Mark McGowan

Can natural language processing be effectively applied for audit data analysis in gynaecological oncology at a UK cancer centre?

The British Gynaecological Cancer Society (BGCS) has highlighted the disparity of ovarian cancer outcomes in the UK compared to other European countries. Therefore, cancer quality assurance audits and subspecialty training are important in improving the UK standard of care for these patients. The current workforce crisis afflicting the NHS creates difficulty in dedicating teams of clinicians to these audits. We present a single institution study to evaluate if NLP-generated code can improve the efficiency of ovarian cancer and subspeciality reaccreditations audits. We used the chat bot Google Bard to write Visual Basic Applications algorithms that utilise Excel files from electronic health records. Primary ovarian cancer data from 2019 to 2022 was retrospectively collected from the Cambridge University Hospital electronic health records. The surgical subspecialty reaccreditation audit analysed the 2022 surgical database. A modular coding approach with Google Bard was applied to generate audit algorithms. The time to complete these current audits was compared against the 2016 ovarian cancer and 2020 subspeciality reaccreditation audits. The previous ovarian cancer audit conducted in 2016 required 3 clinicians for the 135 cases and data collection required 1800 min. Data analysis was completed in 300 min. The current ovarian cancer audit allocated 2 clinicians to the 600 surgical cases. Data collection was completed in 3120 min, 3360 min for code development and 720 min for testing. The 2020 subspecialty reaccreditation audit was completed in 360 min. The 2022 subspecialty reaccreditation audit was completed in 1680 min, with 960 min for code development, 240 for debugging and 480 min for testing. We have demonstrated that NLP-generated code can significantly increase the efficiency of surgical quality assurance audits by eliminating the need for manual data analysis. With the current trajectory of NLP development, increasingly complex algorithms can be developed with minimal programming knowledge.

Neo-adjuvant chemotherapy does not reduce surgical complexity nor the accuracy of intra-operative visual assessment of disease in advanced ovarian cancer

Compare the surgical complexity and histological accuracy of visual inspection of disease in patients undergoing primary debulking (PDS) versus delayed debulking surgery (DDS) following neo-adjuvant chemotherapy (NACT) for advanced ovarian cancer (AOC). All patients undergoing PDS or DDS for stage III / IV AOC at a UK cancer centre between January 2014-October 2021 were included. Retrospective data was collected accessing an electronic gynaecological oncology database, operation and histology records. Comparative frequencies of surgical procedures performed were calculated for primary versus delayed cohorts; and correlation between intra-operative suspicion of disease and specimen histology at PDS and DDS compared. N=232. PDS was performed in 45.3% and DDS in 54.7% of patients; achieving complete cytoreduction in 77.2%. Appendicectomy, pelvic and para-aortic nodal dissection were undertaken significantly more often at primary surgery; whilst right diaphragm stripping, pelvic peritonectomy, splenectomy and cholecystectomy were more likely following NACT. We found no variation in bowel resection rates between cohorts. For the majority of specimens, there was no difference in correlation between intra-operative suspicion of disease and final histopathology - with a significantly lower positive predictive value for visual assessment demonstrated only for liver capsule and pelvic peritoneum at DDS. NACT does not appear to reduce the complexity of surgery, including rates of bowel resection; nor accuracy of intra-operative visual assessment of disease. We therefore caution against both deferring to NACT to facilitate less radical delayed debulking; and any presumption that macroscopically abnormal tissue at DDS may represent inert post-NACT 'burn-out', mitigating indication for excision. We instead suggest reservation of the neo-adjuvant pathway for patients with poor PS and radiologically-confirmed surgical stopping points; and advocate equivalent and maximal cytoreductive effort to remove all visibly abnormal tissue in both the upfront and delayed surgical settings.