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Cochrane Database of Systematic Reviews Review - Intervention

Chinese medicinal herbs for influenza

Authors' declarations of interest

Version published: 28 March 2013 Version history

https://doi.org/10.1002/14651858.CD004559.pub4
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Background

Influenza is a communicable acute respiratory infection which, during epidemics, can cause high morbidity and mortality rates. Traditional Chinese medicinal herbs, often administered following a particular Chinese medical theory, may be a potential treatment of choice.

Objectives

To assess the effect of Chinese medicinal herbs used to prevent and treat influenza and to estimate the frequency of adverse effects.

Search methods

We searched CENTRAL (2012, Issue 11), MEDLINE (January 1966 to November week 2, 2012), EMBASE (January 1988 to November 2012) and CNKI (January 1988 to 29 March 2012). We also searched reference lists of articles and the WHO ICTRP search portal (November 2012).

Selection criteria

Randomised controlled trials (RCTs) comparing traditional Chinese medicinal herbs with placebo, no treatment or conventional medicine normally used in preventing and treating uncomplicated influenza.

Data collection and analysis

Two review authors independently extracted data and assessed trial quality.

Main results

We included 18 studies involving 2521 participants. The methodological quality of 17 included studies was poor. Included RCTs separately compared medicinal herbs with different antiviral drugs, precluding any pooling of results. Only three indicated that compared with antiviral drugs, Chinese medicinal herbs may be effective in preventing influenza and alleviating influenza symptoms. 'Ganmao' capsules were found to be more effective than amantadine in decreasing influenza symptoms and speeding recovery in one study (in which adverse reactions were mentioned in the amantadine group although no data were reported). There were no significant differences between 'E Shu You' and ribavirin in treating influenza, nor in the occurrence of adverse reactions. Ten studies reported mild adverse reactions.

Authors' conclusions

Most Chinese medical herbs in the included studies showed similar effects to antiviral drugs in preventing or treating influenza. Few were shown to be superior to antiviral drugs. No obvious adverse events were reported in the included studies. However, current evidence remains weak due to methodological limitations of the trials. More high‐quality RCTs with larger numbers of participants and clear reporting are needed.

PICOs

Population
Intervention
Comparison
Outcome

The PICO model is widely used and taught in evidence-based health care as a strategy for formulating questions and search strategies and for characterizing clinical studies or meta-analyses. PICO stands for four different potential components of a clinical question: Patient, Population or Problem; Intervention; Comparison; Outcome.

See more on using PICO in the Cochrane Handbook.

Plain language summary

available in

Chinese medicinal herbs for influenza

Influenza is a viral respiratory infection that causes an acute febrile illness with myalgia, headache and cough, and can result in high morbidity and mortality rates during an epidemic. Annual epidemics are thought to result in between three and five million cases of severe influenza and between 250,000 and 500,000 deaths worldwide. Currently, annual vaccination is the primary strategy for preventing influenza, and four influenza antiviral agents (amantadine, rimantadine, zanamivir and oseltamivir) have been approved for treatment of influenza. However, high levels of drug resistance have been recorded. Many Chinese medicinal herbs are used to treat and prevent this condition.

This updated review assessed the therapeutic effects and safety of Chinese medicinal herbs as an alternative and adjunctive therapy to other commonly used drugs for influenza. Eighteen studies involving 2521 participants were included in the review. 'Ganmao' capsules were found to be more effective than amantadine in decreasing influenza symptoms and aiding recovery in one study (in which adverse reactions were mentioned in the amantadine group although no data were reported). There were no significant differences between 'E Shu You' and ribavirin in treating influenza, nor in the occurrence of adverse reactions. The remaining 17 Chinese herbal trials showed a similar effect to antiviral drugs in preventing or treating influenza. However, since these included studies were of poor quality, the evidence does not support or reject the use of any Chinese herbal preparations for influenza. High‐quality trials are required.

Authors' conclusions

Implications for practice

The current evidence is too weak to draw a conclusion which supports or rejects the use of any Chinese medicinal herbs for preventing or treating uncomplicated influenza.

Implications for research

More studies, performed worldwide, with high methodological quality, large numbers of participants and good reporting are required to provide stronger evidence. Information on the conduct of trials should be reported in detail according to CONSORT (Moher 2010). The intervention in the control group should be a placebo, no treatment or the commonly used antiviral and antipyretic‐analgesic drugs, but not herbal medicines or a combination of drugs plus herbal medicines, until proved to be effective for influenza. Co‐interventions given equally to both arms are acceptable. The disease duration on entry should be restricted and if economics permit, laboratory tests (routine blood tests, serum tests or pathogenic examinations) and chest X‐rays should be conducted to define inclusion and exclusion criteria. Attention should also be paid to the definition of outcome measures and the incidence of adverse reactions.

Background

Description of the condition

Influenza is an acute respiratory illness caused by a virus from the Orthomyxoviridae family, of which three serotypes are known (A, B and C). Influenza causes an acute febrile illness with myalgia, headache and cough. Uncomplicated influenza generally resolves over a two to five‐day period. However, in a significant minority, symptoms of weakness and malaise may persist for several weeks, particularly in the elderly. Complications of influenza include otitis media, pneumonia, exacerbation of chronic respiratory disease, croup and bronchiolitis. Additionally, influenza can cause a range of non‐respiratory complications including febrile convulsions, Reyes's syndrome and myocarditis (Wiselka 1994). The influenza virus is transmitted primarily via virus‐laden large droplets from sneezing, coughing or talking. Transmission may also occur by direct (for example, person‐to‐person) or indirect (person‐to‐fomite‐to person) contact (CDC 2007).

Influenza virus types (A, B or C) are based on antigenic characteristics of the nucleoproteins and matrix protein antigens. However, the influenza virus genome is segmented and there is a high frequency of re‐arrangements of the genes (Ahmed 1996; Alves Galvão 2012). A major factor in determining the severity and spread of influenza outbreaks is the level of immunity present in the population at risk. When an antigenically new influenza virus emerges in a community where few or no antibodies are present, extensive outbreaks may occur (Claas 1998; Fleming 1999). Annual epidemics are thought to result in between three and five million cases of severe influenza and between 250,000 and 500,000 deaths worldwide (WHO 2003a). The outbreak in humans of an H5N1 avian influenza virus in Hong Kong in 1997 has increased awareness of our vulnerability to a global pandemic. Since late 2003 the accelerated geographical spread of influenza A (H5N1) among birds has heightened concerns. Up until December 2012, 610 confirmed cases of human infection with influenza A (H5N1) and 360 death in 15 countries has been reported to the World Health Organization (WHO) (WHO 2012).

Description of the intervention

Annual vaccination is recommended as the primary strategy for preventing influenza (WHO 2003b). Over‐the‐counter (OTC) medications for controlling influenza symptoms may be recommended and antiviral medications can be prescribed. Four influenza antiviral agents (amantadine, rimantadine, zanamivir and oseltamivir) have been approved by the US Food and Drug Administration (FDA). Amantadine and rimantadine are effective against influenza A viruses (Jefferson 2012). However, high levels of drug resistance have been recorded and the Advisory Committee on Immunization Practices (ACIP) recommends that neither amantadine nor rimantadine be used for the treatment or chemoprophylaxis of influenza A in the USA until susceptibility to these antiviral medications has been re‐established. Zanamivir and oseltamivir are neuraminidase inhibitors effective against both influenza A and B viruses. Oseltamivir is approved for the treatment of people aged over one year and zanamivir for people aged over seven years. These medications should be taken within two days after the onset of symptoms and continued for five to seven days. They have been shown to lessen both the severity and duration of uncomplicated influenza (Smith 2006). Careful use of these products is encouraged because of the emergence of resistant influenza strains (Moscona 2005). Dosing and side effects vary depending on the drug, age, and hepatic and renal functions. The major side effects tend to affect the central nervous system (CNS) and the gastrointestinal tract. Other side effects include light‐headedness, nervousness, anxiety, difficulty in concentration, diarrhea and anorexia. Use of amantadine in people aged > 65 years, among whom some degree of renal impairment is common, particular attention should be paid to dosages (NACI 2006).

Traditional Chinese medicine (TCM) follows a particular theoretical and methodological pathway for assessing cause, diagnosis and treatment. Chinese medicinal herbs, the most important component of TCM, are derived from plants and usually incorporate one or more herbs as the basic drug(s) to treat the disease. Depending upon the different symptoms or causes, the herbs are selected and mixed together, following a particular process, to form the prescription.

How the intervention might work

In TCM the aim in treating influenza is not only to cure the respiratory symptoms but also to treat the whole body. In TCM, influenza is differentiated into two types: Wind‐cold Syndrome and Wind‐heat Syndrome (Table 1). The main symptoms of the Wind‐cold type are: severe cold, slight fever, absence of sweat, headache, aching pain of extremities, stuffy nose with nasal discharge, cough with thin sputum, thin, whitish coating on the tongue and a floating and tight pulse (Zhao 2001). Treatment of this type aims to relieve external symptoms with drugs which are pungent in flavour and warm in property, and to ventilate the lungs and expel the pathogenic cold. Herba Schizonepetae, Radix Ledebouriellae, Radix Bupleuri, Radix Platycodi and Rhizoma Zingiberis Recens are usually the main components of a prescription for Wind‐cold Syndrome. Moreover, supplementary drugs may be added when particular symptoms are present (Wang 2012).

