Revisiting basal cell carcinoma clinical margins : Leveraging natural language processing and multivariate analysis with updated Royal College of Pathologists histological reporting standards
Copyright © 2023. Published by Elsevier Ltd..
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 the 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, managed with surgical excision using a pre-determined clinical margin, over a 17-year period (2004-2021) 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 the 1447 BCCs that met the inclusion criteria, the peripheral margin clearance was not influenced by the BCC risk level (p = 0.670). A clinical peripheral margin of 6 mm achieved a 95% histological clearance rate (95% confidence interval [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 the peripheral margin histological clearance in BCC. Larger clinical peripheral margins than those indicated by current guidelines may be necessary to achieve excision rates of ≥95%. These findings emphasise the need for continuous reassessment of clinical standards to enhance patient care.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:88 |
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| Enthalten in: |
Journal of plastic, reconstructive & aesthetic surgery : JPRAS - 88(2024) vom: 01. Jan., Seite 443-451 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Ali, Stephen R [VerfasserIn] |
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| Links: |
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| Themen: |
Basal cell carcinoma |
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| Anmerkungen: |
Date Completed 02.01.2024 Date Revised 06.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.bjps.2023.10.106 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 100 | 1 | |a Ali, Stephen R |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Revisiting basal cell carcinoma clinical margins |b Leveraging natural language processing and multivariate analysis with updated Royal College of Pathologists histological reporting standards |
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| 500 | |a Date Revised 06.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023. Published by Elsevier Ltd. | ||
| 520 | |a 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 the 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 | ||
| 520 | |a METHODS: A validated NLP information extraction model was used to perform a rapid multi-centre, pan-specialty, consecutive retrospective analysis of BCCs, managed with surgical excision using a pre-determined clinical margin, over a 17-year period (2004-2021) at Swansea Bay University Health Board. Logistic regression assessed the relationship between the peripheral and deep margins and histological clearance | ||
| 520 | |a RESULTS: We ran our NLP algorithm on 34,955 BCCs. Out of the 1447 BCCs that met the inclusion criteria, the peripheral margin clearance was not influenced by the BCC risk level (p = 0.670). A clinical peripheral margin of 6 mm achieved a 95% histological clearance rate (95% confidence interval [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 | ||
| 520 | |a CONCLUSION: Updated RCPath reporting standards minimally impact the peripheral margin histological clearance in BCC. Larger clinical peripheral margins than those indicated by current guidelines may be necessary to achieve excision rates of ≥95%. These findings emphasise the need for continuous reassessment of clinical standards to enhance patient care | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Basal cell carcinoma | |
| 650 | 4 | |a Clinical margins | |
| 650 | 4 | |a Histological reporting guidelines | |
| 650 | 4 | |a Multivariate analysis | |
| 650 | 4 | |a Natural language processing | |
| 650 | 4 | |a Royal College of Pathologists | |
| 700 | 1 | |a Dobbs, Thomas D |e verfasserin |4 aut | |
| 700 | 1 | |a Jovic, Matthew |e verfasserin |4 aut | |
| 700 | 1 | |a Strafford, Huw |e verfasserin |4 aut | |
| 700 | 1 | |a Lacey, Arron S |e verfasserin |4 aut | |
| 700 | 1 | |a Williams, Namor |e verfasserin |4 aut | |
| 700 | 1 | |a Pickrell, William Owen |e verfasserin |4 aut | |
| 700 | 1 | |a Hutchings, Hayley A |e verfasserin |4 aut | |
| 700 | 1 | |a Whitaker, Iain S |e verfasserin |4 aut | |
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