Risedronate for the primary and secondary prevention of osteoporotic fractures in postmenopausal women.

Osteoporosis is an abnormal reduction in bone mass and bone deterioration leading to increased fracture risk. Risedronate belongs to the bisphosphonate class of drugs which act to inhibit bone resorption by interfering with the activity of osteoclasts. This is an update of a Cochrane Review that was originally published in 2003. We assessed the benefits and harms of risedronate in the primary and secondary prevention of osteoporotic fractures for postmenopausal women at lower and higher risk for fractures, respectively. With broader and updated strategies, we searched the Cochrane Central Register of Control Trials (CENTRAL), MEDLINE and Embase. A grey literature search, including the online databases ClinicalTrials.gov, International Clinical Trials Registry Platform (ICTRP), and drug approval agencies, as well as bibliography checks of relevant systematic reviews was also performed. Eligible trials published between 1966 to 24 March 2021 were identified. We included randomised controlled trials that assessed the benefits and harms of risedronate in the prevention of fractures for postmenopausal women. Participants must have received at least one year of risedronate, placebo or other anti-osteoporotic drugs, with or without concurrent calcium/vitamin D. Major outcomes were clinical vertebral, non-vertebral, hip and wrist fractures, withdrawals due to adverse events, and serious adverse events. In the interest of clinical relevance and applicability, we classified a study as secondary prevention if its population fulfilled more than one of the following hierarchical criteria: a diagnosis of osteoporosis, a history of vertebral fractures, low bone mineral density (BMD)T score ≤ -2.5, and age ≥ 75 years old. If none of these criteria was met, the study was considered to be primary prevention. We used standard methodology expected by Cochrane. We pooled the relative risk (RR) of fractures using a fixed-effect model based on the expectation that the clinical and methodological characteristics of the respective primary and secondary prevention studies would be homogeneous, and the experience from the previous review suggesting that there would be a small number of studies. The base case included the data available for the longest treatment period in each placebo-controlled trial and a >15% relative change was considered clinically important. The main findings of the review were presented in summary of findings tables, using the GRADE approach. In addition, we looked at benefit and harm comparisons between different dosage regimens for risedronate and between risedronate and other anti-osteoporotic drugs. Forty-three trials fulfilled the eligibility criteria, among which 33 studies (27,348 participants) reported data that could be extracted and quantitatively synthesized. We had concerns about particular domains of risk of bias in each trial. Selection bias was the most frequent concern, with only 24% of the studies describing appropriate methods for both sequence generation and allocation concealment. Fifty per cent and 39% of the studies reporting benefit and harm outcomes, respectively, were subject to high risk. None of the studies included in the quantitative syntheses were judged to be at low risk of bias in all seven domains. The results described below pertain to the comparisons for daily risedronate 5 mg versus placebo which reported major outcomes. Other comparisons are described in the full text. For primary prevention, low- to very low-certainty evidence was collected from four studies (one to two years in length) including 989 postmenopausal women at lower risk of fractures. Risedronate 5 mg/day may make little or no difference to wrist fractures [RR 0.48 ( 95% CI 0.03 to 7.50; two studies, 243 participants); absolute risk reduction (ARR) 0.6% fewer (95% CI 1% fewer to 7% more)] and withdrawals due to adverse events [RR 0.67 (95% CI 0.38 to 1.18; three studies, 748 participants); ARR 2% fewer (95% CI 5% fewer to 1% more)], based on low-certainty evidence. However, its preventive effects on non-vertebral fractures and serious adverse events are not known due to the very low-certainty evidence. There were zero clinical vertebral and hip fractures reported therefore the effects of risedronate for these outcomes are not estimable.  For secondary prevention, nine studies (one to three years in length) including 14,354 postmenopausal women at higher risk of fractures provided evidence. Risedronate 5 mg/day probably prevents non-vertebral fractures [RR 0.80 (95% CI 0.72 to 0.90; six studies, 12,173 participants); RRR 20% (95% CI 10% to 28%) and ARR 2% fewer (95% CI 1% fewer to 3% fewer), moderate certainty], and may reduce hip fractures [RR 0.73 (95% CI 0.56 to 0.94); RRR 27% (95% CI 6% to 44%) and ARR 1% fewer (95% CI 0.2% fewer to 1% fewer), low certainty]. Both of these effects are probably clinically important. However, risedronate's effects are not known for wrist fractures [RR 0.64 (95% CI 0.33 to 1.24); three studies,1746 participants); ARR 1% fewer (95% CI 2% fewer to 1% more), very-low certainty] and not estimable for clinical vertebral fractures due to zero events reported (low certainty). Risedronate results in little to no difference in withdrawals due to adverse events [RR 0.98 (95% CI 0.90 to 1.07; eight studies, 9529 participants); ARR 0.3% fewer (95% CI 2% fewer to 1% more); 16.9% in risedronate versus 17.2% in control, high certainty] and probably results in little to no difference in serious adverse events [RR 1.00 (95% CI 0.94 to 1.07; six studies, 9435 participants); ARR 0% fewer (95% CI 2% fewer to 2% more; 29.2% in both groups, moderate certainty). This update recaps the key findings from our previous review that, for secondary prevention, risedronate 5 mg/day probably prevents non-vertebral fracture, and may reduce the risk of hip fractures. We are uncertain on whether risedronate 5mg/day reduces clinical vertebral and wrist fractures.  Compared to placebo, risedronate probably does not increase the risk of serious adverse events.  For primary prevention, the benefit and harms of risedronate were supported by limited evidence with high uncertainty.

