Center for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas Department of Medicine, University of Cape Town, Observatory, South Africa.
Center for Infectious Diseases Research and Experimental Therapeutics, Baylor Research Institute, Baylor University Medical Center, Dallas, Texas.
Clin Infect Dis. 2015 Aug 15;61 Suppl 1:S25-31. doi: 10.1093/cid/civ427.
The hollow fiber system model of tuberculosis (HFS-TB), in tandem with Monte Carlo experiments, represents a drug development tool (DDT) with the potential for use to develop tuberculosis treatment regimens. However, the predictive accuracy of the HFS-TB, or any other nonclinical DDT such as an animal model, has yet to be robustly evaluated.
To avoid hindsight bias, a literature search was performed to identify clinical studies published at least 6 months after HFS-TB experiments' quantitative predictions. Steps to minimize bias and for reporting systematic reviews were applied as outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Publications were scored for quality of evidence. Accuracy was calculated using the mean absolute percentage error, then summated with weighting assigned by sample size and quality-of-evidence score. Given the lack of a gold-standard tuberculosis DDT, the forecasting accuracy of a completely unreliable tool was also calculated from 1000 simulated experiments for a random or "total guesswork" model.
The quantitative forecasting accuracy (95% confidence interval [CI]) for the "total guesswork" model was 15.6% (95% CI, 8.7%-22.5%); bias was -0.1% (95% CI, -2.5% to 2.2%). Twenty clinical studies were published after HFS-TB experiments predicted optimal drug exposures and doses, susceptibility breakpoints, and optimal combination regimens. Based on these clinical studies, the predictive accuracy of the HFS-TB was 94.4% (95% CI, 84.3%-99.9%), and bias was 1.8% (95% CI, -13.7% to 6.2%).
The HFS-TB model is highly accurate at forecasting optimal drug exposures, doses, and dosing schedules for use in the clinic.
中空纤维系统结核模型（HFS-TB）与蒙特卡罗实验相结合，代表了一种有潜力用于开发结核病治疗方案的药物开发工具（DDT）。然而，HFS-TB 或任何其他非临床 DDT（如动物模型）的预测准确性尚未得到稳健评估。
为避免后见之明偏差，进行了文献检索，以确定至少在 HFS-TB 实验的定量预测发表后 6 个月发表的临床研究。应用系统评价和荟萃分析的首选报告项目中概述的步骤来最小化偏差并报告系统评价。出版物的证据质量进行评分。使用平均绝对百分比误差计算准确性，然后通过样本量和证据质量评分加权求和。鉴于缺乏黄金标准的结核病 DDT，还从 1000 次模拟实验中计算了完全不可靠工具的预测准确性，该模拟实验是针对随机或“完全猜测”模型的。
“完全猜测”模型的定量预测准确性（95%置信区间 [CI]）为 15.6%（95%CI，8.7%-22.5%）；偏差为-0.1%（95%CI，-2.5%至 2.2%）。在 HFS-TB 实验预测最佳药物暴露量和剂量、药敏断点和最佳联合治疗方案后，发表了 20 项临床研究。基于这些临床研究，HFS-TB 的预测准确性为 94.4%（95%CI，84.3%-99.9%），偏差为 1.8%（95%CI，-13.7%至 6.2%）。
HFS-TB 模型在预测最佳药物暴露量、剂量和临床用药方案方面具有很高的准确性。
