Medicine misuse: A systematic review and proposed hierarchical terminology.

AIMS: Although medicine misuse is a public health issue, it has multiple meanings in the medical literature. This study aimed to characterize, classify and identify the most appropriate definitions of medicine misuse. METHODS: A systematic review was performed in Medline, ISI Web of Science, SocINDEX, PsycInfo, PsycArticles and Psychological and Behavioral Sciences Collection, using keywords related to "misuse", "appropriateness" and "medicine" between 1 November 2008 and 25 August 2020. Additional searches were conducted in websites of regulatory agencies and public health institutions. Two authors independently selected studies providing both definitions and examples of misuse, while a third resolved disagreements. Definitions were used to propose a hierarchical classification based on initiator, intent, purpose and context of medicine misuse. The study is registered on PROSPERO: CRD42018115789. RESULTS: Of 3404 identified records, 51 were included. A total of 71 definitions and 74 examples of misuse were retrieved. When the prescriber is initiator and according to intent, potential medicine misuse referred to "intentional or unintentional prescribing not in line with clinical evidence". Based on context, they could prescribe medicines not clinically justified, i.e. overprescribing, or prescribe indicated medicines incorrectly, i.e. misprescribing. Among other groups of definitions, those overlapping with drug abuse or medication use errors were considered out-of-scope. CONCLUSION: This systematic review provides a comprehensive overview of the terms and definitions used to characterize medicine misuse and could serve as a basis for a terminology that makes clear distinctions between misuse, abuse and errors.

Risk of bradyarrhythmia related to ticagrelor: A systematic review and meta-analysis.

CONTEXT: Ticagrelor was related to bradycardia in DISPERSE-II trial. This risk has been integrated into the European risk-management plan, and its use is warned in at-risk patients. Nevertheless, this risk was not systematically assessed nor measured. OBJECTIVES: To estimate the risk of bradyarrhythmia associated with ticagrelor. STUDY DESIGN: Systematic review and meta-analysis. DATA-SOURCE: MEDLINE, Scopus, Cochrane Central Register of Controlled Trials, ISI web of Science, clinicaltrial.gov, clinicaltrialsregister.eu. STUDY SELECTION: Randomized controlled trials (RCTs) and observational studies in patients treated with ticagrelor or comparator(s). META-ANALYSIS: Risk of bias in each RCT was assessed using Cochrane tool. Relative Risks (RR) with 95 % confidence intervals (95 %CI) were calculated for each RCT, and pooled using fixed-effect or random-effects models, when appropriate. Subgroup and sensitivity analyses were performed. A potential publication bias was searched. RESULTS: Among 82 eligible studies, event data were missing for 56 studies, due to detected reporting bias (i.e. inability to confirm zero events). Fifteen RCTs were selected and the combined RR of bradyarrhythmia was 1.15 (95 %CI 1.05-1.26), and 1.29 (1.02-1.65) for severe bradyarrhythmia. The risk appeared to be dose dependent. Restricting the analysis only to RCTs performed in patients without previous bradyarrhythmia resulted in a non-increased risk. CONCLUSION: This meta-analysis confirmed the risk of bradyarrhythmia or severe bradyarrhythmia related to ticagrelor, and its use in patients without previous bradycardia was effective in preventing it. The evidence coming from this meta-analysis was low to moderate due to missing outcome in 2/3 of eligible studies. Waiting for access to these data, the use of ticagrelor in patients with risk factors of bradycardias should be avoided.

Real-World Treatment Patterns and Effectiveness of Patients With Advanced Renal Cell Carcinoma: A Nationwide Observational Study.

