Robust parametric indirect estimates of the expected cost of a hospital stay with covariates and censored data.

We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.

Cytogenetic response to imatinib in chronic myeloid leukaemia patients: concentration dependency and associated influences under field-conditions

Introduction: Imatinib, a first-line drug for chronic myeloid leukaemia (CML), has been increasingly proposed for therapeutic drug monitoring (TDM), as trough concentrations >=1000 ng/ml (Cmin) have been associated with improved molecular and complete cytogenetic response (CCyR). The pharmacological monitoring project of EUTOS (European Treatment and Outcome Study) was launched to validate retrospectively the correlation between Cmin and response in a large population of patients followed by central TDM in Bordeaux.¦Methods: 1898 CML patients with first TDM 0-9 years after imatinib initiation, providing cytogenetic data along with demographic and comedication (37%) information, were included. Individual Cmin, estimated by non-linear regression (NONMEM), was adjusted to initial standard dose (400 mg/day) and stratified at 1000 ng/ml. Kaplan-Meier estimates of overall cumulative CCyR rates (stratified by sex, age, comedication and Cmin) were compared using asymptotic logrank k-sample test for interval-censored data. Differences in Cmin were assessed by Wilcoxon test.¦Results: There were no significant differences in overall cumulative CCyR rates between Cmin strata, sex and comedication with P-glycoprotein inhibitors/inducers or CYP3A4 inhibitors (p >0.05). Lower rates were observed in 113 young patients <30 years (p = 0.037; 1-year rates: 43% vs 60% in older patients), as well as in 29 patients with CYP3A4 inducers (p = 0.001, 1-year rates: 40% vs 66% without). Higher rates were observed in 108 patients on organic-cation-transporter-1 (hOCT-1) inhibitors (p = 0.034, 1-year rates: 83% vs 56% without). Considering 1-year CCyR rates, a trend towards better response for Cmin above 1000 ng/ml was observed: 64% (95%CI: 60-69%) vs 59% (95%CI: 56-61%). Median Cmin (400 mg/day) was significantly reduced in male patients (732 vs 899ng/ml, p <0.001), young patients <30 years (734 vs 802 ng/ml, p = 0.037) and under CYP3A4 inducers (758 vs 859 ng/ml, p = 0.022). Under hOCT-1 inhibitors, Cmin was increased (939 vs 827 ng/ml, p = 0.038).¦Conclusion: Based on observational TDM data, the impact of imatinib Cmin >1000 ng/ml on CCyR was not salient. Young CML patients (<30 years) and patients taking CYP3A4 inducers probably need close monitoring and possibly higher imatinib doses, due to lower Cmin along with lower CCyR rates. Patients taking hOCT-1 inhibitors seem in contrast to have improved CCyR response rates. The precise role for imatinib TDM remains to be established prospectively.

Robust accelerated failure time regression

Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

Influenza surveillance using data from a telemedicine centre.

OBJECTIVES: This study aimed at investigating whether data from medical teleconsultations may contribute to influenza surveillance. METHODS: International Classification of Primary Care 2nd Edition (ICPC-2) codes were used to analyse the proportion of teleconsultations due to influenza-related symptoms. Results were compared with the weekly Swiss Sentinel reports. RESULTS: When using the ICPC-2 code for fever we could reproduce the seasonal influenza peaks of the winter seasons 07/08, 08/09 and 09/10 as depicted by the Sentinel data. For the pandemic influenza 09/10, we detected a much higher first peak in summer 2009 which correlated with a potential underreporting in the Sentinel system. CONCLUSIONS: ICPC-2 data from medical teleconsultations allows influenza surveillance in real time and correlates very well with the Swiss Sentinel system.

