Drug development stats and research
Statistics 101 for the oncologist
David L. Streiner, PhD, of McMaster University and the University of Toronto, joins Blood & Cancer host David Henry, MD, of Pennsylvania Hospital, Philadelphia, to break down the basic statistics knowledge that doctors need – but may not have – to understand and contextualize research findings.
In Clinical Correlation, Ilana Yurkiewicz, MD, of Stanford (Calif.) University talks about reclaiming the term “sorry.” Dr. Yurkiewicz writes a regular column for Hematology News, which you can find by clicking here.
By Emily Bryer, DO, resident in the department of internal medicine, University of Pennsylvania, Philadelphia
- Statistics provide objective evidence for whether we are seeing a true effect of a medicine or intervention, or if that outcome occurs because of chance alone.
- Clinical trials include a selective population (usually from tertiary care hospitals) and tend to involve the most severe cases.
- When interpreting data reported from a trial, it is essential to ask how similar the population in the trial is to the population you see in your clinical practice.
- Drug Approval Stages
- Phase 1: Assess drug efficacy and toxicity
- Phase 2: Identify correct dose; assess pharmacodynamics and pharmacokinetics
- Phase 3: Randomized, controlled trial necessary for confirming drug effectiveness and providing a comparison to current standard of care treatments
- How to design a trial
- Ensure that the surrogate endpoint is highly correlated to the outcome of interest
Additional reading by Dr. Streiner: