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Neoadjuvant Chemotherapy for Breast Cancer: Functional Tumor Volume by MR Imaging Predicts Recurrence-free Survival-Results from the ACRIN 6657/CALGB 150007 I-SPY 1 TRIAL.
Hylton, Nola M; Gatsonis, Constantine A; Rosen, Mark A; Lehman, Constance D; Newitt, David C; Partridge, Savannah C; Bernreuter, Wanda K; Pisano, Etta D; Morris, Elizabeth A; Weatherall, Paul T; Polin, Sandra M; Newstead, Gillian M; Marques, Helga S; Esserman, Laura J; Schnall, Mitchell D.
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  • Hylton NM; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Gatsonis CA; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Rosen MA; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Lehman CD; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Newitt DC; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Partridge SC; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Bernreuter WK; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Pisano ED; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Morris EA; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Weatherall PT; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Polin SM; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Newstead GM; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Marques HS; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Esserman LJ; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
  • Schnall MD; From the Departments of Radiology (N.M.H., D.C.N.) and Surgery (L.J.E.), University of California, San Francisco, 1600 Divisadero St, Room C250, Box 1667, San Francisco, CA 94115; Department of Biostatistics (C.A.G.) and Center for Statistical Sciences (C.A.G., H.S.M.), Brown University, Providence,
Radiology ; 279(1): 44-55, 2016 Apr.
Article en En | MEDLINE | ID: mdl-26624971
PURPOSE: To evaluate volumetric magnetic resonance (MR) imaging for predicting recurrence-free survival (RFS) after neoadjuvant chemotherapy (NACT) of breast cancer and to consider its predictive performance relative to pathologic complete response (PCR). MATERIALS AND METHODS: This HIPAA-compliant prospective multicenter study was approved by institutional review boards with written informed consent. Women with breast tumors 3 cm or larger scheduled for NACT underwent dynamic contrast-enhanced MR imaging before treatment (examination 1), after one cycle (examination 2), midtherapy (examination 3), and before surgery (examination 4). Functional tumor volume (FTV), computed from MR images by using enhancement thresholds, and change from baseline (ΔFTV) were measured after one cycle and before surgery. Association of RFS with FTV was assessed by Cox regression and compared with association of RFS with PCR and residual cancer burden (RCB), while controlling for age, race, and hormone receptor (HR)/ human epidermal growth factor receptor type 2 (HER2) status. Predictive performance of models was evaluated by C statistics. RESULTS: Female patients (n = 162) with FTV and RFS were included. At univariate analysis, FTV2, FTV4, and ΔFTV4 had significant association with RFS, as did HR/HER2 status and RCB class. PCR approached significance at univariate analysis and was not significant at multivariate analysis. At univariate analysis, FTV2 and RCB class had the strongest predictive performance (C statistic = 0.67; 95% confidence interval [CI]: 0.58, 0.76), greater than for FTV4 (0.64; 95% CI: 0.53, 0.74) and PCR (0.57; 95% CI: 0.39, 0.74). At multivariate analysis, a model with FTV2, ΔFTV2, RCB class, HR/HER2 status, age, and race had the highest C statistic (0.72; 95% CI: 0.60, 0.84). CONCLUSION: Breast tumor FTV measured by MR imaging is a strong predictor of RFS, even in the presence of PCR and RCB class. Models combining MR imaging, histopathology, and breast cancer subtype demonstrated the strongest predictive performance in this study.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Imagen por Resonancia Magnética / Protocolos de Quimioterapia Combinada Antineoplásica Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Límite: Adult / Aged / Female / Humans / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Radiology Año: 2016 Tipo del documento: Article
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Imagen por Resonancia Magnética / Protocolos de Quimioterapia Combinada Antineoplásica Tipo de estudio: Clinical_trials / Observational_studies / Prognostic_studies Límite: Adult / Aged / Female / Humans / Middle aged País/Región como asunto: America do norte Idioma: En Revista: Radiology Año: 2016 Tipo del documento: Article