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Table 1. TCM definitions

TCM term

Definition

Qi

In the theory of TCM, 'qi' is considered as a life force or energy in every body. 'Qi' must be kept balanced and flow freely to keep organs working well. When 'qi' is blocked in a certain part of the body, the organs involved get sick and people can have a pain there. For example, constrained 'gan qi' should be released to make 'qi' flow freely so that the liver can work well and 'qi' should be regulated to flow freely so that pain is relieved. Similarly, when the 'qi' of the lungs is not balanced, such as by being lost ascending out, people may cough; 'qi' must therefore be put down to maintain an adequate amount of 'qi' in the lungs

Wind‐cold type cold

If manifested by more severe chilliness, slight fever and a tongue with thin, white fur, then it belongs to the exterior syndrome caused by wind and cold and should be treated with strong perspiration drugs which are pungent in taste and warm in property, to dispel the wind and cold

Wind‐heat type cold

If manifested by more severe fever, milder chilliness and a tongue with thin, yellow fur, then it belongs to the exterior syndrome caused by wind and heat

The main symptoms of Wind‐heat type are: a high fever, slight aversion to cold, headache, sore throat with congestion, expectoration of yellowish sputum, thirst, epistaxis, reddened tongue with a thin, yellowish coating and a floating and rapid pulse (Zhao 2001). Treatment of this type aims to: relieve external symptoms with drugs which are pungent in flavour and cool in property, and to promote the dispersing function of the lungs and clear up pathogenic heat. Flos Lonicerae, Fructus Forsythiae, Radix Isatidis, Radix Puerariae, Folium Mori, Flos Chrysanthemi, Fructus Arctii, Herba Lophatheri and Radix Platycodi are usually the main components of a prescription for Wind‐heat Syndrome. Supplementary drugs are sometimes added according to particular symptoms (Deng 1998; Hou 1995; Liu 2001; Ou 1992; Xu 1998; Zhang 1991) (Table 1; Table 2).

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Table 2. Medicinal herbs for influenza

Latin name

Common name

Properties, tastes

Function

Herba Schizonepetae

Schizonepeta

Pungent, slightly warm

1. Expel wind, release the symptoms. 2. Promote the formation of eruption. 3. Stop bleeding and ablate boils. 4. Restrain and kill bacteria. 5. Tranquilliser, analgesic. 6. Anti‐inflammation, anti‐allergy

Radix Ledebouriellae

Ledebouriella root

Pungent, slightly warm

1. Expel wind and relieve the symptoms. 2. Expel wind, dampness and alleviate pain. 3. Antipyretic, anti‐inflammatory, analgesic. 4. Relieve spasms. 5. Stop diarrhea

Radix Bupleuri

Bupleurum root

Pungent, bitter and slightly cold

1. Reduce and disperse fever. 2. Relax constrained 'gan qi' and alleviate mental depression. 3. Improve immune function. 4. Regulate the flow of 'qi' to relieve pain. 5. Tranquillise the mind, stop coughing. 6. Anti‐inflammatory, anti‐influenza, anti‐mycobacterium, tuberculosis. 7. Reduce plasma cholesterol. 8. Strengthen body immunity

Radix Peucedani

Peucedanum root

Bitter, sour and slightly cold

1. Descend 'qi' and expel phlegm. 2. Disperse wind heat. 3. Dilate coronary artery. 4. Inhibit influenza virus. 5. Relieve pain, tranquilliser

Radix Platycodi

Platycodon root

Bitter, sour, medium

1. Promote the dispersing function of the lungs, relieve sore throat. 2. Expel phlegm and evacuate pus. 3. Relieve cough. 4. Anti‐inflammatory. 5. Tranquilliser, relieve pain and reduce fever. 6. Inhibit gastric juice secretion, anti‐gastric ulcer. 7. Reduce blood sugar. 8. Reduce blood lipid

Rhizoma Zingiberis Recens

Fresh ginger

Pungent, slightly warm

1. Induce diaphoresis and relieve the symptoms. 2. Warm the mid section of the abdomen and alleviate vomiting. 3. Warm the lungs to arrest cough. 4. Reduce the poisonous effect of other herbs

Fructus Forsythiae

Forsythia fruit

Bitter, slightly cold

1. Clear away pathogenic fever from the body. 2. Treat boils and resolve masses. 3. Control influenza virus. 4. Resist bacteria. 5. Reduce diuresis. 6. Resist hepatic injury. 7. Relieve vomiting

Radix Isatidis

Isatis root

Bitter, cold

1. Clear away heat and toxic material. 2. Remove pathogenic heat from blood and relieve sore throat. 3. Resist virus. 4. Resist bacteria

Radix Puerariae

Pueraria root

Sweet, pungent and cool

1. Reduce fever. 2. Stimulate the rash of measles to appear on the surface of the skin. 3. Control diarrhea. 4. Relieve spasms. 5. Invigorate vital function and promote the production of body fluid. 6. Reduce blood pressure. 7. Relieve coronary heart disease and angina pectoris. 8. Improve cerebral circulation

Folium Mori

Mulberry leaf

Bitter, sweet and cold

1. Expel wind and clear heat from the lungs. 2. Clear the liver and the eyes. 3. Remove heat from blood to arrest bleeding. 4. Restrain and kill bacteria. 5. Lower blood pressure, reduce blood lipids

Flos Chrysanthemi

Chrysanthemum

Pungent, sweet, bitter and slightly cold

1. Disperse wind and clear heat. 2. Clear away liver heat and brighten the eyes. 3. Restrain and kill bacteria, anti‐inflammation. 4. Increase volume of blood flow in coronary artery. 5. Increase oxygen consumption of heart. 6. Reduce blood pressure

Fructus Arctii

Chrysanthemum

Pungent, bitter and cold

1. Disperse wind heat. 2. Reduce fever and relieve swelling. 3. Benefit the throat. 4. Stimulate rashes to appear on the surface of the skin

Why it is important to do this review

A number of clinical trials of Chinese medicinal herbs for influenza have been conducted. The quality and effects of all these trials had not yet been assessed and systematically reviewed. Natural medicinal herbs are potential drug resources and the therapeutic and toxic effects of medicinal herbs need to be identified through a systematic review. Hundreds of millions of dollars are spent treating influenza annually in China, suggesting that a systematic review on the effectiveness of these medicinal herbs would be extremely useful in health policy planning.

This review summarises the existing evidence on the comparative effectiveness and safety of medicinal herbs for preventing and treating influenza, according to current clinical trials.

Objectives

To assess the effect of Chinese medicinal herbs used to prevent and treat influenza and to estimate the frequency of adverse effects.

Methods

Criteria for considering studies for this review

Types of studies

We included randomised controlled trials (RCTs) only. We confirmed authentic randomisation processes by telephoning the article authors.

Types of participants

People of all ages diagnosed with influenza by their clinical symptoms alone (for example, epidemic season, fever, myalgia, headache, cough, muscle aches and fatigue etc.), or with laboratory evidence (relatively elevated lymphatic cell count in routine blood tests, influenza antigen detected in the patients' secretions, serum antibody reaction or isolated influenza virus) were included.

In prophylaxis studies, healthy people of all ages in an influenza epidemic area were included.

Patients with influenza complications such as otitis media, pneumonia, secondary bacterial infection, exacerbation of chronic respiratory disease, croup and bronchiolitis, and non‐respiratory complications such as febrile convulsions, Reye's syndrome and myocarditis were excluded.

Types of interventions

Chinese medicinal herbs (including natural herbs and herbal products extracted from natural herbs) compared with placebo, no treatment or chemical drugs normally used in care. Co‐interventions were allowed if they were offered to both arms of the trial. Trials comparing different Chinese medicinal herbs were excluded.

Types of outcome measures

Primary outcomes

  1. Rate of recovery: the symptoms and clinical manifestations were completely cleared and the body temperature returned to normal within one to three days after treatment. Or, time to symptom clearance, including fever, muscle pain, headache, cough, sore throat, stuffy nose, etc. This could be described as the rate by which symptoms cleared after treatment, for example, by day three. Or, rate of no improvement at a time point after treatment, for example, day three.

  2. Mortality.

  3. Incidence of influenza in prophylaxis studies.

Secondary outcomes

  1. Length of hospital stay.

  2. Marked improvement: most of the clinical symptoms had cleared and the body temperature returned to normal within one to three days. Partial improvement: some of the symptoms or manifestations of influenza neither improved nor did not worsen and the body temperature fell within three days.

  3. Incidence of complications.

  4. Adverse events: any adverse events such as malaise, nausea, fever, arthralgia, rash, headache and more generalised and serious signs resulting from the treatment that may be life‐threatening, cause a toxic response, anaphylaxis or discontinuation of treatment.

Search methods for identification of studies

Electronic searches

For this 2012 update we searched the Cochrane Central Register of Controlled Trials (CENTRAL) 2012, Issue 11, part of The Cochrane Library, www.thecochranelibrary.com (accessed 27 November 2012), which includes the Cochrane Acute Respiratory Infections Review Group Specialised Register, MEDLINE (December 2006 to November week 2, 2012), EMBASE (December 2006 to November 2012) and CNKI (1988 to November 2012). See Appendix 1 for details of the previous search.

We used the following search strategy to search CENTRAL and MEDLINE. We combined the MEDLINE search with the Cochrane Highly Sensitive Search Strategy for identifying randomised trials in MEDLINE: sensitivity‐maximising version (2008 revision); Ovid format (Lefebvre 2011). We adapted the search strategy to search EMBASE (see Appendix 2) and CNKI (see Appendix 3). We did not use any publication or language restrictions.

