Network analysis of drug prescriptions

Healthberry 865® and Its Related, Specific, Single Anthocyanins Exert a Direct Vascular Action, Modulating Both Endothelial Function and Oxidative Stress

In recent years, epidemiological studies have identified a relationship between diet and cerebro-cardiovascular disease (CVD). In this regard, there is a promising dietary group for cardiovascular protection are polyphenols, especially anthocyanins. Vascular reactivity studies were performed using Healthberry 865^® and constituent single anthocyanins to characterize vasomotor responses; immunofluorescence analysis with dichlorofluorescein diacetate and dihydroethidium were used to evaluate nitric oxide and oxidative stress; lucigenin assay was used to measure NADPH oxidase activity; and gel electrophoresis and immunoblotting were used to dissect the molecular mechanisms involved. We demonstrated that Healthberry 865^® exerts an important vasorelaxant effect of resistance artery functions in mice. Its action is mediated by nitric oxide release through the intracellular signaling PI3K/Akt. Moreover, behind its capability of modulating vascular tone, it also exerts an important antioxidant effect though the modulation of the NADPH oxidase enzyme. Interestingly, its cardiovascular properties are mediated by the selective action of different anthocyanins. Finally, the exposure of human dysfunctional vessels to Healthberry 865^® significantly reduces oxidative stress and improves NO bioavailability. Although further investigations are needed, our data demonstrate the direct role of Healthberry 865^® on the modulation of vasculature, both on the vasorelaxation and on oxidative stress; thus, supporting the concept that a pure mixture of anthocyanins could be helpful in preventing the onset of vascular dysfunction associated with the development of CVD.

An introduction to network analysis for studies of medication use

BACKGROUND

Network Analysis (NA) is a method that has been used in various disciplines such as Social sciences and Ecology for decades. So far, NA has not been used extensively in studies of medication use. Only a handful of papers have used NA in Drug Prescription Networks (DPN). We provide an introduction to NA terminology alongside a guide to creating and extracting results from the medication networks.

OBJECTIVE

To introduce the readers to NA as a tool to study medication use by demonstrating how to apply different NA measures on 3 generated medication networks.

METHODS

We used the Norwegian Prescription Database (NorPD) to create a network that describes the co-medication in elderly persons in Norway on January 1, 2013. We used the Norwegian Electronic Prescription Support System (FEST) to create another network of severe drug-drug interactions (DDIs). Lastly, we created a network combining the two networks to show the actual use of drugs with severe DDIs. We used these networks to elucidate how to apply and interpret different network measures in medication networks.

RESULTS

Interactive network graphs are made available online, Stata and R syntaxes are provided. Various useful network measures for medication networks were applied such as network topological features, modularity analysis and centrality measures. Edge lists data used to generate the networks are openly available for readers in an open data repository to explore and use.

CONCLUSION

We believe that NA can be a useful tool in medication use studies. We have provided information and hopefully inspiration for other researchers to use NA in their own projects. While network analyses are useful for exploring and discovering structures in medication use studies, it also has limitations. It can be challenging to interpret and it is not suitable for hypothesis testing.

Identifying frequent drug combinations associated with delirium in older adults: Application of association rules method to a case-time-control design

BACKGROUND

Older adults are at an increased risk of delirium because of age, polypharmacy, multiple comorbidities, frailty, and acute illness. Although medication-induced delirium in older adults is well understood, limited population-level evidence is available, particularly on combinations of medications associated with delirium in older adults.

OBJECTIVES

We aimed to apply association rule analysis to identify drug combinations contributing to delirium risk in adults aged 65 and older using a case-time-control design.

METHOD

We sourced a nationwide representative sample of New Zealander's aged ≥65 years from the pharmaceutical collections and hospital discharge information. Prescription records (2005-2015) were obtained from New Zealand pharmaceutical collections (Pharms). Medication exposures were coded as binary variables (exposed vs. not exposed) at the individual drug level. All medications, including antimicrobials, antihistamines, diuretics, opioids, and nonsteroidal anti-inflammatory medications, were considered drugs of interest. The first-time coded diagnosis of delirium was extracted from the National Minimal Dataset (NMDS). A unique patient identifier linked the prescription dataset to the event dataset to set up a case-time-control cohort, indexed at the first delirium event. Association rules were then applied to identify frequent drug combinations in the case and the control periods (l-day with a 35-day washout period) that are statistically associated with delirium, and the association was tested by computing a time-trend adjusted matched odds-ratio (MOR) and its 95% confidence interval (CI).

