FACE-Q for Measuring Patient-reported Outcomes after Facial Skin Cancer Surgery: Cross-cultural Validation.

Background: Facial skin cancer and its surgical treatment can affect health-related quality of life. The FACE-Q Skin Cancer Module is a patient-reported outcome measure that measures different aspects of health-related quality of life and has recently been translated into Dutch. This study aimed to evaluate the performance of the translated version in a Dutch cohort using modern psychometric measurement theory (Rasch).

Service implications of the revised 2022 National Institute for Health and Care Excellence (NICE) follow-up guidelines for stage IA-IIC melanoma.

Background: The 2022 National Institute for Health and Care Excellence melanoma guideline update made significant changes to follow-up. The aim of this study was to assess the impact these changes will have on a national melanoma cohort over a 5-year follow-up interval.

Methods: Anonymized, individual-level, population-scale, linkable primary and secondary care National Health Service data for an 18-year interval (2000-2018) in Wales, UK were analysed.

Natural language processing to automate a web-based model of care and modernize skin cancer multidisciplinary team meetings.

Background: Cancer multidisciplinary team (MDT) meetings are under intense pressure to reform given the rapidly rising incidence of cancer and national mandates for protocolized streaming of cases. The aim of this study was to validate a natural language processing (NLP)-based web platform to automate evidence-based MDT decisions for skin cancer with basal cell carcinoma as a use case.

Methods: A novel and validated NLP information extraction model was used to extract perioperative tumour and surgical factors from histopathology reports.

Prevalence and odds of anxiety and depression in cutaneous malignant melanoma: a proportional meta-analysis and regression.

Background: The psychological burden of cutaneous malignant melanoma (CM) is all-encompassing, affecting treatment adherence, recurrence and mortality. However, the prevalence and risk factors of anxiety and depression in CM remain unclear.

Objectives: To establish a benchmark pooled prevalence of anxiety and depression in CM, to provide magnitudes of association for clinical, therapeutic and demographic correlates, and to elucidate temporal trends in anxiety and depression from the time of diagnosis.

Can Large Language Models Generate Outpatient Clinic Letters at First Consultation That Incorporate Complication Profiles From UK and USA Aesthetic Plastic Surgery Associations?

The importance of written communication between clinicians and patients, especially in the wake of the Supreme Court case of Montgomery vs Lanarkshire, has led to a shift toward patient-centric care in the United Kingdom. This study investigates the use of large language models (LLMs) like ChatGPT and Google Bard in enhancing clinic letters with gold-standard complication profiles, aiming to improve patients' understanding and save clinicians' time in aesthetic plastic surgery. The aim of this study is to assess the effectiveness of LLMs in integrating complication profiles from authoritative sources into clinic letters, thus enhancing patient comprehension and clinician efficiency in aesthetic plastic surgery.

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

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.

Comparative study of ChatGPT and human evaluators on the assessment of medical literature according to recognised reporting standards.

Introduction: Amid clinicians' challenges in staying updated with medical research, artificial intelligence (AI) tools like the large language model (LLM) ChatGPT could automate appraisal of research quality, saving time and reducing bias. This study compares the proficiency of ChatGPT3 against human evaluation in scoring abstracts to determine its potential as a tool for evidence synthesis.

Methods: We compared ChatGPT's scoring of implant dentistry abstracts with human evaluators using the Consolidated Standards of Reporting Trials for Abstracts reporting standards checklist, yielding an overall compliance score (OCS).

The incidence of non-melanoma skin cancer in the UK and the Republic of Ireland: a systematic review.

Background: Basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC) remain the most prevalent malignancies, contributing a higher workload to cancer registries than all cancers combined. The nature of skin cancers in addition to current coding methods employed by registries give a skewed representation of the workload.

Objectives: A comprehensive search examining the incidence of BCC and/or cSCC at a regional or national level in the UK and Ireland was devised.

Evaluating remote skin cancer multidisciplinary team meetings in the United Kingdom post-COVID-19.

