Search

Background: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting., Objectives: To investigate the perspectives of patients and dermatologists after skin cancer screening by human, artificial and augmented intelligence., Methods: A prospective comparative cohort study conducted at the University Hospital Basel included 205 patients (at high-risk of developing melanoma, with resected or advanced disease) and 8 dermatologists. Patients underwent skin cancer screening by a dermatologist with subsequent 2D and 3D total-body photography (TBP). Any suspicious and all melanocytic skin lesions ≥3 mm were imaged with digital dermoscopes and classified by corresponding convolutional neural networks (CNNs). Excisions were performed based on dermatologist's melanoma suspicion, study-defined elevated CNN risk-scores and/or melanoma suspicion by AuI. Subsequently, all patients and dermatologists were surveyed about their experience using questionnaires, including quantification of patient's safety sense following different examinations (subjective safety score (SSS): 0-10)., Results: Most patients believed AI could improve diagnostic performance (95.5%, n = 192/201). In total, 83.4% preferred AuI-based skin cancer screening compared to examination by AI or dermatologist alone (3D-TBP: 61.3%; 2D-TBP: 22.1%, n = 199). Regarding SSS, AuI induced a significantly higher feeling of safety than AI (mean-SSS (mSSS): 9.5 vs. 7.7, p < 0.0001) or dermatologist screening alone (mSSS: 9.5 vs. 9.1, p = 0.001). Most dermatologists expressed high trust in AI examination results (3D-TBP: 90.2%; 2D-TBP: 96.1%, n = 205). In 68.3% of the examinations, dermatologists felt that diagnostic accuracy improved through additional AI-assessment (n = 140/205). Especially beginners (<2 years' dermoscopic experience; 61.8%, n = 94/152) felt AI facilitated their clinical work compared to experts (>5 years' dermoscopic experience; 20.9%, n = 9/43). Contrarily, in divergent risk assessments, only 1.5% of dermatologists trusted a benign CNN-classification more than personal malignancy suspicion (n = 3/205)., Conclusions: While patients already prefer AuI with 3D-TBP for melanoma recognition, dermatologists continue to rely largely on their own decision-making despite high confidence in AI-results., Trial Registration: ClinicalTrials.gov (NCT04605822)., (© 2024 European Academy of Dermatology and Venereology.)

Importance: The COVID-19 pandemic resulted in delayed access to medical care. Restrictions to health care specialists, staff shortages, and fear of SARS-CoV-2 infection led to interruptions in routine care, such as early melanoma detection; however, premature mortality and economic burden associated with this postponement have not been studied yet., Objective: To determine the premature mortality and economic costs associated with suspended melanoma screenings during COVID-19 pandemic lockdowns by estimating the total burden of delayed melanoma diagnoses for Europe., Design, Setting, and Participants: This multicenter economic evaluation used population-based data from patients aged at least 18 years with invasive primary cutaneous melanomas stages I to IV according to the American Joint Committee on Cancer (AJCC) seventh and eighth editions, including melanomas of unknown primary (T0). Data were collected from January 2017 to December 2021 in Switzerland and from January 2019 to December 2021 in Hungary. Data were used to develop an estimation of melanoma upstaging rates in AJCC stages, which was verified with peripandemic data. Years of life lost (YLL) were calculated and were, together with cost data, used for financial estimations. The total financial burden was assessed through direct and indirect treatment costs. Models were building using data from 50 072 patients aged 18 years and older with invasive primary cutaneous melanomas stages I to IV according to the AJCC seventh and eighth edition, including melanomas of unknown primary (T0) from 2 European tertiary centers. Data from European cancer registries included patient-based direct and indirect cost data, country-level economic indicators, melanoma incidence, and population rates per country. Data were analyzed from July 2021 to September 2022., Exposure: COVID-19 lockdown-related delay of melanoma detection and consecutive public health and economic burden. As lockdown restrictions varied by country, lockdown scenario was defined as elimination of routine medical examinations and severely restricted access to follow-up examinations for at least 4 weeks., Main Outcomes and Measures: Primary outcomes were the total burden of a delay in melanoma diagnosis during COVID-19 lockdown periods, measured using the direct (in US$) and indirect (calculated as YLL plus years lost due to disability [YLD] and disability-adjusted life-years [DALYs]) costs for Europe. Secondary outcomes included estimation of upstaging rate, estimated YLD, YLL, and DALY for each European country, absolute direct and indirect treatment costs per European country, proportion of the relative direct and indirect treatment costs for the countries, and European health expenditure., Results: There were an estimated 111 464 (range, 52 454-295 051) YLL due to pandemic-associated delay in melanoma diagnosis in Europe, and estimated total additional costs were $7.65 (range, $3.60 to $20.25) billion. Indirect treatment costs were the main cost driver, accounting for 94.5% of total costs. Estimates for YLD in Europe resulted in 15 360 years for the 17% upstaging model, ranging from 7228 years (8% upstaging model) to 40 660 years (45% upstaging model). Together, YLL and YLD constitute the overall disease burden, ranging from 59 682 DALYs (8% upstaging model) to 335 711 DALYs (45% upstaging model), with 126 824 DALYs for the real-world 17% scenario., Conclusions and Relevance: This economic analysis emphasizes the importance of continuing secondary skin cancer prevention measures during pandemics. Beyond the personal outcomes of a delayed melanoma diagnosis, the additional economic and public health consequences are underscored, emphasizing the need to include indirect economic costs in future decision-making processes. These estimates on DALYs and the associated financial losses complement previous studies highlighting the cost-effectiveness of screening for melanoma.

