Remdesivir for the treatment of COVID-19.

Remdesivir is an antiviral medicine approved for the treatment of mild-to-moderate coronavirus disease 2019 (COVID-19). This led to widespread implementation, although the available evidence remains inconsistent. This update aims to fill current knowledge gaps by identifying, describing, evaluating, and synthesising all evidence from randomised controlled trials (RCTs) on the effects of remdesivir on clinical outcomes in COVID-19. To assess the effects of remdesivir and standard care compared to standard care plus/minus placebo on clinical outcomes in patients treated for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We searched the Cochrane COVID-19 Study Register (which comprises the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, ClinicalTrials.gov, World Health Organization (WHO) International Clinical Trials Registry Platform, and medRxiv) as well as Web of Science (Science Citation Index Expanded and Emerging Sources Citation Index) and WHO COVID-19 Global literature on coronavirus disease to identify completed and ongoing studies, without language restrictions. We conducted the searches on 31 May 2022. We followed standard Cochrane methodology. We included RCTs evaluating remdesivir and standard care for the treatment of SARS-CoV-2 infection compared to standard care plus/minus placebo irrespective of disease severity, gender, ethnicity, or setting. We excluded studies that evaluated remdesivir for the treatment of other coronavirus diseases. We followed standard Cochrane methodology. To assess risk of bias in included studies, we used the Cochrane RoB 2 tool for RCTs. We rated the certainty of evidence using the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) approach for outcomes that were reported according to our prioritised categories: all-cause mortality, in-hospital mortality, clinical improvement (being alive and ready for discharge up to day 28) or worsening (new need for invasive mechanical ventilation or death up to day 28), quality of life, serious adverse events, and adverse events (any grade). We differentiated between non-hospitalised individuals with asymptomatic SARS-CoV-2 infection or mild COVID-19 and hospitalised individuals with moderate to severe COVID-19. We included nine RCTs with 11,218 participants diagnosed with SARS-CoV-2 infection and a mean age of 53.6 years, of whom 5982 participants were randomised to receive remdesivir. Most participants required low-flow oxygen at baseline. Studies were mainly conducted in high- and upper-middle-income countries. We identified two studies that are awaiting classification and five ongoing studies. Effects of remdesivir in hospitalised individuals with moderate to severe COVID-19 With moderate-certainty evidence, remdesivir probably makes little or no difference to all-cause mortality at up to day 28 (risk ratio (RR) 0.93, 95% confidence interval (CI) 0.81 to 1.06; risk difference (RD) 8 fewer per 1000, 95% CI 21 fewer to 6 more; 4 studies, 7142 participants), day 60 (RR 0.85, 95% CI 0.69 to 1.05; RD 35 fewer per 1000, 95% CI 73 fewer to 12 more; 1 study, 1281 participants), or in-hospital mortality at up to day 150 (RR 0.93, 95% CI 0.84 to 1.03; RD 11 fewer per 1000, 95% CI 25 fewer to 5 more; 1 study, 8275 participants). Remdesivir probably increases the chance of clinical improvement at up to day 28 slightly (RR 1.11, 95% CI 1.06 to 1.17; RD 68 more per 1000, 95% CI 37 more to 105 more; 4 studies, 2514 participants; moderate-certainty evidence). It probably decreases the risk of clinical worsening within 28 days (hazard ratio (HR) 0.67, 95% CI 0.54 to 0.82; RD 135 fewer per 1000, 95% CI 198 fewer to 69 fewer; 2 studies, 1734 participants, moderate-certainty evidence). Remdesivir may make little or no difference to the rate of adverse events of any grade (RR 1.04, 95% CI 0.92 to 1.18; RD 23 more per 1000, 95% CI 46 fewer to 104 more; 4 studies, 2498 participants; low-certainty evidence), or serious adverse events (RR 0.84, 95% CI 0.65 to 1.07; RD 44 fewer per 1000, 95% CI 96 fewer to 19 more; 4 studies, 2498 participants; low-certainty evidence). We considered risk of bias to be low, with some concerns for mortality and clinical course. We had some concerns for safety outcomes because participants who had died did not contribute information. Without adjustment, this leads to an uncertain amount of missing values and the potential for bias due to missing data. Effects of remdesivir in non-hospitalised individuals with mild COVID-19 One of the nine RCTs was conducted in the outpatient setting and included symptomatic people with a risk of progression. No deaths occurred within the 28 days observation period. We are uncertain about clinical improvement due to very low-certainty evidence. Remdesivir probably decreases the risk of clinical worsening (hospitalisation) at up to day 28 (RR 0.28, 95% CI 0.11 to 0.75; RD 46 fewer per 1000, 95% CI 57 fewer to 16 fewer; 562 participants; moderate-certainty evidence). We did not find any data for quality of life. Remdesivir may decrease the rate of serious adverse events at up to 28 days (RR 0.27, 95% CI 0.10 to 0.70; RD 49 fewer per 1000, 95% CI 60 fewer to 20 fewer; 562 participants; low-certainty evidence), but it probably makes little or no difference to the risk of adverse events of any grade (RR 0.91, 95% CI 0.76 to 1.10; RD 42 fewer per 1000, 95% CI 111 fewer to 46 more; 562 participants; moderate-certainty evidence). We considered risk of bias to be low for mortality, clinical improvement, and safety outcomes. We identified a high risk of bias for clinical worsening. Based on the available evidence up to 31 May 2022, remdesivir probably has little or no effect on all-cause mortality or in-hospital mortality of individuals with moderate to severe COVID-19. The hospitalisation rate was reduced with remdesivir in one study including participants with mild to moderate COVID-19. It may be beneficial in the clinical course for both hospitalised and non-hospitalised patients, but certainty remains limited. The applicability of the evidence to current practice may be limited by the recruitment of participants from mostly unvaccinated populations exposed to early variants of the SARS-CoV-2 virus at the time the studies were undertaken.  Future studies should provide additional data on the efficacy and safety of remdesivir for defined core outcomes in COVID-19 research, especially for different population subgroups.

