gms | German Medical Science

G-I-N Conference 2012

Guidelines International Network

22.08 - 25.08.2012, Berlin

Using diagnostic meta-analysis to inform decision making for risk scoring systems

Meeting Abstract

  • K. Dworzynski - Royal College of Physicians (National Clinical Guideline Centre), London, UK
  • V. Pollit - Royal College of Physicians (National Clinical Guideline Centre), London, UK
  • T. Reason - Royal College of Physicians (National Clinical Guideline Centre), London, UK
  • A. Kelsey - Royal College of Physicians (National Clinical Guideline Centre), London, UK
  • B. Higgins - Royal College of Physicians (National Clinical Guideline Centre), London, UK

Guidelines International Network. G-I-N Conference 2012. Berlin, 22.-25.08.2012. Düsseldorf: German Medical Science GMS Publishing House; 2012. DocO53

doi: 10.3205/12gin085, urn:nbn:de:0183-12gin0851

Published: July 10, 2012

© 2012 Dworzynski et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

Text

Background: Our guideline development centre received a commission to produce a UK guideline on management of upper gastrointestinal bleeding (UGIB). Two prognostic scoring systems are currently used to identify those patients at high risk for mortality. The guideline development group (GDG) asked whether any one scoring systems was more accurate. A diagnostic meta- analysis was conducted to help the GDG in their decisions on which of these systems should be recommended.

Objectives: To present our experience and key learning points from diagnostic meta-analysis of scoring systems in the UGIB guideline to aid the formation of recommendations.

Methods: A diagnostic meta-analysis was carried out using two-by-two data for each of the scoring systems and results were pooled using the bivariate (random effects) method that models sensitivity and specificity across studies.

Results: Both systems showed good total sensitivity. However using meta-analysis rather than individual results provided clearer evidence in favour of the newer index (better sensitivity/lower heterogeneity). This led to a change in recommendation.

Discussion: Evidence of an improvement in risk identification by the newer scoring system presented the GDG with a dilemma of how strongly to recommend the newer system (and change practice altogether) without discouraging clinicians who are already using the older system. The compromise was an either / or recommendation.

Implications for guideline developers/users: Diagnostic meta-analysis can aid GDGs decision making in prognostic and diagnostic test analysis and can lead to changes in recommendations and improved practice.