Tailored or adapted interventions for adults with chronic obstructive pulmonary disease and at least one other long-term condition: a mixed methods review.

Chronic obstructive pulmonary disease (COPD) is a chronic respiratory condition characterised by shortness of breath, cough and recurrent exacerbations. People with COPD often live with one or more co-existing long-term health conditions (comorbidities). People with more severe COPD often have a higher number of comorbidities, putting them at greater risk of morbidity and mortality. To assess the effectiveness of any single intervention for COPD adapted or tailored to their comorbidity(s) compared to any other intervention for people with COPD and one or more common comorbidities (quantitative data, RCTs) in terms of the following outcomes: Quality of life, exacerbations, functional status, all-cause and respiratory-related hospital admissions, mortality, pain, and depression and anxiety. To assess the effectiveness of an adapted or tailored single COPD intervention (simple or complex) that is aimed at changing the management of people with COPD and one or more common comorbidities (quantitative data, RCTs) compared to usual care in terms of the following outcomes: Quality of life, exacerbations, functional status, all-cause and respiratory-related hospital admissions, mortality, pain, and depression and anxiety. To identify emerging themes that describe the views and experiences of patients, carers and healthcare professionals when receiving or providing care to manage multimorbidities (qualitative data). We searched multiple databases including the Cochrane Airways Trials Register, CENTRAL, MEDLINE, Embase, and CINAHL, to identify relevant randomised and qualitative studies. We also searched trial registries and conducted citation searches. The latest search was conducted in January 2021. Eligible randomised controlled trials (RCTs) compared a) any single intervention for COPD adapted or tailored to their comorbidity(s) compared to any other intervention, or b) any adapted or tailored single COPD intervention (simple or complex) that is aimed at changing the management of people with COPD and one or more comorbidities, compared to usual care. We included qualitative studies or mixed-methods studies to identify themes. We used standard Cochrane methods for analysis of the RCTs. We used Cochrane's risk of bias tool for the RCTs and the CASP checklist for the qualitative studies. We planned to use the Mixed Methods Appraisal tool (MMAT) to assess the risk of bias in mixed-methods studies, but we found none. We used GRADE and CERQual to assess the quality of the quantitative and qualitative evidence respectively. The primary outcome measures for this review were quality of life and exacerbations. Quantitative studies We included seven studies (1197 participants) in the quantitative analyses, with interventions including telemonitoring, pulmonary rehabilitation, treatment optimisation, water-based exercise training and case management. Interventions were either compared with usual care or with an active comparator (such as land-based exercise training). Duration of trials ranged from 4 to 52 weeks. Mean age of participants ranged from 64 to 72 years and COPD severity ranged from mild to very severe. Trials included either people with COPD and a specific comorbidity (including cardiovascular disease, metabolic syndrome, lung cancer, head or neck cancer, and musculoskeletal conditions), or with one or more comorbidities of any type. Overall, we judged the evidence presented to be of moderate to very low certainty (GRADE), mainly due to the methodological quality of included trials and imprecision of effect estimates. Intervention versus usual care Quality of life as measured by the St George's Respiratory Questionnaire (SGRQ) total score may improve with tailored pulmonary rehabilitation compared to usual care at 52 weeks (mean difference (MD) -10.85, 95% confidence interval (CI) -12.66 to -9.04; 1 study, 70 participants; low-certainty evidence). Tailored pulmonary rehabilitation is likely to improve COPD assessment test (CAT) scores compared with usual care at 52 weeks (MD -8.02, 95% CI -9.44 to -6.60; 1 study, 70 participants, moderate-certainty evidence) and with a multicomponent telehealth intervention at 52 weeks (MD -6.90, 95% CI -9.56 to -4.24; moderate-certainty evidence). Evidence is uncertain about effects of pharmacotherapy optimisation or telemonitoring interventions on CAT improvement compared with usual care. There may be little to no difference in the number of people experiencing exacerbations, or mean exacerbations with case management compared with usual care (OR 1.09, 95% CI 0.75 to 1.57; 1 study, 470 participants; very low-certainty evidence). For secondary outcomes, six-minute walk distance (6MWD) may improve with pulmonary rehabilitation, water-based exercise or multicomponent interventions at 38 to 52 weeks (low-certainty evidence). A multicomponent intervention may result in fewer people being admitted to hospital at 17 weeks, although there may be little to no difference in a telemonitoring intervention. There may be little to no difference between intervention and usual care for mortality. Intervention versus active comparator We included one study comparing water-based and land-based exercise (30 participants). We found no evidence for quality of life or exacerbations. There may be little to no difference between water- and land-based exercise for 6MWD (MD 5 metres, 95% CI -22 to 32; 38 participants; very low-certainty evidence). Qualitative studies One nested qualitative study (21 participants) explored perceptions and experiences of people with COPD and long-term conditions, and of researchers and health professionals who were involved in an RCT of telemonitoring equipment. Several themes were identified, including health status, beliefs and concerns, reliability of equipment, self-efficacy, perceived ease of use, factors affecting usefulness and perceived usefulness, attitudes and intention, self-management and changes in healthcare use. We judged the qualitative evidence presented as of very low certainty overall. Owing to a paucity of eligible trials, as well as diversity in the intervention type, comorbidities and the outcome measures reported, we were unable to provide a robust synthesis of data. Pulmonary rehabilitation or multicomponent interventions may improve quality of life and functional status (6MWD), but the evidence is too limited to draw a robust conclusion. The key take-home message from this review is the lack of data from RCTs on treatments for people living with COPD and comorbidities. Given the variation in number and type of comorbidity(s) an individual may have, and severity of COPD, larger studies reporting individual patient data are required to determine these effects.

