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In our center, adjuvant chemotherapy is routinely offered in high-grade serous ovarian cancer (HGSOC) patients but less commonly as a standard treatment in low-grade serous ovarian cancer (LGSOC) patients. This study evaluates the efficacy of this paradigm by analysing survival outcomes and by comparing the influence of different clinical and surgical characteristics between women with advanced LGSOC (n = 37) and advanced HGSOC (n = 300). Multivariate analysis was used to identify independent prognostic features for survival in LGSOC and HGSOC. Adjuvant chemotherapy was given in 99.7% of HGSOC patients versus in 27% of LGSOC (p < 0.0001). The LGSOC patients had greater surgical complexity scores (p < 0.0001), more frequent postoperative ICU/HDU admissions (p = 0.0002), and higher peri-/post-operative morbidity (p < 0.0001) compared to the HGSOC patients. The 5-year OS and progression-free survival (PFS) was 30% and 13% for HGSOC versus 57% and 21.6% for LGSOC, p = 0.016 and p = 0.044, respectively. Surgical complexity (HR 5.3, 95%CI 1.2–22.8, p = 0.024) and complete cytoreduction (HR 62.4, 95% CI 6.8–567.9, p < 0.001) were independent prognostic features for OS in LGSOC. This study demonstrates no clear significant survival advantage of chemotherapy in LGSOC. It highlights the substantial survival benefit of dynamic multi-visceral surgery to achieve complete cytoreduction as the primary treatment for LGSOC patients.

Background: The Peritoneal Carcinomatosis Index (PCI) and the Intra-operative Mapping for Ovarian Cancer (IMO), to a lesser extent, have been universally validated in advanced-stage epithelial ovarian cancer (EOC) to describe the extent of peritoneal dissemination and are proven to be powerful predictors of the surgical outcome with an added sensitivity of assessment at laparotomy of around 70%. This leaves room for improvement because the two-dimensional anatomic scoring model fails to reflect the patient’s real anatomy, as seen by a surgeon. We hypothesized that tumor dissemination in specific anatomic locations can be more predictive of complete cytoreduction (CC0) and survival than PCI and IMO tools in EOC patients. (2) Methods: We analyzed prospectively data collected from 508 patients with FIGO-stage IIIB-IVB EOC who underwent cytoreductive surgery between January 2014 and December 2019 at a UK tertiary center. We adapted the structured ESGO ovarian cancer report to provide detailed information on the patterns of tumor dissemination (cancer anatomic fingerprints). We employed the extreme gradient boost (XGBoost) to model only the variables referring to the EOC disseminated patterns, to create an intra-operative score and judge the predictive power of the score alone for complete cytoreduction (CC0). Receiver operating characteristic (ROC) curves were then used for performance comparison between the new score and the existing PCI and IMO tools. We applied the Shapley additive explanations (SHAP) framework to support the feature selection of the narrated cancer fingerprints and provide global and local explainability. Survival analysis was performed using Kaplan–Meier curves and Cox regression. (3) Results: An intra-operative disease score was developed based on specific weights assigned to the cancer anatomic fingerprints. The scores range from 0 to 24. The XGBoost predicted CC0 resection (area under curve (AUC) = 0.88 CI = 0.854–0.913) with high accuracy. Organ-specific dissemination on the small bowel mesentery, large bowel serosa, and diaphragmatic peritoneum were the most crucial features globally. When added to the composite model, the novel score slightly enhanced its predictive value (AUC = 0.91, CI = 0.849–0.963). We identified a “turning point”, ≤5, that increased the probability of CC0. Using conventional logistic regression, the new score was superior to the PCI and IMO scores for the prediction of CC0 (AUC = 0.81 vs. 0.73 and 0.67, respectively). In multivariate Cox analysis, a 1-point increase in the new intra-operative score was associated with poorer progression-free (HR: 1.06; 95% CI: 1.03–1.09, p < 0.005) and overall survival (HR: 1.04; 95% CI: 1.01–1.07), by 4% and 6%, respectively. (4) Conclusions: The presence of cancer disseminated in specific anatomical sites, including small bowel mesentery, large bowel serosa, and diaphragmatic peritoneum, can be more predictive of CC0 and survival than the entire PCI and IMO scores. Early intra-operative assessment of these areas only may reveal whether CC0 is achievable. In contrast to the PCI and IMO scores, the novel score remains predictive of adverse survival outcomes.

