Multiparametric MRI radiomics for predicting disease-free survival and high-risk histopathological features for tumor recurrence in endometrial cancer.

Background: Current preoperative imaging is insufficient to predict survival and tumor recurrence in endometrial cancer (EC), necessitating invasive procedures for risk stratification. Purpose: To establish a multiparametric MRI radiomics model for predicting disease-free survival (DFS) and high-risk histopathologic features in EC. Methods: This retrospective study included 71 patients with histopathology-proven EC and preoperative MRI over a 10-year period. Clinicopathology data were extracted from health records. Manual MRI segmentation was performed on T2-weighted (T2W), apparent diffusion coefficient (ADC) maps and dynamic contrast-enhanced T1-weighted images (DCE T1WI). Radiomic feature (RF) extraction was performed with PyRadiomics. Associations between RF and histopathologic features were assessed using logistic regression. Associations between DFS and RF or clinicopathologic features were assessed using the Cox proportional hazards model. All RF with univariate analysis p-value < 0.2 were included in elastic net analysis to build radiomic signatures. Results: The 3-year DFS rate was 68% (95% CI = 57%-80%). There were no significant clinicopathologic predictors for DFS, whilst the radiomics signature was a strong predictor of DFS (p<0.001, HR 3.62, 95% CI 1.94, 6.75). From 107 RF extracted, significant predictive elastic net radiomic signatures were established for deep myometrial invasion (p=0.0097, OR 4.81, 95% CI 1.46, 15.79), hysterectomy grade (p=0.002, OR 5.12, 95% CI 1.82, 14.45), hysterectomy histology (p=0.0061, OR 18.25, 95% CI 2.29,145.24) and lymphovascular space invasion (p<0.001, OR 5.45, 95% CI 2.07, 14.36). Conclusion: Multiparametric MRI radiomics has the potential to create a non-invasive a priori approach to predicting DFS and high-risk histopathologic features in EC.

Management of inguinal lymph nodes in locally advanced, surgically unresectable, squamous cell carcinoma of the vulva.

OBJECTIVE: To assess clinical outcomes of inguinal lymph node surgical resection compared to primary groin radiotherapy for locally advanced, surgically unresectable vulvar cancer. METHODS: All patients treated with radiation for vulvar cancer were identified between Jan 1, 2000 - Dec 31, 2020 at 2 academic centres. Inclusion criteria were those treated with curative intent primary radiotherapy +/- chemotherapy, tumors >4 cm, and surgically unresectable squamous cell vulvar carcinoma. Groin recurrence-free survival (RFS) was compared for groin surgery and primary groin radiotherapy using the Kaplan Meier method and log rank test. Groin failures are described by treatment modality, radiation dose and lymph node size. RESULTS: Of 476 patients treated with radiation for vulvar cancer, 112 patients (23.5%) met inclusion and exclusion criteria. The median (95% CI) follow up was 1.9 (1.4-2.5) years. Complete clinical response was significantly higher (80.0%) in patients with surgical groin resection compared to patients treated with primary groin radiotherapy (58.2%) (p = 0.04). On multivariable analysis, after adjusting for clinical and/or radiologically abnormal lymph nodes (p = 0.67), surgical groin resection was significantly associated with lower groin recurrence (HR 0.2 (95%CI 0.05-0.92), p = 0.04). The 3-year groin recurrence-free survival (RFS) was significantly higher at 94.4% (87.1-100) in patients with surgical groin resection compared to 79.2% (69.1-90.9) in patients treated with primary radiation (p = 0.02). CONCLUSIONS: In locally advanced squamous cell vulvar cancer, surgical groin management improves groin RFS compared to radiotherapy alone.

Sustainability of an enhanced recovery pathway after minimally invasive gynecologic oncology surgery.

