Corticosteroid discontinuation, complete clinical response and remission in juvenile dermatomyositis.

OBJECTIVE: A North American registry of JDM patients was examined for frequency of and factors associated with corticosteroid discontinuation, complete clinical response and remission. METHODS: We evaluated probability of achieving final corticosteroid discontinuation, complete clinical response and remission in 307 JDM patients by Weibull time-to-event modelling; conditional probability of complete clinical response and remission using Bayesian network modelling; and significant predictors with multivariable Markov chain Monte-Carlo Weibull extension models. RESULTS: The probability of corticosteroid discontinuation was 56%, complete clinical response 38% and remission 30% by 60 months after initial treatment in 105 patients. The probability of remission was conditional on corticosteroid discontinuation and complete clinical response. Photosensitivity, contractures and a longer time to complete clinical response were predictive of the time to final corticosteroid discontinuation. Anti-MJ (NXP2) autoantibodies and a Northwest residential geoclimatic zone were predictive of shorter time to complete clinical response, while dysphonia, contractures, an increase in medications within 24 months and a longer time to corticosteroid discontinuation were associated with longer time to complete clinical response. Anti-p155/140 (TIF1) autoantibodies, an increase in medications within 12-24 months, or longer times to corticosteroid discontinuation and complete clinical response were associated with longer time to remission. CONCLUSION: JDM patients achieve favourable outcomes, including corticosteroid discontinuation, complete clinical response and remission, although timelines for these may be several years based on time-dependent analyses. These outcomes are inter-related and strong predictors of each other. Selected clinical features and myositis autoantibodies are additionally associated with these outcomes.

Comparative aquatic toxicity of the pyrethroid insecticide lambda-cyhalothrin and its resolved isomer gamma-cyhalothrin.

In this review we compare the sensitivity of a range of aquatic invertebrate and fish species to gamma-cyhalothrin (GCH), the insecticidally active enantiomer of the synthetic pyrethroid lambda-cyhalothrin (LCH), in single-species laboratory tests and outdoor multi-species ecosystem tests. Species sensitivity distribution curves for GCH gave median HC(5) values of 0.47 ng/L for invertebrates, and 23.7 ng/L for fish, while curves for LCH gave median HC(5) values of 1.05 ng/L and 40.9 ng/L for invertebrates and fish, respectively. A model ecosystem test with GCH gave a community-level no observed effect concentration (NOEC(community)) of 5 ng/L, while model ecosystem tests with LCH gave a NOEC(community) of 10 ng/L. These comparisons between GCH and LCH indicate that the single active enantiomer causes effects at approximately one-half the concentration at which the racemate causes similar effects.

Medications received by patients with juvenile dermatomyositis.

OBJECTIVE: Few controlled studies are available to guide treatment decisions in juvenile dermatomyositis (JDM). This study evaluated therapies received, changes of treatment over time, and factors associated with medication choices in JDM. METHODS: We performed a retrospective analysis of the number and type of therapies and duration of treatment for 320 patients with JDM enrolled in a North American registry. Kaplan-Meier and logistic regression analysis were used to assess the association of demographic and clinical features and autoantibodies with medication usage. RESULTS: High-dose oral prednisone was the primary therapy given to 99% of patients. 1997 was determined to be a threshold year for increasing usage of medications other than prednisone. The median time to half the initial oral prednisone dose was shorter in patients diagnosed after vs. before 1997 (10 vs. 19 months, P < 0.01). Patients received intravenous methylprednisolone (IVMP), methotrexate, intravenous immunoglobulin, antimalarial drugs, and combination therapy more frequently when diagnosed after 1997. IVMP was frequently received by patients with severe illness onset, anti-p155/140 (anti-TIF1) and anti-MJ (anti-NXP2) autoantibodies. Treatment with methotrexate was associated with older age at diagnosis and anti-MJ autoantibodies, while antimalarial therapy was associated with anti-p155/140 autoantibodies and mild onset severity. CONCLUSION: Oral prednisone has been the mainstay of therapy in JDM, and prednisone was reduced faster in patients diagnosed after 1997 when there was also an increase in other medications. Specific medications received by patients with JDM correlated with year and age at diagnosis, myositis autoantibodies, onset severity, and illness features.

Using Monte Carlo techniques to judge model prediction accuracy: validation of the pesticide root zone model 3.12.

Individuals from the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) Environmental Model Validation Task Force (FEMVTF) Statistics Committee periodically met to discuss the mechanism for conducting an uncertainty analysis of Version 3.12 of the pesticide root zone model (PRZM 3.12) and to identify those model input parameters that most contribute to model prediction error. This activity was part of a larger project evaluating PRZM 3.12. The goal of the uncertainty analysis was to compare site-specific model predictions and field measurements using the variability in each as a basis of comparison. Monte Carlo analysis was used as an integral tool for judging the model's ability to predict accurately. The model was judged on how well it predicts measured values, taking into account the uncertainty in the model predictions. Monte Carlo analysis provides the tool for inferring model prediction uncertainty. We argue that this is a fairer test of the model than a simple one-to-one comparison between predictions and measurements. Because models are known to be imperfect predictors prior to running the model, the inaccuracy in model predictions should be considered when models are judged for their predictive ability. Otherwise, complex models can easily fail a validation test. Few complex models, such as PRZM 3.12, would pass a typical model validation exercise. This paper describes the approaches to the validation of PRZM 3.12 used by the committee and discusses issues in sampling distribution selection and appropriate statistics for interpreting the model validation results.

