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Prognostic Scores for Predicting Recurrence in Patients with Differentiated Thyroid Cancer

  • Somboonporn, Charoonsak (Department of Radiology, Faculty of Medicine, Khon Kaen University)
  • Published : 2016.05.01

Abstract

Background: Differentiated thyroid cancer (DTC) is a cancer group that shares molecular and cellular origin but shows different clinical courses and prognoses. Several prognostic factors have been reported for predicting recurrence for individual patients. This literature review aimed to evaluate prognostic scores for predicting recurrence of DTC. Materials and Methods: A search of the MEDLINE database for articles published until December 2015 was carried out using the terms "thyroid neoplasms AND (recurrent OR persistent) AND (score OR model OR nomogram)". Studies were eligible for review if they indicated the development of prognostic scoring models, derived from a group of independent prognostic factors, in predicting disease recurrence in DTC patients. Results: Of the 308 articles obtained, five were eligible for evaluation. Two scoring models were developed for DTC including both papillary and follicular carcinoma, one for papillary carcinoma, and the other two for papillary microcarcinoma. The number of patients included in the score development cohort ranged from 59 to 1,669. The number of evaluated potential prognostic factors ranged from 4 to 25. Tumor-related factors were the most common factors included in the final scores, with cervical lymph node metastases being the most common. Only two studies showed internal validation of the derived score. Conclusions: There is a paucity of prognostic scores for predicting disease recurrence in patients with DTC, in particular for follicular thyroid carcinoma. Several limitations of the created scores were found. Performance of the scores has not been adequately studied. Comprehensive validation in multiple cohorts is recommended before widespread use.

Keywords

Thyroid neoplasms;recurrence;prognosis;prognostic scores

Acknowledgement

Supported by : Khon Kaen University

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