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). Methods: Dutch participants with facial skin cancer were prospectively recruited and asked to complete the translated FACE-Q Skin Cancer Module. The following assumptions of the Rasch model were tested: unidimensionality, local independence, and monotonicity. Response thresholds, fit statistics, internal consistency, floor and ceiling effects, and targeting were assessed for all scales and items within the scales. Responsiveness was tested for the "cancer worry" scale. Results: In total, 259 patients completed the preoperative questionnaire and were included in the analysis. All five scales assessed showed a good or sufficient fit to the Rasch model. Unidimensionality and monotonicity were present for all scales. Some items showed a local dependency. Most of the scales demonstrate ordered item thresholds and appropriate fit statistics. Conclusions: The FACE-Q Skin Cancer Module is a well-designed patient-reported outcome measure that shows psychometric validity for the translated version in a Dutch cohort, using classical and modern test theory.

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. A web application with a bespoke application programming interface used data from this model to provide an automated clinical decision support system, mapped to national guidelines and generating a patient letter to communicate ongoing management. Performance was assessed against retrospectively derived recommendations by two independent and blinded expert clinicians. RESULTS: There were 893 patients (1045 lesions) used to internally validate the model. High accuracy was observed when compared against human predictions, with an overall value of 0.92. Across all classifiers the virtual skin MDT was highly specific (0.96), while sensitivity was lower (0.72). CONCLUSION: This study demonstrates the feasibility of a fully automated, virtual, web-based service model to host the skin MDT with good system performance. This platform could be used to support clinical decision-making during MDTs as 'human in the loop' approach to aid protocolized streaming. Future prospective studies are needed to validate the model in tumour types where guidelines are more complex.

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. Seven widely performed aesthetic procedures were chosen, and complication profiles were sourced from the British Association of Aesthetic Plastic Surgeons (BAAPS) and the American Society of Plastic Surgeons (ASPS). We evaluated the proficiency of the ChatGPT4, ChatGPT3.5, and Google Bard in generating clinic letters which incorporated complication profiles from online resources. These letters were assessed for readability using an online tool, targeting a recommended sixth-grade reading level. ChatGPT4 achieved the highest compliance in integrating complication profiles from BAAPS and ASPS websites, with average readability grades between eighth and ninth. ChatGPT3.5 and Google Bard showed lower compliance, particularly when accessing paywalled content like the ASPS Informed Consent Bundle. In conclusion, LLMs, particularly ChatGPT4, show promise in enhancing patient communications in aesthetic plastic surgery by effectively incorporating standard complication profiles into clinic letters. This aids in informed decision making and time saving for clinicians. However, the study underscores the need for improvements in data accessibility, search capabilities, and ethical considerations for optimal LLM integration into healthcare communications. Future enhancements should focus on better interpretation of inaccessible formats and a Human in the Loop approach to combine Artifical Intelligence capabilities with clinician expertise.

Prevalence & Odds of Anxiety & Depression in Cutaneous Malignant Melanoma: A Proportional Meta-analysis & Regression.

BACKGROUND: The psychological burden of cutaneous malignant melanoma (CM) is all-encompassing, affecting treatment adherence, recurrence, and mortality. Yet, the prevalence and risk factors of anxiety and depression (A&D) in CM remain unclear. OBJECTIVES: To establish a benchmark pooled prevalence of A&D in CM, provide magnitudes of association for clinical, therapeutic, and demographic correlates, and elucidate temporal trends in A&D from the time of diagnosis. METHODS: This review was reported in line with MOOSE guidance. MEDLINE, Embase, PsychINFO, Web of Science, and the Cochrane Library were queried from database inception through August 24th, 2023. Study selection, data extraction, and quality assessment were performed by two independent authors, utilising both the JBI and NIH risk of bias (ROB) tools for the latter. The GRADE approach was used to rate the certainty of evidence. Prevalence rates, 95% Confidence (CI), and Prediction (PI) Intervals were derived using a random-effects model, and estimating between- and within-study variance. RESULTS: Nine longitudinal and 29 cross-sectional studies were included (n = 7,995). Quality assessment revealed 20/17 low, 12/15 moderate, and six/five high ROB studies, based on JBI/NIH tools, respectively. The prevalence of A (30.6% [95% CI, 24.6-37.0%; PI, 18-47%]) and D (18.4% [95% CI, 13.4-23.9%; PI, 10-33%]) peaked during treatment, declining to pre-treatment levels after one year (A: 48% vs 20%, p = 0.005; D: 28% vs 13%, p = 0.03). Female gender (OR 1.8; 95% CI, 1.4-2.3; p < 0.001), age <60 years (OR 1.5; 95% CI, 1.2-2.0; p = 0.002), and low educational level (OR 1.5; 95% CI, 1.2-2.0; p < 0.001) were likely to result in a large increase in the odds of anxiety. Depression was 12.3% higher in stage IV vs I CM (p = 0.048). Relative to immune checkpoint inhibition, the rates of depression were 22% (p = 0.002) and 34% (p < 0.001) higher among advanced-stage patients receiving interferon-α and chemotherapy, respectively. A significant diminution in self-reported depression scores was demonstrated over time (p = 0.003). CONCLUSIONS: A&D in CM notably affects women, under-60 s, and the less educated, with up to 80% higher odds of anxiety in these groups. A&D surge during CT & IFN treatment, especially in advanced CM. Our findings facilitate risk stratification and underscore the need for multi-disciplinary vigilance.

