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Revisiting basal cell carcinoma clinical margins: Leveraging natural language processing and multivariate analysis with updated Royal College of Pathologists histological reporting standards

Stephen Ali, Thomas Dobbs, Matt Jovic, Huw Strafford, Arron S. Lacey Orcid Logo, Namor Williams Orcid Logo, Owen Pickrell Orcid Logo, Hayley Hutchings Orcid Logo, Iain Whitaker

Journal of Plastic, Reconstructive and Aesthetic Surgery, Volume: 88, Pages: 443 - 451

Swansea University Authors: Stephen Ali, Thomas Dobbs, Matt Jovic, Huw Strafford, Arron S. Lacey Orcid Logo, Owen Pickrell Orcid Logo, Hayley Hutchings Orcid Logo, Iain Whitaker

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Abstract

Introduction: Data supporting the current British Association of Dermatologists guidelines for the management of basal cell carcinoma (BCC) are based on historic studies and do not consider updated Royal College of Pathologists (RCPath) histological reporting standards. The aim of this study was to...

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Published in: Journal of Plastic, Reconstructive and Aesthetic Surgery
ISSN: 1748-6815
Published: Elsevier BV 2024
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa64779
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Abstract: Introduction: Data supporting the current British Association of Dermatologists guidelines for the management of basal cell carcinoma (BCC) are based on historic studies and do not consider updated Royal College of Pathologists (RCPath) histological reporting standards. The aim of this study was to use natural language processing (NLP)-derived data and undertake a multivariate analysis with updated RCPath standards, providing a contemporary update on the excision margins required to achieve histological clearance in BCC. Methods: A validated NLP information extraction model was used to perform a rapid multi-centre, pan-specialty, consecutive retrospective analysis of BCCs over a 17-year period (2004-2021) managed with surgical excision using a pre-determined clinical margin at Swansea Bay University Health Board. Logistic regression assessed the relationship between the peripheral and deep margins and histological clearance. Results: We ran our NLP algorithm on 34,955 BCCs. Out of 1,447 BCCs meeting inclusion criteria, the peripheral margin clearance was not influenced by BCC risk level (p = 0.670). A clinical peripheral margin of 6 mm achieved a 95% histological clearance rate (95% CI, 0.93-0.98). Tumour thickness inversely affected deep margin histological clearance (OR 0.720, 95% CI, 0.525-0.991, p < 0.05). Depth level 2 had a 97% probability of achieving deep margin histological clearance across all tumour thicknesses. Conclusion: Updated RCPath reporting standards minimally impact peripheral margin histological clearance in BCC. Larger clinical peripheral margins than current guidelines suggest may be necessary to achieve excision rates of ≥95%. These findings emphasise the need for continuous reassessment of clinical standards to enhance patient care.
Keywords: Basal cell carcinoma, clinical margins, natural language processing, multivariate analysis, histological reporting guidelines, Royal College of Pathologists
College: Faculty of Medicine, Health and Life Sciences
Funders: SRA and TDD are funded by the Welsh Clinical Academic Training Fellowship. ISW is the surgical Specialty Lead for Health and Care Research Wales, and reports active grants from the American Association of Plastic Surgeons and the European Association of Plastic Surgeons. SRA received a grant from the British Association of Plastic, Reconstructive and Aesthetic Surgeons specifically for this work. The Reconstructive Surgery & Regenerative Medicine Research Centre is funded by The Scar Free Foundation and Health and Care Research Wales. The Scar Free Foundation is the only medical research charity focused on scarring with the mission to achieve scar free healing within a generation.
Start Page: 443
End Page: 451