Background: Convolutional neural networks (CNNs) have outperformed dermatologists in classifying pigmented skin lesions under artificial conditions. We investigated, for the first time, the performance of three-dimensional (3D) and two-dimensional (2D) CNNs and dermatologists in the early detection of melanoma in a real-world setting., Methods: In this prospective study, 1690 melanocytic lesions in 143 patients with high-risk criteria for melanoma were evaluated by dermatologists, 2D-FotoFinder-ATBM and 3D-Vectra WB360 total body photography (TBP). Excision was based on the dermatologists' dichotomous decision, an elevated CNN risk score (study-specific malignancy cut-off: FotoFinder >0.5, Vectra >5.0) and/or the second dermatologist's assessment with CNN support. The diagnostic accuracy of the 2D and 3D CNN classification was compared with that of the dermatologists and the augmented intelligence based on histopathology and dermatologists' assessment. Secondary end-points included reproducibility of risk scores and naevus counts per patient by medical staff (gold standard) compared to automated 3D and 2D TBP CNN counts., Results: The sensitivity, specificity, and receiver operating characteristics area under the curve (ROC-AUC) for risk-score-assessments compared to histopathology of 3D-CNN with 95% confidence intervals (CI) were 90.0%, 64.6% and 0.92 (CI 0.85-1.00), respectively. While dermatologists and augmented intelligence achieved the same sensitivity (90%) and comparable classification ROC-AUC (0.91 [CI 0.80-1.00], 0.88 [CI 0.77-1.00]) with 3D-CNN, their specificity was superior (92.3% and 86.2%, respectively). The 2D-CNN (sensitivity: 70%, specificity: 40%, ROC-AUC: 0.68 [CI 0.46-0.90]) was outperformed by 3D CNN and dermatologists. The 3D-CNN showed a higher correlation coefficient for repeated measurements of 246 lesions (R = 0.89) than the 2D-CNN (R = 0.79). The mean naevus count per patient varied significantly (gold standard: 210 lesions; 3D-CNN: 469; 2D-CNN: 1324; p < 0.0001)., Conclusions: Our study emphasises the importance of validating the classification of CNNs in real life. The novel 3D-CNN device outperformed the 2D-CNN and achieved comparable sensitivity with dermatologists. The low specificity of CNNs and the lack of automated counting of TBP nevi currently limit the use of augmented intelligence in clinical practice., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: SEC has no conflict of interest. PC has no conflict of interest. LK has received speaking fees for a presentation sponsored by Boehringer Ingelheim. SH has no conflict of interest. MK has received speaking fees from Almirall and Sanofi outside of the current work. J-TM has served as advisor and/or received speaking fees and/or participated in clinical trials sponsored by AbbVie, Almirall, Amgen, BMS, Celgene, Eli Lilly, LEO Pharma, Janssen-Cilag, MSD, Novartis, Pfizer, Pierre Fabre, Roche, Sanofi, UCB. JSB has no conflict of interest. CFD has no conflict of interest. AG has no conflict of interest. CJ has no conflict of interest. LMS has no conflict of interest. JKP has no conflict of interest. ML has received research funding unrelated to the manuscript from Roche, Novartis, Molecular Partners, and Oncobit. AAN declares being a consultant and advisor and/or receiving speaking fees and/or grants and/or served as an investigator in clinical trials for AbbVie, Almirall, Amgen, Biomed, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Galderma, GSK, LEO Pharma, Janssen-Cilag, MSD, Novartis, Pfizer, Pierre Fabre Pharma, Regeneron, Sandoz, Sanofi, and UCB. LVM has served as advisor and/or received speaking fees and/or participated in clinical trials sponsored by Almirall, Amgen, Eli Lilly, MSD, Novartis, Pierre Fabre, Roche, and Sanofi outside of the current work., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: The worldwide incidence of melanoma has been increasing rapidly in recent decades with Switzerland having one of the highest rates in Europe. Ultraviolet (UV) radiation is one of the main risk factors for skin cancer. Our objective was to investigate UV protective behavior and melanoma awareness in a high-risk cohort for melanoma. Methods: In this prospective monocentric study, we assessed general melanoma awareness and UV protection habits in at-risk patients (≥100 nevi, ≥5 dysplastic nevi, known CDKN2A mutation, and/or positive family history) and melanoma patients using questionnaires. Results: Between 01/2021 and 03/ 2022, a total of 269 patients (53.5% at-risk patients, 46.5% melanoma patients) were included. We observed a significant trend toward using a higher sun protection factor (SPF) in melanoma patients compared with at-risk patients (SPF 50+: 48% [n=60] vs. 26% [n=37]; p=0.0016). Those with a college or university degree used a high SPF significantly more often than patients with lower education