Strategies to minimize heterogeneity and optimize clinical trials in Acute Respiratory Distress Syndrome (ARDS): Insights from mathematical modelling.
Strategies to minimize heterogeneity and optimize clinical trials in Acute Respiratory Distress Syndrome (ARDS): Insights from mathematical modelling.
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DOI：
10.1016/j.ebiom.2021.103809
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发表时间：
2022-01
期刊：
影响因子：
11.1
通讯作者：
Munn LL
中科院分区：
文献类型：
--
作者：
Subudhi S;Voutouri C;Hardin CC;Nikmaneshi MR;Patel AB;Verma A;Khandekar MJ;Dutta S;Stylianopoulos T;Jain RK;Munn LL
数学模型可能有助于理解危重疾病中损伤和免疫反应之间复杂的相互作用。我们利用 COVID-19 的系统生物学模型来分析改变患者基线特征对免疫调节治疗结果的影响。我们创建示例参数集，旨在模仿不同的患者类型。对于每种患者类型，我们定义最佳治疗，确定负责临床反应的生物方案，并预测这些方案的生物标志物。代表老年和过度炎症患者的模型状态对免疫调节的反应比代表肥胖和糖尿病患者的模型状态更好。不同的临床反应是由不同的生物程序驱动的。老年患者的最佳治疗开始时间取决于中性粒细胞募集、全身细胞因子表达、全身微血栓形成和肾素血管紧张素系统 (RAS)，而对于炎症过度的患者则取决于 RAS、全身微血栓形成和反式 IL6 信号传导。对于老年和炎症过度的患者，IL6 调节治疗预计在很早（感染后第 4 天以下）开始时是最佳的，而广泛的免疫抑制治疗（皮质类固醇）预计在疾病后期（感染第 7-9 天）开始时最佳。我们表明，模型识别的生物程序标记与临床识别的疾病严重程度标记相对应。我们证明，COVID-19 病理学建模可以提出预测对给定免疫调节治疗的最佳反应的生物标志物。因此，数学模型构成了预测丰富的新辅助手段，并可能有助于减少重症监护试验中的异质性。简历。获得玛丽·斯克沃多夫斯卡·居里行动个人奖学金 (MSCA-IF-GF-2020-101028945)。 R.K.J. 的研究得到 R01-CA208205、U01-CA 224348、R35-CA197743 的支持，以及国家癌症研究基金会、简氏信托基金会、高级医学研究基金会和哈佛路德维希癌症中心的资助。没有资助者参与本手稿的制作或批准。
Mathematical modelling may aid in understanding the complex interactions between injury and immune response in critical illness. We utilize a system biology model of COVID-19 to analyze the effect of altering baseline patient characteristics on the outcome of immunomodulatory therapies. We create example parameter sets meant to mimic diverse patient types. For each patient type, we define the optimal treatment, identify biologic programs responsible for clinical responses, and predict biomarkers of those programs. Model states representing older and hyperinflamed patients respond better to immunomodulation than those representing obese and diabetic patients. The disparate clinical responses are driven by distinct biologic programs. Optimal treatment initiation time is determined by neutrophil recruitment, systemic cytokine expression, systemic microthrombosis and the renin-angiotensin system (RAS) in older patients, and by RAS, systemic microthrombosis and trans IL6 signalling for hyperinflamed patients. For older and hyperinflamed patients, IL6 modulating therapy is predicted to be optimal when initiated very early (<4th day of infection) and broad immunosuppression therapy (corticosteroids) is predicted to be optimally initiated later in the disease (7th – 9th day of infection). We show that markers of biologic programs identified by the model correspond to clinically identified markers of disease severity. We demonstrate that modelling of COVID-19 pathobiology can suggest biomarkers that predict optimal response to a given immunomodulatory treatment. Mathematical modelling thus constitutes a novel adjunct to predictive enrichment and may aid in the reduction of heterogeneity in critical care trials. C.V. received a Marie Skłodowska Curie Actions Individual Fellowship (MSCA-IF-GF-2020-101028945). R.K.J.'s research is supported by R01-CA208205, and U01-CA 224348, R35-CA197743 and grants from the National Foundation for Cancer Research, Jane's Trust Foundation, Advanced Medical Research Foundation and Harvard Ludwig Cancer Center. No funder had a role in production or approval of this manuscript.
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DOI：
10.1016/s2213-2600(21)00099-0
发表时间：
2021-05
期刊：
The Lancet. Respiratory medicine
影响因子：
--
作者：
Lescure FX;Honda H;Fowler RA;Lazar JS;Shi G;Wung P;Patel N;Hagino O;Sarilumab COVID-19 Global Study Group
通讯作者：
Sarilumab COVID-19 Global Study Group
影响因子：
76.2
作者：
Calfee, Carolyn S.;Delucchi, Kevin;Parsons, Polly E.;Thompson, B. Taylor;Ware, Lorraine B.;Matthay, Michael A.
通讯作者：
Matthay, Michael A.
DOI：
10.1164/rccm.201603-0645oc
发表时间：
2017-02-01
影响因子：
24.7
作者：
Famous, Katie R.;Delucchi, Kevin;Calfee, Carolyn S.
通讯作者：
Calfee, Carolyn S.
影响因子：
6.7
作者：
Jenner AL;Aogo RA;Alfonso S;Crowe V;Deng X;Smith AP;Morel PA;Davis CL;Smith AM;Craig M
通讯作者：
Craig M
DOI：
10.1073/pnas.0308531101
发表时间：
2004-03-23
影响因子：
11.1
作者：
Brunet, JP;Tamayo, P;Mesirov, JP
通讯作者：
Mesirov, JP