Key Characteristics of Database Studies on Drug Effectiveness in the Postmarketing Stage: A Systematic Review

In recent years, real-world data (RWD) have been actively used in the field of pharmaceutical research. Database (DB) study, one of the observational studies using RWD, is a comprehensive, continuous, and rapid research method that plays an important role in the postmarketing stage of drugs, although the interpretation of the results may be limited. DB studies are often focused on drug safety, and previous research reviewing DB studies on drug effectiveness across different disease areas have been limited.

The objective of this review was to reveal the current status of DB studies on drug effectiveness in various therapeutic areas and to provide information that allows researchers to consider conducting appropriate DB studies on drug effectiveness in the postmarketing stage.

For this systematic review, we searched Embase and MEDLINE for DB studies on drug effectiveness published between 1 January 2018 and 31 December 2019. We reviewed the title, abstract, and methods to identify studies on drug effectiveness using medical information DBs, and excluded non-medical studies, studies on non-drug, and studies on drug safety, actual use, or cost outcomes that did not include any effectiveness outcomes. The name and type of the DB (administrative claims DB, clinical DB, pharmacy DB, and DB linkage), study design, comparison group, type of outcome, and presence or absence of reference to the outcome definition were extracted and summarized according to disease areas.

We obtained 225 articles on DB studies on drug effectiveness using DBs that integrate large-scale medical data for secondary use across different disease areas. Among the DB classifications, administrative claims DBs (70%, 158/225) were most commonly used, while pharmacy DBs were used in only three studies. The largest number of reported studies were associated with cardiovascular, respiratory, and infectious diseases. Outcomes were often inpatient diagnosis, and some ideas included defining effectiveness based on drug use. While various outcomes were uniformly used in studies for the treatment of infectious diseases and respiratory organs, death (overall survival [OS]) and drug continuation (progression-free survival [PFS]) in patients with cancer, laboratory values in the endocrine system (mainly diabetes) were used as the main outcomes. Outcome validation within the article was limited. New user design (32%, 73/225), propensity score analysis (58%, 131/225), and sensitivity analysis (40%, 90/225) were used as measures to reduce bias in these studies. Sixty-eight studies (30%, 68/225) were supported by pharmaceutical companies.

This systematic review summarized the status of cross-disease research articles on DB studies on drug effectiveness. While considering the strengths and limitations of DB studies, we hope that our comprehensive results would help to promote appropriate DB studies on drug effectiveness in the postmarketing stage.