BACKGROUND: Treatment landscape for advanced renal cell carcinoma (aRCC) has evolved quickly and few data about the real-world treatment patterns are available. This study aimed at describing the real-world treatment patterns and effectiveness of all systemic treatments available for aRCC in first and second-line treatment. MATERIALS AND METHODS: A cohort of patients initiating a first-line systemic treatment for aRCC in 2016 was extracted from the French nationwide healthcare insurance system database (SNDS). The first-line treatment initiation date constituted the index date and patients were followed until death, loss to follow-up, or December 31, 2019, whichever occurred first. aRCC was identified using hospital diagnosis, long-term disease, or renal biopsy before index date. All analyses were performed for first and second-line treatment. Overall survival (OS) and time-to-next treatment or death (TNT-D) were estimated using Kaplan-Meier approach. RESULTS: In 2016, 1629 patients initiated a first-line treatment for aRCC. Most of them were male (75.9%) and the median age was 67 years. Most of patients (91.7%) had received a tyrosine kinase inhibitor as first-line treatment, mainly sunitinib (64.4%), and 53.5% received a second-line, among which 43.7% nivolumab. Median OS (95% confidence interval [CI]) was 20.7 (95% CI:18.2-22.4) months from first-line treatment initiation and 15.4 (13.9-17.5) months from second-line treatment initiation. Median TNT-D were respectively 9.3 (9.7-12.1) months and 6.9 (5.9-7.7) months. CONCLUSION: This study highlights the limited survival of aRCC patients These results provide a valuable baseline and highlight the need for innovation, such as immune checkpoint inhibitor-based combinations that have recently became first-line standard of care.

Risk of Drug-Drug Interactions in Out-Hospital Drug Dispensings in France: Results From the DRUG-Drug Interaction Prevalence Study.

Introduction: Drug interactions could account for 1% of hospitalizations in the general population and 2-5% of hospital admissions in the elderly. However, few data are available on the drugs concerned and the potential severity of the interactions encountered. We thus first aimed to estimate the prevalence of dispensings including drugs Contraindicated or Discommended because of Interactions (CDI codispensings) and to identify the most frequently involved drug pairs. Second, we aimed to investigate whether the frequency of CDI codispensings appeared higher or lower than the expected for the drugs involved. Methods: We carried out a study using a random sample of all drugs dispensings registered in a database of the French Health Insurance System between 2010 and 2015. The distribution of the drugs involved was described considering active principles, detailing the 20 most frequent ones for both contraindicated or discommended codispensings (DCs). To investigate whether the frequency of CDI codispensings appeared higher or lower than the expected for the drugs involved, we developed a specific indicator, the Drug-drug interaction prevalence study-score (DIPS-score), that compares for each drug pair the observed frequency of codispensing to its expected probability. The latter is determined considering the frequencies of dispensings of the individual drugs constituting a pair of interest. Results: We analyzed 6,908,910 dispensings: 13,196 (0.2%) involved contraindicated codispensings (CCs), and 95,410 (1.4%) DCs. For CCS, the most frequently involved drug pair was "bisoprolol+flecainide" (n = 5,036); four out of five of the most represented pairs involved cardiovascular drugs. For DCS, the most frequently involved drug pair was "ramipril+spironolactone" (n = 4,741); all of the five most represented pairs involved cardiovascular drugs. The drug pair involved in the CC with the highest score value was "citalopram+hydroxyzine" (DIPS-score: 3.7; 2.9-4.6); that with the lowest score was "clarithromycin+simvastatin" (DIPS-score: 0.2; 0.2-0.3). DIPS-score median value was 0.4 for CCs and 0.6 for DCs. Conclusion: This high prevalence of CDI codispensings enforces the need for further risk-prevention actions regarding drug-drug interactions (DDIs), especially for arrhythmogenic or anti-arrhythmic drugs. In this perspective, the DIPS-score we develop could ease identifying the interactions that are poorly considered by clinicians/pharmacists and targeting interventions.

Risk of Serious Trauma with Glucose-Lowering Drugs in Older Persons: A Nested Case-Control Study.

OBJECTIVES: To assess the risk of hospitalization for trauma associated with use of hypoglycemic glucose-lowering drugs (GLDs) in individuals aged 65 and older. DESIGN: Observational, nested, case-control study. SETTING: The Echantillon Généraliste de Bénéficiaires claims database, a 1/97th representative sample of the population covered by French healthcare insurance. PARTICIPANTS: All persons with a first hospitalization for trauma between 2009 and 2015 were considered as potential cases. They were selected if they had been followed for 365 days or longer at index date, were aged 65 and older, and had no diagnosed cancer. Cases (n=10,743) were matched with up to 10 randomly selected controls on age, sex, and length of follow-up (n=106,629). MEASUREMENTS: GLD exposure was considered globally and according to use of hypoglycemic GLDs alone, nonhypoglycemic GLDs alone, or both types of GLDs. Risk of hospitalization for trauma was estimated using hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS: Risk of hospitalization for trauma was significantly higher with use of GLDs (HR=1.15, 95% CI=1.08-1.22). Greater risk was found only in individuals treated with hypoglycemic GLDs alone (HR=1.26, 95% CI=1.15-1.38), particularly insulin (HR=1.49, 95% CI=1.32-1.68) and glinides (HR=1.34, 95% CI=1.12-1.61). CONCLUSION: This study highlights the excess risk of serious trauma with the use of insulin and glinides. J Am Geriatr Soc 66:2086-2091, 2018.