MEDLINE (Ovid)

1 Influenza, Human/
2 exp Influenzavirus A/
3 exp Influenzavirus B/
4 Influenzavirus C/
5 (influenza or flu).tw.
6 or/1‐5
7 exp Medicine, Chinese Traditional/
8 Medicine, East Asian Traditional/
9 Drugs, Chinese Herbal/
10 Plants, Medicinal/
11 (Chinese adj4 (herb* or medic*)).tw.
12 (medic* adj2 herb*).tw.
13 Integrative Medicine/
14 (integrat* adj2 medic*).tw.
15 or/7‐14
16 6 and 15

Searching other resources

We attempted to identify additional studies by searching the reference lists of relevant trials, reviews, conference proceedings and journals. In particular, with respect to journals, we searched those not indexed in the electronic databases. We also searched the WHO ICTRP search portal for ongoing trials (latest search 27 November 2012).

Data collection and analysis

Selection of studies

We scanned the titles, abstract sections and keywords of every record retrieved. We located full articles for further assessment when the information given suggested that the study: (1) included patients with uncomplicated influenza; (2) compared Chinese medicinal herbs with placebo or other active drugs; (3) assessed one or more relevant clinical outcome measure; (4) used random allocation for the comparison groups.

If there was any doubt regarding these criteria from the information given in the title and abstract, we retrieved the full article for clarification. We measured inter‐rater agreement for study selection using the kappa statistic (Cohen 1960). We resolved differences in opinion by discussion.

If random allocation was indicated in a trial but the randomisation procedure was not described, we telephoned the primary author to ask for detailed information regarding the randomisation procedure. We excluded the trial if the trial was a quasi‐RCT or falsely randomised (allocating patients by date of birth, date of admission, hospital number, alternation, or by the investigators' or patients' choosing, etc.). We excluded trials not reporting our stated outcome measures. We also excluded studies with a high percentage (more than 20%) of dropouts.

Data extraction and management

Two review authors (LHJ, TXW) independently extracted data concerning details of the study population, interventions and outcomes using a standard data extraction form, specifically designed for this review. We retrieved data on participants, interventions and outcomes, as described above. The data extraction form included the following items:

  1. General information: published/unpublished, title, authors, reference/source, contact address, country, urban/rural etc., publication language, year of publication, duplicate publications, sponsor and setting.

  2. Trial characteristics: design, duration of follow‐up, method of randomisation, allocation concealment, blinding (patients, people administering treatment, outcome assessors), checking of blinding.

  3. Intervention(s): placebo included, interventions(s) (dose, route, timing), comparison intervention(s) (dose, route, timing), co‐medication(s) (contents, dose, route, timing).

  4. Patients: sampling (random/convenience), exclusion criteria, total number and number in comparison groups, sex, age (children/adults), baseline characteristics, duration of influenza, diagnostic criteria, similarity of groups at baseline (including any co‐morbidity), assessment of compliance, withdrawals/losses to follow‐up (reasons/description), subgroups.

  5. Outcomes: outcomes specified above, any other outcomes assessed, other events, length of follow‐up, quality of reporting of outcomes.

  6. Results: for outcomes and times of assessment (including a measure of variation), if necessary converted to measures of effect specified below, intention‐to‐treat (ITT) analysis.

We resolved differences in data extraction by consensus and with reference to the original article. If necessary, we sought information from the authors of the primary studies. We managed to contact trial authors by letter or telephone regarding missing information and confusing points such as methods of randomisation and allocation concealment; separate information for certain patient subgroups; information about complications; and number of dropouts. We managed to contact manufacturers regarding the components of processed Chinese medicines if the components were unclear.

Two review authors (LHJ, TXW) independently extracted the original trial results. We resolved disagreements by discussion. For binary outcomes, we extracted the number of events and total number in each group. For continuous outcomes we extracted the mean, standard deviation and sample size from each group.

Assessment of risk of bias in included studies

We assessed the reporting quality of each trial, based largely on the quality criteria specified by Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011). In particular, we studied the following factors.

  1. Generation of the allocation sequence: an allocation sequence generated from a random numbers table, calculator or computer random‐number generator was considered as a real randomised RCT. Methods of allocating participants according to their date of birth, their hospital record number, the date to which they were invited to participate in the study and so on, were considered inadequate.

  2. Allocation concealment: use of a central independent unit, opaque sealed envelopes, or similar, were considered adequate. Inadequate methods included those not described, an open table of random numbers or similar.

  3. Double‐blinding: blinding of participants and investigators. Not performing double‐blinding or inconsistency in the delivery method (for example, tablets versus injections) were considered inadequate.

  4. Follow‐up: number of and reasons for dropouts and withdrawals described was considered adequate; number of and reasons for dropouts and withdrawals not described was considered inadequate.

Based on these criteria, studies were broadly subdivided into the following three categories:

  1. All quality criteria met: low risk of bias.

  2. One or more of the quality criteria only partly met: moderate risk of bias.

  3. One or more criteria not met: high risk of bias (Higgins 2011).

We used this classification as the basis for a sensitivity analysis. Additionally, we explored the influence of individual quality criteria in a sensitivity analysis. Two review authors (LHJ, TXW) independently assessed each trial. We calculated internal agreement using the kappa statistic and resolved disagreements by discussion. In cases of disagreement, one review author (KL) was consulted and a judgement was made, based on a consensus.

Measures of treatment effect

We intended to include data for some medicinal herbs in a meta‐analysis if possible.

We had decided in advance that a quantitative meta‐analysis should be performed when data for an outcome measure with a similar intervention (same herbal preparation or same main components of a herbal preparation) in more than two included studies were available. The data should be dichotomous or continuous and be expressed as risk ratio (RR) or mean difference (MD), respectively. The overall effect should be tested by using Z score with significance being set at P < 0.05.

Unit of analysis issues

The analysis was based on the individual participant.

Dealing with missing data

We obtained relevant missing data from trial authors by telephoning and carefully performing evaluation of important numerical data such as screened, randomised patients as well as the ITT, as‐treated and per‐protocol (PP) population. We investigated attrition rates, for example dropouts, losses to follow‐up and withdrawals, and critically appraised issues of missing data and imputation methods (for example, last observation carried forward (LOCF)).

Assessment of heterogeneity

In the event of substantial clinical, methodological or statistical heterogeneity we did not report study results as meta‐analytically pooled effect estimates. We identified heterogeneity by visual inspection of the forest plots, by using a standard Chi2 test and a significance level of α = 0.1, in view of the low power of this test. We specifically examined heterogeneity with the I2 statistic, quantifying inconsistency across studies to assess the impact of heterogeneity on the meta‐analysis, where an I2 statistic of 75% and more indicates a considerable level of inconsistency (Higgins 2011). When heterogeneity was found, we attempted to determine the potential causes by examining individual study and subgroup characteristics.

Assessment of reporting biases

We used funnel plots to assess the potential existence of small study bias.

Data synthesis

We will use a fixed‐effect model when the studies in the subgroup were sufficiently similar (P > 0.10, I2 statistic < 50%). We used a random‐effects model in the summary analysis when there was heterogeneity between the subgroups. We planned to test for publication bias by using a funnel plot or other corrective analytical methods, depending on the number of clinical trials included in the systematic review.

We did not find more than two studies using similar interventions in the treatment groups and consequently we did not use a meta‐analysis to calculate the pooled effect size. We analyzed data for each study and expressed the results a risk ratios (RR). We summarised the number of dropouts and the number of participants who were lost to follow‐up for each study, when available, using an ITT analysis. When different herbal preparations (as the intervention) in the treatment groups were considered as a whole and then compared to certain chemical drugs in the control groups, we assessed the therapeutic effect by a qualitative analysis.

Subgroup analysis and investigation of heterogeneity

Heterogeneity was to be tested for using the Chi2 test and I2statistic with significance being set at P < 0.1. Possible sources of heterogeneity were to be assessed by sensitivity and subgroup analyses as described below.

If suitable trials are found in the future, we will perform the following subgroup analyses in order to explore the effect size differences.

  1. Adults versus children.

  2. Intervention: different formulations between studies, administration routes (oral or intravenous) or doses (low and high, based on data).

  3. Timing of outcome measures.

Sensitivity analysis

If suitable trials are found in the future, we will perform the following sensitivity analyses in order to explore the influence of the following factors on effect size.

  1. Repeating the analysis excluding unpublished studies (if there are any).

  2. Repeating the analysis taking into account study quality, as specified above.

  3. Repeating the analysis excluding any very long or large studies to establish how much they dominate the results.

  4. Repeating the analysis excluding studies using the following filters: diagnostic criteria, publication language, funding source (industry versus other) and country.

We will test the robustness of the results by using different measures of effect size (risk difference, odds ratio, etc.) and different statistical models (fixed‐ and random‐effects models), if necessary.

Results

Description of studies

Results of the search

In this updated review, 1487 hits were generated by searching CNKI. The updated searches of MEDLINE, EMBASE and CENTRAL yielded 54 records after duplicates were removed. Five records were identified in WHO ICTRP. We retrieved a total of 63 trials that claimed to be randomised. Of these trials, 42 were excluded, either because the trial authors misunderstood true random allocation or the trial reports were multiple version of same study. The authors of three studies were uncontactable by telephone and we allocated their trials into the Characteristics of studies awaiting classification section. Eighteen studies were identified as true RCTs and fulfilled our inclusion criteria (Chen 2010a; Chen 2010b; Jin 2010; Li 2009; Li 2010; Ouyang 2010; Qian 2011; Shi 2004; Tan 2010; Wang 2010; Wei 2010; Xie 2010; Xue 1999; Zhang 2010a; Zhang 2011; Zhao 2010; Zheng 2010b; Zhu 2010) (Figure 1).

