The impact of COVID-19 on surgical volume and surgical training at a high-volume pelvic oncology centre

Introduction: The coronavirus (COVID-19) pandemic has overwhelmed most health services. As a result, many surgeries have been deferred and diagnoses delayed. The aim of this study was to assess the effect of the COVID-19 pandemic at a high-volume pelvic oncology centre. Methods: A retrospective review was performed of clinical activity from 2017 to 2020. We compared caseload for index procedures 2017–2019 (period 1) versus 2020 (period 2) to see the effect of the COVID pandemic. We then compared the activity during the first lockdown (March 23rd) to the rest of the year when we increased our theatre access by utilising a ‘clean’ site. Results: The average annual number of robotic assisted radical cystectomy (RARC) and robotic assisted radical prostatectomy (RARP) performed during period 1 was 82 and 352 respectively. This reduced to 68 (17.1% reduction) and 262 (25.6% reduction) during period 2. The number of patients who underwent prostate brachytherapy decreased from 308 to 243 (21% reduction). The number of prostate biopsies decreased from 420 to 234 (44.3% reduction). The number of radical orchidectomies decreased from 18 to 11 (39% reduction). The mean number of RARC and RARP per month during period 2 was 5.5 and 22. This decreased to 4 and 9 per month during the first national lockdown but was maintained thereafter despite two further lockdowns. Conclusion: There has been a substantial decrease in urological oncology caseload during the COVID pandemic. The use of alternate pathways such as ‘clean’ sites can ensure continuity of care for cancer surgery and training needs.

Estimating the risk of malignancy of adnexal masses: validation of the ADNEX model in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China

Background This study aims to validate the diagnostic accuracy of the International Ovarian Tumor Analysis (IOTA) the Assessment of Different NEoplasias in the adneXa (ADNEX) model in the preoperative diagnosis of adnexal masses in the hands of nonexpert ultrasonographers in a gynaecological oncology centre in China. Methods This was a single oncology centre, retrospective diagnostic accuracy study of 620 patients. All patients underwent surgery, and the histopathological diagnosis was used as a reference standard. The masses were divided into five types according to the ADNEX model: benign ovarian tumours, borderline ovarian tumours (BOTs), stage I ovarian cancer (OC), stage II-IV OC and ovarian metastasis. Receiver operating characteristic (ROC) curve analysis was used to evaluate the ability of the ADNEX model to classify tumours into different histological types with and without cancer antigen 125 (CA 125) results. Results Of the 620 women, 402 (64.8%) had a benign ovarian tumour and 218 (35.2%) had a malignant ovarian tumour, including 86 (13.9%) with BOT, 75 (12.1%) with stage I OC, 53 (8.5%) with stage II-IV OC and 4 (0.6%) with ovarian metastasis. The AUC of the model to differentiate benign and malignant adnexal masses was 0.97 (95% CI, 0.96–0.98). Performance was excellent for the discrimination between benign and stage II-IV OC and between benign and ovarian metastasis, with AUCs of 0.99 (95% CI, 0.99–1.00) and 0.99 (95% CI, 0.98–1.00), respectively. The model was less effective at distinguishing between BOT and stage I OC and between BOT and ovarian metastasis, with AUCs of 0.54 (95% CI, 0.45–0.64) and 0.66 (95% CI, 0.56–0.77), respectively. When including CA125 in the model, the performance in discriminating between stage II–IV OC and stage I OC and between stage II–IV OC ovarian metastasis was improved (AUC increased from 0.88 to 0.94, P = 0.01, and from 0.86 to 0.97, p = 0.01). Conclusions The IOTA ADNEX model has excellent performance in differentiating benign and malignant adnexal masses in the hands of nonexpert ultrasonographers with limited experience in China. In classifying different subtypes of ovarian cancers, the model has difficulty differentiating BOTs from stage I OC and BOTs from ovarian metastases.