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.

(1) Background: Surgical cytoreduction for epithelial ovarian cancer (EOC) is a complex procedure. Encompassed within the performance skills to achieve surgical precision, intra-operative surgical decision-making remains a core feature. The use of eXplainable Artificial Intelligence (XAI) could potentially interpret the influence of human factors on the surgical effort for the cytoreductive outcome in question; (2) Methods: The retrospective cohort study evaluated 560 consecutive EOC patients who underwent cytoreductive surgery between January 2014 and December 2019 in a single public institution. The eXtreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) algorithms were employed to develop the predictive model, including patient- and operation-specific features, and novel features reflecting human factors in surgical heuristics. The precision, recall, F1 score, and area under curve (AUC) were compared between both training algorithms. The SHapley Additive exPlanations (SHAP) framework was used to provide global and local explainability for the predictive model; (3) Results: A surgical complexity score (SCS) cut-off value of five was calculated using a Receiver Operator Characteristic (ROC) curve, above which the probability of incomplete cytoreduction was more likely (area under the curve [AUC] = 0.644; 95% confidence interval [CI] = 0.598–0.69; sensitivity and specificity 34.1%, 86.5%, respectively; p = 0.000). The XGBoost outperformed the DNN assessment for the prediction of the above threshold surgical effort outcome (AUC = 0.77; 95% [CI] 0.69–0.85; p < 0.05 vs. AUC 0.739; 95% [CI] 0.655–0.823; p < 0.95). We identified “turning points” that demonstrated a clear preference towards above the given cut-off level of surgical effort; in consultant surgeons with 4, and a Peritoneal Carcinomatosis Index >7, in a surgical environment with the optimization of infrastructural support. (4) Conclusions: Using XAI, we explain how intra-operative decisions may consider human factors during EOC cytoreduction alongside factual knowledge, to maximize the magnitude of the selected trade-off in effort. XAI techniques are critical for a better understanding of Artificial Intelligence frameworks, and to enhance their incorporation in medical applications.

Complete surgical cytoreduction (R0 resection) is the single most important prognosticator in epithelial ovarian cancer (EOC). Explainable Artificial Intelligence (XAI) could clarify the influence of static and real-time features in the R0 resection prediction. We aimed to develop an AI-based predictive model for the R0 resection outcome, apply a methodology to explain the prediction, and evaluate the interpretability by analysing feature interactions. The retrospective cohort finally assessed 571 consecutive advanced-stage EOC patients who underwent cytoreductive surgery. An eXtreme Gradient Boosting (XGBoost) algorithm was employed to develop the predictive model including mostly patient- and surgery-specific variables. The Shapley Additive explanations (SHAP) framework was used to provide global and local explainability for the predictive model. The XGBoost accurately predicted R0 resection (area under curve [AUC] = 0.866; 95% confidence interval [CI] = 0.8–0.93). We identified “turning points” that increased the probability of complete cytoreduction including Intraoperative Mapping of Ovarian Cancer Score and Peritoneal Carcinomatosis Index < 4 and 4, patient’s age < 60 years, and largest tumour bulk < 5 cm in a surgical environment of optimized infrastructural support. We demonstrated high model accuracy for the R0 resection prediction in EOC patients and provided novel global and local feature explainability that can be used for quality control and internal audit.