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. These data were used to predict the number of patients over a 10-year interval (2020-2030) that would be diagnosed with melanoma. Follow-up schedules for the 2015 and 2022 National Institute for Health and Care Excellence melanoma guidelines were then used to calculate the number of clinician-led appointments, the number of radiological investigations, and the total healthcare cost between 2025 and 2030, corresponding to a 5-year patient follow-up interval, for those with stage IA-IIC melanoma. RESULTS: Between 2025 and 2030 it is predicted that implementation of the 2022 guidelines would lead to 21 122 (range 19 194-23 083) fewer clinician-led appointments for patients with stage IA-IIC melanoma. However, there would be a significant increase in the number of radiological investigations (7812; range 7444-8189). These changes would lead to a €2.74 million (€1.87 million-€3.61 million) reduction in the total cost of follow-up over the interval 2025-2030. CONCLUSION: Melanoma follow-up guideline changes will result in a substantial reduction in the number of clinical follow-up appointments, but a significant additional burden to radiological services. The overall cost of follow-up at a national level will be reduced.

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. 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.

The association of anxiety disorders and depression with facial scarring: population-based, data linkage, matched cohort analysis of 358 158 patients.

BACKGROUND: Estimates suggest that 1 in 100 people in the UK live with facial scarring. Despite this incidence, psychological support is limited. AIMS: The aim of this study was to strengthen the case for improving such support by determining the incidence and risk factors for anxiety and depression disorders in patients with facial scarring. METHOD: A matched cohort study was performed. Patients were identified via secondary care data sources, using clinical codes for conditions resulting in facial scarring. A diagnosis of anxiety or depression was determined by linkage with the patient's primary care general practice data. Incidence was calculated per 1000 person-years at risk (PYAR). Logistic regression was used to determine risk factors. RESULTS: Between 2009 and 2018, 179 079 patients met the study criteria and were identified as having a facial scar, and matched to 179 079 controls. The incidence of anxiety in the facial scarring group was 10.05 per 1000 PYAR compared with 7.48 per 1000 PYAR for controls. The incidence of depression in the facial scarring group was 16.28 per 1000 PYAR compared with 9.56 per 1000 PYAR for controls. Age at the time of scarring, previous history of anxiety or depression, female gender, socioeconomic status and classification of scarring increased the risk of both anxiety disorders and depression. CONCLUSIONS: There is a high burden of anxiety disorders and depression in this patient group. Risk of these mental health disorders is very much determined by factors apparent at the time of injury, supporting the need for psychological support.

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). Bland-Altman analysis assessed agreement between human and AI-generated OCS percentages. Additional error analysis included mean difference of OCS subscores, Welch's t-test and Pearson's correlation coefficient. RESULTS: Bland-Altman analysis showed a mean difference of 4.92% (95% CI 0.62%, 0.37%) in OCS between human evaluation and ChatGPT. Error analysis displayed small mean differences in most domains, with the highest in 'conclusion' (0.764 (95% CI 0.186, 0.280)) and the lowest in 'blinding' (0.034 (95% CI 0.818, 0.895)). The strongest correlations between were in 'harms' (r=0.32, p<0.001) and 'trial registration' (r=0.34, p=0.002), whereas the weakest were in 'intervention' (r=0.02, p<0.001) and 'objective' (r=0.06, p<0.001). CONCLUSION: LLMs like ChatGPT can help automate appraisal of medical literature, aiding in the identification of accurately reported research. Possible applications of ChatGPT include integration within medical databases for abstract evaluation. Current limitations include the token limit, restricting its usage to abstracts. As AI technology advances, future versions like GPT4 could offer more reliable, comprehensive evaluations, enhancing the identification of high-quality research and potentially improving patient outcomes.

