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应对凸性响应:从金融到肿瘤学的反脆弱性

Working with Convex Responses: Antifragility from Finance to Oncology.

作者信息

Taleb Nassim Nicholas, West Jeffrey

机构信息

Tandon School of Engineering, New York University, Brooklyn, NY 11201, USA.

Integrated Mathematical Oncology, Moffitt Cancer Center, Tampa, FL 33612, USA.

出版信息

Entropy (Basel). 2023 Feb 13;25(2):343. doi: 10.3390/e25020343.

Abstract

We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology, where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis for medical problems, through the properties of nonlinear responses (convex or concave). We (1) link the convexity/concavity of the dose-response function to the statistical properties of the results; (2) define "antifragility" as a mathematical property for local beneficial convex responses and the generalization of "fragility" as its opposite, locally concave in the tails of the statistical distribution; (3) propose mathematically tractable relations between dosage, severity of conditions, and iatrogenics. In short, we propose a framework to integrate the necessary consequences of nonlinearities in evidence-based oncology and more general clinical risk management.

摘要

我们将有关非线性反应随机特性的技术和知识从金融领域拓展到医学,尤其是肿瘤学领域,在该领域它可为给药和干预提供依据。我们定义了反脆弱性。我们通过非线性反应(凸性或凹性)的特性,提出将风险分析用于医疗问题。我们(1)将剂量反应函数的凸性/凹性与结果的统计特性联系起来;(2)将“反脆弱性”定义为局部有益凸反应的一种数学特性,并将“脆弱性”推广为其对立面,即在统计分布尾部呈局部凹性;(3)提出剂量、病情严重程度和医源性之间易于数学处理的关系。简而言之,我们提出了一个框架,以整合循证肿瘤学及更一般临床风险管理中非线性的必然结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56a0/9955868/1ace5e1b9fd3/entropy-25-00343-g001.jpg

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