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Cai J, Li H, Zhang C, Chen Z, Liu H, Lei F, Qin JJ, Liu YM, Zhou F, Song X, Zhou J, Zhao YC, Wu B, He M, Yang H, Zhu L, Zhang P, Ji YX, Zhao GN, Lu Z, Liu L, Mao W, Liao X, Lu H, Wang D, Xia X, Huang X, Wei X, Xia J, Zhang BH, Yuan Y, She ZG, Xu Q, Ma X, Wang Y, Yang J, Zhang X, Zhang XJ, Li H. The Neutrophil-to-Lymphocyte Ratio Determines Clinical Efficacy of Corticosteroid Therapy in Patients with COVID-19. Cell Metab 2021; 33:258-269.e3. [PMID: 33421384 PMCID: PMC7832609 DOI: 10.1016/j.cmet.2021.01.002] [Citation(s) in RCA: 84] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 10/15/2020] [Accepted: 12/30/2020] [Indexed: 02/08/2023]
Abstract
Corticosteroid therapy is now recommended as a treatment in patients with severe COVID-19. But one key question is how to objectively identify severely ill patients who may benefit from such therapy. Here, we assigned 12,862 COVID-19 cases from 21 hospitals in Hubei Province equally to a training and a validation cohort. We found that a neutrophil-to-lymphocyte ratio (NLR) > 6.11 at admission discriminated a higher risk for mortality. Importantly, however, corticosteroid treatment in such individuals was associated with a lower risk of 60-day all-cause mortality. Conversely, in individuals with an NLR ≤ 6.11 or with type 2 diabetes, corticosteroid treatment was not associated with reduced mortality, but rather increased risks of hyperglycemia and infections. These results show that in the studied cohort corticosteroid treatment is associated with beneficial outcomes in a subset of COVID-19 patients who are non-diabetic and with severe symptoms as defined by NLR.
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Affiliation(s)
- Jingjing Cai
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China; Department of Cardiology, The Third Xiangya Hospital, Central South University, Changsha 410000, China
| | - Haomiao Li
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Changjiang Zhang
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China; The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture, Enshi 445000, China
| | - Ze Chen
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Hui Liu
- School of Basic Medical Science, Wuhan University, Wuhan, China; Department of Gastroenterology, Wuhan Third Hospital and Tongren Hospital of Wuhan University, Wuhan, China
| | - Fang Lei
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Juan-Juan Qin
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Ye-Mao Liu
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Feng Zhou
- Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaohui Song
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Jianghua Zhou
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Yan-Ci Zhao
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Bin Wu
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Meiling He
- School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Huilin Yang
- School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Lihua Zhu
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Peng Zhang
- School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yan-Xiao Ji
- Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guang-Nian Zhao
- Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhigang Lu
- Department of Neurology, The First People's Hospital of Jingmen affiliated to Hubei Minzu University, Jingmen 448000, China
| | - Liming Liu
- Department of General Surgery, Ezhou Central Hospital, Ezhou 436000, China
| | - Weiming Mao
- Department of General Surgery, Huanggang Central Hospital, Huanggang 438000, China
| | - Xiaofeng Liao
- Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, China
| | - Haofeng Lu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Changjiang University, Jingzhou, China
| | - Daihong Wang
- Department of Hepatobiliary and Pancreatic Surgery, Xianning Central Hospital, Hubei Province, Xianning, China
| | - Xigang Xia
- Department of Hepatobiliary Surgery, Jingzhou Central Hospital, Jingzhou, China
| | - Xiaodong Huang
- Department of Gastroenterology, Wuhan Third Hospital and Tongren Hospital of Wuhan University, Wuhan, China
| | - Xiang Wei
- Division of Cardiothoracic and Vascular Surgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiahong Xia
- Department of Cardiovascular Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Bing-Hong Zhang
- Department of Neonatology, Renmin Hospital of Wuhan University, Wuhan, China
| | - Yufeng Yuan
- Department of Hepatobiliary and Pancreatic Surgery, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhi-Gang She
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China
| | - Qingbo Xu
- Centre for Clinic Pharmacology, The William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Xinliang Ma
- Department of Emergency Medicine, Thomas Jefferson University, Philadelphia, PA 19004, USA
| | - Yibin Wang
- Departments of Anesthesiology, Physiology, and Medicine, Cardiovascular Research Laboratories, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Juan Yang
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China.
| | - Xin Zhang
- School of Basic Medical Science, Wuhan University, Wuhan, China; Department of Gastroenterology, Wuhan Third Hospital and Tongren Hospital of Wuhan University, Wuhan, China.
| | - Xiao-Jing Zhang
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China.
| | - Hongliang Li
- Department of Cardiology, Renmin Hospital, Wuhan University, Wuhan, China; School of Basic Medical Science, Wuhan University, Wuhan, China; Institute of Model Animal, Wuhan University, Wuhan, China; Medical Science Research Center, Zhongnan Hospital of Wuhan University, Wuhan, China.