Figure 1
Study flow diagram.

Study flow diagram.

Included studies

In the first version of this review (Chen 2005), two trials were identified as true RCTs and fulfilled our inclusion criteria (Shi 2004; Xue 1999). A total of 1012 participants were included in these two trials, with numbers of participants in each trial varying from 61 to 951. Of the included trials, one (Shi 2004) was a treatment trial and the other trial (Xue 1999) was a prophylaxis and treatment trial (Table 3). Information on the herbal preparations used in each trial, including excluded trials and trials awaiting assessment, is shown in Table 4.

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Table 3. Interpretation of the results in each study

Study ID

Interventions

Recovery

Marked improvement

Partial improvement

No improvement

Defervescence

Symptoms clearance

Adverse reaction

Interpretation

Xue 1999

Ganmao capsule versus amantadine

RR 5.17, 95% CI 3.82 to 6.99

Data not available

Data not available

Data not available

Data not available

Data not available

Adverse reaction in alimentary tract was mentioned in control group but data were not available

Ganmao capsule can improve recovery more than amantadine with statistical difference at the end of 2 days of treatment

Shi 2004

E Shu You versus ribavirin

RR 2.18, 95% CI 0.87 to 5.43

RR 1.02, 95% CI 0.45 to 2.29

RR 0.91, 95% CI 0.36 to 2.27

RR 0.40, 95% CI 0.14 to 1.17

Data not available

Data not available

RR 0.58, 95% CI 0.09 to 3.73

There were no significant differences between E Shu You and ribavirin for treating influenza in terms of effectiveness and adverse reactions

CI: confidence interval
RR: risk ratio

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Table 4. The composition of preparations of TCMs

Study ID

TCMs preparation

English TCM name

Pinyin TCM name

Xue 1999

Ganmao capsule

Japanese honeysuckle stem, baical skullcap root, Platycodon root, bitter apricot seed, fine leaf Schizonepeta herb, divaricate Saposhicicovia root, fresh liquorice root

Rendongteng, Huangqi, Jiegeng, Xingren, Jingjie, Fangfeng, Shenggancao

In this updated version of the review, 16 additional trials were identified as true RCTs and fulfilled our inclusion criteria (Chen 2010a; Chen 2010b; Jin 2010; Li 2009; Li 2010; Ouyang 2010; Qian 2011; Tan 2010; Wang 2010; Wei 2010; Xie 2010; Zhang 2010a; Zhang 2011; Zhao 2010; Zheng 2010b; Zhu 2010). A total of 1509 participants were included in the additional 16 trials, with numbers of participants in each trial varying from 48 to 174. The proportion of males to females was 1308 to 1021. All of them were Chinese and aged from seven months to 71 years old. All trials enrolled patients with influenza alone. Three trials (Li 2009; Wang 2010; Zhang 2011) mentioned that an "informed consent form" was signed by participants before they were included and one trial (Wang 2010) was reviewed and approved by the Medical Ethics Committee of the West China Hospital at Sichuan University. Two trials (Chen 2010a; Wang 2010) described withdrawals (2 and 15, respectively).

Details of the included studies are shown in the Characteristics of included studies table. All the included studies were parallel design RCTs.

The number of participants in the 18 included studies ranged from 46 to 951, totaling 2521 participants.

  • In Shi 2004, participants were children aged 6 to 10, clinically diagnosed with influenza B in an epidemic area. Disease duration was less than 17 hours. Laboratory tests excluded a bacterial infection.

  • In Xue 1999, participants were healthy people as well as participants clinically diagnosed with influenza A3/H3N2 within two days of disease onset in an epidemic area. The statistical analyses for prevention and treatment were performed separately. Those who subsequently developed influenza in the prevention study were eventually included in the treatment analyses.

  • Four trials (Chen 2010b; Jin 2010; Xie 2010; Xue 1999) did not report the age of participants included and three trials (Chen 2010b; Jin 2010; Tan 2010) did not mention the gender of the participants in the intervention and comparison groups.

  • In Chen 2010a, the average ages of both intervention and comparison groups were 19.87 and 20.68 years. The proportion of males to females was 18 to 13 in the intervention group and 9 to 13 in the comparison group.

  • In Li 2009, the average ages in both intervention and comparison groups were 19 and 18 years. The proportion of males to females was 11 to 14 in the intervention group and 9 to 16 in the comparison group.

  • In Li 2010, the average ages of both intervention and comparison groups were 31.35 and 30.77 years. The proportion of males to females was 28 to 27 in the intervention group and 32 to 23 in the comparison group.

  • In Ouyang 2010, the average ages of the three groups (intervention versus comparison I versus comparison II) were 19.23, 19.69 and 19.38 years, respectively. The proportion of males to females was 59 to 57 in the intervention group, 16 to 13 in comparison group I and 15 to 14 in comparison group II.

  • In Wang 2010, the average ages of both intervention and comparison groups were 37.3 and 35.9 years. The proportion of males to females was 72 to 105 in the intervention group and 23 to 25 in the comparison group.

  • In Wei 2010, the average ages of both intervention and comparison groups were 17.76 and 16.25 years. The proportion of males to females was 17 to 13 in the intervention group and 10 to 6 in the comparison group.

  • In Zhang 2010a trial, the average ages of both intervention and comparison groups were 17 and 14 years. The proportion of males to females was 19 to 9 in the intervention group and 15 to 13 in the comparison group.

  • In Zhang 2011, the average ages of both intervention and comparison groups were 22.77 and 23.37 years. The proportion of males to females was 17 to 13 in the intervention group and 16 to 14 in the comparison group.

  • In Zhao 2010, the average ages of both intervention and comparison groups were 18.20 and 16.27 years. The proportion of males to females was 18 to 12 in the intervention group and 16 to 14 in the comparison group.

  • In Zheng 2010b, the average ages of the intervention, comparison I and comparison II groups were 22.47, 19.79 and 23.53 years, respectively. The proportion of males to females was 12 to 7 in the intervention group, 7 to 7 in comparison group I and 9 to 6 in comparison group II.

  • In Zhu 2010, the average ages of both intervention and comparison groups were 35.12 and 34.23 years. The proportion of males to females was 25 to 13 in the intervention group and 22 to 10 in the comparison group.

  • In Shi 2004, the average ages of both intervention and comparison groups were 8.69 and 8.48 years. The proportion of males to females was 18 to 14 in the intervention group and 16 to 13 in the comparison group.

Interventions of included studies

The interventions in the 18 trials were Chinese medicinal herbs compared with antiviral drugs. Of those, 14 trials (Chen 2010a; Jin 2010;Li 2009; Li 2010; Ouyang 2010; Qian 2011; Tan 2010; Wei 2010; Xie 2010; Zhang 2010a; Zhang 2011; Zhao 2010 ; Zheng 2010b; Zhu 2010) compared TCM or TCM plus oseltamivir with oseltamivir as follows.

  • In Chen 2010a, the therapeutic effects of TCM versus oseltamivir were tested.

  • In Jin 2010, the therapeutic effects of TCM versus oseltamivir were tested.

  • In Li 2009, the therapeutic effects of Lianhua Qingwen capsule versus oseltamivir were compared.

  • In Li 2010, the therapeutic effects of Tanreqing injection plus oseltamivir versus oseltamivir were tested.

  • In Ouyang 2010, the therapeutic effects of Lianhua Qingwen capsule versus oseltamivir versus paracetamol were tested.

  • In Qian 2011, the therapeutic effects of Tanreqing injection plus oseltamivir versus oseltamivir were tested.

  • In Tan 2010, the therapeutic effects of TCM versus oseltamivir versus TCM plus oseltamivir versus no treatment were tested.

  • In Wei 2010, the therapeutic effects of Lianhua Qingwen capsule versus oseltamivir were tested.

  • In Xie 2010, the therapeutic effects of Tanreqing injection plus oseltamivir versus oseltamivir were tested.

  • In Zhang 2010a, the therapeutic effects of TCM versus TCM plus oseltamivir were tested.

  • In Zhang 2011, the therapeutic effects of TCM versus oseltamivir were tested.

  • In Zhao 2010, the therapeutic effects of TCM plus oseltamivir versus oseltamivir were tested.

  • In Zhu 2010, the therapeutic effects of Ge Geng decoction plus oseltamivir versus oseltamivir were tested.

  • In Zheng 2010b, the therapeutic effects of TCM versus oseltamivir versus TCM plus oseltamivir were tested.

The other four trials (Chen 2010b; Shi 2004; Wang 2010; Xue 1999) used the following comparisons.

  • In Chen 2010b, Fanggan granule was compared with conventional medicine to prevent and treat influenza.

  • In Shi 2004, volatile oil extracted from Zedoary was compared with ribavirin plus vitamin C for injection, used for three to five days, with the antibiotic erythromycin given to both arms for preventing secondary bacterial infection.

  • In Wang 2010, Antiwei was compared with placebo to test the treatment effect on influenza.

  • In Xue 1999, compound herbal preparations were compared with amantadine, both taken in capsular form for seven days, for either the prophylaxis or treatment study.

