Evidence map›Paper›PMID 28480827›Full record

SynthesisStatistical methods in medical research2018

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

Kym Ie Snell, Joie Ensor, Thomas Pa Debray, Karel Gm Moons, Richard D Riley

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Statistical methods in medical research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 33 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
72citing papers in PubMed, 33 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

72 citing papers in PubMed, 33 syntheses or guidelines pooled it.

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  13. Prognostic models for clinical outcomes in patients with venous leg ulcers: A systematic review.Journal of vascular surgery. Venous and lymphatic disorders · 2024
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  16. A Systematic Review and Meta-analysis of Convolutional Neural Network in the Diagnosis of Colorectal Polyps and Cancer.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2023
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12 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Kym Ie Snell1 Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire, UK.
Joie Ensor1 Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire, UK.
Thomas Pa Debray2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Karel Gm Moons2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
Richard D Riley1 Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire, UK.

Funding

Medical Research Council G0800808Medical Research Council MR/J013595/1Medical Research Council MR/J013595/2
6 · The paper itself

Abstract

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Indexed as

CalibrationForecastingModels, StatisticalAlgorithmsBiomedical ResearchTreatment OutcomeValidation Studies as Topicbetween-study distributioncalibrationC-statisticdiscriminationheterogeneitymeta-analysisperformance statisticssimulationValidation

Identifiers

PMID28480827
PMCPMC6193210

What OpenQuestion holds

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Registered trials

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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.