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Background The foundation of modern ovarian cancer care is cytoreductive surgery to remove all macroscopic disease (R0). Identification of R0 resection patients may help individualise treatment. Machine learning and AI have been shown to be effective systems for classification and prediction. For a disease as heterogenous as ovarian cancer, they could potentially outperform conventional predictive algorithms for routine clinical use. We investigated the performance of an AI system, the k -nearest neighbor ( k -NN) classifier, to predict R0, comparing it with logistic regression. Patients diagnosed with advanced stage, high grade serous ovarian, tubal and primary peritoneal cancer, undergoing surgical cytoreduction from 2015 to 2019, was selected from the ovarian database. Performance variables included age, BMI, Charlson Comorbidity Index, timing of surgery, surgical complexity and disease score. The k -NN algorithm classified R0 vs non-R0 patients using 3–20 nearest neighbors. Prediction accuracy was estimated as percentage of observations in the training set correctly classified. Results 154 patients were identified, with mean age of 64.4  +  10.5 yrs., BMI of 27.2  +  5.8 and mean SCS of 3  +  1 (1–8). Complete and optimal cytoreduction was achieved in 62 and 88% patients. The mean predictive accuracy was 66%. R0 resection prediction of true negatives was as high as 90% using k  = 20 neighbors. Conclusions The k -NN algorithm is a promising and versatile tool for R0 resection prediction. It slightly outperforms logistic regression and is expected to improve accuracy with data expansion.

Background The value of the magnetic resonance imaging (MRI) in the assessment of women with endometrial hyperplasia and its role in diagnosis of myometrial invasion or coexistence of cancer is not known. This study aimed to evaluate the accuracy and usefulness of MRI in the management of patients diagnosed on endometrial biopsy with complex endometrial hyperplasia with atypia (CEHA). Methods A retrospective study of 86 cases diagnosed with endometrial hyperplasia with atypia on the initial endometrial biopsy in a tertiary university teaching hospital between 2010 and 2015 was carried out. The MRI accuracy in predicting malignant changes and influence the clinical management was compared among women who had either pelvic MRI, transvaginal ultrasound (TVUS), or no additional imagistic studies. Results MRI was performed in 24 (28%) and TVUS in 11 (13%)cases, while 51 (59%) women had no additional imagistic studies. In the group of women with no imaging studies, 26/51 (51%) were surgically treated and 8/26 (31%) were diagnosed with endometrial cancer (EEC) stage 1a. In the group of women who had TVUS, 5/11 (45%) were surgically treated and none was diagnosed with EEC. In the group of women who underwent an MRI examination, 20/24 (83%) were surgically treated. Among these, 11/20 (55%) were diagnosed with EEC, 7 had EEC stage 1a, and 4 had EEC stage 1b. Although MRI was able to identify malignant changes with a good sensitivity (91.7%), it had a low specificity in characterisation of malignant transformation (8%). MRI correctly identified 31% of the stage 1a and 33% of the stage 1b endometrial cancer. Conclusion In this study, we found a potential diagnostic value of MRI for identifying malignant transformation in patients with CEHA. However, pelvic MRI has a rather weak predictive value of myometrial invasion in women with CEHA and concurrent EEC. The diagnostic and therapeutic benefits of MRI assessment in patients with CEHA need further validation.

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.

More people are living with and beyond a cancer diagnosis. There is limited understanding of the long-term effects of cancer and cancer treatment on quality of life and personal and household finances when compared to people without cancer. In a separate protocol we have proposed to link de-identified data from electronic primary care and hospital records for a large population of cancer survivors and matched controls. In this current protocol, we propose the linkage of Patient Reported Outcomes Measures data to the above data for a subset of this population. The aim of this study is to investigate the full impact of living with and beyond a cancer diagnosis compared to age and gender matched controls. A secondary aim is to test the feasibility of the collection of Patient Reported Outcomes Measures (PROMS) data and the linkage procedures of the PROMs data to electronic health records data. This is a cross-sectional study, aiming to recruit participants treated at the Leeds Teaching Hospitals National Health Service Trust. Eligible patients will be cancer survivors at around 5 years post-diagnosis (breast, colorectal and ovarian cancer) and non-cancer patient matched controls attending dermatology out-patient clinics. They will be identified by running a query on the Leeds Teaching Hospitals Trust patient records system. Approximately 6000 patients (2000 cases and 4000 controls) will be invited to participate via post. Participants will be invited to complete PROMs assessing factors such as quality of life and finances, which can be completed on paper or online (surveys includes established instruments, and bespoke instruments (demographics, financial costs). This PROMs data will then be linked to routinely collected de-identified data from patient's electronic primary care and hospital records. This innovative work aims to create a truly 'comprehensive patient record' to provide a broad picture of what happens to cancer patients across their cancer pathway, and the long-term impact of cancer treatment. Comparisons can be made between the cases and controls, to identify the aspects of life that has had the greatest impact following a cancer diagnosis. The feasibility of linking PROMs data to electronic health records can also be assessed. This work can inform future support offered to people living with and beyond a cancer diagnosis, clinical practice, and future research methodologies.

