Gliomas are common brain tumours with a poor prognosis. It is crucial to understand the progression of gliomas in order to develop new therapeutic treatments, and to evaluate possible factors that influence the promotion of brain tumours. The immune system plays an important role in the formation of brain tumours. Antibiotics are drugs frequently used to treat bacterial infections and that could possibly affect the immune system. Several studies have investigated possible associations between use of antibiotics and the risk of different cancer entities, with inconclusive results. We found only one study that investigated the impact of antibiotic drug use on the risk of brain tumours; the investigators observed a higher risk of brain tumours in people who had taken antibiotics compared to people who had not. We therefore propose to conduct a study using the UK Clinical Practice Research Datalink (CPRD) to investigate the association between use of antibiotic drugs and the risk of gliomas.
Effectors from the immune system like macrophages or T cells can modulate the course of gliomas. Antibiotic drugs are frequently used drugs that could influence gliomas through various mechanisms. To date, there is very limited data available concerning the risk of glioma after exposure to antibiotic drugs and the results for other tumour entities remain inconclusive. Therefore, we intend to perform a matched case-control study based on data from the CPRD to investigate the risk of glioma in relation to use of antibiotic drugs. Cases will be patients with a first diagnosis of glioma between 1995 and 2018. The index date will be the date of the glioma diagnosis minus one year. Controls will be matched 10:1 to cases on index date, age, sex, general practice and number of years of medical history in the database prior to the index date. The exposure of interest will be defined as use of any antibiotic drug, and then use by selected classes of antibiotic drugs, one or more years before the index date. We will also investigate the number of prescriptions of the antibiotic drugs. We will perform conditional logistic regression analyses to estimate crude and adjusted odds ratios (ORs) with 95% confidence intervals (CIs). We will adjust the analyses for potential confounders and include factors altering the risk of glioma by >10% in the final multivariate analysis.
Any antibiotic use and risk of glioma; use of specific antibiotics and risk of glioma;
Record of at least one Read code for glioma will be sufficient to confirm the diagnosis (see appendix A).
Susan Jick - Chief Investigator - BCDSP - Boston Collaborative Drug Surveillance Program
- Corresponding Applicant -
Christoph Meier - Collaborator - University of Basel
Corinna Seliger - Collaborator - University of Regensburg
Michael Leitzmann - Collaborator - University of Regensburg
Peter Hau - Collaborator - University of Regensburg
Ralf Linker - Collaborator - University of Regensburg
Tareq Anssar - Collaborator - University of Regensburg
Christoph Meier - Collaborator - University of Basel