Evaluating a novel approach to stimulate open science collaborations: a case series of "study-a-thon" events within the OHDSI and European IMI communities.

Objective: We introduce and review the concept of a study-a-thon as a catalyst for open science in medicine, utilizing harmonized real world, observation health data, tools, skills, and methods to conduct network studies, generating insights for those wishing to use study-a-thons for future research. Materials and Methods: A series of historical study-a-thons since 2017 to present were reviewed for thematic insights as to the opportunity to accelerate the research method to conduct studies across therapeutic areas. Review of publications and experience of the authors generated insights to illustrate the conduct of study-a-thons, key learning, and direction for those wishing to conduct future such study-a-thons. Results: A review of six study-a-thons have provided insights into their scientific impact, and 13 areas of insights for those wishing to conduct future study-a-thons. Defining aspects of the study-a-thon method for rapid, collaborative research through network studies reinforce the need to clear scientific rationale, tools, skills, and methods being collaboratively to conduct a focused study. Well-characterized preparatory, execution and postevent phases, coalescing skills, experience, data, clinical input (ensuring representative clinical context to the research query), and well-defined, logical steps in conducting research via the study-a-thon method are critical. Conclusions: A study-a-thon is a focused multiday research event generating reliable evidence on a specific medical topic across different countries and health systems. In a study-a-thon, a multidisciplinary team collaborate to create an accelerated contribution to scientific evidence and clinical practice. It critically accelerates the research process, without inhibiting the quality of the research output and evidence generation, through a reproducible process.

Training prediction models for individual risk assessment of postoperative complications after surgery for colorectal cancer.

BACKGROUND: The occurrence of postoperative complications and anastomotic leakage are major drivers of mortality in the immediate phase after colorectal cancer surgery. We trained prediction models for calculating patients' individual risk of complications based only on preoperatively available data in a multidisciplinary team setting. Knowing prior to surgery the probability of developing a complication could aid in improving informed decision-making by surgeon and patient and individualize surgical treatment trajectories. METHODS: All patients over 18 years of age undergoing any resection for colorectal cancer between January 1, 2014 and December 31, 2019 from the nationwide Danish Colorectal Cancer Group database were included. Data from the database were converted into Observational Medical Outcomes Partnership Common Data Model maintained by the Observation Health Data Science and Informatics initiative. Multiple machine learning models were trained to predict postoperative complications of Clavien-Dindo grade ≥ 3B and anastomotic leakage within 30 days after surgery. RESULTS: Between 2014 and 2019, 23,907 patients underwent resection for colorectal cancer in Denmark. A Clavien-Dindo complication grade ≥ 3B occurred in 2,958 patients (12.4%). Of 17,190 patients that received an anastomosis, 929 experienced anastomotic leakage (5.4%). Among the compared machine learning models, Lasso Logistic Regression performed best. The predictive model for complications had an area under the receiver operating characteristic curve (AUROC) of 0.704 (95%CI 0.683-0.724) and an AUROC of 0.690 (95%CI 0.655-0.724) for anastomotic leakage. CONCLUSIONS: The prediction of postoperative complications based only on preoperative variables using a national quality assurance colorectal cancer database shows promise for calculating patient's individual risk. Future work will focus on assessing the value of adding laboratory parameters and drug exposure as candidate predictors. Furthermore, we plan to assess the external validity of our proposed model.

Investigating the impact of development and internal validation design when training prognostic models using a retrospective cohort in big US observational healthcare data.

OBJECTIVE: The internal validation of prediction models aims to quantify the generalisability of a model. We aim to determine the impact, if any, that the choice of development and internal validation design has on the internal performance bias and model generalisability in big data (n~500 000). DESIGN: Retrospective cohort. SETTING: Primary and secondary care; three US claims databases. PARTICIPANTS: 1 200 769 patients pharmaceutically treated for their first occurrence of depression. METHODS: We investigated the impact of the development/validation design across 21 real-world prediction questions. Model discrimination and calibration were assessed. We trained LASSO logistic regression models using US claims data and internally validated the models using eight different designs: 'no test/validation set', 'test/validation set' and cross validation with 3-fold, 5-fold or 10-fold with and without a test set. We then externally validated each model in two new US claims databases. We estimated the internal validation bias per design by empirically comparing the differences between the estimated internal performance and external performance. RESULTS: The differences between the models' internal estimated performances and external performances were largest for the 'no test/validation set' design. This indicates even with large data the 'no test/validation set' design causes models to overfit. The seven alternative designs included some validation process to select the hyperparameters and a fair testing process to estimate internal performance. These designs had similar internal performance estimates and performed similarly when externally validated in the two external databases. CONCLUSIONS: Even with big data, it is important to use some validation process to select the optimal hyperparameters and fairly assess internal validation using a test set or cross-validation.

Prediction of 90-day mortality after surgery for colorectal cancer using standardized nationwide quality-assurance data.

BACKGROUND: Personalized risk assessment provides opportunities for tailoring treatment, optimizing healthcare resources and improving outcome. The aim of this study was to develop a 90-day mortality-risk prediction model for identification of high- and low-risk patients undergoing surgery for colorectal cancer. METHODS: This was a nationwide cohort study using records from the Danish Colorectal Cancer Group database that included all patients undergoing surgery for colorectal cancer between 1 January 2004 and 31 December 2015. A least absolute shrinkage and selection operator logistic regression prediction model was developed using 121 pre- and intraoperative variables and internally validated in a hold-out test data set. The accuracy of the model was assessed in terms of discrimination and calibration. RESULTS: In total, 49 607 patients were registered in the database. After exclusion of 16 680 individuals, 32 927 patients were included in the analysis. Overall, 1754 (5.3 per cent) deaths were recorded. Targeting high-risk individuals, the model identified 5.5 per cent of all patients facing a risk of 90-day mortality exceeding 35 per cent, corresponding to a 6.7 times greater risk than the average population. Targeting low-risk individuals, the model identified 20.9 per cent of patients facing a risk less than 0.3 per cent, corresponding to a 17.7 times lower risk compared with the average population. The model exhibited discriminatory power with an area under the receiver operating characteristics curve of 85.3 per cent (95 per cent c.i. 83.6 to 87.0) and excellent calibration with a Brier score of 0.04 and 32 per cent average precision. CONCLUSION: Pre- and intraoperative data, as captured in national health registries, can be used to predict 90-day mortality accurately after colorectal cancer surgery.

Vascular and metabolic risk factor differences prior to dementia diagnosis: a multidatabase case-control study using European electronic health records.

OBJECTIVE: The objective of the study is to compare body mass index (BMI), systolic/diastolic blood pressure (SBP/DBP) and serum total cholesterol levels between dementia cases and controls at multiple time intervals prior to dementia onset, and to test time interval as a modifying factor for these associations. DESIGN: Case-control study. SETTING: Six European electronic health records databases. PARTICIPANTS: 291 780 cases at the date of first-recorded dementia diagnosis, compared with 29 170 549 controls randomly selected from the same databases, age matched and sex matched at this index date. EXPOSURE: The following measures were extracted whenever recorded within each dataset: BMI (kg/m2), SBP and DBP (mm Hg) and serum total cholesterol (mmol/L). Levels for each of these variables were defined within six 2-year time intervals over the 12 years prior to the index date. MAIN OUTCOMES: Case-control differences in exposures of interest were modelled for each time period and adjusted for demographic and clinical factors (ischaemic/unspecified stroke, type 2 diabetes mellitus, acute myocardial infarction, hypertension diagnosis, antihypertensive medication, cholesterol-lowering medication). Coefficients and interactions with time period were meta-analysed across the six databases. RESULTS: Mean BMI (coefficient -1.16 kg/m2; 95% CI -1.38 to 0.93) and SBP (-2.83 mm Hg; 95% CI -4.49 to -1.16) were lower in cases at diagnosis, and case-control differences were greater in more recent time periods, as indicated by significant case-x-time interaction and case-x-time-squared interaction terms. Time variations in coefficients for cholesterol levels were less consistent between databases and those for DBP were largely not significant. CONCLUSION: Routine clinical data show emerging divergence in levels of BMI and SBP prior to the diagnosis of dementia but less evidence for DBP or total cholesterol levels. These divergences should receive at least some consideration in routine dementia risk screening, although underlying mechanisms still require further investigation.

Comparative cardiovascular safety of strontium ranelate and bisphosphonates: a multi-database study in 5 EU countries by the EU-ADR Alliance.

Strontium ranelate use, compared with oral bisphosphonates, is not associated with increased risk of AMI in patients with no contraindications for SR use. However, current strontium ranelate (compared with current bisphosphonate) appears associated with 25-30% excess risk of VTE and 35% excess risk of CVDeath. INTRODUCTION: Evaluate the risk of cardiac and thromboembolic events among new users of SR and oral BPs without contraindications for SR. METHODS: We conducted three multi-national, multi-database (Aarhus-Denmark, HSD-Italy, IPCI-Netherlands, SIDIAP-Spain, THIN-UK) case-control studies nested within a cohort of new users of SR/BP. We matched cases of acute myocardial infarction (AMI), venous thromboembolism (VTE), and cardiovascular death (CVDeath), up to 10 controls on gender, year of birth, index date, and country. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CIs) according to current SR vs current BP use and current vs past SR use, adjusting for potential confounders. Data were pooled using random effects meta-analysis. RESULTS: No excess risk of AMI (5477 cases/54,674 controls) was found with current SR vs current BP (OR 0.89 (95%CI 0.70, 1.12)) nor with current vs past SR use (0.71(0.56, 0.91)). For VTE (5614 cases/6036 controls), an excess risk was found with current SR compared with current BP use, 1.24 (0.96, 1.61), and current vs past SR use, 1.30 (1.04, 1.62). For CVDeath (3019 cases/29,871 controls), an increased risk was seen with current SR vs current BP use, 1.35 (1.02, 1.80), but not with current vs past SR use (0.68 (0.48, 0.96)). CONCLUSION: In patients without contraindications for SR, we found no evidence of an increased risk of AMI but a 25-30% excess risk of VTE and a 35% excess risk of CVDeath with current SR vs current BP users. This is despite a reduction in risk in CVDeath with current vs past SR users. The latter disparity could still be partially explained by cessation of preventative therapies in end-of-life or residual confounding by indication.

Correction to: Impact of risk minimisation measures on the use of strontium ranelate in Europe: a multi-national cohort study in 5 EU countries by the EU-ADR Alliance.

The original version of this article, published on 26 November 2019 contained a mistake.

Impact of risk minimisation measures on the use of strontium ranelate in Europe: a multi-national cohort study in 5 EU countries by the EU-ADR Alliance.

INTRODUCTION: In May 2013 and March 2014, the European Medicines Agency (EMA) issued two decisions restricting the use of strontium ranelate (SR). These risk minimisation measures (RMM) introduced new contraindications and limited the indications of SR therapy. The EMA required an assessment of the impact of RMMs on the use of SR in Europe. Methods design: multi-national, multi-database cohort Setting: electronic medical record databases based on hospital (Denmark) and primary care provenance (Italy, Spain, the Netherlands, UK). PARTICIPANTS: the database source populations were included for population-based analyses, and SR users for patient-level analyses. INTERVENTION: New RMMs included contraindications (ischaemic heart disease, peripheral arterial disease, cerebrovascular disease, uncontrolled hypertension) and restricted SR indication to severe osteoporosis with initiation by experienced physician and not as first line anti-osteoporosis therapy. METHODS: Prevalence and incidence rates of SR use in the population; prevalence of contraindications and restricted indications in SR users, plus 1-year therapy persistence. Drug use measures were calculated in three periods for comparison: reference (2004 to May 2013), transition (June 2013 to March 2014) and assessment (from April 2014 to end 2016). RESULTS: The study population included 143 million person-years(PY) of follow-up and 76,141 incident episodes of SR treatment. Average monthly prevalence rates of SR use dropped by 86.4% from 62.6/10,000 PY (95 CI 62.4-62.9) in the reference to 8.5 (8.5-8.6) in the assessment period. Similarly, the incidence rate of SR use fell by 97.3% from 7.4/10,000 PY (7.4-7.4) to 0.2 (0.2-0.2) between the reference and assessment period. The prevalence of any contraindication decreased, whilst the prevalence of restricted indications increased in these periods. One-year persistence decreased in the assessment compared with reference period. CONCLUSIONS: Our study demonstrates a substantial impact of the regulatory action to restrict use of SR in Europe: SR utilisation overall decreased strongly. The proportion of patients fulfilling the restricted indications, without contraindications, increased after the proposed RMMs.

