Abstract 2137
Background
The management of papillary thyroid carcinoma (PTC) should be decided by Risk-adapted approach. However, intermediated risk PTC needs to be stratified more precisely. Otherwise, the utility of 18F-FDG PET images in patients with PTC is restrictive. The aim of this study was to investigate the prognostic value of Metabolic Tumor Volume (MTV) measured on 18F-FDG PET images in patients with papillary thyroid carcinoma treated with surgery.
Methods
We retrospectively analyzed 102 patients with PTC who underwent 18F-FDG PET/CT between Feburary 2009 and June 2017 at Osaka University Medical School Hospital for initial staging before surgery. We evaluated the association of MTV of primary tumor (T-MTV) with relapse-free survival (RFS) using Cox regression analysis. Receiver operating characteristic (ROC) curves were used to estimate the optimal cut-off values for T-MTV. We also conducted recursive partitioning analyses to offer a novel risk stratification system.
Results
The 3-year RFS for all patients were 81.2% with median follow-up of 42 months (range 11-111). In Cox model, T-MTV (Hazard Ratio, 1.23; 95% CI, 1.08 to 1.38; P = 0.002) was significantly associated with RFS. ROC analyses showed that the optimal cutoff value of T-MTV was 10.3ml. We classified the patients as having a low, intermediate, or high risk of relapse or death on the basis of T-MTV and lymph node metastasis.
Conclusions
MTV of primary tumor was a significant prognostic factor for RFS in patients with PTC treated with surgery. Incorporation of T-MTV into staging may lead to a better risk stratification.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
4732 - Progesterone Receptor Isoform Ratio Dictates Antiprogestins/Progestins Effects on Metastatic Breast Cancer Models
Presenter: Maria Abascal
Session: Poster Display session 2
Resources:
Abstract
5737 - PAM50 and CGH-array genomic characterization of HER2-Equivocal Breast Cancers defined by the 2018 ASCO/CAP recommendations.
Presenter: Carine Ngo
Session: Poster Display session 2
Resources:
Abstract
1096 - OncotypeDX® predictive nomogram for recurrence score output: a machine learning system based on quantitative immunochemistry analysis - ADAPTED01
Presenter: Fabio Marazzi
Session: Poster Display session 2
Resources:
Abstract
5426 - Geriatric parameters predict both disease-related and patient-reported outcomes in older patients with breast cancer
Presenter: Willeke van der Plas-Krijgsman
Session: Poster Display session 2
Resources:
Abstract
5865 - Patients with a 21-gene assay in South East London differ from the TAILORx trial population
Presenter: Charalampos Gousis
Session: Poster Display session 2
Resources:
Abstract
1312 - Predictive tools in adjuvant breast cancer – what is the standard of evidence supporting their utility? A literature review examining validation of Adjuvant!, Cancermath and NHS Predict
Presenter: Alice Loft
Session: Poster Display session 2
Resources:
Abstract
2445 - Oncologic outcome of invasive lobular carcinoma: Is it different from that of invasive ductal carcinoma?
Presenter: Hee Jun Choi
Session: Poster Display session 2
Resources:
Abstract
2476 - Pathologic response and survival efficacy in patients with initial nodal involvement after neoadjuvant chemotherapy in early breast cancer
Presenter: SERAFIN MORALES Murillo
Session: Poster Display session 2
Resources:
Abstract
3761 - Chemotherapy-induced amenorrhea: prognostic impact on premenopausal Egyptian patients with breast cancer
Presenter: Khaled Abdel Karim
Session: Poster Display session 2
Resources:
Abstract
4687 - Predicting the presence of breast cancer using circulating small RNA in the serum
Presenter: Yumiko Koi
Session: Poster Display session 2
Resources:
Abstract