Scholarlink

Background <p>Although PD-1 inhibitors have significantly reduced metastatic melanoma patients’ mortality, only a small proportion of these patients actually benefit. We aim to develop some parsimonious predictive models for identifying those patients’ survival outcome under anti-PD-1 treatment.</p> Method <p>Based on the genomic mutation and copy number variation data of metastatic melanoma patients in the Liu and Shoushtari cohorts, we developed and validated three different nomograms to identify their survival outcomes under anti-PD-1 monotherapy. Patients without anti-PD-1 monotherapy in the TCGA and MSK cohorts were employed as negative controls to assess the applicability of our models to anti-PD-1 monotherapy. All predictive models developed in this study are accessible and available for use at <a href="https://yyw0505.shinyapps.io/nomogram_app/">https://yyw0505.shinyapps.io/nomogram_app/</a>.</p> Result <p>The first nomogram, and also the one we most recommend, built on five genes including NID1 amplification, TYRP1 deletion, mutations of PIK3C2G, FLT1 and IKZF1, classified patients into the High-Risk and Low-Risk group, and patients in the High-Risk group exhibited shorter overall survival (OS) and progression-free survival (PFS). However, there was no difference of OS between the two groups in both the TCGA and MSK cohorts, indicated the first nomogram was a predictive model rather than prognostic model. Similar results were also observed in the second and third nomogram.</p> Conclusion <p>The parsimonious and robust predictive model could provide valuable assistance for clinical practice.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Predicting of survival in metastatic melanoma patients under anti-PD-1 monotherapy using genomic mutation and copy number variation

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月18日

查看全文
  • Yu Wang,
  • Wei Tang,
  • Yuanyuan Wang,
  • Xiaoyu Lu,
  • Ling Zhang,
  • Jiaojiao Yang,
  • Shuibing Yang,
  • Jingjin Yang

摘要

Background

Although PD-1 inhibitors have significantly reduced metastatic melanoma patients’ mortality, only a small proportion of these patients actually benefit. We aim to develop some parsimonious predictive models for identifying those patients’ survival outcome under anti-PD-1 treatment.

Method

Based on the genomic mutation and copy number variation data of metastatic melanoma patients in the Liu and Shoushtari cohorts, we developed and validated three different nomograms to identify their survival outcomes under anti-PD-1 monotherapy. Patients without anti-PD-1 monotherapy in the TCGA and MSK cohorts were employed as negative controls to assess the applicability of our models to anti-PD-1 monotherapy. All predictive models developed in this study are accessible and available for use at https://yyw0505.shinyapps.io/nomogram_app/.

Result

The first nomogram, and also the one we most recommend, built on five genes including NID1 amplification, TYRP1 deletion, mutations of PIK3C2G, FLT1 and IKZF1, classified patients into the High-Risk and Low-Risk group, and patients in the High-Risk group exhibited shorter overall survival (OS) and progression-free survival (PFS). However, there was no difference of OS between the two groups in both the TCGA and MSK cohorts, indicated the first nomogram was a predictive model rather than prognostic model. Similar results were also observed in the second and third nomogram.

Conclusion

The parsimonious and robust predictive model could provide valuable assistance for clinical practice.