Abstract
Purpose
We applied a novel combined connectivity mapping and pharmacoepidemiological approach to identify medications which alter breast cancer risk.
Methods
The connectivity mapping process identified six potentially cancer-causing (meloxicam, azithromycin, rizatriptan, citalopram, rosiglitazone, verapamil) and four potentially cancer-preventing (bendroflumethiazide, sertraline, fluvastatin, budesonide) medications which were suitable for pharmacoepidemiological investigation. Within the UK Clinical Practice Research Datalink, we matched 45,147 breast cancer cases to one control per case based on age, year and GP practice. Medication use was determined from electronic prescribing records. We used conditional logistic regression to calculate odds ratios (ORs) for the association between medication use and cancer risk after adjustment for comorbidities, lifestyle factors, deprivation and other medication use.
Results
Bendroflumethiazide was associated with increased breast cancer risk (OR: 1.11; 95% CI: 1.06, 1.15) however the connectivity mapping exercise predicted this medication would reduce risk. There were no statistically significant associations for any of the other candidate medications, with ever use ORs ranging from 0.93 (95% CI: 0.78, 1.11) for azithromycin to 1.16 (95% CI: 0.0.99, 1.37) for verapamil.
Conclusions
In this instance, our combined connectivity mapping and pharmaco epidemiological approach did not identify any additional medications which were substantially associated with breast cancer risk. This could be due to limitations in the connectivity mapping, such as implausible dosage requirements, or the pharmaco epidemiology, such as residual confounding.
We applied a novel combined connectivity mapping and pharmacoepidemiological approach to identify medications which alter breast cancer risk.
Methods
The connectivity mapping process identified six potentially cancer-causing (meloxicam, azithromycin, rizatriptan, citalopram, rosiglitazone, verapamil) and four potentially cancer-preventing (bendroflumethiazide, sertraline, fluvastatin, budesonide) medications which were suitable for pharmacoepidemiological investigation. Within the UK Clinical Practice Research Datalink, we matched 45,147 breast cancer cases to one control per case based on age, year and GP practice. Medication use was determined from electronic prescribing records. We used conditional logistic regression to calculate odds ratios (ORs) for the association between medication use and cancer risk after adjustment for comorbidities, lifestyle factors, deprivation and other medication use.
Results
Bendroflumethiazide was associated with increased breast cancer risk (OR: 1.11; 95% CI: 1.06, 1.15) however the connectivity mapping exercise predicted this medication would reduce risk. There were no statistically significant associations for any of the other candidate medications, with ever use ORs ranging from 0.93 (95% CI: 0.78, 1.11) for azithromycin to 1.16 (95% CI: 0.0.99, 1.37) for verapamil.
Conclusions
In this instance, our combined connectivity mapping and pharmaco epidemiological approach did not identify any additional medications which were substantially associated with breast cancer risk. This could be due to limitations in the connectivity mapping, such as implausible dosage requirements, or the pharmaco epidemiology, such as residual confounding.
| Original language | English |
|---|---|
| Pages (from-to) | 78-86 |
| Number of pages | 8 |
| Journal | Pharmacoepidemiology and Drug Safety |
| Volume | 27 |
| Issue number | 1 |
| Early online date | 05 Dec 2017 |
| DOIs | |
| Publication status | Published - 02 Jan 2018 |
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- A combined connectivity mapping and pharmacoepidemiology approach to identify existing medications with breast cancer causing or preventing properties
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