ArticleDiagnostic and prognostic research2018
Evaluating the impact of prediction models: lessons learned, challenges, and recommendations.
Article in Diagnostic and prognostic research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 papers, 12 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
100 citing papers in PubMed, 12 syntheses or guidelines pooled it, 201 citations in OpenAlex.
- Risk prediction for lung cancer screening: a systematic review and meta-regression.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Prognostic models for all-cause and cardiovascular mortality in type 2 diabetes: Systematic review.Diabetic medicine : a journal of the British Diabetic Association · 2026Pooled it
- Risk prediction models for enteral feeding intolerance in critically ill patients: a systematic review.Frontiers in public health · 2026Pooled it
- Risk prediction models for delirium in ICU patients: a systematic review and critical appraisal.BMC anesthesiology · 2025Pooled it
- Facilitators and Barriers of the Use of Prognostic Models for Clinical Decision Making in Acute Neurologic Care: A Systematic Review.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Pooled it
- Systematic Review of Clinical Prediction Models for the Risk of Emergency Caesarean Births.BJOG : an international journal of obstetrics and gynaecology · 2025Pooled it
- A systematic review of fall prediction models for community-dwelling older adults: comparison between models based on research cohorts and models based on routinely collected data.Age and ageing · 2024Pooled it
- Evaluation of Machine Learning Methods Developed for Prediction of Diabetes Complications: A Systematic Review.Journal of diabetes science and technology · 2023Pooled it
- Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review.BMC medical research methodology · 2022Pooled it
- Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges.Molecular psychiatry · 2022Pooled it
- Prediction of hypertension using traditional regression and machine learning models: A systematic review and meta-analysis.PloS one · 2022Pooled it
- Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.BMJ (Clinical research ed.) · 2020Pooled it
- Managing Pregnancies of Unknown Location With the M4 Prediction Model or the NICE Algorithm: A Randomised Controlled Trial With Cross-Sectional Diagnostic Accuracy Data.BJOG : an international journal of obstetrics and gynaecology · 2025Trial
- The effect of proactiveBJA open · 2024Trial
- Randomised trial of stable chest pain investigation: 3-year clinical and quality of life results from CE-MARC 2.Open heart · 2023Trial
- Evaluating the Impact of the Grading and Assessment of Predictive Tools Framework on Clinicians and Health Care Professionals' Decisions in Selecting Clinical Predictive Tools: Randomized Controlled Trial.Journal of medical Internet research · 2020Trial
- Structural requirements for intelligent clinical digital twins in feedback-driven care.npj health systems · 2026Review
- An Evaluation of Clinician and Informatician Perspectives on Medication Harm Risk Prediction Tools for Use in a Tertiary Hospital Setting.Journal of evaluation in clinical practice · 2026Article
- Radiomics-based outcome prediction for irinotecan-TACE in colorectal liver metastases: advanced analysis from the prospective CIREL trial.European radiology · 2026Article
- Clinical and CSF Measurements for Identification of Leptomeningeal Metastasis in Lung Adenocarcinoma.Diagnostics (Basel, Switzerland) · 2026Article
40 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An important aim of clinical prediction models is to positively impact clinical decision making and subsequent patient outcomes. The impact on clinical decision making and patient outcome can be quantified in prospective comparative-ideally cluster-randomized-studies, known as 'impact studies'. However, such impact studies often require a lot of time and resources, especially when they are (cluster-)randomized studies. Before envisioning such large-scale randomized impact study, it is important to ensure a reasonable chance that the use of the prediction model by the targeted healthcare professionals and patients will indeed have a positive effect on both decision making and subsequent outcomes. We recently performed two differently designed, prospective impact studies on a clinical prediction model to be used in surgical patients. Both studies taught us new valuable lessons on several aspects of prediction model impact studies, and which considerations may guide researchers in their decision to conduct a prospective comparative impact study. We provide considerations on how to prepare a prediction model for implementation in practice, how to present the model predictions, and how to choose the proper design for a prediction model impact study.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.