Arjun Jeyarajah

Background/Objectives: Gynaecological–oncological surgery involves substantial perioperative morbidity and mortality risks. Reliable preoperative risk stratification could inform consent, shared decision-making and perioperative optimisation. Several prediction models exist, but their performance and methodological quality in this population remain uncertain. We aimed to provide a comprehensive synthesis of existing evidence to guide the selection and development of prediction tools in this population. Methods: We searched MEDLINE and EMBASE using a prospective protocol (PROSPERO CRD420251179495) and included studies developing or validating multivariable prediction models or risk scores for graded postoperative morbidity/mortality after gynaecological–oncological surgery. Risk of bias and applicability were assessed using the Prediction model Risk Of Bias Assessment Tool (PROBAST) at the study (publication) level. Findings were synthesised narratively. Results: Twenty-eight studies (75,999 patient records, including overlapping cohorts) were included (23 retrospective, five prospective; sample sizes 100–21,359). Models were multifactorial (n = 17), including generic and gynaecological–oncological-specific tools, frailty-based (n = 8) models or biomarker and index-based (n = 3) models. A numerical c-statistic was reported in 20 studies (binary c-statistics 0.50–0.92 across heterogeneous outcome definitions), calibration was reported in nine studies, and internal validation was reported in thirteen. No frailty-based model reported calibration or validation. One model specific to ovarian cytoreductive surgery was independently externally validated, retaining discrimination (c-index 0.715) with reduced calibration. Generic tools performed poorly, (c-statistics ranged from 0.529-0.644). Twenty studies were at high risk of bias, predominantly within the analysis domain. Conclusions: Existing models show, at best, moderate discrimination, limited calibration and infrequent external validation within the gynaecological–oncological surgical population. No model can currently be recommended for routine clinical practice. Further independent external validation of specialty-specific models in local settings, with full calibration reporting, is needed to support preoperative counselling.

Background/Objectives: Borderline ovarian tumours (BOTs) are distinct epithelial neoplasms with excellent survival but variable recurrence, including late relapse and occasional malignant transformation. Follow-up strategies remain inconsistent internationally, with no standardised, risk-adapted framework. We aimed to synthesise the evidence on BOT recurrence patterns, risk factors and surveillance strategies, and to propose a structured, risk-adapted surveillance framework. Methods: This is a narrative expert synthesis rather than a systematic review. Three evidence sources were combined: our previously published comprehensive review of BOTs, our recent meta-analysis of recurrence and malignant transformation, and an appraisal of contemporary international guidelines. Clinicopathological and surgical determinants of recurrence were then mapped onto the available follow-up tools through a three-step approach, and the resulting risk strata, surveillance intervals and total follow-up duration were agreed on by consensus within a single tertiary gynaecological oncology centre (the “Barts Framework”). Results: Recurrence occurs in 3–10% of patients, with up to one-third arising beyond five years. Key predictors include fertility-sparing surgery (particularly cystectomy), incomplete staging, advanced stage, residual disease, and adverse histological features such as micropapillary/cribriform architecture and invasive implants. Three targets for surveillance were identified: early detection of recurrence, detection of malignant transformation, and optimisation of fertility. Transvaginal ultrasound emerged as the cornerstone modality, with cross-sectional imaging and tumour markers applied selectively. Four risk strata were derived, each specifying follow-up intensity, modality, total duration and care setting. Low-risk patients can be managed in decentralised settings (gynaecological units), whereas high-risk groups warrant specialist oversight (gynaecological oncology centres). Patient-initiated follow-up is incorporated to minimise unnecessary interventions. Conclusions: This risk-adapted approach provides a scalable framework to standardise BOT surveillance whilst reducing overuse and maintaining oncological safety. The framework is consensus-based and single-institution in origin, and prospective external validation with long-term outcome data is required before wider adoption. Integration of molecular stratification and artificial-intelligence-assisted imaging represents a key future direction.

