ArticleThe British journal of dermatology2022
Validation of four cutaneous squamous cell carcinoma staging systems using nationwide data.
Article in The British journal of dermatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 40 citations in OpenAlex.
- Cutaneous Squamous Cell Carcinoma Across the Pre-COVID-19, COVID-19 and Post-COVID-19 Eras: Epidemiology, Risk Stratification, Tumour Aggressiveness, and Clinical Outcomes.Dermatopathology (Basel, Switzerland) · 2026Article
- Comprehensive molecular characterization of cutaneous squamous cell carcinoma reveals determinants of metastatic progression.medRxiv : the preprint server for health sciences · 2026Article
- Clinical Equipoise and Unimproved Outcomes following Posttransplant Cutaneous Squamous Cell Carcinoma.Kidney international reports · 2026Article
- Beyond Binary Positivity: Spectrum of Nodal Tumor Burden in Sentinel Lymph Node Biopsy for High-Risk Cutaneous Squamous Cell Carcinoma.Dermatopathology (Basel, Switzerland) · 2026Article
- Poor Outcome of Metastatic Cutaneous Squamous Cell Carcinoma: A Swedish Retrospective Study.Acta dermato-venereologica · 2026Article
- Performance of Staging Systems for Non-head and Neck Cutaneous Squamous Cell Carcinoma.American journal of clinical dermatology · 2026Article
- Special Issue on Skin Cancers of the Head and Neck.Cancers · 2025Article
- Longitudinal data on advanced cutaneous squamous cell carcinoma from the Dutch Keratinocyte Cancer Collaborative (DKCC): a nationwide real-world database study.The Lancet regional health. Europe · 2025Article
- Enhanced metastasis risk prediction in cutaneous squamous cell carcinoma using deep learning and computational histopathology.NPJ precision oncology · 2025Article
- Prognostication System for Squamous Cell Carcinoma Using Retrieval Augmented Generation-Enabled Large Language Model.JAMA dermatology · 2025Article
- Enhancing Early Detection of Metastatic Cutaneous Squamous Cell Carcinoma (CSCC): Integrating AI With Histopathological Assessments.Experimental dermatology · 2025Article
- Unveiling intratumoral heterogeneity in high-risk cutaneous squamous cell carcinoma using single-cell spatial enhanced resolution omics-sequencing (Stereo-seq).Journal of dermatological science · 2025Article
- Bridging the gap: From clinical intuition to structured cutaneous squamous cell carcinoma classification.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Article
- Operational classification of cutaneous squamous cell carcinomas based on unsupervised clustering of real cases by experts.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Article
- Integrating 40-GEP Testing to Improve Clinical Recommendations for Adjuvant Radiation for Cutaneous Squamous Cell Carcinoma: Multidisciplinary Consensus Guidelines.The Journal of clinical and aesthetic dermatology · 2024Review
- Distinguishing Keratoacanthoma from Well-Differentiated Cutaneous Squamous Cell Carcinoma Using Single-Cell Spatial Pathology.The Journal of investigative dermatology · 2023Article
- Personalised decision making to predict absolute metastatic risk in cutaneous squamous cell carcinoma: development and validation of a clinico-pathological model.EClinicalMedicine · 2023Article
- Driver gene combinations dictate cutaneous squamous cell carcinoma disease continuum progression.Nature communications · 2023Article
- Using Gene Expression Profiling to Personalize Skin Cancer Management.The Journal of clinical and aesthetic dermatology · 2022Review
- Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCutaneous squamous cell carcinoma (cSCC) is the second most common cancer worldwide with relatively low metastatic potential (2-5%). Developments in therapeutic options have highlighted the need to better identify high-risk patients who could benefit from closer surveillance, adjuvant therapies and baseline/follow-up imaging, while at the same time safely omitting low-risk patients from further follow-up. Controversy remains regarding the predictive performance of current cSCC staging systems and which methodology to adopt.
objectivesTo validate the performance of four cSCC staging systems [American Joint Committee on Cancer 8th edition (AJCC8), Brigham and Women's Hospital (BWH), Tübingen and Salamanca T3 refinement] in predicting metastasis using a nationwide cohort.
methodsA nested case-control study using data from the National Disease Registration Service, England, 2013-2015 was conducted. Metastatic cSCC cases were identified using an algorithm to identify all potential cases for manual review. These were 1 : 1 matched on follow-up time to nonmetastatic controls randomly selected from 2013. Staging systems were analysed for distinctiveness, homogeneity, monotonicity, specificity, positive predictive value (PPV), negative predictive value (NPV) and c-index.
resultsWe included 887 metastatic cSCC cases and 887 nonmetastatic cSCC controls. The BWH system showed the highest specificity [92.8%, 95% confidence interval (CI) 90.8-94.3%, PPV (13.2%, 95% CI 10.6-16.2) and c-index (0.84, 95% CI 0.82-0.86). The AJCC8 showed superior NPV (99.2%, 95% CI 99.2-99.3), homogeneity and monotonicity compared with the BWH and Tübingen diameter and thickness classifications (P < 0.001). Salamanca refinement did not show any improvement in AJCC8 T3 cSCC staging.
conclusionsWe validated four cSCC staging systems using the largest nationwide dataset of metastatic cSCC so far. Although the BWH system showed the highest overall discriminative ability, PPV was low for all staging systems, which shows the need for further improvement and refining of current cSCC staging systems.
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