TY - JOUR
T1 - The Dutch Early-Stage Melanoma (D-ESMEL) study
T2 - a discovery set and validation cohort to predict the absolute risk of distant metastases in stage I/II cutaneous melanoma
AU - Zhou, Catherine
AU - Mooyaart, Antien L.
AU - Kerkour, Thamila
AU - Louwman, Marieke W.J.
AU - Wakkee, Marlies
AU - Li, Yunlei
AU - Voorham, Quirinus J.M.
AU - Bruggink, Annette
AU - Nijsten, Tamar E.C.
AU - Hollestein, Loes M.
N1 - Publisher Copyright:
© The Author(s) 2025.
PY - 2025/1/9
Y1 - 2025/1/9
N2 - Early-stage cutaneous melanoma patients generally have a favorable prognosis, yet a significant proportion of metastatic melanoma cases arise from this group, highlighting the need for improved risk stratification using novel prognostic biomarkers. The Dutch Early-Stage Melanoma (D-ESMEL) study introduces a robust, population-based methodology to develop an absolute risk prediction model for stage I/II melanoma, incorporating clinical, imaging, and multi-omics data to identify patients at increased risk for distant metastases. Utilizing the Netherlands Cancer Registry and Dutch Nationwide Pathology Databank, we collected primary tumor samples from early-stage melanoma patients, with and without distant metastases during follow-up. Our study design includes a discovery set of metastatic cases and matched controls to identify novel prognostic factors, followed by a validation cohort using a nested case–control design to validate these factors and to build a risk prediction model. Tissue sections underwent Hematoxylin & Eosin (H&E) staining, RNA sequencing (RNAseq), DNA sequencing (DNAseq), immunohistochemistry (IHC), and multiplex immunofluorescence (MxIF).The discovery set included 442 primary melanoma samples (221 case–control sets), with 46% stage I and 54% stage II melanomas. The median time to distant metastasis was 3.4 years, while controls had a median follow-up time of 9.8 years. The validation cohort included 154 cases and 154 controls from a random population-based selection of 5,815 patients. Our approach enabled the collection of a large number of early-stage melanoma samples from population-based databases with extensive follow-up and a sufficient number of metastatic events. This methodology in prognostic cancer research holds the potential to impact clinical decision-making through absolute risk prediction.
AB - Early-stage cutaneous melanoma patients generally have a favorable prognosis, yet a significant proportion of metastatic melanoma cases arise from this group, highlighting the need for improved risk stratification using novel prognostic biomarkers. The Dutch Early-Stage Melanoma (D-ESMEL) study introduces a robust, population-based methodology to develop an absolute risk prediction model for stage I/II melanoma, incorporating clinical, imaging, and multi-omics data to identify patients at increased risk for distant metastases. Utilizing the Netherlands Cancer Registry and Dutch Nationwide Pathology Databank, we collected primary tumor samples from early-stage melanoma patients, with and without distant metastases during follow-up. Our study design includes a discovery set of metastatic cases and matched controls to identify novel prognostic factors, followed by a validation cohort using a nested case–control design to validate these factors and to build a risk prediction model. Tissue sections underwent Hematoxylin & Eosin (H&E) staining, RNA sequencing (RNAseq), DNA sequencing (DNAseq), immunohistochemistry (IHC), and multiplex immunofluorescence (MxIF).The discovery set included 442 primary melanoma samples (221 case–control sets), with 46% stage I and 54% stage II melanomas. The median time to distant metastasis was 3.4 years, while controls had a median follow-up time of 9.8 years. The validation cohort included 154 cases and 154 controls from a random population-based selection of 5,815 patients. Our approach enabled the collection of a large number of early-stage melanoma samples from population-based databases with extensive follow-up and a sufficient number of metastatic events. This methodology in prognostic cancer research holds the potential to impact clinical decision-making through absolute risk prediction.
UR - http://www.scopus.com/inward/record.url?scp=85217398297&partnerID=8YFLogxK
U2 - 10.1007/s10654-024-01188-4
DO - 10.1007/s10654-024-01188-4
M3 - Article
C2 - 39786688
AN - SCOPUS:85217398297
SN - 0393-2990
VL - 40
SP - 27
EP - 42
JO - European Journal of Epidemiology
JF - European Journal of Epidemiology
M1 - e2245269
ER -