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PubMed1989

Evaluation of a two-compartment Bayesian forecasting program for predicting vancomycin concentrations.

The application of a two-compartment Bayesian forecasting program for vancomycin was tested retrospectively in 45 adult patients with stable renal function. Serial blood samples from 25 of these patients were used to determine population-based parameter estimates. The predictive performance of the Bayesian program was assessed by using both non-steady-state and steady-state vancomycin concentrations as feedback information. Overall, the program tended to underpredict peak and trough steady-state vancomycin serum concentrations. A larger mean prediction error (ME) was seen when non-steady-state feedback serum concentrations were used compared with using population-based parameter estimates (no feedback). In contrast, a marked improvement in ME (peaks: -1.03 versus -2.61; troughs: -1.60 versus -2.07) was seen when steady-state feedback serum concentrations were used compared with no feedback data. Precision improved when either feedback serum concentrations were used to predict steady-state peak and trough vancomycin concentrations. The results from this clinical evaluation demonstrate that the initial pharmacokinetic parameter estimates for a two-compartment Bayesian model provided accurate prediction of steady-state vancomycin concentrations. Prediction bias and precision were improved when steady-state vancomycin concentrations were used to determine individualized pharmacokinetic parameters.

Adult↗

PubMed1998

Evaluation of aminoglycoside pharmacokinetics in postpartum patients using Bayesian forecasting.

Many postpartum women have suboptimal serum concentrations after standard doses of aminoglycosides. The purpose of this study was to characterize the pharmacokinetics of aminoglycosides in postpartum patients through the use of Bayesian forecasting and to test the ability of these subpopulation parameters to predict actual aminoglycoside serum concentrations. In phase I, 28 postpartum patients who received empiric gentamicin therapy were identified and Bayesian subpopulation parameters generated. In phase II, additional gentamicin concentrations (peaks and troughs) were evaluated to test bias and precision of Bayesian subpopulation versus traditional estimates in predicting actual aminoglycoside serum concentrations. In phase I, 56 gentamicin serum concentrations in 28 patients, (age, 26 +/- 7 years; actual body weight [ABW], 84.3 +/- 18.4 kg; ideal body weight [IBW], 54.6 +/- 5.1 kg; dosing weight [DW], 66.3 +/- 9.4 kg; creatinine clearance [Clcr], 140.4 +/- 34.0 ml/min / 1.73 m2), were evaluated to calculate subpopulation pharmacokinetic parameters of volume of distribution (Vd) 0.29 +/- 0.07 l/kg (DW); elimination rate constant (ke) 0.29 +/- 0.05 h-1 and half-life (t1/2) 2.5 +/- 0.5 hours. In phase II, 50 gentamicin serum concentrations in 25 patients (age, 23 +/- 4 years; ABW 79.4 +/- 17.5 kg; IBW 55.0 +/- 7.3 kg; DW 64.8 +/- 9.6 kg; Clcr 139.7 +/- 29.3 ml/min/1.73 m2) were evaluated to calculate subpopulation pharmacokinetic parameters of Vd 0.30 +/- 0.04 l/kg (DW); ke 0.27 +/- 0.06 h-1; and t1/2 2.9 +/- 0.8 hours. Predictive performance tests (95% confidence intervals) demonstrate that subpopulation postpartum Bayesian parameters show greater precision for peak concentrations and less bias for trough concentrations than do traditional population estimates (p < 0.05). Definition of the Bayesian subpopulation parameters will allow us to dose aminoglycosides optimally in postpartum patients who have fragmented data.

Adult↗

PubMed1998

Evaluation of pharmacokinetic methods used to estimate caffeine clearance and comparison with a Bayesian forecasting method.

