Anatomical Therapeutic Chemical Research Articles

Classifying Multimorbidity Using Drug Concepts via the Rx-Risk Comorbidity Index: Methods and Comparative Cross-Sectional Study.

The study objective was to update a method to identify comorbid conditions using only medication information in circumstances in which diagnosis codes may be undercaptured, such as in single-specialty electronic health records (EHRs), and to compare the distribution of comorbidities across Rx-Risk versus other traditional comorbidity indices. Using First Databank, RxNorm, and its web-based clients, RxNav and RxClass, we mapped Drug Concept Unique Identifiers (RxCUIs), National Drug Codes (NDCs), and Anatomical Therapeutic Chemical (ATC) codes to Rx-Risk, a medication-focused comorbidity index. In established rheumatoid arthritis (RA) and osteoarthritis (OA) cohorts within the Rheumatology Informatics System for Effectiveness registry, we then compared Rx-Risk with other comorbidity indices, including the Charlson Comorbidity Index, Rheumatic Disease Comorbidity Index (RDCI), and Elixhauser. We identified 965 unique ingredient RxCUIs representing the 46 Rx-Risk comorbidity categories. After excluding dosage form and ingredient related RxCUIs, 80,911 unique associated RxCUIs were mapped to the index. Additionally, 187,024 unique NDCs and 354 ATC codes were obtained and mapped to the index categories. When compared to traditional comorbidity indices in the RA cohort, the median score for Rx-Risk (median 6.00 [25th percentile 2, 75th percentile 9]) was much greater than for Charlson (median 0 [25th percentile 0, 75th percentile 0]), RDCI (median 0 [25th percentile 0, 75th percentile 0]), and Elixhauser (median 1 [25th percentile 1, 75th percentile 1]). Analyses of the OA cohort yielded similar results. For patients with a Charlson score of 0 (85% of total), both the RDCI and Elixhauser were close to 1, but the Rx-Risk score ranged from 0 to 16 or more. The misclassification and under-ascertainment of comorbidities in single-specialty EHRs can largely be overcome by using a medication-focused comorbidity index.

Clinical aspects of reimbursement policies for orphan drugs in Central and Eastern European countries.

Objectives: The aim of this study was to characterize the reimbursement policy for orphan drugs (ODs) in Central and Eastern European (CEE) countries in relation to the availability and impact of clinical evidence, health technology assessment (HTA) procedure, selected economic indicators, and the drug type according to indications. Materials and methods: A list of authorized medicines with orphan designation and information about active substance, Anatomical Therapeutic Chemical (ATC) classification, and therapeutic area was extracted from the web-based register of the European Medicines Agency (EMA). A country-based questionnaire survey was performed between September 2021 and January 2022 in a group of selected experts from nine CEE countries (an invitation was sent to 11 countries). A descriptive and statistical analysis was conducted to determine statistical significance, correlations, between the drug or country characteristic and the positive recommendation or reimbursement of ODs. Results: The proportion of reimbursed orphan drugs differed between countries, ranging from 17.7% in Estonia to 49.6% in Hungary (p < 0.001). The odds that ODs were reimbursed were reduced in countries with a "strong" level of impact of drug safety and efficacy on reimbursement decisions (p=0.018), the presence of other additional specific clinical aspects (e.g., genomic data) considered in the reimbursement decision (p < 0.001) and mandatory (without exception) safety assessments (p=0.004). The probability that ODs were reimbursed was increased in countries with a "moderate" level of impact of drug safety and efficacy on reimbursement decisions (p=0.018), when reimbursement decisions are dependent on the EMA registration status and orphan drug designation (p < 0.001), the presence of the "positive HTA recommendation guarantees reimbursement" policy (p < 0.001), higher GDP per inhabitant (p=0.003), and higher healthcare expenditure (p < 0.001). Conclusion: We found that there are differences among CEE countries in the reimbursement of orphan drugs, and we identified aspects that may influence these differences. Safety, efficacy, and specific clinical aspect issues significantly influenced reimbursement decisions. Antineoplastic and immunomodulating agents drugs were the largest group of ODs and increased the chance of getting a positive recommendation. The higher GDP per inhabitant and healthcare expenditures per inhabitant were positively linked to the chance that an OD receives reimbursement.

