1 Introduction
As of July.1, 2020, coronavirus disease 2019 (COVID-19)[1] has resulted in more than 10 million cases and more than 500 000 deaths worldwide.[2] The worldwide spread of COVID-19 represents a profound threat to human health. However, currently, no specific anti-coronaviral drugs have been approved for the treatment of COVID-19, and no vaccine is available for preventing COVID-19. As of May 27, 2020, the interim guideline of World Health Organization recommend that chloroquine and hydroxychloroquine (+/- azithromycin), lopinavir/ritonavir, remdesivir, tocilizumab, interferon-β-1a, not be administered as treatment or prophylaxis for COVID-19, and safe supportive therapies were the cornerstone of therapy for patients.[3]
In China, Traditional Chinese Medicine (TCM) has a long history and has played an important role in the prevention and treatment of serious epidemic diseases.[4–6] According to the Diagnosis and Treatment Protocol for Coronavirus Pneumonia (Trial version 7), Lianhuaqingwen (LH), a Traditional Chinese Patent Medicine formula including 13 herbs (Table 1), has been recommended by the National Health Commission for the treatment of COVID-19.[7] One prospective multicenter, randomized controlled trial (RCT) involving 284 patients with COVID-19 had shown that LH plus usual treatment could significantly improve the recovery rate (91.5% vs 82.4%) and short the time to symptom recovery (median: 7 days vs 10 days) as compared to usual treatment only.[8] However, an individual trial was limited by the small number of patients included. Therefore, we performed this study to evaluate the efficacy and safety of LH in combination with usual treatment vs usual treatment alone in treating COVID-19 by a meta-analysis of available evidence from randomized trials.
Table 1 -
The formulation of LH.
| Local Name |
Herb |
Medicinal parts |
Notes |
| Ma Huang |
Ephedra sinica Stapf. |
Herbaceous stem |
|
| Ku Xing Ren |
Prunus armeniaca L. |
Seed |
1. The China State Food and Drug Administration approved LH in 2004. |
| Lian Qiao |
Forsythia suspensa (Thunb.)Vahl. |
Fruit |
|
| Bo He |
Mentha haplocalyx Briq. |
Herba |
|
| Ban Lan Gen |
Isatis indigotica Fort. |
Roots |
|
| Yu Xing Cao |
Houttuynia cordata Thunb. |
Herba |
|
| Guan Zhong |
Dryopteris crassirhizoma Nakai. |
Rhizome |
2.LH were manufactured Shijiazhuang Yiling Pharmaceutical Co. Ltd. |
| Jin Yin Hua |
Lonicera japonica Thunb. |
Flower |
|
| Shi Gao |
Gypsum fibrosum |
Mineral substance |
|
| Da Huang |
Rheum palmatum L. |
Roots and rhizomes |
3.LH have two formulations: capsule and granule |
| Guang Huo Xiang |
Pogostemon cablin (Blanco)) Benth. |
Herba |
|
| Hong Jing Tian |
Rhodiola crenulata (Hook.f.et Thoms.) H.Ohba. |
Roots and rhizomes |
|
| Gan Cao |
Glycyrrhiza uralensis Fisch. |
Roots and rhizomes |
|
2 Methods
This meta-analysis was performed and reported according to Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA). Patient consent and ethical approval were not required for this study because it was a meta-analysis of published studies.[9]
2.1 Search strategy
We systematically searched Medline (OVID), Embase, the Cochrane Library, and 4 Chinese databases (including China National Knowledge Infrastructure (CNKI) database, Wanfang Data Knowledge Service Platform, Chinese Biomedicine Literature Database, and Chinese Sci-tech Journals Database) from inception to July 2020 using relevant search terms. The search strategy of PubMed was presented in Table 2. We limited the language of articles to English and Chinese only. We also manually searched the reference list of the included studies and ClinicalTrials.gov as a supplementary source for the literature search.
Table 2 -
Example of PubMed search strategy.
| Number |
Search Terms |
| 1 |
Mesh descriptor: (Lianhuaqingwen) explode all trees |
| 2 |
((((((Lian-Hua Qing-Wen [Title/Abstract]) OR Lianhuaqingwen Capsule [Title/Abstract]) OR LianHua QingWen [Title/Abstract]) OR Lianhua Qingwen [Title/Abstract]) OR Lianhuaqingwen granule [Title/Abstract]) |
| 3 |
Or 1–2 |
| 4 |
Mesh descriptor: (COVID-19) explode all trees |
| 5 |
((((((2019 novel coronavirus infection[Title/Abstract] OR 2019-nCoV infection[Title/Abstract]) OR COVID-19 pandemic[Title/Abstract]) OR coronavirus disease-19[Title/Abstract]) OR 2019-nCoV disease[Title/Abstract]) OR COVID19[Title/Abstract]) OR 2019 novel coronavirus disease[Title/Abstract]) OR coronavirus disease 2019[Title/Abstract] |
| 6 |
Or 4–5 |
| 7 |
3 and 6 |
2.2 Study selection and outcome measures
Three investigators (ZF, YY, and YL) independently selected eligible studies according to the predefined inclusion criteria and exclusion criteria. Included trials must meet the following criteria:
- 1. RCTs or randomized crossover trials (RTs);
- 2. Laboratory-confirmed and suspected cases with COVID-19;
- 3. Patients aged 18 years or greater;
- 4. The interventional group was LH in combination with usual treatment, and the control group was usual treatment alone.
The trials would be excluded if:
- 1. duplicates;
- 2. reviews and conference abstracts;
- 3. severe COVID-19 patients;
- 4. severe systemic diseases (i.e., malignancy, autoimmune diseases, liver or renal diseases);
- 5. asthma or other chronic airway diseases needing maintenance therapy, acute respiratory tract bacterial infection (i.e., bronchiectasis, tonsillitis, bronchitis, rhinosinusitis, otitis media), severe pulmonary interstitial diseases;
- 6. women during pregnancy or lactation.
We screened the titles and abstracts for potential studies in the first screening and then reviewed the full texts of these potential studies in the second screening. The primary outcomes included overall clinical efficacy and safety outcomes, and the secondary outcomes included the conversion to severe cases, the duration of fever, and improvement in chest computed tomographic manifestations. The overall clinical efficacy was defined as the complete resolution of fever, fatigue, and coughing.[8] Any disagreements were resolved through discussion, and if necessary, a third investigator (HT) was consulted.
2.3 Data extraction and quality assessment
Three reviewers (ZF, YY, and YL) extracted the data according to a predesigned data-collection form. We included the following data: authors, publication year, participant characteristic (participation eligibility criteria, gender, and age), intervention information, and outcomes of interest. We assessed the risk of bias of included RCTs and RTs using the Cochrane risk of bias assessment tool.[10] In the case of missing data, we contacted the authors of eligible studies for clarifications. Any disagreements about data extraction and quality assessment were resolved through discussion among all authors.
2.4 Statistical analysis
We compared the treatment effect through meta-analysis in an intention to treat manner (following the allocation of participants in studies). We calculated the mean differences (MDs) and their 95% confidence intervals (CIs) for continuous outcomes and risk ratios (RRs) for binary outcomes. Statistical heterogeneity was assessed using the Chi-Squared test and I2 test. We used a fixed-effects model (FEM) if I2 < 50%, otherwise, a random-effects model (REM) was used. A funnel plot was performed to assess the publication bias if more than 8 trials were included, accordingly no publication bias assessment was performed due to only 5 trials included in this study performed. The data analysis was performed using RevMan version 5.3 software and P < .05 was considered statistically significant.
3 Results
3.1 Search results
Fifty two relevant records were retrieved from the electronic databases and 27 records were left after removing duplicates. Of these, 20 were excluded after title/abstract screening and 7 reports were eligible for full-text review. After full-text review, we excluded 2 reports for the following reason: 2 studies did not compare LH in addition to usual treatment with usual treatment alone. Finally, we included 5 articles involving 824 patients.[8,11–14] The process of literature search and study selection was presented in Figure 1.
;)
Figure 1: Flowchart of study selection.
3.2 Study characteristics and quality assessment
The basic characteristics of the 5 trials were presented in Table 3. Of the 824 patients with mild or moderate COVID-19, 448 were males and 376 were females, with ages ranging from 18 to 75 years. All 5 trials were performed in China. Usual treatment generally involved supportive treatment such as oxygen therapy, antiviral medications, and symptomatic therapies. The dose of LH was 4 capsules thrice daily[8] or 1 packet thrice daily.[11–14] The duration of treatment were 7 days,[11,13] 10 days[12], and 14 days[8].