Simplified pharmacokinetic methods have been used to estimate caffeine clearance in subjects with liver disease. There is a need to have a reliable, easy to implement method for research and possible clinical use. This study evaluates the use of Bayesian pharmacokinetic forecasting techniques to estimate caffeine clearance and compares its performance to other published methods. Commonly used published methods include the two-concentration overnight salivary clearance method (Jost method) and a method that samples caffeine concentrations over a 4-hour time period (Nagel method). Both have been used in studies incorporating serial measurements of caffeine clearance to predict clinical outcomes in subjects with liver disease, but these approaches have not been proven useful. However, neither method has been formally evaluated for accuracy in estimating caffeine clearance in subjects with cirrhosis. The performance of the Jost, Nagel, and Bayesian methods was compared to a Gold Standard method that accurately measured caffeine clearance in healthy subjects and subjects with cirrhosis using an intravenous infusion of stable isotope-labeled caffeine. The Bayesian method, even when only one measured concentration of caffeine was used, was more accurate, better correlated to the Gold Standard method, and had less intraindividual variation than the two previously published methods. Before the idea of using serial measurements of caffeine clearance for clinical usefulness is rejected, a reevaluation using methods of estimating caffeine clearance that are more accurate than previous paradigms is needed.

Bayes Theorem↗

PubMed2002

Potential benefit of Bayesian forecasting for therapeutic drug monitoring in neonates.

Therapeutic drug monitoring in neonate has been hampered by invasiveness of blood samplings raising ethical problems. A methodologic approach has been developped in adults and in children that is still unsufficiently developped in neonates, the Bayesian forecasting of drug plasma concentration. This method is particularly attractive in neonates using a few blood samples from an individual patient and more informations from a prior patient sample representative of the population the individual patient belongs to. The present article aims at reviewing the different procedures and methods to minimize invasiveness during therapeutic drug monitoring in neonate and at reviewing the methods for improving the quality of different dose adjustments using a Bayesian approach.

Bayes Theorem↗

PubMed2003

Bayesian forecasting of oral cyclosporin pharmacokinetics in stable lung transplant recipients with and without cystic fibrosis.

The aims of the current study were (1) to study Neoral pharmacokinetics (PK) in stable lung recipients with or without cystic fibrosis (CF), (2) to compare Neoral PK between these two groups, and (3) to design Bayesian estimators for PK forecasting and dose adjustment in these patients using a limited number of blood samples. The individual PK of 19 adult lung transplant recipients, 9 subjects with CF and 10 subjects without CF, were retrospectively studied. Three profiles obtained within 5 days were available for each patient. A PK model combining a gamma distribution to describe the absorption profile and a two-compartment model were applied. Different exposure indices were estimated using nonlinear regression and Bayesian estimation. The PK model developed reliably described the individual PK of Neoral in lung transplant patients with and without CF, and the values of the first and second half-lives were different in these two populations (lambda(1) = 4.14 +/- 3.01 vs. 2.16 +/- 1.75 h(-1); P < 0.01; lambda(2) = 0.36 +/- 0.11 vs. 0.49 +/- 0.12 h(-1); P < 0.01), while the mean absorption time and standard deviation of absorption time tended to be less in patients with cystic fibrosis (P < 0.1). Also, the patients with CF required higher doses than those without CF to achieve similar drug exposure. Consequently, population modeling was performed in CF and non-CF patients separately. Bayesian estimation allowed accurate prediction of AUC(0-12), AUC(0-4), C(max), and T(max) using three blood samples collected at T0h, T1h, and T3h in both groups. This study demonstrated the applicability and good performance of the PK model previously developed for oral cyclosporin and of the MAP Bayesian estimation of cyclosporin systemic exposure in CF and non-CF patients. Moreover, it is the first to propose a monitoring tool specifically designed for cyclosporin monitoring in patients with CF.

Administration, Oral↗

PubMed2003

Bayesian forecasting and prediction of tacrolimus concentrations in pediatric liver and adult renal transplant recipients.

AIM: To test the predictive capacity of two recently derived population pharmacokinetic models and the usefulness of Bayesian forecasting to predict tacrolimus blood concentrations in pediatric liver and adult kidney transplant recipients. MATERIALS AND METHODS: New databases were added to the Abbottbase PKS (Bayesian dosage prediction) program to incorporate the population pharmacokinetic models developed for tacrolimus. Two independent populations of transplant recipients were used to predict tacrolimus trough concentrations. Pharmacokinetic, demographic, and covariate data were collected from patient records. Different time weighting factors were tested (1, 1.005, 1.01) and the influence of excluding data collected in the first 5 days post-transplant examined. Concentrations were predicted until the 10th tacrolimus measurement. Actual tacrolimus concentrations were compared with those predicted by the PKS program and bias and precision determined. RESULTS: Tacrolimus concentrations predicted by the PKS program were, on average, unbiased for the pediatric liver population, but were over-predicted (9%) for the adult renal population. In both populations predictions were not precise (imprecision ranged from 39 to 50%). CONCLUSIONS: Due to the imprecision seen in this study, these models could not be used in clinical practice in the immediate post-transplant period. Poor precision may be due to reliance on routine drug monitoring data alone, difficulties with expression of covariates in continuous modeling relationships in the PKS program, lack of accurate quantitative measures of liver function, or large, random intraindividual variability in the bioavailability of tacrolimus.

