All Stories

  1. Filgotinib in Moderate to Severe Rheumatoid Arthritis in a Real-World Setting: Up to 6-Month Effectiveness, Patient-Reported Outcomes, and Persistence, and up to 24-Month Safety from More than 1400 Patients in the FILOSOPHY and PARROTFISH Studies
  2. Risk prediction models for cancer therapy related cardiac dysfunction in patients with cancer and cancer survivors: systematic review and meta-analysis
  3. Deriving calibration plots in large clustered datasets
  4. Applying the Principal Stratum Strategy in Equivalence Trials: A Case Study
  5. Adverse fetal and perinatal outcomes associated with Zika virus infection during pregnancy: an individual participant data meta-analysis
  6. The best match: selecting the optimal treatment for depressed individuals.
  7. Measuring the Performance of Survival Models to Personalize Treatment Choices
  8. Developing clinical prediction models: a step-by-step guide
  9. The use of imputation in clinical decision support systems: a cardiovascular risk management pilot vignette study among clinicians
  10. Evaluating individualized treatment effect predictions: A model‐based perspective on discrimination and calibration assessment
  11. Challenges in the Assessment of a Disease Model in the NICE Single Technology Appraisal of Tirzepatide for Treating Type 2 Diabetes: An External Assessment Group Perspective
  12. Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines
  13. Visualizing the target estimand in comparative effectiveness studies with multiple treatments
  14. Evaluation of clinical prediction models (part 3): calculating the sample size required for an external validation study
  15. Network meta-analysis of MS DMTs: In response to “Comparative efficacy and safety of disease-modifying therapies in patients with relapsing multiple sclerosis: A systematic review and network meta-analysis” by Chen et al.
  16. Risk of bias assessments in individual participant data meta-analyses of test accuracy and prediction models: a review shows improvements are needed
  17. The potential benefit of statin prescription based on prediction of treatment responsiveness in older individuals: an application to the PROSPER randomized controlled trial
  18. Multiple imputation of incomplete multilevel data using Heckman selection models
  19. Cord clamping at preterm birth
  20. Umbilical cord clamping at preterm birth
  21. Developing a multivariable prediction model to support personalized selection among five major empirically-supported treatments for adult depression. Study protocol of a systematic review and individual participant data network meta-analysis.
  22. Confounder Adjustment Using the Disease Risk Score: A Proposal for Weighting Methods
  23. Regularized parametric survival modeling to improve risk prediction models
  24. Application of Causal Inference Methods to Pooled Longitudinal Non- Randomized Studies: A Methodological Systematic Review
  25. Handling related publications reporting real-world evidence in network meta-analysis: a case study in multiple sclerosis
  26. Propensity‐based standardization to enhance the validation and interpretation of prediction model discrimination for a target population
  27. Methods for comparative effectiveness based on time to confirmed disability progression with irregular observations in multiple sclerosis
  28. Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)
  29. Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis
  30. Transparent reporting of multivariable prediction models developed or validated using clustered data (TRIPOD-Cluster): explanation and elaboration
  31. Transparent reporting of multivariable prediction models developed or validated using clustered data: TRIPOD-Cluster checklist
  32. Implementing clinical trial data sharing requires training a new generation of biomedical researchers
  33. Measuring the performance of prediction models to personalize treatment choice
  34. Dealing with missing data using the Heckman selection model: methods primer for epidemiologists
  35. Reducing antibiotic use in uncomplicated urinary tract infections in adult women: a systematic review and individual participant data meta-analysis
  36. Adjusting for misclassification of an exposure in an individual participant data meta‐analysis
  37. Development and validation of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis
  38. Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis
  39. Personalizing treatment in end-stage kidney disease: deciding between haemodiafiltration and haemodialysis based on individualized treatment effect prediction
  40. Systematic Review Reveals Lack of Causal Methodology Applied to Pooled Longitudinal Observational Infectious Disease Studies
  41. Patient- and Tumour-related Prognostic Factors for Urinary Incontinence After Radical Prostatectomy for Nonmetastatic Prostate Cancer: A Systematic Review and Meta-analysis
  42. Combining individual patient data from randomized and non-randomized studies to predict real-world effectiveness of interventions
  43. Recommendations for the use of propensity score methods in multiple sclerosis research
  44. A few things to consider when deciding whether or not to conduct underpowered research
  45. ISPE‐Endorsed Guidance in Using Electronic Health Records for Comparative Effectiveness Research in COVID‐19: Opportunities and Trade‐Offs
