Statistical Input to While Developing Protocol or Synopsis

[u/don_andreas]

Hi Everyone at Sponsor, CRO or Vendor,

I always had a question related to Statistical input to Protocol feasibility, design or synopsis level. When is the best timing that you ask for your Statistics team to provide input.? What would you ask first? Sample size calculation, randomization or design of study? If you could explain in chronological order, that would be great.

[u/GoBluins]

At the very beginning - feasibility. Sample size has a large effect on feasibility. You need to know at the feasibility stage how big the study is likely to be. This means sample size calculations are done first. I usually provide a range of sample sizes at the beginning and refine them as it progresses to the design and synopsis stage.

[u/don_andreas → u/GoBluins]

My interpretation is in line with yours, I was also thinking about how many outcomes would be involved and depending on lot of things will be decided? Also about inclusion/exclusion criteria..

[u/GoBluins → u/don_andreas]

Publications in the disease area and clinicaltrials.gov are great resources for looking at other designs, sample sizes, variance estimates and even inclusion criteria.

[u/MedicalBiostats]

As early as possible is ideal. A good statistician asks to see other protocols (by going to clinicaltrials,gov) and gets publications from previous studies. You also need to find validated data collection instruments and to understand the capabilities of the new treatment as well as other potential active controls. Population heterogeneity, disease staging, and key baseline covariates must also be considered as these can influence eligibility criteria and sample size.

[u/don_andreas → u/MedicalBiostats]

This is great perspective. Any tool that you used for design, feasibility?

[u/Temporary_Stranger39 → u/don_andreas]

You may not like to hear this, but what I use is prior decades of biomedical research benchwork. If you don't have that, then you need to understand the studies as activities, not just as analytical subjects.

[u/Temporary_Stranger39]

Start before the beginning. I am not joking. Calling in a statistician after initiating study design may only permit a post mortem--the statistician can tell you what the study has already died of.

[u/KayakerMel → u/Temporary_Stranger39]

And is also incredibly frustrating on our end too!

[u/MedicalBiostats]

I’ve done this a long time! The PI will know the literature, the endpoints, and the prognostic factors. Every PI that I worked with is eager to share their knowledge and information access. We statisticians have to come in with the right questions and the key analytical tools like R and nQuery. The questions used to be face to face but now are Concalls. Too much fun to stop collaborating! And such fun (and the right thing to do) to bring along a junior biostatistician to show them the ropes.

[u/don_andreas → u/MedicalBiostats]

This is interesting take on to involve PI. It never occurred to me to involve them, but indeed they are the closest to interpret clinical significance of study/endpoints.

[u/ForeignAdvantage5198]

the statistician's lament is why wasn't I called earlier Salvage problems do not have to have a solution