| Added by | liaudet-coopman |
|---|---|
| Group name | EquipeELC |
| Item Type | Journal Article |
| Title | Predictive factors of pathologic complete response of HER2-positive breast cancer after preoperative chemotherapy with trastuzumab: development of a specific predictor and study of its utilities using decision curve analysis |
| Creator | Jankowski et al. |
| Author | Clémentine Jankowski |
| Author | S. Guiu |
| Author | M. Cortet |
| Author | C. Charon-Barra |
| Author | I. Desmoulins |
| Author | V. Lorgis |
| Author | L. Arnould |
| Author | P. Fumoleau |
| Author | B. Coudert |
| Author | R. Rouzier |
| Author | C. Coutant |
| Author | F. Reyal |
| Abstract | PURPOSE: The aim of this study was to assess the Institut Gustave Roussy/M.D. Anderson Cancer Center (IGR/MDACC) nomogram in predicting pathologic complete response (pCR) to preoperative chemotherapy in a cohort of human epidermal growth factor receptor 2 (HER2)-positive tumors treated with preoperative chemotherapy with trastuzumab. We then combine clinical and pathological variables associated with pCR into a new nomogram specific to HER2-positive tumors treated by preoperative chemotherapy with trastuzumab. PATIENTS AND METHODS: Data from 270 patients with HER2-positive tumors treated with preoperative chemotherapy with trastuzumab at the Institut Curie and at the Georges François Leclerc Cancer Center were used to assess the IGR/MDACC nomogram and to subsequently develop a new nomogram for pCR based on multivariate logistic regression. Model performance was quantified in terms of calibration and discrimination. We studied the utility of the new nomogram using decision curve analysis. RESULTS: The IGR/MDACC nomogram was not accurate for the prediction of pCR in HER2-positive tumors treated by preoperative chemotherapy with trastuzumab, with poor discrimination (AUC = 0.54, 95% CI 0.51-0.58) and poor calibration (p = 0.01). After uni- and multivariate analysis, a new pCR nomogram was built based on T stage (TNM), hormone receptor status, and Ki67 (%). The model had good discrimination with an area under the curve (AUC) at 0.74 (95% CI 0.70-0.79) and adequate calibration (p = 0.93). By decision curve analysis, the model was shown to be relevant between thresholds of 0.3 and 0.7. CONCLUSION: To the best of our knowledge, ours is the first nomogram to predict pCR in HER2-positive tumors treated by preoperative chemotherapy with trastuzumab. To ensure generalizability, this model needs to be externally validated. |
| Publication | Breast Cancer Research and Treatment |
| Volume | 161 |
| Issue | 1 |
| Pages | 73-81 |
| Date | 01 2017 |
| Journal Abbr | Breast Cancer Res. Treat. |
| Language | eng |
| DOI | 10.1007/s10549-016-4040-4 |
| ISSN | 1573-7217 |
| Short Title | Predictive factors of pathologic complete response of HER2-positive breast cancer after preoperative chemotherapy with trastuzumab |
| Library Catalog | PubMed |
| Extra | PMID: 27807808 |
| Tags | Adult, Antineoplastic Agents, Immunological, Biomarkers, Tumor, Breast Neoplasms, clinic, Clinical Decision-Making, Combined Modality Therapy, Decision Support Techniques, Female, HER2, Humans, Middle Aged, Neoadjuvant chemotherapy, Neoadjuvant Therapy, Neoplasm Staging, Predictive factors, Preoperative Care, Prognosis, Receptor, ErbB-2, Reproducibility of Results, Retrospective Studies, ROC Curve, Trastuzumab, Treatment Outcome |
| Date Added | 2018/09/26 - 14:32:51 |
| Date Modified | 2019/05/29 - 12:22:29 |
Institut de Recherche en Cancérologie de
