アブストラクト | OBJECTIVE: To develop a standardizable, reproducible method for creating drug codelists that incorporates clinical expertise and is adaptable to other studies and databases. MATERIALS AND METHODS: We developed methods to generate drug codelists and tested this using the Clinical Practice Research Datalink (CPRD) Aurum database, accounting for missing data in the database. We generated codelists for: (1) cardiovascular disease and (2) inhaled Chronic Obstructive Pulmonary Disease (COPD) therapies, applying them to a sample cohort of 335 931 COPD patients. We compared searching all drug dictionary variables (A) against searching only (B) chemical or (C) ontological variables. RESULTS: In Search A, we identified 165 150 patients prescribed cardiovascular drugs (49.2% of cohort), and 317 963 prescribed COPD inhalers (94.7% of cohort). Evaluating output per search strategy, Search C missed numerous prescriptions, including vasodilator anti-hypertensives (A and B:19 696 prescriptions; C:1145) and SAMA inhalers (A and B:35 310; C:564). DISCUSSION: We recommend the full search (A) for comprehensiveness. There are special considerations when generating adaptable and generalizable drug codelists, including fluctuating status, cohort-specific drug indications, underlying hierarchical ontology, and statistical analyses. CONCLUSIONS: Methods must have end-to-end clinical input, and be standardizable, reproducible, and understandable to all researchers across data contexts. |
ジャーナル名 | JAMIA open |
Pubmed追加日 | 2023/8/31 |
投稿者 | Graul, Emily L; Stone, Philip W; Massen, Georgie M; Hatam, Sara; Adamson, Alexander; Denaxas, Spiros; Peters, Nicholas S; Quint, Jennifer K |
組織名 | School of Public Health, Imperial College London, London W12 0BZ, United Kingdom.;National Heart & Lung Institute, Imperial College London, London W12 0BZ, United;Kingdom.;Usher Institute, University of Edinburgh, Edinburgh EH16 4UX, United Kingdom.;Institute of Health Informatics, University College London, London NW1 2DA,;United Kingdom.;British Heart Foundation Data Science Centre, Health Data Research UK, London NW1;2DA, United Kingdom. |
Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/37649988/ |