Standardization of immunotherapy adverse events in patient information leaflets and development of an interface terminology for outpatients' monitoring.

INTRODUCTION: Immunotherapy is effective for treating cancer, but it is also associated with a wide spectrum of adverse events. In order to detect them early, the patients need to be monitored at home, between the therapy administrations, e.g., by asking them to report outcomes, usually including symptoms and quality of life measures. For the collected data to be reusable, the symptoms need to be in a standardized form. The aim of this study is to explore the standardization of the information contained in the patient information leaflets (PILs) of immunotherapy drugs, by creating an interface terminology of immunotherapy-related adverse events, which should support a consistent collection of symptoms from the patients. METHODS: PILs contain a significant amount of information in free text, but they mix patient-reportable and clinically assessable events. We extracted a list of patient-reportable adverse events, mapped them to reference terminologies and compared the mapping results to choose the best-performing reference terminology. RESULTS: The PILs standardization led to the extraction of 151 symptoms and 424 terms, including both preferred terms and synonyms in English and Italian. Among the reference terminologies we considered, SNOMED CT allowed us to map all concepts and became, hence, the main reference terminology for the resulting interface terminology. A preliminary validation on the PIL of a new immunotherapy drug showed that our interface terminology already contained all the mentioned symptoms. CONCLUSION: PILs provide a valuable source for determining adverse events. The resulting interface terminology includes Italian and English terms for patient-reportable adverse events for five immunotherapy drugs representative of their category. Further work will be undertaken to evaluate the usability of the interface terminology and the patients' experience and satisfaction with the proposed terms, made available for example through an app, as well as its effectiveness on data quality and quality of care.