Achieving complete surgical cytoreduction in advanced stage high grade serous ovarian cancer (HGSOC) patients warrants an availability of Critical Care Unit (CCU) beds. Machine Learning (ML) could be helpful in monitoring CCU admissions to improve standards of care. We aimed to improve the accuracy of predicting CCU admission in HGSOC patients by ML algorithms and developed an ML-based predictive score. A cohort of 291 advanced stage HGSOC patients with fully curated data was selected. Several linear and non-linear distances, and quadratic discriminant ML methods, were employed to derive prediction information for CCU admission. When all the variables were included in the model, the prediction accuracies were higher for linear discriminant (0.90) and quadratic discriminant (0.93) methods compared with conventional logistic regression (0.84). Feature selection identified pre-treatment albumin, surgical complexity score, estimated blood loss, operative time, and bowel resection with stoma as the most significant prediction features. The real-time prediction accuracy of the Graphical User Interface CCU calculator reached 95%. Limited, potentially modifiable, mostly intra-operative factors contributing to CCU admission were identified and suggest areas for targeted interventions. The accurate quantification of CCU admission patterns is critical information when counseling patients about peri-operative risks related to their cytoreductive surgery.

Simple Summary Immunotherapy hinges on stimulating patients’ immune system to fight cancer. This treatment has led to improved survival in patients with malignancies such as melanoma and lung cancer but, disappointingly, its benefits have not been as forthcoming in ovarian cancer. This review summarises how the ovarian cancer tumour microenvironment hinders the efficacy of immunotherapy by modulating immunoregulatory pathways, reorchestrating metabolism and featuring specific cancer cell genomic aberrations. The impact of novel targeted drugs and combination therapies aiming to overcome these obstacles and improve the clinical success of immunotherapy in ovarian cancer are considered. Abstract A lack of explicit early clinical signs and effective screening measures mean that ovarian cancer (OC) often presents as advanced, incurable disease. While conventional treatment combines maximal cytoreductive surgery and platinum-based chemotherapy, patients frequently develop chemoresistance and disease recurrence. The clinical application of immune checkpoint blockade (ICB) aims to restore anti-cancer T-cell function in the tumour microenvironment (TME). Disappointingly, even though tumour infiltrating lymphocytes are associated with superior survival in OC, ICB has offered limited therapeutic benefits. Herein, we discuss specific TME features that prevent ICB from reaching its full potential, focussing in particular on the challenges created by immune, genomic and metabolic alterations. We explore both recent and current therapeutic strategies aiming to overcome these hurdles, including the synergistic effect of combination treatments with immune-based strategies and review the status quo of current clinical trials aiming to maximise the success of immunotherapy in OC.

Ovarian small-cell carcinoma of the hypercalcemic type is a rare and highly malignant tumor. In two thirds of the patients, the tumor is associated with asymptomatic paraneoplastic hypercalcemia. The diagnosis may be impeded; the tumor must be distinguished from other tumors with similar features.This tumor occurs predominantly in young women and is merely lethal. The 1-year survival is solely 50%, with an overall 5-year survival rate of approximately 10%. It is believed that the empirical treatment characterized by combination of radical surgery, chemotherapy, and radiotherapy results in the most favorable outcome in terms of survival. However, the outcome remains extremely poor despite this aggressive approach.Alternatively, these poor survival rates may justify a less aggressive fertility sparing approach without compromising the outcome. Such an approach is illustrated by a case report involving a patient with ovarian small-cell carcinoma of the hypercalcemic type, FIGO stage IIIC. A fertility-sparing approach was used, consisting of conservative surgery followed by induction chemotherapy, interval debulking surgery, and local radiotherapy. During follow-up of 60 months, there was no evidence of disease and the normal menstrual cycle resumed.In addition to this case report, histopathological features, different therapeutic modalities, and outcome of ovarian small-cell carcinoma of the hypercalcemic type is reviewed. This report suggests that a fertility-sparing approach may be just as feasible as the generally applied aggressive approach.

Objective To evaluate the supplementary value of adding hyperthermia to radiotherapy in patients with primary vaginal cancer. Study design Cohort of 44 patients diagnosed with primary vaginal cancer between 1990 and 2002 was assessed. Survival rates and median survival of patients with primary vaginal cancer undergoing radiotherapy with and without hyperthermia were compared. Hyperthermia was solely added to radiotherapy in case of a tumor size >4 cm in diameter for FIGO stage III disease. Results The calculated overall 5-year survival of primary vaginal cancer was 63%. In comparison to histologic high grade tumors, higher survival rates for histologic low grade tumors were calculated. For FIGO stage III of disease, the addition of hyperthermia to radiotherapy for tumors >4 cm in diameter resulted similar survival rates and median survival when compared to those achieved by radiotherapy as monotherapy in tumors of Conclusions The addition of hyperthermia to radiotherapy might result in better survival rates in primary vaginal cancer for tumors >4 cm in diameter. The supplementary effect of hyperthermia to radiotherapy may be a feasible and beneficial approach in the treatment of vaginal cancer.

