Intraoperative frozen section pathology of vaginal margin in radical hysterectomy on the prognosis and quality of life for patients with IB2-IIA2 cervical cancer: study protocol for a multicenter randomized controlled trial

BACKGROUND

Several risk factors have been identified that compromise the treatment outcome in patients with early-to-mid-stage cervical cancer (CC) who are primarily treated with radical surgery. However, there is no report on the impact of intraoperative frozen pathology examination of vaginal margins on the prognosis of patients with CC. This study aimed to conduct a randomized controlled trial (RCT) to determine whether selective vaginal resection can reduce the incidence of operative complications and the risk of postoperative radiotherapy. The impact of the length of the vagina removed in radical hysterectomy (RH) on prognosis and quality of life (QoL) for IB2-IIA2 CC patients will be investigated.

METHODS

A multicenter, non-inferiority, RCT at 7 institutions in China is designed to investigate the effect of intraoperative frozen pathology exam of vaginal margin in RH on the survival outcomes for patients with IB2-IIA2 CC. Eligible patients aged 18-70 years will be randomly assigned online by one-to-one random allocation to receive intraoperative frozen pathology exam of vaginal margin or not. If frozen pathology indicates positive margin, continue resection of 1 centimeter of vaginal tissue until negative margin is achieved. The primary end point is 2-year disease-free survival (DFS). Adverse events (AEs) caused by further vagina resection, 5-year DFS, 2-year overall survival (OS), 5-year OS and AEs caused by radiotherapy and QoL are secondary end points. A total of 310 patients will be enrolled from 7 tertiary hospitals in China within 3-year period and followed up for 5 years.

TRIAL REGISTRATION

Chinese Clinical Trial Registry Identifier: ChiCTR2000035668.

Impact of surgical margin and extent of lymphadenectomy on oncologic outcomes in plasmacytoid urothelial carcinoma

OBJECTIVE

Guideline recommendations disagree on template boundaries for pelvic lymph node dissection (PLND) in conventional urothelial carcinoma. Less is known about PLND in variant histology. We aimed to analyze the role of LND in plasmacytoid urothelial carcinoma (PUC).

METHODS

A retrospective review of patients with cTanyNanyM0 PUC who underwent radical cystectomy (RC) with PLND was performed from 2012 to 2022. Lymph node count (LNC) was a surrogate for extent of lymph node dissection and dichotomized based on maximally selected rank statistics. Multivariable cox hazard regression analysis (MVA) for overall survival (OS) corrected for age, perioperative chemotherapy, soft tissue margin status, and stage ≥pT3 and/or pN+ was performed. Disease free survival (DFS) and OS were estimated using Kaplan-Meier (KM) analysis.

RESULTS

Sixty-seven patients with median age of 71, who were 79.1% male were included. Neoadjuvant and adjuvant chemotherapy were administered in 61.2% and 19.4% of patients, respectively. At RC, 70.1% were ≥pT3. Median LNC was 22 (IQR 14-27) with 43.3% of patients being pN+. Calculated optimal-LNC cut point for DFS and OS was 19. Grouping by optimal (≥20) vs. suboptimal-LNC (<20), no significant clinicodemographic differences were found. Optimal-LNC provided improved DFS (P = 0.05) and OS (P = 0.02). Optimal-LNC (HR 0.47, 0.24-0.93 CI 95%, P = 0.03) and negative soft tissue margin (HR 0.38, 0.19-0.76 CI 95%, P = 0.01) was associated with improved OS on MVA. Receipt of perioperative chemotherapy did not improve OS (P = 0.46).

CONCLUSION

In PUC, complete surgical extirpation achieving negative soft tissue margins and removing ≥20 lymph should be prioritized if operative intervention is pursued.

Machine learning methods applied to audit of surgical margins after curative surgery for head and neck cancer

Most surgical specialties have attempted to address concerns about the unfair comparison of outcomes by 'risk-adjusting' data to benchmark specialty-specific outcomes that are indicative of quality of care. We explore the ability to predict for positive margin status so that effective benchmarking that will account for complexity of case mix is possible. A dataset of care episodes recorded as a clinical audit of margin status after surgery for head and neck squamous cell carcinoma (n=1316) was analysed within the Waikato Environment for Knowledge Analyisis (WEKA) machine learning programme. The outcome was a classification model that can predict for positivity of tumour margins (defined as less than 1mm) using data on preoperative demographics, operations, functional status, and tumour stage. Positive resection margins of less than 1mm were common, and varied considerably between treatment units (19%-29%). Four algorithms were compared to attempt to risk-adjust for case complexity. The 'champion' model was a Naïve Bayes classifier (AUROC 0.72) that suggested acceptable discrimination. Calibration was good (Hosmer-Lemershow goodness-of-fit test p=0.9). Adjusted positive margin rates are presented on a funnel plot. Subspecialty groups within oral and maxillofacial surgery are seeking metrics that will allow for meaningful comparison of the quality of care delivered by surgical units in the UK. To enable metrics to be effective, we argue that they can be modelled so that meaningful benchmarking, which takes account of variation in complexity of patient need or care, is possible.