levels (p=0.0007).However, higher educational levels correlated with increased annual sun exposure (p=0.041). Neither a positive family history for melanoma, nor gender or Fitzpatrick skin type influenced sun protection behavior. An age of ≥ 50 years presented as a significant risk factor for melanoma development with an odd’s ratio of 2.32. Study participation resulted in improved sun protection behavior with 51% reporting more frequent sunscreen use after study inclusion. Discussion: UV protection remains a critical factor in melanoma prevention. We suggest that melanoma awareness should continue to be raised through public skin cancer prevention campaigns with a particular focus on individuals with low levels of education. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we thoroughly explore the clinical and biological features of immunotherapy-induced vitiligo-like depigmentation (VLD) in patients with stage III-IV melanoma receiving immunotherapy. Key findings include a distinct immune signature with an upregulation of ITGA in the VLD group, an upregulation of EDAR and downregulation of LAG3 in VLD-responders group, a longer time to VLD onset in patients pre-treated with targeted therapy, the distribution of VLD lesions primarily in sun-exposed areas as opposed to mechanically stressed areas in non-immunotherapy-related vitiligo, the predominance of a symmetrical, small-freckle lesional pattern and a prolonged progression-free survival (PFS) and overall survival (OS) in VLD patients without LDH elevation as opposed to those with LDH elevation. Vitiligo-like depigmentation (VLD) is an immune-related adverse event (irAE) of checkpoint-inhibitor (CPI) treatment, which has previously been associated with a favourable outcome. The aim of this study was to explore clinical, biological and prognostic features of melanoma patients with VLD under CPI-treatment and to explore whether they exhibit a characteristic immune response profile in peripheral blood. Melanoma patients developing VLD under CPI were included in a prospective observational single-center cohort study. We collected and analysed clinical parameters, photographs and serum from 28 VLD patients. They received pembrolizumab (36%), nivolumab (11%), ipilimumab/nivolumab (32%) or clinical trial medications (21%). We performed a high-throughput proteomics assay (Olink), in which we identified a distinct proteomic signature in VLD patients in comparison to non-VLD CPI patients. Our clinical assessments revealed that VLD lesions had a predominantly symmetrical distribution pattern, with mostly smaller "freckle-like" macules and a preferential distribution in UV-exposed areas. Patients with previous targeted therapy showed a significantly longer time lapse between CPI initiation and VLD onset compared to non-pre-treated patients (12.5 vs. 6.25 months). Therapy responders exhibited a distinct proteomic profile when compared with non-responders in VLD such as upregulation of EDAR and downregulation of LAG3. ITGA11 was elevated in the VLD-group when compared to non-VLD-CPI-treated melanoma patients. Our findings demonstrate that on a proteomic level, VLD is characterized by a distinct immune signature when compared to CPI-treated patients without VLD and that therapy responsiveness is reflected by a characteristic immune profile. The pathomechanisms underlying these findings and how they could relate to the antitumoral response in melanoma remain to be elucidated. [ABSTRACT FROM AUTHOR]

Lung nodules are frequent findings in chest computed tomography (CT) in patients with metastatic melanoma. In this study, we assessed the frequency and compared morphologic differences of metastases and benign nodules. We retrospectively evaluated 85 patients with melanoma (AJCC stage III or IV). Inclusion criteria were ≤20 lung nodules and follow-up using CT ≥183 days after baseline. Lung nodules were evaluated for size and morphology. Nodules with significant growth, nodule regression in line with RECIST assessment or histologic confirmation were judged to be metastases. A total of 438 lung nodules were evaluated, of which 68% were metastases. At least one metastasis was found in 78% of patients. A 10 mm diameter cut-off (used for RECIST) showed a specificity of 95% and a sensitivity of 20% for diagnosing metastases. Central location (n = 122) was more common in metastatic nodules (p = 0.009). Subsolid morphology (n = 53) was more frequent (p < 0.001), and calcifications (n = 13) were solely found in non-metastatic lung nodules (p < 0.001). Our data show that lung nodules are prevalent in about two-thirds of melanoma patients (AJCC stage III/IV) and the majority are metastases. Even though we found a few morphologic indicators for metastatic or non-metastatic lung nodules, morphology has limited value to predict the presence of lung metastases. [ABSTRACT FROM AUTHOR]