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. Standardisation methods were grouped to permit comparison, and a bias assessment tool was employed. MATERIALS & METHODS: Sixteen UK and Republic of Ireland epidemiological studies on BCC/cSCC over a 48-year period were compiled, examining incidence, trends and emerging risk factors. RESULTS: Incidence of BCC within the UK is increasing annually by up to 4%, with rates in Wales increasing by up to 6.6% and 1.6% annually for BCC and cSCC, respectively. Inverse relationships are noted between BCC/cSCC and social deprivation. Although the elderly remain the most at risk, the 30-49 age group have illustrated growth rates of approximately 4%. CONCLUSION: This review outlines increasing incidence in the UK with higher rates noted in Wales, the Southeast, West and Central regions. Incidence rates are higher amongst the least socially deprived and an increasing incidence amongst younger age groups was found, however further trend analysis is required. A more comprehensive data collection method within registries is necessary to ensure accurate representation and fluid comparison. Service planning and public awareness campaigns must be implemented to prevent overwhelming future services.

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. METHODS: A cross-sectional survey was sent to all Specialist Skin Cancer MDTs (SSMDTs) and the British Association of Plastic, Reconstructive, and Aesthetic Surgeons Skin Oncology Special Interest and Advisory Group. RESULTS: There were 68 responses (55.3% response rate) from 36 SSMDTs in the UK. Respondents felt communication, chairing, and decision-making were similar in virtual and in-person MDTs, but the team working was worse in virtual meetings. Recruitment, data security, and patient confidentiality were maintained in virtual MDTs. Most preferred a hybrid format for future MDTs, with the option to attend virtually. Recommendations for improvement included better connectivity, IT support, training, and staff integration. CONCLUSION: The virtual MDT is here to stay. We highlight the strengths and weaknesses of remote virtual skin MDTs. It is key that we look at ways to retain team working to ensure that the collegiate nature of MDT working, and therefore treatment options for patients, are not lost in this transformation in MDT delivery.

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. Innovative solutions to these problems are therefore warranted. METHODS: We performed a secondary comparative analysis of 3563 quantitative responses to two Cancer Research UK commissioned surveys along with subanalysis of 282 skin cancer MDT respondents. RESULTS: Good uniformity was observed amongst skin respondents in the belief that risk stratification and prioritization of complex cases were the most important factors compared to other cancer MDT members. The most important priorities for areas requiring change to MDT working deemed by the skin MDT were 1) imaging and pathology results ready for the meeting, 2) time to discuss patients in detail, 3) clear meeting owner in charge, and 4) clear agenda, in advance of the meeting. There was agreement (median Likert score 4) amongst skin MDT respondents that patients should be placed on protocolized treatment pathways. CONCLUSION: The responses of skin MDT respondents analyzed in the current study support changes to meeting attendance, preparation, and protocolized streaming. In line with other studies, we support tumor-specific guidance for streamlining MDT discussions. We also encourage stakeholders to adopt an evidence-based approach to test, develop, and reassess changes in this herculean task.

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. Matched controls were sought on the basis of age, gender and socioeconomic deprivation status to yield a total sample size of 709. incidence was calculated using annual and geographic birth rates. Surgical operation codes were used to classify patients into those that had no surgery, autologous reconstruction or prosthetic reconstruction. Educational attainment at 11 years of age, plus a diagnosis of depression or anxiety were used as markers of adverse psychosocial outcomes and the relative risk was attained using logistic regression analyses. Results: There were no significant associations between a diagnosis of microtia and an increased risk of adverse educational attainment or a risk of an affective disorder diagnosis. Male gender and higher deprivation scores were significantly associated with poorer educational attainment, irrespective of a diagnosis of microtia. Surgical intervention of any nature was also not associated with any increased risk of adverse educational or psychosocial outcomes in microtia patients. Discussion: Microtia patients in Wales do not appear to be at greater risk of developing affective disorders or impaired academic performance as a result of their diagnosis or associated surgical intervention. Whilst reassuring, the need for appropriate support mechanisms to maintain positive psychosocial wellbeing and academic achievement in this patient cohort is reinforced.

