Latest research

On this page we provide links to some of the latest methodology research articles in prognosis and prediction research.

Please contact us about methods articles to add, as we want to be inclusive.

2022

  • Minimum sample size calculations for external validation of a clinical prediction model with a time-to-event outcome (PDF)

  • Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review (PDF)

  • Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review (PDF)

  • GRADE concept paper 2: Concepts for judging certainty on the calibration of prognostic models in a body of validation studies (PDF)

  • Performance of binary prediction models in high-correlation low-dimensional settings: a comparison of methods (PDF)
  • Risk prediction models for discrete ordinal outcomes: Calibration and the impact of the proportional odds assumption (PDF)
  • The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression (PDF)
  • Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review (PDF)
  • Assessing performance and clinical usefulness in prediction models with survival outcomes: practical guidance for Cox proportional hazards models (PDF)
  • Individual-specific networks for prediction modelling–A scoping review of methods (PDF)
  • Accuracy of approximations to recover incompletely reported logistic regression models depended on other available information (PDF)
  • Estimation of the Absolute Risk of Cardiovascular Disease and Other Events: Issues With the Use of Multiple Fine-Gray Subdistribution Hazard Models (PDF)
  • Investigating treatment-effect modification by a continuous covariate in IPD meta-analysis: an approach using fractional polynomials (PDF)

2021

  • Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research (new textbook) - details here

  • Lessons learnt when accounting for competing events in the external validation of time-to-event prognostic models (PDF)

  • To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets (PDF)

  • Developing clinical prediction models when adhering to minimum sample size recommendations: The importance of quantifying bootstrap variability in tuning parameters and predictive performance (PDF)

  • Developing more generalizable prediction models from pooled studies and large clustered data sets (PDF)
  • A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint (PDF)

  • Minimum sample size for external validation of a clinical prediction model with a binary outcome (PDF)

  • Estimation of required sample size for external validation of risk models for binary outcomes (PDF)

  • External validation of clinical prediction models: simulation-based sample size calculations were more reliable ... (PDF)

  • A note on estimating the Cox‐Snell R2 from a reported C statistic (AUROC) to inform sample size calculations for developing a prediction model with a binary outcome (PDF)

  • Clinical prediction models to predict the risk of multiple binary outcomes: a comparison of approaches (PDF)

  • Adaptive sample size determination for the development of clinical prediction models (PDF)

  • Clinical prediction models: diagnosis versus prognosis (PDF)

  • IPD meta‐analysis for external validation, recalibration, and updating of a flexible parametric prognostic model (PDF)

  • Penalization and shrinkage methods produced unreliable clinical prediction models especially when sample size was small  (PDF

  • Sample sizes of prediction model studies in prostate cancer were rarely justified and often insufficient (PDF)

  • A two‐stage prediction model for heterogeneous effects of treatments (PDF)

  • Prediction or causality? A scoping review of their conflation within current observational research (PDF)

  • Fine‐Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: Cumulative total failure probability may exceed 1 (PDF)

  • A scoping review of causal methods enabling predictions under hypothetical interventions (PDF)

  • Impact of sample size on the stability of risk scores from clinical prediction models: a case study in cardiovascular disease (PDF)

2020

  • Minimum sample size for external validation of a clinical prediction model with a continuous outcome (PDF)

  • Calculating the sample size required for developing a clinical prediction model (PDF)

  • Regression shrinkage methods for clinical prediction models do not guarantee improved performance (PDF)

  • IPD meta‐analysis to examine interactions between treatment effect and participant‐level covariates (PDF)

  • Temporal recalibration for improving prognostic model development and risk predictions ... (PDF)

  • Use of GRADE for the assessment of evidence about prognostic factors: rating certainty in identification of groups of patients with different absolute risks (PDF)

  • Meta-analysis of continuous outcomes: using pseudo IPD created from aggregate data to adjust for baseline imbalance and assess treatment-by-baseline modification (PDF)

  • Prediction meets causal inference: the role of treatment in clinical prediction models (PDF)

  • State of the art in selection of variables and functional forms in multivariable analysis—outstanding issues (PDF)