Dataset Information

Identification of Associations Between Prescribed Medications and Cancer: A Nationwide Screening Study.

ABSTRACT:

Purpose

We present a systematic screening for identifying associations between prescribed drugs and cancer risk using the high quality Danish nationwide health registries.

Methods

We identified all patients (cases) with incident cancer in Denmark during 2000-2012 (n=278,485) and matched each case to 10 controls. Complete prescription histories since 1995 were extracted. Applying a two-phased case-control approach, we first identified drug classes or single drugs associated with an increased or decreased risk of 99 different cancer types, and further evaluated potential associations by examining specificity and dose-response patterns.

Findings

22,125 drug-cancer pairs underwent evaluation in the first phase. Of 4561 initial signals (i.e., drug-cancer associations), 3541 (78%) failed to meet requirements for dose-response patterns and specificity, leaving 1020 eligible signals. Of these, 510 signals involved the use of single drugs, and 33% (166 signals) and 67% (344 signals) suggested a reduced or an increased cancer risk, respectively. While a large proportion of the signals were attributable to the underlying conditions being treated, our algorithm successfully identified well-established associations, as well as several new signals that deserve further investigation.

Conclusion

Our results provide the basis for future targeted studies of single associations to capture novel carcinogenic or chemopreventive effects of prescription drugs.

SUBMITTER: Pottegard A

PROVIDER: S-EPMC4909325 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Associations Between Prescribed Medications and Cancer: A Nationwide Screening Study.

Pottegård Anton A Friis Søren S Christensen René dePont Rd Habel Laurel A LA Gagne Joshua J JJ Hallas Jesper J

EBioMedicine 20160314

<h4>Purpose</h4>We present a systematic screening for identifying associations between prescribed drugs and cancer risk using the high quality Danish nationwide health registries.<h4>Methods</h4>We identified all patients (cases) with incident cancer in Denmark during 2000-2012 (n=278,485) and matched each case to 10 controls. Complete prescription histories since 1995 were extracted. Applying a two-phased case-control approach, we first identified drug classes or single drugs associated with an ...[more]

PMID: 27322460

Similar Datasets

Project description:ObjectivesThe aim of this study was to demonstrate the existence of systematic associations in drug prescription that lead to the establishment of patterns of polypharmacy, and the clinical interpretation of the associations found in each pattern.MethodsA cross-sectional study was conducted based on information obtained from electronic medical records and the primary care pharmacy database in 2008. An exploratory factor analysis of drug dispensing information regarding 79,089 adult patients was performed to identify the patterns of polypharmacy. The analysis was stratified by age and sex.ResultsSeven patterns of polypharmacy were identified, which may be classified depending on the type of disease they are intended to treat: cardiovascular, depression-anxiety, acute respiratory infection (ARI), chronic obstructive pulmonary disease (COPD), rhinitis-asthma, pain, and menopause. Some of these patterns revealed a clear clinical consistency and included drugs that are prescribed together for the same clinical indication (i.e., ARI and COPD patterns). Other patterns were more complex but also clinically consistent: in the cardiovascular pattern, drugs for the treatment of known risk factors-such as hypertension or dyslipidemia-were combined with other medications for the treatment of diabetes or established cardiovascular pathology (e.g., antiplatelet agents). Almost all of the patterns included drugs for preventing or treating potential side effects of other drugs in the same pattern.ConclusionsThe present study demonstrated the existence of non-random associations in drug prescription, resulting in patterns of polypharmacy that are sound from the pharmacological and clinical viewpoints and that exist in a significant proportion of the population. This finding necessitates future longitudinal studies to confirm some of the proposed causal associations. The information discovered would further the development and/or adaptation of clinical patient guidelines to patients with multimorbidity who are taking multiple drugs.

