Institute of Clinical Physiology (IFC-CNR), Clinical Epidemiology and Physiopathology of Renal Diseases and Hypertension of Reggio Calabria, Ospedali Riuniti, Via Vallone Petrara snc, Reggio Calabria, Italy.
Institute of Clinical Physiology (IFC-CNR), Rome, Italy.
Aging Clin Exp Res. 2021 Feb;33(2):279-283. doi: 10.1007/s40520-020-01542-y. Epub 2020 Apr 2.
Prognosis aims at estimating the future course of a given disease in probabilistic terms. As in diagnosis, where clinicians are interested in knowing the accuracy of a new test to identify patients affected by a given disease, in prognosis they wish to accurately identify patients at risk of a future event conditional to one or more prognostic factors. Thus, accurate risk predictions play a primary role in all fields of clinical medicine and in geriatrics as well because they can help clinicians to tailor the intensity of a treatment and to schedule clinical surveillance according to the risk of the concerned patient. Statistical methods able to evaluate the prognostic accuracy of a risk score demand the assessment of discrimination (the Harrell's C-index), calibration (Hosmer-May test) and risk reclassification abilities (IDI, an index of risk reclassification) of the same risk prediction rule whereas, in spite of the popular belief that traditional statistical techniques providing relative measures of effect (such as the hazard ratio derived by Cox regression analysis or the odds ratio obtained by logistic regression analysis) could be per se enough to assess the prognostic value of a biomarker or of a risk score. In this paper we provide a brief theoretical background of each statistical test and a practical approach to the issue. For didactic purposes, in the paper we also provide a dataset (n = 40) to allow the reader to train in the application of the proposed statistical methods.
预后旨在以概率的方式估计给定疾病的未来病程。与诊断一样，临床医生对了解识别特定疾病患者的新检测的准确性感兴趣，在预后中，他们希望能够根据一个或多个预后因素，准确识别有未来事件风险的患者。因此，准确的风险预测在临床医学和老年医学的所有领域都起着主要作用，因为它们可以帮助临床医生根据患者的风险调整治疗强度并安排临床监测。能够评估风险评分预后准确性的统计方法需要评估区分度（哈雷尔 C 指数）、校准（Hosmer-May 检验）和相同风险预测规则的风险再分类能力（IDI，风险再分类指数），尽管有一个普遍的信念，即提供相对效果度量的传统统计技术（如 Cox 回归分析得出的风险比或 logistic 回归分析得出的优势比）本身就足以评估生物标志物或风险评分的预后价值。本文提供了每个统计检验的简要理论背景和实际应用方法。为了教学目的，本文还提供了一个数据集（n=40），以便读者能够在应用所提出的统计方法方面进行培训。
