Predictors of Response to Treatment with First-Generation Somatostatin Receptor Ligands in Patients with Acromegaly
Marques-Pamies, Montserrat (Hospital Municipal de Badalona)
Gil, Joan (Institut Germans Trias i Pujol)
Jordà, Mireia (Institut Germans Trias i Pujol)
Puig Domingo, Manuel (Universitat Autònoma de Barcelona. Departament de Medicina)

Fecha:	2023
Resumen:	Background and Aims: Predictors of first-generation somatostatin receptor ligands (fgSRLs) response in acromegaly have been studied for over 30 years, but they are still not recommended in clinical guidelines. Is there not enough evidence to support their use? This systematic review aims to describe the current knowledge of the main predictors of fgSRLs response and discuss their current usefulness, as well as future research directions. Methods: A systematic search was performed in the Scopus and PubMed databases for functional, imaging, and molecular predictive factors. Results: A total of 282 articles were detected, of which 64 were included. Most of them are retrospective studies performed between 1990 and 2023 focused on the predictive response to fgSRLs in acromegaly. The usefulness of the predictive factors is confirmed, with good response identified by the most replicated factors, specifically low GH nadir in the acute octreotide test, T2 MRI hypointensity, high Somatostatin receptor 2 (SSTR2) and E-cadherin expression, and a densely granulated pattern. Even if these biomarkers are interrelated, the association is quite heterogeneous. With classical statistical methods, it is complex to define reliable and generalizable cut-off values worth recommending in clinical guidelines. Machine-learning models involving omics are a promising approach to achieve the highest accuracy values to date. Conclusions: This survey confirms a sufficiently robust level of evidence to apply knowledge of predictive factors for greater efficiency in the treatment decision process. The irruption of artificial intelligence in this field is providing definitive answers to such long-standing questions that may change clinical guidelines and make personalized medicine a reality.
Ayudas:	Instituto de Salud Carlos III PI22/01364 Ministerio de Economía y Competitividad PMP15/00027 Instituto de Salud Carlos III PMP22/00021
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Lengua:	Anglès
Documento:	Article de revisió ; recerca ; Versió acceptada per publicar
Materia:	Acromegaly ; Prediction ; First-generation somatostatin analogs ; Precision ; Personalized treatment ; Artificial intelligence
Publicado en:	Archives of Medical Research, Vol. 54 Núm. 8 (december 2023) , p. 102924, ISSN 1873-5487

DOI: 10.1016/j.arcmed.2023.102924

36 p, 417.0 KB

El registro aparece en las colecciones:
Documentos de investigación > Documentos de los grupos de investigación de la UAB > Centros y grupos de investigación (producción científica) > Ciencias de la salud y biociencias > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
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