FDG Avidity and Tumor Burden: Survival Outcomes for Patients With Recurrent Breast Cancer

The objective of this study was to assess the value of quantitative PET parameters in the prediction of survival for patients with recurrent breast cancer.

We conducted a retrospective study of 78 women who had recurrent breast cancer identified by biopsy or follow-up examinations from 2000 to 2012. The maximum and peak standardized uptake values (SUVmax and SUVpeak, respectively), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured for each recurrent lesion at primary, nodal, and distant metastatic sites, with the use of the gradient segmentation method. The optimum cutoff point (i.e., the value with the maximum Youden index, defined as sensitivity plus specificity minus 1) was calculated using the ROC curve. The median follow-up duration was 28.5 months (range, 0-94 months). The primary outcome measure was overall survival (OS). Kaplan-Meier survival plots and Cox regression analyses were performed.

The mean (± SD) values noted for the study population were as follows: an SUVmax of 6.70 ± 4.1, an SUVpeak of 5.12 ± 3.4, total lesion glycolysis of all recurrent lesions (TLGtotal) of 359.73 ± 1114.4 g, and metabolic tumor volume of all recurrent lesions (MTVtotal) of 68.04 ± 144.9 mL. The mean OS for patients who died was 25.5 months, whereas for patients who survived, it was 36.7 months (p = 0.04). Univariate analysis showed that age (p = 0.02), optimum SUVmax (p = 0.006), SUVpeak (p = 0.006), and TLGtotal (p = 0.034) were associated with OS; however, none of the factors remained statistically significant in multivariate analysis. Kaplan-Meier survival analysis was performed, and the SUVmax (threshold, 2.9; hazard ratio [HR], 5.2 [95% CI, 1.6-16.7]; p = 0.002), SUVpeak (threshold, 2.34; HR, 4.3 [95% CI, 1.5-12]; p = 0.002), and TLG (threshold, 11.85 g; HR, 2.8 [95% CI, 1.0-7.1]; p = 0.025) were statistically significant predictors of death during follow-up. An integrated risk stratification model with FDG avidity (SUVmax) and MTVtotal divided into three subgroups of patients predicted patient survival outcomes (HR, 2.48 [95% CI, 1.38-4.46]; p = 0.005, by log-rank test).

FDG PET-determined SUVmax, SUVpeak, and TLG values and an integrated risk stratification scheme using FDG avidity and total tumor burden appear to provide prognostic survival information for patients with recurrent breast cancer.