Advanced ovarian cancer and cytoreductive surgery: Independent validation of a risk-calculator for perioperative adverse events

Predictive value of the Adult Comorbidity Evaluation 27 on adverse surgical outcomes and survival in elderly with advanced epithelial ovarian cancer undergoing cytoreductive surgery

OBJECTIVE

We aimed to evaluate the ability of Adult Comorbidity Evaluation 27 (ACE-27) to predict perioperative outcomes and survival in elderly women with advanced epithelial ovarian cancer (AEOC) undergoing cytoreductive surgery.

METHODS

We collected patients with AEOC in our hospital between January 1, 2012 and January 1, 2021. Patients younger than 65 years old or those with non-epithelial ovarian cancer were excluded. ACE-27 was applied retrospectively to assess comorbidities in the selected patients, who were then classified into two groups based on their ACE-27 scores: low ACE-27 score group (none to mild) and high ACE-27 score group (moderate to severe).

RESULTS

A total of 222 elderly women with AEOC were included, of whom 164 patients accepted debulking surgery. Among those who have undergone surgery, Clavien-Dindo grade III + perioperative complications or unintended intensive care unit (ICU) admission occurred more often in patients of high ACE-27 score group, with statistically significant difference (odds ratio [OR]: 4.21, 95% confidence interval [CI], 1.28-14.35, p = 0.018). Further stratified analyses by age, BMI, FIGO stage and pathology also prove that OS of patients graded severe was shorter than patients graded none to moderate in cohort of age < 70, BMI < 25 kg/m2, FIGO III stage and pathology of serous, respectively. Kaplan-Meier survival curves analyzed by log-rank test showed that the overall survival (OS) of patients with severe comorbidities were shorter than with none to moderate (HR 3.25, 95%CI 1.55-6.79, p = 0.002).

CONCLUSIONS

Our findings demonstrate the ability of ACE-27 to predict grade III + perioperative complications or unintended ICU admission and survival in elderly patients with AEOC. This highlights the possibility for ACE-27 to play an instrumental role in identifying AEOC patients who are more susceptible to adverse surgical outcomes and have a poor survival rate and assisting in decisions regarding treatment.

Impact of postoperative morbidity on outcomes in patients with advanced epithelial ovarian cancer undergoing intestinal surgery at the time of primary or interval cytoreductive surgery: A Memorial Sloan Kettering Cancer Center Team Ovary study

OBJECTIVE

To assess the impact of short-term postoperative complications on oncologic outcomes for patients with epithelial ovarian cancer undergoing primary cytoreductive surgery (PCS) or interval cytoreductive surgery (ICS) with intestinal resection.

METHODS

A retrospective chart review was performed for patients with ovarian cancer who underwent PCS or ICS with at least one intestinal resection at our institution from 1/1/2015 to 12/31/2020. Progression-free survival (PFS) and overall survival (OS) were analyzed for the PCS and ICS cohorts separately. Short-term complications within 30 days of surgery (surgical secondary events [SSEs]) were graded by a validated institutional SSE system.

RESULTS

Among 437 patients who underwent intestinal resections during PCS (n = 289) or ICS (n = 148), 183 (42%) had one, 180 (41%) had two, and 74 (17%) had three intestinal resections. Six (1.4%) of 437 patients experienced an anastomotic leak postoperatively. There were no perioperative deaths. There was no difference in PFS and OS for patients who underwent PCS with any SSE vs. no SSE within 30 days of surgery (HR, 1.05; 95% CI: 0.76-1.47; p = 0.75 and HR, 0.79; 95% CI: 0.49-1.26; p = 0.32, respectively). There was no difference in PFS and OS for patients who underwent ICS with any SSE vs. no SSE within 30 days of surgery (HR, 1.43; 95% CI: 0.99-2.07; p = 0.055 and HR. 1.18; 95% CI: 0.72-1.93; p = 0.52, respectively.

CONCLUSION

Short-term postoperative morbidity for patients who underwent intestinal surgery during primary surgical management for advanced ovarian cancer did not impact oncologic outcomes.

Predicting Neoadjuvant Chemotherapy Response and High-Grade Serous Ovarian Cancer From CT Images in Ovarian Cancer with Multitask Deep Learning: A Multicenter Study

RATIONALE AND OBJECTIVES

Accurate prediction neoadjuvant chemotherapy (NACT) response in ovarian cancer (OC) is essential for personalized medicine. We aimed to develop and validate a deep learning (DL) model based on pretreatment contrast-enhanced CT (CECT) images for predicting NACT responses and classifying high-grade serous ovarian cancer (HGSOC) to identify patients who may benefit from NACT.

