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Immune-checkpoint inhibitor use in patients with cancer and pre-existing autoimmune diseases.

Alice TisonSoizic GaraudLaurent ChicheDivi CornecMarie Kostine
Published in: Nature reviews. Rheumatology (2022)
Immune-checkpoint inhibitors (ICIs) have dramatically changed the management of advanced cancers. Designed to enhance the antitumour immune response, they can also cause off-target immune-related adverse events (irAEs), which are sometimes severe. Although the efficacy of ICIs suggests that they could have wide-ranging benefits, clinical trials of the drugs have so far excluded patients with pre-existing autoimmune disease. However, evidence is accumulating with regard to the use of ICIs in this 'at-risk' population, with retrospective data suggesting that they have an acceptable safety profile, but that there is a risk of disease flare or other irAE occurrence. The management of immunosuppressive drugs at ICI initiation in patients with autoimmune disease (or later in instances of disease flare or irAE) remains a question of particular interest in clinical practice, in which there is always a search for the balance between protecting against autoimmunity and ensuring a good tumour response. Although temporary use of immunosuppressants seems safe, prolonged use or use at ICI initiation might hamper the antitumour immune response, prompting clinicians to use the minimal efficient immunosuppressive regimen. However, a new paradigm is emerging, in which inhibitors of TNF or IL-6 could have synergistic effects with ICIs on tumour response, while also preventing severe irAEs. If confirmed, this 'decoupling' effect on toxicity and efficacy could change therapeutic practice in this field. Knowledge of the current use of ICIs in patients with pre-existing autoimmune disease, particularly with regard to the use of immunosuppressive drugs and/or biologic DMARDs, can help to guide clinical practice.
Keyphrases
  • immune response
  • clinical practice
  • clinical trial
  • healthcare
  • multiple sclerosis
  • rheumatoid arthritis
  • oxidative stress
  • dendritic cells
  • machine learning
  • electronic health record
  • inflammatory response
  • cancer therapy