Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years

Hu, Wan; Fang, Lanlan; Ni, Ruyu; Zhang, Hengchuan; Pan, Guixia

doi:10.1186/s12885-022-09940-3

Cited by 87 publications

(53 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The incidence of malignant skin tumors, especially cutaneous melanoma (CM), basal cell carcinoma (BCC), and squamous cell carcinoma (SCC), has been alarmingly increasing over the last decades [ 353 ]. Nonmelanoma skin cancers (NMSC), including BCC and SCC, are the most prevalent malignancies affecting light-skinned individuals worldwide and represent almost 95% of all cutaneous cancer diagnoses [ 354 ].…”

Section: Discussionmentioning

confidence: 99%

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Dobre

Surcel

Constantin

et al. 2023

IJMS

View full text Add to dashboard Cite

Early diagnosis is essential for completely eradicating skin cancer and maximizing patients’ clinical benefits. Emerging optical imaging modalities such as reflectance confocal microscopy (RCM), optical coherence tomography (OCT), magnetic resonance imaging (MRI), near-infrared (NIR) bioimaging, positron emission tomography (PET), and their combinations provide non-invasive imaging data that may help in the early detection of cutaneous tumors and surgical planning. Hence, they seem appropriate for observing dynamic processes such as blood flow, immune cell activation, and tumor energy metabolism, which may be relevant for disease evolution. This review discusses the latest technological and methodological advances in imaging techniques that may be applied for skin cancer detection and monitoring. In the first instance, we will describe the principle and prospective clinical applications of the most commonly used imaging techniques, highlighting the challenges and opportunities of their implementation in the clinical setting. We will also highlight how imaging techniques may complement the molecular and histological approaches in sharpening the non-invasive skin characterization, laying the ground for more personalized approaches in skin cancer patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Dobre

Surcel

Constantin

et al. 2023

IJMS

View full text Add to dashboard Cite

show abstract

“…where 𝑤𝑤 𝑖𝑖𝑖𝑖𝑛𝑛 (2) is the weight for processing feature maps of dermatological images 𝐷𝐷 𝑓𝑓 ; 𝑤𝑤 𝑖𝑖𝑛𝑛…”

Section: Multimodal Neural Network System For the Analysis Of Unbalan...mentioning

confidence: 99%

“…To date, skin cancer is the most frequently diagnosed form of oncopathology in humans and represents a wide range of malignancies [1]. More than 40% of the total number of diagnosed cancer cases in the world is skin cancer [2]. The sharp increase in the incidence of skin cancer is explained by chronic exposure to ultraviolet radiation (UV) [3] and Disclaimer/Publisher's Note: The statements, opinions, and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s).…”

Section: Introductionmentioning

confidence: 99%

“…The heterogeneous group of NMSCs has a single code (C44) to cover all types of non-melanoma cancers [18]. Therefore, separate data on basal cell carcinoma, squamous cell carcinoma, and other skin malignancies are not available [19], making it difficult to count and accurately assess individual diagnoses of NMSC [2]. Thus, there is a need to develop balanced auxiliary diagnostic tools aimed at identifying various non-melanoma and melanoma types of malignant skin lesions, including basal cell carcinoma, squamous cell carcinoma, and others.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multimodal Neural Network System for Skin Cancer Recognition with a Modified Cross-Entropy Loss Function

Lyakhov¹,

Lyakhova²,

Kalita³

2023

Preprint

View full text Add to dashboard Cite

Currently, skin cancer is the most commonly diagnosed form of cancer in humans and is one of the leading causes of death in patients with cancer. Biopsy methods are an invasive research method and are not always available for primary diagnosis. Imaging methods have low accuracy and depend on the experience of the dermatologist. Artificial intelligence technologies can match and surpass visual analysis methods in accuracy, but they have the risk of a false negative response when a malignant pigmented lesion can be recognized as benign. One possible way to improve accuracy and reduce the risk of false negatives is to analyze heterogeneous data, combine different preprocessing methods, and use modified loss functions to eliminate the negative impact of unbalanced dermatological data. The paper proposes a multimodal neural network system with a modified cross-entropy loss function that is sensitive to unbalanced heterogeneous dermatological data. The accuracy of recognition in 10 diagnostically significant categories for the proposed system was 85.19%. The novelty of the proposed system lies in the use of cross-entropy loss when training the modified function with the help of weight coefficients. The introduction of weighting factors has reduced the number of false negative forecasts, as well as improved accuracy by 1.02-4.03 percentage points compared to the original multimodal systems. The introduction of the proposed multimodal system as an auxiliary diagnostic tool can reduce the consumption of financial and labor resources involved in the medical industry, as well as increase the chance of early detection of skin cancer.

show abstract

“…Nonmelanoma skin cancer (NMSC) is the most common malignancy in people with fair skin, including basal cell carcinoma, squamous cell carcinoma, and other rarer skin tumors [2]. The incidence of NMSC is increasing globally with the aging population [14]. According to the World Health Organization, approximately 2 to 3 million NMSC occur worldwide every year recently [21].…”

Section: Introductionmentioning

confidence: 99%

Association of blood cadmium level with nonmelanoma skin cancer: a cross-sectional study

Chen

Feng

Wang

2022

Preprint

View full text Add to dashboard Cite

Purpose Cadmium is widely used in industries and found in cigarette smoke. While animal studies have shown some potential effects of cadmium exposure on the skin, little has been known about the role of chronic cadmium exposure on the development of nonmelanoma skin cancer (NMSC). We conducted this study to examine whether blood cadmium was related to the risk of NMSC. Methods An analysis of cross-sectional data from the National Health and Nutrition Examination Survey from 1999–2000 to 2017–2018 was conducted. NMSC was ascertained based on self-reported physician diagnoses. Taking the cadmium level as either a continuous variable or a quartile variable, we examined the association between the blood cadmium level and the odds of NMSC with a multivariable logistic regression model. Restricted cubic splines (RCS) were added to the regression model the estimate the non-linear relationship between cadmium and NMSC. Results A total of 41577 participants were included, of which 952 were reported to have NMSC and 40625 did not have any caners. Cadmium was not associated with NMSC when it was taken as a continuous or quartile variable. RCS showed an inverted U-shaped curve between the blood cadmium level and the odds of NMSC. The result remained similar when limiting the participants to non-Hispanic White. Conclusions Blood cadmium level was associated with the risk of NMSC. Further studies are needed to explore the causality and underlying mechanisms.

show abstract

Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years

Cited by 87 publications

References 61 publications

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Skin Cancer Pathobiology at a Glance: A Focus on Imaging Techniques and Their Potential for Improved Diagnosis and Surveillance in Clinical Cohorts

Multimodal Neural Network System for Skin Cancer Recognition with a Modified Cross-Entropy Loss Function

Association of blood cadmium level with nonmelanoma skin cancer: a cross-sectional study

Contact Info

Product

Resources

About