کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
3908196 1599350 2016 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Predictive value of DCE-MRI for early evaluation of pathological complete response to neoadjuvant chemotherapy in resectable primary breast cancer: A single-center prospective study
ترجمه فارسی عنوان
ارزش اخباری DCE-MRI برای ارزیابی اولیه پاسخ کامل پاتولوژیک به شیمی درمانی نئوادجوانتی در سرطان اولیه پستان رزکسیون: یک مطالعه آینده نگر تک مرکز
کلمات کلیدی
موضوعات مرتبط
علوم پزشکی و سلامت پزشکی و دندانپزشکی زنان، زایمان و بهداشت زنان
چکیده انگلیسی


• The study constructed multi-parameter MRI model for early prediction of pCR.
• The study was prospective, and contained training and validation sample.
• The study identified easily-measured DCE-MRI parameters.
• The study strengthened DCE-MR be taken at early stage of neoadjuvant therapy.
• The study proved the effectiveness of predictive DCE-MRI model for pCR.

ObjectiveThis study proposed to establish a predictive model using dynamic enhanced MRI multi-parameters for early predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer.MethodsIn this prospective cohort study, 170 breast cancer patients treated with NAC were enrolled and were randomly grouped into training sample (136 patients) and validation sample (34 patients). DCE-MRI parameters achieved at the end of the first cycle of NAC were screened to establish the predictive model by using multivariate logistic regression model according to pCR status. Receiver operating characteristic curves were conducted to assess the predictive capability. The association between MRI-predicted pCR and actual pCR in survival outcomes was estimated by using the Kaplan–Meier method with log-rank test.ResultsMultivariate analysis showed ΔAreamax and ΔSlopemax were independent predictors for pCR, odds ratio were 0.939 (95%CI, 0.915 to 0.964), and 0.966 (95%CI, 0.947 to 0.986), respectively. A predictive model was established using training sample as “Y = −0.063*ΔAreamax − 0.034*ΔSlopemax”, a cut-off point of 3.0 was determined. The AUC for training and validation sample were 0.931 (95%CI, 0.890–0.971) and 0.971 (95%CI, 0.923–1.000), respectively. MRI-predicted pCR patients showed similar RFS (p = 0.347), DDFS (p = 0.25) and OS (p = 0.423) with pCR patients.ConclusionThe multi-parameter MRI model can be potentially used for early prediction of pCR status at the end of the first NAC cycle, which might allow timely regimen refinement before definitive surgical treatment.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: The Breast - Volume 30, December 2016, Pages 80–86
نویسندگان
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