A methodological review of the high-dimensional propensity score in comparative-effectiveness and safety-of-interventions research finds incomplete reporting relative to algorithm development and robustness.

OBJECTIVES: The use of secondary databases has become popular for evaluating the effectiveness and safety of interventions in real-life settings. However, the absence of important confounders in these databases is challenging. To address this issue, the high-dimensional propensity score (hdPS) algorithm was developed in 2009. This algorithm uses proxy variables for mitigating confounding by combining information available across several healthcare dimensions. This study assessed the methodology and reporting of the hdPS in comparative effectiveness and safety research. STUDY DESIGN AND SETTING: In this methodological review, we searched PubMed and Google Scholar from July 2009 to May 2022 for studies that used the hdPS for evaluating the effectiveness or safety of healthcare interventions. Two reviewers independently extracted study characteristics and assessed how the hdPS was applied and reported. Risk of bias was evaluated with the Rrisk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool. RESULTS: In total, 136 studies met the inclusion criteria; the median publication year was 2018 (Q1-Q3 2016-2020). The studies included 192 datasets, mostly North American databases (n = 132, 69%). The hdPS was used in primary analysis in 120 studies (88%). Dimensions were defined in 101 studies (74%), with a median of 5 (Q1-Q3 4-6) dimensions included. A median of 500 (Q1-Q3 200-500) empirically identified covariates were selected. Regarding hdPS reporting, only 11 studies (8%) reported all recommended items. Most studies (n = 81, 60%) had a moderate overall risk of bias. CONCLUSION: There is room for improvement in the reporting of hdPS studies, especially regarding the transparency of methodological choices that underpin the construction of the hdPS.

Will the future of pharmacovigilance be more automated?

INTRODUCTION: Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to preserve and strengthen medical and pharmacological expertise in drug safety. AREAS COVERED: This work aims to describe PV tasks in which the contribution of AI and intelligent automation (IA) tools is required, in the context of a continuous increase of spontaneous reporting cases and regulatory tasks. A narrative review with expert selection of pertinent references was performed through Medline. Two areas were covered, management of spontaneous reporting cases and signal detection. PERSPECTIVE: The use of AI and IA tools will assist a large spectrum of PV activities, both in public and private PV systems, in particular for tasks of low added value (e.g. initial quality check, verification of essential regulatory information, search for duplicates). Testing, validating, and integrating these tools in the PV routine are the actual challenges for modern PV systems, to guarantee high-quality standards in terms of case management and signal detection.

Drug-Drug Interactions and the Risk of Emergency Hospitalizations: A Nationwide Population-Based Study.

BACKGROUND: Several studies suggest a significant risk of hospitalization because of drug-drug interactions in the general population. However, to our knowledge, this risk has never been measured precisely in a large population. OBJECTIVE: We aimed to estimate the risk of emergency hospitalization associated with exposure to the contraindicated concomitant use of interacting drugs in the general population. METHODS: A self-controlled case-series analysis was carried out on a cohort of 150,000 subjects randomly selected from the French national health insurance database, between 01/01/2016 and 31/12/2016. Exposure to the contraindicated concomitant use of interacting drugs was defined as the overlapping period of dispensings of drugs contraindicated because of clinically meaningful drug-drug interactions. The main outcome, incidence rate ratios, comparing the incidence rate of emergency hospitalizations during each category of exposure time periods with that during the reference period, was estimated using the conditional Poisson regression model. RESULTS: Over the study period, 967 subjects were exposed to at least one contraindicated concomitant use of interacting drug and 177 had been exposed and presented at least one emergency hospitalization. Compared to the unexposed follow-up time, the risk of emergency hospitalization increased during exposure to contraindicated concomitant use of interacting drug periods (incidence rate ratio: 2.41; 95% confidence interval 1.55-3.76). This could translate into 7200 (4500-8900) potentially preventable emergency hospitalizations yearly in France. CONCLUSIONS: We evidenced an almost 2.5-fold increase in the risk of emergency hospitalizations during periods of exposure to contraindicated concomitant use of interacting drugs, with a potential public health impact exceeding 7000 preventable hospitalizations yearly in France. These results confirm the need to reinforce training in prescription practices and tools for prevention concerning contraindicated concomitant use of interacting drugs. These would especially concern drugs involved in an increase in long QT syndrome when associated such as citalopram, and highly prescribed drugs with a risk of overdose if co-prescribed with cytochrome P450 inhibitors, such as antigout and lipid-lowering drugs.

