Data management and data analysis techniques in pharmacoepidemiological studies using a pre-planned multi-database approach : a systematic literature review

PurposeTo identify pharmacoepidemiological multi-database studies and to describe data management and data analysis techniques used for combining data. MethodsSystematic literature searches were conducted in PubMed and Embase complemented by a manual literature search. We included pharmacoepidemiological multi-database studies published from 2007 onwards that combined data for a pre-planned common analysis or quantitative synthesis. Information was retrieved about study characteristics, methods used for individual-level analyses and meta-analyses, data management and motivations for performing the study. ResultsWe found 3083 articles by the systematic searches and an additional 176 by the manual search. After full-text screening of 75 articles, 22 were selected for final inclusion. The number of databases used per study ranged from 2 to 17 (median=4.0). Most studies used a cohort design (82%) instead of a case-control design (18%). Logistic regression was most often used for individual-level analyses (41%), followed by Cox regression (23%) and Poisson regression (14%). As meta-analysis method, a majority of the studies combined individual patient data (73%). Six studies performed an aggregate meta-analysis (27%), while a semi-aggregate approach was applied in three studies (14%). Information on central programming or heterogeneity assessment was missing in approximately half of the publications. Most studies were motivated by improving power (86%). ConclusionsPharmacoepidemiological multi-database studies are a well-powered strategy to address safety issues and have increased in popularity. To be able to correctly interpret the results of these studies, it is important to systematically report on database management and analysis techniques, including central programming and heterogeneity testing. (c) 2015 The Authors. Pharmacoepidemiology and Drug Safety published by John Wiley & Sons, Ltd.Peer reviewe

Principal component analysis for studying the world security problem

This research is a continuation of the work [1], in which the list of ten most essential global threats to the future of mankind have been presented. The initial data on each threat are taken from the respectable international organizations data bases. Then, we defined the summarized impact of the examined ten global threats totality on different countries based on cluster analysis method with the purpose of selecting groups of the countries with “close” performances of summarized threats. By using the Minkovsky type metric the foresight of the future global conflicting has been executed. To facilitate the analysis and make it easier we use the method of Principal Component Analysis (PCA) which allows reduce variables with many properties to several hidden factors. The analysis shows that currently the most considerable threats for most countries are the reduction of energy security, worsening of balance between bio capacity and human demands and the incomes inequality between people and countries.Проведено дослідження національної безпеки різних країн світу з використанням метода головних компонент (Principal Component Analysis) у просторі десяти глобальних загроз. За допомогою обчислення коефіцієнтів кореляції визначено характер залежності між головними чинниками і вихідними загрозами. Визначено три найбільш істотні загрози, які впливають на національну безпеку більшості країн світу: державна нестабільність, дефіцит енергетичних ресурсів і нерівність доходів (Gini Index). Виконано графічну інтерпретацію глобальних загроз і визначено міри залежності між їх основними групами.Проведено исследование национальной безопасности различных стран мира с использованием метода главных компонент (Principal Component Analysis) в пространстве десяти глобальных угроз. С помощью вычисления коэффициентов корреляции определен характер зависимости между главными факторами и исходными угрозами. Проведена кластеризация стран по уровню глобальных угроз. Определены три наиболее существенные угрозы, влияющие на национальную безопасность большинства стран мира: государственная нестабильность, дефицит энергетических ресурсов и неравенство доходов (Gini Index). Выполнена графическая интерпретация глобальных угроз в пространстве трех главных компонент. Проведено исследование факторной структуры угроз и определены степени зависимости между их основными группами

The association of diabetes mellitus and insulin treatment with expression of insulin-related proteins in breast tumors

