Which prediction models best identify additional axillary disease after a positive sentinel node biopsy for breast cancer?

Breast Cancer Research and Treatment

Volumn 133, Issue 2, 2012, Pages 695-702

  Berrang, Tanya S ^a,b   Lesperance, Mary ^c   Truong, Pauline T ^a,b   Walter, Caroline ^c   Hayashi, Allen H ^b,d   Olivotto, Ivo A ^a,b  

^a BRITISH COLUMBIA CANCER AGENCY   (Canada)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c UNIVERSITY OF VICTORIA   (Canada)

^d VANCOUVER ISLAND HEALTH AUTHORITY   (Canada)

Author keywords

Breast cancer; Prediction; Sentinel lymph node biopsy; Validation

Indexed keywords

ACCURACY; ADULT; AGED; AREA UNDER THE CURVE; ARTICLE; BREAST CANCER; CAMBRIDGE UNIVERSITY MODEL; COMPUTER MODEL; FALSE NEGATIVE RESULT; FEMALE; HUMAN; HUMAN TISSUE; KATZ MODEL; LYMPH NODE DISSECTION; MAJOR CLINICAL STUDY; MAYO CLINIC MODEL; MEMORIAL SLOAN KETTERING CANCER CENTER MODEL; MICROMETASTASIS; NATIONAL SURGICAL ADJUVANT BREAST AND BOWEL PROJECT B32; PREDICTION; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; RISK ASSESSMENT; SENTINEL LYMPH NODE BIOPSY; SENTINEL LYMPH NODE METASTASIS; STANFORD UNIVERSITY MODEL; TENON MODEL;

ADULT; AGED; AGED, 80 AND OVER; AXILLA; BREAST NEOPLASMS; COHORT STUDIES; COMPUTER SIMULATION; FEMALE; HUMANS; INTERNET; LYMPH NODES; LYMPHATIC METASTASIS; MIDDLE AGED; MODELS, STATISTICAL; NEOPLASM GRADING; NEOPLASM STAGING; REPRODUCIBILITY OF RESULTS; ROC CURVE; SENSITIVITY AND SPECIFICITY; SENTINEL LYMPH NODE BIOPSY;

EID: 84863723452     PISSN: 01676806     EISSN: 15737217     Source Type: Journal    
DOI: 10.1007/s10549-012-1991-y     Document Type: Article

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