Project description:BACKGROUND:Achieving good medication adherence is a major challenge for patients with chronic conditions. Our study aimed to assess the Threshold for Unacceptable Risk of Non-adherence (TURN), defined as the threshold at which physicians consider the health risks incurred by patients due to medication non-adherence unacceptable, for the most commonly prescribed drugs in France. METHODS:We conducted an online study using a crowdsourcing approach among French general practitioners and specialists from September 2016 to August 2017. Physicians assessed the TURN for various levels of missed doses by evaluating a series of randomly presented clinical vignettes, each presenting a given medication with a given therapeutic indication. For each "drug-indication group" (i.e., all drugs from the same pharmacological class with a similar therapeutic indication): 1) we described the distribution of physicians' assessments, 2) we provided a summary estimate of the TURN, defined as the frequency of missed doses above which 75% of the physicians' assessments were located; 3) we computed the number of pill boxes reimbursed in France in 2016 to put our results into context. RESULTS:We collected a total of 5365 assessments from 544 physicians, each of whom evaluated a random sample among 528 distinct clinical vignettes. Estimates of the TURN varied widely across drug-indication groups, ranging from risk considered unacceptable with 1 daily dose missed per month (e.g., insulin for diabetes) to risk always considered acceptable (e.g., anti-dementia drugs). Drugs with an estimated TURN of over one missing daily dose per week represented 44.9% of the prescription volume of the medications assessed in our study. CONCLUSIONS:According to physicians, the impact of non-adherence may vary greatly. Patient-physician discussions on the variable consequences of non-adherence could lead to a paradigm shift by seeking to reach "optimal adherence" depending on drugs rather than unrealistic "perfect adherence" to all drugs.

Project description:Background and aimsBenzodiazepines are commonly prescribed to patients with opioid use disorder receiving buprenorphine treatment, yet may increase overdose risk. However, prescribed benzodiazepines may improve retention in care by reducing buprenorphine discontinuation and thus may prevent relapse to illicit opioid use. We aimed to test the association between benzodiazepine prescription and fatal opioid overdose, non-fatal opioid overdose, all-cause mortality and buprenorphine discontinuation.Design and settingThis was a retrospective cohort study using five individually linked data sets from Massachusetts, United States government agencies.ParticipantsWe studied 63 389 Massachusetts residents aged 18 years or older who received buprenorphine treatment between January 2012 and December 2015.MeasurementsFilled benzodiazepine prescription during buprenorphine treatment was the main independent variable. The primary outcome was time to fatal opioid overdose. Secondary outcomes were time to non-fatal opioid overdose, all-cause mortality and buprenorphine discontinuation. We defined buprenorphine discontinuation as having a 30-day gap without another prescription following the end date of the previous prescription. We used Cox proportional hazards models to calculate hazards ratios that tested the association between receipt of benzodiazepines and all outcomes, restricted to periods during buprenorphine treatment.FindingsOf the 63 345 individuals who received buprenorphine, 24% filled at least one benzodiazepine prescription during buprenorphine treatment. Thirty-one per cent of the 183 deaths from opioid overdose occurred when individuals received benzodiazepines during buprenorphine treatment. Benzodiazepine receipt during buprenorphine treatment was associated with an increased risk of fatal opioid overdose adjusted hazard ratio (HR) = 2.92, 95% confidence interval (CI) = 2.10-4.06, non-fatal opioid overdose, adjusted HR = 2.05, 95% CI, 1.68-2.50, all-cause mortality, adjusted HR = 1.90, 95% CI, 1.48-2.44 and a decreased risk of buprenorphine discontinuation, adjusted HR = 0.87, 95% CI, 0.85-0.89.ConclusionsBenzodiazepine receipt appears to be associated with both increased risk of opioid overdose and all-cause mortality and decreased risk of buprenorphine discontinuation among people receiving buprenorphine.

Dataset Information

Identification of Associations Between Prescribed Medications and Cancer: A Nationwide Screening Study.

Purpose

Methods

Findings

Conclusion

Publications

Identification of Associations Between Prescribed Medications and Cancer: A Nationwide Screening Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets