OHDSI MEETINGS THIS WEEK
OHDSI Community Call - NO CALL THIS WEEK
OHDSI CDM and Vocabulary WG - Call rescheduled to Tuesday, July 10th from 1-2pm
Architecture Working Group - Thursday at 10am ET
Webex: https://jjconferencing.webex.com/mw3100/mywebex/default.do?service=1&siteurl=jjconferencing&nomenu=true&main_url=%2Fmc3100%2Fe.do%3Fsiteurl%3Djjconferencing%26AT%3DMI%26EventID%3D610982452%26UID%3D501476547%26Host%3DQUhTSwAAAAQu4P1o9qm71JJ1Zj4-uvZbjQttsCinu71JCRxBAHAXnzjjRAiTspTzU9ojLmjMF4CcTBWw4zn1dqYPTWu5vJ9_0%26FrameSet%3D2%26MTID%3Dm3e1ceeca56f1e94c9fcf1ae98c10e02e
GIS working group meeting - Next Monday (July 9th) at 10am ET
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Meeting Number: 735 317 239
Password: gaia
ANNOUNCEMENTS
2018 OHDSI Symposium - REGISTER NOW
Registration is officially open for the 2018 OHDSI Symposium which will take place Friday, October 12th. You can register here: https://www.ohdsi.org/symposium-registration-2/
Please note that registration for symposium tutorials, set to take place on October 11th and 13th is separate from symposium registration.
2018 OHDSI Symposium - TUTORIAL REGISTRATION OPEN
Registration is now open for tutorial sessions at this year’s OHDSI symposium. Intro tutorials will take place on Thursday, October 11th. Advanced tutorials will take place Saturday, October 13th. More information about tutorials is available here:
https://www.ohdsi.org/tutorial-workshops/
https://www.ohdsi.org/tutorial-registration-2/
Intro tutorials are being offered free of cost, however registration does not guarantee a seat in the tutorial. When you register, you will be placed on the tutorial wait-list. The final participant list will be determined by the tutorial faculty.
Advanced tutorials also offer the free wait-list registration. In addition, we are also offering a limited number of paid tickets ($318.17) which will guarantee your seat in the tutorial.
2018 OHDSI Symposium - CALL FOR PARTICIPATION
The OHDSI Symposium Planning Committee are now accepting abstract submissions for the 2018 collaborator showcase. We are inviting collaborators to submit abstracts to present posters, software demonstration or oral presentations during the collaborator showcase which will take place during the main symposium on Friday, October 12th. More details are available here: https://www.ohdsi.org/collaborator-showcase/
Abstract Submissions Due: 5pm on Thursday, August 7, 2018
It doesn’t matter who scores the goals, just that we win the games.
COMMUNITY PUBLICATIONS
Evaluating large-scale propensity score performance through real-world and synthetic data experiments
Levothyroxine use and the risk of breast cancer: a nation-wide population-based case-control study.
CC Wu, YY Yu, HC Yang, PA Nguyen, TN Poly, MM Islam, U Iqbal, HAA Khan, YC Wang, YT Cheng, YC Li and WS Jian,
Archives of gynecology and obstetrics , Aug 2018
To investigate whether the use of levothyroxine was associated with breast cancer risk.We conducted a population-based case-control study in Taiwan. Cases consisted of all patients who were aged 20 years and older, and had a first-time diagnosis of breast cancer for the period between 2001 and 2011. The controls were matched to the cases by age, sex, year, and month of diagnosis. Adjusted odd ratios (ORs) and 95% confidence intervals (CIs) were estimated by a conditional logistic regression.We examined 65,491 breast cancer cases and 261,964 controls. We found that use of levothyroxine was associated with a significant increase in breast cancer risk (OR 1.24, 95% CI 1.15-1.33; P < 0.001). Compared with no use levothyroxine, the adjusted odd ratio was 1.22 (95% CI 1.11-1.35; P = 0.01) for the group having been prescribed levothyroxine 2 months to 1 year, and 1.26 (95% CI 1.12-1.41; P < 0.01) for the group with more than 1 year. When stratified by age, the adjusted odd ratio was 1.45 (95% CI 1.23-1.71; P < 0.01) for the patients aged 65 years or more and 1.19 (95% CI 1.09-1.29, P < 0.01) for the patients aged less than 65 years.The results of the present study are the first to suggest that levothyroxine use increased the risk of breast cancer. However, a larger long-term prospective randomized-controlled trial specifically designed to assess the effect of levothyroxine use on the risk of developing breast cancer is needed.
