Hypermutation In Pancreatic Cancer.

Pancreatic cancer is molecularly diverse, with few effective therapies. Increased mutation burden and defective DNA repair are associated with response to immune checkpoint inhibitors in several other cancer types. We interrogated 385 pancreatic cancer genomes to define hypermutation and its causes. Mutational signatures inferring defects in DNA repair were enriched in those with the highest mutation burdens. Mismatch repair deficiency was identified in 1% of tumors harboring different mechanisms of somatic inactivation of MLH1 and MSH2. Defining mutation load in individual pancreatic cancers and the optimal assay for patient selection may inform clinical trial design for immunotherapy in pancreatic cancer.

Rasch-derived latent trait measurement of outcomes: insightful use leads to precision case management and evidence-based practices in functional healthcare.

The use of Rasch-derived latent trait measurement of outcomes for persons with chronic disease and disablement evolved from other fields, particularly education. Person-metrics is the measurement of how much chronic disease and disablement affects an individual's daily activities physically, cognitively, and through vocational and social role participation. The ability of the Rasch model to assume that the probability of a given person/item interaction is governed by the difficulty of the item and the ability of the person is invaluable to disability measurement. The difference between raw scores and true measures is illustrated by an example of a patient whose physical difficulty is rated on rising from a wheelchair and walking 100m (known to be more difficult), and then walking an additional 200m. Though number ratings of 0-1-2 are assigned to these tasks, they are not equidistant, and only a true measure shows the actual levels of physical difficulty.

The ISR: intelligent student reports.

Rasch-based Scale Scores are a simple linear transformation of the basic logit metric. Scale Scores are the quantification of the measurement continuum. This quantification makes it possible to do arithmetic, computer differences, and apply standard statistical techniques. However, qualitative meaning is not in the numbers and must come from experience with the scale and from the descriptive information that can (and should) be attached. This includes item content and exemplars, normative information for relevant groups, historical data for the individual, and evaluative assessment like performance levels standards. The Scale Score metric is the structure that manages the organization of intelligent reports and recognizes anomalies. Scale Scores have no meaning, per se, but can provide a strong framework for organizing useful reports and presenting meaningful information. They facilitate diagnosis by "Analysis of Fit" and by "Analysis of Misfit." The Analysis of Fit relies on the general definition of the construct to describe what a student at a particular point on the scale can and cannot do. It is meaningful to the extent that the student conforms to the expectations of the measurement model. The Analysis of Misfit uses the model to identify surprises, i.e., departures from the model expectations. It highlights atypical areas of strong and weak performance. The intent is to bring these exceptons to the attention of the experts for informed, substantive interpretation and diagnosis. Intelligent reports, to be useful, and to justify the time and expense of testing, need to provide more information in a useable format than the candidate, student, parent, or educator had available otherwise. This requires more than reporting a single number or a single decision. It should include sufficient scaffolding to allow the consumer to extract quickly and efficiently all the useful information that can be taken from the test. Rasch Scale Scores are an important, perhaps essential, tool in this process.