Background No residual disease (CC 0) following cytoreductive surgery is pivotal for the prognosis of women with advanced stage epithelial ovarian cancer (EOC). Improving CC 0 resection rates without increasing morbidity and no delay in subsequent chemotherapy favors a better outcome in these women. Prerequisites to facilitate this surgical paradigm shift and subsequent ramifications need to be addressed. This quality improvement study assessed 559 women with advanced EOC who had cytoreductive surgery between January 2014 and December 2019 in our tertiary referral centre. Following implementation of the Enhanced Recovery After Surgery (ERAS) pathway and prehabilitation protocols, the surgical management paradigm in advanced EOC patients shifted towards maximal surgical effort cytoreduction in 2016. Surgical outcome parameters before, during, and after this paradigm shift were compared. The primary outcome measure was residual disease (RD). The secondary outcome parameters were postoperative morbidity, operative time (OT), length of stay (LOS) and progression-free-survival (PFS). Results R0 resection rate in patients with advanced EOC increased from 57.3% to 74.4% after the paradigm shift in surgical management whilst peri-operative morbidity and delays in adjuvant chemotherapy were unchanged. The mean OT increased from 133 + 55 min to 197 + 85 min, and postoperative high dependency/intensive care unit (HDU/ICU) admissions increased from 8.1% to 33.1%. The subsequent mean LOS increased from 7.0 + 2.6 to 8.4 + 4.9 days. The median PFS was 33 months. There was no difference for PFS in the three time frames but a trend towards improvement was observed. Conclusions Improved CC 0 surgical cytoreduction rates without compromising morbidity in advanced EOC is achievable owing to the right conditions. Maximal effort cytoreductive surgery should solely be carried out in high output tertiary referral centres due to the associated substantial prerequisites and ramifications.

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. To address this, we devised a Machine Learning (ML)-driven prediction algorithm aimed at prompting and elucidating a communication alert for BT based on anticipated peri-operative events independent of existing BT policies. We analyzed data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. The estimated blood volume (EBV), calculated using the formula EBV = weight × 80, served for setting a 10% EBV threshold for individual intervention. Based on known estimated blood loss (EBL), we identified two distinct groups. The Receiver operating characteristic (ROC) curves revealed satisfactory results for predicting events above the established threshold (AUC 0.823, 95% CI 0.76–0.88). Operative time (OT) was the most significant factor influencing predictions. Intra-operative blood loss exceeding 10% EBV was associated with OT > 250 min, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score > 4. Certain sub-procedures including large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy demonstrated clear associations with an elevated interventional risk. Our findings emphasize the importance of obtaining a rough estimate of OT in advance for precise prediction of blood requirements.

In endometrial cancer (EC), adrenal metastases are rare indicating advanced disease. We report an unusual presentation of EC with solitary adrenal metastases at the time of diagnosis and provide with an updated literature review. A 68-year-old woman was referred with postmenopausal bleeding of several weeks’ duration. Imaging revealed a heterogenous uterine mass and bilateral malignant adnexal masses. Hysteroscopy, endometrial biopsies, and radiological guided biopsies of the adrenal masses confirmed poorly differentiated EC. A PET-CT reported both adrenal metastases being hypermetabolic and suspicious for malignancy. The patient received six neoadjuvant chemotherapy cycles with Carboplatin and Paclitaxel. A repeated CT scan confirmed size reduction for both primary tumour and metastases. The adrenal metastases were no longer PET-avid on repeat PET-CT scan. The patient received a course of hormonal treatment and as per adrenal MDT, she underwent total laparoscopic hysterectomy and bilateral salpingo-oophorectomy followed by bilateral retroperitoneal laparoscopic adrenalectomy two months later. The patient remains asymptomatic on maintenance hydrocortisone 18 months post diagnosis. This is the first report of solitary synchronous adrenal metastases in a patient with EC. Central MDT review is key in providing individualised treatment recommendations of such rare entity.

