Drug interactions in hospital prescriptions in Denmark: Prevalence and associations with adverse outcomes.

PURPOSE: While the beneficial effects of medications are numerous, drug-drug interactions may lead to adverse drug reactions that are preventable causes of morbidity and mortality. Our goal was to quantify the prevalence of potential drug-drug interactions in drug prescriptions at Danish hospitals, estimate the risk of adverse outcomes associated with discouraged drug combinations, and highlight the patient types (defined by the primary diagnosis of the admission) that appear to be more affected. METHODS: This cross-sectional (descriptive part) and cohort study (adverse outcomes part) used hospital electronic health records from two Danish regions (~2.5 million people) from January 2008 through June 2016. We included all inpatients receiving two or more medications during their admission and considered concomitant prescriptions of potentially interacting drugs as per the Danish Drug Interaction Database. We measured the prevalence of potential drug-drug interactions in general and discouraged drug pairs in particular during admissions and associations with adverse outcomes: post-discharge all-cause mortality rate, readmission rate and length-of-stay. RESULTS: Among 2 886 227 hospital admissions (945 475 patients; median age 62 years [IQR: 41-74]; 54% female; median number of drugs 7 [IQR: 4-11]), patients in 1 836 170 admissions were exposed to at least one potential drug-drug interaction (659 525 patients; median age 65 years [IQR: 49-77]; 54% female; median number of drugs 9 [IQR: 6-13]) and in 27 605 admissions to a discouraged drug pair (18 192 patients; median age 68 years [IQR: 58-77]; female 46%; median number of drugs 16 [IQR: 11-22]). Meropenem-valproic acid (HR: 1.5, 95% CI: 1.1-1.9), domperidone-fluconazole (HR: 2.5, 95% CI: 2.1-3.1), imipramine-terbinafine (HR: 3.8, 95% CI: 1.2-12), agomelatine-ciprofloxacin (HR: 2.6, 95% CI: 1.3-5.5), clarithromycin-quetiapine (HR: 1.7, 95% CI: 1.1-2.7) and piroxicam-warfarin (HR: 3.4, 95% CI: 1-11.4) were associated with elevated mortality. Confidence interval bounds of pairs associated with readmission were close to 1; length-of-stay results were inconclusive. CONCLUSIONS: Well-described potential drug-drug interactions are still missed and alerts at point of prescription may reduce the risk of harming patients; prescribing clinicians should be alert when using strong inhibitor/inducer drugs (i.e. clarithromycin, valproic acid, terbinafine) and prevalent anticoagulants (i.e. warfarin and non-steroidal anti-inflammatory drugs - NSAIDs) due to their great potential for dangerous interactions. The most prominent CYP isoenzyme involved in mortality and readmission rates was 3A4.

The Danish model for the quick and safe implementation of infliximab and etanercept biosimilars.

PURPOSE: A rapidly increasing use of biological drugs has led to substantial costs. Shift to biosimilars enables considerable reduction of these costs without jeopardizing the treatment of patients, but most countries have extensive possibilities of untapped cost-savings. The aim of this study was to describe the Danish quick and near-complete implementation of the two first TNF inhibitor biosimilars (infliximab and etanercept). METHODS: We shed light on the considerations and experiences made during the implementation, and present key figures from the implementation. RESULTS: The infliximab biosimilar constituted 90.6% of the total amount of infliximab four months following patent expiration of the biooriginator. Similar results were seen for etanercept biosimilar. Substantial cost reductions were experienced in the way that e.g. the infliximab-shift reduced cost by two thirds. CONCLUSION: We believe that a thorough preparation and an organizational setting supporting the implementation is crucial for the successful implementation. This same implementation model will be used for future biosimilars.

Hypoglycaemia when adding sulphonylurea to metformin: a systematic review and network meta-analysis.

