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The Dutch cutaneous squamous cell carcinoma and metastasis (D-SQUAME) study: a nationwide discovery cohort and nationwide validation cohort with nested case-control designs for risk prediction modeling

  • Dept Res & Dev

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Abstract

Current clinical risk stratification systems are limited in their predictive value for metastasis in cutaneous squamous cell carcinoma (CSCC). Progress requires large population-based datasets integrating clinical, pathological, and molecular data and efficient study design, because the volume of patients is large and the event rate is low. This study describes two nationwide cohorts and the collection of CSCC samples with long-term follow-up and sufficient metastatic events to enable prognostic modelling. Linked data of the Netherlands Cancer Registry and the Dutch Nationwide Pathology Databank were used to collect two nationwide CSCC cohorts and perform nested case–control studies. In the discovery cohort (first CSCC diagnosis: 2007–2009), each metastatic case was matched to a non-metastatic control with similar metastatic risk. In the validation cohort (first CSCC diagnosis: 2017–2018), each case was matched to both a random and a risk-matched control. Tissue sections were prepared for hematoxylin and eosin staining, RNA/DNA sequencing, and immunostaining. The discovery cohort included 19,120 CSCC patients with ten years of follow-up and 472 samples (236 case–control sets) with a median time to metastasis of 1.1 (IQR 0.5–2.1) years. The validation cohort included 25,921 CSCC patients with at least five years of follow-up and 555 samples (~ 185 sets with 2 types of controls, with a median time to metastasis of 0.70 (0.3–1.5) years. This design enables the development of absolute risk prognostic models with sufficient number of events. Clinical, histopathological, and molecular data can be combined, paving the way towards more personalized treatments for CSCC patients.

Original languageEnglish
Number of pages16
JournalEuropean Journal of Epidemiology
Early online date12 Mar 2026
DOIs
Publication statusE-pub ahead of print - 12 Mar 2026

Bibliographical note

Publisher Copyright:
© The Author(s) 2026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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