Introduction: Prior to the COVID-19 pandemic, there was concern that virtual or remote multidisciplinary teams (MDT) meetings represented a niche concept that was unlikely to replace traditional face-to-face meetings in the management of cancer. However, the sudden shift to virtual meetings during COVID-19 has been one of the most dramatic changes since the inception of the MDT. This study aims to investigate the effectiveness of virtual skin MDTs since the move to virtual meetings.

Improving the effectiveness of multidisciplinary team meetings on skin cancer: Analysis of the National Cancer Research UK survey responses.

Introduction: Skin cancer is the most common form of cancer in the UK, comprising at least 25% of all new cancer diagnoses. Many patients require referral to the local or specialist skin cancer multidisciplinary team (MDT) for ongoing management. However, national data have shown that Specialist Skin Cancer MDTs are costly and do not currently meet NICE standards for composition and quoracy.

The psychosocial impact of microtia and ear reconstruction: A national data-linkage study.

Introduction: Children with visible facial differences are believed to be at increased risk of negative psychosocial behaviours which may manifest as affective disorders. The aim of this study was to determine whether a diagnosis of microtia, and the associated surgical intervention, is associated with psychosocial implications including impaired educational attainment and a diagnosis of an affective disorder.

Methods: A retrospective case-control study was conducted using data linkage to identify patients in Wales with a diagnosis of microtia.

The epidemiology, healthcare and societal burden of basal cell carcinoma in Wales 2000-2018: a retrospective nationwide analysis.

Background: Basal cell carcinoma (BCC) represents the most commonly occurring cancer worldwide within the white population. Reports predict 298 308 cases of BCC in the UK by 2025, at a cost of £265-366 million to the National Health Service (NHS). Despite the morbidity, societal and healthcare pressures brought about by BCC, routinely collected healthcare data and global registration remain limited.

Development and validation of an automated basal cell carcinoma histopathology information extraction system using natural language processing.

Introduction: Routinely collected healthcare data are a powerful research resource, but often lack detailed disease-specific information that is collected in clinical free text such as histopathology reports. We aim to use natural Language Processing (NLP) techniques to extract detailed clinical and pathological information from histopathology reports to enrich routinely collected data.

Methods: We used the general architecture for text engineering (GATE) framework to build an NLP information extraction system using rule-based techniques.

Diagnosing and managing a giant primary cutaneous malignant melanoma of the lower limb.

We present a woman who was referred to our plastic surgery unit with a suspected squamous cell carcinoma following a 3-year history of an enlarging mass on her thigh. Surprisingly, histopathological assessment confirmed the diagnosis of nodular malignant melanoma measuring 77×77×54 mm with a Breslow thickness of 52 mm, making it the largest recorded lower limb primary cutaneous malignant melanoma in the UK.

Simulation models for learning local skin flap design and execution: A systematic review of the literature.

Introduction: Early exposure to practical skills in surgical training is essential in order to master technically demanding procedures such as the design and execution of local skin flaps. Changes in working patterns, increasing subspecializations, centralization of surgical services, and the publication of surgeon-specific outcomes have all made hands-on-training in a clinical environment increasingly difficult to achieve for the junior surgeon. This has been further compounded by the COVID-19 pandemic.

Using a ChatBot to support clinical decision-making in free flap monitoring.

Flap monitoring charts and escalation protocols are ubiquitous amongst microsurgical departments and can facilitate converting flap observations into flap monitoring decisions. However, human factors in the recognition-communication process of decision-making still pose a threat to timely intervention and thus are a key determinant of success in microvascular surgery. Digitally transforming paper-based pathways may facilitate early recognition and escalation to potentially salvage a free flap with compromised vascularity.

Can patients with asymptomatic SARS-CoV-2 infection safely undergo elective surgery?

Current or recent infection with SARS-CoV-2 increases the risk of perioperative morbidity and mortality. Consensus guidelines recommend delaying elective major surgery after acute SARS-CoV-2 infection for 7 or 8 weeks. However, because of the growing backlog of untreated surgical disease and the potential risks of delaying surgery, surgical services may be under pressure to reduce this period.