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

Yue Y, Cui X, Bose S, Audeh W, Zhang X, Fraass B - Breast Cancer Res. Treat. (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA. yong.yue@cshs.org.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Kaplan-Meier curves of disease-free survival of PET image features for TNBC patients with pre-treatment PET/CT, a SUVmax at cutoff level 3.5 with log-rank p = 0.002, b SUVmax cutoff value (red circle) is determined by time-dependent survival ROC curve with AUC = 0.654, c SUVmean at cutoff level 2.9 with log-rank p < 0.001, and d SUVvol at cutoff level 10 ml with log-rank p < 0.001
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Fig2: Kaplan-Meier curves of disease-free survival of PET image features for TNBC patients with pre-treatment PET/CT, a SUVmax at cutoff level 3.5 with log-rank p = 0.002, b SUVmax cutoff value (red circle) is determined by time-dependent survival ROC curve with AUC = 0.654, c SUVmean at cutoff level 2.9 with log-rank p < 0.001, and d SUVvol at cutoff level 10 ml with log-rank p < 0.001

Mentions: The prognostic values of image features were examined by univariate Cox analysis, as shown in Table 2. Maximum FDG uptake (SUVmax) was significant in both continuous (p = 0.021) and discrete status (≤3.5 vs. >3.5) with p = 0.006. The cutoff value of SUVmax was estimated using time-dependent survival ROC analysis. As a result, cutoff 3.5 maximized both sensitivity and specificity of SUVmax for the disease-free survival with AUC = 0.654. Figure 2b shows the ROC of SUVmax, where the cutoff point is marked by the red circle. The resultant cutoff percentile was verified by examining the prognostic value of SUVmax using log-rank test (p = 0.002) and Cox regression analysis (p = 0.006). As shown in Fig. 2a, patients were stratified into two risk groups with SUVmax (≤3.5 vs. >3.5), and the patients in high SUVmax groups had worse survival outcome.Table 2


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

Yue Y, Cui X, Bose S, Audeh W, Zhang X, Fraass B - Breast Cancer Res. Treat. (2015)

Kaplan-Meier curves of disease-free survival of PET image features for TNBC patients with pre-treatment PET/CT, a SUVmax at cutoff level 3.5 with log-rank p = 0.002, b SUVmax cutoff value (red circle) is determined by time-dependent survival ROC curve with AUC = 0.654, c SUVmean at cutoff level 2.9 with log-rank p < 0.001, and d SUVvol at cutoff level 10 ml with log-rank p < 0.001
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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Fig2: Kaplan-Meier curves of disease-free survival of PET image features for TNBC patients with pre-treatment PET/CT, a SUVmax at cutoff level 3.5 with log-rank p = 0.002, b SUVmax cutoff value (red circle) is determined by time-dependent survival ROC curve with AUC = 0.654, c SUVmean at cutoff level 2.9 with log-rank p < 0.001, and d SUVvol at cutoff level 10 ml with log-rank p < 0.001
Mentions: The prognostic values of image features were examined by univariate Cox analysis, as shown in Table 2. Maximum FDG uptake (SUVmax) was significant in both continuous (p = 0.021) and discrete status (≤3.5 vs. >3.5) with p = 0.006. The cutoff value of SUVmax was estimated using time-dependent survival ROC analysis. As a result, cutoff 3.5 maximized both sensitivity and specificity of SUVmax for the disease-free survival with AUC = 0.654. Figure 2b shows the ROC of SUVmax, where the cutoff point is marked by the red circle. The resultant cutoff percentile was verified by examining the prognostic value of SUVmax using log-rank test (p = 0.002) and Cox regression analysis (p = 0.006). As shown in Fig. 2a, patients were stratified into two risk groups with SUVmax (≤3.5 vs. >3.5), and the patients in high SUVmax groups had worse survival outcome.Table 2

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Department of Radiation Oncology, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA. yong.yue@cshs.org.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus