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Gigantomastia is a rare condition characterized by excessive hypertrophy of the connective tissue of the breast, which can cause physical and emotional distress. Surgical intervention is crucial for improving patients’ quality of life; however, it is challenging to balance minimizing the risk of recurrence and maximizing favorable aesthetic outcomes. This study documents the successful management of three rare cases of bilateral gigantomastia resulting from benign tumors. These cases included rapidly growing bilateral diffuse tumorous pseudoangiomatous stromal hyperplasia (PASH) and bilateral juvenile giant fibroadenoma, with no long-term recurrence observed. We discuss the diagnostic challenges and management considerations for gigantomastia, with a focus on reviewing PASH and its differential diagnosis. The findings offer valuable insights into the successful management of diverse gigantomastia cases caused by benign tumors, potentially aiding clinicians in making more informed decisions regarding optimal patient care.
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MATLAB® is widely used for numerical analysis, modeling, and simulation. One of MATLAB's tools, SimBiology®, is often used for pharmacokinetic, pharmacodynamic model and dynamic systems; however, SimBiology seems to be rarely used for non-compartmental analysis (NCA), and the published official documentation provides a poor description of the analysis algorithm for NCA. Therefore, we conducted NCAs with a hypothetical dataset and some scenarios and compared the results. According to the results of this study, SimBiology estimates parameters using the unweighted linear regression for the terminal slope and linear interpolation method. Moreover, although the documentation describing the actual analysis algorithm used to process non-numeric data is not easily accessible to users, users may introduce numeric data at time zero to perform NCA properly. Using the command window, users can perform analyses more quickly and effectively. If the NCA official documentation were improved, SimBiology might be more widely adopted to perform NCA in clinical pharmacology.
Assuntos
Conjunto de Dados , Modelos Lineares , Métodos , Farmacocinética , Farmacologia Clínica , Estatística como AssuntoRESUMO
In 2005, the International Council for Harmonization (ICH) established cardiotoxicity assessment guidelines to identify the risk of Torsade de Pointes (TdP). It is focused on the blockade of the human ether-à-go-go-related gene (hERG) channel known to cause QT/QTc prolongation and the QT/QTc prolongation shown on the electrocardiogram. However, these biomarkers are not the direct risks of TdP with low specificity as the action potential is influenced by multiple channels along with the hERG channel. Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative emerged to address limitations of the current model. The objective of CiPA is to develop a standardized in silico model of a human ventricular cell to quantitively evaluate the cardiac response for the cardiac toxicity risk and to come up with a metric for the TdP risk assessment. In silico working group under CiPA developed a standardized and reliable in silico model and a metric that can quantitatively evaluate cellular cardiac electrophysiologic activity. The implementation mainly consists of hERG fitting, Hill fitting, and action potential simulation. In this review, we explained how the in silico model of CiPA works, and briefly summarized current overall CiPA studies. We hope this review helps clinical pharmacologists to understand the underlying estimation process of CiPA in silico modeling.
Assuntos
Humanos , Potenciais de Ação , Biomarcadores , Cardiotoxicidade , Simulação por Computador , Eletrocardiografia , Esperança , Técnicas In Vitro , Medição de Risco , Sensibilidade e Especificidade , Torsades de PointesRESUMO
A clinical trial management system (CTMS) is a comprehensive program that supports an efficient clinical trial. To improve the environment of clinical trials and to be competitive in the global clinical trials market, an advanced and integrated CTMS is necessary. However, there is little information about the status of CTMSs in Korea. To understand the utilization of current CTMSs and requirements for a future CTMS, we conducted a survey on the subjects related to clinical trials. The survey was conducted from July 27 to August 16, 2017. The total number of respondents was 596, and 531 of these responses were used. Almost half of the respondents were from hospitals (46%). The proportion of respondents who are currently using a CTMS was the highest for contract research organizations at 59%, whereas the proportion used by investigators was 39%. The main reason for not using a CTMS was that it is unnecessary and expensive, but it showed a difference between workplaces. Many respondents frequently used CTMSs to check the clinical trial schedule and progress status, which was needed regardless of workplace. While two-thirds of users tended to be satisfied with their current CTMS, there were many users who felt their CTMS was inconvenient. The most requested function for a future CTMS was one that could be used to manage the project schedule and subject enrollment status. Additionally, a systematic linkage to electronic medical records, including prescription and laboratory test results, and a function to confirm the participation history of subjects in other hospitals were requested.