AIMS: The risk of hypoglycaemia may differ among sulphonylureas (SUs), but evidence from head-to-head comparisons is sparse. Performing a network meta-analysis to use indirect evidence from randomized controlled trials (RCTs), we compared the relative risk of hypoglycaemia with newer generation SUs when added to metformin. METHODS: A systematic review identified RCTs lasting 12-52 weeks and evaluating SUs added to inadequate metformin monotherapy (≥1000 mg/day) in type 2 diabetes. Adding RCTs investigating the active comparators from the identified SU trials, we established a coherent network. Hypoglycaemia of any severity was the primary end point. RESULTS: Thirteen trials of SUs and 14 of oral non-SU antihyperglycaemic agents (16 260 patients) were included. All reported hypoglycaemia only as adverse events. Producing comparable reductions in HbA1C of -0.66 to -0.84% (-7 to -9 mmol/mol), the risk of hypoglycaemia was lowest with gliclazide compared to glipizide (OR 0.22, CrI: 0.05 to 0.96), glimepiride (OR 0.40, CrI: 0.13 to 1.27), and glibenclamide (OR 0.21, CrI: 0.03 to 1.48). A major limitation is varying definitions of hypoglycaemia across studies. CONCLUSIONS: When added to metformin, gliclazide was associated with the lowest risk of hypoglycaemia between the newer generation SUs. Clinicians should consider the risk of hypoglycaemia agent-specific when selecting an SU agent.

Danish physicians' preferences for prescribing escitalopram over citalopram and sertraline to treatment-naïve patients: a national, register-based study.

PURPOSE: To investigate whether general practitioners, hospital physicians and specialized practitioners in psychiatry have similar preferences for initiating treatment with expensive serotonin-specific reuptake inhibitors (SSRIs). METHODS: All first-time prescriptions for the SSRIs escitalopram, citalopram and sertraline reported to the Danish National Register of Medicinal Product Statistics from April 1, 2009 until March 31, 2010 were analysed with regard to treatment naivety and type of prescriber. A prescription was considered as first time if the patient had not received a prescription for the same drug within the last 2 years. Patients who had not received a prescription for an antidepressant within 6 months prior to the date of redemption were classified as treatment-naïve. RESULTS: We included 82,702 first-time prescriptions, 65,313 (79 %) of which were for treatment-naïve patients. Of the treatment-naïve patients, 19 % were initially prescribed escitalopram. Hospital physicians prescribed escitalopram to 34 % of their treatment-naïve patients, while practitioners specialized in psychiatry prescribed it to 25 %, and general practitioners prescribed it to 17 %. General practitioners, however, were responsible for initiating 87 % of all treatment-naïve patients. CONCLUSION: The most expensive SSRI, escitalopram, is prescribed as first choice to one in five patients receiving their first antidepressant of escitalopram, citalopram or sertraline. General practitioners made the bulk of all first-time SSRI prescriptions to treatment-naïve patients.

Exploratory pharmacovigilance with machine learning in big patient data: A focused scoping review.

BACKGROUND: Machine learning can operationalize the rich and complex data in electronic patient records for exploratory pharmacovigilance endeavours. OBJECTIVE: The objective of this review is to identify applications of machine learning and big patient data in exploratory pharmacovigilance. METHODS: We searched PubMed and Embase and included original articles with an exploratory pharmacovigilance purpose, focusing on medicinal interventions and reporting the use of machine learning in electronic patient records with ≥1000 patients collected after market entry. FINDINGS: Of 2557 studies screened, seven were included. Those covered six countries and were published between 2015 and 2021. The most prominent machine learning methods were random forests, logistic regressions, and support vector machines. Two studies used artificial neural networks or naive Bayes classifiers. One study used formal concept analysis for association mining, and another used temporal difference learning. Five studies compared several methods against each other. The numbers of patients in most data sets were in the order of thousands; two studies used what can more reasonably be considered big data with >1 000 000 patients records. CONCLUSION: Despite years of great aspirations for combining machine learning and clinical data for exploratory pharmacovigilance, only few studies still seem to deliver somewhat on these expectations.

Psychotropic drugs for patients with glaucoma.

This review offers a summary of the current knowledge of pshychotropic drugs and glaucoma. If exposed to psychotropic drugs, some patients may develop angle-closure glaucoma. Although rarely contraindicated, exposed predisposed and diagnosed patients should be followed-up by an ophthalmologist. It is still unclear if serotonin reuptake inhibitors increase the risk of angle-closure glaucoma. Tricyclic antidepressants and benzodiazepines should be used with caution in predisposed patients. The same applies to antipsychotic drugs, where first-generation antipsychotic drugs might have a smaller impact on the intraocular pressure than second-generation antipsychotic drugs.

