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Visual Abstract. Effect of Recombinant Human Granulocyte Colony-Stimulating Factor for Patients With Coronavirus Disease 2019 (COVID-19) and Lymphopenia: A Randomized Clinical Trial
Effect of Recombinant Human Granulocyte Colony-Stimulating Factor for Patients With Coronavirus Disease 2019 (COVID-19) and Lymphopenia: A Randomized Clinical Trial
Figure 1.  Trial Profile
Trial Profile

Some of the patients had more than 1 comorbidity, and therefore the sum of patients with each category of comorbidities exceeded 117. rhG-CSF indicates recombinant human granulocyte colony-stimulating factor.

Figure 2.  Time to Clinical Improvement at Day 21
Time to Clinical Improvement at Day 21

The blue curve indicates the recombinant human granulocyte colony-stimulating factor (rhG-CSF) group, whereas the orange curve denotes the control group (usual care). The hazard ratio (HR) of achieving clinical improvement, along with the 95% CI and the P value, is also reported. The hazards ratio with the 95% CI was estimated by using the Fine and Gray proportional subdistribution hazards model with treatment group, center, and oxygen therapy being included in the model.

Table 1.  Baseline Demographic Characteristics and Laboratory Findings and Treatments Received Before Enrollmenta
Baseline Demographic Characteristics and Laboratory Findings and Treatments Received Before Enrollmenta
Table 2.  Therapeutic Outcomes in the Intention-to-Treat Population
Therapeutic Outcomes in the Intention-to-Treat Population
Table 3.  Summary of Adverse Events in the Safety Population
Summary of Adverse Events in the Safety Population
1.
World Health Organization. WHO coronavirus disease (COVID-19) dashboard. Accessed August 11, 2020. https://covid19.who.int/
2.
Huang  C, Wang  Y, Li  X,  et al.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.   Lancet. 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5 PubMedGoogle ScholarCrossref
3.
Guan  WJ, Ni  ZY, Hu  Y,  et al; China Medical Treatment Expert Group for Covid-19.  Clinical characteristics of coronavirus disease 2019 in China.   N Engl J Med. 2020;382(18):1708-1720. doi:10.1056/NEJMoa2002032 PubMedGoogle ScholarCrossref
4.
Chen  N, Zhou  M, Dong  X,  et al.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.   Lancet. 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7 PubMedGoogle ScholarCrossref
5.
Yang  X, Yu  Y, Xu  J,  et al.  Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study.   Lancet Respir Med. 2020;8(5):475-481. doi:10.1016/S2213-2600(20)30079-5 PubMedGoogle ScholarCrossref
6.
Zhou  F, Yu  T, Du  R,  et al.  Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study.   Lancet. 2020;395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3 PubMedGoogle ScholarCrossref
7.
Wang  D, Hu  B, Hu  C,  et al.  Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China.   JAMA. 2020. doi:10.1001/jama.2020.1585 PubMedGoogle Scholar
8.
Tan  L, Wang  Q, Zhang  D,  et al.  Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study.   Signal Transduct Target Ther. 2020;5(1):33. doi:10.1038/s41392-020-0148-4 PubMedGoogle ScholarCrossref
9.
Zhao  H, Guo  M, Sun  X,  et al.  Effects of recombinant human granulocyte colony-stimulating factor on central and peripheral T lymphocyte reconstitution after sublethal irradiation in mice.   J Radiat Res. 2013;54(1):83-91. doi:10.1093/jrr/rrs082 PubMedGoogle ScholarCrossref
10.
Ang  CC, Tay  YK.  Hematological abnormalities and the use of granulocyte-colony-stimulating factor in patients with Stevens-Johnson syndrome and toxic epidermal necrolysis.   Int J Dermatol. 2011;50(12):1570-1578. doi:10.1111/j.1365-4632.2011.05007.x PubMedGoogle ScholarCrossref
11.
Koizumi  T, Kubo  K, Koyama  S,  et al.  Neutrophils pretreated with granulocyte colony-stimulating factor (G-CSF) are not related to the severity of endotoxin-induced lung injury.   Exp Lung Res. 1997;23(5):393-404. doi:10.3109/01902149709039234 PubMedGoogle ScholarCrossref
12.
Li  JG, Zhang  YJ, Wu  W,  et al  Effect of recombinant human granulocyte colony-stimulating factor on leukopenia in severe acute respiratory syndrome patients.   Yi Shi Jin Xiu Za Zhi. 2004; 27:21-22. doi:10.3760/cma.j.issn.1673-4904.2004.23.008Google Scholar
13.
Kimura  S, Matsuda  J, Ikematsu  S,  et al.  Efficacy of recombinant human granulocyte colony-stimulating factor on neutropenia in patients with AIDS.   AIDS. 1990;4(12):1251-1255. doi:10.1097/00002030-199012000-00011 PubMedGoogle ScholarCrossref
14.
Zhao  SS, Fang  S, Zhu  CY, Wang  LL, Gao  CJ.  Effect of G-CSF in vitro stimulation on distribution of peripheral lymphocyte subsets in the healthy persons [article in Chinese].   Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2018;26(1):258-262.PubMedGoogle Scholar
15.
Melve  GK, Ersvaer  E, Eide  GE, Kristoffersen  EK, Bruserud  Ø.  Peripheral blood stem cell mobilization in healthy donors by granulocyte colony-stimulating factor causes preferential mobilization of lymphocyte subsets.   Front Immunol. 2018;9:845. doi:10.3389/fimmu.2018.00845 PubMedGoogle ScholarCrossref
16.
San Miguel  JF, Hernández  MD, Gonzalez  M,  et al.  A randomized study comparing the effect of GM-CSF and G-CSF on immune reconstitution after autologous bone marrow transplantation.   Br J Haematol. 1996;94(1):140-147. doi:10.1046/j.1365-2141.1996.d01-1756.x PubMedGoogle ScholarCrossref
17.
Rondelli  D, Raspadori  D, Anasetti  C,  et al.  Alloantigen presenting capacity, T cell alloreactivity and NK function of G-CSF-mobilized peripheral blood cells.   Bone Marrow Transplant. 1998;22(7):631-637. doi:10.1038/sj.bmt.1701413 PubMedGoogle ScholarCrossref
18.
World Health Organization. Coronavirus disease (COVID-2019). Accessed September 1, 2020. https://www.who.int/blueprint/priority-diseases/key-action/novel-coronavirus/en/
19.
International Severe Acute Respiratory and Emerging Infections Consortium. ISARIC home page. Accessed September 1, 2020. https://isaric.tghn.org/
20.
Fine  JP, Gray  RJ.  A proportional hazards model for the subdistribution of a competing risk.   J Am Stat Assoc. 1999;94:496-509. doi:10.1080/01621459.1999.10474144 Google ScholarCrossref
21.
Newcombe  RG.  Interval estimation for the difference between independent proportions: comparison of eleven methods.   Stat Med. 1998;17(8):873-890. doi:10.1002/(SICI)1097-0258(19980430)17:8<873::AID-SIM779>3.0.CO;2-I PubMedGoogle ScholarCrossref
22.
Hodges  JL  Jr, Lehmann  EL.  Estimates of location based on rank tests.   Ann Math Stat. 1963;34:598-611. doi:10.1214/aoms/1177704172 Google ScholarCrossref
23.
Piccirillo  N, Laurenti  L, Chiusolo  P,  et al.  Reliability of leukostasis grading score to identify patients with high-risk hyperleukocytosis.   Am J Hematol. 2009;84(6):381-382. doi:10.1002/ajh.21418 PubMedGoogle ScholarCrossref
24.
Xu  Z, Shi  L, Wang  Y,  et al.  Pathological findings of COVID-19 associated with acute respiratory distress syndrome.   Lancet Respir Med. 2020;8(4):420-422. doi:10.1016/S2213-2600(20)30076-X PubMedGoogle ScholarCrossref
Original Investigation
September 10, 2020

