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A data-driven approach to refine predictions of differentiated thyroid cancer outcomes: a prospective multicenter study.

Giorgio Grani,Michele Gentili,Federico Siciliano, Domenico Albano,Valentina Zilioli,Silvia Morelli,Efisio Puxeddu,Maria Chiara Zatelli,Irene Gagliardi,Alessandro Piovesan,Alice Nervo,Umberto Crocetti,Michela Massa,Maria Teresa Samà,Chiara Mele,Maurilio Deandrea,Laura Fugazzola,Barbara Puligheddu,Alessandro Antonelli,Ruth Rossetto,Annamaria D'Amore,Graziano Ceresini,Roberto Castello,Erica Solaroli,Marco Centanni,Salvatore Monti,Flavia Magri,Rocco Bruno,Clotilde Sparano,Luciano Pezzullo,Anna Crescenzi,Caterina Mian,Dario Tumino,Andrea Repaci,Maria Grazia Castagna,Vincenzo Triggiani,Tommaso Porcelli,Domenico Meringolo,Laura Locati,Giovanna Spiazzi,Giulia Di Dalmazi,Aris Anagnostopoulos,Stefano Leonardi,Sebastiano Filetti,Cosimo Durante

The Journal of clinical endocrinology and metabolism（2023）

Cited 1|Views80
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Abstract
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.
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Key words
clinical practice,differentiated thyroid cancer,evidence-based guidelines,risk stratification
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