Data reduction when aggregating information about harms associated with medical interventions

• Published in: BMJ mental health 2024-03, Vol.27 (1), p.e301025
• Main Authors: Ostinelli, Edoardo Giuseppe, Furukawa, Toshi A
• Format: Article
• Language: English
• Subjects: Data integrity; Depression & mood disorders; Editorial; Flooring; Hospitalization; Information sharing; Mental depression; Systematic review
• ISSN: 2755-9734; 2755-9734
• DOI: 10.1136/bmjment-2024-301025

Correspondence to Dr Edoardo Giuseppe Ostinelli, Department of Psychiatry, University of Oxford, Oxford, UK; [e-mail] In interpreting and aggregating data in published reports, readers and authors must be aware that some data loss and transformation are inevitable in the process (figure 1).1 Kamp and colleagues recently examined the beneficial and adverse event (AE) profiles of tricyclic antidepressants in a systematic review of available evidence from randomised controlled trials. According to study-specific requirements, data may be flattened into distinct formats (data flattening), subsequently reported as an aggregate value (published data). An AE is considered serious and thus cause regulatory implications when it ‘results in death, is life-threatening, requires inpatient hospitalisation or prolongation of existing hospitalisation, results in persistent or significant disability/incapacity, or is a congenital anomaly/birth defect’, with each criterion being evaluated at a patient and event level.3–5 For instance, ‘the term life-threatening in the definition of serious refers to an event in which the patient was at risk of death at the time of the event, rather than an event which hypothetically might have caused death if it were more severe’. When observed clinical information (source event) is translated into source data at the collection site, how data are measured will set implications downstream (figure 1).