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Open access

Luca Giovanella, Maria Luisa Garo, Domenico Albano, Rainer Görges, and Luca Ceriani


In patients with differentiated thyroid cancer (DTC), recurrences may occur in up to 20% and may have a fatal outcome in 10% of cases. Thyroglobulin doubling time (Tg-DT) values may contribute to predict response to treatment and disease recurrence in DTC patients. This study aimed to address the following questions: (1) Are Tg-DT values indicative of response to treatments in patients with DTC (i.e. ’treatment monitoring’)?; (2) Is Tg-DT predictive of 2-[18F]fluoro-2-deoxy-d-glucose (2-[18F]FDG) PET/CT in patients with DTC?; (3) Are Tg-DT values predictive of DTC prognosis (i.e. ‘prediction’)?


Systematic review and meta-analysis.


Methodology was registered in the PROSPERO database (CRD42021257947). A systematic search was carried out in PubMed, Web Of Science, and Scopus from June to August 2021 without time and language restrictions.


Eleven studies were included for a total of 1421 patients. Positive association between Tg-DT < 1 year and recurrence or disease progression was observed. Tg-DT was found to be related with (2-[18F]FDG) PET/CT results in patients with DTC. The area under the curve was 0.86 (95% CI: 0.83–0.89), sensitivity was 0.84 (0.64;0.94), specificity was 0.71 (0.35; 0.92), DOR was 13.1 (3.1; 55.0), LR+ was 2.9 (1.0; 8.1), LR− was 0.22 (0.1; 0.5). For patients with Tg-DT < 1 year (n  = 247), the survival risk ratio was 2.09 (95% CI: 1.49; 2.94).


Tg-DT values are valuable in predicting response to treatment and disease recurrence in patients with DTC, as well as their overall survival. In addition, Tg-DT significantly increases the detection rate of 2-[18F]-FDG PET/CT.

Open access

Maria Luisa Garo, Désirée Deandreis, Alfredo Campennì, Alexis Vrachimis, Petra Petranovic Ovcaricek, and Luca Giovanella


Current staging and risk-stratification systems for predicting survival or recurrence of patients with differentiated thyroid carcinoma may be ineffective at predicting outcomes in individual patients. In recent years, nomograms have been proposed as an alternative to conventional systems for predicting personalized clinical outcomes. We conducted a systematic review to evaluate the predictive performance of available nomograms for thyroid cancer patients.

Design and methods

PROSPERO registration (CRD42022327028). A systematic search was conducted without time and language restrictions. PICOT questions: population, patients with papillary thyroid cancer; comparator prognostic factor, single-arm studies; outcomes, overall survival, disease-free survival, cancer-specific survival, recurrence, central lymph node metastases, or lateral lymph node metastases; timing, all periods; setting, hospital setting. Risk of bias was assessed through PROBAST tool.


Eighteen studies with a total of 20 prognostic models were included in the systematic review (90,969 papillary thyroid carcinoma patients). Fourteen models were at high risk of bias and four were at unclear risk of bias. The greatest concerns arose in the analysis domain. The accuracy of nomograms for overall survival was assessed in only one study and appeared limited (0.77, 95% CI: 0.75–0.79). The accuracy of nomograms for disease-free survival ranged from 0.65 (95% CI: 0.55–0.75) to 0.92 (95% CI: 0.91–0.95). The C-index for predicting lateral lymph node metastasis ranged from 0.72 to 0.92 (95% CI: 0.86–0.97). For central lymph node metastasis, the C-index of externally validated studies ranged from 0.706 (95% CI: 0.685–0.727) to 0.923 (95% CI: 0.893–0.946).


Our work highlights the extremely high heterogeneity among nomograms and the critical lack of external validation studies that limit the applicability of nomograms in clinical practice. Further studies ideally using commonly adopted risk factors as the backbone to develop nomograms are required.

Significance statement

Nomograms may be appropriate tools to plan treatments and predict personalized clinical outcomes in patients with papillary thyroid cancer. However, the nomograms developed to date are very heterogeneous, and their results seem to be closely related to the specific samples studied to generate the same nomograms. The lack of rigorous external validation procedures and the use of risk factors that sometimes appear to be far from those commonly used in clinical practice, as well as the great heterogeneity of the risk factors considered, limit the ability of nomograms to predict patient outcomes and thus their current introduction in clinical practice.