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J Immunother Cancer ; 11(8)2023 08.
Artigo em Inglês | MEDLINE | ID: mdl-37536938

RESUMO

BACKGROUND: Dysthyroidism (DT) is a common toxicity of immune checkpoint inhibitors (ICIs) and prior work suggests that dysthyroidism (DT) might be associated with ICI efficacy. PATIENTS AND METHODS: ConSoRe, a new generation data mining solution, was used in this retrospective study, to extract data from electronic patient records of adult cancer patients treated with ICI at Institut Paoli-Calmettes (Marseille, France). Every DT was verified and only ICI-induced DT was retained. Survival analyses were performed by Kaplan-Meier method (log-rank test) and Cox model. To account for immortal time bias, a conditional landmark analysis was performed (2 months and 6 months), together with a time-varying Cox model. RESULTS: Data extraction identified 1385 patients treated with ICI between 2011 and 2021. DT was associated with improved overall survival (OS) (HR 0.46, (95% CI 0.33 to 0.65), p<0.001), with a median OS of 35.3 months in DT group vs 15.4 months in non-DT group (NDT). Survival impact of DT was consistent using a 6-month landmark analysis with a median OS of 36.7 months (95% CI 29.4 to not reported) in the DT group vs 25.5 months (95% CI 22.8 to 27.8) in the NDT group. In multivariate analysis, DT was independently associated with improved OS (HR 0.49, 95% CI 0.35 to 0.69, p=0.001). After adjustment in time-varying Cox model, this association remained significant (adjusted HR 0.64, 95% CI 0.45 to 0.90, p=0.010). Moreover, patients with DT and additional immune-related adverse event had increased OS compared with patients with isolated DT, with median OS of 38.8 months vs 21.4 months, respectively. CONCLUSION: Data mining identified a large number of patients with ICI-induced DT, which was associated with improved OS accounting for immortal time bias.


Assuntos
Inibidores de Checkpoint Imunológico , Neoplasias , Humanos , Adulto , Inibidores de Checkpoint Imunológico/efeitos adversos , Registros Eletrônicos de Saúde , Estudos Retrospectivos , Neoplasias/tratamento farmacológico , Mineração de Dados
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