Yao Yi, Wang Dapeng, Zheng Li, Zhao Jinmin, Tan Manli
Guangxi Engineering Center in Biomedical Materials for Tissue and Organ Regeneration, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, The First Affiliated Hospital of Guangxi Medical University, Guangxi Medical University, Nanning, 530021, China.
Heliyon. 2024 Mar 26;10(7):e28493. doi: 10.1016/j.heliyon.2024.e28493. eCollection 2024 Apr 15.
The risk prognosis model is a statistical model that uses a set of features to predict whether an individual will develop a specific disease or clinical outcome. It can be used in clinical practice to stratify disease severity and assess risk or prognosis. With the advancement of large-scale second-generation sequencing technology, along Prognosis models for osteosarcoma are increasingly being developed as large-scale second-generation sequencing technology advances and clinical and biological data becomes more abundant. This expansion greatly increases the number of prognostic models and candidate genes suitable for clinical use. This article will present the predictive effects and reliability of various prognosis models, serving as a reference for their evaluation and application.
风险预后模型是一种统计模型，它使用一组特征来预测个体是否会发生特定疾病或临床结局。它可用于临床实践中对疾病严重程度进行分层，并评估风险或预后。随着大规模第二代测序技术的进步，随着大规模第二代测序技术的发展以及临床和生物学数据变得更加丰富，骨肉瘤的预后模型越来越多地被开发出来。这种扩展极大地增加了适用于临床的预后模型和候选基因的数量。本文将介绍各种预后模型的预测效果和可靠性，为其评估和应用提供参考。
