Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.

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

Molecular diagnostic cytopathology: definitions, scope and clinical utility

Molecular diagnosis is the application of molecular biology techniques and knowledge of the molecular mechanisms of disease to diagnosis, prognostication and treatment of diseases. Although it is not widely used in routine molecular cytological practice, some examples are presented here of the application of molecular techniques to the routine cytopathological diagnosis of solid tumours and lymphoreticular malignancies. The term 'molecular diagnostic cytopathology' is proposed to define the application of molecular diagnosis to cytopathology, and the challenges of the introduction of molecular diagnosis into routine diagnostic histopathology and cytopathology are discussed. Finally, the importance of a combined morphological, immunophenotypic and molecular approach to maintain the diagnostic pathologist at the heart of the clinical decision-making process is emphasized.

Utility, Caller, and Patient Profile of a Novel Chemotherapy Telephone Helpline Service Within a Regional Cancer Centre in Northern Ireland

Background: The telephone is an accepted and useful means of communication for the management of patient care. The Chemotherapy Telephone Helpline (CTH) service, located in a large inner-city Trust within the United Kingdom, is a unique nurse-led service within Northern Ireland.

Objective: The objective of the study was to investigate the utility, caller, and patient profile of a novel CTH.

Methods: This was a retrospective study of telephone contacts during 2007 to the CTH. Calls were categorized by caller and patient characteristics, reason for call, and subsequent action.

Results: A total of 7498 calls were made to the CTH during 2007. Of these, 25.6% occurred outside 8AM-4PM. Callers included patients (45.8%), lay carers (31%), and health care professionals (20.5%); 35.2% of calls concerned patients with polysymptomatic problems; 36.8% of calls led directly to patients being medically assessed.

Conclusions: The utility of the CTH service confirms the need of this nurse-led service. This service facilitates access to specialist advice and support for patients, their families, and allied health care professionals.

Implications for Practice: The international significance of these findings for practice includes its demonstration of the multifaceted symptom experience of patients receiving chemotherapy and highlights the importance of rapid access to specialist cancer services for patients and their lay and professional carers. In addition, it demonstrates the capacity of helplines to identify gaps in professional skills and training.

Site choices in recreational demand: a matter of utility maximization or regret minimization?

This paper compares the Random Regret Minimization and the Random Utility Maximization models for determining recreational choice. The Random Regret approach is based on the idea that, when choosing, individuals aim to minimize their regret – regret being defined as what one experiences when a non-chosen alternative in a choice set performs better than a chosen one in relation to one or more attributes. The Random Regret paradigm, recently developed in transport economics, presents a tractable, regret-based alternative to the dominant choice paradigm based on Random Utility. Using data from a travel cost study exploring factors that influence kayakers’ site-choice decisions in the Republic of Ireland, we estimate both the traditional Random Utility multinomial logit model (RU-MNL) and the Random Regret multinomial logit model (RR-MNL) to gain more insights into site choice decisions. We further explore whether choices are driven by a utility maximization or a regret minimization paradigm by running a binary logit model to examine the likelihood of the two decision choice paradigms using site visits and respondents characteristics as explanatory variables. In addition to being one of the first studies to apply the RR-MNL to an environmental good, this paper also represents the first application of the RR-MNL to compute the Logsum to test and strengthen conclusions on welfare impacts of potential alternative policy scenarios.