Prognosis and prognostic research: application and impact of prognostic models in clinical practice

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

922 citations recorded by the source corpus.

Subfields: Cardiology and Cardiovascular Medicine, Epidemiology, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/9b1bff6f591356b25f6301344d0729014bb2745f

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In Cardiology and Cardiovascular Medicine

In Epidemiology

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Citations in the corpus

Prediction models for cardiovascular disease risk in the general population: systematic review (2016, positive): “We included all primary articles that reported on one or more multivariable (that is, including at least two predictors 16 ) prediction models, tools, or scores, that have been proposed for individual risk estimation of any future CVD outcome in the general population.”
PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies (2019, neutral): “Round 6 refined the domains and introduced further optional guidance for the use of PROBAST.”
Effect of Ebola Progression in Liberia (2015, positive): “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.(13,38) Reporting guidelines for observat”
A novel clinical risk prediction model for sudden cardiac death in hypertrophic cardiomyopathy (HCM risk-SCD). (2014, methodology): “The aim of this prediction model, like any other prognostic tool, is not to render physicians’ clinical judgment obsolete, but rather to complement clinical reasoning by providing objective individualized prognostic information.(45,46) Guidelines recommend ICD therapy for the primary prevention of S”
External validation of a Cox prognostic model: principles and methods (2013, background): “Arguably, inadequate discrimination is a more important failing than poor calibration, since the latter can be improved by model recalibration [3,12], whereas the former cannot be altered.”
Prognosis and prognostic research: what, why, and how? (2009, background): “and the application and impact of prognostic models in practice.”
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement (2015, positive): “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 (13, 38).”
Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement (2015, positive): “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).”
Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review (2022, methodology): “…of the AIPM, external AIPM model validation can be based on discrimination (area under the receiver operating characteristic curve, sensitivity, speci ﬁ city, positive and negative predictive values), calibration (calibration plot) 5,6,13,17,49,56,78 , and Decision Curve Analysis 5,6,17,49,68,72 .”
Prognosis and prognostic research: Developing a prognostic model (2009, background): “index for a prognostic model is typically between about 0.6 and 0.85 (higher values are seen in diagnostic settings”
Prognosis and prognostic research: validating a prognostic model (2009, background): “Poor performance in new patients can also arise from differences between the setting of patients in the new and derivation samples, including differences in healthcare systems, methods of measurement, and patient characteristics. We consider those issues in the final article in the series.”
Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research (2013, background): “Assessment of the impact of a model on decision making and patient outcome requires a comparative study [9,33].”