Is the CYP2D6 Genotype Associated with Antipsychotic-Induced Weight Gain?

Antipsychotic-induced weight gain (AIWG) is a serious adverse effect. Studies have linked genetically-predicted CYP2D6 metabolic capacity to AIWG. The evidence, however, is ambiguous. We performed multiple regression analyses examining the association between genetic-predicted CYP2D6 metabolic capacity and AIWG. Analyses were based on previously unpublished data from an RCT investigating the clinical utility of routine genotyping of CYP2D6 and CYP2C19 in patients with schizophrenia. A total of 211 patients, corresponding to 71% of the original study population, were included. Our analyses indicated an effect of genetically predicted CYP2D6 metabolic capacity on AIWG with significant weight gain in both CYP2D6 poor metabolizers (PMs) (4.00 kg (95% CI: 0.80; 7.21)) and ultrarapid metabolizers (UMs) (6.50 kg (95% CI: 1.03; 12.0)). This finding remained stable after adjustment for covariates (PMs: 4.26 kg (0.88; 7.64), UMs: 7.26 kg (1.24; 13.3)). In addition to the CYP2D6 metabolic capacity, both baseline body mass index (-0.24 (95% CI: -0.44; -0.03)) and chlorpromazine equivalents per day (0.0041 (95% CI: 0.0005; 0.0077)) were statistically significantly associated with weight change in the adjusted analysis. Our results support that the genetically predicted CYP2D6 metabolic capacity matters for AIWG.

Using Machine Learning to Identify Patients at High Risk of Inappropriate Drug Dosing in Periods with Renal Dysfunction.

PURPOSE: Dosing of renally cleared drugs in patients with kidney failure often deviates from clinical guidelines, so we sought to elicit predictors of receiving inappropriate doses of renal risk drugs. PATIENTS AND METHODS: We combined data from the Danish National Patient Register and in-hospital data on drug administrations and estimated glomerular filtration rates for admissions between 1 October 2009 and 1 June 2016, from a pool of about 2.6 million persons. We trained artificial neural network and linear logistic ridge regression models to predict the risk of five outcomes (>0, ≥1, ≥2, ≥3 and ≥5 inappropriate doses daily) with index set 24 hours after admission. We used time-series validation for evaluating discrimination, calibration, clinical utility and explanations. RESULTS: Of 52,451 admissions included, 42,250 (81%) were used for model development. The median age was 77 years; 50% of admissions were of women. ≥5 drugs were used between admission start and index in 23,124 admissions (44%); the most common drug classes were analgesics, systemic antibacterials, diuretics, antithrombotics, and antacids. The neural network models had better discriminative power (all AUROCs between 0.77 and 0.81) and were better calibrated than their linear counterparts. The main prediction drivers were use of anti-inflammatory, antidiabetic and anti-Parkinson's drugs as well as having a diagnosis of chronic kidney failure. Sex and age affected predictions but slightly. CONCLUSION: Our models can flag patients at high risk of receiving at least one inappropriate dose daily in a controlled in-silico setting. A prospective clinical study may confirm that this holds in real-life settings and translates into benefits in hard endpoints.

Language-agnostic pharmacovigilant text mining to elicit side effects from clinical notes and hospital medication records.

We sought to craft a drug safety signalling pipeline associating latent information in clinical free text with exposures to single drugs and drug pairs. Data arose from 12 secondary and tertiary public hospitals in two Danish regions, comprising approximately half the Danish population. Notes were operationalised with a fastText embedding, based on which we trained 10 270 neural-network models (one for each distinct single-drug/drug-pair exposure) predicting the risk of exposure given an embedding vector. We included 2 905 251 admissions between May 2008 and June 2016, with 13 740 564 distinct drug prescriptions; the median number of prescriptions was 5 (IQR: 3-9) and in 1 184 340 (41%) admissions patients used ≥5 drugs concomitantly. A total of 10 788 259 clinical notes were included, with 179 441 739 tokens retained after pruning. Of 345 single-drug signals reviewed, 28 (8.1%) represented possibly undescribed relationships; 186 (54%) signals were clinically meaningful. Sixteen (14%) of the 115 drug-pair signals were possible interactions, and two (1.7%) were known. In conclusion, we built a language-agnostic pipeline for mining associations between free-text information and medication exposure without manual curation, predicting not the likely outcome of a range of exposures but also the likely exposures for outcomes of interest. Our approach may help overcome limitations of text mining methods relying on curated data in English and can help leverage non-English free text for pharmacovigilance.

