(Step-Ident-CSCC Study) A stepwise prediction model integrating high-risk clinicopathological characteristics and genomics to identify advanced cutaneous squamous cell carcinoma

Project summary

In collaboration with SkylineDx, the Erasmus MC will develop a novel prediction model that combines high-risk clinical and pathological characteristics with a genetic tumour profile to accurately identify which cutaneous squamous cell carcinoma patients are at high risk of developing metastasis.

In the Netherlands, 14.000 people annually develop a CSCC and the incidence rate is still increasing. Although the prognosis of a CSCC is generally excellent, a subset metastasizes of whom half dies. Due to lack of data, current staging systems are inaccurate to identify which patients are at risk of developing metastasis. Consequently, all CSCC patients receive 5-year intensive follow-up. This causes unnecessary psychological stress among all low-risk patients (95%) and significantly burdens the healthcare system. Furthermore, it is uncertain who would benefit from adjuvant treatment, which would improve CSCC curation rates and lead to preservation of good health. Accurate identification of high-risk CSCC patients is therefore a big research gap with major social, scientific and economic implications.

The StepIdent study aims to fill this gap by developing an exclusive stepwise prediction model that combines true high-risk clinicopathological characteristics with a genetic tumor profile to accurately identify high risk CSCC patients. We have the unique ability to combine large metastatic cohorts of CSCC patients from the United Kingdom with Dutch national linked datasets with access to primary tumour blocks that metastasize.

The prediction model will be developed under ideal circumstances by an all-round, interdisciplinary consortium with a comparable successful collaboration on melanoma and will be the first ever to combine large, robust CSCC data with advanced stepwise methodology.