Accuracy of an automated knowledge base for identifying drug adverse reactions.

INTRODUCTION: Drug safety researchers seek to know the degree of certainty with which a particular drug is associated with an adverse drug reaction. There are different sources of information used in pharmacovigilance to identify, evaluate, and disseminate medical product safety evidence including spontaneous reports, published peer-reviewed literature, and product labels. Automated data processing and classification using these evidence sources can greatly reduce the manual curation currently required to develop reference sets of positive and negative controls (i.e. drugs that cause adverse drug events and those that do not) to be used in drug safety research. METHODS: In this paper we explore a method for automatically aggregating disparate sources of information together into a single repository, developing a predictive model to classify drug-adverse event relationships, and applying those predictions to a real world problem of identifying negative controls for statistical method calibration. RESULTS: Our results showed high predictive accuracy for the models combining all available evidence, with an area under the receiver-operator curve of ⩾0.92 when tested on three manually generated lists of drugs and conditions that are known to either have or not have an association with an adverse drug event. CONCLUSIONS: Results from a pilot implementation of the method suggests that it is feasible to develop a scalable alternative to the time-and-resource-intensive, manual curation exercise previously applied to develop reference sets of positive and negative controls to be used in drug safety research.

Risk of cardiac valvulopathy with use of bisphosphonates: a population-based, multi-country case-control study.

UNLABELLED: Analyses of healthcare data from 30 million individuals in three countries showed that current use of bisphosphonates may be associated with a small increased risk of cardiac valvulopathy (vs. those not exposed within the previous year), although confounding cannot be entirely ruled out. The observed tendency for decreased valvulopathy risk with cumulative duration of bisphosphonate use >6 months may even indicate a protective effect with prolonged use. Further studies are still needed to evaluate whether bisphosphonates increase or decrease the risk of valvulopathy. INTRODUCTION: A signal of cardiac valve disorders with use of bisphosphonates was identified in the literature and EudraVigilance database, which contains reports of suspected adverse drug reactions from worldwide sources. The aim of this study was to evaluate the association using population-based healthcare data. METHODS: This was a case-control study among users of bisphosphonates and other drugs for osteoporosis in six healthcare databases covering over 30 million individuals in Italy, Netherlands and the UK from 1996 to 2012. Prescriptions/dispensations were used to assess drug exposure. Newly diagnosed cases of cardiac valvulopathy were identified via disease codes/free-text search. Controls were matched to each case by age, sex, database and index date. Adjusted odds ratios (ORs) were estimated using conditional logistic regression for the pooled data and meta-analysis of individual database risk estimates. RESULTS: A small but statistically significant association was found between exposure to bisphosphonates as a class and risk of valvulopathy. Overall risk was 18 % higher (95 % CI 12-23 %) in those currently exposed to any bisphosphonate (mainly alendronate and risedronate) vs. those not exposed within the previous year. Risk of valve regurgitation was 14 % higher (95 % CI 7-22 %). Decreased valvulopathy risk was observed with longer cumulative duration of bisphosphonate use, compared to use of less than 6 months. Meta-analyses of database-specific estimates confirmed results from pooled analyses. CONCLUSIONS: The observed increased risks of cardiac valvulopathy with bisphosphonate use, although statistically significant, were quite small and unlikely to be clinically significant. Further studies are still needed to evaluate whether bisphosphonates increase or decrease the risk of valvulopathy and to investigate possible mechanisms for the association.

Antidepressants and heart-rate variability in older adults: a population-based study.

