Prescription channeling of COX-2 inhibitors and traditional nonselective nonsteroidal anti-inflammatory drugs: a population-based case–control study

Moride, Yola; Ducruet, Thiérry; Boivin, Jean‐François; Moore, Nicholas; Perreault, Sylvie; Zhao, Sean Z.

doi:10.1186/ar1488

Cited by 24 publications

(4 citation statements)

References 19 publications

(8 reference statements)

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“…Indeed, for newly marketed drug classes, the number of exposed patients, as well as the characteristics of newly treated patients and the preferences of patients and prescribers with respect to specific active substances and formulations, are expected to change rapidly during the period following the introduction into clinical practice [11, 12]. In this context, evidence on the real-world utilization of medicines is paramount to understand the magnitude of possible drug-related issues, identify early signals of irrational drug use, and discuss measures and interventions to improve prescribing habits [13].…”

Section: Introductionmentioning

confidence: 99%

Patterns and trends of utilization of incretin-based medicines between 2008 and 2014 in three Italian geographic areas

et al. 2019

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BackgroundThe incretin-based medicines GLP1 analogues (GLP1a) and dipeptidyl peptidase-4 inhibitors (DPP4i) are hypoglycaemic agents licensed for the treatment of type 2 diabetes mellitus (T2DM). Although these drugs possess comparable efficacy and low risk of hypoglycaemia, differences in terms of route of administration (subcutaneous versus oral), effect on body weight and gastrointestinal tolerabily can impact their actual use in clinical practice. This study aimed to describe the real-world utilization of incretin-based medicines in the Italian clinical practice.MethodsA multi-database, population-based, descriptive, cohort study was performed using administrative data collected between 2008 and 2014 from three Italian geographic areas. Subjects aged ≥18 were selected. New users were defined as those with ≥1 dispensing of GLP1a or DPP4i during the year of interest and none in the past. Trends of cumulative annual incidence of use in the general adult population were observed. New users of GLP1a or DPP4i were respectively described in terms of demographic characteristics and use of antidiabetic drugs during 1 year before and after the first incretin dispensing.ResultsThe overall study population included 4,943,952 subjects. A total of 7357 new users of GLP1a and 41,907 of DPP4i were identified during the study period. Incidence of use increased between 2008 (0.2‰ for both GLP1a and DPP4i) and 2011 (GLP1a = 0.6‰; DPP4i = 2.5‰) and slightly decreased thereafter. In 2014, 61% of new GLP1a users received once-daily liraglutide while 52% of new DPP4i users received metformin/DPP4i in fixed-dose. The percentage of new DPP4i users older than 65 years of age increased from 30.9 to 62.6% during the study period. Around 12% of new users had not received any antidiabetic before starting an incretin.ConclusionsDuring the study period, DPP4i rapidly became the most prescribed incretin-based medicine, particularly among older new user. The choice of the specific incretin-based medicine at first prescription appeared to be directed towards those with higher convenience of use (e.g. oral DPP4i rather than subcutaneous GLP1a, once-daily liraglutide rather than twice-daily exenatide). The non-negligibile use of incretin-based medicines as first-line pharmacotherapy for T2DM warrants further effectiveness and safety evaluations to better define their place in therapy.Electronic supplementary materialThe online version of this article (10.1186/s12902-019-0334-y) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Patterns and trends of utilization of incretin-based medicines between 2008 and 2014 in three Italian geographic areas

et al. 2019

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“…Results from clinical trials have suggested a positive risk/benefit balance of DPP4i in the treatment of T2D ( Moride et al, 2005 ; Schneeweiss et al, 2011 ). Moreover, results from pre-clinical studies showed a favorable effect on b cell preservation ( Deacon, 2004 ; Drucker and Nauck, 2006 ).…”

Section: Introductionmentioning

confidence: 99%

Time to Treatment Intensification in Patients Receiving DPP4 Inhibitors Versus Sulfonylureas as the First Add-On to Metformin Monotherapy: A Retrospective Cohort Study

