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. 2019 Oct 28;8:243. doi: 10.1186/s13643-019-1162-x

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© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 1 — Example of effort/loss curve for a single meta-analysis using screening prioritization. The evolution of the sensitivity and specificity estimates for one diagnostic test “CD008803 1 GDx: inferior average” (n=48), where the candidate studies are screened using screening prioritization. The x-axis measures the number of screened studies (effort) and the the y-axis measures the summary estimates at the 25%, 50%, and 75% percentiles over 20 simulated screenings using screening prioritization. We also plot the difference to the “true” values (bottom)