BACKGROUND: Tricyclic antidepressants (TCAs) and selective serotonin reuptake inhibitors (SSRIs) may be associated with lower heart rate variability (HRV), a condition associated with increased mortality risk. We aimed to investigate the association between TCAs, SSRIs and HRV in a population-based study. METHOD: In the prospective Rotterdam Study cohort, up to five electrocardiograms (ECGs) per participant were recorded (1991-2012). Two HRV variables were studied based on 10-s ECG recordings: standard deviation of normal-to-normal RR intervals (SDNN) and root mean square of successive RR interval differences (RMSSD). We compared the HRV on ECGs recorded during use of antidepressants with the HRV on ECGs recorded during non-use of any antidepressant. Additionally, we analysed the change in HRV on consecutive ECGs. Those who started or stopped using antidepressants before the second ECG were compared with non-users on two ECGs. RESULTS: We included 23 647 ECGs from 11 729 participants (59% women, mean age 64.6 years at baseline). Compared to ECGs recorded during non-use of antidepressants (n = 22 971), SDNN and RMSSD were lower in ECGs recorded during use of TCAs (n = 296) and SSRIs (n = 380). Participants who started using TCAs before the second ECG had a decrease in HRV and those who stopped had an increase in HRV compared to consistent non-users (p < 0.001). Starting or stopping SSRIs was not associated with HRV changes. CONCLUSION: TCAs were associated with a lower HRV in all analyses, indicating a real drug effect. For SSRIs the results are mixed, indicating a weaker association, possibly due to other factors.

Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how?

A growing number of international initiatives (e.g. EU-ADR, Sentinel, OMOP, PROTECT and VAESCO) are based on the combined use of multiple healthcare databases for the conduct of active surveillance studies in the area of drug and vaccine safety. The motivation behind combining multiple healthcare databases is the earlier detection and validation, and hence earlier management, of potential safety issues. Overall, the combination of multiple healthcare databases increases statistical sample size and heterogeneity of exposure for postmarketing drug and vaccine safety surveillance, despite posing several technical challenges. Healthcare databases generally differ by underlying healthcare systems, type of information collected, drug/vaccine and medical event coding systems and language. Therefore, harmonization of medical data extraction through homogeneous coding algorithms across highly different databases is necessary. Although no standard procedure is currently available to achieve this, several approaches have been developed in recent projects. Another main challenge involves choosing the work models for data management and analyses whilst respecting country-specific regulations in terms of data privacy and anonymization. Dedicated software (e.g. Jerboa) has been produced to deal with privacy issues by sharing only anonymized and aggregated data using a common data model. Finally, storage and safe access to the data from different databases requires the development of a proper remote research environment. The aim of this review is to provide a summary of the potential, disadvantages, methodological issues and possible solutions concerning the conduct of postmarketing multidatabase drug and vaccine safety studies, as demonstrated by several international initiatives.

Minimum bandwidth requirements for recording of pediatric electrocardiograms.

BACKGROUND: Previous studies that determined the frequency content of the pediatric ECG had their limitations: the study population was small or the sampling frequency used by the recording system was low. Therefore, current bandwidth recommendations for recording pediatric ECGs are not well founded. We wanted to establish minimum bandwidth requirements using a large set of pediatric ECGs recorded at a high sampling rate. METHODS AND RESULTS: For 2169 children aged 1 day to 16 years, a 12-lead ECG was recorded at a sampling rate of 1200 Hz. The averaged beats of each ECG were passed through digital filters with different cut off points (50 to 300 Hz in 25-Hz steps). We measured the absolute errors in maximum QRS amplitude for each simulated bandwidth and determined the percentage of records with an error >25 microV. We found that in any lead, a bandwidth of 250 Hz yields amplitude errors <25 microV in >95% of the children <1 year. For older children, a gradual decrease in ECG frequency content was demonstrated. CONCLUSIONS: We recommend a minimum bandwidth of 250 Hz to record pediatric ECGs. This bandwidth is considerably higher than the previous recommendation of 150 Hz from the American Heart Association.

New normal limits for the paediatric electrocardiogram.

AIMS: Previous studies that determined the normal limits for the paediatric ECG had their imperfections: ECGs were recorded at a relatively low sampling rate, ECG measurements were conducted manually, or normal limits were presented for only a limited set of parameters. The aim of this study was to establish an up-to-date and complete set of clinically relevant normal limits for the paediatric ECG. METHODS AND RESULTS: ECGs from 1912 healthy Dutch children (age 11 days to 16 years) were recorded at a sampling rate of 1200 Hz. The digitally stored ECGs were analysed using a well-validated ECG computer program. The normal limits of all clinically relevant ECG measurements were determined for nine age groups. Clinically significant differences were shown to exist, compared with previously established normal limits. Sex differences could be demonstrated for QRS duration and several amplitude measurements. CONCLUSIONS: These new normal limits differ substantially from those commonly used and suggest that diagnostic criteria for the paediatric ECG should be adjusted.