Highly aneuploid tumours are common in epithelial ovarian cancers (EOC). We investigated whether NuMA expression was associated with this phenomenon.NuMA protein levels in normal and tumour tissues, ovarian cell lines and primary cultures of malignant cells derived from ovarian ascitic fluids were analysed by Affymetrix microarray analysis, immunoblotting, immunohistochemistry (IHC) and immunofluorescence (IF), with results correlated to associated clinical data. Aneuploidy status in primary cultures was determined by FACS analysis.Affymetrix microarray data indicated that NuMA was overexpressed in tumour tissue, primary cultures and cell lines compared to normal ovarian tissue. IHC revealed low to weak NuMA expression in normal tissues. Expression was upregulated in tumours, with a significant association with disease stage in mucinous EOC subtypes (p = 0.009), lymph node involvement (p = 0.03) and patient age (p = 0.04). Additional discontinuous data analysis revealed that high NuMA levels in tumours decreased with grade (p = 0.02) but increased with disease stage (p = 0.04) in serous EOC. NuMA expression decreased in late disease stage 4 endometrioid EOCs. High NuMA levels decreased with increased tumour invasion in all subtypes (p = 0.03). IF of primary cultures revealed that high NuMA levels at mitotic spindle poles were significantly associated with a decreased proportion of cells in cytokinesis (p = 0.05), increased binucleation (p = 0.021) and multinucleation (p = 0.007), and aneuploidy (p = 0.008).NuMA is highly expressed in EOC tumours and high NuMA levels correlate with increases in mitotic defects and aneuploidy in primary cultures.

BackgroundExtramammary Paget’s disease is a rare condition, and the vulva is a common site for it to occur. Despite this, there is a paucity of literature on Paget’s disease of the vulva (VPD). A Cochrane meta-analysis could not draw any conclusions on interventions in VPD. Our aim was to review our practice and improve further management of VPD in our center.MethodsWe reviewed all the cases presented to Leeds Gynaecological Oncology Centre between 1988 and 2016. All cases identified in this interval were followed up until April 2016. All case notes and electronic patient data were retrieved to collate the data.ResultsWe identified 18 cases of VPD. The median age at presentation was 76.9 years. Primary surgery was used in 18 cases. Eight patients had wide local excision with graft reconstruction. Ten women had wide local excision with primary reconstruction. Margins were negative in 27% of the excisions. Sixty percent of patients with clear surgical margins had a recurrence, and 69% of patients with positive margins had a recurrence; there was no statistical difference between the 2 groups for recurrence (P > 0.05). Fifty-eight percent of patients who had recurrence had coexisting malignancy. Logistic regression showed no correlation of recurrence rates due to either age, margin status, or coexisting malignancies.ConclusionsPaget’s disease of the vulva is a rare condition. Our experience indicates that most cases may be amenable to surgical treatment at first presentation. Negative margin status does not reduce the chance of recurrence, and hence patients should be under follow-up for life. The benefit of radical surgery in the absence of reduced recurrences, based on margin status, is questionable. Radiotherapy and imiquimod are options for extensive lesions or recurrent settings. Coexisting malignancies are associated with VPD.

Purpose To assess the significance of CA-125 regression as a prognostic indicator and predictor of optimal cytoreduction at interval debulking surgery (IDS) in women with ovarian or primary peritoneal carcinoma receiving neoadjuvant chemotherapy (NAC). Methods 63 women treated between 2004 and 2007 with neoadjuvant platinum-based chemotherapy followed by IDS were studied retrospectively. Pre-operative CA-125 values were used to calculate a regression coefficient (CA-125r) using exponential regression analysis. Outcome endpoints were overall survival (OS), time to CA-125 progression (TTC) by Rustin criteria and time to second-line treatment (TTS). Results Women with a CA-125 half-life greater than 18 days had a significantly worse OS compared to those with a half-life less than 12 days on univariate testing (HR 3.34, 95% CI 1.25–8.94, p  = 0.017). On multivariable analysis, CA-125r was an independent predictor of OS [HR 1.18 (per 0.01 increase in CA-125r), 95% CI 1.01–1.40, p  = 0.043]. CA-125r was independently predictive of TTC and TTS (HR 1.17, p  ≈ 0.03 for each). CA-125r was also predictive of achieving optimal cytoreduction at IDS (AUC 0.756, p  < 0.001). Conclusions CA-125 regression rate during pre-operative NAC is of independent prognostic value. CA-125 regression rate strongly predicts for optimal cytoreduction.