906 resultados para ONCOLOGIC RISKS


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Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukemia (CML) and gastrointestinal stromal tumor (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P-glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualization. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after the latest dose, were measured in 59 patients receiving Glivec at diverse regimens, using a validated HPLC-UV method developed for this study. The results were analyzed by non-linear mixed effect modeling (NONMEM). A one-compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. At present, only the MDR1 polymorphism has been assessed and seems to affect the pharmacokinetic parameters of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40 %) and distribution volume (71 %). Together with intra-patient variability (34 %), this translates into an 8-fold width of the 90 %-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring program for imatinib. It may help to individualize the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

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The anticancer drug imatinib has transformed the treatment and prognosis of chronic myeloid leukemia and gastrointestinal stromal tumor. However, the treatment must be taken indefinitely and is not devoid of inconveniences and toxicity. Moreover, resistance or escape from disease control are occurring. Considering the large interindividual differences in the function of the enzymatic and transport systems involved in imatinib disposition, exposure to this drug can be expected to vary widely among patients. This book describes an observational clinical trial aiming at exploring the influence of these covariates on imatinib pharmacokinetics and assessing the interindividual variability of the pharmacokinetic parameters of the drug. A large interindividual variability was observed, together with some preliminary concentration-effect relationships. These elements are arguments to further investigate the potential benefit of a therapeutic drug monitoring program to optimize the use of imatinib in patients. Such results should be especially useful to clinical oncologists or scientists involved in clinical oncology research.

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The written report (or its electronic counterpart) is the primary mode of communication between the physician interpreting an imaging study and the referring physician. The content of this report not only influences patient management and clinical outcomes but also serves as legal documentation of services provided and can be used to justify medical necessity, billing accuracy, and regulatory compliance. Generating a high-quality PET/CT report is perhaps more challenging than generating a report for other imaging studies because of the complexity of this hybrid imaging modality. This article discusses the essential elements of a concise and complete oncologic (18)F-FDG PET/CT report and illustrates these elements through examples taken from routine clinical practice.

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We show that a simple mixing idea allows one to establish a number of explicit formulas for ruin probabilities and related quantities in collective risk models with dependence among claim sizes and among claim inter-occurrence times. Examples include compound Poisson risk models with completely monotone marginal claim size distributions that are dependent according to Archimedean survival copulas as well as renewal risk models with dependent inter-occurrence times.

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We present a standard model of financial innovation, in which intermediaries engineer securities with cash flows that investors seek, but modify two assumptions. First, investors (and possibly intermediaries) neglect certain unlikely risks. Second, investors demand securities with safe cash flows. Financial intermediaries cater to these preferences and beliefs by engineering securities perceived to be safe but exposed to neglected risks. Because the risks are neglected, security issuance is excessive. As investors eventually recognize these risks, they fly back to safety of traditional securities and markets become fragile, even without leverage, precisely because the volume of new claims is excessive.

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Background: Imatinib has revolutionized the treatment of chronic myeloid leukemia (CML) and gastrointestinal stromal tumors (GIST). Considering the large inter-individual differences in the function of the systems involved in its disposition, exposure to imatinib can be expected to vary widely among patients. This observational study aimed at describing imatinib pharmacokinetic variability and its relationship with various biological covariates, especially plasma alpha1-acid glycoprotein (AGP), and at exploring the concentration-response relationship in patients. Methods: A population pharmacokinetic model (NONMEM) including 321 plasma samples from 59 patients was built up and used to derive individual post-hoc Bayesian estimates of drug exposure (AUC; area under curve). Associations between AUC and therapeutic response or tolerability were explored by ordered logistic regression. Influence of the target genotype (i.e. KIT mutation profile) on response was also assessed in GIST patients. Results: A one-compartment model with first-order absorption appropriately described the data, with an average oral clearance of 14.3 L/h (CL) and volume of distribution of 347 L (Vd). A large inter-individual variability remained unexplained, both on CL (36%) and Vd (63%), but AGP levels proved to have a marked impact on total imatinib disposition. Moreover, both total and free AUC correlated with the occurrence and number of side effects (e.g. OR 2.9±0.6 for a 2-fold free AUC increase; p<0.001). Furthermore, in GIST patients, higher free AUC predicted a higher probability of therapeutic response (OR 1.9±0.5; p<0.05), notably in patients with tumor harboring an exon 9 mutation or wild-type KIT, known to decrease tumor sensitivity towards imatinib. Conclusion: The large pharmacokinetic variability, associated to the pharmacokinetic-pharmacodynamic relationship uncovered are arguments to further investigate the usefulness of individualizing imatinib prescription based on TDM. For this type of drug, it should ideally take into consideration either circulating AGP concentrations or free drug levels, as well as KIT genotype for GIST.

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Over the last two decades, thanks to the discovery of several pharmaceutical agents, multiple sclerosis (MS) has been transformed into a treatable disorder although the degree of therapeutic response may vary considerably. As more medications find their entry into the MS market, a clinician faces a mounting challenge of comparing risk and benefit profiles of various agents in an attempt to find the best treatment approach for each individual patient. In this review, we aim to summarize the available data on safety profiles of available MS therapies while focusing mostly on serious medication specific potential adverse events without discussing the teratogenic potential of each agent (unless there is a black box warning) or hypersensitivity reactions. Our goal is to provide a clinician with guidance on assuring the appropriate safety monitoring for patients treated with one of the agents discussed. We also comment on the future of risk management in MS and discuss possible enhancements to the current model of drug approval process and general strategies to improve the patient safety.

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In this paper we propose a subsampling estimator for the distribution ofstatistics diverging at either known rates when the underlying timeseries in strictly stationary abd strong mixing. Based on our results weprovide a detailed discussion how to estimate extreme order statisticswith dependent data and present two applications to assessing financialmarket risk. Our method performs well in estimating Value at Risk andprovides a superior alternative to Hill's estimator in operationalizingSafety First portofolio selection.

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Recent progress in cancer therapy has dramatically modified the course and prognosis of some malignancies. Chemo and radiotherapy, along with newer targeted treatments, are given to control symptoms, postpone relapse, or attempt cure. However, many of these regimens are associated with adverse cardiovascular effects such as impaired left ventricular function, myocardial ischemia, hypertension, and arrhythmia. Awareness of potential cardiotoxicity is important, as it may allow practitioners to recognize early signs of cardiac complications and to adapt therapy in order to limit detrimental effects. Diagnosis of cardiovascular complications may iustify the introduction of cardiologic therapies, and may require the reassessment of risk/benefit ratios related to specific cancer therapy. Screening and follow up strategies are proposed.

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Applying the competing--risks model to multi--cause mortality,this paper provides a theoretical and empirical investigation of the positive complementarities that occur between disease--specific policy interventions. We argue that since an individual cannot die twice, competing risks imply that individuals will not waste resources on causes that are not the most immediate, but will make health investments so as to equalize cause--specific mortality. However, equal mortality risk from a variety of diseases does not imply that disease--specific public health interventions are a waste. Rather, a cause--specific intervention produces spillovers to other disease risks, so that the overall reduction in mortality will generally be larger than the direct effect measured on the targeted disease. The assumption that mortality from non--targeted diseases remains the same after a cause--specific intervention under--estimates the true effect of such programs, since the background mortality is also altered as a result of intervention. Analyzing data from one of the most important public health programs ever introduced, the Expanded Program on Immunization (EPI) of the United Nations, we find evidence for the existence of such complementarities, involving causes that are not biomedically, but behaviorally, linked.