Prognosis and prognostic research: what, why, and how?

By Karel G. M. Moons, Patrick Royston, Y. Vergouwe, Diederick E. Grobbee, Douglas G. Altman. British medical journal, 2009

1,324 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Public Health, Environmental and Occupational Health, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/24fc7d5907e21a086c0c855ade11dd390a898918

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Citations in the corpus

PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies (2019, neutral): “A multivariable prediction model is defined as any combination or equation of two or more predictors for estimating the probability or risk for an individual.(7, 8, 33-35)”
The residual‐based predictiveness curve: A visual tool to assess the performance of prediction models (2016, background): “In this respect, Pepe et al. (2008) and Gu and Pepe (2009) have shown that many relevant properties of a marker can be summarized through the predictiveness curve.”
Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research (2013, methodology): “Ideally this produces an estimate of the absolute risk (absolute probability) of experiencing the endpoint, but it may instead provide a relative risk or risk score [3–5].”
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement (2015, neutral): “Furthermore, TRIPOD is also not intended for impact studies that quantify the impact of using a prediction model on participant or doctors’ behavior and management, participant health outcomes, or cost-effectiveness of care, compared with not using the model (Moons et al, 2009a, 2012a).”
Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies: The CHARMS Checklist (2014, background): “For example, relevance to physicians and patients is enhanced by models that predict patient-relevant outcomes, such as death, pain, or recurrence of disease, rather than those that predict process outcomes such as duration of hospital stay or intermediate outcomes, except when there is a clear and ”
External validation of a Cox prognostic model: principles and methods (2013, background): “See Moons et al [2] for a general discussion of prognostic research.”
Effect of Ebola Progression in Liberia (2015, neutral): “In the prognostic setting, predictions can be used for planning lifestyle or therapeutic decisions based on the risk for developing a particular outcome or state of health within a specific period (1, 2).”
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement (2015, neutral): “In the prognostic setting, predictions can be used for planning lifestyle or therapeutic decisions based on the risk for developing a particular outcome or state of health within a specific period (1, 2).”
Prognosis and prognostic research: Developing a prognostic model (2009, background): “The first article in this series reviewed why prognosis is important and how it is practised in different medical settings.”
Risk prediction models: II. External validation, model updating, and impact assessment (2012, background): “QUANTIFYING THE IMPACT OF A PREDICTION MODEL Prediction models are not developed to replace doctors, but to provide objective estimates of health outcome risks for both individuals (patients) and healthcare providers, to assist their subjective interpretations, intuitions and guidelines.(8) 33 34 Ho”