In silico off-target profiling for enhanced drug safety assessment

Ensuring drug safety in the early stages of drug development is crucial to avoid costly failures in subsequent phases. However, the economic burden associated with detecting drug off-targets and potential side effects through in vitro safety screening and animal testing is substantial. Drug off-target interactions, along with the adverse drug reactions they induce, are significant factors affecting drug safety. To assess the liability of candidate drugs, we developed an artificial intelligence model for the precise prediction of compound off-target interactions, leveraging multi-task graph neural networks. The outcomes of off-target predictions can serve as representations for compounds, enabling the differentiation of drugs under various ATC codes and the classification of compound toxicity. Furthermore, the predicted off-target profiles are employed in adverse drug reaction (ADR) enrichment analysis, facilitating the inference of potential ADRs for a drug. Using the withdrawn drug Pergolide as an example, we elucidate the mechanisms underlying ADRs at the target level, contributing to the exploration of the potential clinical relevance of newly predicted off-target interactions. Overall, our work facilitates the early assessment of compound safety/toxicity based on off-target identification, deduces potential ADRs of drugs, and ultimately promotes the secure development of drugs.

Treatment failure of Helicobacter pylori in primary care: a retrospective cohort study.

Owing to increasing antibiotic resistance, the worldwide efficacy of Helicobacter pylori (HP) eradication treatment has decreased. To determine antimicrobial resistance of HP in primary care. Retrospective cohort study using real-world routine healthcare data from 80 general practices in the Netherlands. Patients with International Classification of Primary Care (ICPC) codes for gastric symptoms or Anatomical Therapeutic Chemical (ATC) codes for acid inhibition in the period 2010-2020 were selected. Main outcomes were antimicrobial resistance of HP, defined as the prescription of a second eradication treatment within 12 months, and clinical remission of gastric symptoms, defined as no usage of acid inhibition 1 year following eradication therapy. We identified 138 455 patients with gastric symptoms and/or acid inhibition use (mean age 57 years [standard deviation 18.2 years], 43% male). A total of 5224 (4%) patients received an HP eradication treatment. A second treatment was prescribed to 416 (8%) of those patients. From these, 380 patients received amoxicillin-clarithromycin, 16 amoxicillin-metronidazole, and 11 clarithromycin-metronidazole as first regimen and were considered antimicrobial resistant. We observed a 0.8% increment per year of patients requiring a second eradication treatment (P = 0.003, 95% confidence interval = 0.33 to 1.22). After successful eradication, 2329/4808 (48%) patients used acid inhibition compared with 355/416 (85%) patients following treatment failure (P<0.001). Antimicrobial treatment is not successful in almost one-tenth of HP infections in primary care after a first treatment containing clarithromycin and/or metronidazole. Although the treatment failure rate is not as high as reported in secondary care, the increasing trend is concerning and may require revision of the current guidelines.

EVALUATION OF ANTIBIOTIC USE USING THE ATC/DD AND DU 90% METHODS IN OUTPATIENT PATIENTS IN PUSKESMAS RI TENAYAN RAYA

Infectious diseases are one of the health problem that threaten developing countries, including Indonesia. Riau as one of the provinces with its coastal coverage is not spared from this problem. Inaccurate use of antibiotics is found in the wider community, which can be a cause of negative risks such as antibiotic resistance. Antibiotics are drugs that are used to treat diseases caused by microbes. The improper use of antibiotics can lead to a risk of resistance. Resistance can be avoided using antibiotics. This study aimed to classify antibiotic use using ATC codes and determine the quantity of antibiotic use in outpatients by calculating the DDD. This research method was observational, with a descriptive design and retrospective data collection using secondary data by searching medical records. The sample in this study consisted of outpatients at the Tenayan Raya Inpatient Health Center Outpatient Installation between January and December 2022 who received antibiotic therapy with an ATC code and DDD value in accordance with the provisions of the WHO Collaborating Center, using a total sampling technique.The results of the study showed that based on the ATC/DDD and DU 90% methods, there were 3 antibiotics with the highest quantity of use, namely amoxicillin at 165,92 DDD/1000 KPRJ with a percentage of 67,02%, ciprofloxacin at 41,07 DDD/1000 KPRJ with a percentage of 16,59 %, and cefixime as much as 14,69 DDD/1000 KPRJ with a percentage of 5,93%. Keywords: antibiotics, ATC/DD, DU 90%, resistance

Hoarding of insulin and oral antidiabetics in the first phase oftheCOVID-19 pandemic: Regulatory actions taken to avoid shortage.