Effect of Recombinant Human Granulocyte Colony–Stimulating Factor for Patients With Coronavirus Disease 2019 (COVID-19) and Lymphopenia: A Randomized Clinical Trial

Author Affiliations
  • 1State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, China
  • 2Guangzhou Eighth People’s Hospital, Guangzhou Medical University, Guangzhou, China
  • 3State Key Laboratory of Organ Failure Research, National Clinical Research Center for Kidney Disease, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
  • 4Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
  • 5Medical Department, Hankou Hospital of Wuhan City, Wuhan, China
  • 6Department of Haematology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
JAMA Intern Med. 2021;181(1):71-78. doi:10.1001/jamainternmed.2020.5503
Visual Abstract. Effect of Recombinant Human Granulocyte Colony-Stimulating Factor for Patients With Coronavirus Disease 2019 (COVID-19) and Lymphopenia: A Randomized Clinical Trial
Effect of Recombinant Human Granulocyte Colony-Stimulating Factor for Patients With Coronavirus Disease 2019 (COVID-19) and Lymphopenia: A Randomized Clinical Trial
Key Points

Question  Can treating patients with coronavirus disease 2019 (COVID-19) with recombinant human granulocyte colony-stimulating factor (rhG-CSF) increase their peripheral blood leukocyte and lymphocyte cell counts and lead to clinical improvement?

Findings  In this open-label, randomized clinical trial of 200 Chinese patients with COVID-19, lymphopenia, and no comorbidities, rhG-CSF treatment did not accelerate clinical improvement, but the number of patients progressing to critical illness or death may have been reduced, without an increased risk of serious adverse events.

Meaning  Preliminary findings from a randomized clinical trial suggest that rhG-CSF treatment should be studied in larger trials and in a broader range of patients with COVID-19.

Abstract

Importance  Lymphopenia is common and correlates with poor clinical outcomes in patients with coronavirus disease 2019 (COVID-19).