An Automated System Combining Safety Signal Detection and Prioritization from Healthcare Databases: A Pilot Study.

INTRODUCTION: Signal detection from healthcare databases is possible, but is not yet used for routine surveillance of drug safety. One challenge is to develop methods for selecting signals that should be assessed with priority. AIM: The aim of this study was to develop an automated system combining safety signal detection and prioritization from healthcare databases and applicable to drugs used in chronic diseases. METHODS: Patients present in the French EGB healthcare database for at least 1 year between 2005 and 2015 were considered. Noninsulin glucose-lowering drugs (NIGLDs) were selected as a case study, and hospitalization data were used to select important medical events (IME). Signal detection was performed quarterly from 2008 to 2015 using sequence symmetry analysis. NIGLD/IME associations were screened if one or more exposed case was identified in the quarter, and three or more exposed cases were identified in the population at the date of screening. Detected signals were prioritized using the Longitudinal-SNIP (L-SNIP) algorithm based on strength (S), novelty (N), and potential impact of signal (I), and pattern of drug use (P). Signals scored in the top 10% were identified as of high priority. A reference set was built based on NIGLD summaries of product characteristics (SPCs) to compute the performance of the developed system. RESULTS: A total of 815 associations were screened and 241 (29.6%) were detected as signals; among these, 58 (24.1%) were prioritized. The performance for signal detection was sensitivity = 47%; specificity = 80%; positive predictive value (PPV) 33%; negative predictive value = 82%. The use of the L-SNIP algorithm increased the early identification of positive controls, restricted to those mentioned in the SPCs after 2008: PPV = 100% versus PPV = 14% with its non-use. The system revealed a strong new signal with dipeptidylpeptidase-4 inhibitors and venous thromboembolism. CONCLUSION: The developed system seems promising for the routine use of healthcare data for safety surveillance of drugs used in chronic diseases.

Methods for safety signal detection in healthcare databases: a literature review.

INTRODUCTION: With increasing availability, the use of healthcare databases as complementary data source for drug safety signal detection has been explored to circumvent the limitations inherent in spontaneous reporting. Areas covered: To review the methods proposed for safety signal detection in healthcare databases and their performance. Expert opinion: Fifteen different data mining methods were identified. They are based on disproportionality analysis, traditional pharmacoepidemiological designs (e.g. self-controlled designs), sequence symmetry analysis (SSA), sequential statistical testing, temporal association rules, supervised machine learning (SML), and the tree-based scan statistic. When considering the performance of these methods, the self-controlled designs, the SSA, and the SML seemed the most interesting approaches. In the perspective of routine signal detection from healthcare databases, pragmatic aspects such as the need for stakeholders to understand the method in order to be confident in the results must be considered. From this point of view, the SSA could appear as the most suitable method for signal detection in healthcare databases owing to its simple principle and its ability to provide a risk estimate. However, further developments, such as automated prioritization, are needed to help stakeholders handle the multiplicity of signals.

Trends in the incidence of use of noninsulin glucose-lowering drugs between 2006 and 2013 in France.