Validation of pesticide root zone model 3.12: employing uncertainty analysis.

Computer models are being increasingly used to provide an efficient cost-effective means of evaluating the fate and behavior of chemicals in the environment. These models can be used in lieu of or in conjunction with field studies. Because of the increasing reliance on models for critical regulatory decision making, the need arose to assess the validity of regulatory models via an analysis of the correlation of model response estimates with measured data. In conjunction with the evaluation of the correlation of model response estimates and measured field data, a rigorous statistically based validation was also warranted. Because of the unique nature of the correlative exercise using modeled and measured data, standard statistical analyses, while informative, failed to encompass factors associated with the uncertainty of measured environmental fate data and potential model inputs. In an effort to evaluate this uncertainty, an initial sensitivity analysis was performed where key model input parameters for runoff and leaching simulations were identified. Once the sensitive input parameters were identified, a Monte Carlo-based preprocessor was developed whereby the sampling distributions of these parameters were used to propagate uncertainty in the input parameters into error in model predictions. Importantly, assumptions about parameter distributions for input into the Monte Carlo tool were made only after a formal detailed site-specific analysis of measured field data. Employing the functionality of the Crystal Ball Pro development environment, the pesticide root zone model (PRZM) 3.12 was run iteratively for 500 trials, and model output was collated and analyzed. The model predictions were considered reasonably accurate for most regulatory requirements, and the model prediction error was considered acceptable.

Development of a Monte Carlo sampling shell for the pesticide root zone model and its application by the Federal Insecticide, Fungicide, and Rodenticide Act Environmental Modeling Validation Task Force.

A user interface to the U.S. Environmental Protection Agency pesticide root zone model (PRZM) was constructed to allow Monte Carlo sampling of input parameter distributions. The interface was constructed employing the Visual Basic for Applications development environment, along with the functionality of the Crystal Ball Professional forecasting and risk analysis package. The tool has been utilized by the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) Environmental Model Validation Task Force to perform detailed statistical analyses of model input parameter uncertainty and the propagation of this uncertainty on the model outputs as well as comparisons of modeled and field-measured data.

Assessment of aquatic ecological risk and site-specific criteria of copper in San Francisco Bay, California, USA.

A new regression-based copper toxicity model was applied in a case study of San Francisco Bay, California, USA, to demonstrate its utility in estimating risk and site-specific water quality criteria. This was accomplished using probabilistic techniques and a simple model relating dissolved organic carbon (DOC) concentrations with the toxicity of dissolved copper to embryos of the most copper sensitive taxon (Mytilus) in the US Environmental Protection Agency's (USEPA) water quality criteria database. Similar probabilistic techniques were applied to data developed for San Francisco Bay using the USEPA's water-effect ratio (WER) methods for comparison with the DOC-based method. Based on 595 site- and date-specific DOC model observations at 26 sites in San Francisco Bay, none suggested risk of chronic toxicity. Safety factors (1/risk quotient) on average across all sites ranged from 2.4 to 9.1. Comparisons were made between 1) estimates of site-specific criteria made using the DOC method, 2) estimates of site-specific criteria made using the WER method, 3) USEPA national and California Toxics Rule criteria, and 4) region-specific criteria recommended for regulatory implementation by the Clean Estuary Partnership. The DOC- and WER-based methods indicated that copper criteria for San Francisco Bay could be increased above USEPA and California Toxics Rule criteria and will retain the level of protection (> or =97%) embodied in the USEPA copper saltwater water quality criteria. The DOC method overall was more conservative (i.e., implies the need for lower criteria in the Bay) than the WER method. The DOC method suggests that the region-specific criteria being recommended for regulatory implementation would be underprotective in some areas and yet could be increased and remain protective in other areas of San Francisco Bay.

Probability-based estimates of site-specific copper water quality criteria for the Chesapeake Bay, USA.

The object of this study was to estimate site- and region-specific dissolved copper criteria for a large embayment, the Chesapeake Bay, USA. The intent is to show the utility of 2 copper saltwater quality site-specific criteria estimation models and associated region-specific criteria selection methods. The criteria estimation models and selection methods are simple, efficient, and cost-effective tools for resource managers. The methods are proposed as potential substitutes for the US Environmental Protection Agency's water effect ratio methods. Dissolved organic carbon data and the copper criteria models were used to produce probability-based estimates of site-specific copper saltwater quality criteria. Site- and date-specific criteria estimations were made for 88 sites (n = 5,296) in the Chesapeake Bay. The average and range of estimated site-specific chronic dissolved copper criteria for the Chesapeake Bay were 7.5 and 5.3 to 16.9 microg Cu/L. The average and range of estimated site-specific acute dissolved copper criteria for the Chesapeake Bay were 11.7 and 8.3 to 26.4 microg Cu/L. The results suggest that applicable national and state copper criteria can increase in much of the Chesapeake Bay and remain protective. Virginia Department of Environmental Quality copper criteria near the mouth of the Chesapeake Bay, however, need to decrease to protect species of equal or greater sensitivity to that of the marine mussel, Mytilus sp.