The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.

Best Sample Size Calculators for iPhone

March 6, 2018


Photo by Dose Media on Unsplash

By Charles Liu, Senior Product Manager, Cytel

Several years ago, I was one of few Luddites in my social circle still using a “dumb” phone. Other than calls, and (text only!) messaging, it had no other functionality. Once I made the switch, a whole new magical world unveiled itself. With the tap of a button, I could read my email, listen to a podcast, find a nearby restaurant, order a cab, snap a photo, and so on. What was once considered science fiction seems an indispensable part of life today.

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2017 ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop

October 24, 2017

The ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop is sponsored by the ASA Biopharmaceutical Section in cooperation with the FDA Statistical Association. Each year 800 statistical practitioners come together to absorb new information on statistical practices in all areas regulated by the FDA.

Cytel was honored to be involved in the workshop program, and our subject matter experts added value to the conference by sharing their academic and regulatory experiences.

Don’t worry if you missed the event!

In this blog, we share the full slide set slide from Cytel contributions at the ASA Biopharmaceutical Section Regulatory Industry Statistics Workshop.

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3 Strategies to Combat Inferential Conservatism in Small Sample Sizes

June 25, 2015

When conducting a clinical trial with small or sparse data sets, statistical methods meant for large sample sizes may fail to obtain an accurate interpretation of data. This is where computationally challenging exact methods often come into play.

Exact methods, however, are inferentially conservative in the sense that due to small sample sizes, the actual Type 1 error rate is often smaller than the nominal (intended) rate [1]. There exists an array of strategies to combat this troublesome feature of exact tests, each of which varies along the parameter of computational complexity.

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Operationally Seamless & Inferentially Seamless Adaptive Designs

December 4, 2014

Fulyzaq® from Napo/Salix was the first drug ever to be approved using an adaptive two-stage "seamless" clinical trial design. However, when Napo Pharmaceuticals sought orphan drug status for Crofelemer (made from the croton lechleri plant, pictured above left), it received a short window from the FDA in which to complete a Phase 3 trial for safety and efficacy. Aiming to diminish both time and cost, Napo submitted an adaptive design for a Crofelemer trial to the FDA. Initially, the design was rejected on grounds that it would not demonstrate strong control of the type-1 error rate.

Napo then approached Cytel consultants which advised it to consider a seamless adaptive trial. A seamless adaptive trial combines 2 phases of a study into one trial, thereby allowing a trial to complete within a short window. Using appropriate techniques, it is possible to conduct such studies while maintaining strong control of type-1 error.  

A seamless adaptive design may be operationally seamless or inferentially seamless. An operationally seamless design is one in which a confirmatory trial proceeds after an exploratory one, but the data from the two are kept distinct. By contrast, an inferentially seamless trial combines data from both phases to make the final inference. Due to these two varieties of seamless adaptive designs, Napo/Salix had the following 3 trial designs from which to choose:

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The Perils of Poor Recruitment

May 5, 2014

A new JAMA study on discontinued randomized trials in Switzerland, Germany and Canada, reports that poor recruitment accounts for 101 out of 253 trials that were eventually discontinued (or about 10% of the 1017 trials which participated in the study). When restricted to industry-sponsored trials with non-healthy volunteers, poor recruitment accounted for the discontinuation of 40 trials out of 119 that were discontinued. Across the board, poor recruitment was the foremost cause of trial discontinuity.

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