Table 3 -
Characteristics of included studies.
|
Patients |
Intervention |
|
| Studies |
Disease |
T/C |
M/F |
Age (years) |
Treatment group |
Control group |
Duration (days) |
Outcomes |
| Hu 2020 |
Confirmed |
142/142 |
150/134 |
≥18 |
LH capsules (4 capsules thrice daily) in combination with usual treatment |
usual treatment including oxygen therapy, antiviral medications, and symptomatic therapies |
14 |
O1,O2,O3,O4,O5, |
| Yu 2020 |
Confirmed |
147/148 |
171/124 |
18-75 |
LH granules (1 packet thrice daily) in combination with usual treatment |
usual treatment including abidol (0.2g,tid)+ moxifloxacin (0.4g,qd)+ ambroxol (30 mg,tid) |
7 |
O1, O2, O4, |
| Lv 2020 |
Suspected |
63/38 |
46/55 |
≥18 |
LH granules (1 packet thrice daily) in combination with usual treatment |
usual treatment including nutritional support, symptomatic treatment, antiviral and antibiotic drug treatment |
10 |
O2,O5 |
| Cheng 2020 |
Confirmed |
51/51 |
53/49 |
18-70 |
LH granules (1 packet thrice daily) in combination with usual treatment |
usual treatment including nutritional support, symptomatic treatment, antiviral and antibiotic drug treatment |
7 |
O1, O2,O3,O4, |
| Yao 2020 |
Confirmed |
21/21 |
28/14 |
≥18 |
LH granules (1 packet thrice daily) in combination with usual treatment |
usual treatment recommended in the Diagnosis and Treatment Protocol for Coronavirus Pneumonia (Trial version 4) |
— |
O3 |
T = treatment group, C = control group, O1 = overall clinical efficacy, O2 = conversion to severe cases, O3 = the duration of fever, O4 = improvement in chest computed tomographic manifestations, O5 = safety, —, unclear.
Of the 5 trials included, 4 trials[8,11,13,14] reported random sequence generation. Only one trial[8] reported allocation concealment and blinding (outcome assessor). No blinding (participants) was implemented in all trials. None of the included trials had selective reporting. All trials have a low risk of incomplete outcome data. And, the baseline data of all trials was comparative (Fig. 2).
Figure 2: Summary of risk of bias assessment of each trial.
3.3 Efficacy outcomes
3.3.1 Overall clinical efficacy
Of the 5 trials included, 3 trials[8,11,13] with 681 cases reported the overall clinical efficacy of LH combination with usual treatment. There was no statistical heterogeneity among the trials (P = .92, I2 = 0%). Therefore, the data were synthesized using FEM. Meta-analysis showed that LH in combination with usual treatment could significantly improve the overall clinical efficacy as compared to usual treatment alone (RR = 2.39, 95% CI 1.61–3.55, P < .0001) (Fig. 3A).
Figure 3: Effects of Lianhuaqingwen in combination with usual treatment on the following outcomes (A) overall clinical efficacy; (B) conversion to severe cases; (C) improvement in chest computed tomographic manifestations compared to usual treatment only in patients with mild or moderate COVID-19. COVID-19 = coronavirus Disease 2019.
3.3.2 The conversion to severe cases
Four trials[8,11,12,13] involving 782 cases reported the rate of the conversion to severe cases There was no statistical heterogeneity among the trials (P = .85, I2 = 0%). The meta-analysis using FEM showed that LH in combination with usual treatment was significantly associated with a lower rate of conversion to severe cases than usual treatment alone (RR = 0.47, 95% CI 0.29–0.74, P = .001) (Fig. 3B).
3.3.3 Improvement in chest computed tomographic manifestations
Three trials[8,11,13] with 456 cases reported the rate of improvement in chest computed tomographic manifestations. There was statistical heterogeneity among the trials (P = .11, I2 = 55%). Therefore, the data were synthesized using REM. Meta-analysis showed that LH in combination with usual treatment was significantly associated with a higher rate of improvement in chest computed tomographic manifestations as compared with usual treatment alone (RR = 1.80, 95% CI 1.08–3.01, P < .05) (Fig. 3C).
