Preliminary assessment also suggested no impairment of the patient’s quality of life.

Conclusion

Our comprehensive protocol might represent a promising all-in-one approach for advanced ovarian cancer. The patient recruitment for this trial is ongoing.

Predictive modeling for determination of microscopic residual disease at primary cytoreduction: An NRG Oncology/Gynecologic Oncology Group 182 Study

OBJECTIVE

Microscopic residual disease following complete cytoreduction (R0) is associated with a significant survival benefit for patients with advanced epithelial ovarian cancer (EOC). Our objective was to develop a prediction model for R0 to support surgeons in their clinical care decisions.

METHODS

Demographic, pathologic, surgical, and CA125 data were collected from GOG 182 records. Patients enrolled prior to September 1, 2003 were used for the training model while those enrolled after constituted the validation data set. Univariate analysis was performed to identify significant predictors of R0 and these variables were subsequently analyzed using multivariable regression. The regression model was reduced using backward selection and predictive accuracy was quantified using area under the receiver operating characteristic area under the curve (AUC) in both the training and the validation data sets.

RESULTS

Of the 3882 patients enrolled in GOG 182, 1480 had complete clinical data available for the analysis. The training data set consisted of 1007 patients (234 with R0) while the validation set was comprised of 473 patients (122 with R0). The reduced multivariable regression model demonstrated several variables predictive of R0 at cytoreduction: Disease Score (DS) (p<0.001), stage (p=0.009), CA125 (p<0.001), ascites (p<0.001), and stage-age interaction (p=0.01). Applying the prediction model to the validation data resulted in an AUC of 0.73 (0.67 to 0.78, 95% CI). Inclusion of DS enhanced the model performance to an AUC of 0.83 (0.79 to 0.88, 95% CI).

CONCLUSIONS

We developed and validated a prediction model for R0 that offers improved performance over previously reported models for prediction of residual disease. The performance of the prediction model suggests additional factors (i.e. imaging, molecular profiling, etc.) should be explored in the future for a more clinically actionable tool.

High-Grade Serous Ovarian Cancer: Associations between BRCA Mutation Status, CT Imaging Phenotypes, and Clinical Outcomes

Purpose To investigate the associations between BRCA mutation status and computed tomography (CT) phenotypes of high-grade serous ovarian cancer (HGSOC) and to evaluate CT indicators of cytoreductive outcome and survival in patients with BRCA-mutant HGSOC and those with BRCA wild-type HGSOC. Materials and Methods This HIPAA-compliant, institutional review board-approved retrospective study included 108 patients (33 with BRCA mutant and 75 with BRCA wild-type HGSOC) who underwent CT before primary debulking. Two radiologists independently reviewed the CT findings for various qualitative CT features. Associations between CT features, BRCA mutation status, cytoreductive outcome, and progression-free survival (PFS) were evaluated by using logistic regression and Cox proportional hazards regression, respectively. Results Peritoneal disease (PD) pattern, presence of PD in gastrohepatic ligament, mesenteric involvement, and supradiaphragmatic lymphadenopathy at CT were associated with BRCA mutation status (multiple regression: P < .001 for each CT feature). While clinical and CT features were not associated with cytoreductive outcome for patients with BRCA-mutant HGSOC, presence of PD in lesser sac (odds ratio [OR] = 2.40) and left upper quadrant (OR = 1.19), mesenteric involvement (OR = 7.10), and lymphadenopathy in supradiaphragmatic (OR = 2.83) and suprarenal para-aortic (OR = 4.79) regions were associated with higher odds of incomplete cytoreduction in BRCA wild-type HGSOC (multiple regression: P < .001 each CT feature). Mesenteric involvement at CT was associated with significantly shorter PFS for both patients with BRCA-mutant HGSOC (multiple regression: hazard ratio [HR] = 26.7 P < .001) and those with BRCA wild-type HGSOC (univariate analysis: reader 1, HR = 2.42, P < .001; reader 2, HR = 2.61; P < .001). Conclusion Qualitative CT features differed between patients with BRCA-mutant HGSOC and patients with BRCA wild-type HGSOC. CT indicators of cytoreductive outcome varied according to BRCA mutation status. Mesenteric involvement at CT was an indicator of significantly shorter PFS for both patients with BRCA-mutant HGSOC and those with BRCA wild-type HGSOC. ^© RSNA, 2017 Online supplemental material is available for this article.