What place for intelligent automation and artificial intelligence to preserve and strengthen vigilance expertise in the face of increasing declarations?

In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI) and led its experts to confirm the potential contribution and theoretical benefit of AI in clinical research, pharmacovigilance, and in improving the efficiency of care. The 2022 workshop is a continuation of this reflection on AI and intelligent automation (IA) by focusing on its contribution to pharmacovigilance and the applications and tasks could be optimized to preserve and strengthen medical and pharmacological expertise in pharmacovigilance. The evolution of pharmacovigilance work is characterized by many tasks with low added value, a growing volume of pharmacovigilance reporting of suspected side effects, and a scarcity of medical staff with expertise in clinical pharmacology and pharmacovigilance and human resources to support this growing need. Together, these parameters contribute to an embolization of the pharmacovigilance system at risk of missing its primary mission: to identify and characterize a risk or even a health alert on a drug. The participants of the workshop (representatives of the Regional Pharmacovigilance Centres (CRPV), the French National Agency for Safety of Medicinal Products (ANSM), patients, the pharmaceutical industry, or start-ups working in the development of AI in the field of medicine) shared their experiences, their pilot projects and their expectations on the expected potential, theoretical or proven, AI and IA. This work has made it possible to identify the needs and challenges that AI or IA represent, in the current or future modes of organization of pharmacovigilance activities. This approach led to the development of a SWOT matrix (strengths, weaknesses, opportunities, threats), a basis for reflection to identify critical points and consider four main recommendations: (1) preserve and develop business expertise in pharmacovigilance (including research and development in methods) with the integration of new technologies; (2) improve the quality of pharmacovigilance reports; (3) adapt technical and regulatory means; (4) implement a development strategy for AI and IA tools at the service of expertise.

Efficacy and Safety of TiNO-Coated Stents versus Drug-Eluting Stents in Acute Coronary Syndrome: Systematic Literature Review and Meta-Analysis.

(1) Background: Practice guidelines define drug-eluting stents (DES) as the standard of care in coronary percutaneous coronary intervention (PCI), including in acute coronary syndrome (ACS). This is based on comparisons with bare-metal stents (BMS). However, non-drug-eluting titanium-nitride-oxide-coated stents (TiNOS) have not been taken into account. The objective of this study is to determine whether TiNOS can be used as an alternative to DES in ACS. (2) Methods: A prospective systematic literature review (SLR), conducted according to the PRISMA guidelines, was performed, wherein multiple literature databases from 2018 and 2022 were searched. Prospective, randomised, controlled trials comparing outcomes after PCI with TiNOS vs. DES in any coronary artery disease (CAD) were searched. Clinical outcomes were meta-analytic pooled risk ratios (RR) of device-oriented Major Adverse Cardiac Events (MACE) and their components. The analysis stratified outcomes reported with ACS-only vs. ACS jointly with chronic coronary syndrome (CCS). (3) Results: Five RCTs were eligible, comprising 1855 patients with TiNOS vs. 1363 with DES at a 1-year follow-up. Three enrolled patients presented with ACS only and two with ACS or CCS. The latter accounted for most of the patients. The one-year pooled RRs in those three RCTs were as follows: MACE 0.93 [0.72, 1.20], recurrent myocardial infarction (MI) 0.48 [0.31, 0.73], cardiac death (CD) 0.66 [0.33, 1.31], clinically driven target lesion revascularization (TLR) 1.55 [1.10, 2.19], and stent thrombosis (ST) 0.35 [0.20, 0.64]. Those results were robust to a sensitivity analysis. The evidence certainty was high in MACE and moderate or low in the other endpoints. (4) Conclusions: TiNOS are a non-inferior and safe alternative to DES in patients with ACS.

Validation of Artificial Intelligence to Support the Automatic Coding of Patient Adverse Drug Reaction Reports, Using Nationwide Pharmacovigilance Data.

