INTRODUCTION
Deprescribing literature has been increasing continuously for the last
ten years, as have systematic reviews focusing on deprescribing-related
questions. Authors developed various search strategies to retrieve
deprescribing literature. To our knowledge, there is still no consensus
on the terms to use to exhaustively retrieve deprescribing articles in
bibliographic databases (i.e. MEDLINE, Embase, etc. ). The
use of carefully selected terms is recommended to ensure the
exhaustiveness of a systematic review search
strategy1. However controlled vocabulary aimed at
identifying deprescribing articles remains unclear.
Search filters are specifically developed to avoid indexing pitfalls due
to imprecise controlled vocabulary, therefore improving search
effectiveness2. Search filters usually focus on a
particular study design or a specific topic3. The
performance of a search filter is usually evaluated based on a reference
set of relevant articles for the target study design or topic.
We recently developed two deprescribing search filters with maximized
sensitivity for MEDLINE (using PubMed interface) and for Embase (using
Embase.com interface) with a sensitivity of 92% (95% CI: 83–97) and
91% (95% CI: 82–96) respectively4. The efficiency
gained by using these maximized sensitivity filters in systematic
reviews search strategies remains unknown. Simultaneously, The US
Deprescribing Network (USDeN) developed a deprescribing search strategy
that included a deprescribing search filter for MEDLINE using PubMed
interface, but its performance has not been evaluated yet5.
The aim of this case study was to implement these three deprescribing
search filters in systematic review search strategies and evaluate their
performances.