To report on hoarding of prescribed medicines, with focus on insulins, in the early phase of the COVID-19 pandemic and on regulatory actions taken to avoid shortage. The National Prescribed Drug Register which utilizes the Anatomic Therapeutic Chemical (ATC) Classification System and covers the total Swedish population was used. We calculated the number of packages of insulins (ATC code A10A), oral anti-diabetics (A10B), and all medicines across all ATC codes combined (A-S) dispensed per week in 2019 and 2020. Correspondingly, the number of packages of glucose test strips dispensed was calculated using the data source Concise held by the Swedish eHealth Agency. Prompt increases in numbers of dispensed packages were observed in March, peaking at week 11/2020. The absolute numbers of packages dispensed in week 11/2019 and week 11/2020 were: insulin, 49,694 and 95,767, an increase by +92.7%; oral antidiabetics, 55,478 and 82,684, +47.1%; glucose test strips, 18,119 and 23,476, +29:6%; and all medicines across all ATC codes combined, 1,988,456 and 2,659,421, +33.7%. Voluntary restriction of dispensing and a rapid change to applicable regulation were implemented within 2 weeks. A steep decline occurred, which became more pronounced after temporary regulation came in force from April 1, then leveling out during the following months. A signal of insulin hoarding was detected early in the COVID-19 pandemic. A temporary regulation, reducing dispensing to a maximum supply of 3 months was rapidly implemented. A shortage of vitally important prescribed medicines was avoided.

Categorical Analysis of Database Consistency in Reporting Drug-Drug Interactions for Cardiovascular Diseases.

Drug-drug interactions (DDIs) can either enhance or diminish the positive or negative effects of the associated drugs. Multiple drug combinations create difficulties in identifying clinically relevant drug interactions; this is why electronic drug interaction checkers frequently report DDI results inconsistently. Our paper aims to analyze drug interactions in cardiovascular diseases by selecting drugs from pharmacotherapeutic subcategories of interest according to Level 2 of the Anatomical Therapeutic Chemical (ATC) classification system. We checked DDIs between 9316 pairs of cardiovascular drugs and 25,893 pairs of cardiovascular and other drugs. We then evaluated the overall agreement on DDI severity results between two electronic drug interaction checkers. Thus, we obtained a fair agreement for the DDIs between drugs in the cardiovascular category, as well as for the DDIs between drugs in the cardiovascular and other (i.e., non-cardiovascular) categories, as reflected by the Fleiss' kappa coefficients of κ=0.3363 and κ=0.3572, respectively. The categorical analysis of agreement between ATC-defined subcategories reveals Fleiss' kappa coefficients that indicate levels of agreement varying from poor agreement (κ<0) to perfect agreement (κ=1). The main drawback of the overall agreement assessment is that it includes DDIs between drugs in the same subcategory, a situation of therapeutic duplication seldom encountered in clinical practice. Our main conclusion is that the categorical analysis of the agreement on DDI is more insightful than the overall approach, as it allows a more thorough investigation of the disparities between DDI databases and better exposes the factors that influence the different responses of electronic drug interaction checkers. Using categorical analysis avoids potential inaccuracies caused by particularizing the results of an overall statistical analysis in a heterogeneous dataset.

Trends in orphan medicinal products approvals in the European Union between 2010–2022

BackgroundOver the last twenty years of orphan drug regulation in Europe, the regulatory framework has increased its complexity, with different regulatory paths and tools engineered to facilitate the innovation and accelerate approvals. Recently, the proposal of the new Pharmaceutical Legislation for the European Union, which will replace at least three Regulations and one Directive, was released and its new framework is raising many questions. The aim of this study was to present a characterisation of the Orphan Medicinal Products (OMPs) authorised by the European Commission (EC), between 2010 and 2022, looking into eighteen variables, contributing to the ongoing discussion on the proposal and implementation of the new Pharmaceutical Legislation proposed.MethodsData of the OMPs identified and approved between 2010 and 2022 were extracted from the European Public Assessment Reports (EPARs) produced by the European Medicines Agency. Information regarding legal basis of the application, applicant, protocol assistance received, type of authorization, registration status, type of molecule, ATC code, therapeutic area, target age, disease prevalence, number of pivotal clinical trials supporting the application, clinical trial designs, respective efficacy endpoints and number of patients enrolled in the pivotal clinical trials were extracted. A descriptive statistical analysis was applied.ResultsWe identified 192 OMPs approved in the period between 2010 and 2022. 89% of the OMPs have legal basis of “full application”. 86% of the sponsors received protocol assistance whereas 64% of the MAA benefited from the accelerated assessment. 53% of the active substances are small molecules; about 1 in 5 molecules are repurposed. 40% of the OMPs have oncological therapeutic indications and 56% of the OMPs are intended to treat only adults. 71% of the products were approved based on a single pivotal trial.ConclusionsThis analysis of OMPs approved between 2010 and 2022 shows that a shift has occurred in the rare disease medicine development space. Through the period studied we observe an increase of non-small molecules approved, accelerated assessment received and non-standard MA’s granted.

Injectable antibiotic use in India: public-private share in volume and cost.

Consumption of injectable antibiotics is not widely studied, despite injectables constitute a major share of antibiotic cost. This study aimed to understand the share of oral and injectable antibiotic consumption and cost at the national level in India, and the public and private sector shares in the provision and cost of injectables in Kerala state. We used the PharmaTrac private sector sales dataset and the Kerala Medical Services Corporation public sector procurement dataset. Using WHO Access, Watch, Reserve (AWaRe) and Anatomical Therapeutic Chemical (ATC) Classifications, we estimated the annual total and per-capita consumption, and the annual total, per defined daily dose (DDD), and per-capita spending on injectables. Although 94.9% of total antibiotics consumed at the national level were oral preparations, 35.8% of total spending were on injectables. In Kerala , around 33% of total antibiotic spending in the private sector were for injectables, compared to around 25% in the public sector. The public sector used fewer injectable antibiotic formulations (n=21) compared the private sector (n=69). The cost per DDD was significantly higher in the private sector as compared to the public sector. Despite only accounting for 6.3% of the cost share, the public sector provided 31.4% of injectables, indicating very high efficiency. Across both sectors, Watch group antibiotics were significantly more consumed and at a significantly higher cost than Access group antibiotics, for example in nearly double the quantity and at 1.75 times the price per DDD in the private sector. Reserve group antibiotics made up the lowest consumption share (0.61% in the private sector), but at the highest cost per DDD (over 16 times that of Access). Public sector showed higher cost efficiency in antibiotic provisioning compared to private sector. Appropriate antibiotic use cannot be achieved through drug price control alone but requires extensive engagement with private providers through structured stewardship programs.

Applying Machine Learning and Statistical Forecasting Methods for Enhancing Pharmaceutical Sales Predictions

In today’s evolving global world, the pharmaceutical sector faces an emerging challenge, which is the rapid surge of the global population and the consequent growth in drug production demands. Recognizing this, our study explores the urgent need to strengthen pharmaceutical production capacities, ensuring drugs are allocated and stored strategically to meet diverse regional and demographic needs. Summarizing our key findings, our research focuses on the promising area of drug demand forecasting using artificial intelligence (AI) and machine learning (ML) techniques to enhance predictions in the pharmaceutical field. Supplied with a rich dataset from Kaggle spanning 600,000 sales records from a singular pharmacy, our study embarks on a thorough exploration of univariate time series analysis. Here, we pair conventional analytical tools such as ARIMA with advanced methodologies like LSTM neural networks, all with a singular vision: refining the precision of our sales. Venturing deeper, our data underwent categorisation and were segmented into eight clusters premised on the ATC Anatomical Therapeutic Chemical (ATC) Classification System framework. This segmentation unravels the evident influence of seasonality on drug sales. The analysis not only highlights the effectiveness of machine learning models but also illuminates the remarkable success of XGBoost. This algorithm outperformed traditional models, achieving the lowest MAPE values: 17.89% for M01AB (anti-inflammatory and antirheumatic products, non-steroids, acetic acid derivatives, and related substances), 16.92% for M01AE (anti-inflammatory and antirheumatic products, non-steroids, and propionic acid derivatives), 17.98% for N02BA (analgesics, antipyretics, and anilides), and 16.05% for N02BE (analgesics, antipyretics, pyrazolones, and anilides). XGBoost further demonstrated exceptional precision with the lowest MSE scores: 28.8 for M01AB, 1518.56 for N02BE, and 350.84 for N05C (hypnotics and sedatives). Additionally, the Seasonal Naïve model recorded an MSE of 49.19 for M01AE, while the Single Exponential Smoothing model showed an MSE of 7.19 for N05B. These findings underscore the strengths derived from employing a diverse range of approaches within the forecasting series. In summary, our research accentuates the significance of leveraging machine learning techniques to derive valuable insights for pharmaceutical companies. By applying the power of these methods, companies can optimize their production, storage, distribution, and marketing practices.