DPYD genotyping and dihydropyrimidine dehydrogenase (DPD) phenotyping in clinical oncology. A clinically focused minireview.

BACKGROUND: In clinical oncology, systemic 5-fluorouracil (5-FU) and its oral pro-drugs are used to treat a broad group of solid tumours. Patients with dihydropyrimidine dehydrogenase (DPD) enzyme deficiency are at elevated risk of toxicity if treated with standard doses of 5-FU. DPYD genotyping and measurements of plasma uracil concentration (DPD phenotyping) can be applied as tests for DPD deficiency. In April 2020, the European Medicines Agency recommended pre-treatment DPD testing to reduce the risk of 5-FU-related toxicity. OBJECTIVES: The objective of this study is to present the current evidence for DPD testing in routine oncological practice. METHODS: Two systematic literature searches were performed following the PRISMA guidelines. We identified studies examining the possible benefit of DPYD genotyping or DPD phenotyping on the toxicity risk. FINDINGS: Nine and 12 studies met the criteria for using DPYD genotyping and DPD phenotyping, respectively. CONCLUSIONS: The evidence supporting either DPYD genotyping or DPD phenotyping as pre-treatment tests to reduce 5-FU toxicity is poor. Further evidence is still needed to fully understand and guide clinicians to dose by DPD activity.

Assessment of drug treatment quality in two Danish health-care centres.

INTRODUCTION: Bridging the primary and secondary sector, health-care centres aim to reduce morbidity and prevent further hospitalization in patients with chronic heart diseases. The aim of this study was to describe the quality of drug treatment in patients with chronic heart diseases in two Copenhagen health-care centres. MATERIAL AND METHODS: Over a period of three months, 28 patients with heart failure (HF) or ischaemic heart disease (IHD) were included. The participants were interviewed and clinically examined. RESULTS: The patients received an average of nine drugs, and only about one third were clinically well-treated. Among IHD patients, 74% received beta blockers and 64% angiotensin converting enzyme-inhibitors (ACE-I) as indicated. All received statins and 92% acetylsalicylic acid. Among HF patients, 67% received ACE-I, 87% beta blockers and 77% diuretics as indicated. Overall, 10%, 31% and 40% of the HF patients received smaller than recommended doses of ACE-I, beta blockers, and diuretics, respectively. In 68% of the patients, 35 potential drug interactions were identified, none of which were deemed potentially harmful. CONCLUSION: This small descriptive study indicates that patients in health-care centres might be undertreated and receive drug therapy only partly in accordance with the guidelines. However, since we had no access to medical charts, any reasons for not treating patients with a certain drug or selecting a lower than recommended dose could not be evaluated. Nevertheless, patients may benefit from closer involvement of clinicians or GPs in the multidisciplinary teams of the health-care centres.

[Biological disease-modifying anti-rheumatic drugs for pregnant and lactating women or male partners].

Effective medical treatment of rheumatic diseases during pregnancy and lactation is important, but the evidence for use of biological disease-modifying anti-rheumatic drugs (bDMARDs) is sparse and recommendations conflicting, which we discuss in this review. While some tumour necrosis factor (TNF)-α inhibitors appear safe during pregnancy and lactation, the evidence for use of non-TNF-α inhibitors is still too sparse to exclude adverse pregnancy outcomes and harm to the lactating child. The limited evidence on paternal exposure indicates, that TNF-α inhibitors do not affect male fertility or harm offspring. For non-TNF-α inhibitors, the evidence is still insufficient to draw any conclusion.

Chronic medicine users' self-managing medication with information - A typology of patients with self-determined, security-seeking and dependent behaviors.