Outcome measures of included studies

Eleven trials (Chen 2010a; Chen 2010b; Li 2009; Li 2010; Qian 2011;Tan 2010; Wang 2010; Zhang 2010a; Zhang 2011; Zhao 2010; Zhu 2010) reported the duration of fever; seven trials (Chen 2010b; Li 2010; Ouyang 2010; Shi 2004; Xie 2010; Xue 1999; Zhang 2011) reported the total effective rate; five trials (Li 2010; Ouyang 2010; Shi 2004; Xue 1999; Zhang 2011) reported the events of cure; four trials (Chen 2010b; Li 2010; Zhang 2011; Zhu 2010) reported the duration of cough; two trials (Li 2009; Zhang 2011) reported the time to muscle pain remission; four trials (Chen 2010a; Chen 2010b; Zhao 2010; Zhu 2010) reported the time to symptom remission; one trial (Zhang 2011) reported sore throat remission; four trials (Chen 2010a; Qian 2011; Tan 2010; Zhang 2010a) reported length of hospital stay; eight trials (Chen 2010b; Li 2010; Ouyang 2010; Shi 2004; Wang 2010; Xie 2010; Xue 1999; Zhang 2011) reported recovery; seven trials (Chen 2010b; Li 2010; Ouyang 2010; Shi 2004; Xie 2010; Xue 1999; Zhang 2011) reported the outcome "no improvement"; and 10 trials (Chen 2010a; Chen 2010b; Jin 2010; Li 2009; Ouyang 2010; Shi 2004; Wang 2010; Wei 2010; Xie 2010; Zheng 2010b) reported adverse effects.

One trial (Shi 2004) assessed the rate of effectiveness at the end of day three, following treatment, as the outcome (recovery/marked improvement/partial improvement/no improvement), according to the defervescence period, the period and extent of symptoms alleviation. Adverse reactions in the gastrointestinal tract were reported in both trial arms.

The other trial (Xue 1999) assessed the incidence of influenza at the end of day seven following treatment, as the outcome for the prophylaxis study; and the rate of recovery and inefficacy at the end of day two after treatment, as the outcome for the treatment study. Inefficacy was defined as effectiveness other than recovery in this study, which covered marked improvement, partial improvement and no improvement as regulated in our review. Adverse reactions in the gastrointestinal tract were mentioned in the control group but no data were reported. Neither study used time to fever clearance or other symptom alleviation, or both, as outcome measures.

Excluded studies

A total of 57 trials claiming to be RCTs were retrieved. Of these, 41 trials were excluded for the following reasons (see Characteristics of excluded studies table): the interventions were one Chinese medicinal herb compared to another, with or without chemical drugs added in one arm in 17 trials (Chen 2010c; Dou 2010; Huang 2010b; Jiang 2003; Liu 2010; Wang 2001; Yang 2000b; Yang 2005a; Yang 2005b; Yu 2000; Zeng 2004; Zhang 2000; Zhang 2002; Zhang 2004; Zhang 2005; Zhao 2006; Zhong 2005); five trials did not provide the data to meet the outcome criteria (Hamazaki 2006; Hang 1998; Lindenmuth 2000; Lu 2004; Zhou 2010); participants in five trials experienced complications (Jin 1998; Li 2005; Liu 2002; Zeng 2004; Zheng 2010); and one trial used a Japanese herbal medicine as the intervention (Kubo 2007). We then conducted telephone interviews with the authors of the remaining 14 trials to obtain the information on the randomisation procedure and found that 13 trials were actually false or quasi‐RCTs (Du 1991; Hou 2002; Huang 2003; Huang 2010a; Li 2001; Qu 2005; Tang 2010; Xu 2001; Yang 2000a; Yao 2003; Yuan 2003; Xia 2010; Zhang 2010b). We failed to contact the authors of two trials, which are listed in the Studies awaiting classification section (Qiu 1997; Song 2002).

Risk of bias in included studies

The overall risk of bias is presented graphically in Figure 2 and summarised in Figure 3.

Figure 2
'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

Figure 3
'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study.

'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study.

Description of withdrawals and losses to follow‐up and intention‐to‐treat analysis

Two of the included studies (Chen 2010a; Wang 2010) mentioned dropouts but none of the included studies performed an intention‐to‐treat analysis.

In the Xue 1999 trial there were 519 participants in the intervention group and 432 in the control group. It is unclear whether the imbalance of participant numbers in the two arms was produced by inadequate randomisation or withdrawals during follow‐up, or for another reason. However, the trial author did not give us a satisfactory answer, as he could not remember the details. We considered both included studies at high risk for bias and graded them as category C.

Allocation

Nine trials reported on allocation sequence generation. Of these, two trials (Chen 2010b; Tan 2010) were based on a random numbers table; four trials used a computer to generate the allocate sequence (Chen 2010a; Shi 2004; Wang 2010; Xue 1999); and one trial was based on drawing lots. The other trials did not describe how participants were allocated. After conducting a telephone interview with the trial authors, we learned that the allocation sequence was generated by random number table.

Except for one included trial (Wang 2010), none of the studies mentioned allocation concealment. After conducting telephone interviews, we learned that allocation in four trials (Chen 2010a; Shi 2004; Wang 2010; Xue 1999) was generated by computer and allocation concealment was performed.

Blinding

With the exception of two studies (Wang 2010; Xue 1999), the trials did not mention blinding. Xue 1999 mentioned double‐blinding. Neither the participants nor the assessors knew which interventions were administered. The drugs in both arms were the same in appearance, route and schedule, to ensure blinding. Wang 2010 also mentioned double‐blinding and gave a very detailed description of how to make the dummy visually the same as Antiwei medicine.

Incomplete outcome data

Two trials (Chen 2010a; Wang 2010) recorded withdrawals as two and 34 respectively. However, none of the trials used ITT analysis on dropouts or withdrawals.

Selective reporting

The protocols for the included studies were unavailable. Eight trials (Li 2010; Qian 2011; Tan 2010; Xue 1999; Zhang 2010a; Zhang 2011; Zhao 2010; Zhu 2010) did not report adverse events.

Other potential sources of bias

The seriousness of influenza in each trial was different, which may have influenced the outcomes.

Effects of interventions

Due to clinical heterogeneity it was not possible to combine the results of the studies. Therefore, the results are presented as separate risk ratios (RR) for each study. We did not perform any of the planned subgroup/sensitivity analyses.

Primary outcomes

1. Rate of recovery
Trials showing statistically significant differences between the intervention and comparison

  • Lianhua Qingwen capsule showed a significantly better result than paracetamol within 24 hours after treatment (Ouyang 2010: risk ratio (RR) 1.91, 95% confidence interval (CI) 1.03 to 3.52) (Analysis 1.1).

  • Antiwei capsule showed a significantly better result than placebo within four days after treatment (Wang 2010: RR 3.80, 95% CI 1.23 to 11.72) (Analysis 1.1).

  • Ganmao capsule showed a significantly better result than amantadine for recovery within two days of treatment (Xue 1999: RR 5.17, 95% CI 3.82 to 6.99) (Analysis 1.1).

Trials showing no statistically significant differences between the intervention and comparison

  • E Shu You (volatile oil extracted from Zedoary) showed a better result than ribavirin for recovery within three days of treatment, however the difference was not significant (Shi 2004: RR 2.17, 95% CI 0.87 to 5.43) (Analysis 1.1).

  • Fanggan decoction showed a better result than conventional medicines, however the difference was not significant (Chen 2010b: RR 1.02, 95% CI 0.67 to 1.56) (Analysis 1.1).

  • Lianhua Qingwen capsule showed a better result than oseltamivir, however the difference was not significant (Ouyang 2010: RR 0.95, 95% CI 0.66 to 1.38) (Analysis 1.1).

  • Ganmao capsule showed a better result than amantadine, however the difference was not significant (Ouyang 2010: RR 0.48, 95% CI 0.38 to 0.61) in influenza prevention (Analysis 1.1).

  • Tanreqing plus oseltamivir showed a better result than oseltamivir alone, however the difference was not significant (Li 2010 and Xie 2010: RR 1.32, 95% CI 0.87 to 2.00) (Analysis 1.1).

  • Traditional Chinese medicine (TCM) showed a better result than oseltamivir, however the difference was not significant (Zhang 2011: RR 1.13, 95% CI 0.50 to 2.52) (Analysis 1.1).

Time to fever clearance

Different TCM appeared different effect compared to oseltamivir (Analysis 1.2):

Chen 2010a's TCM had longer clearance time than oseltamivir (MD 3.44, 95%CI 2.31 to 4.57); Tan 2010's TCM had a similar time of fever clearance, there was no statistical significant (MD 3.44, 95%CI ‐4.03 to 10.91).

Zhang 2011's TCM had a much shorter time of fever clearance with statistical significant (MD ‐11.96, 95%‐12.98 to ‐10.94).

Li 2009 reported Lianhua Qingwen capsule had a similar time of fever clearance (MD 0.8, 95%CI ‐7.40 to 9.00).

Dramatic results appeared in the comparison of integrated TCM's and oseltamivir did not appear superior than oseltamivir alone:

Tan 2010's TCM + oseltamivir versus oseltamivir: MD ‐3.97, 95%CI ‐10.47 to 2.53;

Zhang 2010a's TCM + oseltamivir versus oseltamivir: MD ‐6.2, 95%CI ‐18.69 to 6.29;

Zhao 2010's TCM + oseltamivir versus oseltamivir: MD ‐5.40, 95%CI ‐11.29 to 0.49.

