The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.

Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative of lung or liver toxicity in rodents, or of breast cancer, multiple myeloma or neuroblastoma in humans. In total, >30,000 models were built using many combinations of analytical methods. The teams generated predictive models without knowing the biological meaning of some of the endpoints and, to mimic clinical reality, tested the models on data that had not been used for training. We found that model performance depended largely on the endpoint and team proficiency and that different approaches generated models of similar performance. The conclusions and recommendations from MAQC-II should be useful for regulatory agencies, study committees and independent investigators that evaluate methods for global gene expression analysis.

Neuronal in vitro models for the estimation of acute systemic toxicity.

The objective of the EU funded integrated project "ACuteTox" is to develop a strategy in which general cytotoxicity, together with organ-specific endpoints and biokinetic features, are taken into consideration in the in vitro prediction of oral acute systemic toxicity. With regard to the nervous system, the effects of 23 reference chemicals were tested with approximately 50 endpoints, using a neuronal cell line, primary neuronal cell cultures, brain slices and aggregated brain cell cultures. Comparison of the in vitro neurotoxicity data with general cytotoxicity data generated in a non-neuronal cell line and with in vivo data such as acute human lethal blood concentration, revealed that GABA(A) receptor function, acetylcholine esterase activity, cell membrane potential, glucose uptake, total RNA expression and altered gene expression of NF-H, GFAP, MBP, HSP32 and caspase-3 were the best endpoints to use for further testing with 36 additional chemicals. The results of the second analysis showed that no single neuronal endpoint could give a perfect improvement in the in vitro-in vivo correlation, indicating that several specific endpoints need to be analysed and combined with biokinetic data to obtain the best correlation with in vivo acute toxicity.

Estimation de la fonction rénale par l'equation MDRD: intérêt et limites pour l'adaptation des doses de médicaments [Renal function estimation by MDRD equation: interest and limitations for drug dosing].

The MDRD (Modification of diet in renal disease) equation enables glomerular filtration rate (GFR) estimation from serum creatinine only. Thus, the laboratory can report an estimated GFR (eGFR) with each serum creatinine assessment, increasing therefore the recognition of renal failure. Predictive performance of MDRD equation is better for GFR < 60 ml/min/1,73 m2. A normal or near-normal renal function is often underestimated by this equation. Overall, MDRD provides more reliable estimations of renal function than the Cockcroft-Gault (C-G) formula, but both lack precision. MDRD is not superior to C-G for drug dosing. Being adjusted to 1,73 m2, MDRD eGFR has to be back adjusted to the patient's body surface area for drug dosing. Besides, C-G has the advantage of a greater simplicity and a longer use.

Dummy run and conformity indices in the ongoing EORTC low-grade glioma trial 22033-26033: First evaluation of quality of radiotherapy planning.

PURPOSE: Early assessment of radiotherapy (RT) quality in the ongoing EORTC trial comparing primary temozolomide versus RT in low-grade gliomas. MATERIALS AND METHODS: RT plans provided for dummy cases were evaluated and compared against expert plans. We analysed: (1) tumour and organs-at-risk delineation, (2) geometric and dosimetric characteristics, (3) planning parameters, compliance with dose prescription and Dmax for OAR (4) indices: RTOG conformity index (CI), coverage factor (CF), tissue protection factor (PF); conformity number (CN = PF x CF); dose homogeneity in PTV (U). RESULTS: Forty-one RT plans were evaluated. Only two (5%) centres were requested to repeat CTV-PTV delineations. Three (7%) plans had a significant under-dosage and dose homogeneity in one deviated > 10%. Dose distribution was good with mean values of 1.5, 1, 0.68, and 0.68 (ideal values = 1) for CI, CF, PF, and CN, respectively. CI and CN strongly correlated with PF and they correlated with PTV. Planning with more beams seems to increase PTV(Dmin), improving CF. U correlated with PTV(Dmax). CONCLUSION: Preliminary results of the dummy run procedure indicate that most centres conformed to protocol requirements. To quantify plan quality we recommend systematic calculation of U and either CI or CN, both of which measure the amount of irradiated normal brain tissue.

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Adaptation au codage CIM-10 de 15 indicateurs de la sécurité des patients proposés par l'Agence étasunienne pour la recherche et la qualité des soins de santé (AHRQ) [ICD-10 adaptation of 15 Agency for Healthcare Research and Quality patient safety indicators].