3.3.4 The duration of fever
Three trials[8,13,14] with 387 cases reported the duration of fever. There was no statistical heterogeneity among the trials (P = .85, I2 = 0%). Therefore, the data were synthesized using FEM. Meta-analysis showed that LH in combination with usual treatment could significantly shorten the duration of fever as compared to treatment alone [MD = −1.00, 95% CI −1.17, −0.84, Z = 11.77, P < .0001] (Fig. 4).
Figure 4: Effects of Lianhuaqingwen in combination with usual treatment on the duration of fever compared to usual treatment only in patients with mild or moderate COVID-19.
3.4 Safety outcomes
Two studies[8,12] reported adverse events during the follow-up periods. There was statistical heterogeneity among the trials (P = .08, I2 = 68%). Therefore, the data were synthesized using REM. Meta-analysis showed that there was no statistical significance between LH in combination with usual treatment and usual treatment alone (RR = 0.43, 95% CI 0.12–1.54, P = .19) (Fig. 5).
Figure 5: Effects of Lianhuaqingwen in combination with usual treatment on adverse events compared to usual treatment only in patients with mild or moderate COVID-19.
4 Discussion
To our knowledge, this is the first meta-analysis of randomized trials to evaluate the efficacy and safety of LH in combination with usual treatment for the treatment of COVID-19. Our results showed that LH in combination with usual treatment could significantly improve overall clinical efficacy, decrease the rate of conversion to severe cases, shorten the duration of fever, and increase the rate of improvement in chest computed tomographic manifestations compared to usual treatment alone. Moreover, LH in combination with usual treatment did not increase the occurrence of adverse events as compared to usual treatment alone.
During the development of the COVID-19 epidemic in China, TCM was widely used in treating COVID-19,[15] and was included in the guidelines for the diagnosis and treatment of COVID-19.[7] A total of 60,107 confirmed cases (more than 85% of COVID-19 patients) used TCM to treat COVID-19.[16] Among the commonly used TCMs, the most used one is LH. LH, which is a patented product, has been marketed since the outbreak of SARS in 2003 in China. LH which could suppress the replication of SARS-CoV,[17] H3N2, H1N1, and H7N9 in vitro,[18–21] has been endorsed by the National Health Commission for the treatment of SARS, MERS, influenza, and human infection with H7N9 avian influenza.[22–25] Previous research has shown that LH conferred suppression of the cytopathic effect of SARS-CoV-2 in vitro and reduced the viral loads in the cytoplasm and cellular membrane,[26] and regulated immune response to viral infection,[19] anti-inflammation,[27] anti-acute lung injury.[28] A series of studies have also been carried out to explore the targets and signaling pathways of LH for treating COVID-19 and explore its underlying mechanism.[29,30] LH was shown to have an anti-virus (coronavirus) effect, antipyretic and analgesic effect, immune-regulation, anti-inflammation, and anti-acute lung injury.[31]
There were some limitations in this study. Firstly, we only searched Chinese and English databases; all included trials were carried out in China. Secondly, the risk of bias of included trials was high. Only one trial clearly described the allocation concealment. No blinding was implemented in all trials because of the urgency of the outbreak that entailed a timely treatment, and a placebo-controlled trial would be unethical considering the rapid outbreak of communicable diseases such as COVID-19. Thirdly, statistical heterogeneity across trials was observed in some meta-analyses, which might be caused by differences in the usual treatment used and dose and duration of LH. However, we cannot further explore the source of heterogeneity using meta-regression or subgroup analysis due to the limited number of included studies. Finally, due to only 5 trials included in this meta-analysis, we did not perform a publication bias assessment, thus we cannot exclude the potential publication bias in this study.
In summary, the available evidence from available randomized trials showed that in patients with mild or moderate COVID-19, LH in combination with usual treatment might improve the clinical efficacy, decrease the rate of conversion to severe cases, shorten the duration of fever, and increase the rate of improvement in chest computed tomographic manifestations compared to usual treatment alone. However, given the limitations and poor quality of included trials in this study, further large-sample RCTs or high-quality real-world studies are needed to confirm our conclusions.
Author contributions
Conceptualization: Guiming Guo, Xiaoping Che, Luyang Li, Huilin Tang.
Data curation: Ying Yang, Yang Liu.
Formal analysis: Lijuan Han, Xiaorong Cai.
Writing – original draft: Zheng Fan, Xinyu Chang.
Writing – review & editing: Huilin Tang.
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