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Thyroglobulin measurement is the most powerful outcome predictor in differentiated thyroid cancer: a decision tree analysis in a European multicenter series.
Giovanella, Luca; Milan, Lisa; Roll, Wolfgang; Weber, Manuel; Schenke, Simone; Kreissl, Michael; Vrachimis, Alexis; Pabst, Kim; Murat, Tuncel; Petranovic Ovcaricek, Petra; Campenni, Alfredo; Görges, Rainer; Ceriani, Luca.
Afiliação
  • Giovanella L; Nuclear Medicine, Gruppo Ospedaliero Moncucco, Lugano, Switzerland.
  • Milan L; Nuclear Medicine, University Hospital Zürich, Zürich, Switzerland.
  • Roll W; Nuclear Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland.
  • Weber M; Nuclear Medicine, University Hospital Münster, Münster, Germany.
  • Schenke S; Nuclear Medicine, 39081 University Hospital Essen , Essen, Germany.
  • Kreissl M; Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany.
  • Vrachimis A; Nuclear Medicine, University Hospital Magdeburg, Magdeburg, Germany.
  • Pabst K; Nuclear Medicine, German Oncology Center, Limassol, Cyprus.
  • Murat T; Nuclear Medicine, 39081 University Hospital Essen , Essen, Germany.
  • Petranovic Ovcaricek P; Nuclear Medicine, Hacettepe University, Ankara, Türkiye.
  • Campenni A; Oncology and Nuclear Medicine, University Hospital Center "Sestre milosrdnice", Zagreb, Croatia.
  • Görges R; Nuclear Medicine, University Hospital Messina, Messina, Italy.
  • Ceriani L; Nuclear Medicine, 39081 University Hospital Essen , Essen, Germany.
Clin Chem Lab Med ; 2024 May 07.
Article em En | MEDLINE | ID: mdl-38706105
ABSTRACT

OBJECTIVES:

An accurate prognostic assessment is pivotal to adequately inform and individualize follow-up and management of patients with differentiated thyroid cancer (DTC). We aimed to develop a predictive model for recurrent disease in DTC patients treated by surgery and 131I by adopting a decision tree model.

METHODS:

Age, sex, histology, T stage, N stage, risk classes, remnant estimation, thyroid-stimulating hormone (TSH), thyroglobulin (Tg), administered 131I activities and post-therapy whole body scintigraphy (PT-WBS) were identified as potential predictors and put into regression algorithm (conditional inference tree, c-tree) to develop a risk stratification model for predicting persistent/recurrent disease over time.

RESULTS:

The PT-WBS pattern identified a partition of the population into two subgroups (PT-WBS positive or negative for distant metastases). Patients with distant metastases exhibited lower disease-free survival (either structural, DFS-SD, and biochemical, DFS-BD, disease) compared to those without metastases. Meanwhile, the latter were further stratified into three risk subgroups based on their Tg values. Notably, Tg values >63.1 ng/mL predicted a shorter survival time, with increased DFS-SD for Tg values <63.1 and <8.9 ng/mL, respectively. A comparable model was generated for biochemical disease (BD), albeit different DFS were predicted by slightly different Tg cutoff values (41.2 and 8.8 ng/mL) compared to DFS-SD.

CONCLUSIONS:

We developed a simple, accurate and reproducible decision tree model able to provide reliable information on the probability of structurally and/or biochemically persistent/relapsed DTC after a TTA. In turn, the provided information is highly relevant to refine the initial risk stratification, identify patients at higher risk of reduced structural and biochemical DFS, and modulate additional therapies and the relative follow-up.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Chem Lab Med Assunto da revista: QUIMICA CLINICA / TECNICAS E PROCEDIMENTOS DE LABORATORIO Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Clin Chem Lab Med Assunto da revista: QUIMICA CLINICA / TECNICAS E PROCEDIMENTOS DE LABORATORIO Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Suíça