Adolescent↗

PubMed1998

Forecasting generalized epileptic seizures from the EEG signal by wavelet analysis and dynamic unsupervised fuzzy clustering.

Dynamic state recognition and event-prediction are fundamental tasks in biomedical signal processing. We present a new, electroencephalogram (EEG)-based, brain-state identification method which could form the basis for forecasting a generalized epileptic seizure. The method relies on the existence in the EEG of a preseizure state, with extractable unique features, a priori undefined. We exposed 25 rats to hyperbaric oxygen until the appearance of a generalized EEG seizure. EEG segments from the preexposure, early exposure, and the period up to and including the seizure were processed by the fast wavelet transform. Features extracted from the wavelet coefficients were imputed to the unsupervised optimal fuzzy clustering (UOFC) algorithm. The UOFC is useful for classifying similar discontinuous temporal patterns in the semistationary EEG to a set of clusters which may represent brain-states. The unsupervised selection of the number of cluster overcomes the a priori unknown and variable number of states. The usually vague brain state transitions are naturally treated by assigning each temporal pattern to one or more fuzzy clusters. The classification succeeded in identifying several, behavior-backed, EEG states such as sleep, resting, alert and active wakefulness, as well as the seizure. In 16 instances a preseizure state, lasting between 0.7 and 4 min was defined. Considerable individual variability in the number and characteristics of the clusters may postpone the realization of an early universal epilepsy warning. University may not be crucial if using a dynamic version of the UOFC which has been taught the individual's normal vocabulary of EEG states and can be expected to detect unspecified new states.

Algorithms↗

PubMed2002

Forecasting the performance status of head and neck cancer patient treatment by an interval arithmetic pruned perceptron.

The integration of chemotherapy and radiotherapy for the treatment of advanced head and neck cancer is still a matter of clinical investigation. An important limitation is that the concomitant administration of chemotherapy and radiotherapy still induces severe toxicity. In this paper, a simple artificial neural network is used to predict, on the basis of biological and clinical data, if the cumulative toxicity of the combined chemo-radiation treatment itself would be tolerated. The resulting method, tested on clinical data from a phase II trial, proved to be able to forecast which patients will tolerate a combined chemo-radiotherapeutic approach. This result should open a new perspective in the clinical approach, by supplying a potential predictive indicator for toxicity.

Antineoplastic Agents↗

PubMed1989

Comparison of Sawchuk-Zaske and Bayesian forecasting for aminoglycosides in seriously ill patients.

1. Individual pharmacokinetic parameters and predicted steady-state serum concentrations of aminoglycosides were calculated by Sawchuck-Zaske (SZ) and Bayesian methods. 2. Predicted concentrations were compared with observed steady-state concentrations for 36 seriously ill patients with systemic infections. Four aminoglycoside concentrations were used for the SZ method. Differing numbers of serum aminoglycoside samples were used in the Bayesian parameter estimation: one sample Bayesian used one post-infusion concentration, two sample Bayesian used a trough plus one post-infusion concentrations and four sample Bayesian used a trough plus three post-infusion concentrations. 3. 79% of the SZ predictions were with +/- 2 mg l-1 of the observed peak concentrations, and 72% of the two sample Bayesian predictions were within the same range. 82% of SZ and the two sample Bayesian predictions were within +/- 1 mg l-1 of the observed trough concentrations. 4. A confidence interval comparison of estimated pharmacokinetic parameters and precision for the predicted concentrations showed no important differences between the SZ and the two sample Bayesian. The four sample Bayesian was the most precise method. 5. We conclude that the Bayesian forecasting method utilizing a trough plus one post-infusion concentrations is as useful as the SZ method which requires three to four serum concentrations in individualizing aminoglycoside therapy for seriously ill patients.

