ArticleFrontiers in oncology2021
A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Review
- Development and validation of a novel combinational index of liquid biopsy biomarker for longitudinal lung cancer patient management.The journal of liquid biopsy · 2024Article
- Prognostic nomograms for predicting long-term overall survival in spindle cell melanoma: a population-based study.Frontiers in endocrinology · 2024Article
- Ligand Recognition by the Macrophage Galactose-Type C-Type Lectin: Self or Non-Self?-A Way to Trick the Host's Immune System.International journal of molecular sciences · 2023Review
- Identification of Molecular Subtypes and Prognostic Characteristics of Adrenocortical Carcinoma Based on Unsupervised Clustering.International journal of molecular sciences · 2023Article
- A seven-immune-genes risk model predicts the survival and suitable treatments for patients with skin cutaneous melanoma.Heliyon · 2023Article
- Identification of Pyroptosis-Relevant Signature in Tumor Immune Microenvironment and Prognosis in Skin Cutaneous Melanoma Using Network Analysis.Stem cells international · 2023Article
- Hsa_circRNA_0040462: a sensor of cells' response to CAP treatment with double-edged roles on breast cancer malignancy.International journal of medical sciences · 2022Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCurrently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.
methodsFour hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set. The prognostic gene biomarker was developed and validated based on the above three sets. The developed gene biomarker combined with clinical characteristics was used as variables to develop and validate a nomogram predictive model based on 379 patients with complete clinical data from TCGA (Among 470 cases, 91 cases with missing clinical data were excluded from the study), which were randomly divided into the training set II (n = 189) and validation set II (n = 190). Area under the curve (AUC), concordance index (C-index), calibration curve, and Kaplan-Meier estimate were used to assess predictive performance of the nomogram model.
resultsFour genes, i.e.,
conclusionWe developed and validated a nomogram predictive model combining a four-gene biomarker and six clinical factors for melanoma patients, which could facilitate risk stratification and treatment planning.
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