RESULTS

We identified 28 503 individuals (mean age 84.1 years) from 2005 to 2015 with delirium. Our combined association rule and case-time-control analysis identified several drug classes, including antipsychotics, benzodiazepines, opioids, and diuretics associated with delirium. Our analysis also identified frequently used drug combinations that are associated with delirium. Examples include combined exposures to quetiapine and furosemide (MOR = 6.17; 95%CI = [2.05-18.54]), haloperidol (MOR = 4.81; 95%CI = [3.16-6.69]), combined exposures to furosemide, omeprazole, and lorazepam (MOR = 3.94; 95%CI = [3.03-5.10]), and fentanyl exposure (MOR = 3.46; 95%CI [2.05-9.21]).

CONCLUSION

The association rule method applied to a case-time-control design is a novel approach to identifying drug combinations contributing to delirium with adjustment for any temporal trends in exposures. The study provides new insight into the combination of medicines linked to delirium.

A Network Approach for the Study of Drug Prescriptions: Analysis of Administrative Records from a Local Health Unit (ASL TO4, Regione Piemonte, Italy)

In a Drug Prescription Network (DPN), each drug is represented as a node and two drugs co-prescribed to the same patient are represented as an edge linking the nodes. The use of DPNs is a novel approach that has been proposed as a means to study the complexity of drug prescription. The aim of this study is to demonstrate the analytical power of the DPN-based approach when it is applied to the analysis of administrative data. Drug prescription data that were collected at a local health unit (ASL TO4, Regione Piemonte, Italy), over a 12-month period (July 2018–June 2019), were used to create several DPNs that correspond to the five levels of the Anatomical Therapeutic Chemical classification system. A total of 5,431,335 drugs prescribed to 361,574 patients (age 0–100 years; 54.7% females) were analysed. As indicated by our results, the DPNs were dense networks, with giant components that contain all nodes. The disassortative mixing of node degrees was observed, which implies that non-random connectivity exists in the networks. Network-based methods have proven to be a flexible and efficient approach to the analysis of administrative data on drug prescription.

Prescribing Behavior of General Practitioners for Generic Drugs

The factors influencing General Practitioners’ (GPs) prescribing behavior are diverse in terms of health care policies and regulations, GPs’ education and experience, demographic trends and disease profiles. Thus, it can be useful to analyze the specific local patterns, as they affect the quality of healthcare and the stability of the healthcare market. The aim of the present longitudinal retrospective study is to investigate the prescription of generic drugs in a database of about 4.6 million prescriptions from a sample of 38 GPs practicing in Salerno, Italy, within a timeframe of 15 years, from 2001 to 2015. The GPs in our study show a general tendency to increase prescriptions of generic drugs during the studied time span, to fulfill regulatory obligations and with some differences in prescription behavior according to age, gender and experience. The generics prescription depends also on the different diagnoses, with some diagnostic areas showing a greater generic drug prescription rate. Expanding this research to larger datasets would allow deepening the knowledge of the patterns of GPs’ prescribing decisions, to provide evidence to be used in comparison between different national settings.

Social success of perfumes

We study data on perfumes and their odour descriptors—notes—to understand how note compositions, called accords, influence successful fragrance formulas. We obtain accords which tend to be present in perfumes that receive significantly more customer ratings. Our findings show that the most popular notes and the most over-represented accords are different to those that have the strongest effect to the perfume ratings. We also used network centrality to understand which notes have the highest potential to enhance note compositions. We find that large degree notes, such as musk and vanilla as well as generically-named notes, e.g. floral notes, are amongst the notes that enhance accords the most. This work presents a framework which would be a timely tool for perfumers to explore a multidimensional space of scent compositions.

Prevalence and correlates of Benign Pancreatic Hyperenzymemia in a large general population sample: The Damocles sword perception

BACKGROUND

Benign Pancreatic Hyperenzymemia (BPH) is characterized by a long-term increase of serum pancreatic enzymes (PE) in otherwise healthy subjects. The study investigates the prevalence and correlates of the condition using data from Electronic Health Records (EHR) in a large sample of general population, to identify subjects potentially affected by BPH.

METHODS

Cross-sectional retrospective observational study integrated by a follow-up visit.

