{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T02:02:39Z","timestamp":1784512959513,"version":"3.55.0"},"reference-count":66,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T00:00:00Z","timestamp":1783641600000},"content-version":"vor","delay-in-days":9,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Pharmacoepidemiology and Drug"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Negative controls (NCs) are increasingly used in real\u2010world observational studies to detect residual confounding and systematic bias, but their implementation and reporting remain heterogeneous in applied pharmacoepidemiology. We conducted a methodological scoping review to characterize how NCs were selected, implemented, reported, and interpreted in real\u2010world studies evaluating glucagon\u2010like peptide\u20101 receptor agonists (GLP\u20101 RAs) for non\u2010indicated clinical outcomes. We systematically searched PubMed and Embase from database inception through November 2025 and additionally screened reference lists of included studies. Eligible studies used real\u2010world data, applied an observational analytic framework to evaluate GLP\u20101 RAs, focused on non\u2010indicated outcomes, and explicitly incorporated NCs for bias detection, falsification, validation, or empirical calibration. Among 489 records identified, 42 studies met the inclusion criteria. Most studies were cohort\u2010based and were conducted in diabetes\u2010related populations using electronic health records or administrative claims. Negative control outcomes (NCOs) were the dominant approach, whereas negative control exposures (NCEs), positive controls, and empirical calibration were less common. An explicit rationale for NC selection was reported in most studies, but none of the\u00a0included studies explicitly discussed the assumptions underlying NC analysis. Most NC findings were reported as null or consistent with expectations,\u00a0and were primarily used to support validity or robustness rather than to materially alter interpretation. Overall, our findings suggest that the current use of NCs in GLP\u20101 RA observational research has increased, while\u00a0standardized implementation and reporting have lagged. Greater transparency regarding why NCs were selected, what source of bias they were intended to probe, how results were interpreted, and whether they changed analytic conclusions may improve the credibility and interpretability of real\u2010world evidence in this rapidly evolving therapeutic area.<\/jats:p>","DOI":"10.1002\/pds.70420","type":"journal-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T03:41:15Z","timestamp":1783741275000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How Negative Controls Are Used in Pharmacoepidemiology: A Methodological Scoping Review of Real\u2010World Observational Studies of Glucagon\u2010Like Peptide\u20101 Receptor Agonists"],"prefix":"10.1002","volume":"35","author":[{"given":"Zhengxuan","family":"Li","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Health Outcomes and Policy, College of Pharmacy University of Houston  Houston 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