Dennett EJ ，Janjua S ，Stovold E ，Harrison SL ，McDonnell MJ ，Holland AE ... -  《Cochrane Database of Systematic Reviews》

Telehealth interventions: remote monitoring and consultations for people with chronic obstructive pulmonary disease (COPD).

Chronic obstructive pulmonary disease (COPD, including bronchitis and emphysema) is a chronic condition causing shortness of breath, cough, and exacerbations leading to poor health outcomes. Face-to-face visits with health professionals can be hindered by severity of COPD or frailty, and by people living at a distance from their healthcare provider and having limited access to services. Telehealth technologies aimed at providing health care remotely through monitoring and consultations could help to improve health outcomes of people with COPD. To assess the effectiveness of telehealth interventions that allow remote monitoring and consultation and multi-component interventions for reducing exacerbations and improving quality of life, while reducing dyspnoea symptoms, hospital service utilisation, and death among people with COPD. We identified studies from the Cochrane Airways Trials Register. Additional sources searched included the US National Institutes of Health Ongoing Trials Register, the World Health Organization International Clinical Trials Registry Platform, and the IEEEX Xplore Digital Library. The latest search was conducted in April 2020. We used the GRADE approach to judge the certainty of evidence for outcomes. Eligible randomised controlled trials (RCTs) included adults with diagnosed COPD. Asthma, cystic fibrosis, bronchiectasis, and other respiratory conditions were excluded. Interventions included remote monitoring or consultation plus usual care, remote monitoring or consultation alone, and mult-component interventions from all care settings. Quality of life scales included St George's Respiratory Questionnaire (SGRQ) and the COPD Assessment Test (CAT). The dyspnoea symptom scale used was the Chronic Respiratory Disease Questionnaire Self-Administered Standardized Scale (CRQ-SAS). We used standard Cochrane methodological procedures. We assessed confidence in the evidence for each primary outcome using the GRADE method. Primary outcomes were exacerbations, quality of life, dyspnoea symptoms, hospital service utilisation, and mortality; a secondary outcome consisted of adverse events. We included 29 studies in the review (5654 participants; male proportion 36% to 96%; female proportion 4% to 61%). Most remote monitoring interventions required participants to transfer measurements using a remote device and later health professional review (asynchronous). Only five interventions transferred data and allowed review by health professionals in real time (synchronous). Studies were at high risk of bias due to lack of blinding, and certainty of evidence ranged from moderate to very low. We found no evidence on comparison of remote consultations with or without usual care. Remote monitoring plus usual care (8 studies, 1033 participants) Very uncertain evidence suggests that remote monitoring plus usual care may have little to no effect on the number of people experiencing exacerbations at 26 weeks or 52 weeks. There may be little to no difference in effect on quality of life (SGRQ) at 26 weeks (very low to low certainty) or on hospitalisation (all-cause or COPD-related; very low certainty). COPD-related hospital re-admissions are probably reduced at 26 weeks (hazard ratio 0.42, 95% confidence interval (CI) 0.19 to 0.93; 106 participants; moderate certainty). There may be little to no difference in deaths between intervention and usual care (very low certainty). We found no evidence for dyspnoea symptoms or adverse events. Remote monitoring alone (10 studies, 2456 participants) Very uncertain evidence suggests that remote monitoring may result in little to no effect on the number of people experiencing exacerbations at 41 weeks (odds ratio 1.02, 95% CI 0.67 to 1.55). There may be little to no effect on quality of life (SGRQ total at 17 weeks, or CAT at 38 and 52 weeks; very low certainty). There may be little to no effect on dyspnoea symptoms on the CRQ-SAS at 26 weeks (low certainty). There may be no difference in effects on the number of people admitted to hospital (very low certainty) or on deaths (very low certainty). We found no evidence for adverse events. Multi-component interventions with remote monitoring or consultation component (11 studies, 2165 participants) Very uncertain evidence suggests that multi-component interventions may have little to no effect on the number of people experiencing exacerbations at 52 weeks. Quality of life at 13 weeks may improve as seen in SGRQ total score (mean difference -9.70, 95% CI -18.32 to -1.08; 38 participants; low certainty) but not at 26 or 52 weeks (very low certainty). COPD assessment test (CAT) scores may improve at a mean of 38 weeks, but evidence is very uncertain and interventions are varied. There may be little to no effect on the number of people admitted to hospital at 33 weeks (low certainty). Multi-component interventions are likely to result in fewer people re-admitted to hospital at a mean of 39 weeks (OR 0.50, 95% CI 0.31 to 0.81; 344 participants, 3 studies; moderate certainty). There may be little to no difference in death at a mean of 40 weeks (very low certainty). There may be little to no effect on people experiencing adverse events (very low certainty). We found no evidence for dyspnoea symptoms. Remote monitoring plus usual care provided asynchronously may not be beneficial overall compared to usual care alone. Some benefit is seen in reduction of COPD-related hospital re-admissions, but moderate-certainty evidence is based on one study. We have not found any evidence for dyspnoea symptoms nor harms, and there is no difference in fatalities when remote monitoring is provided in addition to usual care. Remote monitoring interventions alone are no better than usual care overall for health outcomes. Multi-component interventions with asynchronous remote monitoring are no better than usual care but may provide short-term benefit for quality of life and may result in fewer re-admissions to hospital for any cause. We are uncertain whether remote monitoring is responsible for the positive impact on re-admissions, and we are unable to discern the long-term benefits of receiving remote monitoring as part of patient care. Owing to paucity of evidence, it is unclear which COPD severity subgroups would benefit from telehealth interventions. Given there is no evidence of harm, telehealth interventions may be beneficial as an additional health resource depending on individual needs based on professional assessment. Larger studies can determine long-term effects of these interventions.