RESULTS

The database of a reference laboratory identified, out of 577.251 admittances from 2011 to 2015, 4964 patients tested at least for one PE assay and 1688 subjects who had at least 3 PE tests (normal or increased) over two years. Forty-two individuals showed an increase of PE at least three times throughout 2 years without any evidence of pancreatic disease, even after matching with the ICD 9-CM code in the GPs database. Data retrieved at follow-up visit showed that for 34 the diagnosis of BPH could be made.

CONCLUSIONS

Our data indicate that BPH prevalence among subjects underwent blood testing for multiple PE testing is 2%. This condition, even if not a disease, is perceived by nearly all the BPH patients as a serious threat to their life. Further studies are needed to manage its heavy psychological impact.

Pharmacoepidemiology in older people: Purposes and future directions

Knowledge of the benefit/risk ratio of drugs in older adults is essential to optimise medication use. While randomised controlled trials are fundamental to the process of drug development and bringing new drugs to the market, they often exclude older adults, especially those suffering from frailty, multimorbidity and/or receiving polypharmacy. Therefore, it is generally unknown whether the benefits and harms of drugs established through pre-marketing clinical trials are translatable to the real-word population of older adults. Pharmacoepidemiology can provide real-world data on drug utilisation and drug effects in older people with multiple comorbidities and polypharmacy and can greatly contribute towards the goal of high quality use of drugs and well-being in older adults. A wide variety of pharmacoepidemiology studies can be used and exciting progress is being made with the use of novel and advanced statistical methods to improve the robustness of data. Coordinated and strategic initiatives are required internationally in order for this field to reach its full potential of optimising drug use in older adults so as to improve health care outcomes.

New approaches to pharmacosurveillance for monitoring prescription frequency, diversity, and co-prescription in a large sentinel network of companion animal veterinary practices in the United Kingdom, 2014-2016

Pharmaceutical agents (PAs) are commonly prescribed in companion animal practice in the United Kingdom. However, little is known about PA prescription on a population-level, particularly with respect to PAs authorised for human use alone prescribed via the veterinary cascade; this raises important questions regarding the efficacy and safety of PAs prescribed to companion animals. This study explored new approaches for describing PA prescription, diversity and co-prescription in dogs, cats and rabbits utilising electronic health records (EHRs) from a sentinel network of 457 companion animal-treating veterinary sites throughout the UK over a 2-year period (2014-2016). A novel text mining-based identification and classification methodology was utilised to semi-automatically map practitioner-defined product descriptions recorded in 918,333 EHRs from 413,870 dogs encompassing 1,242,270 prescriptions; 352,730 EHRs from 200,541 cats encompassing 491,554 prescriptions, and 22,526 EHRS from 13,398 rabbits encompassing 18,490 prescriptions respectively. PA prescription as a percentage of booked consultations was 65.4% (95% confidence interval, CI, 64.6-66.3) in dogs; in cats it was 69.1% (95% CI, 67.9-70.2) and in rabbits, 56.3% (95% CI, 54.7-57.8). Vaccines were the most commonly prescribed PAs in all three species, with antibiotics, antimycotics, and parasiticides also commonly prescribed. PA prescription utilising products authorised for human use only (hence, 'human-authorised') comprised 5.1% (95% CI, 4.7-5.5) of total canine prescription events; in cats it was 2.8% (95% CI, 2.6-3.0), and in rabbits, 7.8% (95% CI, 6.5-9.0). The most commonly prescribed human-authorised PA in dogs was metronidazole (antibiotic); in cats and rabbits it was ranitidine (H2 histamine receptor antagonist). Using a new approach utilising the Simpson's Diversity Index (an ecological measure of relative animal, plant etc. species abundance), we identified differences in prescription based on presenting complaint and species, with rabbits generally exposed to a less diverse range of PAs than dogs or cats, potentially reflecting the paucity of authorised PAs for use in rabbits. Finally, through a novel application of network analysis, we demonstrated the existence of three major co-prescription groups (preventive health; treatment of disease, and euthanasia); a trend commonly observed in practice. This study represents the first time PA prescription has been described across all pharmaceutical families in a large population of companion animals, encompassing PAs authorised for both veterinary and human-only use. These data form a baseline against which future studies could be compared, and provides some useful tools for understanding PA comparative efficacy and risks when prescribed in the varied setting of clinical practice.