  46. Development of a clinical prediction model for perinatal deaths in low resource settings
  47. Missing data is poorly handled and reported in prediction model studies using machine learning: a literature review
  48. Predicting personalised absolute treatment effects in individual participant data meta‐analysis: An introduction to splines
  49. Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review
  50. Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: a protocol for a methodological systematic review
  51. Internal-external cross-validation helped to evaluate the generalizability of prediction models in large clustered datasets
  52. A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint
  53. Measurement error in meta‐analysis (MEMA)—A Bayesian framework for continuous outcome data subject to non‐differential measurement error
  54. External validation of clinical prediction models: simulation-based sample size calculations were more reliable than rules-of-thumb
  55. Real-time imputation of missing predictor values improved the application of prediction models in daily practice
  56. Minimum sample size for external validation of a clinical prediction model with a binary outcome
  57. Developing more generalizable prediction models from pooled studies and large clustered data sets
  58. Current trends in the application of causal inference methods to pooled longitudinal observational infectious disease studies—A protocol for a methodological systematic review
  59. Individual participant data meta‐analysis for external validation, recalibration, and updating of a flexible parametric prognostic model
  60. How well can we assess the validity of non-randomised studies of medications? A systematic review of assessment tools
  61. Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?
  62. Real-time imputation of missing predictor values in clinical practice
  63. Framework for the synthesis of non-randomised studies and randomised controlled trials: a guidance on conducting a systematic review and meta-analysis for healthcare decision making
  64. Corrigendum to “Can personalized treatment prediction improve the outcomes, compared with the group average approach, in a randomized trial? Developing and validating a multivariable prediction model in a pragmatic megatrial of acute treatment for majo...
  65. Prognostic models for chronic kidney disease: a systematic review and external validation
  66. Strategies to reduce antibiotic use in women with uncomplicated urinary tract infection in primary care: protocol of a systematic review and meta-analysis including individual patient data
  67. The Zika Virus Individual Participant Data Consortium: A Global Initiative to Estimate the Effects of Exposure to Zika Virus during Pregnancy on Adverse Fetal, Infant, and Child Health Outcomes
  68. Can personalized treatment prediction improve the outcomes, compared with the group average approach, in a randomized trial? Developing and validating a multivariable prediction model in a pragmatic megatrial of acute treatment for major depression
  69. UMBRELLA protocol: systematic reviews of multivariable biomarker prognostic models developed to predict clinical outcomes in patients with heart failure
  70. Handling missing predictor values when validating and applying a prediction model to new patients
  71. Individual participant data meta‐analysis to examine interactions between treatment effect and participant‐level covariates: Statistical recommendations for conduct and planning
  72. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal
  73. Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection
  74. Systematic review and network meta-analysis with individual participant data on cord management at preterm birth (iCOMP): study protocol
  75. On the aggregation of published prognostic scores for causal inference in observational studies
  76. Individual participant data meta‐analysis of intervention studies with time‐to‐event outcomes: A review of the methodology and an applied example
  77. Predicting disability progression in multiple sclerosis: Insights from advanced statistical modeling
  78. Systematic review and network meta-analysis with individual participant data on Cord Management at Preterm Birth (iCOMP): study protocol
  79. Statistical approaches to identify subgroups in meta-analysis of individual participant data: a simulation study
  80. Assessment of heterogeneity in an individual participant data meta‐analysis of prediction models: An overview and illustration
  81. Guidance from key organisations on exploring, confirming and interpreting subgroup effects of medical treatments: a scoping review
  82. Evidence synthesis in prognosis research
  83. Development and validation of a novel prediction model to identify patients in need of specialized trauma care during field triage: design and rationale of the GOAT study
  84. Performance of the Framingham risk models and pooled cohort equations for predicting 10-year risk of cardiovascular disease: a systematic review and meta-analysis
  85. Understanding the relation between Zika virus infection during pregnancy and adverse fetal, infant and child outcomes: a protocol for a systematic review and individual participant data meta-analysis of longitudinal studies of pregnant women and their ...