Advanced Primary Epithelial Ovarian and Peritoneal Carcinoma-Does Diagnostic Accuracy of Preoperative CT Scan for Detection of Peritoneal Metastatic Sites Reflect into Prediction of Suboptimal Debulking? A Prospective Study

Ovarian cancer is the seventh most common cancer in females worldwide. Optimal debulking is the standard treatment but possible only in 30-85% of advanced stages. Knowing exactly the disease extent preoperatively may predict suboptimal debulking. We analyzed diagnostic accuracy of preoperative CT scan in disease mapping and prediction of suboptimal debulking in a prospective observational study from March 2013 to May 2015 in a tertiary hospital. Adults below the age of 75 years with ECOG PS-0, 1, 2, clinically/radiologically newly diagnosed stage IIIc epithelial ovarian (EOC), and primary peritoneal carcinoma (PPC) were included. Neoadjuvant chemotherapy recipients were excluded. Preoperative multidetector CT (MDCT) scan showing deposits at 19 predetermined abdominopelvic sites were compared with the same sites seen at laparotomy and corresponding accuracies of CT scan calculated. Primary debulking surgery was done to achieve debulking to nil or less than 1-cm residual disease. Stepwise logistic regression models were used to determine the frequent suboptimal debulking sites and the predictive performance of the clinical and CT scan findings. A total of 36 patients were enrolled. The optimal debulking rate was 50%. The CT scan could detect the disease-bearing sites with overall sensitivity of 68.29%, specificity of 89%, accuracy of 78.07%, and positive and negative predictive values of 99 and 50.1%, respectively. Upon multivariate analysis, bowel mesentery (p 0.011) and omental extension (p 0.025) were associated with suboptimal debulking. CT scan accuracy at these sites (predictive performance) was 86.1%. We identified small bowel mesentery and omental extension (to spleen/stomach/colon) as sites associated with suboptimal debulking. MDCT accurately depicts peritoneal metastases, although sensitivity is reduced in certain areas of significance for optimal debulking. Further validation with more number of patients is warranted.

Serum HE4 superior to CA125 in predicting poorer surgical outcome of epithelial ovarian cancer

Epithelial ovarian cancer (EOC) remains the deadliest form of gynecological cancers. Optimal tumor debulking, no matter the primary or the interval, is the most important prognostic factor for EOC, so there is an urgent demand for biomarkers to predict surgical outcome. The aim of this study was to investigate whether serum human epididymis protein 4 (HE4) and cancer antigen 125 (CA125) could predict surgical outcome of EOC. The levels of preoperative serum HE4 and CA125 were determined by electrochemiluminescence (ECLIA) in 82 EOC patients, comprising 39 subjected to primary debulking surgery (PDS) and 43 with extensive stage III or IV disease to neoadjuvant chemotherapy followed by interval debulking surgery (NACT-IDS). Among 39 patients subjected to primary debulking surgery, HE4 was superior to CA125 in predicting surgical outcome (area under curve [AUC] 0.758 vs. 0.633). At a cutoff of 353.22 pmol/L, HE4 reached 77.4 % in sensitivity and 75 % in specificity. The prediction of surgical outcome of interval debulking surgery based on preoperative HE4 and CA125 values was performed in 43 patients who received NACT-IDS. The difference of AUC between HE4 and CA125 (0.793 vs. 0.663) indicating that HE4 was the better biomarker to predict surgical outcome of IDS. A pre-IDS HE4 value of 154.3 pmol/L is the optimal cutoff to identify patients who would not benefit from IDS with a sensitivity of 92.9 % and a specificity of 69 %. The change (>70 %) of HE4 before and after neoadjuvant chemotherapy could predict optimal interval debulking surgery. Serum HE4 was superior to CA125 in predicting surgical outcome of primary debulking surgery and interval debulking surgery. The change (absolute value or percentage) of HE4 in neoadjuvant chemotherapy could predict the outcome of interval debulking surgery.