Janjua S ，Carter D ，Threapleton CJ ，Prigmore S ，Disler RT ... -  《Cochrane Database of Systematic Reviews》

Digital interventions for the management of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is associated with dyspnoea, cough or sputum production (or both) and affects quality of life and functional status. More efficient approaches to alternative management that may include patients themselves managing their condition need further exploration in order to reduce the impact on both patients and healthcare services. Digital interventions may potentially impact on health behaviours and encourage patient engagement. To assess benefits and harms of digital interventions for managing COPD and apply Behaviour Change Technique (BCT) taxonomy to describe and explore intervention content. We identified randomised controlled trials (RCTs) from the Cochrane Airways Trials Register (date of last search 28 April 2020). We found other trials at web-based clinical trials registers. We included RCTs comparing digital technology interventions with or without routine supported self-management to usual care, or control treatment for self-management. Multi-component interventions (of which one component was digital self-management) compared with usual care, standard care or control treatment were included. We used standard Cochrane methods. Two review authors independently selected trials for inclusion, extracted data, and assessed risk of bias. Discrepancies were resolved with a third review author. We assessed certainty of the evidence using the GRADE approach. Primary outcomes were impact on health behaviours, self-efficacy, exacerbations and quality of life, including the St George's Respiratory Questionnaire (SGRQ). The minimally important difference (MID) for the SGRQ is 4 points. Two review authors independently applied BCT taxonomy to identify mechanisms in the digital interventions that influence behaviours. Fourteen studies were included in the meta-analyses (1518 participants) ranging from 13 to 52 weeks duration. Participants had mild to very severe COPD. Risk of bias was high due to lack of blinding. GRADE ratings were low to very low certainty due to lack of blinding and imprecision. Common BCT clusters identified as behaviour change mechanisms in interventions were goals and planning, feedback and monitoring, social support, shaping knowledge and antecedents. Digital technology intervention with or without routine supported self-management Interventions included mobile phone (three studies), smartphone applications (one study), and web or Internet-based (five studies). Evidence is very uncertain about effects on impact on health behaviours as measured by six-minute walk distance (6MWD) at 13 weeks (mean difference (MD) 26.20, 95% confidence interval (CI) -21.70 to 74.10; participants = 122; studies = 2) or 23 to 26 weeks (MD 14.31, 95% CI -19.41 to 48.03; participants = 164; studies = 3). There may be improvement in 6MWD at 52 weeks (MD 54.33 95% CI -35.47 to 144.12; participants = 204; studies = 2) but studies were varied (very low certainty). There may be no difference in self-efficacy on managing Chronic Disease Scale (SEMCD) or pulmonary rehabilitation adapted index of self-efficacy tool (PRAISE). Evidence is very uncertain. Quality of life may be slightly improved on the chronic respiratory disease questionnaire (CRQ) at 13 weeks (MD 0.45, 95% CI 0.01 to 0.90; participants = 123; studies = 2; low certainty), but is not clinically important (MID 0.5). There may be little or no difference at 23 or 52 weeks (low to very low certainty). There may be a clinical improvement on SGRQ total at 52 weeks (MD -26.57, 95% CI -34.09 to -19.05; participants = 120; studies = 1; low certainty). Evidence for COPD assessment test (CAT) and Clinical COPD Questionnaire (CCQ) is very uncertain. There may be little or no difference in dyspnoea symptoms (CRQ dyspnoea) at 13, 23 weeks or 52 weeks (low to very low certainty evidence) or mean number of exacerbations at 26 weeks (low-certainty evidence). There was no evidence for the number of people experiencing adverse events. Multi-component interventions Digital components included mobile phone (one study), and web or internet-based (four studies). Evidence is very uncertain about effects on impact on health behaviour (6MWD) at 13 weeks (MD 99.60, 95% CI -15.23 to 214.43; participants = 20; studies = 1). No evidence was found for self-efficacy. Four studies reported effects on quality of life (SGRQ and CCQ scales). The evidence is very uncertain. There may be no difference in the number of people experiencing exacerbations or mean days to first exacerbation at 52 weeks with a multi-component intervention compared to standard care. Evidence is very uncertain about effects on the number of people experiencing adverse events at 52 weeks. There is insufficient evidence to demonstrate a clear benefit or harm of digital technology interventions with or without supported self-management, or multi-component interventions compared to usual care in improving the 6MWD or self-efficacy. We found there may be some short-term improvement in quality of life with digital interventions, but there is no evidence about whether the effect is sustained long term. Dyspnoea symptoms may improve over a longer duration of digital intervention use. The evidence for multi-component interventions is very uncertain and as there is little or no evidence for adverse events, we cannot determine the benefit or harm of these interventions. The evidence base is predominantly of very low certainty with concerns around high risk of bias due to lack of blinding. Given that variation of interventions and blinding is likely to be a concern, future, larger studies are needed taking these limitations in consideration. Future studies are needed to determine whether the small improvements observed in this review can be applied to the general COPD population. A clear understanding of behaviour change through the BCT classification is important to gauge uptake of digital interventions and health outcomes in people with varying severity of COPD. Currently there is no guidance for interpreting BCT components of a digital intervention for changes to health outcomes. We could not interpret the BCT findings to the health outcomes we were investigating due to limited evidence that was of very low certainty. In future research, standardised approaches need to be considered when designing protocols to investigate effectiveness of digital interventions by including a standardised approach to BCT classification in addition to validated behavioural outcome measures that may reflect changes in behaviour.

Janjua S ，Banchoff E ，Threapleton CJ ，Prigmore S ，Fletcher J ，Disler RT ... -  《Cochrane Database of Systematic Reviews》

Interventions to improve adherence to pharmacological therapy for chronic obstructive pulmonary disease (COPD).