Concordance between essential medicines lists and diabetes guidelines in Latin America and the CaribbeanConcordância entre as listas de medicamentos essenciais e diretrizes para diabetes na América Latina e no Caribe

Conduct an analysis to determine the existence and updating of national essential medicines lists (EMLs) and clinical practice guidelines (CPGs) for the treatment of diabetes in Latin America and the Caribbean (LAC); and compare the medicines included in each country's list and guidelines both with each other and with those of the World Health Organization (WHO). Cross-sectional study. EMLs and CPGs for diabetes were found on the websites of the Pan American Health Organization and national health authorities. Medicines were noted and analyzed according to pharmacological group, based on the fourth level of nomenclature of the Anatomical Therapeutic Chemical (ATC) classification system. F1 scoring was used to assess the proximity of EMLs to the WHO Model List of Essential Medicines (MLEM). Of the total number of countries, 87.2% have EMLs, and 91% have CPGs (78% and 45% updated in the last five years, respectively). Compared to the six hypoglycemic groups of the MLEM, the EMLs had a median (range) of 6 (4-13) and an F1 score of 0.80; This indicates proper alignment. CPGs had a median (range) of 12 (1-12) hypoglycemic drugs compared to eight in the WHO guidelines. CPGs had a median of 15 more drugs than their respective EMLs. While most LAC countries have EMLs and CPGs for diabetes, the lack of concordance among them limits their effectiveness. It is necessary to align the processes and criteria for the development of these two tools for policymaking on medicines.

Prescriptions of psychotropic and somatic medications among patients with severe mental disorders and healthy controls in a naturalistic study

Purpose Psychotropic and somatic medications are both used in treating severe mental disorders (SMDs). Realistic estimates of the prevalence of use across medication categories are needed. We obtained this in a clinical cohort of patients with SMD and healthy controls (HCs). Materials and methods Prescriptions filled at Norwegian pharmacies the year before and after admittance to the Thematically Organized Psychosis (TOP) study were examined in 1406 patients with SMD (mean age 32.5 years, 48.2% women) and 920 HC (34.1 years, 46.2% women). Using data from the Norwegian Prescription Database (NorPD), the number of users in different anatomical therapeutic chemical (ATC) categories was compared using logistic regression. Population estimates were used as reference data. Results Use of antipsychotics (N05A), antiepileptics (N03A), antidepressants (N06A), anxiolytics (N05B), hypnotics and sedatives (N05C), anticholinergics (N04A), psychostimulants, attention deficit hyperactivity disorder and nootropic agents (N06B) and drugs for addiction disorders (N07B) was significantly more prevalent in patients with SMD than HC. Use of diabetes treatment (A10), antithrombotic drugs (B01), beta blockers (C07), lipid modifiers (C10), and thyroid and endocrine therapeutics (H03) was also more prevalent in patients with SMD, but with two exceptions somatic medication use was comparable to the general population. Among HC, there was low prevalence of use for most medication categories. Conclusion Patients were using psychiatric medications, but also several types of somatic medications, more often than HC. Still, somatic medication use was mostly not higher than in the general population. The results indicate that HC had low use of most medication types.

Cardiovascular medications and overall survival in metastatic hormone-sensitive prostate cancer.

