Data retrieval and harmonisation for individual participant data meta-analysis in the context of a neglected tropical...

Individual participant data meta-analysis (IPD-MA) is the gold-standard approach for evidence synthesis. Poverty-related infectious diseases, a context in which standalone trials often have small sample sizes and consequently observe relatively few treatment failures, can benefit from this approach.

In collaboration with the global research community, the Infectious Diseases Data Observatory (IDDO) has developed a data platform for visceral leishmaniasis (VL)-a neglected tropical disease (NTD), primarily to facilitate IPD-MA aimed at addressing questions of public health importance. Initially, a systematic review (SR) was undertaken to identify relevant trials since 1980 and study authors were invited to collaboratively develop the platform and participate in two IPD-MAs. IPD non-retrievability (data loss) was tracked and defined as unsuccessful attempts to contact study authors, or when the authors explicitly stated data loss, or declined participation.

The SR identified 147 VL trials (1983-2019), of which IPD was shared to the IDDO platform from 31 (21.1%). Reasons for data non-retrievability of 116 studies included: authors' retirement (n=42, 36.2%), data were lost (n=30, 25.9%), authors' non-response (n=22, 19.0%), authors were no longer contactable (n=17, 14.7%) and a lack of clarity over data ownership (n=5, 4.3%). The median sample size was 226 (IQR: 120-542, range: 30-1,143) for retrieved studies compared with 81 (IQR: 34-151, range: 7-3,126) for non-retrieved studies. No IPD were retrieved from trials published pre-2000 (0%, 0/63). Following solicitation, the median time to complete data harmonisation was 633 days (n=29 studies).

Data solicitation and harmonisation steps remain underappreciated challenges in undertaking IPD-MA, particularly for NTDs where resources are severely limited. A critical mass of IPD from historical VL trials is no longer retrievable. It is imperative that further loss of such valuable data from ongoing and future trials is prevented.