Partially Ordered Preferences in Decision Trees: Computing Strategies with Imprecision in Probabilities

Partially ordered preferences generally lead to choices that do not abide by standard expected utility guidelines; often such preferences are revealed by imprecision in probability values. We investigate five criteria for strategy selection in decision trees with imprecision in probabilities: “extensive” Γ-maximin and Γ-maximax, interval dominance, maximality and E-admissibility. We present algorithms that generate strategies for all these criteria; our main contribution is an algorithm for Eadmissibility that runs over admissible strategies rather than over sets of probability distributions.

Stated choices and benefit estimates in the context of traffic calming schemes:Utility maximization, regret minimization, or both?

This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.

The Utility of Cardiopulmonary Exercise Testing in Difficult Asthma

Background: Unexplained persistent breathlessness in patients with difficult asthma despite multiple treatments is a common clinical problem. Cardiopulmonary exercise testing (CPX) may help identify the mechanism causing these symptoms, allowing appropriate management.

Methods: This was a retrospective analysis of patients attending a specialist-provided service for difficult asthma who proceeded to CPX as part of our evaluation protocol. Patient demographics, lung function, and use of health care and rescue medication were compared with those in patients with refractory asthma. Medication use 6 months following CPX was compared with treatment during CPX.

Results: Of 302 sequential referrals, 39 patients underwent CPX. A single explanatory feature was identified in 30 patients and two features in nine patients: hyperventilation (n = 14), exercise-induced bronchoconstriction (n = 8), submaximal test (n = 8), normal test (n = 8), ventilatory limitation (n = 7), deconditioning (n = 2), cardiac ischemia (n = 1). Compared with patients with refractory asthma, patients without “pulmonary limitation” on CPX were prescribed similar doses of inhaled corticosteroid (ICS) (median, 1,300 µg [interquartile range (IQR), 800-2,000 µg] vs 1,800 µg [IQR, 1,000-2,000 µg]) and rescue oral steroid courses in the previous year (median, 5 [1-6] vs 5 [1-6]). In this group 6 months post-CPX, ICS doses were reduced (median, 1,300 µg [IQR, 800-2,000 µg] to 800 µg [IQR, 400-1,000 µg]; P < .001) and additional medication treatment was withdrawn (n = 7). Patients with pulmonary limitation had unchanged ICS doses post CPX and additional therapies were introduced.

Conclusions: In difficult asthma, CPX can confirm that persistent exertional breathlessness is due to asthma but can also identify other contributing factors. Patients with nonpulmonary limitation are prescribed inappropriately high doses of steroid therapy, and CPX can identify the primary mechanism of breathlessness, facilitating steroid reduction.

Clinical Utility of Microarray-Based Gene Expression Profiling in the Diagnosis and Subclassification of Leukemia: Report From the International Microarray Innovations in Leukemia Study Group

The Microarray Innovations in Leukemia study assessed the clinical utility of gene expression profiling as a single test to subtype leukemias into conventional categories of myeloid and lymphoid malignancies. METHODS: The investigation was performed in 11 laboratories across three continents and included 3,334 patients. An exploratory retrospective stage I study was designed for biomarker discovery and generated whole-genome expression profiles from 2,143 patients with leukemias and myelodysplastic syndromes. The gene expression profiling-based diagnostic accuracy was further validated in a prospective second study stage of an independent cohort of 1,191 patients. RESULTS: On the basis of 2,096 samples, the stage I study achieved 92.2% classification accuracy for all 18 distinct classes investigated (median specificity of 99.7%). In a second cohort of 1,152 prospectively collected patients, a classification scheme reached 95.6% median sensitivity and 99.8% median specificity for 14 standard subtypes of acute leukemia (eight acute lymphoblastic leukemia and six acute myeloid leukemia classes, n = 693). In 29 (57%) of 51 discrepant cases, the microarray results had outperformed routine diagnostic methods. CONCLUSION: Gene expression profiling is a robust technology for the diagnosis of hematologic malignancies with high accuracy. It may complement current diagnostic algorithms and could offer a reliable platform for patients who lack access to today's state-of-the-art diagnostic work-up. Our comprehensive gene expression data set will be submitted to the public domain to foster research focusing on the molecular understanding of leukemias