Cargando…

Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging

This study aims to stratify prognosis of triple-negative breast cancer (TNBC) patients using pre-treatment 18F-FDG-PET/CT, alone and with correlation to immunohistochemistry biomarkers. 200 consecutive TNBC breast cancer patients treated between 2008 and 2012 were retrieved. Among the full cohort, 7...

Descripción completa

Detalles Bibliográficos
Autores principales: Yue, Yong, Cui, Xiaojiang, Bose, Shikha, Audeh, William, Zhang, Xiao, Fraass, Benedick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4589560/
https://www.ncbi.nlm.nih.gov/pubmed/26346756
http://dx.doi.org/10.1007/s10549-015-3558-1
_version_ 1782392803866705920
author Yue, Yong
Cui, Xiaojiang
Bose, Shikha
Audeh, William
Zhang, Xiao
Fraass, Benedick
author_facet Yue, Yong
Cui, Xiaojiang
Bose, Shikha
Audeh, William
Zhang, Xiao
Fraass, Benedick
author_sort Yue, Yong
collection PubMed
description This study aims to stratify prognosis of triple-negative breast cancer (TNBC) patients using pre-treatment 18F-FDG-PET/CT, alone and with correlation to immunohistochemistry biomarkers. 200 consecutive TNBC breast cancer patients treated between 2008 and 2012 were retrieved. Among the full cohort, 79 patients had pre-treatment 18F-FDG-PET/CT scans. Immunostaining status of basal biomarkers (EGFR, CK5/6) and other clinicopathological variables were obtained. Three PET image features were evaluated: maximum uptake values (SUVmax), mean uptake (SUVmean), and metabolic volume (SUVvol) defined by SUV > 2.5. All variables were analyzed versus disease-free survival (DFS) using univariate and multivariate Cox analysis, Kaplan-Meier curves, and log-rank tests. The optimal cutoff points of variables were estimated using time-dependent survival receiver operating characteristic (ROC) analysis. All PET features significantly correlated with proliferation marker Ki-67 (all p < 0.010). SUVmax stratified the prognosis of TNBC patients with optimal cutoff derived by ROC analysis (≤3.5 vs. >3.5, AUC = 0.654, p = 0.006). SUVmax and EGFR were significant prognostic factors in univariate and multivariate Cox analyses. To integrate prognosis of biological and imaging markers, patients were first stratified by EGFR into low (≤15 %) and high (>15 %) risk groups. Further, SUVmax was used as a variable to stratify the two EGFR groups. In the high EGFR group, patients with high FDG uptake (SUVmax > 3.5) had worse survival outcome (median DFS = 7.6 months) than those patients with low FDG uptake (SUVmax ≤ 3.5, median DFS = 11.6 months). In the low EGFR group, high SUVmax also indicated worse survival outcome (17.2 months) than low SUVmax (22.8 months). The risk stratification with integrative EGFR and PET was statistically significant with log-rank p ≪ 0.001. Pre-treatment 18F-FDG-PET/CT imaging has significant prognostic value for predicting survival outcome of TNBC patients. Integrated with basal-biomarker EGFR, PET imaging can further stratify patient risks in the pre-treatment stage and help select appropriate treatment strategies for individual patients.
format Online
Article
Text
id pubmed-4589560
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Springer US
record_format MEDLINE/PubMed
spelling pubmed-45895602015-10-06 Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging Yue, Yong Cui, Xiaojiang Bose, Shikha Audeh, William Zhang, Xiao Fraass, Benedick Breast Cancer Res Treat Epidemiology This study aims to stratify prognosis of triple-negative breast cancer (TNBC) patients using pre-treatment 18F-FDG-PET/CT, alone and with correlation to immunohistochemistry biomarkers. 200 consecutive TNBC breast cancer patients treated between 2008 and 2012 were retrieved. Among the full cohort, 79 patients had pre-treatment 18F-FDG-PET/CT scans. Immunostaining status of basal biomarkers (EGFR, CK5/6) and other clinicopathological variables were obtained. Three PET image features were evaluated: maximum uptake values (SUVmax), mean uptake (SUVmean), and metabolic volume (SUVvol) defined by SUV > 2.5. All variables were analyzed versus disease-free survival (DFS) using univariate and multivariate Cox analysis, Kaplan-Meier curves, and log-rank tests. The optimal cutoff points of variables were estimated using time-dependent survival receiver operating characteristic (ROC) analysis. All PET features significantly correlated with proliferation marker Ki-67 (all p < 0.010). SUVmax stratified the prognosis of TNBC patients with optimal cutoff derived by ROC analysis (≤3.5 vs. >3.5, AUC = 0.654, p = 0.006). SUVmax and EGFR were significant prognostic factors in univariate and multivariate Cox analyses. To integrate prognosis of biological and imaging markers, patients were first stratified by EGFR into low (≤15 %) and high (>15 %) risk groups. Further, SUVmax was used as a variable to stratify the two EGFR groups. In the high EGFR group, patients with high FDG uptake (SUVmax > 3.5) had worse survival outcome (median DFS = 7.6 months) than those patients with low FDG uptake (SUVmax ≤ 3.5, median DFS = 11.6 months). In the low EGFR group, high SUVmax also indicated worse survival outcome (17.2 months) than low SUVmax (22.8 months). The risk stratification with integrative EGFR and PET was statistically significant with log-rank p ≪ 0.001. Pre-treatment 18F-FDG-PET/CT imaging has significant prognostic value for predicting survival outcome of TNBC patients. Integrated with basal-biomarker EGFR, PET imaging can further stratify patient risks in the pre-treatment stage and help select appropriate treatment strategies for individual patients. Springer US 2015-09-07 2015 /pmc/articles/PMC4589560/ /pubmed/26346756 http://dx.doi.org/10.1007/s10549-015-3558-1 Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided 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.
spellingShingle Epidemiology
Yue, Yong
Cui, Xiaojiang
Bose, Shikha
Audeh, William
Zhang, Xiao
Fraass, Benedick
Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title_full Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title_fullStr Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title_full_unstemmed Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title_short Stratifying triple-negative breast cancer prognosis using 18F-FDG-PET/CT imaging
title_sort stratifying triple-negative breast cancer prognosis using 18f-fdg-pet/ct imaging
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4589560/
https://www.ncbi.nlm.nih.gov/pubmed/26346756
http://dx.doi.org/10.1007/s10549-015-3558-1
work_keys_str_mv AT yueyong stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging
AT cuixiaojiang stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging
AT boseshikha stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging
AT audehwilliam stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging
AT zhangxiao stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging
AT fraassbenedick stratifyingtriplenegativebreastcancerprognosisusing18ffdgpetctimaging