Adolescent↗

PubMed2004

Seismic anisotropy beneath Ruapehu volcano: a possible eruption forecasting tool.

The orientation of crustal seismic anisotropy changed at least twice by up to 80 degrees because of volcanic eruptions at Ruapehu Volcano, New Zealand. These changes provide the basis for a new monitoring technique and possibly for future midterm eruption forecasting at volcanoes. The fast anisotropic direction was measured during three seismometer deployments in 1994, 1998, and 2002, providing an in situ measurement of the stress in the crust under the volcano. The stress direction changed because of an eruption in 1995-1996. Our 2002 measurements revealed a partial return to the pre-eruption stress state. These changes were probably caused by repeated filling and depressurizing of a magmatic dike system.

Journal Article↗

PubMed1985

Forecasting cephalosporin and monobactam antibiotic half-lives in humans from data collected in laboratory animals.

The postdistribution half-lives of 10 cephalosporin and 2 monobactam antibiotics in humans were predicted from data obtained in other mammals. This forecasting was accomplished with the allometric equation t1/2 = aWb, where a is the y intercept and b is the slope obtained from the log-log plot of antibiotic half-life (t1/2) versus body weight (W). Dimensionless similarity criteria were used to produce a biological clock for ceftizoxime elimination. The creation of the biological clock, which measured physiologic time (heartbeats) rather than chronologic time (minutes), demonstrated that ceftizoxime half-life was identical in five mammals. This methodology will contribute to infectious disease research through a greater understanding of pharmacokinetic scaling in mammals.

Animals↗

PubMed1993

Effect of obesity on vancomycin pharmacokinetic parameters as determined by using a Bayesian forecasting technique.

Few data exist concerning the effect of obesity on the pharmacokinetic parameters of vancomycin. The purpose of this investigation was to assess the effect of obesity on vancomycin pharmacokinetic parameters in 95 nonobese and 135 obese adult patients (age range, 18 to 92 years) receiving vancomycin. All subjects had normal renal function as defined by a creatinine concentration in serum of < or = 1.5 mg/dl (mean estimated creatinine clearance +/- 1 standard deviation, 76 +/- 34; range, 23 to 215 ml/min). Vancomycin concentrations in serum were determined by the fluorescence polarization immunoassay. All data for vancomycin concentration in serum versus time for each course of therapy were fitted by using a two-compartment Bayesian forecasting program. Subjects were stratified into nine groups on the basis of the percent difference between actual body weight (ABW) and lean body weight (LBW) (> -10%, -10 to 0%, > 0 to 10%, > 10 to 20%, > 20 to 30%, > 30 to 40%, > 40 to 50%, > 50 to 60%, > 60%). Analysis of variance with post hoc Scheffe's testing revealed that statistically significant differences occurred in terminal disposition half-life (t1/2 beta) between the extremes of modestly obese (group 4) and morbidly obese (group 9, P < 0.05) patients. Similar analysis with distribution volume (V) identified significant differences in patients at or near their LBW (groups 2 to 4) and patients who were morbidly obese (groups 8 and 9, P < 0.05). Multiple regression models for the pharmacokinetic parameters V, t1/2beta, and vancomycin total body clearance were developed to assess the joint predictive power of LBW, ABW, and percent over LBW, controlling for the effects of age, initial creatinine concentration in serum, initial creatinine clearance, and gender. In the final model for V, both ABW and percent over LBW were independent and significant predictors. For total body clearance, only ABW was significant and predictive. Percent over LBW was a significant and independent predictor of t1/2beta. LBW is not predictive of these pharmacokinetic parameters and should not be used for initial dosing. On the basis of these data, ABW appears to be superior to LBW for calculating initial dose requirements for vancomycin.

Adolescent↗

PubMed1978

Forecasting the incidence of parasitic gastroenteritis in lambs in England and Wales.