Objective  To determine whether a therapy that increases peripheral blood leukocyte and lymphocyte cell counts leads to clinical improvement in patients with COVID-19.

Design, Setting and Participants  Between February 18 and April 10, 2020, we conducted an open-label, multicenter, randomized clinical trial at 3 participating centers in China. The main eligibility criteria were pneumonia, a blood lymphocyte cell count of 800 per μL (to convert to ×109/L, multiply by 0.001) or lower, and no comorbidities. Severe acute respiratory syndrome coronavirus 2 infection was confirmed with reverse-transcription polymerase chain reaction testing.

Exposures  Usual care alone, or usual care plus 3 doses of recombinant human granulocyte colony-stimulating factor (rhG-CSF, 5 μg/kg, subcutaneously at days 0-2).

Main Outcomes and Measures  The primary end point was the time from randomization to improvement of at least 1 point on a 7-category disease severity score.

Results  Of 200 participants, 112 (56%) were men and the median (interquartile range [IQR]) age was 45 (40-55) years. There was random assignment of 100 patients (50%) to the rhG-CSF group and 100 (50%) to the usual care group. Time to clinical improvement was similar between groups (rhG-CSF group median of 12 days (IQR, 10-16 days) vs usual care group median of 13 days (IQR, 11-17 days); hazard ratio, 1.28; 95% CI, 0.95-1.71; P = .06). For secondary end points, the proportion of patients progressing to acute respiratory distress syndrome, sepsis, or septic shock was lower in the rhG-CSF group (rhG-CSF group, 2% vs usual care group, 15%; difference, −13%; 95%CI, −21.4% to −5.4%). At 21 days, 2 patients (2%) had died in the rhG-CSF group compared with 10 patients (10%) in the usual care group (hazard ratio, 0.19; 95%CI, 0.04-0.88). At day 5, the lymphocyte cell count was higher in the rhG-CSF group (rhG-CSF group median of 1050/μL vs usual care group median of 620/μL; Hodges-Lehmann estimate of the difference in medians, 440; 95% CI, 380-490). Serious adverse events, such as sepsis or septic shock, respiratory failure, and acute respiratory distress syndrome, occurred in 29 patients (14.5%) in the rhG-CSF group and 42 patients (21%) in the usual care group.

Conclusion and Relevance  In preliminary findings from a randomized clinical trial, rhG-CSF treatment for patients with COVID-19 with lymphopenia but no comorbidities did not accelerate clinical improvement, but the number of patients developing critical illness or dying may have been reduced. Larger studies that include a broader range of patients with COVID-19 should be conducted.

Trial Registration  Chinese Clinical Trial Registry: ChiCTR2000030007

Introduction

As of August 11, 2020, coronavirus disease 2019 (COVID-19) has led to a global pandemic, with more than 19 000 000 laboratory-confirmed cases and 720 000 deaths.1 To our knowledge, there are few effective therapies for COVID-19.

Lymphopenia is prevalent among patients with COVID-19.2-7 The magnitude and duration of peripheral blood lymphocyte (PBL) cell count decline is predictive of disease severity and death.2-8 In mouse models and people, recombinant human granulocyte colony-stimulating factor (rhG-CSF) increases peripheral blood leukocyte and lymphocyte (including lymphocyte subsets) cell counts.9,10 Although rhG-CSF did not alter the severity of acute lung injury in a sheep model,11 rhG-CSF normalized PBL cell counts in patients with severe acute respiratory syndrome.12 In an observational study, rhG-CSF was associated with improved clinical outcomes in patients with AIDS.13

The potential therapeutic effects of rhG-CSF for patients with COVID-19 are uncertain. In healthy persons, rhG-CSF reportedly increased PBL cell counts via mobilizing CD4+ and CD8+ T cells14,15; findings after autologous bone marrow transplant were similar.16 Nonetheless, rhG-CSF did not mobilize natural killer (NK) cells in vivo.17

In a clinical trial, we sought to determine whether patients with COVID-19 with lymphopenia would benefit from treatment with rhG-CSF. To minimize the potential adverse effects of other conditions on immune responses, we excluded patients who had comorbidities.

Methods
Study Design

This study was an open-label, multicenter, parallel-group randomized clinical trial conducted from February 18, 2020, to April 10, 2020. We recruited patients from 3 trial sites (Guangzhou No. 8 People’s Hospital [Guangzhou, China], Wuhan Union Hospital, and Wuhan Hankou Hospital [Wuhan, China]).

Ethics approval was obtained from institutional review boards at each participating site. Patients (n = 156) or their legal representative (n = 44) provided written informed consent; legal representatives provided consent for patients requiring noninvasive ventilation who had illness too severe to consent themselves. The clinical trial was conducted in accordance with the Declaration of Helsinki, the International Conference on Harmonization–Good Clinical Practice, and Consolidated Standards of Reporting Trials guidelines. Supplement 1 includes the study protocol and further details of the methods are described in Supplement 2.