Other three studies appeared TCM plus oseltamivir superior than oseltamivir alone:

Zhu 2010's Gegentang granule plus oseltamivir had a statistical significant shorter time than oseltamivir alone: MD ‐6.44, 95%CI ‐10.29 to ‐2.59;

Both Li 2010 and Qian 2011 used Tanreqing injection plus oseltamivir had a statistical significant shorter time than oseltamivir alone: MD ‐4.11, 95%CI ‐4.72 to ‐3.50 and MD ‐0.37, 95%CI ‐0.69 to ‐0.05, respectively, the combined MD‐1.18, 95%CI‐1.46 to ‐0.90.

Chen 2010b's Fanggan granule had a shorter time of fever clearance than conventional medicine with statistical significant (MD‐1.01, 95%CI‐1.52 to ‐0.5).

Duration of cough

Zhu 2010's Gegeng Tang granule did not show any benefit when combined use with oseltamivir versus oseltamivir alone (MD ‐0.56, 95%CI ‐29.71 to 28.59).

Other three studies showed that use of TCM had a statistical significant shorter duration than oseltamivir alone on cough:

Chen 2010b's Fanggan decoction shorter than conventional medicine (MD ‐3.04, 95%CI ‐4.27 to ‐1.81);

Li 2010 used Tanreqing injection plus oseltamivir had a shorter duration than oseltamivir alone (MD ‐3.87, 95%CI ‐4.77 to ‐2.97)

Zhang 2011's TCM had a shorter duration than oseltamivir (MD‐18.73, 95%CI ‐19.7 to ‐17.76).

Time to remission of muscle pain

Two studies reported time to remission of muscle pain:

Li 2009 reported Lianhuan Qingwen capsule similar with oseltamivir (MD ‐5.90, 95%CI ‐14.01 to 2.21);

Zhang 2011's TCM had a statisitically significant shorter time than oseltamivir to remission of muscle pain (MD ‐22.83, 95%CI ‐25.15 to ‐20.51).

Time to symptom remission

Four studies reported this outcome:

Chen 2010a's TCM had a similar time to symptom remission (MD ‐2.64, 95%CI ‐16.52 to 11.24);

Chen 2010b's Fanggan granule had a significantly shorter time than conventional medicine (MD ‐1.24, 95%CI ‐1.71 to ‐0.77);

Zhu 2010's Gegeng Tang granule plus oseltamivir had a significantly shorter time than oseltamivir alone (MD ‐14.11, 95%CI ‐18.35 to ‐9.87);

Zhao 2010's TCM plus oseltamivir had a significantly shorter time than oseltamivir alone (MD ‐13.33, 95%CI ‐24.28 to ‐2.38).

Time to remission of sore throat

Zhang 2011's TCM had a significant shorter time of remission the sore throat than oseltamivir (MD ‐15.60, 95%CI ‐17.87 to ‐13.33).

No improvement

Six trials reported the outcome "no improvement" and none of them showed statistical significance.

Shi 2004: E Shu You showed a lower rate of no improvement than ribavirin in the treatment of influenza, without a significant difference (RR 0.40, 95% CI 0.14 to 1.17) (Analysis 1.8).

Chen 2010b: Fanggan granule versus conventional medicine: RR 0.70, 95% CI 0.24 to 2.05 (Analysis 1.8).

Li 2010 and Xie 2010: Tanreqing plus oseltamivir versus oseltamivir: RR 0.37, 95% CI 0.17 to 0.80 (Analysis 1.8).

Zhang 2011: TCM versus oseltamivir: RR 2.00, 95% CI 0.19 to 20.90 (Analysis 1.8).

Ouyang 2010: Lianhua Qingwen capsule versus oseltamivir: RR 1.00, 95% CI 0.22 to 4.46 (Analysis 1.8).

Ouyang 2010: Lianhua Qingwen capsule versus paracetamol: RR 0.20, 95% CI 0.09 to 0.46 (Analysis 1.8).

Xue 1999: Ganmao capsule versus amantadine: RR 0.15, 95% CI 0.10 to 0.21 (Analysis 1.8).

2. Mortality

No study reported mortality.

3. Incidence of influenza in prophylaxis studies

In the prophylaxis study (Xue 1999) the incidence of influenza was statistically significantly lower in the Ganmao capsule group than in the amantadine group, within seven days of treatment (RR 0.48, 95% CI 0.38 to 0.61).

Secondary outcomes

1. Length of hospital stay

Four studies reported length of hospital stay, except one study (Qian 2011), other three studies showed no difference with control remedies:

Chen 2010a's TCM similar as oseltamivir (MD ‐0.04, 95%CI ‐0.71 to 0.63);

Tan 2010's TCM similar as oseltamivir (MD 0.26, 95%CI ‐0.43 to 0.95);

Tan 2010's TCM plus oseltamivir versus oseltamivir alone (MD ‐0.57, 95%CI ‐1.38 to 0.24);

Tan 2010's TCM versus placebo (MD ‐0.62, 95%CI ‐1.92 to 0.68);

Zhang 2010a's TCM plus oseltamivir versus oseltamivir (MD‐0.20, 95%CI ‐1.46 to 1.06);

Qian 2011 reported Tanreqing injection plus oseltamivir had significant shorter time than oseltamivir alone (MD ‐1.01, 95%CI ‐2.00 to ‐0.02).

2. Marked improvement

Only one study (Shi 2004) provided data for marked improvement for analysis with no significant difference between E Shu You and ribavirin in the treatment of influenza (RR 1.02, 95% CI 0.45 to 2.29).

Partial improvement

Data for partial improvement were available for analysis in six trials (Chen 2010b; Li 2010; Ouyang 2010; Shi 2004; Xie 2010; Zhang 2011). Chen 2010b, Li 2010, Ouyang 2010, Shi 2004, Xie 2010 and Zhang 2011 found no significant difference between treatment and comparison groups in the treatment of influenza, with the data as follows.

3. Incidence of complications

No studies reported this outcome.

4. Adverse events

Data on adverse reactions were available in 10 studies, but none of the recorded adverse reactions fulfilled the definition in this review and were slight. Two trials (Wang 2010; Xie 2010) reported that none of the participants experienced adverse reactions. The other eight trials reported as follows.

Discussion

Summary of main results

Due to clinical heterogeneity, we did not perform meta‐analyses. Of the 18 included studies, only three (Ouyang 2010; Wang 2010; Xue 1999) indicated that compared with antiviral drugs, Chinese medicinal herbs showed a superior effect in preventing influenza and alleviating influenza symptoms. The remain 15 studies (Chen 2010a; Chen 2010b; Jin 2010; Li 2009; Li 2010; Qian 2011; Shi 2004; Tan 2010; Wei 2010; Xie 2010; Zhang 2010a; Zhang 2011; Zhao 2010; Zheng 2010b; Zhu 2010) had a similar effect to antiviral drugs. No obvious adverse events were reported in the included studies. However, the small number of participants and studies, together with the poor quality of these studies, does not allow us to draw reliable conclusions.

Overall completeness and applicability of evidence

Definitive conclusions could not be reached as differences between the traditional Chinese medicine (TCM) formulations in the included studies lower the generalisability of the results regarding the effectiveness of TCM for patients with influenza.

The applicability of the included studies was limited, since their inclusion criteria, interventions, durations and outcome measures were different. More well‐designed trials are required.

Quality of the evidence

We rated the quality of the evidence from the included studies as very low to low, and the reasons for this are listed below.

Most of the retrieved studies did not give adequate descriptions of the methodology used, which may have misled us if we had not clarified the details, for example, inclusion of non‐randomised trials and classification the trials into category B rather than C. It was an exhausting but necessary process to interview every primary trial author before deciding whether to include these trials, when the methodological details were not reported. Contacting authors by telephone was more effective than writing to them because of a higher response rate. However, even after confirmation of true randomisation, we found that the methodological quality of the studies remained poor.

Allocation concealment is an important marker of trial quality. However, very few potential articles considered for our review reported or performed allocation concealment; the included trials failed to perform allocation concealment, leading to high risk of selection and confounding bias.

In one of the included trials, no blinding was used for either the participants or the investigators, which led to a high risk of performance bias. None of the studies mentioned blinding to the outcome assessors, which promotes suspicion of detection bias. Publication bias may exist as all the included studies were published in Chinese and no primary articles reporting negative results were found. The huge difference in the number of participants between the two arms raises suspicion of inadequate randomisation or a significant number of withdrawals, which may have led to high selection or attrition bias in one study (Xue 1999).

During the process of interviewing the trial authors, we understood that it was difficult for them to perform double‐blinding because of certain features associated with Chinese medicinal herbs, for example, aroma and appearance. Capsules were used in one study (Xue 1999). Other methods included extracts from herbal medicines administered by injection by using an opaque cover around the fluid bag if the herb was of a particular colour. Many trials are conducted to assess the efficacy of a plant before making the expensive decision to produce it as a patented medicine and double‐blinding is almost impossible.

All the patients in the included studies were diagnosed by epidemiology, clinical symptoms and routine tests. It is possible that participants with other acute respiratory infections not caused by the influenza virus, such as the common cold, may have been misdiagnosed as having influenza and were included in the trials. The disease duration on entry varied between the potential studies we retrieved for inclusion. Secondary bacterial infection or other complications that complicate influenza treatment may have been present, even if the trial authors did not find or report them.

In the practice of TCM, herbal preparations should match the type of 'zheng' which equates to a diagnosis. Trial authors are encouraged to explain each 'zheng' by using conventional medical terms, therefore making it more convenient for physicians and consumers to choose an appropriate preparation.

