Explaining the Elusive Nature of a Well-Defined Threshold for Blood Transfusion in Advanced Epithelial Ovarian Cancer Cytoreductive Surgery

Alexandros Laios; Evangelos Kalampokis; Marios Evangelos Mamalis; Amudha Thangavelu; Yong Sheng Tan; Richard Hutson; Sarika Munot; Timothy Broadhead; David Nugent; Georgios Theophilou; Robert Edward Jackson; Diederick De Jong

doi:10.20944/preprints202310.1819.v1

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preprints.org > medicine and pharmacology > oncology and oncogenics > doi: 10.20944/preprints202310.1819.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Explaining the Elusive Nature of a Well-Defined Threshold for Blood Transfusion in Advanced Epithelial Ovarian Cancer Cytoreductive Surgery

Alexandros Laios

^* ,

Evangelos Kalampokis

Marios Evangelos Mamalis

Robert Edward Jackson

Diederick De Jong

Version 1 : Received: 26 October 2023 / Approved: 27 October 2023 / Online: 27 October 2023 (14:21:45 CEST)

A peer-reviewed article of this Preprint also exists.

Laios, A.; Kalampokis, E.; Mamalis, M.-E.; Thangavelu, A.; Tan, Y.S.; Hutson, R.; Munot, S.; Broadhead, T.; Nugent, D.; Theophilou, G.; Jackson, R.-E.; Jong, D.D. Explaining the Elusive Nature of a Well-Defined Threshold for Blood Transfusion in Advanced Epithelial Ovarian Cancer Cytoreductive Surgery. Diagnostics 2024, 14, 94. Laios, A.; Kalampokis, E.; Mamalis, M.-E.; Thangavelu, A.; Tan, Y.S.; Hutson, R.; Munot, S.; Broadhead, T.; Nugent, D.; Theophilou, G.; Jackson, R.-E.; Jong, D.D. Explaining the Elusive Nature of a Well-Defined Threshold for Blood Transfusion in Advanced Epithelial Ovarian Cancer Cytoreductive Surgery. Diagnostics 2024, 14, 94.

Abstract

There is no well-defined threshold for intra-operative blood transfusion (BT) in advanced epithelial ovarian cancer (EOC) surgery. We developed a Machine Learning (ML)-driven prediction algorithm to trigger and explain a communication alert for BT based on anticipated peri-operative events irrespective of BT policies. We analysed prospectively collected data from 403 EOC patients who underwent cytoreductive surgery between 2014 and 2019. We calculated the estimated blood volume (EBV) using the formula EBV = weight x 80 and set off 10%EBV as threshold for individual intervention. Based on the known estimated blood loss (EBL) we identified two groups. We employed Receiver operating characteristic (ROC) curves for performance metrics. The model performance for the above threshold prediction was satisfactory (AUC 0.823, 95% CI 0.76-0.88). The top feature commonly shared between interrogators was operative time (OT). Intra-operative blood loss of at least 10%EBV was associated with OT>250 minutes, primary surgery, serous histology, performance status 0, R2 resection and surgical complexity score >4. Large bowel resection, stoma formation, ileocecal resection/right hemicolectomy, mesenteric resection, bladder and upper abdominal peritonectomy were amongst sub-procedures clearly associated with increased intervention risk. Precise prediction of blood requirements is not possible unless a rough estimate of OT is known in advance.

Keywords

epithelial ovarian cancer; complete cytoreduction; estimated blood loss; estimated blood volume; blood transfusion; intra-operative mapping; machine learning; explainable artificial intelligence

Subject

Medicine and Pharmacology, Oncology and Oncogenics

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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