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On the Accuracy of Drug-Resistant Cell Population Estimation from Total Cancer Size Measurements

机译:从总癌症大小的测量上耐药细胞群体估计的准确性。

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This paper analyzes the accuracy with which the drug-resistant sub-population of cancer cells in a tumor can be estimated from measurements of total tumor size. The paper is motivated by two key facts. First, drug resistance is one of the main reasons for the failure of cancer chemotherapy treatment: a fact that makes it critical to monitor and estimate such resistance. Second, recent research has shown that above a threshold level of drug resistance, the optimal treatment protocol is one that regulates total cancer size rather than attempting to eliminate the cancer. This makes the accurate estimation of resistance critical for treatment protocol selection. The literature already examines the causes and dynamics of resistance in cancerous tumors. However, the problem of determining the accuracy with which the prevalence of resistance can be estimated remains relatively unexplored. To address this gap in the literature, we apply Fisher information analysis to the problem of estimating the fraction of a total cancer cell population that is drug-resistant, assuming a constant drug administration rate. Our analysis reveals that drug-resistant cell population estimation accuracy worsens with increasing drug administration rate up to the point where the drug-sensitive and drug-resistant cell population growth rates are equal. Beyond that point, additional drug administration improves resistance estimation accuracy.
机译:本文分析了可通过测量肿瘤总大小来估计肿瘤细胞中耐药性亚群的准确性。本文的动机是基于两个关键事实。首先,耐药性是导致癌症化学疗法治疗失败的主要原因之一:这一事实使得监测和评估此类耐药性变得至关重要。其次,最近的研究表明,在耐药性阈值以上时,最佳治疗方案是调节总癌症大小而不是试图消除癌症的方案。这使得对耐药性的准确评估对于治疗方案的选择至关重要。文献已经检查了癌症肿瘤中耐药性的原因和动力学。然而,确定可以估计电阻的流行程度的精度的问题仍然没有被探索。为了解决文献中的这一空白,我们假设假设药物的施用率恒定,将Fisher信息分析应用于估计耐药性的总癌细胞群体比例的问题。我们的分析表明,耐药菌群估计的准确性随着给药速率的增加而恶化,直到药物敏感性和耐药菌群增长率相等。超过这一点,额外的药物管理可以提高耐药性估计的准确性。

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