BACKGROUND: Information on medicines is key for safety and quality of care in long-term treatment courses with medicines. Little is known on how patients self-manage medication with information, and how interactions with health professionals influence such self-managing. OBJECTIVE: The objective of this study was to investigate how patients manage long-term medication with information, and how interactions with health professionals influence this managing, with the aim of developing a typology of patients' practices for managing with information. A secondary objective was to generate theoretical reflections on patients' roles in establishing resilience in health care systems. METHODS: Qualitative interviews with 15 chronic medicine users. A Safety-II-approach was used to obtain knowledge of what worked for medicine users, at the same time as acknowledging hindrances. Data were analyzed using thematic analysis and Halkiers' method for ideal-typologizing. RESULTS: Four types of practices for managing medication with information were identified, distinguished by patients' ways of self-managing on their own and through relations with health professionals: Ideal-type I: Self-determined and highly self-managing; Ideal-type II: Security-seeking and self-managing; Ideal-type III: Dependent with limited self-managing; Ideal-type IV: Co-managing with close family. The findings suggest that patients with a high degree of self-managing medication with information have good chances for facilitating quality of medical treatment. For patients who are more dependent on oral information from health professionals, the character of dialogue facilitated or hindered their self-managing. All patients had the best options for managing medication when being recognized by health professionals through dialogues. CONCLUSION: A typology of 4 types of managing practices was developed, characterized by patients' different abilities to self-manage medication with information and their relations to health professionals. Recognizing patients' different behaviors for managing medication with information is important for maximizing treatment quality of long-term medical treatment in a modern and resilient healthcare system.

[Phenotype- or genotype test for dihydropyrimidin dehydrogenase deficiency before treatment with a fluoropyrimidine].

Some patients may have partial or complete deficiency of dihydropyrimidin dehydrogenase (DPD) and be more likely to experience severe toxicity with 5-fluorouracil. Since the spring of 2020, the Danish Medicines Agency has recommended genotype or phenotype testing before treatment with a fluoropyrimidine, but the most appropriate test strategy is debated. In this review, we present polymorphisms in the genes coding for DPD and summarise the evidence for DPD-enzyme deficiency testing and pharmacokinetic guided dosing.

CYP2D6 Genetic Variation and Antipsychotic-Induced Weight Gain: A Systematic Review and Meta-Analysis.

BACKGROUND: Antipsychotic-induced weight gain is a contributing factor in the reduced life expectancy reported amongst people with psychotic disorders. CYP2D6 is a liver enzyme involved in the metabolism of many commonly used antipsychotic medications. We investigated if CYP2D6 genetic variation influenced weight or BMI among people taking antipsychotic treatment. METHODS: We conducted a systematic review and a random effects meta-analysis of publications in Pubmed, Embase, PsychInfo, and CENTRAAL that had BMI and/or weight measurements of patients on long-term antipsychotics by their CYP2D6-defined metabolic groups (poor, intermediate, normal/extensive, and ultra-rapid metabolizers, UMs). RESULTS: Twelve studies were included in the systematic review. All cohort studies suggested that the presence of reduced-function or non-functional alleles for CYP2D6 was associated with greater antipsychotic-induced weight gain, whereas most cross-sectional studies did not find any significant associations. Seventeen studies were included in the meta-analysis with clinical data of 2,041 patients, including 93 poor metabolizers (PMs), 633 intermediate metabolizers (IMs), 1,272 normal metabolizers (NMs), and 30 UMs. Overall, we did not find associations in any of the comparisons made. The estimated pooled standardized differences for the following comparisons were (i) PM versus NM; weight = -0.07 (95%CI: -0.49 to 0.35, p = 0.74), BMI = 0.40 (95%CI: -0.19 to 0.99, p = 0.19). (ii) IM versus NM; weight = 0.09 (95% CI: -0.04 to 0.22, p = 0.16) and BMI = 0.09 (95% CI: -0.24 to 0.41, p = 0.60). (iii) UM versus EM; weight = 0.01 (95% CI: -0.37 to 0.40, p = 0.94) and BMI = -0.08 (95%CI: -0.57 to 0.42, p = 0.77). CONCLUSION: Our systematic review of cohort studies suggested that CYP2D6 poor metabolizers have higher BMI than normal metabolizers, but the data of cross-sectional studies and the meta-analysis did not show this association. Although our review and meta-analysis constitutes one of the largest studies with comprehensively genotyped samples, the literature is still limited by small numbers of participants with genetic variants resulting in poor or UMs status. We need further studies with larger numbers of extreme metabolizers to establish its clinical utility in antipsychotic treatment. CYP2D6 is a key gene for personalized prescribing in mental health.