OBJECTIVE: Same day discharge is safe after minimally invasive gynecology oncology surgery. Our quality improvement peri-operative program based on enhanced recovery after surgery principles led to an increase in same day discharge from 30% to 75% over a 12 month period. Twelve months after program implementation, we assessed the sustainability of same day discharge rates, determined post-operative complication rates, and evaluated factors affecting same day discharge rates. METHODS: A retrospective chart review was conducted of 100 consecutive patients who underwent minimally invasive surgery at an academic cancer center from January to 2021 to December 2021. This cohort was compared with the active intervention cohort (n=102) from the implementation period (January 2020 to December 2020). Same day discharge rates and complications were compared. Multivariable analysis was performed to assess which factors remained associated with same day discharge post-intervention. RESULTS: Same day discharge post-intervention was 72% compared with 75% during active intervention (p=0.69). Both cohorts were similar in age (p=0.24) and body mass index (p=0.27), but the post-intervention cohort had longer operative times (p=0.001). There were no significant differences in 30-day complications, readmission, reoperation, or emergency room visits (p>0.05). There was a decrease in 30-day post-operative clinic visits from 18% to 5% in the post-intervention cohort (p=0.007), and unnecessary bowel prep use decreased from 35% to 14% (p<0.001). On multivariable analysis, start time (second case of the day) (OR 0.06; 95% CI 0.01 to 0.35), and ward narcotic use (OR 0.12; 95% CI 0.03 to 0.42) remained associated with overnight admission. CONCLUSION: Same day discharge rate was sustained at 72%, 12 months after the implementation of a quality improvement program to optimize same day discharge rate after minimally invasive surgery, while maintaining low post-operative complications and reducing unplanned clinic visits. To maximize same day discharge, minimally invasive gynecologic oncology surgery should be prioritized as the first case of the day, and post-operative narcotic use should be limited.

Gestational trophoblastic neoplasia: does centralization of care impact clinical management?

OBJECTIVE: International societies advocate for gestational trophoblastic neoplasia referral to designated expert centers. This study assessed the impact of centralization of trophoblastic care on clinical outcomes. METHODS: A centralized program was implemented in 2018 at two affiliated academic hospitals, Princess Margaret Cancer Center and Mount Sinai Hospital. A retrospective analysis of patients treated between 2000 and 2022 was performed and the clinical outcomes were compared before (2000-2017) and after (2018-2022) centralization. Statistical analyses were performed with significance set as p<0.05. RESULTS: A total of 94 patients with trophoblastic neoplasia were included: 60 pre-centralization and 34 post-centralization, 79.8% low-risk and 18.1% high-risk. Centralization led to significant improvement for: (1) accurate score documentation (from 37.9% to 89.3%,); (2) contraception counseling (from 67.2% to 96.7%); (3) median time from diagnosis to chemotherapy (from 9 days to 1 day); and (4) incomplete follow-up (from 20.7% to 3.3%) (all p<0.05). First-line chemotherapy for low-risk neoplasia was dactinomycin in 47.9% and 87.0% pre- and post-centralization, respectively (p=0.005). The median number of chemotherapy cycles decreased from seven to four (p=0.01), and the median number of consolidation cycles increased from two to three (p<0.001). Serum human chorionic gonadotropin (hCG) levels of 10 000-100 000 IU/L were significantly associated with longer time to hCG normalization and higher risk of resistance to first-line chemotherapy compared with hCG levels <1000 IU/L. CONCLUSION: Centralization of trophoblastic neoplasia care leads to greater guideline compliance, faster chemotherapy initiation, fewer chemotherapy cycles with optimized consolidation, and enhanced surveillance completion. This supports the establishment of trophoblastic neoplasia expert centers.

Cost impact analysis of enhanced recovery after minimally invasive gynecologic oncology surgery.

OBJECTIVE: The implementation of a peri-operative care program based on enhanced recovery after surgery principles for minimally invasive gynecologic oncology surgery led to an improvement in same day discharge from 29% to 75% at our center. This study aimed to determine the program's economic impact. METHODS: Our initial enhanced recovery quality improvement program enrolled consecutive patients undergoing minimally invasive hysterectomy at a single center during a 12-month period and compared them to a pre-intervention cohort. The primary outcome was overall costs. The secondary outcomes were surgical and post-operative visit costs. The surgical visit costs included pre-operative and operating room, post-operative stay, pharmacy, and interventions costs. The 30-day post-operative visit costs included clinic and emergency room, and readmission costs. The costs for every visit were collected from the case-cost department and expressed in 2020 Canadian dollars (CAD). RESULTS: A total of 96 and 101 patients were included in the pre- and post-intervention groups, respectively. The median total cost per patient for post-intervention was $7252 compared with $8381 pre-intervention (p=0.02), resulting in a $1129 cost reduction per patient. The total cost for the program implementation was $134 per patient for a total cost of $13 106. The median post-operative stay cost was $816 post-intervention compared with $1278 pre-intervention (p<0.05). Statistically significant savings for the post-intervention group were also found for operative visit, operating room costs, and pharmacy (p<0.05). On multivariate analysis, surgical approach was the only factor associated with operating room costs, whereas both surgical approach and group (pre- vs post-intervention) impacted the total and post-operative stay costs (p<0.05). CONCLUSION: In addition to increasing the same day discharge rate after minimally invasive gynecologic oncology surgery, an enhanced recovery-based peri-operative care program led to significant reductions in cost.