MATERIALS AND METHODS

This multicenter study, which contained both retrospective and prospective studies, included consecutive OC patients (n = 757) from three hospitals. Using WHO RECIST 1.1 for the reference standard, a total of 587 women with 1761 images were included in the training and validation sets, 67 women with 201 images were included in the prospective sets, and 103 women with 309 images were included in the external sets. A multitask DL model based on the multiperiod CT image was developed to predict NACT response and HGSOC.

RESULTS

Logistic regression analysis showed that peritoneal invasion, retinal invasion, and inguinal lymph node metastasis were independent predictors. The DL achieved promising segmentation performances with DICEmean= 0.83 (range: 0.78-0.87). For predicting NACT response, the DL model combined with clinical risk factors obtained area under the receiver operating characteristic curve (AUCs) of 0.87 (0.83-0.89), 0.88 (0.86-0.91), 0.86 (0.82-0.89), and 0.79 (0.75-0.82) in the training, validation, prospective, and external sets, respectively. The AUCs were 0.91 (0.87-0.94), 0.89 (0.86-0.91), 0.80 (0.76-0.84), and 0.80 (0.75-0.85) in four sets in HGSOC classification.

CONCLUSION

The multitask DL model developed using multiperiod CT images exhibited a promising performance for predicting NACT response and HGSOC with OC, which could provide valuable information for individualized treatment.

The KORE-INNOVATION trial, a prospective controlled multi-site clinical study to implement and assess the effects of an innovative peri-operative care pathway for patients with ovarian cancer: rationale, methods and trial design

BACKGROUND

Advanced ovarian cancer is managed by extensive surgery, which could be associated with high morbidity. A personalized pre-habilitation strategy combined with an 'enhanced recovery after surgery' (ERAS) pathway may decrease post-operative morbidity.

PRIMARY OBJECTIVE

To analyze the effects of a combined multi-modal pre-habilitation and ERAS strategy on severe post-operative morbidity for patients with ovarian cancer (primary diagnosis or first recurrence) undergoing cytoreductive surgery.

STUDY HYPOTHESIS

A personalized multi-modal pre-habilitation algorithm entailing a physical fitness intervention, nutritional and psycho-oncological support, completed by an ERAS pathway, reduces post-operative morbidity.

TRIAL DESIGN

This is a prospective, controlled, non-randomized, open, interventional two-center clinical study. Endpoints will be compared with a three-fold control: (a) historic control group (data from institutional ovarian cancer databases); (b) prospective control group (assessed before implementing the intervention); and (c) matched health insurance controls.

INCLUSION CRITERIA

Patients with ovarian, fallopian, or primary peritoneal cancer undergoing primary surgical treatment (primary ovarian cancer or first recurrence) can be included. The intervention group receives an additional multi-level study treatment: (1) standardized frailty assessment followed by (2) a personalized tri-modal pre-habilitation program and (3) peri-operative care according to an ERAS pathway.

EXCLUSION CRITERIA

Inoperable disease or neoadjuvant chemotherapy, simultaneous diagnosis of simultaneous primary tumors, in case of interference with the overall prognosis (except for breast cancer); dementia or other conditions that impair compliance or prognosis.

PRIMARY ENDPOINT

Reduction of severe post-operative complications (according to Clavien- Dindo Classification (CDC) III-V) within 30 days after surgery.

SAMPLE SIZE

Intervention group (n=414, of which approximately 20% insure with the participating health insurance); historic control group (n=198); prospective control group (n=50), health insurance controls (for those intervention patients who are members of the participating health insurance).

ESTIMATED DATES FOR COMPLETING ACCRUAL AND PRESENTING RESULTS

The intervention phase started in December 2021 and will continue until June 2023. As of March 2023, 280 patients have been enrolled in the intervention group. The expected completion of the entire study is September 2024.

TRIAL REGISTRATION

NCT05256576.

Validation of a risk-based algorithm to reduce poor operative outcomes after complex surgery for ovarian cancer

OBJECTIVE

We developed an algorithm that identifies patients at high risk of morbidity/mortality after cytoreductive surgery for advanced ovarian cancer. We have previously shown that the Mayo triage algorithm reduces operative mortality internally, followed by validation using an external low complexity national dataset. However, validation in a higher complexity surgical setting is required before widespread acceptance of this approach, and this was the goal of our study.

METHODS

We included patients who underwent debulking surgery (including primary or interval debulking surgery) for stage IIIC/IV ovarian cancer between October 2011 and November 2019 (SCORPION trial patients until May 2016 and non-trial patients thereafter) at Fondazione Policlinico A Gemelli, Italy. Using the algorithm, we classified patients as either high-risk or triage-appropriate and compared 30-day grade 3+ complications and 90-day mortality using a χ2 test or Fisher's exact test.