General Practitioners Records Are Epidemiological Predictors of Comorbidities: An Analytical Cross-Sectional 10-Year Retrospective Study

Background. Comorbidity represents the co-occurrence of pathological conditions in the same individual, and presents with very complex patterns. In most cases, reference data for the study of various types of comorbidities linked to complex diseases are those of hospitalized patients. Such patients may likely require cure due to acute conditions. We consider the emerging role of EHR (Electronic Healthcare Records), and study comorbidity patterns in a general population, focusing on diabetic and non-diabetic patients. Methods. We propose a cross-sectional 10-year retrospective study of 14,958 patients and 1,728,736 prescriptions obtained from family doctors, and thus refer to these data as General Practitioner Records (GPR). We then choose networks as the tools to analyze the diabetes comorbidity patterns, distinguished by both prescription type and main patient characteristics (age, gender). Results. As expected, comorbidity increases with patients’ age, and the network representations allow the assessment of associations between morbidity groups. The specific morbidities present in the diabetic population justify the higher comorbidity patterns observed in the target group compared to the non-diabetic population. Conclusions. GPR are usually combined with other data types in EHR studies, but we have shown that prescription data have value as standalone predictive tools, useful to anticipate trends observed at epidemiological level on large populations. This study is thus relevant to policy makers seeking inference tools for an efficient use of massive administrative database resources, and suggests a strategy for detecting comorbidities and investigating their evolution.

Polypharmacy in older adults: Association Rule and Frequent-Set Analysis to evaluate concomitant medication use

The aim of this study was to apply Association Rule and Frequent-Set analysis, and novel means of data visualisation to ascertain patterns of medication use and medication combinations contributing to medication group clusters according to geriatric syndrome status in older adults. Participants were community-dwelling men (aged ≥70 years, n=1686), Sydney, Australia. Medication exposure was categorised at medication class level and data were analysed according to geriatric syndrome status (presence of at least one syndrome including frailty, falls, cognitive impairment and urinary incontinence). Association Rule and Frequent-Set analysis were performed to identify "interesting" patterns of medication combinations that occur together. This analysis involves advanced computer algorithms that investigated all possible combinations of medications in the dataset in order to identify those which are observed more or much less frequently than expected. Frequent-Set Analysis demonstrated one unexpected medication combination, antiulcer and antidiabetic medications (3.5% of participants) in the overall population (n=1687). Frequency of medication combinations was similar in participants with (n=666) and without (n=1020) geriatric syndromes. Among participants with geriatric syndromes, the most frequent combinations included antigout with lipid-lowering agents (5.7%) followed by angiotensin II and diuretics combination (22%). This novel methodology can be used to detect common medication combinations overall by data visualisation, and against specific adverse drug reactions such as geriatric syndromes. This methodology may be a valuable pharmacovigilance approach to monitor large databases for the safety of medications.

High-throughput thermal stability analysis of a monoclonal antibody by attenuated total reflection FT-IR spectroscopic imaging

The use of biotherapeutics, such as monoclonal antibodies, has markedly increased in recent years. It is thus essential that biotherapeutic production pipelines are as efficient as possible. For the production process, one of the major concerns is the propensity of a biotherapeutic antibody to aggregate. In addition to reducing bioactive material recovery, protein aggregation can have major effects on drug potency and cause highly undesirable immunological effects. It is thus essential to identify processing conditions which maximize recovery while avoiding aggregation. Heat resistance is a proxy for long-term aggregation propensity. Thermal stability assays are routinely performed using various spectroscopic and scattering detection methods. Here, we evaluated the potential of macro attenuated total reflection Fourier transform infrared (ATR-FT-IR) spectroscopic imaging as a novel method for the high-throughput thermal stability assay of a monoclonal antibody. This chemically specific visualization method has the distinct advantage of being able to discriminate between monomeric and aggregated protein. Attenuated total reflection is particularly suitable for selectively probing the bottom of vessels, where precipitated aggregates accumulate. With focal plane array detection, we tested 12 different buffer conditions simultaneously to assess the effect of pH and ionic strength on protein thermal stability. Applying the Finke model to our imaging kinetics allowed us to determine the rate constants of nucleation and autocatalytic growth. This analysis demonstrated the greater stability of our immunoglobulin at higher pH and moderate ionic strength, revealing the key role of electrostatic interactions. The high-throughput approach presented here has significant potential for analyzing the stability of biotherapeutics as well as any other biological molecules prone to aggregation.