Johanna Damen

Assistant Professor

University Medical Center Groningen

Netherlands

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About

Johanna Damen is an Assistant Professor at the University Medical Center Utrecht in the Netherlands. Her research primarily focuses on the reporting quality and applicability of clinical trial results, prediction models in health care, and methodological quality assessment in medical research. Recent publications include work on trial results reporting practices, the development of risk assessment tools for prediction models, and systematic reviews in migraine treatment and mortality outcomes in patients with peripheral arterial disease.

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Collaborators (21)

Mahdad Noursadeghi

Professor of Infectious Disease

University College London

UNITED KINGDOM

Johanna Damen

Research Interests

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About

Articles (22)

Improving the reporting and use of trial results in clinical trials registries: global practices, barriers, and recommendations

Write Your Abstracts Carefully - The Impact of Abstract Reporting Quality on Findability by Semi-Automated Title-Abstract Screening Tools

Assessing the quality of prediction models in health care using the Prediction model Risk Of Bias ASsessment Tool (PROBAST): an evaluation of its use and practical application

PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods

Comparative Effectiveness of Pharmacologic Treatments for the Prevention of Episodic Migraine Headache: A Systematic Review and Network Meta-analysis for the American College of Physicians

Methodological quality assessment tools for diagnosis and prognosis research: overview and guidance

Editor's Choice – Prognostic Factors and Models to Predict Mortality Outcomes in Patients with Peripheral Arterial Disease: A Systematic Review

SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models

Both clinical trial register and electronic bibliographic database searches were needed to identify randomized clinical trials for systematic reviews: an evaluation study

Increased endorsement of TRIPOD and other reporting guidelines by high impact factor journals: survey of instructions to authors

Validation of prognostic models predicting mortality or ICU admission in patients with COVID-19 in low- and middle-income countries: a global individual participant data meta-analysis

Prognostic Factors and Models to Predict Mortality Outcomes in Patients with Peripheral Arterial Disease: A Systematic Review

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models

Indicators of questionable research practices were identified in 163,129 randomized controlled trials

Systematic review finds “spin” practices and poor reporting standards in studies on machine learning-based prediction models

Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review

One Heartbeat Away from a Prediction Model for Cardiovascular Diseases in Patients with Chronic Kidney Disease: A Systematic Review

Clinical prediction models for mortality in patients with covid-19: external validation and individual participant data meta-analysis

Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review

External Validation of Risk Prediction Models to Improve Selection of Patients for Carotid Endarterectomy

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review

The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement

Collaborators (21)

Mahdad Noursadeghi

Kim van der Braak

Maarten van Smeden

Marianne Verhaar

Shona Kirtley

Richard D Riley

Paula Dhiman

Lex Bouter

Joeri Tijdink

Melissa McCradden

Laure Wynants

Martin Modrák

Bada Yang

Wim Otte

Michiel Poorthuis

Michiel Bots

Ram Bajpai

Pranabashis Haldar

Jie Ma

Lotty Hooft

Vasa Curcin

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