  86. Empirical evidence of the impact of study characteristics on the performance of prediction models: a meta-epidemiological study
  87. A guide to systematic review and meta-analysis of prognostic factor studies
  88. The use of prognostic scores for causal inference with general treatment regimes
  89. Cardiovascular risk prediction models for women in the general population: A systematic review
  90. Erratum
  91. The life expectancy of Stephen Hawking, according to the ENCALS model
  92. A framework for meta-analysis of prediction model studies with binary and time-to-event outcomes
  93. Prognostic models for predicting the severity and mortality in people with acute pancreatitis
  94. Prognosis for patients with amyotrophic lateral sclerosis: development and validation of a personalised prediction model
  95. Predicition models for delayed graft function: external validation on The Dutch Prospective Renal Transplantation Registry
  96. Exacerbations in adults with asthma: A systematic review and external validation of prediction models
  97. Validation of an imaging based cardiovascular risk score in a Scottish population
  98. The development of CHAMP: a checklist for the appraisal of moderators and predictors
  99. Methods for examining publication bias
  100. Practical implications of using real-world evidence (RWE) in comparative effectiveness research: learnings from IMI-GetReal
  101. Predictive performance of the CHA2DS2-VASc rule in atrial fibrillation: a systematic review and meta-analysis
  102. Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?
  103. Reporting of Bayesian analysis in epidemiologic research should become more transparent
  104. Erratum to: Methods for evaluating medical tests and biomarkers
  105. Methods for Evaluating Medical Tests and Biomarkers
  106. Combining randomized and non-randomized evidence in network meta-analysis
  107. A guide to systematic review and meta-analysis of prediction model performance
  108. A closed testing procedure to select an appropriate method for updating prediction models
  109. GetReal in mathematical modelling: a review of studies predicting drug effectiveness in the real world
  110. Network meta-analysis using individual participant data
  111. External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges
  112. Prediction models for cardiovascular disease risk in the general population: systematic review
  113. Explicit inclusion of treatment in prognostic modeling was recommended in observational and randomized settings
  114. GetReal in network meta-analysis: a review of the methodology
  115. Multivariate meta-analysis of individual participant data helped externally validate the performance and implementation of a prediction model
  116. Isoniazid Prophylactic Therapy for the Prevention of Tuberculosis in HIV Infected Adults: A Systematic Review and Meta-Analysis of Randomized Trials
  117. Individual Participant Data (IPD) Meta-analyses of Diagnostic and Prognostic Modeling Studies: Guidance on Their Use
  118. Get real in individual participant data (IPD) meta-analysis: a review of the methodology
  119. Qualitative elastography can replace thyroid nodule fine-needle aspiration in patients with soft thyroid nodules. A systematic review and meta-analysis
  120. Summarising and validating test accuracy results across multiple studies for use in clinical practice
  121. A new framework to enhance the interpretation of external validation studies of clinical prediction models
  122. Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE
  123. Meta‐analysis and aggregation of multiple published prediction models
  124. Developing and validating risk prediction models in an individual participant data meta-analysis
  125. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study
  126. Individual participant data meta-analyses should not ignore clustering
  127. Individual Participant Data Meta-Analysis for a Binary Outcome: One-Stage or Two-Stage?
  128. A framework for developing, implementing, and evaluating clinical prediction models in an individual participant data meta-analysis
  129. Incorporating published univariable associations in diagnostic and prognostic modeling
  130. Aggregating published prediction models with individual participant data: a comparison of different approaches
  131. Development and validation of clinical prediction models: Marginal differences between logistic regression, penalized maximum likelihood estimation, and genetic programming