Patients

Patients 18 years or older who had positive test results with reverse-transcription polymerase chain reaction (RT-PCR) assay for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in oropharyngeal samples were eligible if they had pneumonia as confirmed by chest imaging and a PBL cell count of 800 per μL (to convert to ×109/L, multiply by 0.001) or lower. Patients were excluded if they had a peripheral blood leukocyte cell count greater than 15 000 per μL, any comorbidity (eg, chronic obstructive pulmonary disease, hypertension, diabetes, coronary heart disease, and/or malignancy), required invasive ventilation, developed shock or other organ failure that required admission to an intensive care unit, had an allergy to rhG-CSF, or were breastfeeding or pregnant.

Randomization and Masking

Eligible patients were randomized in a 1:1 ratio to receive either usual care alone or usual care plus rhG-CSF (GRAN; Kyowa Hakko Kirin China Pharmaceutical Co Ltd; 5 μg/kg, subcutaneously once daily, from days 0 to 2). Usual care comprised supplemental oxygen, noninvasive ventilation, or intravenous antibiotics when indicated. Randomization was stratified by the center and oxygen therapy (nasal cannula or mask, or high-flow oxygen, noninvasive ventilation). A statistician who was masked to trial allocation generated the permuted block (4 patients per block) randomization sequence by using SAS software (version 9.4; SAS Institute). Randomization was conducted by using the Interactive Voice Response service provided by Guangzhou University. The allocation team was masked to the block size and random allocation table. A placebo-controlled trial was not performed because of the outbreak emergency.

Procedures

Patients were dynamically monitored daily by trained physicians. Diary cards were dispensed to investigators to collect a 7-category ordinal scale and safety score from day 0 to day 21, hospital discharge, or death. The remaining clinical data were gathered from the customized case report form on which information from the clinical charts was recorded.

Serial oropharyngeal swab specimens were obtained on days 1 (before rhG-CSF injection), 3, 5, 7, 10, 14, and 21 until discharge or death and were subject to real-time RT-PCR assays. Viral RNA was extracted with Nucleic Acid Isolation Kit (category DA0630) on an automatic workstation Smart 32 (Da’an Gene Corporation). The RT–PCR reagent (category DA0930; Da’an Gene Corporation) was used for viral detection. Briefly, 2 PCR primer and probe sets that targeted the ORF1ab (FAM reporter) and N genes (VIC reporter) separately were added. Positive and negative controls were included for each batch of detection. A cycle threshold (Ct) of less than 37 was defined as positive, and a Ct of 40 or greater was defined as negative and recorded as 40. Oropharyngeal swab samples were obtained for 200 patients at every point. Higher Cts indicated lower viral loads. Sampling was continued regardless of the findings.

Peripheral blood samples were obtained on days 1, 3, 5, 7, 10, and 14 and processed to isolate peripheral blood mononuclear cells by density gradient centrifugation. Isolated peripheral blood mononuclear cells were stained with BD multitest IMK kit (category 340503; BD Biosciences). The total T, CD4+ T, CD8+ T, B, and NK cells were enumerated by flow cytometry on an LSR Fortessa Cell Analyzer (BD Biosciences) and analyzed using the FlowJo software (TreeStar). Safety was also evaluated based on the Good Clinical Practice principles. Supplement 2 provides further details.

Outcome Measures

The primary end point was the time to clinical improvement,18 ie, the duration from randomization to the improvement of at least 1 point on a 7-category ordinal scale (adopted from a scale for hospitalized patients with severe influenza)19 or discharge from hospital, whichever occurred first. The 7-category ordinal scale was graded based on the following scheme: 1 for nonhospitalized with normal activities; 2 for nonhospitalized but unable to resume normal activities; 3 for hospitalized but not requiring supplemental oxygen; 4 for hospitalized and requiring supplemental oxygen; 5 for hospitalized and requiring nasal high-flow oxygen therapy, noninvasive mechanical ventilation, or both; 6 for hospitalized and requiring extracorporeal membrane oxygenation, invasive ventilation, or both; and 7 for death.

Secondary outcomes included lymphocyte cell counts on day 5 posttreatment, mortality at day 21, the proportions of patients progressing to critical conditions (eg, acute respiratory distress syndrome, sepsis, or septic shock), and viral loads (reflected by the Ct values as measured with real-time RT-PCR assays) at day 21. Safety outcomes included adverse events, serious adverse events, and premature discontinuation of treatment. Classifications were based on National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0.

Statistical Analysis

A detailed description of the statistical analysis plan is provided in Supplement 3. Assuming a 2-sided significance level of P < .05, the median duration of illness of 14 days in usual care group, and 140 patients (70%) achieving clinical improvement, 192 patients (96%) would be needed to provide a power of 90% to detect a 6-day difference in the median time to clinical improvement.

Efficacy assessment was based on the intention-to-treat population, ie, all patients who were randomized. A sensitivity analysis was performed based on the actual treatment exposure (2 patients [1%] randomized to the rhG-CSF group who did not receive rhG-CSF were included in the usual care group). The safety population consisted of participants who received at least 1 dose of the study drug.