Example of Data Telemetry for Biomedical Applications: An In Vivo Experiment

This letter describes a data telemetry biomedical experiment. An implant, consisting of a biometric data sensor, electronics, an antenna, and a biocompatible capsule, is described. All the elements were co-designed in order to maximize the transmission distance. The device was implanted in a pig for an in vivo experiment of temperature monitoring.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

Linking Global Youth Tobacco Survey (GYTS) data to the WHO Framework Convention on Tobacco Control (FCTC): the case for the Seychelles

Tobacco control has been recognized as a main public health concern in Seychelles for the past two decades. Tobacco advertising, sponsoring and promotion has been banned for years, tobacco products are submitted to high taxes, high-profile awareness programs are organized regularly, and several other control measures have been implemented. The Republic of Seychelles was the first country to ratify the WHO Framework Convention on Tobacco Control (FCTC) in the African region. Three population-based surveys have been conducted in adults in Seychelles and results showed a substantial decrease in the prevalence of smoking among adults between 1989 and 2004. A first survey in adolescents was conducted in Seychelles in 2002 (the Global Youth Tobacco Survey, GYTS) in a representative sample of 1321 girls and boys aged 13-15 years. The results show that approximately half of students had tried smoking and a quarter of both boys and girls had smoked at least one cigarette during the past 30 days. Although "current smoking" is defined differently in adolescents (>or=1 cigarette during the past 30 days) and in adults (>or=1 cigarette per day), which precludes direct comparison, the high smoking prevalence in youth in Seychelles likely predicts an increasing prevalence of tobacco use in the next adult generation, particularly in women. GYTS 2002 also provides important data on a wide range of specific individual and societal factors influencing tobacco use. Hence, GYTS can be a powerful tool for monitoring the situation of tobacco use in adolescents, for highlighting the need for new policy and programs, and for evaluating the impact of current and future programs.

Handheld-assisted field data collection for occupational risk assessment.

A computerized handheld procedure is presented in this paper. It is intended as a database complementary tool, to enhance prospective risk analysis in the field of occupational health. The Pendragon forms software (version 3.2) has been used to implement acquisition procedures on Personal Digital Assistants (PDAs) and to transfer data to a computer in an MS-Access format. The data acquisition strategy proposed relies on the risk assessment method practiced at the Institute of Occupational Health Sciences (IST). It involves the use of a systematic hazard list and semi-quantitative risk assessment scales. A set of 7 modular forms has been developed to cover the basic need of field audits. Despite the minor drawbacks observed, the results obtained so far show that handhelds are adequate to support field risk assessment and follow-up activities. Further improvements must still be made in order to increase the tool effectiveness and field adequacy.

Hydrogeophysical data integration at larger scales: Application of Bayesian sequential simulation for the characterization of heterogeneous alluvial aquifers

Knowledge of the spatial distribution of hydraulic conductivity (K) within an aquifer is critical for reliable predictions of solute transport and the development of effective groundwater management and/or remediation strategies. While core analyses and hydraulic logging can provide highly detailed information, such information is inherently localized around boreholes that tend to be sparsely distributed throughout the aquifer volume. Conversely, larger-scale hydraulic experiments like pumping and tracer tests provide relatively low-resolution estimates of K in the investigated subsurface region. As a result, traditional hydrogeological measurement techniques contain a gap in terms of spatial resolution and coverage, and they are often alone inadequate for characterizing heterogeneous aquifers. Geophysical methods have the potential to bridge this gap. The recent increased interest in the application of geophysical methods to hydrogeological problems is clearly evidenced by the formation and rapid growth of the domain of hydrogeophysics over the past decade (e.g., Rubin and Hubbard, 2005).

Are there two species of Pygmy Shrews (Sorex)? Revisiting the question using DNA sequence data

Pygmy Shrews in North America have variously been considered to be one species (Sorex hoyi) or two species (S. hoyi and S. thompsoni). Currently, only S. hoyi is recognized. In this study, we examine mitochondrial DNA sequence data for the cytochrome b gene to evaluate the level of differentiation and phylogeographic relationships among eleven samples of Pygmy Shrews from across Canada. Pygmy Shrews from eastern Canada (i.e., Ontario, Quebec, New Brunswick, Nova Scotia, and Prince Edward Island) are distinct from Pygmy Shrews from western Canada (Alberta, Yukon) and Alaska. The average level of sequence divergence between these clades (3.3%) falls within the range of values for other recognized pairs of sister species of shrews. A molecular clock based on third position transversion substitutions suggests that these two lineages diverged between 0.44 and 1.67 million years ago. These molecular phylogenetic data. combined with a reinterpretation of previously published morphological data, are suggestive of separate species status for S. hoyi and S. thompsoni as has been previously argued by others. Further analysis of specimens from geographically intermediate areas (e.g., Manitoba. northern Ontario) is required to determine if there is secondary contact and/or introgression between these two putative species.