INTRODUCTION: Adverse drug reaction reports are usually manually assessed by pharmacovigilance experts to detect safety signals associated with drugs. With the recent extension of reporting to patients and the emergence of mass media-related sanitary crises, adverse drug reaction reports currently frequently overwhelm pharmacovigilance networks. Artificial intelligence could help support the work of pharmacovigilance experts during such crises, by automatically coding reports, allowing them to prioritise or accelerate their manual assessment. After a previous study showing first results, we developed and compared state-of-the-art machine learning models using a larger nationwide dataset, aiming to automatically pre-code patients' adverse drug reaction reports. OBJECTIVES: We aimed to determine the best artificial intelligence model identifying adverse drug reactions and assessing seriousness in patients reports from the French national pharmacovigilance web portal. METHODS: Reports coded by 27 Pharmacovigilance Centres between March 2017 and December 2020 were selected (n = 11,633). For each report, the Portable Document Format form containing free-text information filled by the patient, and the corresponding encodings of adverse event symptoms (in Medical Dictionary for Regulatory Activities Preferred Terms) and seriousness were obtained. This encoding by experts was used as the reference to train and evaluate models, which contained input data processing and machine-learning natural language processing to learn and predict encodings. We developed and compared different approaches for data processing and classifiers. Performance was evaluated using receiver operating characteristic area under the curve (AUC), F-measure, sensitivity, specificity and positive predictive value. We used data from 26 Pharmacovigilance Centres for training and internal validation. External validation was performed using data from the remaining Pharmacovigilance Centres during the same period. RESULTS: Internal validation: for adverse drug reaction identification, Term Frequency-Inverse Document Frequency (TF-IDF) + Light Gradient Boosted Machine (LGBM) achieved an AUC of 0.97 and an F-measure of 0.80. The Cross-lingual Language Model (XLM) [transformer] obtained an AUC of 0.97 and an F-measure of 0.78. For seriousness assessment, FastText + LGBM achieved an AUC of 0.85 and an F-measure of 0.63. CamemBERT (transformer) + Light Gradient Boosted Machine obtained an AUC of 0.84 and an F-measure of 0.63. External validation for both adverse drug reaction identification and seriousness assessment tasks yielded consistent and robust results. CONCLUSIONS: Our artificial intelligence models showed promising performance to automatically code patient adverse drug reaction reports, with very similar results across approaches. Our system has been deployed by national health authorities in France since January 2021 to facilitate pharmacovigilance of COVID-19 vaccines. Further studies will be needed to validate the performance of the tool in real-life settings.

Emergency department admissions induced by drug-drug interactions in the elderly: A cross-sectional study.

The elderly people are increasingly exposed to polymedication and therefore to the risks of drug-drug interactions (DDIs). However, there are few data available on the clinical consequences of these drug combinations. We investigated the impact of the various DDIs classified as severe in terms of emergency admissions in the elderly. A cross-sectional study was conducted using information from the emergency department admissions of Bordeaux University Hospital between September 2016 and August 2017. Events of interest were frequency of concomitant uses of interacting drugs that are contraindicated or warned against and frequency of emergency admissions due to contraindicated or warned against concomitant uses of interacting drugs. Five thousand, eight hundred sixty (5860) admissions to the emergency department were analyzed. A total of 375 (6.4%) contraindicated or warned against concomitant uses were identified, including 163 contraindicated (43.5%) and 212 warned against (56.5%). Reason for admission appeared likely related to the underlying DDI in 58 cases. Within these, 36 admissions were assessed as probably due to a DDI (0.6% of hospitalizations) and 22 as certainly (0.4% of hospitalizations). Of these, there were 24 (45%) admissions related to a long QT syndrome (LQTS), nine (16%) related to a drug overdose, and eight (14%) related to a hemorrhage. An antidepressant was involved in 22 of the 24 cases of LQTS. Seven of the eight cases of hemorrhage involved the antithrombotic agents / non-steroidal anti-inflammatory drugs combination. Elderly patients admitted to emergency departments are particularly exposed to high-risk potential DDIs. These drug combinations lead mainly to LQTS and involve certain antidepressants.

Psychoactive substance use among students: A cross-sectional analysis.