This study aimed at describing trends in the incidence of use of noninsulin glucose-lowering drugs (NIGLDs) between 2006 and 2013 in France. Repeated cross-sectional studies on NIGLD new users were performed annually from 2006 to 2013 within the Echantillon Généraliste des Bénéficiaires (EGB) database, a 1/97th representative sample of the population covered by the French healthcare insurance system. NIGLD included metformin, sulfonylureas, α-glucosidase inhibitors, thiazolidinediones, dipeptidylpeptidase-4 (DPP-4) inhibitors, glinides and glucagon-like peptide-1 analogues. New users were defined as patients with no delivery of any NIGLD (first-line new users) or no delivery of a NIGLD of the same class (add-on/switch new users) in the preceding year. Incidence rates of use and corresponding 95% confidence intervals (95% CI) were estimated per 1000 persons. Among the 507 043 persons included in the EGB in 2006, 2036 were identified as NIGLD first-line new users and 2192 as add-on/switch new users, which corresponded to an incidence of use of 4.0‰ (95%CI 3.8-4.2) and 4.3‰ (4.1-4.5), respectively. First-line incidence increased to 5.3‰ (5.1-5.5) in 2010 and then decreased to 4.2‰ (4.0-4.4) in 2013; add-on/switch incidence increased to 8.0‰ (7.8-8.2) in 2010 and then decreased to 5.3‰ (5.1-5.5) in 2013. This reduction was mainly related to DPP-4 inhibitors, whose use as add-on/switch NIGLDs was roughly halved between 2010 and 2013. Concomitantly, the use of sulfonylureas and glinides increased. In conclusion, after reaching a peak in 2010, the incidence of use of NIGLDs has markedly decreased in France. Since then, prescribers seem to have reverted to older and well-known therapies.

Risk of Motor Vehicle Accidents Related to Sleepiness at the Wheel: A Systematic Review and Meta-Analysis.

Study Objectives: Sleepiness at the wheel is widely believed to be a cause of motor vehicle accidents. Nevertheless, a systematic review of studies investigating this relationship has not yet been published. The objective of this study was to quantify the relationship between sleepiness at the wheel and motor vehicle accidents. Methods: A systematic review was performed using Medline, Scopus, and ISI Web of Science. The outcome measure of interest was motor vehicle accident defined as involving four- or two-wheeled vehicles in road traffic, professional and nonprofessional drivers, with or without objective consequences. The exposure was sleepiness at the wheel defined as self-reported sleepiness at the wheel. Studies were included if they provided adjusted risk estimates of motor vehicle accidents related to sleepiness at the wheel. Risk estimates and 95% confidence intervals (95% CIs) were extracted and pooled as odds ratios (ORs) using a random-effect model. Heterogeneity was quantified using Q statistics and the I2 index. The potential causes of heterogeneity were investigated using meta-regressions. Results: Ten cross-sectional studies (51,520 participants), six case-control studies (4904 participants), and one cohort study (13,674 participants) were included. Sleepiness at the wheel was associated with an increased risk of motor vehicle accidents (pooled OR 2.51 [95% CI 1.87; 3.39]). A significant heterogeneity was found between the individual risk estimates (Q = 93.21; I2 = 83%). Conclusions: Sleepiness at the wheel increases the risk of motor vehicle accidents and should be considered when investigating fitness to drive. Further studies are required to explore the nature of this relationship. Systematic review registration number: PROSPERO 2015 CRD42015024805.

Impact of Medicine Withdrawal on Reporting of Adverse Events Involving Therapeutic Alternatives: A Study from the French Spontaneous Reporting Database.

INTRODUCTION: The consequences of the withdrawal of marketing authorisation of drugs have mostly been studied considering drug prescription patterns for the therapeutic alternatives of the withdrawn drugs. The potential concomitant changes in the reporting of adverse reactions concerning these alternatives have been studied less often. OBJECTIVE: The objective of this study was to analyse the changes in the reporting of adverse events (AEs) for therapeutic alternatives after the withdrawal of three medicines (dextropropoxyphene, pioglitazone and tetrazepam) from the market for safety reasons. METHODS: This study was performed using both the French pharmacovigilance database and the Echantillon Généraliste des Bénéficiaires (a random sample of French health insurance affiliates). For dextropropoxyphene, pioglitazone and tetrazepam alternatives, the number and types of case reports were studied for both the year preceding the first official safety warning and the year following the withdrawal. Reporting rates expressed per 10,000 reimbursements (RRReimb) and per 10,000 treated patients (RRPat) were also compared for the two periods. RESULTS: After dextropropoxyphene withdrawal, case reports and reimbursements increased for tramadol (case reports: +23%, reimbursements: +13%) and codeine (case reports: +74%, reimbursements: +47%), RRPat being significantly increased for tramadol (0.92 vs. 1.06, p = 0.02). After pioglitazone withdrawal, case reports increased for dipeptidyl peptidase-4 (DPP-4) inhibitors, glinides, and glucagon-like peptide 1 (GLP-1) analogues (+84%, +22% and +5%, respectively) and reimbursements (+55, +11 and +50%, respectively); both decreased for sulfonylureas (case reports: -6%, reimbursements: -2%). RRPat increased for DPP-4 inhibitors (1.63 vs. 2.26, p = 0.008). After tetrazepam withdrawal, case reports increased for diazepam, methocarbamol and thiocolchicoside (+110, +86 and +157%, respectively), as lesser did reimbursements. RRPat increased for diazepam (1.78 vs. 2.41, p = 0.054) and thiocolchicoside (0.14 vs. 0.24, p = 0.013). CONCLUSION: For the three drug withdrawals investigated, the number of case reports involving alternatives increased to a larger extent than the numbers of prescriptions. This could relate to a higher occurrence of AEs in new users of alternatives who switched from the withdrawn medicines or to an increased awareness of possible AEs.