75 Background: The assessment of comorbid cardiovascular disease can predict health outcomes and may risk-stratify patients for adverse events and death. Current methods used to estimate patient risk, such as the Charlson Comorbidity Index (CCI), are based on International Classification of Diseases (ICD) codes, which are a poor indicator of severity and complexity of comorbid disease. Alternatively, the number of cardiovascular drugs could be an efficient tool for estimating patient risk. In this study, we examined the relationship between cardiovascular medications and survival in patients being treated for metastatic hormone-sensitive prostate cancer (mHSPC). Methods: A nationwide retrospective observational study of US Veterans with de novo mHSPC in the Veterans Health Administration between 2011-2021 with at least 1 prescription medicine of any class. We determined the number of cardiovascular drugs from Anatomic Therapeutic Chemical (ATC) drug class C prescribed in the year prior up to 14 days before initiation of treatment. Multivariable logistic regression and Cox proportional hazard modeling was used to assess the association between number of drugs with overall survival (OS) while accounting for important covariates including age, body-mass index (BMI), prostate specific antigen (PSA), CCI, race, and weight change. Results: Among 7,875 veterans, a median (IQR) of 2 (1-4) unique cardiovascular medications were filled in the year prior to treatment. The mean age was 74.3 years (SD 10.0) with a median CCI of 3 (3-6). Age was associated with increased number of cardiac medicines with a mean of 1.6 drugs in &lt;60 years, 2.2 drugs in 60-69, 2.5 drugs in 70-80, and 2.5 drugs in 80+ years (p&lt;0.001). Increased number of medications was associated with decreased OS using the Kaplan-Meier method (p&lt;0.001, see table). After adjusting for age, race, BMI, weight change, PSA, and CCI, the number of medications was independently associated with increased mortality with an adjusted hazard ratio (aHR) of 1.05 (1.03-1.06) for each additional cardiac drug. Increased mortality was observed in patients treated with 2 or more cardiac drugs (see table). Conclusions: The number of cardiovascular medications is associated with decreased survival in veterans undergoing treatment for mHSPC, even after accounting for important covariates including age, BMI, PSA, and CCI. The assessment of cardiovascular medications may provide a simple and reliable tool to estimate comorbid disease and survival in patients with cancer. [Table: see text]

Number of prescription medications and overall survival in veterans with metastatic hormone-sensitive prostate cancer.

68 Background: Robustassessment of comorbid conditions is essential to clinical care and the risk-stratification of patients for adverse events and death. Prescription medications may be a simple and readily available tool to estimate patient risk independent of established comorbidity indices, such as the Charlson Comorbidity Index (CCI). Clinicians have access to medication lists, facilitating assessment of comorbidities. We sought to examine the relationship between prescription medications and long-term outcomes in veterans treated for metastatic hormone-sensitive prostate cancer (mHSPC). Methods: We conducted a nationwide retrospective observational study of United States Veterans diagnosed with mHSPC in the Veterans Health Administration from 2010-2021. We determined the number of unique drugs and their respective Anatomic Therapeutic Chemical (ATC) Level One classes prescribed in the year prior to the initiation of treatment. Multivariable logistic regression and Cox proportional hazard modeling was used to assess the association between number of drugs with all-cause 90-day mortality and overall survival (OS) while accounting for covariates including age, CCI, body mass index, prostate specific antigen, and race. Results: Among 8,434 Veterans, a median (IQR) of 9 (5-14) unique medications and 5 (3-7) unique ATC medication classes were filled in the year prior to treatment. The mean age was 74.2 (SD 10.1) years, and 2,126 Veterans were black (25.2%). The median CCI was 3 (2.75-6). Increasing age was associated with increased CCI across age strata with mean CCI of 3.16 in age &lt;60, 3.76 in 60-70, 4.43 in 70-80, and 5.25 in 80+ (p&lt;0.001). Increasing age was associated with an increased number of unique medicines with mean 8.59 in age &lt;60, 9.53 in 60-70, 10.1 in 70-80, and 10.4 in 80+ (p&lt;0.001). There was no significant difference in the number of medications prescribed based on race. Veterans with 1-4 medicines had the longest average survival at 38.2 months compared to 5-9 medicines (33.1 months), 10-14 medicines (27.1 months), and 15+ medicines (22.0 months) (p&lt;0.001). After adjusting for relevant patient, tumor, and treatment factors, the number of medications and drug classes were each independently associated with increased mortality with adjusted HR (95% CI) of 1.03 (1.02-1.03) and 1.05 (1.04-1.07), respectively. Veterans treated with 5-9, 10-14, and 15+ medicines had an increased risk of death compared to Veterans on 1-4 medicines [aHR 1.11 (1.03-1.19); 1.29 (1.19-1.39); and 1.51 (1.39-1.65) respectively]. Conclusions: The number of prescription medications and drug classes are independently associated with OS in patients diagnosed with mHSPC, even after accounting for important covariates including age and CCI. Assessment of patient medications may provide a simple, yet reliable tool to assess comorbidities, risk of adverse events, and death.