Objective: To investigate relations between dose of GnRH antagonist and follicular phase characteristics. Design: Randomized controlled multicenter trial. Setting: Tertiary referral fertility centers. Patient(s): Three hundred and twenty-nine IVF patients. Intervention(s): Ovarian stimulation for IVF with recombinant FSH starting on cycle day 2. From cycle day 7 onwards, cotreatment was provided with 0.0625, 0.125, 0.25, 0.5, 1.0, or 2.0 mg/d GnRH antagonist. Main Outcome Measure(s): Number of follicles, total follicular surface area, gonadotropin, and serum steroid concentrations. Result(s): In 311 patients, similar follicular growth was observed in all treatment groups. FSH levels increased during the follicular phase. Late follicular phase LH, androstenedione (AD), and E 2 levels showed a GnRH antagonist dose-related decrease ( P 2 levels correlated with total follicular surface area, AD, LH, and FSH (all P 2 levels. Conclusion(s): Follicular growth was unaffected by the dose of GnRH antagonist. A rise in follicular phase FSH serum concentrations during the follicular phase, largely related to exogenous FSH, enabled ongoing follicular growth in all treatment groups. The effect of GnRH antagonist on late follicular phase E 2 levels could not be exclusively attributed to suppression of LH.

Objective: To assess the prevalence and etiology of the empty follicle syndrome (EFS). Design: Observational longitudinal study. Setting: Tertiary fertility centers. Patient(s): All patients beginning in vitro fertilization (IVF) treatment from December 2002 to November 2004 were included. Couples undergoing IVF with donor oocytes or participating in an experimental IVF study were excluded from analysis. Intervention(s): Identification of EFS cycles. Comparing ovarian hyperstimulation strategy, follicle count, and timing of human chorionic gonadotropin (hCG) for final oocyte maturation of the EFS cycles with normal IVF cycles. Main Outcome Measure(s): Number of follicles punctured, number of oocytes recovered, previous and future IVF attempts, and serum hormone levels. Result(s): Twenty-five of a total of 1,849 patients were identified with an EFS cycle. Reasons for occurrence of EFS cycles were mistiming of hCG for final oocyte maturation, premature ovulation, and poor ovarian response. None of the affected patients had experienced EFS cycles in earlier IVF attempts nor were there any recurrence in subsequent treatments. Conclusion(s): Accurate timing of induction of final oocyte maturation, properly scheduled ovarian hyperstimulation, instruction of patients and doctors, and full workup for IVF are essential for the successful recovery of oocytes. Occurrence of EFS in IVF can normally be attributed to a failure of at least one of these factors and probably rarely or never occurs otherwise.