BACKGROUND: In the United States, the Agency for Healthcare Research and Quality (AHRQ) has developed 20 Patient Safety Indicators (PSIs) to measure the occurrence of hospital adverse events from medico-administrative data coded according to the ninth revision of the international classification of disease (ICD-9-CM). The adaptation of these PSIs to the WHO version of ICD-10 was carried out by an international consortium. METHODS: Two independent teams transcoded ICD-9-CM diagnosis codes proposed by the AHRQ into ICD-10-WHO. Using a Delphi process, experts from six countries evaluated each code independently, stating whether it was "included", "excluded" or "uncertain". During a two-day meeting, the experts then discussed the codes that had not obtained a consensus, and the additional codes proposed. RESULTS: Fifteen PSIs were adapted. Among the 2569 proposed diagnosis codes, 1775 were unanimously adopted straightaway. The 794 remaining codes and 2541 additional codes were discussed. Three documents were prepared: (1) a list of ICD-10-WHO codes for the 15 adapted PSIs; (2) recommendations to the AHRQ for the improvement of the nosological frame and the coding of PSI with ICD-9-CM; (3) recommendations to the WHO to improve ICD-10. CONCLUSIONS: This work allows international comparisons of PSIs among the countries using ICD-10. Nevertheless, these PSIs must still be evaluated further before being broadly used.

Quality of Web-based information on obsessive compulsive disorder.

BACKGROUND: The Internet is increasingly used as a source of information for mental health issues. The burden of obsessive compulsive disorder (OCD) may lead persons with diagnosed or undiagnosed OCD, and their relatives, to search for good quality information on the Web. This study aimed to evaluate the quality of Web-based information on English-language sites dealing with OCD and to compare the quality of websites found through a general and a medically specialized search engine. METHODS: Keywords related to OCD were entered into Google and OmniMedicalSearch. Websites were assessed on the basis of accountability, interactivity, readability, and content quality. The "Health on the Net" (HON) quality label and the Brief DISCERN scale score were used as possible content quality indicators. Of the 235 links identified, 53 websites were analyzed. RESULTS: The content quality of the OCD websites examined was relatively good. The use of a specialized search engine did not offer an advantage in finding websites with better content quality. A score ≥16 on the Brief DISCERN scale is associated with better content quality. CONCLUSION: This study shows the acceptability of the content quality of OCD websites. There is no advantage in searching for information with a specialized search engine rather than a general one. Practical implications: The Internet offers a number of high quality OCD websites. It remains critical, however, to have a provider-patient talk about the information found on the Web.

Building energy saving techniques and indoor air quality : a dilemma

In European countries and North America, people spend 80 to 90% of time inside buildings and thus breathe indoor air. In Switzerland, special attention has been devoted to the 16 stations of the national network of observation of atmospheric pollutants (NABEL). The results indicate a reduction in outdoor pollution over the last ten years. With such a decrease in pollution over these ten years the question becomes: how can we explain an increase of diseases? Indoor pollution can be the cause. Indoor contaminants that may create indoor air quality (IAQ) problems come from a variety of sources. These can include inadequate ventilation, temperature and humidity dysfunction, and volatile organic compounds (VOCs). The health effects from these contaminants are varied and can range from discomfort, irritation and respiratory diseases to cancer. Among such contaminants, environmental tobacco smoke (ETS) could be considered the most important in terms of both health effects and engineering controls of ventilation. To perform indoor pollution monitoring, several selected ETS tracers can be used including carbon monoxide (CO), carbon dioxide (CO2), respirable particles (RSP), condensate, nicotine, polycyclic aromatic hydrocarbons (PAHs), nitrosamines, etc. In this paper, some examples are presented of IAQ problems that have occurred following the renewal of buildings and energy saving concerns. Using industrial hygiene sampling techniques and focussing on selected priority pollutants used as tracers, various problems have been identified and solutions proposed. [Author]

