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Medline ® Abstract for Reference 60

of 'Approach to the patient following treatment for breast cancer'

Whole-body (18)F-FDG PET and conventional imaging for predicting outcome in previously treated breast cancer patients.
Vranjesevic D, Filmont JE, Meta J, Silverman DH, Phelps ME, Rao J, Valk PE, Czernin J
J Nucl Med. 2002;43(3):325.
UNLABELLED: This study was conducted to determine the ability of (18)F-FDG PET and conventional imaging (CI) to predict the outcomes in breast cancer patients who have previously undergone primary treatment.
METHODS: The study population consisted of 61 female patients (median age, 54 y; range, 32--91 y) who were reevaluated with (18)F-FDG PET and CI after treatment. The median interval between the last treatment and PET was 0.4 y (range, 0--16 y). PET was performed within 3 mo of CI (median interval, 25 d; range, 2--84 d). To determine the independent impact of PET on outcome, PET images were reinterpreted in a blind fashion. Availability of clinical information after PET scanning (21 plus minus 12 mo) was required for study inclusion. Study endpoints were clinical evidence of progression of disease or death.
RESULTS: Of 61 patients, 19 (31.1%) had no clinical evidence and 38 (62.3%) had evidence of residual or recurrent disease by the end of follow-up. Four patients (6.6%) had died. The positive and negative predictive values (PPV and NPV, respectively) of PET were 93% and 84%, respectively. CI yielded a PPV of 85% and an NPV of 59%. The prognostic accuracy of single whole-body PET was superior to that of multiple procedures with CI (90% vs. 75%; P<0.05). Kaplan--Meier estimates of disease-free survival in patients with negative PET findings compared with those with positive PET findings revealed a significant difference between the 2 curves (log-rank test = 0.001). Kaplan--Meier estimates of disease-free survival stratified by CI results showed a marginally significant difference between CI-positive and CI-negative patients (log-rank test = 0.04).
CONCLUSION: FDG PET can be used to improve prediction of the clinical outcome of previously treated breast cancer patients relative to what is achievable through CI alone.
Department of Nuclear Medicine, UCLA School of Medicine, Los Angeles, California 90095-6942, USA.