Network Update #34

Happy New Year 2022 to all subscribers to the newsletter! Hope this year will mark the end of the global Covid19 pandemic and same time next year we will celebrate un-masking ourselves :)

Let's start!

Programming:

Jagadish Katam shared another article on?#R?in?Linkedin. In this article Jagadish looks into the different approaches of pattern matching and replacement through stringr?package?with?perl?regular expressions?in?#R.?Link

Hengwei Liu has published an abstract - "Cross-check SDTM and ADaM in Regulatory Submission Package." According to the ADaM IG 1.1, if the same variable name is in both SDTM and ADaM datasets, the label and type of the variable should remain the same for this variable. We set up SAS? macros to check this rule in a regulatory submission package. The checking consists of two aspects: compare the variables in the SDTM datasets and the ADaM datasets; compare the define.xml for SDTM and the define.xml for ADaM. Two different approaches are discussed in the comparison of the define.xml. One approach requires the use of Pinnacle 21 community, the other SAS XML mapper. Link

Biostatistics: Thanks to Stefano Vezzoli!

"Using principal stratification in analysis of clinical trials." The ICH E9(R1) addendum (2019) proposed principal stratification (PS) as one of five strategies for dealing with intercurrent events. Therefore, understanding the strengths, limitations, and assumptions of PS is important for the broad community of clinical trialists. Check this tutorial. Link

"Addressing exaggeration of effects from single RCTs." Randomised controlled trials are often presented as the gold standard for testing new medical treatments. In the early stages of research, however, reports from single trials are likely to show exaggerated effect estimates.?Erik van Zwet, Simon Schwab?and?Sander Greenland?explain why – and propose a remedy. Link

"A Systematic Review of Methods used to Conduct Decentralised Clinical Trials." To evaluate, using quantitative and qualitative approaches, published data on the design and conduct of decentralised clinical trials (DCTs).Link

"Solutions to problems of nonexistence of parameter estimates and sparse data bias in Poisson regression." Poisson regression can be challenging with sparse data, in particular with certain data constellations where maximum likelihood estimates of regression coefficients do not exist. This paper provides a comprehensive evaluation of methods that give finite regression coefficients when maximum likelihood estimates do not exist, including Firth’s general approach to bias reduction, exact conditional Poisson regression, and a Bayesian estimator using weakly informative priors that can be obtained via data augmentation. Link

Webinars and articles:

Sangeeta Bhattacharya has published a very interesting article on her blog "Machine Learning in Drug Development" with a few examples from her experience of adding ML to drug development. Link

PSI Vaccine & COVID-19 SIGs Joint Webinar: Statistics, Vaccine Development, and the COVID-19 Crisis - VOD series. The first talk is about "Introduction to Statistical Methods and Challenges in Vaccine Development" by Ivan Chan and the second talk about "Vaccine quintet. Statistical issues in the design and analysis of five vaccine programmes" by Stephen Senn. Link

PSI Training Course: "Use of Historical Data in Clinical Trials: An Evidence Synthesis Approach." Attendees will have the chance to cover; Bayesian Dynamic Borrowing designs based on the meta-analytic predictive (MAP) model; Design planning, operating characteristics, statistical analysis; and Applications using the R package RBesT. Link

Events:

"Causal Inference: Learn from the Experts." This 4-day course introduces concepts and methods for causal inference from observational data. Upon completion of the course, participants will be prepared to further explore the causal inference literature. Topics covered include the g-formula, inverse probability weighting of marginal structural models, causal mediation analysis, and methods to handle unmeasured confounding.(21 June - 1 July 2022). Link

The 2022 CDISC Europe Interchange is an event consisting of workshops, training courses, and a two day Main Conference. This event will provide an opportunity to share progress, implementation experiences, and strategic ideas on world wide data interchange standards for medical research. April 25, 2022—April 29, 2022 Copenhagen Link

Royal Statistical Society trainings for 2022. Basic statistics, data visualisation, essentials of survey research design, identifying trends and making forecasts, intermediate statistics, introduction to Bayesian statistics, presenting data. Link