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. 2021 Jan 7;23:2. doi: 10.1186/s13058-020-01378-4

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© The Author(s) 2021

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

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Fig. 4 — Power analyses illustrating the effects of ROI sample size. a, b Power curve according to ROI size, holding patient sample size (n = 15) fixed, for the PD-L1 mIF biomarker (a) and the sTIL mIF biomarker (b) produced using a Monte Carlo simulation approach (n = 1000 simulations), based on the generalized linear mixed effects model and the observed data structure [i.e., effect sizes and variations obtained post hoc from the pilot experiment]. c, d Mean fold change and 95% confidence intervals based upon a bootstrap simulation method (1000 simulations) according to ROI size, for the PD-L1 mIF biomarker (c) and the sTIL mIF biomarker (d). ROI: region of interest; FC: fold change; CI: confidence interval