Background/Objectives: We evaluated perioperative morbidity, recurrence patterns and survival outcomes following pelvic exenteration (PE) at a tertiary referral centre. Methods: A retrospective observational study was conducted in women undergoing PE from 2004 to 2024. We collected demographics, performance status (PS), comorbidities, body mass index (BMI), tumour histology, intraoperative details, postoperative morbidity (Clavien–Dindo classification), mortality, length of stay (LOS), recurrence patterns and cancer-related death. Descriptive statistics were performed alongside Kaplan–Meier survival analysis. Results: Forty-seven patients underwent PE; median PS was 0 [interquartile range (IQR) 0–0]. Median ages at diagnosis and surgery were 55 (IQR 49–66) and 60 (IQR 50–68) years, respectively, with a median follow-up of 26 months (IQR 12–64). Thirty-two procedures (68%) were performed for recurrent and N = 15 (32%) for primary disease. Histology included N = 17 endometrial (36%), N = 10 vulval (23%), ovarian (15%), N = 5 cervical (11%) and N = 7 vaginal (15%) cases. Eighteen patients (38%) underwent total PE, N = 15 (32%) anterior PE and N = 14 (30%) posterior PE. Median blood loss was 1.5 L (IQR 0.85–2.0) and median operative time was 391 mis (IQR 313–482). Median HDU stay was 4 days (IQR 2–5) and LOS was 17 days (IQR 13–31). One postoperative death occurred. Major complications (Clavien–Dindo ≥3) occurred in 15 patients (32%). Late complications occurred in n = 17 (36.2%) women. Nineteen patients (41%) remained recurrence-free; N = 4 (9%) developed local and N = 24 (51%) distant recurrence. Mean overall survival time post-surgery for curative intent PE (N = 46) was 94 months (95%CI = 57–131 months); for primary tumours this was 51.6 (95%CI = 31–72) vs. 99 (56.01–142) for recurrent disease (p > 0.05). Conclusions: Pelvic exenteration is associated with acceptable morbidity and mortality in carefully selected patients, offering excellent locoregional disease control.

Objective: The P-POSSUM scale is widely used in predicting perioperative morbidity and mortality. Evidence on the performance of P-POSSUM in predicting outcomes after cytoreductive surgery (CRS) for ovarian cancer (OC) is limited. In this study, we assess how well P-POSSUM predicts morbidity in OC CRS and explore whether incorporating additional clinical variables can enhance its predictive accuracy. We retrospectively collected data on consecutive patients undergoing OC CRS within a tertiary gynaecologic oncology network. The collected information included demographic characteristics, P-POSSUM morbidity and mortality scores, Edmonton Frail Scale (EFS) scores, preoperative serum albumin levels, and observed 30-day postoperative morbidity and mortality, classified using the Clavien–Dindo (CD) scale. The predictive performance of P-POSSUM was evaluated using receiver operating characteristic (ROC) curves to calculate sensitivity and specificity. A stepwise regression analysis was then applied to identify additional variables that could improve model performance, incorporating preoperative covariates. The final model incorporated parameters chosen through bootstrap investigation of the model variability (stepAIC). Predicted versus observed morbidity was calibrated and performance compared between P-POSSUM and the final model. Results: Of 161 sequential OC patients, 95 (59%) underwent primary, 45 (28%) interval, and 21 (13%) delayed CRS. The mean age was 66.4 (95%CI: 60–75) and duration of surgery was 223 mins (95%CI: 142–279). Sixty-five (40.3%) patients had ≥1 postoperative complication. Two deaths were reported. Among the observed complications, 4 patients (6.1%) experienced CD4, 10 patients (15.3%) CD3, 38 patients (58.5%) CD2, and 11 patients (16.9%) CD1 events. The mean P-POSSUM-predicted morbidity and mortality were 59.5% (95%CI: 56.7–62.3%) and 5.86% (95%CI: 5.02–6.70%), respectively. The area under the curve (AUC) for P-POSSUM in predicting morbidity and mortality was 0.539 (p = 0.401) and 0.569 (p = 0.137), respectively. Given the small number of deaths, no robust conclusions regarding mortality are possible. EFS and BMI emerged as significant predictors of observed morbidity using a stepwise-model selection process. The AIC of this final model was 211.44. Our final model of PPOSSUM + EFS + BMI had AUC = 0.6551 (Delong’s Z = 1.8845, p-value = 0.05949). Conclusions: The P-POSSUM scale shows poor performance for predicting morbidity in OC CRS. New validated and accurate model(s) are necessary for predicting surgical morbidity. Our proposed model incorporates additional variables to improve P-POSSUM’s performance. This requires further development and validation.

