New horizons in evidence synthesis for older adults

Age Ageing. 2023 Nov 2;52(11):afad211. doi: 10.1093/ageing/afad211.

Abstract

Evidence synthesis, embedded within a systematic review of the literature, is a well-established approach for collating and combining all the relevant information on a particular research question. A robust synthesis can establish the evidence base, which underpins best practice guidance. Such endeavours are frequently used by policymakers and practitioners to inform their decision making. Traditionally, an evidence synthesis of interventions consisted of a meta-analysis of quantitative data comparing two treatment alternatives addressing a specific and focussed clinical question. However, as the methods in the field have evolved, especially in response to the increasingly complex healthcare questions, more advanced evidence synthesis techniques have been developed. These can deal with extended data structures considering more than two treatment alternatives (network meta-analysis) and complex multicomponent interventions. The array of questions capable of being answered has also increased with specific approaches being developed for different evidence types including diagnostic, prognostic and qualitative data. Furthermore, driven by a desire for increasingly up-to-date evidence summaries, living systematic reviews have emerged. All of these methods can potentially have a role in informing older adult healthcare decisions. The aim of this review is to increase awareness and uptake of the increasingly comprehensive array of newer synthesis methods available and highlight their utility for answering clinically relevant questions in the context of older adult research, giving examples of where such techniques have already been effectively applied within the field. Their strengths and limitations are discussed, and we suggest user-friendly software options to implement the methods described.

Keywords: ageing; evidence; meta-analysis; methods; older people; systematic review.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Aged
  • Data Accuracy*
  • Humans
  • Network Meta-Analysis