Grundeis F ，Ansems K ，Dahms K ，Thieme V ，Metzendorf MI ，Skoetz N ，Benstoem C ，Mikolajewska A ，Griesel M ，Fichtner F ，Stegemann M ... -  《Cochrane Database of Systematic Reviews》

Remdesivir for the treatment of COVID-19.

Remdesivir is an antiviral medicine with properties to inhibit viral replication of SARS-CoV-2. Positive results from early studies attracted media attention and led to emergency use authorisation of remdesivir in COVID-19.  A thorough understanding of the current evidence regarding the effects of remdesivir as a treatment for SARS-CoV-2 infection based on randomised controlled trials (RCTs) is required. To assess the effects of remdesivir compared to placebo or standard care alone on clinical outcomes in hospitalised patients with SARS-CoV-2 infection, and to maintain the currency of the evidence using a living systematic review approach. We searched the Cochrane COVID-19 Study Register (which comprises the Cochrane Central Register of Controlled Trials (CENTRAL), PubMed, Embase, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, and medRxiv) as well as Web of Science (Science Citation Index Expanded and Emerging Sources Citation Index) and WHO COVID-19 Global literature on coronavirus disease to identify completed and ongoing studies without language restrictions. We conducted the searches on 16 April 2021. We followed standard Cochrane methodology. We included RCTs evaluating remdesivir for the treatment of SARS-CoV-2 infection in hospitalised adults compared to placebo or standard care alone irrespective of disease severity, gender, ethnicity, or setting.  We excluded studies that evaluated remdesivir for the treatment of other coronavirus diseases. We followed standard Cochrane methodology. To assess risk of bias in included studies, we used the Cochrane RoB 2 tool for RCTs. We rated the certainty of evidence using the GRADE approach for outcomes that were reported according to our prioritised categories: all-cause mortality at up to day 28, duration to liberation from invasive mechanical ventilation, duration to liberation from supplemental oxygen, new need for mechanical ventilation (high-flow oxygen or non-invasive or invasive mechanical ventilation), new need for invasive mechanical ventilation, new need for non-invasive mechanical ventilation or high-flow oxygen, new need for oxygen by mask or nasal prongs, quality of life, adverse events (any grade), and serious adverse events. We included five RCTs with 7452 participants diagnosed with SARS-CoV-2 infection and a mean age of 59 years, of whom 3886 participants were randomised to receive remdesivir. Most participants required low-flow oxygen (n=4409) or mechanical ventilation (n=1025) at baseline. We identified two ongoing studies, one was suspended due to a lack of COVID-19 patients to recruit. Risk of bias was considered to be of some concerns or high risk for clinical status and safety outcomes because participants who had died did not contribute information to these outcomes. Without adjustment, this leads to an uncertain amount of missing values and the potential for bias due to missing data. Effects of remdesivir in hospitalised individuals  Remdesivir probably makes little or no difference to all-cause mortality at up to day 28 (risk ratio (RR) 0.93, 95% confidence interval (CI) 0.81 to 1.06; risk difference (RD) 8 fewer per 1000, 95% CI 21 fewer to 7 more; 4 studies, 7142 participants; moderate-certainty