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Eosinophil counts can be a predictive marker of immune checkpoint inhibitor-induced secondary adrenal insufficiency: a retrospective cohort study.

Shinobu TakayasuSatoru MizushiriYutaka WatanukiSatoshi YamagataMari UsutaniYuki NakadaYuko AsariShingo MurasawaKazunori KageyamaMakoto Daimon
Published in: Scientific reports (2022)
Immune checkpoint inhibitors (ICIs) treatment can result in endocrine immune-related adverse events (irAEs), including pituitary dysfunction. Quick diagnosis of secondary adrenal insufficiency (AI) is challenging because no universal definition of ICI-induced secondary AI has been agreed. The aim of this study was to clarify the clinical features of ICI-induced secondary AI that can be used for screening in standard clinical practice. This retrospective study was performed using the medical records of patients who received ICIs at Hirosaki University Hospital between 1 September 2014 and 31 January 2021. Longitudinal clinical data of patients who developed AI were analyzed and compared with the data of thyroid irAEs. Regression analysis showed a significant correlation between ICI-induced secondary AI and absolute or relative eosinophil counts at pre-onset of AI, as well as differences or rate of increase in eosinophil counts at baseline and at pre-onset. Absolute eosinophil counts > 198.36/µL or relative eosinophil counts > 5.6% at pre-onset, and a difference of 65.25/µL or a rate of eosinophil count increase of 1.97 between the baseline and at pre-onset showed the best sensitivity and specificity. This is the first report to demonstrate that eosinophil counts can be a predictor of ICI-induced secondary AI.
Keyphrases
  • artificial intelligence
  • high glucose
  • diabetic rats
  • peripheral blood
  • drug induced
  • healthcare
  • oxidative stress
  • cross sectional
  • deep learning
  • stress induced
  • smoking cessation