Vickers, Andrew J.

Decision curve analysis: a novel method for evaluating prediction models

Vickers, A. J., & Elkin, E. B. (2006) · Medical Decision Making

Statistical Methods in EpidemiologyClinical Reasoning and Diagnostic Skills

Cited by 6,341

Assessing the Performance of Prediction Models: A Framework for Traditional and Novel Measures

Steyerberg, E. W., Vickers, A. J., Cook, N. R., Gerds, T., Gonen, M., Obuchowski, N., Pencina, M. J., & Kattan, M. W. (2010) · Epidemiology

Statistical Methods in EpidemiologyStatistical Methods and Inference

Cited by 5,170

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration

Moons, K. G. M., Altman, D. G., Reitsma, J. B., Ioannidis, J. P. A., Macaskill, P., Steyerberg, E. W., Vickers, A. J., Ransohoff, D. F., & Collins, G. S. (2015) · Annals of Internal Medicine

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 5,147

Analysing controlled trials with baseline and follow up measurements

Vickers, A. J., & Altman, D. G. (2001) · BMJ

Statistical Methods in Clinical TrialsStatistical Methods and Bayesian Inference

Cited by 2,116

A simple, step-by-step guide to interpreting decision curve analysis

Vickers, A. J., van Calster, B., & Steyerberg, E. W. (2019) · Diagnostic and Prognostic Research

Statistical Methods in EpidemiologyMeta-analysis and systematic reviews

Cited by 1,174

Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests

Vickers, A. J., Van Calster, B., & Steyerberg, E. W. (2016) · BMJ

Statistical Methods in EpidemiologyHealth Systems, Economic Evaluations, Quality of Life

Cited by 1,163

Increasing value and reducing waste: addressing inaccessible research

Chan, A.-W., Song, F., Vickers, A., Jefferson, T., Dickersin, K., Gøtzsche, P. C., Krumholz, H. M., Ghersi, D., & van der Worp, H. B. (2014) · The Lancet

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 887

The Predictive Approaches to Treatment effect Heterogeneity (PATH) statement

Kent, D. M., Paulus, J. K., van Klaveren, D., D'Agostino, R., Goodman, S., Hayward, R., Ioannidis, J. P. A., Patrick-Lake, B., Morton, S., Pencina, M., et al. (2020) · Annals of Internal Medicine

Statistical Methods in Clinical TrialsAdvanced Causal Inference Techniques

Cited by 469

Pilot Randomized Controlled Trial of Individual Meaning-Centered Psychotherapy for Patients With Advanced Cancer

Breitbart, W., Poppito, S., Rosenfeld, B., Vickers, A. J., Li, Y., Abbey, J., Olden, M., Pessin, H., Lichtenthal, W., Sjoberg, D., et al. (2012) · Journal of Clinical Oncology

Religion, Spirituality, and PsychologyPalliative and Oncologic Care

Cited by 426

Empirical Study of Data Sharing by Authors Publishing in PLoS Journals

Savage, C. J., & Vickers, A. J. (2009) · PLoS ONE

Research Data Management PracticesAcademic Publishing and Open Access

Cited by 411

Calibration of Risk Prediction Models: Impact on Decision-Analytic Performance

Van Calster, B., & Vickers, A. J. (2015) · Medical Decision Making

Statistical Methods in EpidemiologyClinical Reasoning and Diagnostic Skills

Cited by 371

Guidelines for Reporting of Statistics for Clinical Research in Urology

Assel, M., Sjoberg, D., Elders, A., Wang, X., Huo, D., Botchway, A., Delfino, K., Fan, Y., Zhao, Z., Koyama, T., et al. (2019) · European Urology

Meta-analysis and systematic reviewsStatistical Methods in Epidemiology

Cited by 335

Massage for promoting growth and development of preterm and/or low birth-weight infants

Vickers, A., Ohlsson, A., Lacy, J., & Horsley, A. (2004) · Cochrane Database of Systematic Reviews

Infant Development and Preterm CareInfant Health and Development

Cited by 293

Prostate Cancer Prevention Trial Risk Calculator 2.0 for the Prediction of Low- vs High-grade Prostate Cancer

Ankerst, D. P., Hoefler, J., Bock, S., Goodman, P. J., Vickers, A., Hernandez, J., Sokoll, L. J., Sanda, M. G., Wei, J. T., Leach, R. J., et al. (2014) · Urology

Prostate Cancer Diagnosis and TreatmentGlobal Cancer Incidence and Screening

Cited by 236

Assessing the incremental value of diagnostic and prognostic markers: a review and illustration

Steyerberg, E. W., Pencina, M. J., Lingsma, H. F., Kattan, M. W., Vickers, A. J., & Van Calster, B. (2012) · European Journal of Clinical Investigation

Statistical Methods in EpidemiologyStatistical Methods and Inference

Cited by 219

Using Relative Utility Curves to Evaluate Risk Prediction

Baker, S. G., Cook, N. R., Vickers, A., & Kramer, B. S. (2009) · Journal of the Royal Statistical Society Series A: Statistics in Society

Statistical Methods in EpidemiologyHealth Systems, Economic Evaluations, Quality of Life

Cited by 142

Why use placebos in clinical trials? A narrative review of the methodological literature

Vickers, A. (2000) · Journal of Clinical Epidemiology

Statistical Methods in Clinical TrialsPain Management and Placebo Effect

Cited by 121

Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance

Van Calster, B., Collins, G. S., Vickers, A. J., Wynants, L., Kerr, K. F., Barreñada, L., Varoquaux, G., Singh, K., Moons, K. G., Hernandez-Boussard, T., et al. (2025) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationStatistical Methods in Epidemiology

Cited by 112

Everything you always wanted to know about evaluating prediction models (but were too afraid to ask)

Vickers, A. J., & Cronin, A. M. (2010) · Urology

Statistical Methods in EpidemiologyMeta-analysis and systematic reviews

Cited by 112

Underpowering in randomized trials reporting a sample size calculation

Vickers, A. J. (2003) · Journal of Clinical Epidemiology

Statistical Methods in Clinical TrialsStatistical Methods in Epidemiology

Cited by 102

Acupuncture for the treatment of post-chemotherapy chronic fatigue: a randomized, blinded, sham-controlled trial

Deng, G., Chan, Y., Sjoberg, D., Vickers, A., Yeung, K. S., Kris, M., Straus, D., & Cassileth, B. (2013) · Supportive Care in Cancer

Acupuncture Treatment Research StudiesCancer survivorship and care

Cited by 69

Genetic Polymorphisms of CFH and ARMS2 Do Not Predict Response to Antioxidants and Zinc in Patients with Age-Related Macular Degeneration

Assel, M. J., Li, F., Wang, Y., Allen, A. S., Baggerly, K. A., & Vickers, A. J. (2018) · Ophthalmology

Retinal Diseases and TreatmentsNutrition, Genetics, and Disease

Cited by 48

Assessing the net benefit of machine learning models in the presence of resource constraints

Singh, K., Shah, N. H., & Vickers, A. J. (2023) · Journal of the American Medical Informatics Association

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 21