Biagetti, BetinaMarques, PedroFerrer, RosaCardoso, Luis MiguelVenegas Moreno, EvaFajardo-Montañana, CarmenGonzález-Fernández, LauraPérez Pena, Marta MaríaGarcía-Centeno, RogelioLozano Aida, ClaudiaNovoa-Testa, IriaPascual-Corrales, EiderSanchón, RaúlGuerrero-Pérez, FernandoOliva Rodríguez, RosarioRodríguez-Jiménez, BeatrizOllero García-Agulló, María DoloresIrigaray Echarri, AnaSimó-Servat, AndreuMoure Rodríguez, María DoloresCalatayud, MaríaVillar-Taibo, RocíoTenorio-Jiménez, CarmenNovo-Rodríguez, CristinaGonzález-Molero, InmaculadaIglesias, PedroBlanco, ConcepciónVidal-Ostos De Lara, FernandoAulinas, AnnaAsla, QueraltPaja Fano, MiguelAbellán Galiana, PabloCordido, FernandoMenéndez Torre, EdelmiroCámara, RosaSarria-Estrada, SilvanaAznar, SilviaLamas, CristinaÁlvarez-Escola, CristinaBernabeu Morón, IgnacioHanzu, Felicia AlexandraMarazuela, MónicaPuig-Domingo, ManuelAraújo-Castro, Marta2026-03-272026-03-272025-10-14Biagetti B, Marques P, Ferrer R, Cardoso LM, Moreno EV, Fajardo-Montañana C, Gonzalez-Fernandez L, Pérez Pena MM, García-Centeno R, Lozano-Aida C, Novoa-Testa I, Pascual-Corrales E, Sánchón R, Guerrero-Pérez F, Rodríguez RO, Jiménez BR, Ollero García MD, Echarri AI, Simó-Servat A, Moure Rodríguez MD, Calatayud M, Villar-Taibo R, Tenorio-Jimenéz C, Novo-Rodríguez C, Molero IG, Iglesias P, Blanco C, Vidal-Ostos De Lara F, Aulinas A, Asla Roca Q, Paja M, Abellán Galiana P, Cordido F, Menéndez Torre E, Cámara R, Sarria-Estrada S, Aznar Rodríguez S, Lamas C, Alvarez-Escola C, Bernabéu I, Hanzu F, Marazuela M, Puig-Domingo M, Araujo-Castro M. Growth hormone assay-adjusted standardization reveals distinct clinical phenotypes in acromegaly. Endocr Pract. 2026 Feb;32(2):236-245.1934-2403https://hdl.handle.net/2183/47830Multicenter study[Abstract] Objective: To identify distinct clinical phenotypes in acromegaly based on growth hormone (GH) assay standardization and unsupervised machine learning. Methods: This was a multicenter cross-sectional analysis of 416 patients diagnosed with acromegaly from 2010 onward. Patients were stratified according to baseline serum GH levels standardized to the assay-specific upper limit of normal (GHxULN) using a binary classification (GH-B: <1.0×ULN vs ≥1.0×ULN) and a four-tier classification (GH-4: <0.25, 0.25-0.99, 1.0-9.9, ≥10×ULN). Unsupervised cluster analysis included age, GHxULN, insulin-like growth factor 1 (IGF-1)xULN, tumor diameter, and T2-weighted signal intensity. Results: Overall, 36% of patients had GH levels within the normal reference range for their assay (GH-B <1.0×ULN). Microadenomas (23.1%) were more frequent in older patients and associated with lower GH/IGF-1 levels. Across GH-4 categories, significant gradients were observed for age (z = -5.34, P < .001), tumor size (z = 8.01, P < .001), IGF-1 (z = 9.00, P < .001), and symptom duration (z = 4.34, P < .001). Higher GH categories were associated with greater odds of arthropathy (odds ratio 3.5, P = .015 for 1.0-9.9×ULN and odds ratio 6.58, P = .002 for ≥10×ULN). Cluster analysis revealed 3 phenotypes: cluster 1 (49.0%) [older age, lower GH/IGF-1, intermediate tumor size]; cluster 2 (44.4%) [intermediate age, moderate biochemical activity, smaller tumors]; cluster 3 (6.6%) [younger age, markedly elevated GH/IGF-1, large aggressive tumors]. Conclusion: GH standardization to assay-specific ULN reveals clinically meaningful phenotypes in acromegaly that correlate with age, tumor characteristics, and disease severity (particularly arthropathy). GHxULN complements IGF-1 by capturing tumor secretory activity, and this stratification approach may support more individualized clinical decision-making.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/IGF-1AcromegalyGrowth hormoneMicromegalyPhenotypesPituitaryjournal articleembargoed access10.1016/J.EPRAC.2025.10.006