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. 2022 Feb 15;13:873. doi: 10.1038/s41467-022-28410-9

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© The Author(s) 2022

Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 4 — Comparison of nonparametric and parametric (Weibull distribution) methods to compute 12-month OS confidence intervals (CIs) for trials with small cohorts (20–100 patients) produced by randomly subsampling patient events from 125 actual trial arms. Note that nonparametric estimates did not return an informative confidence interval for 41% of OS curves (out of 213 OS curves with at least 100 patients), while Weibull fitting made it possible to calculate 12-month confidence intervals for every survival curve in every simulation. Precision is defined as the width of the confidence interval in percent survival. Accuracy is defined as the absolute difference between the 12-month survival estimated from small cohorts and the value computed from all patients in a given Phase 3 trial arm. Lines denote mean values and shaded regions are 95% confidence intervals.