Validation of the Integrated Prediction Model algorithm for outcome of cytoreduction in advanced ovarian cancer.

BACKGROUND: We previously developed the Integrated Prediction Model using a 4-step algorithm of unresectable stage IVB, patient factors, surgical resectability, and surgical complexity to predict outcome of <1 cm cytoreduction in advanced epithelial ovarian cancer, and triaged patients to neoadjuvant chemotherapy or primary cytoreductive surgery. OBJECTIVE: To validate the Integrated Prediction Model on a retrospective cohort of patients. METHODS: A retrospective cohort study of 107 patients with advanced ovarian cancer treated between January 2017 and September 2018 was carried out. The above mentioned 4-step algorithm determined cut-off points using the Youden Index. This validation study reports sensitivity, specificity, negative and positive predictive value on an external cohort. RESULTS: Among 107 patients, 61 had primary surgery and 46 had neoadjuvant chemotherapy. Compared with primary surgery, patients treated with neoadjuvant chemotherapy were significantly older (63.5 vs 61, p=0.037), more likely to have stage IV disease (52% vs 18%, p<0.001), Eastern Cooperative Oncology Group (ECOG) score >1 (30% vs 11%, 0.045), lower pre-operative albumin (37 vs 40, p<0.001), and higher CA-125 (970 vs 227.5, p<0.001). They also had higher patient factors (2 vs 0, p=0.013), surgical resectability (4 vs 1, p<0.001), and anticipated surgical complexity (8 vs 5, p<0.001). There was no significant difference in outcome of cytoreduction (<1 cm residual disease: 85% for primary surgery vs 87% interval surgery, p=0.12)In this validation cohort, triaging patients with patient factors ≤2, surgical resectability score ≤5, and surgical complexity score ≤9 to primary surgery had a sensitivity of 91% for optimal cytoreduction <1 cm and a specificity of 81%. The positive predictive value, negative predictive value, and accuracy were 83%, 90%, and 86%, respectively. Application of the Integrated Prediction Model would have prevented five patients from receiving suboptimal cytoreduction and triaged them to neoadjuvant chemotherapy. CONCLUSIONS: We validated the proposal that a triage algorithm integrating patient factors, surgical complexity, and surgical resectability in advanced ovarian cancer had high sensitivity and specificity to predict optimal cytoreduction <1 cm.

Using a machine learning algorithm to predict outcome of primary cytoreductive surgery in advanced ovarian cancer.

OBJECTIVE: To develop a machine learning (ML) algorithm to predict outcome of primary cytoreductive surgery (PCS) in patients with advanced ovarian cancer (AOC) METHODS: This retrospective cohort study included patients with AOC undergoing PCS between January 2017 and February 2021. Using radiologic criteria, patient factors (age, CA-125, performance status, BRCA) and surgical complexity scores, we trained a random forest model to predict the dichotomous outcome of optimal cytoreduction (<1 cm) and no gross residual (RD = 0 mm) using JMP-Pro 15 (SAS). This model is available at https://ipm-ml.ccm.sickkids.ca. RESULTS: One hundred and fifty-one patients underwent PCS and randomly assigned to train (n = 92), validate (n = 30), or test (n = 29) the model. The median age was 58 (27-83). Patients with suboptimal cytoreduction were more likely to have an Eastern Cooperative Oncology Group 3-4 (11% vs. 0.75%, p = 0.004), lower albumin (38 vs. 41, p = 0.02), and higher CA125 (1126 vs. 388, p = 0.012) than patients with optimal cytoreduction (n = 133). There were no significant differences in age, histology, stage, or BRCA status between groups. The bootstrap random forest model had AUCs of 99.8% (training), 89.6%(validation), and 89.0% (test). The top five contributors were CA125, albumin, diaphragmatic disease, age, and ascites. For RD = 0 mm, the AUCs were 94.4%, 52%, and 84%, respectively. CONCLUSION: Our ML algorithm demonstrated high accuracy in predicting optimal cytoreduction in patients with AOC selected for PCS and may assist decision-making.