Little is known about psychoactive substance use in students, apart from tobacco, alcohol, and cannabis. This study investigated the prevalence of substance use and overlap between various psychoactive substances in students. This cross-sectional study was conducted in 10 066 students included in the i-Share cohort between January 1, 2015, and December 31, 2017. The baseline questionnaire was the key source of information. Psychoactive substances of interest (PSI) were cannabis, cocaine, amphetamines, nitrous oxide, poppers, and MDMA. Their patterns of use were categorized as lifetime, past year, and current use. The use of other psychoactive substances including alcohol and tobacco was described in PSI users and non-users. Most participants were female (75%), and their average age was 21 years. Lifetime use of at least one PSI was reported by 65.5% of participants. Cannabis was the most frequently used substance both over lifetime (57% of students) and past year (35%), followed by poppers and nitrous oxide (28% and 26% of students over lifetime, respectively). Among polydrug users (n = 1242), 65% used only nitrous oxide and poppers, showing a strong link between these two substances. Regular alcohol use, binge drinking, and current tobacco use were higher in PSI users than in non-users. Substance use was higher than previously found in both French and European studies in young people. Nitrous oxide use was particularly high. Regular alcohol use, binge drinking, and tobacco use could be used as markers to identify students at risk of PSI use to be targeted by prevention programs.

Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.

Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The aim of this study was to develop an automated system allowing to code ADRs from patient reports. Our system was based on a knowledge base about drugs, enriched by supervised machine learning (ML) models trained on patients reporting data. To train our models, we selected all cases of ADRs reported by patients to a French Pharmacovigilance Centre through a national web-portal between March 2017 and March 2019 (n = 2,058 reports). We tested both conventional ML models and deep-learning models. We performed an external validation using a dataset constituted of a random sample of ADRs reported to the Marseille Pharmacovigilance Centre over the same period (n = 187). Here, we show that regarding area under the curve (AUC) and F-measure, the best model to identify ADRs was gradient boosting trees (LGBM), with an AUC of 0.93 (0.92-0.94) and F-measure of 0.72 (0.68-0.75). This model was run for external validation showing an AUC of 0.91 and a F-measure of 0.58. We evaluated an artificial intelligence pipeline that was found able to learn how to identify correctly ADRs from unstructured data. This result allowed us to start a new study using more data to further improve our performance and offer a tool that is useful in practice to efficiently manage drug safety information.

Safety profile of drugs for advanced melanoma: A report based on 2008-2018 US Food and Drug Administration Data.

We describe the safety profiles of all drug classes used for the treatment of advanced melanoma from the US Food and Drug Administration Adverse Event Reporting System over 2008-2018. Adverse reactions reported in 25 900 pharmacovigilance cases are described for chemotherapies, immunomodulators, targeted therapies and immunotherapies. There was a sharp increase in the number of cases over time, with peaks associated with the launch of new treatments. The adverse reactions diversified over time; notably, skin (alopecias, dermatitis) and retinal disorders were frequently associated with targeted therapies and endocrine disorders (hypothalamus, thyroid and adrenal dysfunctions) with immunotherapies. Less well-known reactions were also detected, such as neuropsychiatric disorders with targeted therapies and gastrointestinal ulcers, pneumothorax and pleural effusions with immunotherapies. The findings highlight the need for various health professionals (including medical specialists or trained nurses) to enhance management of complications.

Genesis of an emergency public drug information website by the French Society of Pharmacology and Therapeutics during the COVID-19 pandemic.

On March 16, 2020, the French Society of Pharmacology and Therapeutics put online a national Question and Answer (Q&A) website, https://sfpt-fr.org/covid19 on the proper use of drugs during the COVID-19 pandemic. The working group 'Drugs and COVID-19' was composed of a scientific council, an editorial team, and experts in the field. The first questions were posted online during the first evening of home-confinement in France, March 17, 2020. Six weeks later, 140 Q&As have been posted. Questions on the controversial use of hydroxychloroquine and to a lesser extent concerning azithromycin have been the most consulted Q&As. Q&As have been consulted 226 014 times in 41 days. This large visibility was obtained through an early communication on Twitter, Facebook, traditional print, and web media. In addition, an early communication through the French Ministry of Health and the French National Agency for Medicines and Health Products Safety ANSM had a large impact in terms of daily number of views. There is a pressing need to sustain a public drug information service combining the expertise of scholarly pharmacology societies, pharmacovigilance network, and the Ministry of Health to quickly provide understandable, clear, expert answers to the general population's concerns regarding COVID-19 and drug use and to counter fake news.

DPP-4 Inhibitors in Combination with Lipid-Lowering Agents and Risk of Serious Muscular Injury: A Nested Case-Control Study in a Nationwide Cohort of Patients with Type 2 Diabetes Mellitus.

