Sharing Is Caring? International Society for Pharmacoepidemiology Review and Recommendations for Sharing Programming Code.

John Tazare ORCID logo ; Shirley V Wang ORCID logo ; Rosa Gini ORCID logo ; Daniel Prieto-Alhambra ORCID logo ; Peter Arlett ; Daniel R Morales Leaver ; Caroline Morton ; John Logie ; Jennifer Popovic ; Katherine Donegan ; +3 more... Sebastian Schneeweiss ORCID logo ; Ian Douglas ORCID logo ; Anna Schultze ORCID logo ; (2024) Sharing Is Caring? International Society for Pharmacoepidemiology Review and Recommendations for Sharing Programming Code. Pharmacoepidemiology and drug safety, 33 (9). e5856-. ISSN 1053-8569 DOI: 10.1002/pds.5856
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PURPOSE: There is increasing recognition of the importance of transparency and reproducibility in scientific research. This study aimed to quantify the extent to which programming code is publicly shared in pharmacoepidemiology, and to develop a set of recommendations on this topic. METHODS: We conducted a literature review identifying all studies published in Pharmacoepidemiology and Drug Safety (PDS) between 2017 and 2022. Data were extracted on the frequency and types of programming code shared, and other key open science practices (clinical codelist sharing, data sharing, study preregistration, and stated use of reporting guidelines and preprinting). We developed six recommendations for investigators who choose to share code and gathered feedback from members of the International Society for Pharmacoepidemiology (ISPE). RESULTS: Programming code sharing by articles published in PDS ranged from 1.8% in 2017 to 9.5% in 2022. It was more prevalent among articles with a methodological focus, simulation studies, and papers which also shared record-level data. CONCLUSION: Programming code sharing is rare but increasing in pharmacoepidemiology studies published in PDS. We recommend improved reporting of whether code is shared and how available code can be accessed. When sharing programming code, we recommend the use of permanent digital identifiers, appropriate licenses, and, where possible, adherence to good software practices around the provision of metadata and documentation, computational reproducibility, and data privacy.


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