et al. 2022

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Background: To verify whether, in patients on metformin (MET) monotherapy for type 2 diabetes (T2D), the add-on of a dipeptidyl peptidase inhibitor (DPP4i) compared to a sulfonylurea (SU) can delay the time to the subsequent treatment intensification (TI).Methods: Population-based administrative data banks from four Italian geographic areas were used. Patients aged ≥18 years on MET monotherapy receiving first DPP4i or SU dispensing between 2008 and 2015 (cohort entry) were followed up to the occurrence of TI (insulin dispensing or add-on of a third non-insulin hypoglicemic >180 days after cohort entry), treatment discontinuation, switch, cancer, death, TI occurrence within, end of data availability, end of study period (31 December 2016), whichever came first. Patients on MET + DPP4i were matched 1:1 with those on MET + SU by sex, age, year of cohort entry, and data bank. Hazard Ratio (HR) and 95% confidence intervals (95%CI) were estimated using multivariable Cox regression model including matching variables and potential confounders measured at baseline. Different sensitivity analyses were performed: i) matching at 180 days after cohort entry, ii) intent to treat (ITT) analysis, iii) matching by duration of MET monotherapy, iv) matching by propensity score.Results: The matched study cohort included 10,600 patients. Overall, 763 TI were observed (4.5/100 person-years; mean follow-up = 1.6 years). The primary analysis showed no difference in time to TI between the two groups (HR = 1.02; 95% CI = 0.88–1.19). Sensitivity analyses confirmed this result, except from the ITT analysis (HR = 1.27; 1.13–1.43).Conclusion: The use of a DPP4i rather than a SU as add-on to MET monotherapy was not associated with a delay in treatment intensification.

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“…This phenomenon of preferential prescribing is also known as channeling and may lead to confounding by indication [7,8]. A well-known example of channeling is the preference of doctors to prescribe selective cyclo-oxygenase-2 inhibitors (COX-2 inhibitors) over nonselective (ns) non-steroidal anti-inflammatory drugs (NSAIDs) to patients at risk of developing upper gastrointestinal bleeding (UGIB) [9,10], as the COX-2 inhibitors were developed on purpose to mitigate the GI effects of NSAIDs. Although clinical trials showed that COX-2 inhibitors are ‘safer’ than nsNSAIDs in relation to UGIB [11], observational studies showed no large differences between the rate of UGIB between COX-2 inhibitor and nsNSAIDs, possibly due to residual confounding by indications arising from channeling [12].…”

Section: Introductionmentioning

confidence: 99%

Generating and evaluating a propensity model using textual features from electronic medical records

et al. 2019

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Background Propensity score (PS) methods are commonly used to control for confounding in comparative effectiveness studies. Electronic health records (EHRs) contain much unstructured data that could be used as proxies for potential confounding factors. The goal of this study was to assess whether the unstructured information can also be used to construct PS models that would allow to properly deal with confounding. We used an example of coxibs (Cox-2 inhibitors) vs. traditional NSAIDs and the risk of upper gastro-intestinal bleeding as example, since this association is often confounded due to channeling of coxibs to patients at higher risk of upper gastro-intestinal bleeding. Methods In a cohort study of new users of nonsteroidal anti-inflammatory drugs (NSAIDs) from the Dutch Integrated Primary Care Information (IPCI) database, we identified all patients who experienced an upper gastrointestinal bleeding (UGIB). We used a large-scale regularized regression to fit two PS models using all structured and unstructured information in the EHR. We calculated hazard ratios (HRs) to estimate the risk of UGIB among selective cyclo-oxygenase-2 (COX-2) inhibitor users compared to nonselective NSAID (nsNSAID) users. Results The crude hazard ratio of UGIB for COX-2 inhibitors compared to nsNSAIDs was 0.50 (95% confidence interval 0.18–1.36). Matching only on age resulted in an HR of 0.36 (0.11–1.16), and of 0.35 (0.11–1.11) when further adjusted for sex. Matching on PS only, the first model yielded an HR of 0.42 (0.13–1.38), which reduced to 0.35 (0.96–1.25) when adjusted for age and sex. The second model resulted in an HR of 0.42 (0.13–1.39), which dropped to 0.31 (0.09–1.08) after adjustment for age and sex. Conclusions PS models can be created using unstructured information in EHRs. An incremental benefit was observed by matching on PS over traditional matching and adjustment for covariates.

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Prescription channeling of COX-2 inhibitors and traditional nonselective nonsteroidal anti-inflammatory drugs: a population-based case–control study

Cited by 24 publications

References 19 publications

Patterns and trends of utilization of incretin-based medicines between 2008 and 2014 in three Italian geographic areas

Patterns and trends of utilization of incretin-based medicines between 2008 and 2014 in three Italian geographic areas

Time to Treatment Intensification in Patients Receiving DPP4 Inhibitors Versus Sulfonylureas as the First Add-On to Metformin Monotherapy: A Retrospective Cohort Study

Generating and evaluating a propensity model using textual features from electronic medical records

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