Regarding interventions, we considered the commonly used antiviral and antipyretic‐analgesic drugs to be acceptable controls. However, there is potential for bias. If the trial author knows that a 'positive' drug was used and the study was an 'equal effect test' study, there is a potential risk that the outcome detectors will consider similar results for the two groups. In this case, even double‐blinding is useless. If it is a 'superior effect test', the trial authors tend to overestimate the effect in the treatment group if allocation concealment and blinding were inadequate. When a Chinese herbal medicine combined with a supposed 'positive' intervention is found to be more effective than the 'positive' drug alone for influenza, this herbal medicine is considered effective. An alternative would be to compare Chinese medicinal herbs to a placebo (it is also recommended to compare first to placebo to test effectiveness and subsequently to compare to another treatment that was tested against placebo and proved as effective), with another 'positive' drug given to both arms.

For superior trial design, one of the key techniques for avoiding performance and detection bias is blinding. As most TCMs have particular characteristics, blinding is rather difficult. The TCM industry should develop a simulation agent when designing trials.

Although Chinese herbal medicines as a treatment for influenza and the method of manufacturing these medicines are widely accepted in China, most of the constituents of the pharmacologically prepared drugs used in trials cannot be specified. This is in marked contrast to the pharmacological agents used in conventional medicine, for which the chemical constituents, their quantities and the percentage of any impurities or contaminants are precisely known. In addition, the variation between different production batches of conventional medicines is kept within specified limits. In contrast, variation between formulations and batches of pharmacological agents is inevitable in TCM, although the Chinese government specifies the acceptable limits of variation. This variation is a factor that may contribute to any heterogeneity between different study results. The application of TCM signs is also limited as not everyone is familiar with them. However, one must accept that the overall treatment concept for TCM is different to that used in conventional medicines.

Ten included studies reported slight adverse reactions. This suggests that the TCMs used in the included studies are safe.

The definition and timing of outcome measures varied between studies. The outcome measures, defined in the primary version of this review, were based on a subjective assessment of defervescence and symptom withdrawal using dichotomous data. We may have missed additional information from studies which did not use the outcome measures stated in our original review. In this updated review, we added continuous data for duration of defervescence and symptom withdrawal, as well as influenza incidence in the prophylaxis studies. In one of the included studies (Shi 2004) ibuprofen was added temporally to patients with high fever, whereas no data were provided about how many participants in each group received the extra drug. This may have influenced the results.

TCM signs are important outcome measures in traditional practice. We will consider including TCM signs as a secondary or an additional outcome in the next update of this review. However, it is difficult to compare or quantify TCM signs as they have subjective outcomes. For example, 'mai xiang' equates to pulse presentations. Diagnosing 'mai xiang' in TCM is a complex and difficult technique, dependent on the TCM physician's experience. TCM researchers and physicians should find a gold standard method which is repeatable and easy to practice when measuring TCM signs.

In addition to the methodological limitations, the imprecision of the results is a common problem in each included study. The confidence intervals for the effects were wide in most of the results. Another problem is that most Chinese medicines were tested in one study only.

Potential biases in the review process

Most of the trials did not adequately report their methodology in the original publications, so we obtained this information by telephone communication with the authors. The studies were conducted several years ago and may be influenced by recall bias.

Agreements and disagreements with other studies or reviews

The results of well‐designed randomised controlled trials (RCTs) with large sample sizes in the future may confirm or refute our current conclusions. There is no other known systematic review of TCM for influenza.

Study flow diagram.
Figures and Tables -
Figure 1

Study flow diagram.

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'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.
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Figure 2

'Risk of bias' graph: review authors' judgements about each risk of bias item presented as percentages across all included studies.

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'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study.
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Figure 3

'Risk of bias' summary: review authors' judgements about each risk of bias item for each included study.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 1 Recovery.
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Analysis 1.1

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 1 Recovery.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 2 Time to fever clearance.
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Analysis 1.2

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 2 Time to fever clearance.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 3 Duration of cough.
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Analysis 1.3

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 3 Duration of cough.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 4 Time to remission of muscle pain.
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Analysis 1.4

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 4 Time to remission of muscle pain.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 5 Time to symptom remission.
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Analysis 1.5

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 5 Time to symptom remission.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 6 Time to remission of sore throat.
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Analysis 1.6

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 6 Time to remission of sore throat.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 7 Length of hospital stay.
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Analysis 1.7

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 7 Length of hospital stay.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 8 No improvement or worsening influenza.
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Analysis 1.8

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 8 No improvement or worsening influenza.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 9 Partial improvement.
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Analysis 1.9

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 9 Partial improvement.

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Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 10 Adverse events.
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Analysis 1.10

Comparison 1 Traditional Chinese medicine (TCM) versus other treatments, Outcome 10 Adverse events.

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Table 1. TCM definitions

TCM term

Definition

Qi

In the theory of TCM, 'qi' is considered as a life force or energy in every body. 'Qi' must be kept balanced and flow freely to keep organs working well. When 'qi' is blocked in a certain part of the body, the organs involved get sick and people can have a pain there. For example, constrained 'gan qi' should be released to make 'qi' flow freely so that the liver can work well and 'qi' should be regulated to flow freely so that pain is relieved. Similarly, when the 'qi' of the lungs is not balanced, such as by being lost ascending out, people may cough; 'qi' must therefore be put down to maintain an adequate amount of 'qi' in the lungs

Wind‐cold type cold

If manifested by more severe chilliness, slight fever and a tongue with thin, white fur, then it belongs to the exterior syndrome caused by wind and cold and should be treated with strong perspiration drugs which are pungent in taste and warm in property, to dispel the wind and cold

Wind‐heat type cold

If manifested by more severe fever, milder chilliness and a tongue with thin, yellow fur, then it belongs to the exterior syndrome caused by wind and heat

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Table 1. TCM definitions
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Table 2. Medicinal herbs for influenza

Latin name

Common name

Properties, tastes

Function

Herba Schizonepetae

Schizonepeta

Pungent, slightly warm

1. Expel wind, release the symptoms. 2. Promote the formation of eruption. 3. Stop bleeding and ablate boils. 4. Restrain and kill bacteria. 5. Tranquilliser, analgesic. 6. Anti‐inflammation, anti‐allergy

Radix Ledebouriellae

Ledebouriella root

Pungent, slightly warm

1. Expel wind and relieve the symptoms. 2. Expel wind, dampness and alleviate pain. 3. Antipyretic, anti‐inflammatory, analgesic. 4. Relieve spasms. 5. Stop diarrhea

Radix Bupleuri

Bupleurum root

Pungent, bitter and slightly cold

1. Reduce and disperse fever. 2. Relax constrained 'gan qi' and alleviate mental depression. 3. Improve immune function. 4. Regulate the flow of 'qi' to relieve pain. 5. Tranquillise the mind, stop coughing. 6. Anti‐inflammatory, anti‐influenza, anti‐mycobacterium, tuberculosis. 7. Reduce plasma cholesterol. 8. Strengthen body immunity

Radix Peucedani

Peucedanum root

Bitter, sour and slightly cold

1. Descend 'qi' and expel phlegm. 2. Disperse wind heat. 3. Dilate coronary artery. 4. Inhibit influenza virus. 5. Relieve pain, tranquilliser

Radix Platycodi

Platycodon root

Bitter, sour, medium

1. Promote the dispersing function of the lungs, relieve sore throat. 2. Expel phlegm and evacuate pus. 3. Relieve cough. 4. Anti‐inflammatory. 5. Tranquilliser, relieve pain and reduce fever. 6. Inhibit gastric juice secretion, anti‐gastric ulcer. 7. Reduce blood sugar. 8. Reduce blood lipid

Rhizoma Zingiberis Recens

Fresh ginger

Pungent, slightly warm

1. Induce diaphoresis and relieve the symptoms. 2. Warm the mid section of the abdomen and alleviate vomiting. 3. Warm the lungs to arrest cough. 4. Reduce the poisonous effect of other herbs

Fructus Forsythiae

Forsythia fruit

Bitter, slightly cold

1. Clear away pathogenic fever from the body. 2. Treat boils and resolve masses. 3. Control influenza virus. 4. Resist bacteria. 5. Reduce diuresis. 6. Resist hepatic injury. 7. Relieve vomiting

Radix Isatidis

Isatis root

Bitter, cold

1. Clear away heat and toxic material. 2. Remove pathogenic heat from blood and relieve sore throat. 3. Resist virus. 4. Resist bacteria

Radix Puerariae

Pueraria root

Sweet, pungent and cool

1. Reduce fever. 2. Stimulate the rash of measles to appear on the surface of the skin. 3. Control diarrhea. 4. Relieve spasms. 5. Invigorate vital function and promote the production of body fluid. 6. Reduce blood pressure. 7. Relieve coronary heart disease and angina pectoris. 8. Improve cerebral circulation

Folium Mori

Mulberry leaf

Bitter, sweet and cold

1. Expel wind and clear heat from the lungs. 2. Clear the liver and the eyes. 3. Remove heat from blood to arrest bleeding. 4. Restrain and kill bacteria. 5. Lower blood pressure, reduce blood lipids

Flos Chrysanthemi

Chrysanthemum

Pungent, sweet, bitter and slightly cold

1. Disperse wind and clear heat. 2. Clear away liver heat and brighten the eyes. 3. Restrain and kill bacteria, anti‐inflammation. 4. Increase volume of blood flow in coronary artery. 5. Increase oxygen consumption of heart. 6. Reduce blood pressure