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Prada-Ramallal G, Takkouche B, Figueiras A. Bias in pharmacoepidemiologic studies using secondary health care databases: a scoping review. BMC Med Res Methodol 2019; 19:53. [PMID: 30871502 PMCID: PMC6419460 DOI: 10.1186/s12874-019-0695-y] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2018] [Accepted: 02/26/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The availability of clinical and therapeutic data drawn from medical records and administrative databases has entailed new opportunities for clinical and epidemiologic research. However, these databases present inherent limitations which may render them prone to new biases. We aimed to conduct a structured review of biases specific to observational clinical studies based on secondary databases, and to propose strategies for the mitigation of those biases. METHODS Scoping review of the scientific literature published during the period 2000-2018 through an automated search of MEDLINE, EMBASE and Web of Science, supplemented with manually cross-checking of reference lists. We included opinion essays, methodological reviews, analyses or simulation studies, as well as letters to the editor or retractions, the principal objective of which was to highlight the existence of some type of bias in pharmacoepidemiologic studies using secondary databases. RESULTS A total of 117 articles were included. An increasing trend in the number of publications concerning the potential limitations of secondary databases was observed over time and across medical research disciplines. Confounding was the most reported category of bias (63.2% of articles), followed by selection and measurement biases (47.0% and 46.2% respectively). Confounding by indication (32.5%), unmeasured/residual confounding (28.2%), outcome misclassification (28.2%) and "immortal time" bias (25.6%) were the subcategories most frequently mentioned. CONCLUSIONS Suboptimal use of secondary databases in pharmacoepidemiologic studies has introduced biases in the studies, which may have led to erroneous conclusions. Methods to mitigate biases are available and must be considered in the design, analysis and interpretation phases of studies using these data sources.
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Affiliation(s)
- Guillermo Prada-Ramallal
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, c/ San Francisco s/n, 15786 Santiago de Compostela, A Coruña Spain
- Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Clinical University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
| | - Bahi Takkouche
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, c/ San Francisco s/n, 15786 Santiago de Compostela, A Coruña Spain
- Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Clinical University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública – CIBERESP), Santiago de Compostela, Spain
| | - Adolfo Figueiras
- Department of Preventive Medicine and Public Health, University of Santiago de Compostela, c/ San Francisco s/n, 15786 Santiago de Compostela, A Coruña Spain
- Health Research Institute of Santiago de Compostela (Instituto de Investigación Sanitaria de Santiago de Compostela - IDIS), Clinical University Hospital of Santiago de Compostela, 15706 Santiago de Compostela, Spain
- Consortium for Biomedical Research in Epidemiology & Public Health (CIBER en Epidemiología y Salud Pública – CIBERESP), Santiago de Compostela, Spain
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Mapel DW, Nelson LS, Lydick E, Soriano J, Yood MU, Davis KJ. Survival among COPD patients using fluticasone/salmeterol in combination versus other inhaled steroids and bronchodilators alone. COPD 2007; 4:127-34. [PMID: 17530506 DOI: 10.1080/15412550701341111] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
Recent retrospective studies have suggested that use of inhaled corticosteroids (ICS) may improve survival in chronic obstructive pulmonary disease (COPD), particularly when combined with a long-acting beta-agonist (LABA). However, the study methodologies have been questioned, and no study has examined the survival effect of the newer combination ICS/LABA inhalers. The goal of this project was to further examine the relationship between ICS treatment, with or without LABA, and survival in COPD. COPD patients were identified from the administrative databases of four different integrated health care delivery systems. All patients who were diagnosed with COPD between September 1, 2000 and August 31, 2001 and who had at least 3 months treatment with either a combined fluticasone/salmeterol inhaler (FSI, N=866), any ICS used with a LABA (ICS/LABA, N=525), ICS alone (N=742), LABA alone (N=531), or a short-acting bronchodilator alone (SABD, N=1832), were included. Analyses were conducted using three different analysis approaches that adjust for various biases that may affect the results. In the basic Cox proportional hazards models, use of FSI, ICS/LABA, ICS alone, and LABA alone had significant survival benefits as compared to SABD, after adjustment for differences in age, gender, comorbidities, asthma status, and disease severity (HRs 0.61 [0.45-0.83], 0.59 [0.46-0.77], 0.76 [0.61-0.95], 0.75 [0.57-0.98], respectively). Propensity score matching to reduce the clinical differences between the treatment groups versus the SABD reference group found very similar results. Nested case-control analyses, which are based on survival status instead of treatment, continued to show a significant survival benefit for FSI, ICS/LABA, and ICS alone. Treatment with FSI or another ICS with or without LABA is associated with improved survival in COPD. The treatment benefit is reproducible and is robust to application of a number of different analysis techniques designed to adjust for differences in confounding variables and for bias by indication.
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