Presentation (CTI)

OBJECTIVES: Social Media listening (SML) is a growing method of gathering patient experience data (PED) acknowledged by the US Food and Drug Administration, often employed for oncological conditions. We aimed to map the research landscape of cancer PED captured using SML, including who conducts research, why, and the types and volume of data gathered.
METHODS: We conducted a review according to the PRISMA Extension for Scoping Reviews checklist. We searched six databases including PubMed and Embase for studies published from inception until October 2024. Abstract and full-text screening and data extraction were completed by one investigator; at each stage a second investigator assessed 20% of studies. We synthesised the study characteristics (e.g. funding) and mapped the data gathered via SML to six a priori specified categories.
RESULTS: The database search yielded 375 studies; 48 met the inclusion criteria. Half (24/48) were published between January 2022 and October 2024. 54% (26/48) studies received or reported no funding, 15/48 (31%) were industry-funded. 21/48 (44%) reported (some) patient-specific demographics. The cancers most frequently analysed were breast (33%, 16/48) and leukaemia (15%, 7/48). The studies contained SML data on: (i) impact on patients’ lives/disease burden (92%, 44/48), (ii) treatment/medication experiences (excluding side effects) (88%, 42/48), (iii) treatment/medication side effects (39/48, 81%), (iv) unmet needs (13/48, 27%), (v) priorities for disease management (9/48, 19%), (vi) ranking/trade-offs of potential improvements/treatment modalities (6/48, 13%). 32/48 (67%) studies reported the number of patient-specific data points gathered (e.g. individual tweets or posts); these ranged from 14 to 1,620,755 (average 75,474, median 327).
CONCLUSIONS: Using SML to gather oncology-specific PED is employed by researchers in heterogenous ways. This data often relates to general disease impacts and treatment experiences/side effects. SML-specific reporting standards could improve consistency and thoroughness of published studies and their usability.