Predictors of Response to Treatment with First-Generation Somatostatin Receptor Ligands in Patients with Acromegaly

被引:7
作者
Marques-Pamies, Montserrat [1 ]
Gil, Joan [2 ,3 ,4 ]
Jorda, Mireia [2 ]
Puig-Domingo, Manel [2 ,3 ,5 ,6 ,7 ]
机构
[1] Hosp Municipal Badalona, Dept Endocrinol, Badalona, Catalonia, Spain
[2] Germans Trias & Pujol Res Inst, Endocrine Res Unit, Badalona, Spain
[3] Inst Salud Carlos III, Network Res Ctr Rare Dis, CIBERER, Unit 747, Madrid, Spain
[4] Hosp Santa Creu & Sant Pau, Res Ctr Pituitary Dis, Dept Endocrinol, IIB SPau, Barcelona, Spain
[5] Germans Trias & Pujol Univ Hosp, Dept Endocrinol & Nutr, Badalona, Spain
[6] Univ Autonoma Barcelona, Dept Med, Barcelona, Spain
[7] Germans Trias & Pujol Res Inst IGTP, Dept Endocrinol & Nutr, Cami Escoles S-N, Badalona 08916, Catalonia, Spain
关键词
Acromegaly; Prediction; First-generation somatostatin analogs; Precision; Personalized treatment; Artificial intelligence; PREOPERATIVE OCTREOTIDE TREATMENT; NONFUNCTIONING PITUITARY-ADENOMAS; LONG-TERM TREATMENT; GROWTH-HORMONE; BIOCHEMICAL RESPONSE; GRANULATION PATTERN; SUPPRESSION TEST; ANALOG THERAPY; TUMOR VOLUME; SIGNAL INTENSITY;
D O I
10.1016/j.arcmed.2023.102924
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
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.(c) 2023 Instituto Mexicano del Seguro Social (IMSS). Published by Elsevier Inc. All rights reserved.
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页数:14
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