Medication-overuse headache: A pharmacovigilance study in France

Overusing medication for primary headaches or other medical conditions can lead to dependency and medication-overuse headache (MOH) as an adverse drug reaction (ADR). To analyse reports of ADRs associated with MOH recorded in the French national pharmacovigilance database (FPVD). This retrospective study selected all MOH cases reported in the FPVD from January 2000 to June 2023. A search of the High-Level Group Term "headache" was performed for drugs classified under ATC codes for the musculoskeletal and nervous systems. Specific keywords were searched in report narratives to further reduce their number. Voluntary intoxication reports were excluded. Only MOH cases according to the International Classification of Headache Disorders or with a medical diagnosis of MOH were considered. Among the 2674 reports associated with the HLGT "headache", for 649 ATC drug codes, only 234 reports correspond to MOH, primarily notified by physicians. The median age was 45 years (IQR: 32-56), with 74.4% females and approximately 61.0% having pre-existing primary headaches. In all, 53.4% of the reports were classified as serious. Among patients, 84.2% had an isolated "headache" as the ADR. One drug was suspected in 47.4% of cases, two drugs in 29.1%, and three or more in 23.5%. In total, 473 suspected drugs, corresponding to 104 active ingredients, were involved, including analgesics (63.0%), in particular, acetaminophen-containing drugs, opioids, triptans and ergots, and non-steroidal anti-inflammatory drugs (12.7%). Antiepileptics and psycholeptics were found in 6.6% and 6.1% of cases, respectively. Drug withdrawal was successful in 84.6% of drug-discontinuation cases. Warnings about MOH are mentioned in the summary of product characteristics (SmPCs) for triptans, ergots, and certain acetaminophen-containing drugs, but not other drug classes. Certain drug classes show a high reporting rate of MOH and caution should be exercised when prescribing these drugs. Notably, warnings about MOH must be mentioned in the SmPC of all concerned drug classes.

Childhood Bullying as a Predictor of Suicidality in Young Adults in a Nationwide Population-Based Health Examination Study

Objective Having been bullied at school in childhood links to suicidality. We aimed at verifying earlier findings and delivering diverse data from a representative population-based sample of young adults to characterize the impacts beyond childhood. Method A random sample of adults, aged 18–28 years and representative of the general population living in Finland, participated in a nationwide health examination study. Adverse childhood experiences before the age of 16 years were analyzed for 779 participants in relation to lifetime suicidality (suicidal ideation, suicide attempts), current suicidal thoughts (HSCL-25), mental disorders (self-reports for lifetime, M-CIDI for DSM-IV during the past 12 months), current usage of mental health services, current usage of prescription medicines (ATC codes), current psychological distress (GHQ-12), and current work capacity and work ability. Results Having been bullied in childhood contributed to greater suicidality (p < 0.001), more frequent current usage of antipsychotics (p < 0.001) as well as antidepressants (p < 0.001), greater current psychological distress (p < 0.001), and poorer current work capacity (p < 0.001) as well as work ability (p < 0.001). Of the self-reported mental disorders on lifetime basis, psychosis had the strongest association (p = 0.03) with having been bullied, whereas the interview-based diagnosis of mental disorders during the past 12 months had no significant association. Conclusions Having been bullied at school before the age of 16 years was independently associated not only with suicidality, but also with the self-report of psychosis as well as a range of indicators of poorer mental health at the age of 18–28 years.

A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research.

Observational research utilizes patient information from many disparate databases worldwide. To be able to systematically analyze data and compare the results of such research studies, information about exposure to drugs or classes of drugs needs to be harmonized across these data. The NLM's RxNorm drug terminology and WHO's ATC classification serve these needs but are currently not satisfactorily combined into a common system. Creating such system is hampered by a number of challenges, resulting from different approaches to representing attributes of drugs and ontological rules. Here, we present a combined ATC-RxNorm drug hierarchy, allowing to use ATC classes for retrieval of drug information in large scale observational data. We present the heuristic for maintaining this resource and evaluate it in a real world database containing drug and drug classification information.

Treatment patterns in women of childbearing age and pregnant women with epilepsy in Poland between the years 2019 and 2022—A nationwide population-based cohort study

