A hierarchical prognostic model for risk stratification in patients with early breast cancer according to 18 F-fludeoxyglucose uptake and clinicopathological parameters

Jongtae Cha, Hyung Seok Park, Dongwoo Kim, Hyun Jeong Kim, Min Jung Kim, Young Up Cho, Mijin Yun

Research output: Contribution to journalArticle

4 Citations (Scopus)


This study was to investigate a hierarchical prognostic model using clinicopathological factors and 18 F-fludeoxyglucose (FDG) uptake on positron emission tomography/computed tomography (PET/CT) for recurrence-free survival (RFS) in patients with early breast cancer who underwent surgery without neoadjuvant chemotherapy. A total of 524 patients with early breast cancer were included. The Cox proportional hazards model was used with clinicopathological variables and maximum standardized uptake value (SUVmax) on PET/CT. After classification and regression tree (CART) modeling, RFS curves were estimated using the Kaplan–Meier method and differences in each risk layer were assessed using the log-rank test. During a median follow-up of 46.2 months, 31 (5.9%) patients experienced recurrence. The CART model identified four risk layers: group 1 (SUVmax ≤6.75 and tumor size ≤2.0 cm); group 2 (SUVmax ≤6.75 and Luminal A [LumA] or TN tumor >2.0 cm); group 3 (SUVmax ≤6.75 and Luminal B [LumB] or human epidermal growth factor receptor 2 [HER2]-enriched] tumor >2.0 cm); group 4 (SUVmax >6.75). Five-year RFS was as follows: 95.9% (group 1), 98% (group 2), 82.8% (group 3), and 85.4% (group 4). Group 3 or group 4 showed worse prognosis than group 1 or group 2 (group 1 vs. group 3: P = 0.040; group 1 vs. group 4: P < 0.001; group 2 vs. group 3: P = 0.016; group 2 vs. group 4: P < 0.001). High SUVmax (>6.75) in primary breast cancer was an independent factor for poor RFS. In patients with low SUVmax, LumB or HER2-enriched tumor >2 cm was also prognostic for poor RFS, similar to high SUVmax.

Original languageEnglish
Pages (from-to)1127-1134
Number of pages8
JournalCancer medicine
Issue number4
Publication statusPublished - 2018 Apr

All Science Journal Classification (ASJC) codes

  • Oncology
  • Radiology Nuclear Medicine and imaging
  • Cancer Research

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