Fructus Arctii

Chrysanthemum

Pungent, bitter and cold

1. Disperse wind heat. 2. Reduce fever and relieve swelling. 3. Benefit the throat. 4. Stimulate rashes to appear on the surface of the skin

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Table 2. Medicinal herbs for influenza
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Table 3. Interpretation of the results in each study

Study ID

Interventions

Recovery

Marked improvement

Partial improvement

No improvement

Defervescence

Symptoms clearance

Adverse reaction

Interpretation

Xue 1999

Ganmao capsule versus amantadine

RR 5.17, 95% CI 3.82 to 6.99

Data not available

Data not available

Data not available

Data not available

Data not available

Adverse reaction in alimentary tract was mentioned in control group but data were not available

Ganmao capsule can improve recovery more than amantadine with statistical difference at the end of 2 days of treatment

Shi 2004

E Shu You versus ribavirin

RR 2.18, 95% CI 0.87 to 5.43

RR 1.02, 95% CI 0.45 to 2.29

RR 0.91, 95% CI 0.36 to 2.27

RR 0.40, 95% CI 0.14 to 1.17

Data not available

Data not available

RR 0.58, 95% CI 0.09 to 3.73

There were no significant differences between E Shu You and ribavirin for treating influenza in terms of effectiveness and adverse reactions

CI: confidence interval
RR: risk ratio

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Table 3. Interpretation of the results in each study
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Table 4. The composition of preparations of TCMs

Study ID

TCMs preparation

English TCM name

Pinyin TCM name

Xue 1999

Ganmao capsule

Japanese honeysuckle stem, baical skullcap root, Platycodon root, bitter apricot seed, fine leaf Schizonepeta herb, divaricate Saposhicicovia root, fresh liquorice root

Rendongteng, Huangqi, Jiegeng, Xingren, Jingjie, Fangfeng, Shenggancao
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Table 4. The composition of preparations of TCMs
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Comparison 1. Traditional Chinese medicine (TCM) versus other treatments

Outcome or subgroup title

No. of studies

No. of participants

Statistical method

Effect size

1 Recovery Show forest plot

8

Risk Ratio (M‐H, Random, 95% CI)

Subtotals only

1.1 Fanggan decoction versus conventional medicine

1

95

Risk Ratio (M‐H, Random, 95% CI)

1.02 [0.67, 1.56]

1.2 Fever resolved within 24 hours after treatment (Lianhua Qingwen capsule versus oseltamivir)

1

145

Risk Ratio (M‐H, Random, 95% CI)

0.95 [0.66, 1.38]

1.3 Fever resolved within 24 hours after treatment (Lianhua Qingwen capsule versus control 2)

1

145

Risk Ratio (M‐H, Random, 95% CI)

1.91 [1.03, 3.52]

1.4 Ganmao capsule versus amantadine

1

738

Risk Ratio (M‐H, Random, 95% CI)

0.48 [0.38, 0.61]

1.5 Ganmao capsule versus amantadine (Day 2)

1

432

Risk Ratio (M‐H, Random, 95% CI)

5.17 [3.82, 6.99]

1.6 E Shu You versus ribavirin (Day 3)

1

61

Risk Ratio (M‐H, Random, 95% CI)

2.18 [0.87, 5.43]

1.7 Tanreqing + oseltamivir versus oseltamivir

2

197

Risk Ratio (M‐H, Random, 95% CI)

1.32 [0.87, 2.00]

1.8 TCM versus oseltamivir

1

60

Risk Ratio (M‐H, Random, 95% CI)

1.13 [0.50, 2.52]

1.9 Antiwei versus placebo (day 4)

1

225

Risk Ratio (M‐H, Random, 95% CI)

3.80 [1.23, 11.72]

2 Time to fever clearance Show forest plot

10

Mean Difference (IV, Fixed, 95% CI)

Totals not selected

2.1 TCM versus oseltamivir

3

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

2.2 Gegeng Tang granule + oseltamivir versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

2.3 Lianhua Qingwen capsule versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

2.4 TCM + oseltamivir versus oseltamivir

3

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

2.5 Tanreqing injection + oseltamivir versus oseltamivir

2

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

2.6 Fanggan granule versus conventional medicine

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

3 Duration of cough Show forest plot

4

Mean Difference (IV, Fixed, 95% CI)

Totals not selected

3.1 Fanggan decoction versus conventional medicine

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

3.2 Ge Geng Tang granule + oseltamivir versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

3.3 Tanreqing injection + oseltamivir versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

3.4 TCM versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

4 Time to remission of muscle pain Show forest plot

2

Mean Difference (IV, Fixed, 95% CI)

Totals not selected

4.1 Lianhua Qingwen capsule

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

4.2 TCM versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

5 Time to symptom remission Show forest plot

4

Mean Difference (IV, Fixed, 95% CI)

Totals not selected

5.1 TCM versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

5.2 Fanggan granule versus conventional medicine

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

5.3 Gegeng Tang granule + oseltamivir versus oseltamivir (body pain)

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

5.4 TCM + oseltamivir versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

6 Time to remission of sore throat Show forest plot

1

Mean Difference (IV, Fixed, 95% CI)

Subtotals only

6.1 TCM versus oseltamivir

1

60

Mean Difference (IV, Fixed, 95% CI)

‐15.60 [‐17.87, ‐13.33]

7 Length of hospital stay Show forest plot

4

Mean Difference (IV, Fixed, 95% CI)

Totals not selected

7.1 TCM versus oseltamivir

2

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

7.2 Tanreqing injection + oseltamivir versus oseltamivir

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

7.3 TCM plus oseltamivir versus oseltamivir

2

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

7.4 TCM versus placebo

1

Mean Difference (IV, Fixed, 95% CI)

0.0 [0.0, 0.0]

8 No improvement or worsening influenza Show forest plot

7

Risk Ratio (M‐H, Random, 95% CI)

Subtotals only

8.1 E Shu You versus ribavirin (Day 3)

1

61

Risk Ratio (M‐H, Random, 95% CI)

0.40 [0.14, 1.17]

8.2 Fanggan decoction versus conventional medicines

1

95

Risk Ratio (M‐H, Random, 95% CI)

0.70 [0.24, 2.05]

8.3 Tanreqing injection + oseltamivir versus oseltamivir

2

197

Risk Ratio (M‐H, Random, 95% CI)

0.37 [0.17, 0.80]

8.4 TCM versus oseltamivir

1

60

Risk Ratio (M‐H, Random, 95% CI)

2.0 [0.19, 20.90]

8.5 Lianhua Qingwen versus oseltamivir

1

145

Risk Ratio (M‐H, Random, 95% CI)

1.0 [0.22, 4.46]

8.6 Lianhua Qingwen versus Anga huangmin

1

145

Risk Ratio (M‐H, Random, 95% CI)

0.20 [0.09, 0.46]

8.7 Ganmao capsule versus amantadine

1

951

Risk Ratio (M‐H, Random, 95% CI)

0.15 [0.10, 0.21]

9 Partial improvement Show forest plot

6

703

Risk Ratio (M‐H, Random, 95% CI)

1.05 [0.82, 1.36]

9.1 Tanreqing injection + oseltamivir

1

110

Risk Ratio (M‐H, Random, 95% CI)

0.6 [0.23, 1.54]

9.2 Fanggan granule versus Western medicine

1

95

Risk Ratio (M‐H, Random, 95% CI)

1.09 [0.66, 1.78]

9.3 Lianhua Qingwen versus oseltamivir

1

145

Risk Ratio (M‐H, Random, 95% CI)

1.2 [0.50, 2.87]

9.4 Lianhua Qingwen capsule versus An ga huang min

1

145

Risk Ratio (M‐H, Random, 95% CI)

1.2 [0.50, 2.87]

9.5 Tanreqing + oseltamivir versus oseltamivir

1

87

Risk Ratio (M‐H, Random, 95% CI)

1.29 [0.84, 1.96]

9.6 TCM versus oseltamivir

1

60

Risk Ratio (M‐H, Random, 95% CI)

0.44 [0.15, 1.29]

9.7 E Shu You versus ribavirin

1

61

Risk Ratio (M‐H, Random, 95% CI)

0.91 [0.36, 2.27]

10 Adverse events Show forest plot

10

1011

Risk Ratio (M‐H, Random, 95% CI)

0.54 [0.26, 1.11]

10.1 TCM versus oseltamivir

3

154

Risk Ratio (M‐H, Random, 95% CI)

1.12 [0.04, 32.35]

10.2 Lianhua Qingwen versus oseltamivir

3

241

Risk Ratio (M‐H, Random, 95% CI)

0.34 [0.11, 1.02]

10.3 Fanggan granule versus conventional medicine

1

95

Risk Ratio (M‐H, Random, 95% CI)

0.98 [0.14, 6.67]

10.4 Antiwei versus placebo

1

225

Risk Ratio (M‐H, Random, 95% CI)

0.0 [0.0, 0.0]

10.5 Tanreqing plus oseltamivir versus oseltamivir

1

87

Risk Ratio (M‐H, Random, 95% CI)

0.0 [0.0, 0.0]

10.6 E Shu You versus Lymbaweilim

1

61

Risk Ratio (M‐H, Random, 95% CI)

0.60 [0.11, 3.36]

10.7 Lianhua Qingwen versus An ga huang min

1

148

Risk Ratio (M‐H, Random, 95% CI)

0.73 [0.08, 6.78]
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Comparison 1. Traditional Chinese medicine (TCM) versus other treatments
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