The time to clinical improvement was assessed by reviewing all patients who had reached day 21. Right censoring at day 21 was conducted in case of a failure to reach clinical improvement. Death that occurred before day 21 was treated as not improved and analyzed as the competing risk event. The cumulative incidence function plot was used to demonstrate the time to clinical improvement, with the Gray test being applied for the between-group comparisons. The Fine and Gray proportional subdistribution hazards model adjusting for the center and the oxygen therapy was used to calculate the hazard ratios (HRs) and the 95% confidence intervals.20 The time to death was compared by the log-rank test, and the HR with 95% CIs were estimated by the Cox proportional hazards model. The difference in the day-21 mortality and proportion of patients progressing to critical conditions was expressed as the difference of the rate and the Newcombe hybrid score 95% CIs.21 The difference in the median hospital stay and oxygen support days were analyzed by using the Hodges-Lehmann estimate, along with 95% CIs.22 The change from baseline in the viral load, posttreatment PBL, leukocyte, CD8+T, and NK cell counts was compared by using a linear mixed-effect model, with the baseline level being the covariate. Because lymphocyte cell counts reportedly correlated with the outcomes of viral pneumonia, a predefined subgroup analysis was performed based on the cutoff of 400 per μL (patients requiring high-flow nasal cannula oxygen therapy or noninvasive mechanical ventilation consistently had PBL cell counts ≤400/μL). A predefined subgroup analysis based on age, sex, and oxygen therapy was also performed. Safety analyses were based on actual treatment exposure. As we did not adjust for the multiplicity of secondary analyses, the uncorrected 95% CIs cannot be used to definitively infer therapeutic effects. All analyses were conducted with SAS software (version 9.4; SAS Institute).

Results

Of 329 patients with COVID-19 who underwent screening, 117 (35.6%) did not meet eligibility criteria, and consent was not obtained from family guardians for 12 (3.6%). Therefore, 100 patients were assigned to receive rhG-CSF plus usual care and 100 usual care alone. Ninety-eight patients in the rhG-CSF group received treatment as assigned and were included in the safety population (Figure 1). Two patients did not receive rhG-CSF, as the treatment was declined after randomization.

Table 1 presents the baseline demographic and clinical characteristics of the participants. The median age was 45 years (interquartile range [IQR], 40-55 years), and 112 (56%) were men. The median interval was 6 days (IQR, 5-8 days) from symptom onset to randomization and 2 days (IQR, 2-3 days) from hospital admission to randomization. Both groups were well matched for baseline variables. Systemic corticosteroids were administered for 25 patients (12.5%) in the rhG-CSF group and 32 patients (16%) in the usual care group. Lopinavir-ritonavir, arbidol, and α-interferon inhalation were administered in 14%, 16%, and 8% of patients in the rhG-CSF group before enrollment, respectively. These figures were 17%, 20%, and 10% in the usual care group, respectively (Table 1). Other treatments at enrollment are shown in eTable 1 in Supplement 2.

In the intention-to-treat analysis, the time to clinical improvement did not differ between the rhG-CSF group and the usual care groups (median [IQR]: 12 [10-16] vs 13 [11-17] days; HR, 1.28; 95% CI, 0.95-1.71; Figure 2; Table 2). However, a sensitivity analysis based on actual treatment exposure showed a modest difference in the time to clinical improvement in the rhG-CSF group (median [IQR], 12 [10-16] vs 13 [11-17] days; HR, 1.34; 95% CI, 1.00-1.79) (eTable 2 in Supplement 2). In the subgroup analysis, rhG-CSF had greater effects on time to clinical improvement in patients with a PBL cell count 400 per μL or less (rhG-CSF group median [IQR] of 12 [9-15] vs usual care group median of 14 [11-18] days; HR, 1.86; 95% CI, 1.23-2.83) compared with patients with a PBL cell count of more than 400 per μL (rhG-CSF group median [IQR] of 12 [11-17] vs usual care group median [IQR] of 12 [10-17] days; HR, 0.92; 95% CI, 0.64-1.33). The rhG-CSF also had greater effects on the time to clinical improvement in patients requiring high-flow nasal cannula oxygen therapy or noninvasive mechanical ventilation (rhG-CSF group median [IQR] of 9.5 [8-11] vs usual care group median of 11 days; HR, 2.06; 95% CI, 1.16-3.67). No significant inconsistent treatment effects on the time to clinical improvement across age and sex subgroups were observed (eFigure 1 in Supplement 2).

The proportion of patients developing critical conditions was lower in the rhG-CSF group compared with the usual care group (2% vs 15%; difference, −13%; 95% CI, −21.4% to −5.4%). The 21-day fatality rate was 2% in the rhG-CSF group compared with 10% in the usual care group (HR, 0.19; 95% CI, 0.04-0.88; Table 2). eTable 3 in Supplement 2 summarizes the information about the patients who died; eTable 4 in Supplement 2 presents more information about death rates. There were no significant differences between the groups for the duration of hospitalization and oxygen support (Table 2).