Body mass index, cigarette smoking, and alcohol consumption and cancers of the oral cavity, pharynx, and larynx: modeling odds ratios in pooled case-control data.

Odds ratios for head and neck cancer increase with greater cigarette and alcohol use and lower body mass index (BMI; weight (kg)/height(2) (m(2))). Using data from the International Head and Neck Cancer Epidemiology Consortium, the authors conducted a formal analysis of BMI as a modifier of smoking- and alcohol-related effects. Analysis of never and current smokers included 6,333 cases, while analysis of never drinkers and consumers of < or =10 drinks/day included 8,452 cases. There were 8,000 or more controls, depending on the analysis. Odds ratios for all sites increased with lower BMI, greater smoking, and greater drinking. In polytomous regression, odds ratios for BMI (P = 0.65), smoking (P = 0.52), and drinking (P = 0.73) were homogeneous for oral cavity and pharyngeal cancers. Odds ratios for BMI and drinking were greater for oral cavity/pharyngeal cancer (P < 0.01), while smoking odds ratios were greater for laryngeal cancer (P < 0.01). Lower BMI enhanced smoking- and drinking-related odds ratios for oral cavity/pharyngeal cancer (P < 0.01), while BMI did not modify smoking and drinking odds ratios for laryngeal cancer. The increased odds ratios for all sites with low BMI may suggest related carcinogenic mechanisms; however, BMI modification of smoking and drinking odds ratios for cancer of the oral cavity/pharynx but not larynx cancer suggests additional factors specific to oral cavity/pharynx cancer.

The ghost of past species occurrence: improving species distribution models for presence-only data

1. Model-based approaches have been used increasingly in conservation biology over recent years. Species presence data used for predictive species distribution modelling are abundant in natural history collections, whereas reliable absence data are sparse, most notably for vagrant species such as butterflies and snakes. As predictive methods such as generalized linear models (GLM) require absence data, various strategies have been proposed to select pseudo-absence data. However, only a few studies exist that compare different approaches to generating these pseudo-absence data. 2. Natural history collection data are usually available for long periods of time (decades or even centuries), thus allowing historical considerations. However, this historical dimension has rarely been assessed in studies of species distribution, although there is great potential for understanding current patterns, i.e. the past is the key to the present. 3. We used GLM to model the distributions of three 'target' butterfly species, Melitaea didyma, Coenonympha tullia and Maculinea teleius, in Switzerland. We developed and compared four strategies for defining pools of pseudo-absence data and applied them to natural history collection data from the last 10, 30 and 100 years. Pools included: (i) sites without target species records; (ii) sites where butterfly species other than the target species were present; (iii) sites without butterfly species but with habitat characteristics similar to those required by the target species; and (iv) a combination of the second and third strategies. Models were evaluated and compared by the total deviance explained, the maximized Kappa and the area under the curve (AUC). 4. Among the four strategies, model performance was best for strategy 3. Contrary to expectations, strategy 2 resulted in even lower model performance compared with models with pseudo-absence data simulated totally at random (strategy 1). 5. Independent of the strategy model, performance was enhanced when sites with historical species presence data were not considered as pseudo-absence data. Therefore, the combination of strategy 3 with species records from the last 100 years achieved the highest model performance. 6. Synthesis and applications. The protection of suitable habitat for species survival or reintroduction in rapidly changing landscapes is a high priority among conservationists. Model-based approaches offer planning authorities the possibility of delimiting priority areas for species detection or habitat protection. The performance of these models can be enhanced by fitting them with pseudo-absence data relying on large archives of natural history collection species presence data rather than using randomly sampled pseudo-absence data.