An empirical method for forecasting the incidence of parasitic gastroenteritis in sheep in England and Wales is described. The level of disease in lambs in late summer depends on the date soil moisture returns to field capacity (the autumn return date) in the previous year together with rainfall from May to July in the current year. The importance of a late autumn return date and winter weather in relation to disease in stock at other times of the year is also discussed.

Animals↗

PubMed2004

A novel approach for short-term load forecasting using support vector machines.

A support vector machine (SVM) modeling approach for short-term load forecasting is proposed. The SVM learning scheme is applied to the power load data, forcing the network to learn the inherent internal temporal property of power load sequence. We also study the performance when other related input variables such as temperature and humidity are considered. The performance of our proposed SVM modeling approach has been tested and compared with feed-forward neural network and cosine radial basis function neural network approaches. Numerical results show that the SVM approach yields better generalization capability and lower prediction error compared to those neural network approaches.

Artificial Intelligence↗

PubMed1991

Forecasting correct sodium balance in hemodiafiltration procedures involving infusions.

Four patients, stable on acetate hemodialysis (AHD), were switched to acetate-free biofiltration (AFB) which differs from AHD and bicarbonate hemodialysis (BHD) in that the dialysate contains no buffer, which is given intravenously as a hypertonic (1/6 M) Na bicarbonate solution. Within the 1st month the patients developed thirst and hypertension attributed to a positive Na balance. The aim of this investigation was to check this (1) by a study based on the predictable changes induced in the body compartments of 13 patients by the infusion and ultrafiltration (UF) of a hypertonic solution and (2) by direct determination and calculation of 28 Na mass balances in BHD and AFB. The theoretical model indicated that infusion of 4.87 liters of a 166.7 mEq/l Na bicarbonate solution and UF of the same amount caused a positive balance of 233 mosm of Na. The Na mass balances showed a relationship between Na transmembrane gradient and loss or gain of Na in both methods (p less than 0.0001). The slopes of the regression lines were not significantly different but there was a highly significant difference between the y axis intercepts (p less than 0.0001), which indicates that the same Na transmembrane gradient that gives no net change of Na in BHD, induces a net gain of 240 mosm (120 mEq of Na) in AFB and that to obtain the same Na balance dialysate Na should be reduced by about 8 mEq/l in AFB. These data are the same as the theoretical forecast which could be extended to all hemodiafiltration methods in which solutions of any tonicity have to be infused, in order to correctly predict the Na balance.

Body Fluid Compartments↗

PubMed1998

Preliminary report of detecting microembolic signals in transcranial Doppler time series with nonlinear forecasting.

BACKGROUND AND PURPOSE: Most algorithms used for automatic detection of microembolic signals (MES) are based on power spectral analysis of the Doppler shift. However, controversies exist as to whether these algorithms can replace the human expert. Therefore, a different algorithm was applied that takes advantage of the periodicity of the MES. This so-called nonlinear forecasting (NLF) is able to detect periodicity in a time series, and it is hypothesized that this technique has the potential to detect MES. Moreover, because of the lack of prominent periodicity in both the normal Doppler signals (DS) and movement artifacts (MA), the NLF has a potential to differentiate MES from normal blood flow variations and MA. METHODS: Twenty single MES and 100 MA were selected by 2 human experts. NLF was applied to MES and MA and compared with 200 randomly chosen DS. NLF resulted in a so-called prediction value that ranges from + 1 in signals with prominent periodicity to 0 in signals that lack periodicity. RESULTS: NLF revealed that MES are more predictable than the normal Doppler signals (prediction [MES]=0.829+/-0.084 versus prediction [DS]= -0.060+/-0.228; P<0.0001). Moreover, MES are more predictable than the MA (prediction [MA]=-0.034+/-0.223; P<0.0001). No difference in prediction could be found between DS and MA. CONCLUSIONS: This preliminary report shows that MES can be separated from DS and MA by NLF. Research is needed as to whether this technology can be further developed for automatic detection of MES.

Artifacts↗

PubMed1998

Calcitonin is a progesterone-regulated marker that forecasts the receptive state of endometrium during implantation.