Comparative Safety of Targeted Therapies for Metastatic Colorectal Cancer between Elderly and Younger Patients: a Study Using the International Pharmacovigilance Database.

BACKGROUND: Metastatic colorectal cancer (mCRC) is increasingly treated using targeted therapies. Post-marketing safety of these agents is understudied, especially in the elderly. OBJECTIVE: This study aimed to compare, according to age, the adverse drug reactions (ADRs) of targeted therapies used for mCRC in real life. PATIENTS AND METHODS: An extraction of VigiBase, which contains World Health Organization individual case safety reports (ICSRs), was performed. All ADR reports with aflibercept, bevacizumab, cetuximab, panitumumab, or regorafenib used in CRC were considered. For all drugs, chi-square tests were used to compare frequencies of serious ADRs between patients aged ≥75 and <75 years. For selected ADRs and each drug, the drug-ADR association compared to other anticancer drugs was estimated through the proportional reporting ratio (PRR) in both age groups. RESULTS: There were 21,565 ICSRs included, among which 74% were serious and 11% were fatal. Median age was 64 years (Inter Quartile Range = 56-71) and 15% of patients were aged ≥75; 57% were male. Serious ICSRs accounted for 47,292 ADRs. Neutropenia was not more reported in elderly for all drugs while diarrhea was more reported in elderly for panitumumab. Cardiac disorders were more reported in elderly patients, in particular heart failure, especially for bevacizumab, cetuximab, and regorafenib, as were respiratory, thoracic, and mediastinal disorders. Most of PRR were not different between the two groups, except encephalopathies, which were significantly associated with bevacizumab in the elderly only. CONCLUSIONS: ADRs related to targeted therapies used for mCRC treatment were different across age groups; yet, not systematically more reported or worse in elderly patients. Selected elderly patients could, therefore, be treated with these targeted therapies.

Signal of Gastrointestinal Congenital Malformations with Antipsychotics After Minimising Competition Bias: A Disproportionality Analysis Using Data from Vigibase(®).

INTRODUCTION: Investigations have highlighted the lack of evidence regarding the likelihood of congenital malformations following exposure to antipsychotic drugs during pregnancy. To gain further knowledge regarding their safety, we evaluated signals of congenital malformations with antipsychotics using VigiBase(®), the World Health Organization (WHO) Global Individual Case Safety Report (ICSR) database. METHOD: A case/non-case study was conducted in VigiBase(®) between 1967 and 2014. Signals of disproportionate reporting (SDRs) were detected using the proportional reporting ratio (PRR), which defines SDRs as drug-report associations with a PRR ≥2, Chi square ≥4, and number of cases ≥3. SDR detection for antipsychotics was performed for congenital malformations after removing all reports related to drug competitors and reports of movement disorders from the database. RESULTS: After removing reports related to drug competitors (antiepileptics, antidepressants, antivirals) and movement disorders, three signals were revealed: 'palate disorders congenital' (PRR 2.1, 95 % CI 1.6-2.9, Chi square = 30; n = 41), 'oesophageal disorders congenital' (PRR 2.5, 95 % CI 1.3-4.7, Chi square = 11; n = 10) and 'anorectal disorders congenital' (PRR 3.0, 95 % CI 1.6-5.6, Chi square = 13; n = 11). Among antipsychotics, phenothiazines with a piperazine side-chain, risperidone and aripiprazole appeared to be more suspect. CONCLUSION: Confirming a first signal from spontaneous reporting data, three SDRs for antipsychotics and gastrointestinal congenital abnormalities were unmasked in VigiBase(®). This signal should be further explored by ad hoc pharmacoepidemiologic studies in order to assess whether it is relevant for prescription and public health.