A novel index for preoperative, non-invasive prediction of macro-radical primary surgery in patients with stage IIIC-IV ovarian cancer-a part of the Danish prospective pelvic mass study

The purpose of this study was to develop a novel index for preoperative, non-invasive prediction of complete primary cytoreduction in patients with FIGO stage IIIC-IV epithelial ovarian cancer. Prospectively collected clinical data was registered in the Danish Gynecologic Cancer Database. Blood samples were collected within 14 days of surgery and stored by the Danish CancerBiobank. Serum human epididymis protein 4 (HE4), serum cancer antigen 125 (CA125), age, performance status, and presence/absence of ascites at ultrasonography were evaluated individually and combined to predict complete tumor removal. One hundred fifty patients with advanced epithelial ovarian cancer were treated with primary debulking surgery (PDS). Complete PDS was achieved in 41 cases (27 %). The receiver operating characteristic curves demonstrated an area under the curve of 0.785 for HE4, 0.678 for CA125, and 0.688 for age. The multivariate model (Cancer Ovarii Non-invasive Assessment of Treatment Strategy (CONATS) index), consisting of HE4, age, and performance status, demonstrated an AUC of 0.853. According to the Danish indicator level, macro-radical PDS should be achieved in 60 % of patients admitted to primary surgery (positive predictive value of 60 %), resulting in a negative predictive value of 87.5 %, sensitivity of 68.3 %, specificity of 83.5 %, and cutoff of 0.63 for the CONATS index. Non-invasive prediction of complete PDS is possible with the CONATS index. The CONATS index is meant as a supplement to the standard preoperative evaluation of each patient. Evaluation of the CONATS index combined with radiological and/or laparoscopic findings may improve the assessment of the optimal treatment strategy in patients with advanced epithelial ovarian cancer.

Functional MR Imaging in Gynecologic Cancer

Dynamic-contrast enhanced (DCE) and diffusion-weighted (DW) MR imaging are invaluable in the detection, staging, and characterization of uterine and ovarian malignancies, for monitoring treatment response, and for identifying disease recurrence. When used as adjuncts to morphologic T2-weighted (T2-W) MR imaging, these techniques improve accuracy of disease detection and staging. DW-MR imaging is preferred because of its ease of implementation and lack of need for an extrinsic contrast agent. MR spectroscopy is difficult to implement in the clinical workflow and lacks both sensitivity and specificity. If used quantitatively in multicenter clinical trials, standardization of DCE- and DW-MR imaging techniques and rigorous quality assurance is mandatory.

Predicting surgical outcome in patients with International Federation of Gynecology and Obstetrics stage III or IV ovarian cancer using computed tomography: a systematic review of prediction models

OBJECTIVE

Maximal cytoreduction to no residual disease is an important predictor of prognosis in patients with advanced-stage epithelial ovarian cancer. Preoperative prediction of outcome of surgery should guide treatment decisions, for example, primary debulking or neoadjuvant chemotherapy followed by interval debulking surgery. The objective of this study was to systematically review studies evaluating computed tomography imaging based models predicting the amount of residual tumor after cytoreductive surgery for advanced-stage epithelial ovarian cancer.

METHODS

We systematically searched the literature for studies investigating multivariable models that predicted the amount of residual disease after cytoreductive surgery in advanced-stage epithelial ovarian cancer using computed tomography imaging. Detected studies were scored for quality and classified as model derivation or validation studies. We summarized their performance in terms of discrimination when possible.

RESULTS

We identified 11 studies that described 13 models. The 4 models that were externally validated all had a poor discriminative capacity (sensitivity, 15%-79%; specificity, 32%-64%). The only internal validated model had an area under the receiver operating characteristic curve of 0.67. Peritoneal thickening, mesenterial and diaphragm disease, and ascites were most often used as predictors in the final models. We did not find studies that assessed the impact of prediction model on outcomes.

CONCLUSIONS

Currently, there are no external validated studies with a good predictive performance for residual disease. Studies of better quality are needed, especially studies that focus on predicting any residual disease after surgery.

Prediction of incomplete primary debulking surgery in patients with advanced ovarian cancer: An external validation study of three models using computed tomography

OBJECTIVE

To test the ability of three prospectively developed computed tomography (CT) models to predict incomplete primary debulking surgery in patients with advanced (International Federation of Gynecology and Obstetrics stages III-IV) ovarian cancer.

METHODS

Three prediction models to predict incomplete surgery (any tumor residual >1cm in diameter) previously published by Ferrandina (models A and B) and by Gerestein were applied to a validation cohort consisting of 151 patients with advanced epithelial ovarian cancer. All patients were treated with primary debulking surgery in the Eastern part of the Netherlands between 2000 and 2009 and data were retrospectively collected. Three individual readers evaluated the radiographic parameters and gave a subjective assessment. Using the predicted probabilities from the models, the area under the curve (AUC) was calculated which represents the discriminative ability of the model.