evidence). Considering the initial severity of condition, only one study showed a beneficial effect of remdesivir in patients who received low-flow oxygen at baseline (RR 0.32, 95% CI 0.15 to 0.66, 435 participants), but conflicting results exists from another study, and we were unable to validly assess this observations due to limited availability of comparable data. Remdesivir may have little or no effect on the duration to liberation from invasive mechanical ventilation (2 studies, 1298 participants, data not pooled, low-certainty evidence). We are uncertain whether remdesivir increases or decreases the chance of clinical improvement in terms of duration to liberation from supplemental oxygen at up to day 28 (3 studies, 1691 participants, data not pooled, very low-certainty evidence).   We are very uncertain whether remdesivir decreases or increases the risk of clinical worsening in terms of new need for mechanical ventilation at up to day 28 (high-flow oxygen or non-invasive ventilation or invasive mechanical ventilation) (RR 0.78, 95% CI 0.48 to 1.24; RD 29 fewer per 1000, 95% CI 68 fewer to 32 more; 3 studies, 6696 participants; very low-certainty evidence); new need for non-invasive mechanical ventilation or high-flow oxygen (RR 0.70, 95% CI 0.51 to 0.98; RD 72 fewer per 1000, 95% CI 118 fewer to 5 fewer; 1 study, 573 participants; very low-certainty evidence); and new need for oxygen by mask or nasal prongs (RR 0.81, 95% CI 0.54 to 1.22; RD 84 fewer per 1000, 95% CI 204 fewer to 98 more; 1 study, 138 participants; very low-certainty evidence). The evidence suggests that remdesivir may decrease the risk of clinical worsening in terms of new need for invasive mechanical ventilation (67 fewer participants amongst 1000 participants; RR 0.56, 95% CI 0.41 to 0.77; 2 studies, 1159 participants; low-certainty evidence).  None of the included studies reported quality of life. Remdesivir probably decreases the serious adverse events rate at up to 28 days (RR 0.75, 95% CI 0.63 to 0.90; RD 63 fewer per 1000, 95% CI 94 fewer to 25 fewer; 3 studies, 1674 participants; moderate-certainty evidence). We are very uncertain whether remdesivir increases or decreases adverse events rate (any grade) (RR 1.05, 95% CI 0.86 to 1.27; RD 29 more per 1000, 95% CI 82 fewer to 158 more; 3 studies, 1674 participants; very low-certainty evidence). Based on the currently available evidence, we are moderately certain that remdesivir probably has little or no effect on all-cause mortality at up to day 28 in hospitalised adults with SARS-CoV-2 infection. We are uncertain about the effects of remdesivir on clinical improvement and worsening. There were insufficient data available to validly examine the effect of remdesivir on mortality in subgroups depending on the extent of respiratory support at baseline.  Future studies should provide additional data on efficacy and safety of remdesivir for defined core outcomes in COVID-19 research, especially for different population subgroups. This could allow us to draw more reliable conclusions on the potential benefits and harms of remdesivir in future updates of this review. Due to the living approach of this work, we will update the review periodically.

Ansems K ，Grundeis F ，Dahms K ，Mikolajewska A ，Thieme V ，Piechotta V ，Metzendorf MI ，Stegemann M ，Benstoem C ，Fichtner F ... -  《Cochrane Database of Systematic Reviews》

Colchicine for the treatment of COVID-19.

