Two-sample binary phase 2 trials with low type I error and low sample size.

We address design of two-stage clinical trials comparing experimental and control patients. Our end point is success or failure, however measured, with null hypothesis that the chance of success in both arms is p0 and alternative that it is p0 among controls and p1  > p0 among experimental patients. Standard rules will have the null hypothesis rejected when the number of successes in the (E)xperimental arm, E, sufficiently exceeds C, that among (C)ontrols. Here, we combine one-sample rejection decision rules, E⩾m, with two-sample rules of the form E - C > r to achieve two-sample tests with low sample number and low type I error. We find designs with sample numbers not far from the minimum possible using standard two-sample rules, but with type I error of 5% rather than 15% or 20% associated with them, and of equal power. This level of type I error is achieved locally, near the stated null, and increases to 15% or 20% when the null is significantly higher than specified. We increase the attractiveness of these designs to patients by using 2:1 randomization. Examples of the application of this new design covering both high and low success rates under the null hypothesis are provided. Copyright © 2017 John Wiley & Sons, Ltd.

A fortune cookie problem: A test for nominal data whether two samples are from the same population of equally likely elements.

This article considers a way to test the hypothesis that two collections of objects are from the same uniform distribution of such objects. The exact p-value is calculated based on the distribution for the observed overlaps. In addition, an interval estimate of the number of distinct objects, when all objects are equally likely, is indicated.

Source, co-occurrence, and prognostic value of PTEN mutations or loss in colorectal cancer.

Somatic PTEN mutations are common and have driver function in some cancer types. However, in colorectal cancers (CRCs), somatic PTEN-inactivating mutations occur at a low frequency (~8-9%), and whether these mutations are actively selected and promote tumor aggressiveness has been controversial. Analysis of genomic data from ~53,000 CRCs indicates that hotspot mutation patterns in PTEN partially reflect DNA-dependent selection pressures, but also suggests a strong selection pressure based on protein function. In microsatellite stable (MSS) tumors, PTEN alterations co-occur with mutations activating BRAF or PI3K, or with TP53 deletions, but not in CRC with microsatellite instability (MSI). Unexpectedly, PTEN deletions are associated with poor survival in MSS CRC, whereas PTEN mutations are associated with improved survival in MSI CRC. These and other data suggest use of PTEN as a prognostic marker is valid in CRC, but such use must consider driver mutation landscape, tumor subtype, and category of PTEN alteration.