A prospective study of patient adherence to topical treatments: 95% of patients underdose.

BACKGROUND: Adherence is essential to a positive treatment outcome. Whether adequate doses of topically applied drugs are used among patients with dermatologic conditions has not been investigated adequately. OBJECTIVES: The objective of this prospective study was to determine to what extent first-time outpatients with dermatologic conditions apply the appropriate dosage of initial treatment with topically administered medication. METHODS: Consultations with first-time patients in the dermatologic outpatient clinic were observed. Patients receiving a prescription for a previously untried topically administered drug were eligible. The expected quantity of topical treatment to be used by each patient was calculated from the affected skin area to be treated. The affected area was estimated in numbers of palms of the hand, and an amount of 0.25 g of ointment or cream was chosen as sufficient treatment to cover the area of one palm. Two weeks after the consultation, a questionnaire with items regarding the size of the affected area, intentions to follow the treatment, and the applied dose the previous day was mailed to each patient. The questionnaires were personally collected from the patients' homes and at the same visit the patients' topical drug containers were weighed on a balance. Both patients and staff were blinded to the particular study purpose concerning adherence and dosing. RESULTS: In all, 17 patients were eligible. The majority received a prescription for topical corticosteroids, and the median area to be treated was 3 palms of the hand (interquartile range: 1.5-8). Two patients did not redeem their prescriptions. Only one patient used the expected dosage; in general median 35% (interquartile range: 22%-50%) of the expected individual dosages were used. LIMITATIONS: Only first-time patients who received a new and previously untried topical treatment were included, resulting in a small study size. CONCLUSIONS: Most first-time patients with dermatologic conditions underdose new topical treatments. Consequently, clinicians should always consider nonadherence when topical therapies fail.

One in 3 prescriptions are never redeemed: primary nonadherence in an outpatient clinic.

BACKGROUND: Despite being essential to medication adherence, redemption of initial prescriptions (ie, primary adherence) has been investigated only sparsely. OBJECTIVES: The objectives were to determine the frequency and risk factors for primary nonadherence among outpatients with dermatologic conditions. METHODS: Every 15th day during 2006, all patients receiving a prescription for an initial treatment with a previously untried medication were studied. Redemptions were traced in an electronic register after 4 weeks. Exclusions were a result of identical treatments within the last 6 months or hospitalizations within 4 weeks. RESULTS: In all, 30.7% of the 322 eligible patients did not collect their medication. Patients with psoriasis were least adherent with nearly 50% of the prescriptions being unredeemed. LIMITATIONS: Only initial prescriptions for previously untried medications issued to hospital outpatients were studied. CONCLUSIONS: For the clinician, primary nonadherence is an essential differential diagnosis when a given therapy fails.

A Regional Drug and Therapeutics Committee-led Intervention to Reduce the Hospital Costs of Expensive HIV Drugs.

In 2009, the regional Drug and Therapeutics Committee (DTC) began a series of meetings with lead specialists in infectious diseases. The role of the DTC was to engage clinicians and ensure commitment to prescribing the least expensive drugs among the clinically equivalent HAARTs (highly active antiretroviral therapy). DTC also led implementation of a national guideline. This study analyses the impact of this process on HAART consumption and expenditure. The HAART consumption and expenditure (2009-2013) was compared to forecasts produced by exponential smoothing (2004-2009). Abrupt switches between drug regimens coincided with the DTC-led meetings. Overall, HAART consumption rose 16%, while price per defined daily dose (DDD) fell 11% and the 2013 expenditure decreased 23%. The consumption of drugs addressed by the guideline rose 48%. Still, the 2013 expenditure was 41.5 million DKK (5.5 million €) (27%) lower than expected, reflecting a fall in price per DDD that coincided with the intervention. The consumption of drugs not addressed by the guideline rose 8.3%, while price per DDD fell 8.5% and the 2013 expenditure was 26.8 million DKK (3.6 million €) (19%) lower than expected. Despite a steadily increasing consumption, significant cost savings followed this DTC-led intervention. This multifaceted approach might be applicable to changing the prescribing of other expensive drug classes.