The development of severe coronavirus disease 2019 (COVID-19) and poor clinical outcomes are associated with hyperinflammation and a complex dysregulation of the immune response. Colchicine is an anti-inflammatory medicine and is thought to improve disease outcomes in COVID-19 through a wide range of anti-inflammatory mechanisms. Patients and healthcare systems need more and better treatment options for COVID-19 and a thorough understanding of the current body of evidence. To assess the effectiveness and safety of Colchicine as a treatment option for COVID-19 in comparison to an active comparator, placebo, or standard care alone in any setting, and to maintain the currency of the evidence, using a living systematic review approach. We searched the Cochrane COVID-19 Study Register (comprising CENTRAL, MEDLINE (PubMed), Embase, ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, and medRxiv), Web of Science (Science Citation Index Expanded and Emerging Sources Citation Index), and WHO COVID-19 Global literature on coronavirus disease to identify completed and ongoing studies without language restrictions to 21 May 2021. We included randomised controlled trials evaluating colchicine for the treatment of people with COVID-19, irrespective of disease severity, age, sex, or ethnicity. We excluded studies investigating the prophylactic effects of colchicine for people without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection but at high risk of SARS-CoV-2 exposure. We followed standard Cochrane methodology. We used the Cochrane risk of bias tool (ROB 2) to assess bias in included studies and GRADE to rate the certainty of evidence for the following prioritised outcome categories considering people with moderate or severe COVID-19: all-cause mortality, worsening and improvement of clinical status, quality of life, adverse events, and serious adverse events and for people with asymptomatic infection or mild disease: all-cause mortality, admission to hospital or death, symptom resolution, duration to symptom resolution, quality of life, adverse events, serious adverse events. We included three RCTs with 11,525 hospitalised participants (8002 male) and one RCT with 4488 (2067 male) non-hospitalised participants. Mean age of people treated in hospital was about 64 years, and was 55 years in the study with non-hospitalised participants. Further, we identified 17 ongoing studies and 11 studies completed or terminated, but without published results. Colchicine plus standard care versus standard care (plus/minus placebo) Treatment of hospitalised people with moderate to severe COVID-19 All-cause mortality: colchicine plus standard care probably results in little to no difference in all-cause mortality up to 28 days compared to standard care alone (risk ratio (RR) 1.00, 95% confidence interval (CI) 0.93 to 1.08; 2 RCTs, 11,445 participants; moderate-certainty evidence). Worsening of clinical status: colchicine plus standard care probably results in little to no difference in worsening of clinical status assessed as new need for invasive mechanical ventilation or death compared to standard care alone (RR 1.02, 95% CI 0.96 to 1.09; 2 RCTs, 10,916 participants; moderate-certainty evidence). Improvement of clinical status: colchicine plus standard care probably results in little to no difference in improvement of clinical status, assessed as number of participants discharged alive up to day 28 without clinical deterioration or death compared to standard care alone (RR 0.99, 95% CI 0.96 to 1.01; 1 RCT, 11,340 participants; moderate-certainty evidence). Quality of life, including fatigue and neurological status: we identified no studies reporting this outcome. Adverse events: the evidence is very uncertain about the effect of colchicine on adverse events compared to placebo (RR 1.00, 95% CI 0.56 to 1.78; 1 RCT, 72 participants; very low-certainty evidence). Serious adverse events: the evidence is very uncertain about the effect of colchicine plus standard care on serious adverse events compared to standard care alone (0 events observed in 1 RCT of 105 participants; very low-certainty evidence). Treatment of non-hospitalised people with asymptomatic SARS-CoV-2 infection or mild COVID-19 All-cause mortality: the evidence is uncertain about the effect of colchicine on all-cause mortality at 28 days (Peto odds ratio (OR) 0.57, 95% CI 0.20 to 1.62; 1 RCT, 4488 participants; low-certainty evidence). Admission to hospital or death within 28 days: colchicine probably slightly reduces the need for hospitalisation or death within 28 days compared to placebo (RR 0.80, 95% CI 0.62 to 1.03; 1 RCT, 4488 participants; moderate-certainty evidence). Symptom resolution: we identified no studies reporting this outcome. Quality of life, including fatigue and neurological status: we identified no studies reporting this outcome. Adverse events: the evidence is uncertain about the effect of colchicine on adverse events compared to placebo . Results are from one RCT reporting treatment-related events only in 4412 participants (low-certainty evidence). Serious adverse events: colchicine probably slightly reduces serious adverse events (RR 0.78, 95% CI 0.61 to 1.00; 1 RCT, 4412 participants; moderate-certainty evidence). Colchicine versus another active treatment (e.g. corticosteroids, anti-viral drugs, monoclonal antibodies) No studies evaluated this comparison. Different formulations, doses, or schedules of colchicine No studies assessed this. Based on the current evidence, in people hospitalised with moderate to severe COVID-19 the use of colchicine probably has little to no influence on mortality or clinical progression in comparison to placebo or standard care alone. We do not know whether colchicine increases the risk of (serious) adverse events. We are uncertain about the evidence of the effect of colchicine on all-cause mortality for people with asymptomatic infection or mild disease. However, colchicine probably results in a slight reduction of hospital admissions or deaths within 28 days, and the rate of serious adverse events compared with placebo. None of the studies reported data on quality of life or compared the benefits and harms of colchicine versus other drugs, or different dosages of colchicine. We identified 17 ongoing and 11 completed but not published RCTs, which we expect to incorporate in future versions of this review as their results become available. Editorial note: due to the living approach of this work, we monitor newly published results of RCTs on colchicine on a weekly basis and will update the review when the evidence or our certainty in the evidence changes.