For women achieving clinical remission after the completion of initial treatment for epithelial ovarian cancer, 80% with advanced-stage disease will develop recurrence. However, the standard treatment of women with recurrent platinum-sensitive diseases remains poorly defined. Secondary (SCS), tertiary (TCS) or quaternary (QCS) cytoreduction surgery for recurrence has been suggested to be associated with increased overall survival (OS). We searched five databases for studies reporting death rate, OS, cytoreduction rates, post-operative morbidity/mortality and diagnostic models predicting complete cytoreduction in a platinum-sensitive disease recurrence setting. Death rates calculated from raw data were pooled based on a random-effects model. Meta-regression/linear regression was performed to explore the role of complete or optimal cytoreduction as a moderator. Pooled death rates were 45%, 51%, 66% for SCS, TCS and QCS, respectively. Median OS for optimal cytoreduction ranged from 16–91, 24–99 and 39–135 months for SCS, TCS and QCS, respectively. Every 10% increase in complete cytoreduction rates at SCS corresponds to a 7% increase in median OS. Complete cytoreduction rates ranged from 9–100%, 35–90% and 33–100% for SCS, TCS and QCS, respectively. Major post-operative thirty-day morbidity was reported to range from 0–47%, 13–33% and 15–29% for SCS, TCS and QCS, respectively. Thirty-day post-operative mortality was 0–6%, 0–3% and 0–2% for SCS, TCS and QCS, respectively. There were two externally validated diagnostic models predicting complete cytoreduction at SCS, but none for TCS and QCS. In conclusion, our data confirm that maximal effort higher order cytoreductive surgery resulting in complete cytoreduction can improve survival.

We present findings of a cancer multidisciplinary-team (MDT) coordinated mainstreaming pathway of unselected 5-panel germline BRCA1/BRCA2/RAD51C/RAD51D/BRIP1 and parallel somatic BRCA1/BRCA2 testing in all women with epithelial-OC and highlight the discordance between germline and somatic testing strategies across two cancer centres. Patients were counselled and consented by a cancer MDT member. The uptake of parallel multi-gene germline and somatic testing was 97.7%. Counselling by clinical-nurse-specialist more frequently needed >1 consultation (53.6% (30/56)) compared to a medical (15.0% (21/137)) or surgical oncologist (15.3% (17/110)) (p < 0.001). The median age was 54 (IQR = 51–62) years in germline pathogenic-variant (PV) versus 61 (IQR = 51–71) in BRCA wild-type (p = 0.001). There was no significant difference in distribution of PVs by ethnicity, stage, surgery timing or resection status. A total of 15.5% germline and 7.8% somatic BRCA1/BRCA2 PVs were identified. A total of 2.3% patients had RAD51C/RAD51D/BRIP1 PVs. A total of 11% germline PVs were large-genomic-rearrangements and missed by somatic testing. A total of 20% germline PVs are missed by somatic first BRCA-testing approach and 55.6% germline PVs missed by family history ascertainment. The somatic testing failure rate is higher (23%) for patients undergoing diagnostic biopsies. Our findings favour a prospective parallel somatic and germline panel testing approach as a clinically efficient strategy to maximise variant identification. UK Genomics test-directory criteria should be expanded to include a panel of OC genes.