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. 2021 Jun 23;40:205. doi: 10.1186/s13046-021-02015-4

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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. 2 — Nomogram established based on CARMN’s relationship with better cisplatin-based neoadjuvant chemotherapy response in breast cancer. A, B Texture feature selection for predicting response of neoadjuvant chemotherapy using lasso logistics regression. A Using minimum criteria of 10-fold cross-validation to select parameter lambda(λ) of LASSO model, and selected minimum λ turns out to be 0.0361. The upper x axis shows number of variants response to different λ values. The left dot line shows the minimum of λ and the right one shows λmin -SD. B LASSO coefficient profile plot of 12 texture features according to λ value selected in (A) which is also drawn as vertical line. Six optimal features are finally selected by lasso coefficient. C Forest plot illustrating factors selected by LASSO regression in predicting neoadjuvant chemotherapy response using multivariate logistics regression. D A nomogram is built for evaluating cisplatin-based neoadjuvant chemotherapy pCR rate based on multivariate logistics regression. E ROC curve of nomogram and other models for predicting cisplatin-based NAC response. F Calibration curve of the prediction model. X axis means the predicted probability of pCR. Y axis means the actual probability of pCR. The line between opposite angles means the ideal line. The other two lines means the actual prediction performance of the nomogram. G Decision curve of multivariate logistics model. The red line represents the multivariate logistics model including CARMN and clinicopathological factors, the blue one represents model with only clinicopathological factors. H ROC curve of nomogram in a validation set. I CARMN expression in ER- breast cancer with different neoadjuvant chemotherapy response. H Distribution of CARMN expression level in ER- breast cancer with different neoadjuvant chemotherapy response. ER: estrogen receptor; HER2: human epidermal growth factor receptor 2; TNBC: triple negative breast cancer; NAC: neoadjuvant chemotherapy; pCR: pathological complete response. Error bars represent means ± SD, *P < 0.05