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. OBJECTIVES: To calculate the incidence of BCC in Wales between 2000 and 2018 and to establish the related healthcare utilization and estimated cost of care. METHODS: The Secure Anonymised Information Linkage (SAIL) databank is one of the largest and most robust health and social care data repositories in the UK. Cancer registry data were linked to routinely collected healthcare databases between 2000 and 2018. Pathological data from Swansea Bay University Health Board (SBUHB) were used for internal validation. RESULTS: A total of 61 404 histologically proven BCCs were identified within the SAIL Databank during the study period. The European age-standardized incidence for BCC in 2018 was 224.6 per 100 000 person-years. Based on validated regional data, a 45% greater incidence was noted within SBUHB pathology vs. matched regions within SAIL between 2016 and 2018. A negative association between deprivation and incidence was noted with a higher incidence in the least socially deprived and rural dwellers. Approximately 2% travelled 25-50 miles for dermatological services compared with 37% for plastic surgery. Estimated NHS costs of surgically managed lesions for 2002-2019 equated to £119.2-164.4 million. CONCLUSIONS: Robust epidemiological data that are internationally comparable and representative are scarce for nonmelanoma skin cancer. The rising global incidence coupled with struggling healthcare systems in the post-COVID-19 recovery period serve to intensify the societal and healthcare impact. This study is the first to demonstrate the incidence of BCC in Wales and is one of a small number in the UK using internally validated large cohort datasets. Furthermore, our findings demonstrate one of the highest published incidences within the UK and Europe.

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. During validation, we deployed our rule-based NLP pipeline on 200 previously unseen, de-identified and pseudonymised basal cell carcinoma (BCC) histopathological reports from Swansea Bay University Health Board, Wales, UK. The results of our algorithm were compared with gold standard human annotation by two independent and blinded expert clinicians involved in skin cancer care. Results: We identified 11,224 items of information with a mean precision, recall, and F1 score of 86.0% (95% CI: 75.1-96.9), 84.2% (95% CI: 72.8-96.1), and 84.5% (95% CI: 73.0-95.1), respectively. The difference between clinician annotator F1 scores was 7.9% in comparison with 15.5% between the NLP pipeline and the gold standard corpus. Cohen's Kappa score on annotated tokens was 0.85. Conclusion: Using an NLP rule-based approach for named entity recognition in BCC, we have been able to develop and validate a pipeline with a potential application in improving the quality of cancer registry data, supporting service planning, and enhancing the quality of routinely collected data for research.

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. This necessitates alternative methods of surgical skills training. To date, there are no standardized or ideal simulation models for local skin flap teaching. Aim: This systematic review aims to summarize and evaluate local skin flap simulation and teaching models published in the literature. Materials and Methods: A systematic review protocol was developed and undertaken in accordance with PRISMA guidelines. Key search terms encompassed both "local skin flaps" and "models" or "surgical simulation". These were combined using Boolean logic and used to search Embase, Medline, and the Cochrane Library. Studies were collected and screened according to the inclusion criteria. The final included articles were graded for their level of evidence and recommendation based on a modified educational Oxford Center for evidence-based medicine classification system and assessed according to the CRe-DEPTH tool for articles describing training interventions in healthcare professionals. Results: A total of 549 articles were identified, resulting in the inclusion of 16 full-text papers. Four articles used 3D simulators for local flap teaching and training, while two articles described computer simulation as an alternative method for local flap practicing. Four models were silicone based, while gelatin, Allevyn dressings, foam rubber, and ethylene-vinyl acetate-based local flap simulators were also described. Animal models such as pigs head, porcine skin, chicken leg, and rat, as well as a training model based on fresh human skin excised from body-contouring procedures, were described. Each simulation and teaching method was assessed by a group of candidates via a questionnaire or evaluation survey grading system. Most of the studies were graded as level of evidence 3 or 4. Conclusion: Many methods of simulation for the design and execution of local skin flaps have been described. However, most of these have been assessed only in small cohort numbers, and, therefore, larger candidate sizes and a standardized method for assessment are required. Moreover, some proposed simulators, although promising, are in a very preliminary stage of development. Further development and evaluation of promising high-fidelity models is required in order to improve training in such a complex area of surgery.