Previous studies established that in the rat, the uterus can accept a developing blastocyst for implantation only during a limited period of time on day 5 of gestation, termed the receptive phase. Our previous studies showed that the expression of calcitonin, a peptide hormone that regulates calcium homeostasis, is induced in rat uterus between days 3-5 of gestation and is switched off once the implantation process has progressed to day 6. In the present study, we analyze in detail how the expression of calcitonin messenger RNA (mRNA) in the uterus is regulated by the steroid hormones progesterone and estrogen and explore the possibility that calcitonin may serve as a potential marker of uterine receptivity. We demonstrate by in situ hybridization that calcitonin mRNA is synthesized specifically in the glandular epithelial cells between days 3-5 of pregnancy. Interestingly, calcitonin synthesis is also induced in these cells during pseudopregnancy, indicating that this peptide hormone is produced in the endometrium in response to maternal, rather than embryonic, signals. We also demonstrate that calcitonin mRNA expression during pseudopregnancy, like that in normal pregnancy, is under progesterone regulation. We further examined the steroid hormone regulation of uterine calcitonin expression in a delayed implantation model. In pregnant rats in which implantation is blocked upon removal of both ovaries on day 4 of gestation, continued administration of progesterone sustains calcitonin expression in the uterus for several days in the absence of estrogen. Administration of estrogen, which allows delayed implantation, also rapidly reduces calcitonin expression, indicating a role for this steroid hormone in turning off calcitonin gene expression. In gene transfection studies, expression of the progesterone receptor B isoform in cultured endometrial cells induces RNA synthesis from a reporter gene containing a 1.3-kb calcitonin promoter fragment in a hormone-dependent manner. As expected, mifepristone-complexed progesterone receptor B isoform fails to activate the calcitonin promoter. Progesterone acting through its nuclear receptor therefore regulates the expression of the calcitonin gene at the level of transcription. Finally, using RIA we investigated whether calcitonin is secreted from its glandular site of synthesis at the time of implantation by analyzing uterine flushings obtained from pregnant rats. We report the detection of a significant amount of calcitonin in the luminal secretions collected on day 4 and a lower amount on day 5 of gestation, whereas similar samples collected from animals on either day 3 or 6 of gestation did not contain detectable amounts of this peptide hormone. A transient burst of calcitonin secretion into the uterine lumen therefore occurs immediately preceding implantation. Based on these results, we propose that calcitonin is a measurable marker that forecasts the receptive state of rat endometrium during blastocyst implantation.

Animals↗

PubMedDate not supplied

Pharmacy benefit forecast for a new interferon Beta-1a for the treatment of multiple sclerosis: development of a first-line decision tool for pharmacy-budget planning using administrative claims data.

OBJECTIVE: To estimate the incremental change in pharmacy per-member-permonth (PMPM) costs, according to various formulary designs, for a new interferon beta-1a product (IB1a2) using administrative claims data. METHODS: Cross-sectional sex- and age-specific disease prevalence and treatment rates for relapsing, remitting multiple sclerosis (RRMS) patients were measured using integrated medical and pharmacy claims data from a 500,000- member employer group in the southern United States. Migration to IB1a2 from other drugs in the class was based on market-share data for new and existing RRMS patients. Duration of therapy was estimated by analyzing claims for current RRMS therapies. Daily therapy cost was provided by the manufacturer of IB1a2, adjusted for migration from other therapies, and multiplied by estimated volume to predict incremental and total PMPM cost impact. Market-share estimates were used to develop a PMPM cost forecast for the next 2 years. PMPM cost estimates were calculated for preferred (copayment tier 2) and nonpreferred (copayment tier 3) formulary designs with and without prior authorization (PA). One-way sensitivity analysis was performed to assess the influence of product pricing, duration of therapy, and other market factors. RESULTS: Annual incremental PMPM change was $0.047 for the scenario of third copayment tier with PA. The incremental change was greatest for those aged 55 to 65 years ($0.056 PMPM) and did not vary greatly by benefit design. Duration of therapy had the greatest impact on the PMPM estimate across benefit designs. CONCLUSION: IB1a2 will not cause a significant change in managed care pharmacy budgets under a variety of formulary conditions, according to this crosssectional analysis of current care-seeking behavior by RRMS patients. Economic impact may differ if IB1a2 expands RRMS patients. treatment-seeking behavior.

Adjuvants, Immunologic↗