Chronic obstructive pulmonary disease (COPD) is a chronic lung condition characterised by persistent respiratory symptoms and limited lung airflow, dyspnoea and recurrent exacerbations. Suboptimal therapy or non-adherence may result in limited effectiveness of pharmacological treatments and subsequently poor health outcomes. To determine the efficacy and safety of interventions intended to improve adherence to single or combined pharmacological treatments compared with usual care or interventions that are not intended to improve adherence in people with COPD. We identified randomised controlled trials (RCTs) from the Cochrane Airways Trials Register, CENTRAL, MEDLINE and Embase (search date 1 May 2020). We also searched web-based clinical trial registers. RCTs included adults with COPD diagnosed by established criteria (e.g. Global Initiative for Obstructive Lung Disease). Interventions included change to pharmacological treatment regimens, adherence aids, education, behavioural or psychological interventions (e.g. cognitive behavioural therapy), communication or follow-up by a health professional (e.g. telephone, text message or face-to-face), multi-component interventions, and interventions to improve inhaler technique. We used standard Cochrane methodological procedures. Working in pairs, four review authors independently selected trials for inclusion, extracted data and assessed risk of bias. We assessed confidence in the evidence for each primary outcome using GRADE. Primary outcomes were adherence, quality of life and hospital service utilisation. Adherence measures included the Adherence among Patients with Chronic Disease questionnaire (APCD). Quality of life measures included the St George's Respiratory Questionnaire (SGRQ), COPD Assessment Test (CAT) and Clinical COPD Questionnaire (CCQ). We included 14 trials (2191 participants) in the analysis with follow-up ranging from six to 52 weeks. Age ranged from 54 to 75 years, and COPD severity ranged from mild to very severe. Trials were conducted in the USA, Spain, Germany, Japan, Jordan, Northern Ireland, Iran, South Korea, China and Belgium. Risk of bias was high due to lack of blinding. Evidence certainty was downgraded due to imprecision and small participant numbers. Single component interventions Six studies (55 to 212 participants) reported single component interventions including changes to pharmacological treatment (different roflumilast doses or different inhaler types), adherence aids (Bluetooth inhaler reminder device), educational (comprehensive verbal instruction), behavioural or psychological (motivational interview). Change in dose of roflumilast may result in little to no difference in adherence (odds ratio (OR) 0.67, 95% confidence interval (CI) 0.22 to 1.99; studies = 1, participants = 55; low certainty). A Bluetooth inhaler reminder device did not improve adherence, but comprehensive verbal instruction from a health professional did improve mean adherence (prescription refills) (mean difference (MD) 1.00, 95% CI 0.46 to 1.54). Motivational interview improved mean adherence scores on the APCD scale (MD 22.22, 95% CI 8.42 to 36.02). Use of a single inhaler compared to two separate inhalers may have little to no impact on quality of life (SGRQ; MD 0.80, 95% CI -3.12 to 4.72; very low certainty). A Bluetooth inhaler monitoring device may provide a small improvement in quality of life on the CCQ (MD 0.40, 95% CI 0.07 to 0.73; very