Influence of body mass index at diagnosis on outcome of thyroid cancer in children and adolescents

A novel risk stratification model based on tumor size and multifocality to predict recurrence in pediatric PTC: comparison with adult PTC

Background

Pediatric papillary thyroid cancer presents with a more advanced stage of disease than adult PTC; and it is more likely to be aggresive and distant metastases, although the survival rate is high.

Methods

A retrospective observational study was performed in children and adults with PTC. Fisher's exact, chi-square, and rank-sum tests were used to examine the differences. Univariate and multivariate Cox regression analyses were applied to determine the possible risk factors for prognosis. A Kaplan-Meier curve analysis was performed to investigate the relationship between the clinicopathological characteristics and recurrence rate.

Results

The study involved 156 children and 1,244 adults with PTC. Compared to the group without recurrence, proportions of tumors measuring > 1 cm (48.3% vs. 90.9%) and multifocality (30.3% vs. 63.6%) were higher, N1b stage occurred more frequently (33.8% vs. 100%). However, among adult PTC patients, those with recurrence were older (76.1% vs. 59.4%) than those without recurrence. Risk factors for pediatric PTC recurrence included tumor size and multifocality. However, in adult PTC, the risk factor was LLNM. The newly constructed Stratification.N showed better performance, as illustrated by the fact that patients who were classified into Stratification.N 3 showed an obviously poorer prognosis (P=0.01 and P=0.00062), especially in those aged >14 years (P=0.0052).

Conclusion

Compared with adult PTC, pediatric PTC showed unique characteristics in terms of clinical pathology and recurrence. Tumor size and multifocality were strong risk factors for pediatric PTC. Accordingly, the novel proposed risk stratification method could effectively predict the recurrence of pediatric PTC.

Prognostic Value of Tumor Multifocality in Pediatric Papillary Thyroid Carcinoma: A Real-Life Multicentric Study

OBJECTIVE

To investigate the association of multifocality with clinical outcomes in pediatric papillary thyroid cancer.

STUDY DESIGN

Multicenter retrospective study of prospectively collected data.

SETTING

Tertiary referral center.

METHODS

This study included patients 18 years or younger who underwent total thyroidectomy and radioiodine ablation for papillary thyroid carcinoma (PTC) between 2005 and 2020 at 3 tertiary adult and pediatric hospitals in China. For disease-free survival (DFS), events were defined as persistent and/or recurrent diseases. The primary outcome was the association of tumor multifocality and DFS, assessed using Cox proportional hazards regression models.

RESULTS

One hundred and seventy-three patients (median age 16 years [range, 5-18 years]) were recruited. Multifocal diseases were seen in 59 patients (34.1%). After a median follow-up of 57 (range, 12-193 months) months, 63 (36.4%) patients had persistent diseases. There was a significant association between tumor multifocality and decreased DFS on univariable analysis (hazard ratio [HR] = 1.90, p = .01), yet it was nonsignificant after multivariate adjustment (HR = 1.20, p = .55). In a subgroup analysis of 132 pediatric patients with clinically M0 PTC, neither unadjusted HR (2.21, p = .06) nor adjusted HR (1.70, p = .27) of multifocal PTC was significantly higher in comparison to unifocal PTC.

CONCLUSION

In this highly selective surgical pediatric patient cohort with PTC, tumor multifocality was not an independent risk factor for decreased DFS.

A Data-Driven Approach to Refine Predictions of Differentiated Thyroid Cancer Outcomes: A Prospective Multicenter Study

CONTEXT

The risk stratification of patients with differentiated thyroid cancer (DTC) is crucial in clinical decision making. The most widely accepted method to assess risk of recurrent/persistent disease is described in the 2015 American Thyroid Association (ATA) guidelines. However, recent research has focused on the inclusion of novel features or questioned the relevance of currently included features.

OBJECTIVE

To develop a comprehensive data-driven model to predict persistent/recurrent disease that can capture all available features and determine the weight of predictors.

METHODS

In a prospective cohort study, using the Italian Thyroid Cancer Observatory (ITCO) database (NCT04031339), we selected consecutive cases with DTC and at least early follow-up data (n = 4773; median follow-up 26 months; interquartile range, 12-46 months) at 40 Italian clinical centers. A decision tree was built to assign a risk index to each patient. The model allowed us to investigate the impact of different variables in risk prediction.

RESULTS

By ATA risk estimation, 2492 patients (52.2%) were classified as low, 1873 (39.2%) as intermediate, and 408 as high risk. The decision tree model outperformed the ATA risk stratification system: the sensitivity of high-risk classification for structural disease increased from 37% to 49%, and the negative predictive value for low-risk patients increased by 3%. Feature importance was estimated. Several variables not included in the ATA system significantly impacted the prediction of disease persistence/recurrence: age, body mass index, tumor size, sex, family history of thyroid cancer, surgical approach, presurgical cytology, and circumstances of the diagnosis.

CONCLUSION

Current risk stratification systems may be complemented by the inclusion of other variables in order to improve the prediction of treatment response. A complete dataset allows for more precise patient clustering.