BACKGROUND: The insulin receptor (INSR) and the insulin growth factor 1 receptor (IGF1R) play important roles in the etiology of both diabetes mellitus and breast cancer. We aimed to evaluate the expression of hormone and insulin-related proteins within or related to the PI3K and MAPK pathway in breast tumors of women with or without diabetes mellitus, treated with or without insulin (analogues). METHODS: Immunohistochemistry was performed on tumor tissue of 312 women with invasive breast cancer, with or without pre-existing diabetes mellitus, diagnosed in 2000-2010, who were randomly selected from a Danish breast cancer cohort. Women with diabetes were 2:1 frequency matched by year of birth and age at breast cancer diagnosis to those without diabetes. Tumor Microarrays were successfully stained for p-ER, EGFR, p-ERK1/2, p-mTOR, and IGF1R, and scored by a breast pathologist. Associations of expression of these proteins with diabetes, insulin treatment (human insulin and insulin analogues) and other diabetes medication were evaluated by multivariable logistic regression adjusting for menopause and BMI; effect modification by menopausal status, BMI, and ER status was assessed using interactions terms. RESULTS: We found no significant differences in expression of any of the proteins in breast tumors of women with (n = 211) and without diabetes (n = 101). Among women with diabetes, insulin use (n = 53) was significantly associated with higher tumor protein expression of IGF1R (OR = 2.36; 95%CI:1.02-5.52; p = 0.04) and p-mTOR (OR = 2.35; 95%CI:1.13-4.88; p = 0.02), especially among women treated with insulin analogues. Menopause seemed to modified the association between insulin and IGF1R expression (p = 0.07); the difference in IGF1R expression was only observed in tumors of premenopausal women (OR = 5.10; 95%CI:1.36-19.14; p = 0.02). We found no associations between other types of diabetes medication, such as metformin, and protein expression of the five proteins evaluated. CONCLUSIONS: In our study, breast tumors of women with pre-existing diabetes did not show an altered expression of selected PI3K/MAPK pathway-related proteins. We observed an association between insulin treatment and increased p-mTOR and IGF1R expression of breast tumors, especially in premenopausal women. This observation, if confirmed, might be clinically relevant since the use of IGF1R and mTOR inhibitors are currently investigated in clinical trials

Prescribing of low-dose rivaroxaban in patients with atherosclerotic cardiovascular disease in the United Kingdom and the Netherlands

Aims: Low-dose rivaroxaban has been indicated for the management of atherosclerotic cardiovascular disease (ASCVD) after recent (2019-2020) updates to European guidelines. We aimed to describe prescription trends of low-dose rivaroxaban in ASCVD patients over the period 2015-2022 in two European countries, to compare the trends before and after guideline changes, and to determine the characteristics of users. Methods: In a cross-sectional interrupted time series analysis, utilization of low-dose rivaroxaban (2.5 mg, twice daily) was measured in Clinical Practice Research Datalink Aurum (United Kingdom [UK]) and the PHARMO Database Network (the Netherlands) from 1 January 2015 to 28 February 2022 in patients with an ASCVD diagnosis. Incidence rates (IRs) and incidence rate ratios (IRRs) of new use (within 182 days) compared to the reference period, 2015-2018, were calculated. Age, sex and comorbidities of users were compared to those of nonusers. Results: In the UK, from 721 271 eligible subjects the IR of new use of low-dose rivaroxaban in the period 2015-2018, before guideline changes, was 12.4 per 100 000 person-years and after guideline changes in 2020-2022 was 124.0 (IRR 10.0, 95% confidence interval [CI] 8.5, 11.8). In the Netherlands from 394 851 subjects, the IR in 2015-2018 was 2.4 per 100 000 person-years and in 2020 was 16.3 (IRR 6.7, 95% CI 4.0, 11.4). Users were younger (UK mean difference [MD] −6.1 years, Netherlands −2.4 years; P <.05) and more likely to be male (UK difference 11.5%, Netherlands 13.4%; P <.001) than nonusers. Conclusions: There was a statistically significant increase in the use of low-dose rivaroxaban for the management of ASCVD after guideline changes in the UK and the Netherlands. There were international differences, but low-dose rivaroxaban has not been put into widespread practice

Cancer risk among insulin users : comparing analogues with human insulin in the CARING five-country cohort study