Adaptively weighted maximum likelihood estimation of discrete distributions

SummaryDiscrete data arise in various research fields, typically when the observations are count data.I propose a robust and efficient parametric procedure for estimation of discrete distributions. The estimation is done in two phases. First, a very robust, but possibly inefficient, estimate of the model parameters is computed and used to indentify outliers. Then the outliers are either removed from the sample or given low weights, and a weighted maximum likelihood estimate (WML) is computed.The weights are determined via an adaptive process such that if the data follow the model, then asymptotically no observation is downweighted.I prove that the final estimator inherits the breakdown point of the initial one, and that its influence function at the model is the same as the influence function of the maximum likelihood estimator, which strongly suggests that it is asymptotically fully efficient.The initial estimator is a minimum disparity estimator (MDE). MDEs can be shown to have full asymptotic efficiency, and some MDEs have very high breakdown points and very low bias under contamination. Several initial estimators are considered, and the performances of the WMLs based on each of them are studied.It results that in a great variety of situations the WML substantially improves the initial estimator, both in terms of finite sample mean square error and in terms of bias under contamination. Besides, the performances of the WML are rather stable under a change of the MDE even if the MDEs have very different behaviors.Two examples of application of the WML to real data are considered. In both of them, the necessity for a robust estimator is clear: the maximum likelihood estimator is badly corrupted by the presence of a few outliers.This procedure is particularly natural in the discrete distribution setting, but could be extended to the continuous case, for which a possible procedure is sketched.RésuméLes données discrètes sont présentes dans différents domaines de recherche, en particulier lorsque les observations sont des comptages.Je propose une méthode paramétrique robuste et efficace pour l'estimation de distributions discrètes. L'estimation est faite en deux phases. Tout d'abord, un estimateur très robuste des paramètres du modèle est calculé, et utilisé pour la détection des données aberrantes (outliers). Cet estimateur n'est pas nécessairement efficace. Ensuite, soit les outliers sont retirés de l'échantillon, soit des faibles poids leur sont attribués, et un estimateur du maximum de vraisemblance pondéré (WML) est calculé.Les poids sont déterminés via un processus adaptif, tel qu'asymptotiquement, si les données suivent le modèle, aucune observation n'est dépondérée.Je prouve que le point de rupture de l'estimateur final est au moins aussi élevé que celui de l'estimateur initial, et que sa fonction d'influence au modèle est la même que celle du maximum de vraisemblance, ce qui suggère que cet estimateur est pleinement efficace asymptotiquement.L'estimateur initial est un estimateur de disparité minimale (MDE). Les MDE sont asymptotiquement pleinement efficaces, et certains d'entre eux ont un point de rupture très élevé et un très faible biais sous contamination. J'étudie les performances du WML basé sur différents MDEs.Le résultat est que dans une grande variété de situations le WML améliore largement les performances de l'estimateur initial, autant en terme du carré moyen de l'erreur que du biais sous contamination. De plus, les performances du WML restent assez stables lorsqu'on change l'estimateur initial, même si les différents MDEs ont des comportements très différents.Je considère deux exemples d'application du WML à des données réelles, où la nécessité d'un estimateur robuste est manifeste : l'estimateur du maximum de vraisemblance est fortement corrompu par la présence de quelques outliers.La méthode proposée est particulièrement naturelle dans le cadre des distributions discrètes, mais pourrait être étendue au cas continu.

Canakinumab relieves symptoms of acute flares and improves health-related quality of life in patients with difficult-to-treat Gouty Arthritis by suppressing inflammation: results of a randomized, dose-ranging study.

INTRODUCTION: We report the impact of canakinumab, a fully human anti-interleukin-1β monoclonal antibody, on inflammation and health-related quality of life (HRQoL) in patients with difficult-to-treat Gouty Arthritis. METHODS: In this eight-week, single-blind, double-dummy, dose-ranging study, patients with acute Gouty Arthritis flares who were unresponsive or intolerant to--or had contraindications for--non-steroidal anti-inflammatory drugs and/or colchicine were randomized to receive a single subcutaneous dose of canakinumab (10, 25, 50, 90, or 150 mg) (N = 143) or an intramuscular dose of triamcinolone acetonide 40 mg (N = 57). Patients assessed pain using a Likert scale, physicians assessed clinical signs of joint inflammation, and HRQoL was measured using the 36-item Short-Form Health Survey (SF-36) (acute version). RESULTS: At baseline, 98% of patients were suffering from moderate-to-extreme pain. The percentage of patients with no or mild pain was numerically greater in most canakinumab groups compared with triamcinolone acetonide from 24 to 72 hours post-dose; the difference was statistically significant for canakinumab 150 mg at these time points (P < 0.05). Treatment with canakinumab 150 mg was associated with statistically significant lower Likert scores for tenderness (odds ratio (OR), 3.2; 95% confidence interval (CI), 1.27 to 7.89; P = 0.014) and swelling (OR, 2.7; 95% CI, 1.09 to 6.50, P = 0.032) at 72 hours compared with triamcinolone acetonide. Median C-reactive protein and serum amyloid A levels were normalized by seven days post-dose in most canakinumab groups, but remained elevated in the triamcinolone acetonide group. Improvements in physical health were observed at seven days post-dose in all treatment groups; increases in scores were highest for canakinumab 150 mg. In this group, the mean SF-36 physical component summary score increased by 12.0 points from baseline to 48.3 at seven days post-dose. SF-36 scores for physical functioning and bodily pain for the canakinumab 150 mg group approached those for the US general population by seven days post-dose and reached norm values by eight weeks post-dose. CONCLUSIONS: Canakinumab 150 mg provided significantly greater and more rapid reduction in pain and signs and symptoms of inflammation compared with triamcinolone acetonide 40 mg. Improvements in HRQoL were seen in both treatment groups with a faster onset with canakinumab 150 mg compared with triamcinolone acetonide 40 mg. TRIAL REGISTRATION: clinicaltrials.gov: NCT00798369.