The economic burden of preventable adverse drug reactions: a systematic review of observational studies.
D Formica, J Sultana, PM Cutroneo, S Lucchesi, R Angelica, S Crisafulli, Y Ingrasciotta, F Salvo, E Spina and G Trifirò,
Expert opinion on drug safety , Jul 2018
Adverse drug reactions (ADRs) are an important cause of morbidity and mortality worldwide. They are associated with healthcare costs due to hospital admissions or prolonged length of stay, as well as additional interventions. The aim of this study was to conduct a systematic review of observational studies to evaluate the economic impact of preventable ADRs. Areas covered: Published observational research investigating the cost of preventable ADRs in Western countries (limited to the USA and European countries). Expert opinion: Several reviews have been carried out in the field of the ADR epidemiology but fewer reviews have investigated the economic impact of ADRs, and at the time of writing, none has focused on preventable ADRs. The reason why future research should focus on the costs of preventable ADRs is that both the costs and the negative clinical outcomes are preventable, and as such, are a key point of public health policy action. Nevertheless, the present review highlights an important and sobering limitation of published research on the cost of preventable ADRs, of which the major limitation is the heterogeneity in methods and in reporting which limit what can be known through the summarizing work of a systematic review.
Computational methods for birth-death processes.
FW Crawford, LST Ho and MA Suchard,
Wiley interdisciplinary reviews. Computational statistics , Mar-Apr 2018
Many important stochastic counting models can be written as general birth-death processes (BDPs). BDPs are continuous-time Markov chains on the non-negative integers in which only jumps to adjacent states are allowed. BDPs can be used to easily parameterize a rich variety of probability distributions on the non-negative integers, and straightforward conditions guarantee that these distributions are proper. BDPs also provide a mechanistic interpretation - birth and death of actual particles or organisms - that has proven useful in evolution, ecology, physics, and chemistry. Although the theoretical properties of general BDPs are well understood, traditionally statistical work on BDPs has been limited to the simple linear (Kendall) process. Aside from a few simple cases, it remains impossible to find analytic expressions for the likelihood of a discretely-observed BDP, and computational difficulties have hindered development of tools for statistical inference. But the gap between BDP theory and practical methods for estimation has narrowed in recent years. There are now robust methods for evaluating likelihoods for realizations of BDPs: finite-time transition, first passage, equilibrium probabilities, and distributions of summary statistics that arise commonly in applications. Recent work has also exploited the connection between continuously- and discretely-observed BDPs to derive EM algorithms for maximum likelihood estimation. Likelihood-based inference for previously intractable BDPs is much easier than previously thought and regression approaches analogous to Poisson regression are straightforward to derive. In this review, we outline the basic mathematical theory for BDPs and demonstrate new tools for statistical inference using data from BDPs.
Comparative effectiveness of canagliflozin, SGLT2 inhibitors and non-SGLT2 inhibitors on the risk of hospitalization for heart failure and amputation in patients with type 2 diabetes mellitus: A real-world meta-analysis of 4 observational databases (OBSERVE-4D).
PB Ryan, JB Buse, MJ Schuemie, F DeFalco, Z Yuan, PE Stang, JA Berlin and N Rosenthal,
Diabetes, obesity & metabolism , Nov 2018
Sodium glucose co-transporter 2 inhibitors (SGLT2i) are indicated for treatment of type 2 diabetes mellitus (T2DM); some SGLT2i have reported cardiovascular benefit, and some have reported risk of below-knee lower extremity (BKLE) amputation. This study examined the real-world comparative effectiveness within the SGLT2i class and compared with non-SGLT2i antihyperglycaemic agents.Data from 4 large US administrative claims databases were used to characterize risk and provide population-level estimates of canagliflozin's effects on hospitalization for heart failure (HHF) and BKLE amputation vs other SGLT2i and non-SGLT2i in T2DM patients. Comparative analyses using a propensity score-adjusted new-user cohort design examined relative hazards of outcomes across all new users and a subpopulation with established cardiovascular disease.Across the 4 databases (142 800 new users of canagliflozin, 110 897 new users of other SGLT2i, 460 885 new users of non-SGLT2i), the meta-analytic hazard ratio estimate for HHF with canagliflozin vs non-SGLT2i was 0.39 (95% CI, 0.26-0.60) in the on-treatment analysis. The estimate for BKLE amputation with canagliflozin vs non-SGLT2i was 0.75 (95% CI, 0.40-1.41) in the on-treatment analysis and 1.01 (95% CI, 0.93-1.10) in the intent-to-treat analysis. Effects in the subpopulation with established cardiovascular disease were similar for both outcomes. No consistent differences were observed between canagliflozin and other SGLT2i.In this large comprehensive analysis, canagliflozin and other SGLT2i demonstrated HHF benefits consistent with clinical trial data, but showed no increased risk of BKLE amputation vs non-SGLT2i. HHF and BKLE amputation results were similar in the subpopulation with established cardiovascular disease. This study helps further characterize the potential benefits and harms of SGLT2i in routine clinical practice to complement evidence from clinical trials and prior observational studies.
Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization.
J Luo, W Chen, M Wu and C Weng,
International journal of medical informatics , 2017 12
Prior studies of clinical trial planning indicate that it is crucial to search and screen recruitment sites before starting to enroll participants. However, currently there is no systematic method developed to support clinical investigators to search candidate recruitment sites according to their interested clinical trial factors.In this study, we aim at developing a new approach to integrating the location data of over one million heterogeneous recruitment sites that are stored in clinical trial documents. The integrated recruitment location data can be searched and visualized using a map-based information retrieval method. The method enables systematic search and analysis of recruitment sites across a large amount of clinical trials.The location data of more than 1.4 million recruitment sites of over 183,000 clinical trials was normalized and integrated using a geocoding method. The integrated data can be used to support geographic information retrieval of recruitment sites. Additionally, the information of over 6000 clinical trial target disease conditions and close to 4000 interventions was also integrated into the system and linked to the recruitment locations. Such data integration enabled the construction of a novel map-based query system. The system will allow clinical investigators to search and visualize candidate recruitment sites for clinical trials based on target conditions and interventions.The evaluation results showed that the coverage of the geographic location mapping for the 1.4 million recruitment sites was 99.8%. The evaluation of 200 randomly retrieved recruitment sites showed that the correctness of geographic information mapping was 96.5%. The recruitment intensities of the top 30 countries were also retrieved and analyzed. The data analysis results indicated that the recruitment intensity varied significantly across different countries and geographic areas.This study contributed a new data processing framework to extract and integrate the location data of heterogeneous recruitment sites from clinical trial documents. The developed system can support effective retrieval and analysis of potential recruitment sites using target clinical trial factors.
Impact of the black triangle label on prescribing of new drugs in the United Kingdom: lessons for the United States at a time of deregulation.
DB Horton, T Gerhard, A Davidow and BL Strom,
Pharmacoepidemiology and drug safety , Nov 2017
Newly approved novel drugs in Europe receive a black triangle label to promote pharmacovigilance. With growing momentum for earlier drug approvals and reliance on real-world evidence, we studied if the black triangle label promotes more judicious prescribing.We examined whether general practitioners prescribed escitalopram, tadalafil, and vardenafil with a black triangle more cautiously than the same or similar drugs without a black triangle in The Health Improvement Network (UK). We performed interrupted time-series analyses to estimate changes in new prescription rates and nested case-control studies to compare characteristics of new users before and after removal of a black triangle.Prescribing rates to the 33 441 new users of these new drugs were highest shortly after initial approval and declined subsequently; there were no increases in rates of new prescriptions after a black triangle's removal (new prescriptions/million/month postlabel: escitalopram -1.5 [95% CI, -1.9 to -1.2]; tadalafil and vardenafil: -0.1 [95% CI, -0.6 to 0.4]). Among drugs in the same class, loss of a patent had more impact on prescribing rates than loss of a black triangle. People who began taking black triangle drugs were less likely to be young or to have multiple comorbidities or recent hospitalization compared with those starting the same drugs after the label's removal. However, these differences generally reflected secular trends seen also in similar, unlabeled medicines.Accelerated drug approvals could cause more uncertainty about drug effectiveness and safety, but specific labeling of newly approved medicines is unlikely to promote more judicious prescribing.
Quality Assessment of Biomedical Metadata Using Topic Modeling
http://ceur-ws.org/Vol-2112/sewebmeda_paper_2.pdf
A design framework and exemplar metrics for FAIRness
https://www.nature.com/articles/sdata2018118