Autoantibody positivity predicts severity of rheumatic immune-related adverse events to immune-checkpoint inhibitors.

OBJECTIVE: Immune-related adverse events (irAEs) due to immune checkpoint inhibitors are responsible for a considerable burden of morbidity and mortality. Predictors of severity of rheumatic irAEs have not been identified yet. The objective of this study was to test the hypothesis whether the presence of autoantibodies could be associated with a more severe and difficult-to-treat clinical phenotype of rheumatic irAEs. METHODS: Patients referred to our centre due to the onset of rheumatic irAEs were prospectively recruited between June 2018 and December 2020. A pre-specified panel of autoantibodies was tested in each patient at baseline visit. All patients were started on glucocorticoids and then followed-up. Conventional or biologic immunosuppressants were started in case of steroid-refractory or relapsing disease. Logistic regression analysis was performed to evaluate the association between the baseline positivity of at least one autoantibody and the necessity of an add-on therapy. RESULTS: Fourty-three patients with rheumatic irAEs were enrolled. Twenty-five (58%) patients had positivity of at least one of the tested autoantibodies. Twenty-two (51%) patients required the start of an additional immunosuppressant during follow-up. The only factor associated with the necessity of an add-on therapy was autoantibody positivity (OR=9.65, 95% CI:2.09-44.56; p-value 0.004). CONCLUSIONS: The presence of autoantibodies in patients with cancer who develop rheumatic irAEs could predict their progression to difficult-to-treat clinical manifestations. This finding might prompt a future therapeutic approach based on a tailored and earlier immunosuppressive treatment in selected cases.

Telematic integration of health data: a practicable contribution.

The patients' clinical and healthcare data should virtually be available everywhere, both to provide a more efficient and effective medical approach to their pathologies, as well as to make public healthcare decision makers able to verify the efficacy and efficiency of the adopted healthcare processes. Unfortunately, customised solutions adopted by many local Health Information Systems in Italy make it difficult to share the stored data outside their own environment. In the last years, worldwide initiatives have aimed to overcome such sharing limitation. An important issue during the passage towards standardised, integrated information systems is the possible loss of previously collected data. The herein presented project realises a suitable architecture able to guarantee reliable, automatic, user-transparent storing and retrieval of information from both modern and legacy systems. The technical and management solutions provided by the project avoid data loss and overlapping, and allow data integration and organisation suitable for data-mining and data-warehousing analysis.