low certainty). Single inhaler use may have little to no impact on the number of people admitted to hospital compared to two separate inhalers (OR 1.47, 95% CI 0.75 to 2.90; very low certainty). Single component interventions may have little to no impact on the number of people expereincing adverse events (very low certainty evidence from studies of a change in pharmacotherapy or use of adherence aids). A change in pharmacotherapy may have little to no impact on exacerbations or deaths (very low certainty). Multi-component interventions Eight studies (30 to 734 participants) reported multi-component interventions including tailored care package that included adherence support as a key component or included inhaler technique as a component. A multi-component intervention may result in more people adhering to pharmacotherapy compared to control at 40.5 weeks (risk ratio (RR) 1.37, 95% CI 1.18 to 1.59; studies = 4, participants = 446; I2 = 0%; low certainty). There may be little to no impact on quality of life (SGRQ, Chronic Respiratory Disease Questionnaire, CAT) (studies = 3; low to very low certainty). Multi-component interventions may help to reduce the number of people admitted to hospital for any cause (OR 0.37, 95% CI 0.22 to 0.63; studies = 2, participants = 877; low certainty), or COPD-related hospitalisations (OR 0.15, 95% CI 0.07 to 0.34; studies = 2, participants = 220; moderate certainty). There may be a small benefit on people experiencing severe exacerbations. There may be little to no effect on adverse events, serious adverse events or deaths, but events were infrequently reported and were rare (low to very certainty). Single component interventions (e.g. education or motivational interviewing provided by a health professional) can help to improve adherence to pharmacotherapy (low to very low certainty). There were slight improvements in quality of life with a Bluetooth inhaler device, but evidence is from one study and very low certainty. Change to pharmacotherapy (e.g. single inhaler instead of two, or different doses of roflumilast) has little impact on hospitalisations or exacerbations (very low certainty). There is no difference in people experiencing adverse events (all-cause or COPD-related), or deaths (very low certainty). Multi-component interventions may improve adherence with education, motivational or behavioural components delivered by health professionals (low certainty). There is little to no impact on quality of life (low to very low certainty). They may help reduce the number of people admitted to hospital overall (specifically pharmacist-led approaches) (low certainty), and fewer people may have COPD-related hospital admissions (moderately certainty). There may be a small reduction in people experiencing severe exacerbations, but evidence is from one study (low certainty). Limited evidence found no difference in people experiencing adverse events, serious adverse events or deaths (low to very low certainty). The evidence presented should be interpreted with caution. Larger studies with more intervention types, especially single interventions, are needed. It is unclear which specific COPD subgroups would benefit, therefore discussions between health professionals and patients may help to determine whether they will help to improve health outcomes.

Janjua S ，Pike KC ，Carr R ，Coles A ，Fortescue R ，Batavia M ... -  《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》