INTRODUCTION: After a safety warning was issued for a risk of muscular injury associated with dipeptidyl peptidase-4 (DPP-4) inhibitor use, especially when co-prescribed with statins, spontaneous reporting analyses provided conflicting results. OBJECTIVE: The aim of this study was to investigate the association between DPP-4 inhibitor use and the risk of muscular injury in individuals with type 2 diabetes mellitus using statins or fibrates. METHODS: We conducted a nested case-control study amongst a cohort of individuals with type 2 diabetes using statins or fibrates, identified from a nationwide French health insurance database (2009-2014). Cases of serious muscular injury were defined as subjects hospitalized for rhabdomyolysis or myopathy, or for whom testing for myoglobin or creatine phosphokinase followed by a change in statin or fibrate prescription (dose decrease, treatment switch, or stop) was identified. Up to ten controls were matched to each case according to sex, age, and type of lipid-lowering agent. Associations between DPP-4 inhibitor use and serious muscular injury were estimated using a multivariate conditional logistic regression model, providing odds ratios (ORs) adjusted for alcoholism, chronic renal failure, hypothyroidism, and number of concomitant drugs. RESULTS: Within the 35,117 individuals with type 2 diabetes mellitus constituting the source cohort, 437 statin-user cases were identified who were matched to 4358 statin-user controls. Similarly, 54 fibrate-user cases were identified who were matched to 540 fibrate-user controls. The adjusted OR for DPP-4 inhibitor use and serious muscular injury was estimated at 1.0 (95% confidence interval [CI] 0.7-1.2) in statin users and 0.8 (95% CI 0.4-1.9) in fibrate users. CONCLUSION: In this study, DPP-4 inhibitor use was not associated with an increased risk of serious muscular injury among patients with type 2 diabetes mellitus using statins or fibrates.

Cardiovascular Toxicity of Tyrosine Kinase Inhibitors Used in Chronic Myeloid Leukemia: An Analysis of the FDA Adverse Event Reporting System Database (FAERS).

Tyrosine kinase inhibitors (TKIs), the treatment of choice for chronic myeloid leukemia (CML), can be associated to cardiovascular (CV) adverse events (AEs). A case/non-case study was performed using AE reports registered in the Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database to compare the risk of CV event reports related to TKIs indicated in the management of chronic myeloid leukemia (CML). Disproportionality of CV event-related TKIs was computed using the Reporting Odds Ratio (ROR) as a measure of potential risk increase. Nilotinib accounts for more than half of reported cases related to TKIs. Signal of Disproportionate Reporting (SDR) was found for cardiac failure, ischemic heart disease, cardiac arrhythmias, torsade de pointes/QT prolongation, hypertension, and pulmonary hypertension. Dasatinib and bosutinib were related to the highest disproportionality for cardiac failure. Nilotinib was associated with the highest SDR for ischemic heart disease, torsade de pointes/QT prolongation and cardiac arrhythmias. Only ponatinib was related to an SDR for hypertension, while dasatinib and imatinib were related to pulmonary hypertension. In the context of CML, TKIs have different safety profiles related to CV events, among which nilotinib seems particularly related to. These results claim for a revision of its CV safety profile mainly for the risk of torsade de pointes/QT prolongation.

Spontaneous Reports of Serious Adverse Drug Reactions Resulting From Drug-Drug Interactions: An Analysis From the French Pharmacovigilance Database.

Few data are available on the clinical impact of drug-drug interactions (DDIs). Most of the studies are limited to the analysis of exposure to potential DDI or the targeted impact of the combination of a few drugs or therapeutic classes. The analysis of adverse drug reaction (ADR) reports could be a mean to study generally the adverse effects identified due to a DDI. Our objective was to describe the characteristics of ADRs resulting from DDIs reported to the French Pharmacovigilance system and to identify the drugs most often implicated in these ADRs. Considering all ADR reports from January 01, 2012, to December 31, 2016, we identified all cases of ADR resulting from a DDI (DDI-ADRs). We then described these in terms of patients' characteristics, ADR seriousness, drugs involved (two or more per case), and ADR type. Of the 4,027 reports relating to DDI-ADRs, 3,303 were related to serious ADRs. Patients with serious DDI-ADRs had a median age of 76 years (interquartile range: 63-84); 53% were male. Of all serious DDI-ADRs, 11% were life-threatening and 8% fatal. In 36% of cases, the DDI causing the ADR involved at least three drugs. Overall, 8,424 different drugs were mentioned in the 3,303 serious DDI-ADRs considered. Altogether, drugs from the "antithrombotic agents" subgroup were incriminated in 34% of serious DDI-ADRs. Antidepressants were the second most represented therapeutic/pharmacological subgroup (5% of serious DDI-ADRs). Among the 3,843 ADR types reported in the 3,303 serious DDI-ADRs considered, the most frequently represented were hemorrhage (40% clinical hemorrhage; 6% biological hemorrhage), renal failure (8%), pharmacokinetic alteration (5%), and cardiac arrhythmias (4%). Hemorrhagic accidents are still an important part of serious ADRs resulting from DDIs reported in France. The other clinical consequences of DDIs seem less well identified by pharmacovigilance. Moreover, more than one-third of serious DDI-ADRs involved at least three drugs.

