医学
肢端肥大症
内科学
回顾性队列研究
队列
激素
生长激素
作者
Sabrina Chiloiro,Rossana Moroni,Antonella Giampietro,Flavia Angelini,Marco Gessi,Liverana Lauretti,Pier Paolo Mattogno,Rosalinda Calandrelli,Tommaso Tartaglione,Angela Carlino,Simona Gaudino,Alessandro Olivi,Guido Rindi,Laura De Marinis,Alfredo Pontecorvi,Francesco Doglietto,Antonio Bianchi
标识
DOI:10.1210/clinem/dgad673
摘要
Abstract Context The prompt control of acromegaly is a primary treatment aim for reducing related disease morbidity and mortality. First-generation somatostatin receptor ligands (fg-SRLs) are the cornerstone of medical therapies. A non-negligible number of patients do not respond to this treatment. Several predictors of fg-SRL response were identified, but a comprehensive prognostic model is lacking. Objective We aimed to design a prognostic model based on clinical and biochemical parameters, and pathological features, including data on immune tumor microenvironment. Methods A retrospective, monocenter, cohort study was performed on 67 medically naïve patients with acromegaly. Fifteen clinical, pathological, and radiological features were collected and analyzed as independent risk factors of fg-SRLs response, using univariable and multivariable logistic regression analyses. A stepwise selection method was applied to identify the final regression model. A nomogram was then obtained. Results Thirty-seven patients were fg-SRLs responders. An increased risk to poor response to fg-SRLs were observed in somatotropinomas with absent/cytoplasmatic SSTR2 expression (OR 5.493 95% CI 1.19-25.16, P = .028), with low CD68+/CD8+ ratio (OR 1.162, 95% CI 1.01-1.33, P = .032). Radical surgical resection was associated with a low risk of poor fg-SRLs response (OR 0.106, 95% CI 0.025-0.447 P = .002). The nomogram obtained from the stepwise regression model was based on the CD68+/CD8+ ratio, SSTR2 score, and the persistence of postsurgery residual tumor and was able to predict the response to fg-SRLs with good accuracy (area under the curve 0.85). Conclusion Although our predictive model should be validated in prospective studies, our data suggest that this nomogram may represent an easy to use tool for predicting the fg-SRL outcome early.
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