Skip to main content
main-content

01.12.2017 | Research article | Ausgabe 1/2017 Open Access

BMC Medical Research Methodology 1/2017

Multiple Score Comparison: a network meta-analysis approach to comparison and external validation of prognostic scores

Zeitschrift:
BMC Medical Research Methodology > Ausgabe 1/2017
Autoren:
Sarah R. Haile, Beniamino Guerra, Joan B. Soriano, Milo A. Puhan, for the 3CIA collaboration
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​s12874-017-0433-2) contains supplementary material, which is available to authorized users.
A correction to this article is available online at https://​doi.​org/​10.​1186/​s12874-018-0481-2.

Abstract

Background

Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.

Methods

Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.

Results

We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.

Conclusions

We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
Zusatzmaterial
Literatur
Über diesen Artikel

Weitere Artikel der Ausgabe 1/2017

BMC Medical Research Methodology 1/2017 Zur Ausgabe

Neu im Fachgebiet AINS

Mail Icon II Newsletter

Bestellen Sie unseren kostenlosen Newsletter Update AINS und bleiben Sie gut informiert – ganz bequem per eMail.

Bildnachweise