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.

Impact of cancer diagnosis on persistence of oral antidiabetic drugs.

AIMS: The purpose of this study was to determine the effects of cancer occurrence on persistence of oral antidiabetic drugs (OAD) in France. METHODS: A retrospective cohort including incident OAD users between 2006 and 2011 was set up using a permanent sample of health insurance beneficiaries (Echantillon Généraliste de Bénéficiaires, EGB). A Cox model was used to assess the association between cancer occurrence and OAD persistence. Non-persistence was defined as a gap in OAD treatment coverage between the end of a given prescription and a new one greater than or equal to 90 days. Cancer occurrence was studied as a time-dependent variable. RESULTS: The study included 13,943 OAD users. Median follow-up was 760 days. After adjustment for age, sex, first OAD used, type of prescriber and polypharmacy, non-persistence risk was higher after a diagnosis of cancer: (HR: 1.93 and IC 95% 1.69; 2.21). Subgroup analyses according to cancer localization found a higher risk of non-persistence for lung cancer (HR: 2.66 and IC 95% 1.68; 4.23) and colorectal cancer (HR: 2.02 and IC 95% 1.40; 2.91). CONCLUSIONS: Our findings indicate there is an association between cancer diagnosis and OAD non-persistence. Additional studies of this type would be useful to evaluate the association between cancer diagnosis and persistence of treatment of other chronic diseases.

Parachuting psychoactive substances: Pharmacokinetic clues for harm reduction.

BACKGROUND: Parachuting, also called bombing, is a way to ingest psychoactive substances wrapped into cigarette paper, toilet paper, etc. There is little data describing parachuting in terms of substances use, context of use and, most importantly, the motivations for using such wrappers, although some authors hypothesized that parachute could be used for pharmacokinetic reason. However, inconsistently, some authors report that parachutes are used for sustained-release whereas others report that users are looking for an immediate effect. RESEARCH DESIGN AND METHODS: Considering parachute as a "home-made" dosage form, we have applied the dissolution testing to characterize the dissolution performance of a substance wrapped into a parachute and to characterize whether a parachute represents an immediate-release form or not. RESULTS: This in-vitro study provides the first pharmacokinetic data for drugs wrapped in parachutes. It shows that parachute acts as sustained-release form when made with a cigarette paper wrapper, but as immediate release form in the presence of alcohol or if wrapped with toilet paper. CONCLUSIONS: An important message to harm reduction is that users must be aware that a parachute can have unexpected pharmacokinetics and have to avoid taking another parachute in the absence of an immediate-effect to avoid overdose.

Pharmacological treatments of cardiovascular diseases: Evidence from real-life studies.

The management of chronic cardiovascular diseases has evolved greatly in the last decades. Over the last thirty years, the management of acute coronary syndrome has improved, leading to an important lowering of the mortality in the acute phase of the event. Consequently, the optimal management of the secondary prevention of acute coronary syndrome has greatly evolved. Moreover, the increased number of pharmacological alternatives for patients affected by chronic heart failure and by non-valvular atrial fibrillation reserves a number of challenges for their correct management. Moreover, these diseases are without any reasonable doubt the largest contributor to global mortality in the present and will continue to be it in the future. The aim of this study was to provide the most updated information of the real-life drug use and their effectiveness. This review was performed to assess the potential knowledge gaps in the treatments of these diseases and to indicate potential perspective of pharmaco-epidemiological research in this area.