ORIGINAL PAPER Nomogram predicting clinical outcomes in breast cancer patients treated with neoadjuvant chemotherapy Bhumsuk Keam • Seock-Ah Im • Sohee Park • Byung-Ho Nam • Sae-Won Han • Do-Youn Oh • Jee Hyun Kim • Se-Hoon Lee • Wonshik Han • Dong-Wan Kim • Tae-You Kim • In Ae Park • Dong-Young Noh • Dae Seog Heo • Yung-Jue Bang Received: 2 May 2011 / Accepted: 26 May 2011 / Published online: 30 June 2011 Ó Springer-Verlag 2011 Abstract Purpose The aim of this study was to combine clinical pathologic variables that are associated with pathologic completer response (pCR) and relapse-free survival (RFS) after neoadjuvant chemotherapy into prediction nomograms. Methods A total of 370 stage II or III breast cancer patients who received neoadjuvant docetaxel/doxorubicin chemotherapy were enrolled in this study. We developed the nomograms using logistic regression model for pCR and Cox proportional hazard regression model for RFS. Results The nomogram for pCR based on initial tumor size, estrogen receptor (ER), human epidermal growth factor receptor 2, and Ki67 had good discrimination per- formance (AUROC = 0.830). Multivariate Cox model identified age less than 35, initial clinical stage, pathologic stage, ER, Ki67 as prognostic factors, and the nomogram for RFS was developed based on these covariates. The concordance index for the second nomogram was 0.781, and calibration was also good. Conclusions We developed nomograms based on clinical and pathologic characteristics to predict the probability of pCR and RFS for patients receiving neoadjuvant docetaxel/ doxorubicin chemotherapy. Keywords Nomogram Á Breast cancer Á Neoadjuvant chemotherapy Á Prediction Introduction Breast cancer is a heterogeneous disease with a demon- strated difference in prognosis based on molecular pheno- types. Neoadjuvant chemotherapy (NAC), also called as preoperative systemic chemotherapy, has emerged as the preferred initial component of therapy for patients diag- nosed with locally advanced breast cancer. However, a potential disadvantage of NAC is the loss of prognostic value provided by tumor size and nodal status at surgery and before adjuvant chemotherapy (Estevez and Gradishar 2004; Shimizu et al. 2007). Many researchers have attempted to perform risk stratification and individualized treatment according to molecular phenotypes. B. Keam Á S.-A. Im (&) Á S.-W. Han Á D.-Y. Oh Á J. H. Kim Á S.-H. Lee Á D.-W. Kim Á T.-Y. Kim Á D. S. Heo Á Y.-J. Bang Department of Internal Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Gu, Seoul 110-744, Korea e-mail: moisa@snu.ac.kr B. Keam Á S.-A. Im Á S.-W. Han Á D.-Y. Oh Á J. H. Kim Á S.-H. Lee Á W. Han Á D.-W. Kim Á T.-Y. Kim Á I. A. Park Á D.-Y. Noh Á D. S. Heo Á Y.-J. Bang Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea S. Park Á B.-H. Nam Cancer Biostatistics Branch, Research Institute, National Cancer Center, Goyang-si, Korea J. H. Kim Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Korea W. Han Á D.-Y. Noh Department of Surgery, Seoul National University College of Medicine, Seoul, Korea I. A. Park Department of Pathology, Seoul National University College of Medicine, Seoul, Korea 123 J Cancer Res Clin Oncol (2011) 137:1301–1308 DOI 10.1007/s00432-011-0991-3