Mikolajewska A ，Fischer AL ，Piechotta V ，Mueller A ，Metzendorf MI ，Becker M ，Dorando E ，Pacheco RL ，Martimbianco ALC ，Riera R ，Skoetz N ，Stegemann M ... -  《Cochrane Database of Systematic Reviews》

Janus kinase inhibitors for the treatment of COVID-19.

With potential antiviral and anti-inflammatory properties, Janus kinase (JAK) inhibitors represent a potential treatment for symptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. They may modulate the exuberant immune response to SARS-CoV-2 infection. Furthermore, a direct antiviral effect has been described. An understanding of the current evidence regarding the efficacy and safety of JAK inhibitors as a treatment for coronavirus disease 2019 (COVID-19) is required. To assess the effects of systemic JAK inhibitors plus standard of care compared to standard of care alone (plus/minus placebo) on clinical outcomes in individuals (outpatient or in-hospital) with any severity of COVID-19, and to maintain the currency of the evidence using a living systematic review approach. We searched the Cochrane COVID-19 Study Register (comprising MEDLINE, Embase, ClinicalTrials.gov, World Health Organization (WHO) International Clinical Trials Registry Platform, medRxiv, and Cochrane Central Register of Controlled Trials), Web of Science, WHO COVID-19 Global literature on coronavirus disease, and the US Department of Veterans Affairs Evidence Synthesis Program (VA ESP) Covid-19 Evidence Reviews to identify studies up to February 2022. We monitor newly published randomised controlled trials (RCTs) weekly using the Cochrane COVID-19 Study Register, and have incorporated all new trials from this source until the first week of April 2022. We included RCTs that compared systemic JAK inhibitors plus standard of care to standard of care alone (plus/minus placebo) for the treatment of individuals with COVID-19. We used the WHO definitions of illness severity for COVID-19. We assessed risk of bias of primary outcomes using Cochrane's Risk of Bias 2 (RoB 2) tool. We used GRADE to rate the certainty of evidence for the following primary outcomes: all-cause mortality (up to day 28), all-cause mortality (up to day 60), improvement in clinical status: alive and without need for in-hospital medical care (up to day 28), worsening of clinical status: new need for invasive mechanical ventilation or death (up to day 28), adverse events (any grade), serious adverse events, secondary infections. We included six RCTs with 11,145 participants investigating systemic JAK inhibitors plus standard of care compared to standard of care alone (plus/minus placebo). Standard of care followed local protocols and included the application of glucocorticoids (five studies reported their use in a range of 70% to 95% of their participants; one study restricted glucocorticoid use to non-COVID-19 specific indications), antibiotic agents, anticoagulants, and antiviral agents, as well as non-pharmaceutical procedures. At study entry, about 65% of participants required low-flow oxygen, about 23% required high-flow oxygen or non-invasive ventilation, about 8% did not need any respiratory support, and only about 4% were intubated. We also identified 13 ongoing studies, and 9 studies that are completed or terminated and where classification is pending. Individuals with moderate to severe disease Four studies investigated the single agent baricitinib (10,815 participants), one tofacitinib (289 participants), and one ruxolitinib (41 participants). Systemic JAK inhibitors probably decrease all-cause mortality at up to day 28 (95 of 1000 participants in the intervention group versus 131 of 1000 participants in the control group; risk ratio (RR) 0.72, 95% confidence interval (CI) 0.57 to 0.91; 6 studies, 11,145 participants; moderate-certainty