Ryan J. Lennon is a statistician with clinical research experience in the areas of coronary artery disease, spinal cord injury rehabilitation and gastrointestinal diseases. The majority of Mr. Lennon's work comprises observational study designs and outcomes research for which he uses several statistical tools including propensity scores, case-referent matching and survival analysis.
Recently, Mr. Lennon has also been a co-investigator for an international multisite pharmacogenomics clinical trial investigating whether a genotype-guided medication strategy improves outcomes after coronary stent placement.
- Outcomes research. Mr. Lennon is interested in many statistical tools for comparison of nonrandomized group assignments, including propensity scores, matching, stratification, regression and weighted estimation.
- Statistical software. Mr. Lennon is the author of several SAS macros and seeks to create software tools aiming to streamline the programming effort and improve the tabular and graphical displays of statistical analyses.
- Prediction models. Mr. Lennon has been a co-author of several prediction models for coronary angioplasty outcomes and has interest in statistical methods for assessing model overfit, discrimination and calibration, and presentation of model results.
Significance to patient care
Mr. Lennon's research assists physicians in exploring the efficacy and safety of myriad treatment options, as well as identifying patient subsets with substantially different prognoses. Understanding individually tailored risk estimates for a given treatment assists with physician-patient dialogue and aids in decision making.