A new approach to mechanical simulation of lung behaviour: pressure-controlled and time-related piston movement.

A mechanical lung simulator is described (an extension of a previous mechanical simulator) which simulates normal breathing and artificial ventilation in patients. The extended integration of hardware and software offers many new possibilities and advantages over the former simulator. The properties of components which simulate elastance and airway resistance of the lung are defined in software rather than by the mechanical properties of the components alone. Therefore, a more flexible simulation of non-linear behaviour and the cross-over effects of lung properties is obtained. Furthermore, the range of lung compliance is extended to simulate patients with emphysema. The dependency of airway resistance on lung recoil pressure and transmural pressure of the airways can also be simulated. The new approach enables one to incorporate time-related mechanics such as the influence of lung viscosity or cardiac oscillation. The different relations defined in the software can be changed from breath to breath. Three simulations are presented: (1) computer-controlled expiration in the artificially ventilated lung; (2) simulation of normal breathing; and (3) simulation of viscoelastance and cardiac influences during artificial ventilation. The mechanical simulator provides a reproducible and flexible environment for testing new software and equipment in the lung function laboratory and in intensive care, and can be used for instruction and training.

PEDMEANS: a computer program for the interpretation of pediatric electrocardiograms.

The interpretation pediatric electrocardiograms (ECGs) is complicated because of the strong age-dependency of the diagnostic criteria. We wanted to develop and evaluate a computer program for the interpretation of pediatric 12-lead ECGs. Continuous age-dependent normal limits were established based on ECGs from 1,912 healthy Dutch children. Additionally, a reference interpretation was obtained for 1,718 ECGs recorded at the Sophia Children's Hospital. The total set of ECGs was divided in a training set of 1076 ECGs and a test set of 642 ECGs. All ECGs were recorded at a sampling rate of 1,200 Hz. Based on the normal limits and the training set, diagnostic rules were formalized in an iterative process by using expert interviews and automatic rule induction. The resultant rules were evaluated on the test set. The performance of the program, on our study population, appears to justify its use in a clinical setting. Preferably, the program should also be evaluated in other clinical centers.

Effects of fluticasone propionate on methacholine dose-response curves in nonsmoking atopic asthmatics.

Methacholine is frequently used to determine bronchial hyperresponsiveness (BHR) and to generate dose-response curves. These curves are characterized by a threshold (provocative concentration of methacholine producing a 20% fall in forced expiratory volume in one second (PC20) = sensitivity), slope (reactivity) and maximal response (plateau). We investigated the efficacy of 12 weeks of treatment with 1,000 microg fluticasone propionate in a double-blind, placebo-controlled study in 33 atopic asthmatics. The outcome measures used were the influence on BHR and the different indices of the methacholine dose-response (MDR) curve. After 2 weeks run-in, baseline lung function data were obtained and a MDR curve was measured with doubling concentrations of the methacholine from 0.03 to 256 mg x mL(-1). MDR curves were repeated after 6 and 12 weeks. A recently developed, sigmoid cumulative Gaussian distribution function was fitted to the data. Although sensitivity was obtained by linear interpolation of two successive log2 concentrations, reactivity, plateau and the effective concentration at 50% of the plateau value (EC50) were obtained as best fit parameters. In the fluticasone group, significant changes occurred after 6 weeks with respect to means of PC20 (an increase of 3.4 doubling doses), plateau value fall in forced expiratory volume in one second (FEV1) (from 58% at randomization to 41% at 6 weeks) and baseline FEV1 (from 3.46 to 3.75 L) in contrast to the placebo group. Stabilization occurred after 12 weeks. Changes for reactivity were less marked, whereas changes in log, EC50 were not significantly different between the groups. We conclude that fluticasone is very effective in decreasing the maximal airway narrowing response and in increasing PC20. However, it is likely that part of this increase is related to the decrease of the plateau of maximal response.