RESULTS

A total of 625 patients were included. The mean age was 58.7±11.4 years, 73.6% (n=460) were stage IIIC, and 63.0% (n=394) underwent primary debulking surgery. Surgical complexity was intermediate or high in 82.6% (n=516) of patients (95.7% (n=377) for primary surgery and 60.2% (n=139) for interval surgery), and 20.3% (n=127) were classified as high-risk. When compared with triage-appropriate patients, high-risk patients had (1) a threefold higher rate of 90-day mortality (6.3% vs 2.0%, p=0.02); (2) a higher likelihood of 90-day mortality following a grade 3+ complication (25.9% vs 10.0%, p=0.05); and (3) comparable rates of grade 3+ complications (21.3% vs 16.1%, p=0.17).

CONCLUSION

The evidence-based triage algorithm identifies patients at high risk of morbidity/mortality after cytoreductive surgery. Triage high-risk patients are poor candidates for surgery when complex surgery is required. This algorithm has been validated in heterogeneous settings (internal, national, and international) and degree of surgical complexity. Risk-based decision making should be standard of care when planning surgery for patients with advanced ovarian cancer, whether primary or interval surgery.

Integrated prediction model of patient factors, resectability scores and surgical complexity to predict cytoreductive outcome and guide treatment plan in advanced ovarian cancer

OBJECTIVE

To report performance of an integrated predictive model (IPM) algorithm based on patient factors, surgical resectability and surgical complexity to predict outcome of primary cytoreductive surgery (PCS) and guide treatment plan in patients with advanced epithelial ovarian cancer (AEOC).

METHODS

Patients with AEOC between October 2018 and October 2020 were enrolled into a dedicated AEOC program and decision for PCS or neoadjuvant chemotherapy (NACT) was based on multidisciplinary consensus. Data of unresectable stage IVb, patient factors (PF), surgical resectability scores (SRS) and surgical complexity scores (SCS) was prospectively documented. An integrated prediction model (IPM) was developed to predict outcome of optimal (RD < 1 cm) cytoreduction. Retrospective analysis was performed to assess the performance of the IPM. Cut-offs were selected using the Youden Index.

RESULTS

Of 185 eligible patients, 81 underwent PCS and 104 were treated with NACT. Patients undergoing PCS had significantly lower median PF (0 vs 2, p < 0.01), SRS (2 vs 4, p < 0.01) and pre-operative SCS (6 vs 8.5, p = 0.01) compared to NACT. In patients undergoing PCS, 88% had optimal cytoreduction and 34.5% had grade 3-4 post-operative complications. A model triaging patients with unresectable Stage IVb, PF > 2, SRS > 5 and SCS > 9 to NACT had 85% sensitivity, 75% specificity and 85% accuracy for outcome of optimal cytoreduction. Our model would have improved triage of 3/10 sub-optimally cytoreduced patients to NACT. For outcome of no-gross residual disease (RD = 0 mm) using the same cut-offs sensitivity and specificity were 85% and 76% respectively.

CONCLUSION

The 4-step IPM algorithm had high sensitivity and specificity for optimal cytoreduction with acceptable morbidity without delay to adjuvant therapy. This algorithm may be used to triage patients to PCS or NACT once it is further validated.

Applying low coverage whole genome sequencing to detect malignant ovarian mass

To evaluate whether low coverage whole genome sequencing is suitable for the detection of malignant pelvic mass and compare its diagnostic value with traditional tumor markers. We enrolled 63 patients with a pelvic mass suspicious for ovarian malignancy. Each patient underwent low coverage whole genome sequencing (LCWGS) and traditional tumor markers test. The pelvic masses were finally confirmed via pathological examination. The copy number variants (CNVs) of whole genome were detected and the Stouffers Z-scores for each CNV was extracted. The risk of malignancy (RM) of each suspicious sample was calculated based on the CNV counts and Z-scores, which was subsequently compared with ovarian cancer markers CA125 and HE4, and the risk of ovarian malignancy algorithm (ROMA). Receiver Operating Characteristic Curve (ROC) were used to access the diagnostic value of variables. As confirmed by pathological diagnosis, 44 (70%) patients with malignancy and 19 patients with benign mass were identified. Our results showed that CA125 and HE4, the CNV, the mean of Z-scores (Zmean), the max of Z-scores (Zmax), the RM and the ROMA were significantly different between patients with malignant and benign masses. The area under curve (AUC) of CA125, HE4, CNV, Zmax, and Zmean was 0.775, 0.866, 0.786, 0.685 and 0.725 respectively. ROMA and RM showed similar AUC (0.876 and 0.837), but differed in sensitivity and specificity. In the validation cohort, the AUC of RM was higher than traditional serum markers. In conclusion, we develop a LCWGS based method for the identification of pelvic mass of suspicious ovarian cancer. LCWGS shows accurate result and could be complementary with the existing diagnostic methods.