Aims/hypothesis The aim of this work was to investigate the relationship between use of certain insulins and risk for cancer, when addressing the limitations and biases involved in previous studies. Methods National Health Registries from Denmark (1996-2010), Finland (1996-2011), Norway (2005-2010) and Sweden (2007-2012) and the UK Clinical Practice Research Datalink database (1987-2013) were used to conduct a cohort study on new insulin users (N = 327,112). By using a common data model and semi-aggregate approach, we pooled individual-level records from five cohorts and applied Poisson regression models. For each of ten cancer sites studied, we estimated the rate ratios (RRs) by duration (6 years) of cumulative exposure to insulin glargine or insulin detemir relative to that of human insulin. Results A total of 21,390 cancer cases occurred during a mean follow-up of 4.6 years. No trend with cumulative treatment time for insulin glargine relative to human insulin was observed in risk for any of the ten studied cancer types. Of the 136 associations tested in the main analysis, only a few increased and decreased risks were found: among women, a higher risk was observed for colorectal (RR 1.54, 95% CI 1.06, 2.25) and endometrial cancer (RR 1.78, 95% CI 1.07, 2.94) for 6 years (RR 0.22, 95% CI 0.05, 0.92). Comparisons of insulin detemir with human insulin also showed no consistent differences. Conclusions/interpretation The present multi-country study found no evidence of consistent differences in risk for ten cancers for insulin glargine or insulin detemir use compared with human insulin, at follow-up exceeding 5 years.Peer reviewe

Mapping the risk of infections in patients with multiple sclerosis: A multi-database study in the United Kingdom Clinical Practice Research Datalink GOLD and Aurum

BACKGROUND: People with multiple sclerosis (pwMS) have an increased risk of infections; risk factors include underlying disease, physical impairment and use of some disease-modifying treatments. OBJECTIVE: To quantify changes in population-level infection rates among pwMS and compare these to the general population and people with rheumatoid arthritis (pwRA), and identify patient characteristics predictive of infections after MS diagnosis. METHODS: We conducted a multi-database study using data on 23,226 people with MS diagnosis from the UK Clinical Practice Research Datalink Aurum and GOLD (January 2000-December 2020). PwMS were matched to MS-free controls and pwRA. We calculated infection rates, and estimated incidence rate ratios (IRR) and 95% confidence intervals (CI) of predictors for infections ⩽ 5 years after MS diagnosis using Poisson regression. RESULTS: Among pwMS, overall infection rates remained stable - 1.51-fold (1.49-1.52) that in MS-free controls and 0.87-fold (0.86-0.88) that in pwRA - although urinary tract infection rate per 1000 person-years increased from 98.7 (96.1-101) (2000-2010) to 136 (134-138) (2011-2020). Recent infection before MS diagnosis was most predictive of infections (1 infection: IRR 1.92 (1.86-1.97); ⩾2 infections: IRR 3.00 (2.89-3.10)). CONCLUSION: The population-level elevated risk of infection among pwMS has remained stable despite the introduction of disease-modifying treatments

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p

Cross-Regional Data Initiative for the Assessment and Development of Treatment for Neurological and Mental Disorders

Purpose: To describe and categorize detailed components of databases in the Neurological and Mental Health Global Epidemiology Network (NeuroGEN). Methods: An online 132-item questionnaire was sent to key researchers and data custodians of NeuroGEN in North America, Europe, Asia and Oceania. From the responses, we assessed data characteristics including population coverage, data follow-up, clinical information, validity of diagnoses, medication use and data latency. We also evaluated the possibility of conversion into a common data model (CDM) to implement a federated network approach. Moreover, we used radar charts to visualize the data capacity assessments, based on different perspectives. Results: The results indicated that the 15 databases covered approximately 320 million individuals, included in 7 nationwide claims databases from Australia, Finland, South Korea, Taiwan and the US, 6 population-based electronic health record databases from Hong Kong, Scotland, Taiwan, the Netherlands and the UK, and 2 biomedical databases from Taiwan and the UK. Conclusion: The 15 databases showed good potential for a federated network approach using a common data model. Our study provided publicly accessible information on these databases for those seeking to employ real-world data to facilitate current assessment and future development of treatments for neurological and mental disorders.</p