External validation of prognostic models: what, why, how, when and where?
Prognostic models that aim to improve the prediction of clinical events, individualized
treatment and decision-making are increasingly being developed and published. However …
treatment and decision-making are increasingly being developed and published. However …
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Objectives The objective of this study was to compare performance of logistic regression
(LR) with machine learning (ML) for clinical prediction modeling in the literature. Study …
(LR) with machine learning (ML) for clinical prediction modeling in the literature. Study …
There is no such thing as a validated prediction model
Background Clinical prediction models should be validated before implementation in clinical
practice. But is favorable performance at internal validation or one external validation …
practice. But is favorable performance at internal validation or one external validation …
Calculating the sample size required for developing a clinical prediction model
Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or
prognosis in healthcare. Hundreds of prediction models are published in the medical …
prognosis in healthcare. Hundreds of prediction models are published in the medical …
The diagnosis of bronchopulmonary dysplasia in very preterm infants. An evidence-based approach
EA Jensen, K Dysart, MG Gantz… - American journal of …, 2019 - atsjournals.org
Rationale: Current diagnostic criteria for bronchopulmonary dysplasia rely heavily on the
level and duration of oxygen therapy, do not reflect contemporary neonatal care, and do not …
level and duration of oxygen therapy, do not reflect contemporary neonatal care, and do not …
PROBAST: a tool to assess risk of bias and applicability of prediction model studies: explanation and elaboration
KGM Moons, RF Wolff, RD Riley, PF Whiting… - Annals of internal …, 2019 - acpjournals.org
Prediction models in health care use predictors to estimate for an individual the probability
that a condition or disease is already present (diagnostic model) or will occur in the future …
that a condition or disease is already present (diagnostic model) or will occur in the future …
A simple, evidence-based approach to help guide diagnosis of heart failure with preserved ejection fraction
Background: Diagnosis of heart failure with preserved ejection fraction (HFpEF) is
challenging in euvolemic patients with dyspnea, and no evidence-based criteria are …
challenging in euvolemic patients with dyspnea, and no evidence-based criteria are …
Hyperprogressors after immunotherapy: analysis of genomic alterations associated with accelerated growth rate
S Kato, A Goodman, V Walavalkar, DA Barkauskas… - Clinical Cancer …, 2017 - AACR
Purpose: Checkpoint inhibitors demonstrate salutary anticancer effects, including long-term
remissions. PD-L1 expression/amplification, high mutational burden, and mismatch repair …
remissions. PD-L1 expression/amplification, high mutational burden, and mismatch repair …
Early warning scores for detecting deterioration in adult hospital patients: systematic review and critical appraisal of methodology
Objective To provide an overview and critical appraisal of early warning scores for adult
hospital patients. Design Systematic review. Data sources Medline, CINAHL, PsycInfo, and …
hospital patients. Design Systematic review. Data sources Medline, CINAHL, PsycInfo, and …
The importance of being external. methodological insights for the external validation of machine learning models in medicine
Abstract Background and Objective Medical machine learning (ML) models tend to perform
better on data from the same cohort than on new data, often due to overfitting, or co-variate …
better on data from the same cohort than on new data, often due to overfitting, or co-variate …