The dynamic changes in leukocyte and lymphocyte cell counts are shown in eFigures 2, 3, and 4 in Supplement 2. Leukocyte cell counts increased rapidly and then generally plateaued after day 5 in the rhG-CSF group (eFigure 2 in Supplement 2). At day 5, the median lymphocyte cell count was significantly higher in the rhG-CSF group (rhG-CSF group median [IQR] of 1050/μL [900-1200/μL] vs a usual care group median [IQR] of 620/μL [480-740/μL]; Hodges-Lehmann estimate of the difference in medians, 440; 95% CI, 380-490). Similar findings applied at days 7 and 10. The rhG-CSF rapidly increased CD8+ cell counts (which plateaued at day 5), although the difference was less pronounced at day 14. There was a significant, albeit modest, increase in NK cell counts at days 5, 7, and 10 in the rhG-CSF group compared with the usual care group (eFigure 3 in Supplement 2). The trend of increases in peripheral blood CD4+ T cell and B cell counts was comparable between the 2 groups despite more prominent increases in rhG-CSF group at certain points (eFigure 4 in Supplement 2).

Sixty-one patients in the rhG-CSF group (30.5%) and 58 in the usual group (29%) had available virologic data, whereas the others had undetectable viral RNA on oropharyngeal swabs. Mean (SD) baseline Cts of SARS-CoV-2 in rhG-CSF group were lower than that in the usual care group (29.3 [5.2] vs 31.0 [4.2]) (Table 1). Overall, viral RNA loads over time did not differ between the 2 groups. However, the viral RNA loads declined more rapidly in rhG-CSF group at day 10 (Mean [SD] Ct of Orf1b gene, 37.9 [2.5] vs 36.9 [3.0]; mean difference, 1.2; 95% CI, 0.1-2.3) (eFigure 5 in Supplement 2).

Adverse events occurred in 91 of 98 patients (92.9%) in the rhG-CSF group and 47 of 102 patients (46.1%) in the usual care group. Muscular soreness, osteodynia, rash, fatigue, nausea, and vomiting were most common. The incidence of osteodynia, muscular soreness, fatigue, increased lactate dehydrogenase, and alkaline phosphatase levels was higher in the rhG-CSF group. Serious adverse events occurred in 29 of 98 (29.6%) in the rhG-CSF group and 42 of 102 patients (41.2%) in the usual care group. Respiratory failure (defined by the partial pressure of arterial blood oxygen being <60 mm Hg while breathing room air), acute respiratory distress syndrome, sepsis, and septic shock were more common in the usual care group. Six patients in the rhG-CSF group developed severe leukocytosis based on a leukostasis grading score.23 There were no anaphylactic or delayed hypersensitivity reactions (Table 3).

The therapeutic effects of rhG-CSF were inconsistent among the subgroups with different PBL cell counts and oxygen therapy. Because our main study assumption was that rhG-CSF modulated the trafficking of PBL (including lymphocyte subpopulations) and patients requiring high-flow nasal cannula oxygen therapy or noninvasive mechanical ventilation consistently had PBL cell counts of 400 per μL or less (eTable 5 in Supplement 2), we performed a post hoc subgroup analysis based on PBL cell counts (≤400/μL and >400/μL) (eTables 6 and 7 and eFigures 6, 7, 8, and 9 in Supplement 2). In these analyses, rhG-CSF was associated with accelerated clinical improvement and a decreased rate of progression to critical conditions or death in patients with a PBL cell count of 400 per μL or less (eTable 6 in Supplement 2).

Discussion

In preliminary findings from a randomized clinical trial, treatment of patients with COVID-19 with lymphopenia and no comorbidities did not change the time to clinical improvement. However, rhG-CSF treatment led to rapid restoration of the lymphocyte (including subsets) and NK cell counts and appeared to decrease the frequency of patients progressing to critical illness or death.

The aberrant immune responses, characterized by severe lymphopenia and leukopenia and exhaustion of NK cells,24 contribute to the poor outcomes of some patients with COVID-19. In this study, rhG-CSF led to a sustained increase in lymphocyte (including subsets) and NK cell counts. By contrast, in an observational study, no significant effect of rhG-CSF on NK cell count was identified,17 which might have stemmed from the difference in study design and population.

Adverse events were mostly classified as mild to moderate. Serious adverse events (ie, sepsis or septic shock, respiratory failure, and acute respiratory distress syndrome) were less common in the rhG-CSF group. Because patients with comorbidities might have more contraindications for rhG-CSF treatment, this study was enriched for young patients without comorbidities. The exclusion of patients without comorbidities might have accounted for the low fatality rate (approximately 7%). Furthermore, the lower incidence of sepsis in the rhG-CSF group might be associated with the increased leukocyte cell count. Our findings also suggest that caution should be exercised in patients with leukocytosis. Leukocytosis was observed in nearly 90% of patients receiving rhG-CSF (6 of whom had severe leukocytosis). However, capillary obstruction leading to organ infarction was not documented.