In a randomized multicenter study, the efficacies of two different GnRH agonists were compared with that of hCG for triggering final stages of oocyte maturation after ovarian hyperstimulation for in vitro fertilization. Ovarian stimulation was conducted by recombinant FSH (Puregon), and the GnRH antagonist ganirelix (Orgalutran) was coadministered for the prevention of a premature LH rise. Luteal support was provided by daily progestin administration. Frequent blood sampling was performed at midcycle in the first 47 eligible subjects included in the current study, who were randomized for a single dose of 0.2 mg triptorelin (n 17), 0.5 mg leuprorelin (n 15), or 10,000 IU hCG (n 15). Serum concentrations of LH, FSH, E2, and progesterone (P) were assessed at variable intervals. LH peaked at 4 h after both triptorelin and leuprorelin administration, with median LH levels of 130 and 107 IU/liter (P < 0.001), respectively. LH levels returned to baseline after 24 h. Subjects receiving hCG showed peak levels of 240 IU/liter hCG 24 h after administration. A rise in FSH to 19 IU/liter (P < 0.001) was noted in both GnRH agonist groups 8 h after injection. Within 24 h the areas under the curve for LH and FSH were significantly higher (P < 0.001) in both GnRH agonist groups compared with that for hCG. E2 and P levels were similar for all groups up to the day of oocyte retrieval. Luteal phase areas under the curve for P and E2 were significantly elevated (P < 0.001) in the hCG group. The mean (SD) numbers of oocytes retrieved were 9.8 5.4, 8.7 4.5, and 8.3 3.3; the percentages of metaphase II oocytes were 72%, 85%, and 86%; and fertilization rates were 61%, 62%, and 56% in the triptorelin, leuprorelin, and hCG group, respectively (P NS for all three comparisons). These findings support the effective induction of final oocyte maturation in both GnRH agonist groups. In summary, after treatment with the GnRH antagonist ganirelix for the prevention of premature LH surges, triggering of final stages of oocyte maturation can be induced effectively by a single bolus injection of GnRH agonist, as demonstrated by the induced endogenous LH and FSH surge and the quality and fertilization rate of recovered oocytes. Moreover, corpus luteum formation is induced by GnRH agonists with luteal phase steroid levels closer to the physiological range compared with hCG. This more physiological approach for inducing oocyte maturation may represent a successful and safer alternative for in vitro fertilization patients undergoing ovarian hyperstimulation. (J Clin Endocrinol Metab 87: 709 –715, 2002)

Objective: To study whether minimal interference in the process of selection of the single dominant follicle may serve as the basis for a simplified ovarian stimulation regimen for IVF. Design: Single-center randomized pilot study. Setting: Tertiary referral fertility center. Patient(s): Fifteen normo-ovulatory patients with a regular indication for IVF. Intervention(s): Ovarian stimulation for IVF was begun with 100 or 150 IU/d recombinant FSH starting on cycle day 5. From cycle day 8 or later, cotreatment was begun with 0.25 mg/d GnRH antagonist. No luteal support was provided. Main Outcome Measure(s): Total number of dominant follicles and characteristics of the endocrine cycle. Result(s): Multiple follicle development occurred in five of eight patients in the 100-IU group and in all seven women in the 150-IU group. Follicular phase and luteal phase lengths were normal, but the endocrine profile was abnormal. Conclusion(s): A fixed daily dose of 150 IU recombinant FSH starting in the midfollicular phase resulted in ongoing growth of a restricted number of dominant follicles and sufficient oocytes retrieved to lead to ET. A marked reduction in the total amount of gonadotropins administered compared with standard treatment was achieved. Withholding luteal support did not exclude pregnancies.

The hypothalamic gonadotrophin-releasing hormone (GnRH) stimulates synthesis and secretion of luteinizing hormone (LH) and follicle stimulating hormone (FSH) by the gonadotrophic cells of the pituitary. The mechanisms of action of GnRH antagonists and of agonists is completely different. Due tot competitive blockage of GnRH receptors by antagonist administration, LH (and to a lesser extent FSH) levels drop rapidly. Moreover pituitary function normalizes immediately following cessation of medication. The direct and rapid action of GnRH antagonists, the dose dependent suppression of LH and FSH and the rapid restoration of hypophyseal function after cessation of the use of antagonists may shorten and simplify in-vitro fertilization, with less chance of side effects or complications. Further studies are required to decide whether antagonists can usefully be applied for other gynecological indications such as the polycystic ovary syndrome. The possibilities of profitable long term treatment will increase considerably if it proves possible to develop a sustained action formulation.

Objective : To study a possible role of plasma endothelin in angiotensin-induced vasoconstriction. Study design : Plasma endothelin levels were measured before and after an angiotensin sensitivity test at 32 gestational weeks in 19 nulliparous women. Results : No significant change in plasma endothelin occured as a result of angiotensin infusion. Conclusion : The angiotensin-induced rise in diastolic blood pressure is not associated with changes in plasma endothelin