RESULTS

The AUC of the Ferrandina models was 0.56, 0.59 and 0.59 in model A, and 0.55, 0.60 and 0.59 in model B for readers 1, 2 and 3, respectively. The AUC of Gerestein's model was 0.69, 0.61 and 0.69 for readers 1, 2 and 3, respectively. AUC values of 0.69 and 0.63 for reader 1 and 3 were found for subjective assessment.

CONCLUSIONS

Models to predict incomplete surgery in advanced ovarian cancer have limited predictive ability and their reproducibility is questionable. Subjective assessment seems as successful as applying predictive models. Present prediction models are not reliable enough to be used in clinical decision-making and should be interpreted with caution.

Suboptimal cytoreduction in ovarian carcinoma is associated with molecular pathways characteristic of increased stromal activation

OBJECTIVE

Suboptimal cytoreductive surgery in advanced epithelial ovarian cancer (EOC) is associated with poor survival but it is unknown if poor outcome is due to the intrinsic biology of unresectable tumors or insufficient surgical effort resulting in residual tumor-sustaining clones. Our objective was to identify the potential molecular pathway(s) and cell type(s) that may be responsible for suboptimal surgical resection.

METHODS

By comparing gene expression in optimally and suboptimally cytoreduced patients, we identified a gene network associated with suboptimal cytoreduction and explored the biological processes and cell types associated with this gene network.

RESULTS

We show that primary tumors from suboptimally cytoreduced patients express molecular signatures that are typically present in a distinct molecular subtype of EOC characterized by increased stromal activation and lymphovascular invasion. Similar molecular pathways are present in EOC metastases, suggesting that primary tumors in suboptimally cytoreduced patients are biologically similar to metastatic tumors. We demonstrate that the suboptimal cytoreduction network genes are enriched in reactive tumor stroma cells rather than malignant tumor cells.

CONCLUSION

Our data suggest that the success of cytoreductive surgery is dictated by tumor biology, such as extensive stromal reaction and increased invasiveness, which may hinder surgical resection and ultimately lead to poor survival.

Role of aggressive surgical cytoreduction in advanced ovarian cancer

Ovarian cancer is the eighth most frequent cancer in women and is the most lethal gynecologic malignancy worldwide. The majority of ovarian cancer patients are newly diagnosed presenting with advanced-stage disease. Primary cytoreductive surgery and adjuvant taxane- and platinum-based combination chemotherapy are the standard treatment for advanced ovarian cancer. A number of studies have consistently shown that successful cytoreductive surgery and the resultant minimal residual disease are significantly associated with survival in patients with this disease. Much has been written and even more debated regarding the competing perspectives of biology of ovarian cancer versus the value of aggressive surgical resection. This review will focus on the current evidences and outcomes supporting the positive impact of aggressive surgical effort on survival in the primary management of ovarian cancer.

Role of aggressive surgical cytoreduction in advanced ovarian cancer

Ovarian cancer is the eighth most frequent cancer in women and is the most lethal gynecologic malignancy worldwide. The majority of ovarian cancer patients are newly diagnosed presenting with advanced-stage disease. Primary cytoreductive surgery and adjuvant taxane- and platinum-based combination chemotherapy are the standard treatment for advanced ovarian cancer. A number of studies have consistently shown that successful cytoreductive surgery and the resultant minimal residual disease are significantly associated with survival in patients with this disease. Much has been written and even more debated regarding the competing perspectives of biology of ovarian cancer versus the value of aggressive surgical resection. This review will focus on the current evidences and outcomes supporting the positive impact of aggressive surgical effort on survival in the primary management of ovarian cancer.

Usefulness of human epididymis protein 4 in predicting cytoreductive surgical outcomes for advanced ovarian tubal and peritoneal carcinoma

OBJECTIVE

Human epididymis protein 4 (HE4) is a promising biomarker of epithelial ovarian cancer (EOC). But its role in assessing the primary optimal debulking (OD) of EOC remains unknown. The purpose of this study is to elucidate the ability of preoperative HE4 in predicting the primary cytoreductive outcomes in advanced EOC, tubal or peritoneal carcinoma.

METHODS

We reviewed the records of 90 patients with advanced ovarian, tubal or peritoneal carcinoma who underwent primary cytoreduction at the Department of Obstetrics and Gynecology of Peking University People's Hospital between November 2005 and October 2010. Preoperative serum HE4 and CA125 levels were detected with EIA kit. A receiver operating characteristic (ROC) curve was used to determine the most useful HE4 cut-off value. Logistic regression analysis was performed to identify significant preoperative clinical characteristics to predict optimal primary cytoreduction.