evidence), and decrease all-cause mortality at up to day 60 (125 of 1000 participants in the intervention group versus 181 of 1000 participants in the control group; RR 0.69, 95% CI 0.56 to 0.86; 2 studies, 1626 participants; high-certainty evidence). Systemic JAK inhibitors probably make little or no difference in improvement in clinical status (discharged alive or hospitalised, but no longer requiring ongoing medical care) (801 of 1000 participants in the intervention group versus 778 of 1000 participants in the control group; RR 1.03, 95% CI 1.00 to 1.06; 4 studies, 10,802 participants; moderate-certainty evidence). They probably decrease the risk of worsening of clinical status (new need for invasive mechanical ventilation or death at day 28) (154 of 1000 participants in the intervention group versus 172 of 1000 participants in the control group; RR 0.90, 95% CI 0.82 to 0.98; 2 studies, 9417 participants; moderate-certainty evidence). Systemic JAK inhibitors probably make little or no difference in the rate of adverse events (any grade) (427 of 1000 participants in the intervention group versus 441 of 1000 participants in the control group; RR 0.97, 95% CI 0.88 to 1.08; 3 studies, 1885 participants; moderate-certainty evidence), and probably decrease the occurrence of serious adverse events (160 of 1000 participants in the intervention group versus 202 of 1000 participants in the control group; RR 0.79, 95% CI 0.68 to 0.92; 4 studies, 2901 participants; moderate-certainty evidence). JAK inhibitors may make little or no difference to the rate of secondary infection (111 of 1000 participants in the intervention group versus 113 of 1000 participants in the control group; RR 0.98, 95% CI 0.89 to 1.09; 4 studies, 10,041 participants; low-certainty evidence). Subgroup analysis by severity of COVID-19 disease or type of JAK inhibitor did not identify specific subgroups which benefit more or less from systemic JAK inhibitors. Individuals with asymptomatic or mild disease We did not identify any trial for this population. In hospitalised individuals with moderate to severe COVID-19, moderate-certainty evidence shows that systemic JAK inhibitors probably decrease all-cause mortality. Baricitinib was the most often evaluated JAK inhibitor. Moderate-certainty evidence suggests that they probably make little or no difference in improvement in clinical status. Moderate-certainty evidence indicates that systemic JAK inhibitors probably decrease the risk of worsening of clinical status and make little or no difference in the rate of adverse events of any grade, whilst they probably decrease the occurrence of serious adverse events. Based on low-certainty evidence, JAK inhibitors may make little or no difference in the rate of secondary infection. Subgroup analysis by severity of COVID-19 or type of agent failed to identify specific subgroups which benefit more or less from systemic JAK inhibitors. Currently, there is no evidence on the efficacy and safety of systemic JAK inhibitors for individuals with asymptomatic or mild disease (non-hospitalised individuals).

Kramer A ，Prinz C ，Fichtner F ，Fischer AL ，Thieme V ，Grundeis F ，Spagl M ，Seeber C ，Piechotta V ，Metzendorf MI ，Golinski M ，Moerer O ，Stephani C ，Mikolajewska A ，Kluge S ，Stegemann M ，Laudi S ，Skoetz N ... -  《Cochrane Database of Systematic Reviews》

Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.

Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria. To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure? Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).

Crider K ，Williams J ，Qi YP ，Gutman J ，Yeung L ，Mai C ，Finkelstain J ，Mehta S ，Pons-Duran C ，Menéndez C ，Moraleda C ，Rogers L ，Daniels K ，Green P ... -  《Cochrane Database of Systematic Reviews》