AimTo describe the antiseizure medications (ASMs) prescription pattern in women of childbearing age (WOCA) and pregnant women with epilepsy in the 2019–2022 period in Poland Materials and methodsThe National Health Fund (NHF) databases were analyzed. Women aged 15–49 years were considered as being of childbearing age, while exposure during pregnancy was estimated taking into account 15 months before delivery. ASMs belonging to the N03A subgroup of the Anatomical Therapeutic Chemical Classification System, reimbursed by NHF were analyzed. ResultsDuring 2019, 36 784 WOCA and 921 pregnant women filled at least 1 ASM prescription. In 2022, these numbers were 32 304 and 594, respectively. Valproate was the most widely used ASM in WOCA (38.4 %) in 2019, followed by levetiracetam (35.6 %), lamotrigine (30.1 %), and carbamazepine (20.0 %). The percentage of ASM users decreased in 2022 for valproate (32.1 %; p < 0.001) and carbamazepine (17 %; p < 0.001) and increased for levetiracetam (40.8 %; p < 0.001) and lamotrigine (32.7 %; p < 0.001). In 2019 lamotrigine (42.1 %) and levetiracetam (41.5 %) were the most frequently prescribed ASMs to pregnant women. During the study period, a significant increase in prescriptions for levetiracetam was observed (49.5 %; p = 0.003). The proportion of ASMs exposed pregnancies declined for valproate (from 24.7 to 16 %; p < 0.001) and topiramate (from 6.6 to 3.2 %; p = 0.005). The percentage of polytherapy regimens remained stable over the years, both for WOCA (39 %) and pregnant women (32 %). ConclusionDespite the decline in valproate usage, the drug was still among the most commonly prescribed ASMs in women of childbearing age and pregnant women with epilepsy. The awareness of teratogenic risks and new treatment guidelines should be improved in Poland.

Mental comorbidities in adolescents and young adults with juvenile idiopathic arthritis: an analysis of German nationwide health insurance data

BackgroundStudies on prevalence rates of mental comorbidities in patients with juvenile idiopathic arthritis (JIA) have reported varying results and provided limited information on related drugs. The purpose of this study was to determine the prevalence of selected mental health diagnoses and the range of associated drug prescriptions among adolescents and young adults (AYA) with JIA compared with general population controls.FindingsNationwide statutory health insurance data of the years 2020 and 2021 were used. Individuals aged 12 to 20 years with an ICD-10-GM diagnosis of JIA in ≥ 2quarters, treated with disease-modifying antirheumatic drugs and/or glucocorticoids were included. The frequency of selected mental health diagnoses (depression, anxiety, emotional and adjustment disorders) was determined and compared with age- and sex-matched controls. Antirheumatic, psychopharmacologic, psychiatric, and psychotherapeutic therapies were identified by Anatomical Therapeutic Chemical (ATC) codes and specialty numbers. Based on data from 628 AYA with JIA and 6270 controls, 15.3% vs. 8.2% had a diagnosed mental health condition, with 68% vs. 65% receiving related drugs and/or psychotherapy. In both groups, depression diagnosis became more common in older teenagers, whereas emotional disorders declined. Females with and without JIA were more likely to have a mental health diagnosis than males. Among AYA with any psychiatric diagnosis, 5.2% (JIA) vs. 7.0% (controls) received psycholeptics, and 25% vs. 27.3% psychoanaleptics.ConclusionsSelected mental health conditions among 12-20-year-old JIA patients are diagnosed more frequently compared to general population. They tend to occur more frequently among females and later in childhood. They are treated similarly among AYA regardless of the presence of JIA.

Community Antibiotic Consumption in Cyprus for the Period 2015 to 2022.

Cyprus currently reports to ESAC-Net the total consumption of antimicrobials, without distinguishing between hospital and community-based antibiotic use. As a result, these data can only provide generalized insights into antimicrobial trends in the country. This study is a first attempt to retrospectively analyze community antibiotic consumption in Cyprus for the period of 2015 to 2022. Data on community antimicrobial consumption between 2015 and 2022 were extracted from Pharmatrack's database. Orally administered dispensed antibiotics were categorized under the J01 group of the WHO Anatomical Therapeutic Chemical (ATC) classification and by the WHO's AWaRe classification of antibiotics. Antibiotic consumption was calculated in both packages consumed and per 1000 inhabitants, overall, by year of consumption and districts. During the period of 2015-2022, there was variability in the mean outpatient antibiotic consumption per 1000 inhabitants among the five districts in Cyprus. Community consumption increased by 38% throughout the study period. Additionally, a decrease of 3% in the consumption of WHO 'Access' antibiotics was observed, accompanied with a concurrent increase of 3% in the 'Watch' group. Specifically, in 2022 the WHO 'Access' group consumption in the Cypriot community was 48%, significantly lower than the WHO's goal of 60% and the EU's goal of 70% for 'Access' antibiotic consumption. Antibiotic consumption in the community of Cyprus between 2015 and 2022 demonstrated substantial variability among districts, with higher consumption in less populated areas. There was an increasing trend in community consumption over the years and a decreasing trend in the percentage of 'Access' antibiotics prescribed.