Limitations

This study has limitations. First, it was limited by its small size and the observational time frame of 21 days, within which discharge from hospital or death might not have been documented. Second, the open-label trial design might have affected the outcome measures. However, most of the measures on the 7-category ordinal scare were objective, thus the risk of biased findings was minimized. Third, we did not exclude patients who had received antiviral therapy or systemic corticosteroids before enrollment, which could have confounded the findings. Finally, we excluded patients who had comorbidities to minimize the potential adverse effects of other comorbidities on the immune responses of patients and also the potential for adverse events related to rhG-CSF treatment.

Conclusions

Whether our findings may apply to other groups of patients with COVID-19 merits further investigation. Larger studies that include a broader range of patients with COVID-19 should be conducted.

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Article Information

Accepted for Publication: August 18, 2020.

Corresponding Author: Nan-shan Zhong, MD, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, 151 Yanjiang Rd, Guangzhou, Guangdong 510120, China (nanshan@vip.163.com).

Published Online: September 10, 2020. doi:10.1001/jamainternmed.2020.5503

Author Contributions: Drs Lin-ling Cheng and Duan had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Lin-ling Cheng, Guan, and Duan are co–first authors. Dr Zhong was the guarantor of the study.

Concept and design: L-l. Cheng, Duan, N-f. Zhang, A-l. Chen, S-y. Li, Zhuo, J-h. Zhang, P-y. Chen, C-y. Wang, Zhong.

Acquisition, analysis, or interpretation of data: L-l. Cheng, Guan, Duan, Lei, Hu, Deng, F-j. Cheng, Gao, J-h. Zhang, Xie, Hong Peng, Y-s. Li, Wu, Liu, Hui Peng, J. Wang, Xiao, P-y. Chen, Yang, Zhao, Zhong.

Drafting of the manuscript: L-l. Cheng, Guan, N. Zhang, Lei, A. Chen, S-y. Li, J-h. Zhang, Xie, Hong Peng, Hui Peng, J. Wang, P-y. Chen, Zhong.

Critical revision of the manuscript for important intellectual content: L-l. Cheng, Guan, Duan, Lei, Hu, Zhuo, Deng, F-j. Cheng, Gao, J. Zhang, Y-s. Li, Wu, Liu, Xiao, P-y. Chen, C-y. Wang, Yang, Zhao, Zhong.

Statistical analysis: Duan, J-h. Zhang, Wu, Liu, P-y. Chen.

Obtained funding: L-l. Cheng, J-h. Zhang.

Administrative, technical, or material support: L-l. Cheng, N-f. Zhang, Lei, Hu, A-l. Chen, S-y. Li, Zhuo, Deng, Gao, J-h. Zhang, Xie, Y. Li, Wu, J. Wang, Xiao, C-y. Wang, Yang, Zhao, Zhong.

Supervision: L-l. Cheng, N-f. Zhang, J-h. Zhang, Zhong.

Conflict of Interest Disclosures: Dr L. Cheng reported grants from Guangzhou Institute of Respiratory Health during the conduct of the study. No other disclosures were reported.

Funding/Support: The study was supported by grants related to the prevention and management of coronavirus disease 2019 and Guangzhou Institute for Respiratory Health. We thank Kyowa Hakko Kirin China Pharmaceutical Co Ltd for their provision of the recombinant human granulocyte colony-stimulating factor.

Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Data Sharing Statement: See Supplement 4.

