The EORTC QLU-C10D distinguished better between cancer patients and the general population than PROPr and EQ-5D-5L in a cross-sectional study.

Objectives: Health state utility (HSU) instruments for calculating quality-adjusted life years, such as the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Utility - Core 10 Dimensions (QLU-C10D), derived from the EORTC QLQ-30 questionnaire, the Patient-Reported Outcome Measurement Information System (PROMIS) preference score (PROPr), and the EuroQoL-5-Dimensions-5-Levels (EQ-5D-5L), yield different HSU values due to different modeling and different underlying descriptive scales. For example the QLU-C10D includes cancer-relevant dimensions such as nausea. This study aimed to investigate how these differences in descriptive scales contribute to differences in HSU scores by comparing scores of cancer patients receiving chemotherapy to those of the general population.

The PROPr can be measured using different PROMIS domain item sets.

Background: The Patient-Reported Outcomes Measurement Information System (PROMIS) Preference Score (PROPr) is estimated from descriptive health assessments within the PROMIS framework. The underlying item response theory (IRT) allows researchers to measure PROMIS health domains with any subset of items that are calibrated to this domain. Consequently, this should also be true for the PROPr.

Scale agreement, ceiling and floor effects, construct validity, and relative efficiency of the PROPr and EQ-5D-3L in low back pain patients.

Background: The PROMIS Preference score (PROPr) is a new health state utility (HSU) score that aims to comprehensively incorporate the biopsychosocial model of health and apply favorable psychometric properties from the descriptive PROMIS system to HSU measurements. However, minimal evidence concerning comparisons to the EQ-5D-3L and the PROPr's capability to differentiate clinical severity are available. Therefore, the aim of this study was to compare the PROPr to the EQ-5D-3L in terms of scale agreement, ceiling/floor effects, distribution, construct validity, discriminatory power, and relative efficiency (RE) in terms of the Oswestry Disability Index (ODI) for patients with low back pain (LBP).

Tailored machine learning models for functional RNA detection in genome-wide screens.

The prediction of non-coding and protein-coding genetic loci has received considerable attention in comparative genomics aiming in particular at the identification of properties of nucleotide sequences that are informative of their biological role in the cell. We present here a software framework for the alignment-based training, evaluation and application of machine learning models with user-defined parameters. Instead of focusing on the one-size-fits-all approach of pervasive annotation pipelines, we offer a framework for the structured generation and evaluation of models based on arbitrary features and input data, focusing on stable and explainable results.

Measuring PROMIS pain interference in German patients with chronic conditions: calibration, validation, and cross-cultural use of item parameters.

Purpose: To calibrate the item parameters of the German PROMIS® Pain interference (PROMIS PI) items using an item-response theory (IRT) model and investigate psychometric properties of the item bank.

Methods: Forty items of the PROMIS PI item bank were collected in a convenience sample of 660 patients, which were recruited during inpatient rheumatological treatment or outpatient psychosomatic medicine visits in Germany. Unidimensionality, monotonicity, and local independence were tested as required for IRT analyses.