From clinical trials to clinical practice: How long are drugs tested and then used by patients?

Abstract Objective Evidence is scarce regarding the safety of long-term drug use, especially for drugs treating chronic diseases. To bridge this knowledge gap, this research investigated the differences in drug exposure between clinical trials and clinical practice. Materials and Methods We extracted drug follow-up times from clinical trials in ClinicalTrials.gov and compared the difference between clinical trials and real-world usage data for 914 drugs taken by 96 645 927 patients. Results A total of 17.5% of drugs had longer median exposure in practice than in trials, 6% of patients had extended exposure to at least 1 drug, and drugs treating nervous system disorders and cardiovascular diseases were the most common among drugs with high rates of extended exposure. Conclusions For most of patients, the drug use length is shorter than the tested length in clinical trials. Still, a remarkable number of patients experienced extended drug exposure, particularly for drugs treating nervous system disorders or cardiovascular disorders.

[1]  Chunhua Weng,et al.  Correlating eligibility criteria generalizability and adverse events using Big Data for patients and clinical trials , 2017, Annals of the New York Academy of Sciences.

[2]  W. Barbaresi,et al.  Long-Term Stimulant Medication Treatment of Attention-Deficit/Hyperactivity Disorder: Results from a Population-Based Study , 2006, Journal of developmental and behavioral pediatrics : JDBP.

[3]  S. Krähenbühl,et al.  Long-Term Metformin Use Is Associated With Decreased Risk of Breast Cancer , 2010, Diabetes Care.

[4]  Organización Mundial de la Salud.  Guidelines for ATC classification and DDD assignment , 1996 .

[5]  Patrick B. Ryan,et al.  The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0 , 2017, J. Am. Medical Informatics Assoc..

[6]  A. Perotte,et al.  Translating evidence into practice: eligibility criteria fail to eliminate clinically significant differences between real-world and study populations. , 2020, npj Digital Medicine.

[7]  E. Biganzoli,et al.  Phase IV Studies: Some Insights, Clarifications, and Issues. , 2018, Current clinical pharmacology.

[8]  M. Doody,et al.  Association of Radioactive Iodine Treatment With Cancer Mortality in Patients With Hyperthyroidism , 2019, JAMA internal medicine.

[9]  T. Furukawa,et al.  National Prescription Patterns of Antidepressants in the Treatment of Adults With Major Depression in the US Between 1996 and 2015: A Population Representative Survey Based Analysis , 2020, Frontiers in Psychiatry.

[10]  Cecilia Jernberg,et al.  Long-term impacts of antibiotic exposure on the human intestinal microbiota. , 2010, Microbiology.

[11]  A. Hofman,et al.  Duration of antihypertensive drug use and risk of dementia , 2009, Neurology.

[12]  Yu-Chuan Li,et al.  Observational Health Data Sciences and Informatics (OHDSI): Opportunities for Observational Researchers , 2015, MedInfo.

[13]  J. Hippisley-Cox,et al.  Antidepressant use and risk of adverse outcomes in people aged 20–64 years: cohort study using a primary care database , 2018, BMC Medicine.

[14]  S. Pocock,et al.  Long-Term Use of Cardiovascular Drugs: Challenges for Research and for Patient Care. , 2015, Journal of the American College of Cardiology.

[15]  A Schmoldt,et al.  Digitoxin metabolism by rat liver microsomes. , 1975, Biochemical pharmacology.

[16]  Harlan M. Krumholz,et al.  Clinical trial evidence supporting FDA approval of novel therapeutic agents, 2005-2012. , 2014, JAMA.

[17]  Angel X. Chang,et al.  SUTime: A library for recognizing and normalizing time expressions , 2012, LREC.