References
1.
World Health Organization. WHO coronavirus disease (COVID-19) dashboard. Accessed August 11, 2020. https://covid19.who.int/
2.
Huang  C, Wang  Y, Li  X,  et al.  Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.   Lancet. 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5 PubMedGoogle ScholarCrossref
3.
Guan  WJ, Ni  ZY, Hu  Y,  et al; China Medical Treatment Expert Group for Covid-19.  Clinical characteristics of coronavirus disease 2019 in China.   N Engl J Med. 2020;382(18):1708-1720. doi:10.1056/NEJMoa2002032 PubMedGoogle ScholarCrossref
4.
Chen  N, Zhou  M, Dong  X,  et al.  Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study.   Lancet. 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7 PubMedGoogle ScholarCrossref
5.
Yang  X, Yu  Y, Xu  J,  et al.  Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study.   Lancet Respir Med. 2020;8(5):475-481. doi:10.1016/S2213-2600(20)30079-5 PubMedGoogle ScholarCrossref
6.
Zhou  F, Yu  T, Du  R,  et al.  Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study.   Lancet. 2020;395(10229):1054-1062. doi:10.1016/S0140-6736(20)30566-3 PubMedGoogle ScholarCrossref
7.
Wang  D, Hu  B, Hu  C,  et al.  Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China.   JAMA. 2020. doi:10.1001/jama.2020.1585 PubMedGoogle Scholar
8.
Tan  L, Wang  Q, Zhang  D,  et al.  Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study.   Signal Transduct Target Ther. 2020;5(1):33. doi:10.1038/s41392-020-0148-4 PubMedGoogle ScholarCrossref
9.
Zhao  H, Guo  M, Sun  X,  et al.  Effects of recombinant human granulocyte colony-stimulating factor on central and peripheral T lymphocyte reconstitution after sublethal irradiation in mice.   J Radiat Res. 2013;54(1):83-91. doi:10.1093/jrr/rrs082 PubMedGoogle ScholarCrossref
10.
Ang  CC, Tay  YK.  Hematological abnormalities and the use of granulocyte-colony-stimulating factor in patients with Stevens-Johnson syndrome and toxic epidermal necrolysis.   Int J Dermatol. 2011;50(12):1570-1578. doi:10.1111/j.1365-4632.2011.05007.x PubMedGoogle ScholarCrossref
11.
Koizumi  T, Kubo  K, Koyama  S,  et al.  Neutrophils pretreated with granulocyte colony-stimulating factor (G-CSF) are not related to the severity of endotoxin-induced lung injury.   Exp Lung Res. 1997;23(5):393-404. doi:10.3109/01902149709039234 PubMedGoogle ScholarCrossref
12.
Li  JG, Zhang  YJ, Wu  W,  et al  Effect of recombinant human granulocyte colony-stimulating factor on leukopenia in severe acute respiratory syndrome patients.   Yi Shi Jin Xiu Za Zhi. 2004; 27:21-22. doi:10.3760/cma.j.issn.1673-4904.2004.23.008Google Scholar
13.
Kimura  S, Matsuda  J, Ikematsu  S,  et al.  Efficacy of recombinant human granulocyte colony-stimulating factor on neutropenia in patients with AIDS.   AIDS. 1990;4(12):1251-1255. doi:10.1097/00002030-199012000-00011 PubMedGoogle ScholarCrossref
14.
Zhao  SS, Fang  S, Zhu  CY, Wang  LL, Gao  CJ.  Effect of G-CSF in vitro stimulation on distribution of peripheral lymphocyte subsets in the healthy persons [article in Chinese].   Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2018;26(1):258-262.PubMedGoogle Scholar
15.
Melve  GK, Ersvaer  E, Eide  GE, Kristoffersen  EK, Bruserud  Ø.  Peripheral blood stem cell mobilization in healthy donors by granulocyte colony-stimulating factor causes preferential mobilization of lymphocyte subsets.   Front Immunol. 2018;9:845. doi:10.3389/fimmu.2018.00845 PubMedGoogle ScholarCrossref
16.
San Miguel  JF, Hernández  MD, Gonzalez  M,  et al.  A randomized study comparing the effect of GM-CSF and G-CSF on immune reconstitution after autologous bone marrow transplantation.   Br J Haematol. 1996;94(1):140-147. doi:10.1046/j.1365-2141.1996.d01-1756.x PubMedGoogle ScholarCrossref
17.
Rondelli  D, Raspadori  D, Anasetti  C,  et al.  Alloantigen presenting capacity, T cell alloreactivity and NK function of G-CSF-mobilized peripheral blood cells.   Bone Marrow Transplant. 1998;22(7):631-637. doi:10.1038/sj.bmt.1701413 PubMedGoogle ScholarCrossref
18.
World Health Organization. Coronavirus disease (COVID-2019). Accessed September 1, 2020. https://www.who.int/blueprint/priority-diseases/key-action/novel-coronavirus/en/
19.
International Severe Acute Respiratory and Emerging Infections Consortium. ISARIC home page. Accessed September 1, 2020. https://isaric.tghn.org/
20.
Fine  JP, Gray  RJ.  A proportional hazards model for the subdistribution of a competing risk.   J Am Stat Assoc. 1999;94:496-509. doi:10.1080/01621459.1999.10474144 Google ScholarCrossref
21.
Newcombe  RG.  Interval estimation for the difference between independent proportions: comparison of eleven methods.   Stat Med. 1998;17(8):873-890. doi:10.1002/(SICI)1097-0258(19980430)17:8<873::AID-SIM779>3.0.CO;2-I PubMedGoogle ScholarCrossref
22.
Hodges  JL  Jr, Lehmann  EL.  Estimates of location based on rank tests.   Ann Math Stat. 1963;34:598-611. doi:10.1214/aoms/1177704172 Google ScholarCrossref
23.
Piccirillo  N, Laurenti  L, Chiusolo  P,  et al.  Reliability of leukostasis grading score to identify patients with high-risk hyperleukocytosis.   Am J Hematol. 2009;84(6):381-382. doi:10.1002/ajh.21418 PubMedGoogle ScholarCrossref
24.
Xu  Z, Shi  L, Wang  Y,  et al.  Pathological findings of COVID-19 associated with acute respiratory distress syndrome.   Lancet Respir Med. 2020;8(4):420-422. doi:10.1016/S2213-2600(20)30076-X PubMedGoogle ScholarCrossref
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