Addition of dipeptidyl peptidase-4 inhibitors to sulphonylureas and risk of hypoglycaemia: systematic review and meta-analysis.

OBJECTIVE: To quantify the risk of hypoglycaemia associated with the concomitant use of dipeptidyl peptidase-4 (DPP-4) inhibitors and sulphonylureas compared with placebo and sulphonylureas. DESIGN: Systematic review and meta-analysis. DATA SOURCES: Medline, ISI Web of Science, SCOPUS, Cochrane Central Register of Controlled Trials, and clinicaltrial.gov were searched without any language restriction. STUDY SELECTION: Placebo controlled randomised trials comprising at least 50 participants with type 2 diabetes treated with DPP-4 inhibitors and sulphonylureas. REVIEW METHODS: Risk of bias in each trial was assessed using the Cochrane Collaboration tool. The risk ratio of hypoglycaemia with 95% confidence intervals was computed for each study and then pooled using fixed effect models (Mantel Haenszel method) or random effect models, when appropriate. Subgroup analyses were also performed (eg, dose of DPP-4 inhibitors). The number needed to harm (NNH) was estimated according to treatment duration. RESULTS: 10 studies were included, representing a total of 6546 participants (4020 received DPP-4 inhibitors plus sulphonylureas, 2526 placebo plus sulphonylureas). The risk ratio of hypoglycaemia was 1.52 (95% confidence interval 1.29 to 1.80). The NNH was 17 (95% confidence interval 11 to 30) for a treatment duration of six months or less, 15 (9 to 26) for 6.1 to 12 months, and 8 (5 to 15) for more than one year. In subgroup analysis, no difference was found between full and low doses of DPP-4 inhibitors: the risk ratio related to full dose DPP-4 inhibitors was 1.66 (1.34 to 2.06), whereas the increased risk ratio related to low dose DPP-4 inhibitors did not reach statistical significance (1.33, 0.92 to 1.94). CONCLUSIONS: Addition of DPP-4 inhibitors to sulphonylurea to treat people with type 2 diabetes is associated with a 50% increased risk of hypoglycaemia and to one excess case of hypoglycaemia for every 17 patients in the first six months of treatment. This highlights the need to respect recommendations for a decrease in sulphonylureas dose when initiating DPP-4 inhibitors and to assess the effectiveness of this risk minimisation strategy.

A Method for the Minimization of Competition Bias in Signal Detection from Spontaneous Reporting Databases.

INTRODUCTION: The two methods for minimizing competition bias in signal of disproportionate reporting (SDR) detection--masking factor (MF) and masking ratio (MR)--have focused on the strength of disproportionality for identifying competitors and have been tested using competitors at the drug level. OBJECTIVES: The aim of this study was to develop a method that relies on identifying competitors by considering the proportion of reports of adverse events (AEs) that mention the drug class at an adequate level of drug grouping to increase sensitivity (Se) for SDR unmasking, and its comparison with MF and MR. METHODS: Reports in the French spontaneous reporting database between 2000 and 2005 were selected. Five AEs were considered: myocardial infarction, pancreatitis, aplastic anemia, convulsions, and gastrointestinal bleeding; related reports were retrieved using standardized Medical Dictionary for Regulatory Activities (MedDRA(®)) queries. Potential competitors of AEs were identified using the developed method, i.e. Competition Index (ComIn), as well as MF and MR. All three methods were tested according to Anatomical Therapeutic Chemical (ATC) classification levels 2-5. For each AE, SDR detection was performed, first in the complete database, and second after removing reports mentioning competitors; SDRs only detected after the removal were unmasked. All unmasked SDRs were validated using the Summary of Product Characteristics, and constituted the reference dataset used for computing the performance for SDR unmasking (area under the curve [AUC], Se). RESULTS: Performance of the ComIn was highest when considering competitors at ATC level 3 (AUC: 62 %; Se: 52 %); similar results were obtained with MF and MR. CONCLUSION: The ComIn could greatly minimize the competition bias in SDR detection. Further study using a larger dataset is needed.