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MelRisk: Using neutrophil-to-lymphocyte ratio to improve risk prediction models for metastatic cutaneous melanoma in the sentinel lymph node
- Source :
- Journal of Plastic, Reconstructive & Aesthetic Surgery. 75:1653-1660
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- Background: Identifying metastatic melanoma in the sentinel lymph node (SLN) is important because 80% of SLN biopsies are negative and 11% of patients develop complications. The neutrophil-to-lymphocyte ratio (NLR), a biomarker of micrometastatic disease, could improve prediction models for SLN status. We externally validated existing models and developed ‘MelRisk’ prognostic score to better predict SLN metastasis. Methods: The models were externally validated using data from a multicenter cohort study of 1,251 adults. Additionally, we developed and internally validated a new prognostic score `MelRisk’, using candidate predictors derived from the extant literature. Results: The Karakousis model had a C-statistic of 0.58 (95% CI, 0.54–0.62). The Sondak model had a C-statistic of 0.57 (95% CI 0.53–0.61). The MIA model had a C-statistic of 0.60 (95% CI. 0.56–0.64). Our ‘MelRisk’ model (which used Breslow thickness, ulceration, age, anatomical site, and the NLR) showed an adjusted C-statistic of 0.63 (95% CI, 0.56–0.64). Conclusion: Our prediction tool is freely available in the Google Play Store and Apple App Store, and we invite colleagues to externally validate its performance.
- Subjects :
- Adult
Oncology
medicine.medical_specialty
Skin Neoplasms
Neutrophils
Sentinel lymph node
Risk prediction models
Metastasis
Cohort Studies
Breslow Thickness
Internal medicine
medicine
Humans
Lymphocytes
Neutrophil to lymphocyte ratio
Melanoma
Sentinel Lymph Node Biopsy
business.industry
Prognosis
medicine.disease
Surgery
Biomarker (medicine)
Lymph Nodes
Sentinel Lymph Node
business
Cohort study
Subjects
Details
- ISSN :
- 17486815
- Volume :
- 75
- Database :
- OpenAIRE
- Journal :
- Journal of Plastic, Reconstructive & Aesthetic Surgery
- Accession number :
- edsair.doi.dedup.....23bcbe21f9d7908c432515416bef26b1