RESULTS

OD was achieved in 47.7% (43/48) of patients. The median preoperative HE4 level for patients with OD vs. suboptimal debulking was 423 and 820 pmol/L, respectively (P<0.001). The areas under the ROC curve for HE4 and CA125 were 0.716 and 0.599, respectively (P=0.080). The most useful HE4 cut-off value was 473 pmol/L. Suboptimal cytoreduction was obtained in 66.7% (38/57) of cases with HE4 ≥473 pmol/L compared with only 27.3% (9/33) of cases with HE4 <473 pmol/L. At this threshold, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for diagnosing suboptimal debulking were 81%, 56%, 67%, and 73%, respectively. Logistic regression analysis showed that the patients with HE4 ≥473 pmol/L were less likely to achieve OD (odds ratio =5.044, P=0.002).

CONCLUSIONS

Preoperative serum HE4 may be helpful to predict whether optimal cytoreductive surgery could be obtained or whether extended cytoreduction would be needed by an interdisciplinary team.

Differences in regional diagnostic strategies and in intended versus actual first-line treatment of patients with advanced ovarian cancer in Denmark

BACKGROUND

Triage of patients with ovarian cancer to primary debulking surgery (PDS) or neoadjuvant chemotherapy (NACT) is challenging. In Denmark, the use of NACT has increased, but substantial differences in the use of NACT or PDS exist among centers. We aimed to characterize the differences between intended and actual first-line treatments in addition to the differences in the triage process among the centers and to evaluate the different diagnostic modalities and the clinical aspects' influence in the triage process.

MATERIALS AND METHODS

From 4 centers, forms containing data about the diagnostic process and intended treatment were prospectively collected and merged with data from the Danish Gynecological Cancer Database and medical records.

RESULTS

Of the 671 completed forms, 540 patients had stage IIIC or IV epithelial ovarian cancer. Of the 238 (44%) referred to PDS, 91% received PDS and 4% never had debulking surgery. Of the 288 patients (53%) referred to NACT, 44% were never debulked. Fourteen patients (3%) were referred to palliative treatment. The use of different imaging modalities, diagnostic laparoscopy, and laparotomy varied significantly among the centers. Diagnostic surgical procedures were considered to be most influential in the triage process. Regardless of the intended first-line treatment or center, the tumor size and dissemination was the most influential clinical aspect.

CONCLUSIONS

In Denmark, substantial differences exist between intended and actual first-line treatments as well as in the diagnostic process and use of NACT, calling for further discussion on diagnostic strategy and therapeutically approach for patients with advanced ovarian cancer.

Nomogram for predicting incomplete cytoreduction in advanced ovarian cancer patients

OBJECTIVE

Accurately predicting cytoreducibility in advanced-ovarian cancer is needed to establish preoperative plans, consider neoadjuvant chemotherapy, and improve clinical trial protocols. We aimed to develop a positron-emission tomography/computed tomography-based nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients.

METHODS

Between 2006 and 2012, 343 consecutive advanced-ovarian cancer patients underwent positron-emission tomography/computed tomography before primary cytoreduction: 240 and 103 patients were assigned to the model development or validation cohort, respectively. After reviewing the detailed surgical documentation, incomplete cytoreduction was defined as a remaining gross residual tumor. We evaluated each individual surgeon's surgical aggressiveness index (number of high-complex surgeries/total number of surgeries). Possible predictors, including surgical aggressiveness index and positron-emission tomography/computed tomography features, were analyzed using logistic regression modeling. A nomogram based on this model was developed and externally validated.

RESULTS

Complete cytoreduction was achieved in 120 patients (35%). Surgical aggressiveness index and five positron-emission tomography/computed tomography features were independent predictors of incomplete cytoreduction. Our nomogram predicted incomplete cytoreduction by incorporating these variables and demonstrated good predictive accuracy (concordance index = 0.881; 95% CI = 0.838-0.923). The predictive accuracy of our validation cohort was also good (concordance index = 0.881; 95% CI = 0.790-0.932) and the predicted probability was close to the actual observed outcome. Our model demonstrated good performance across surgeons with varying degrees of surgical aggressiveness.

CONCLUSION

We have developed and validated a nomogram for predicting incomplete cytoreduction in advanced-ovarian cancer patients which may help stratify patients for clinical trials, establish meticulous preoperative plans, and determine if neoadjuvant chemotherapy is warranted.