ArticleBMC medical research methodology2019
Facilitating validation of prediction models: a comparison of manual and semi-automated validation using registry-based data of breast cancer patients in the Netherlands.
Article in BMC medical research methodology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed, 15 citations in OpenAlex.
- Article
- Validation of Predictive Analyses for Interim Decisions in Clinical Trials.JCO precision oncology · 2023Review
- Article
- Head-to-head comparison of 14 prediction models for postoperative delirium in elderly non-ICU patients: an external validation study.BMJ open · 2022Article
- A scoping review of interactive and personalized web-based clinical tools to support treatment decision making in breast cancer.Breast (Edinburgh, Scotland) · 2022Article
- Nomogram Predicting Cancer-Specific Death in Parotid Carcinoma: a Competing Risk Analysis.Frontiers in oncology · 2021Article
- Validation of a Prognostic Multivariable Prediction Model for Insufficient Clinical Response to Methotrexate in Early Rheumatoid Arthritis and Its Clinical Application in Evidencio.Rheumatology and therapy · 2020Article
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 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical prediction models are not routinely validated. To facilitate validation procedures, the online Evidencio platform ( https://www.evidencio.com ) has developed a tool partly automating this process. This study aims to determine whether semi-automated validation can reliably substitute manual validation.
methodsFour different models used in breast cancer care were selected: CancerMath, INFLUENCE, Predicted Probability of Axillary Metastasis, and PREDICT v.2.0. Data were obtained from the Netherlands Cancer Registry according to the inclusion criteria of the original development population. Calibration (intercepts and slopes) and discrimination (area under the curve (AUC)) were compared between semi-automated and manual validation.
resultsDifferences between intercepts and slopes of all models using semi-automated validation ranged from 0 to 0.03 from manual validation, which was not clinically relevant. AUCs were identical for both validation methods.
conclusionsThis easy to use semi-automated validation option is a good substitute for manual validation and might increase the number of validations of prediction models used in clinical practice. In addition, the validation tool was considered to be user-friendly and to save a lot of time compared to manual validation. Semi-automated validation will contribute to more accurate outcome predictions and treatment recommendations in the target population.
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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.