SKCMhrp

SKCMhrp predicts high-risk status in skin cutaneous melanoma (SKCM) patients using HLA-superalleles and clinical characteristics to forecast overall survival.

Key Features:

• HLA-superallele–based prediction: Uses HLA-superalleles to associate specific HLA alleles with patient survival outcomes.
• Integration of clinical characteristics: Combines five clinical characteristics with genetic markers for risk assessment.
• Dataset used: Prediction models were developed using data from 415 SKCM patients.
• Survival analysis: Employs survival analysis to differentiate high-risk and low-risk SKCM patients based on overall survival.
• Statistical analysis and effect sizes: Reports hazard ratios (e.g., HR=0.15 for HLA-B*55) and p-values to quantify associations.
• Identified prognostic HLA superalleles: Highlights specific alleles associated with improved survival (HLA-B*55, HLA-A*01) and poorer survival (HLA-B*50, HLA-DRB1*12).
• Combined-marker model: Integrates 14 identified HLA-superalleles with five clinical characteristics to predict high-risk patients (reported HR=4.52, p-value = 8.01E-15).

Scientific Applications:

• Risk stratification: Stratifies SKCM patients into high-risk and low-risk groups for overall survival prediction.
• Prognostic marker identification: Identifies HLA-superalleles that correlate with favorable or unfavorable survival outcomes.
• Evidence-based survival prediction: Provides quantitative survival risk estimates using hazard ratios and p-values derived from SKCM datasets.

Methodology:

Statistical and survival analyses were performed on SKCM datasets from 415 patients; prediction models were developed using HLA-alleles and five clinical characteristics, with hazard ratios and p-values calculated to assess associations and combine 14 identified HLA-superalleles into a risk model.