2021
DOI: 10.3389/fendo.2021.677919
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Clinical and Radiological Predictors of Biochemical Response to First-Line Treatment With Somatostatin Receptor Ligands in Acromegaly: A Real-Life Perspective

Abstract: BackgroundFirst-generation somatostatin receptor ligands (fg-SRLs) represent the first-line medical treatment for acromegaly, recommended in patients with persistent disease after neurosurgery, or when surgical approach is not feasible. Despite the lack of strong recommendations from guidelines and consensus statements, data from national Registries report an increasing use of medical therapy as first-line treatment in acromegaly.ObjectiveWe retrospectively evaluated the potential role of a large number of cli… Show more

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Cited by 18 publications
(8 citation statements)
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References 55 publications
(83 reference statements)
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“…Younger age at diagnosis appears to be the most important determinant of not responding, and a significant inverse association was seen between GH concentration at diagnosis and absolute IGF-1 reduction after treatment. Recently, Nista et al (36) retrospectively evaluated the potential predictors of SRL response in a cohort of 55 naïve acromegaly patients aged 57 (IQR: 45-63) and found that dichotomized age, IGF1 ULN at diagnosis, and T2-hypointense MRI signal of the tumor were reliable predictors of SRL response. However, this study was not fully comparable to ours, as patients were much younger.…”
Section: Discussionmentioning
confidence: 99%
“…Younger age at diagnosis appears to be the most important determinant of not responding, and a significant inverse association was seen between GH concentration at diagnosis and absolute IGF-1 reduction after treatment. Recently, Nista et al (36) retrospectively evaluated the potential predictors of SRL response in a cohort of 55 naïve acromegaly patients aged 57 (IQR: 45-63) and found that dichotomized age, IGF1 ULN at diagnosis, and T2-hypointense MRI signal of the tumor were reliable predictors of SRL response. However, this study was not fully comparable to ours, as patients were much younger.…”
Section: Discussionmentioning
confidence: 99%
“…We recently developed a machine learning based prediction model, including clinical (age and sex), biochemical (GH and IGF-I levels), and immunohistochemical (SST2 and SST5 expression and cytokeratin granulation pattern) features, that predicted response to fg-SRL with an accuracy of 86.3%, positive predictive value of 83.3% and negative predictive value of 87.5% [ 42 ]. Another recent study evaluated clinical, biochemical, and imaging parameters, and found that age was negatively correlated with IGF-I reduction, whereas IGF-I levels at diagnosis and tumor T2 hypointensity at MRI were positively correlated [ 43 ].…”
Section: Discussionmentioning
confidence: 99%
“…The main clinical predictors of fg-SRL resistance recognized in the literature include: male sex [5,13,14], young age [5,[13][14][15][16][17] and tumor hyperintensity on T2-weighted magnetic resonance imaging (MRI) scans [1,7,13,15,16]; however, IGF-I and r-GH values at diagnosis also deserve to be taken into consideration [5,8,[13][14][15][16][17]. Furthermore, the most relevant histological and molecular characteristics identified so far are the following: the grade of expression of the type 2 somatostatin receptors (SSTR2) [1,7,8,15,18], the pathological classification based on cytoplasmic granulation and keratin pattern analyzed by the CAM5.2 antibody [1,7,8,15], the proliferation index Ki-67 [7,18,19] and the presence of aryl hydrocarbon receptor-interacting protein (AIP) gene mutation [8,20,21].…”
Section: Of 12mentioning
confidence: 99%