Wells GA ，Hsieh SC ，Zheng C ，Peterson J ，Tugwell P ，Liu W ... -  《Cochrane Database of Systematic Reviews》

Etidronate for the primary and secondary prevention of osteoporotic fractures in postmenopausal women.

Osteoporosis is an abnormal reduction in bone mass and bone deterioration, leading to increased fracture risk. Etidronate belongs to the bisphosphonate class of drugs which act to inhibit bone resorption by interfering with the activity of osteoclasts - bone cells that break down bone tissue. This is an update of a Cochrane review first published in 2008. For clinical relevance, we investigated etidronate's effects on postmenopausal women stratified by fracture risk (low versus high). To assess the benefits and harms of intermittent/cyclic etidronate in the primary and secondary prevention of osteoporotic fractures in postmenopausal women at lower and higher risk of fracture, respectively. We searched the Cochrane Central Register of Control Trials (CENTRAL), MEDLINE, Embase, two clinical trial registers, the websites of drug approval agencies, and the bibliographies of relevant systematic reviews. We identified eligible trials published between 1966 and February 2023. We included randomized controlled trials that assessed the benefits and harms of etidronate in the prevention of fractures for postmenopausal women. Women in the experimental arms must have received at least one year of etidronate, with or without other anti-osteoporotic drugs and concurrent calcium/vitamin D. Eligible comparators were placebo (i.e. no treatment; or calcium, vitamin D, or both) or another anti-osteoporotic drug. Major outcomes were clinical vertebral, non-vertebral, hip, and wrist fractures, withdrawals due to adverse events, and serious adverse events. We classified a study as secondary prevention if its population fulfilled one or more of the following hierarchical criteria: a diagnosis of osteoporosis, a history of vertebral fractures, a low bone mineral density T-score (≤ -2.5), or aged 75 years or older. If none of these criteria were met, we considered the study to be primary prevention. We used standard methodological procedures expected by Cochrane. The review has three main comparisons: (1) etidronate 400 mg/day versus placebo; (2) etidronate 200 mg/day versus placebo; (3) etidronate at any dosage versus another anti-osteoporotic agent. We stratified the analyses for each comparison into primary and secondary prevention studies. For major outcomes in the placebo-controlled studies of etidronate 400 mg/day, we followed our original review by defining a greater than 15% relative change as clinically important. For all outcomes of interest, we extracted outcome measurements at the longest time point in the study. Thirty studies met the review's eligibility criteria. Of these, 26 studies, with a total of 2770 women, reported data that we could extract and quantitatively synthesize. There were nine primary and 17 secondary prevention studies. We had concerns about at least one risk of bias domain in each study. None of the studies described appropriate methods for allocation concealment, although 27% described adequate methods of random sequence generation. We judged that only 8% of the studies avoided performance bias, and provided adequate descriptions of appropriate blinding methods. One-quarter of studies that reported efficacy outcomes were at high risk of attrition bias, whilst 23% of studies reporting safety outcomes were at high risk in this domain. The 30 included studies compared (1) etidronate 400 mg/day to placebo (13 studies: nine primary and four secondary prevention); (2) etidronate 200 mg/day to placebo (three studies, all secondary prevention); or (3) etidronate (both dosing regimens) to another anti-osteoporotic agent (14 studies: one primary and 13 secondary prevention). We discuss only the etidronate 400 mg/day versus placebo comparison here. For primary prevention, we collected moderate- to very low-certainty evidence from nine studies (one to four years in length) including 740 postmenopausal women at lower risk of fractures. Compared to placebo, etidronate 400 mg/day probably results in little to no difference in non-vertebral fractures (risk ratio (RR) 0.56, 95% confidence interval (CI) 0.20 to 1.61); absolute risk reduction (ARR) 4.8% fewer, 95% CI 8.9% fewer to 6.1% more) and serious adverse events (RR 0.90, 95% CI 0.52 to 1.54; ARR 1.1% fewer, 95% CI 4.9% fewer to 5.3% more), based on moderate-certainty evidence. Etidronate 400 mg/day may result in little to no difference in clinical vertebral fractures (RR 3.03, 95% CI 0.32 to 28.44; ARR 0.02% more, 95% CI 0% fewer to 0% more) and withdrawals due to adverse events (RR 1.41, 95% CI 0.81 to 2.47; ARR 2.3% more, 95% CI 1.1% fewer to 8.4% more), based on low-certainty evidence. We do not know the effect of etidronate on hip fractures because the evidence is very uncertain (RR not estimable based on very low-certainty evidence). Wrist fractures were not reported in the included studies. For secondary prevention, four studies (two to four years in length) including 667 postmenopausal women at higher risk of fractures provided the evidence. Compared to placebo, etidronate 400 mg/day may make little or no difference to non-vertebral fractures (RR 1.07, 95% CI 0.72 to 1.58; ARR 0.9% more, 95% CI 3.8% fewer to 8.1% more), based on low-certainty evidence. The evidence is very uncertain about etidronate's effects on hip fractures (RR 0.93, 95% CI 0.17 to 5.19; ARR 0.0% fewer, 95% CI 1.2% fewer to 6.3% more), wrist fractures (RR 0.90, 95% CI 0.13 to 6.04; ARR 0.0% fewer, 95% CI 2.5% fewer to 15.9% more), withdrawals due to adverse events (RR 1.09, 95% CI 0.54 to 2.18; ARR 0.4% more, 95% CI 1.9% fewer to 4.9% more), and serious adverse events (RR not estimable), compared to placebo. Clinical vertebral fractures were not reported in the included studies. This update echoes the key findings of our previous review that etidronate probably makes or may make little to no difference to vertebral and non-vertebral fractures for both primary and secondary prevention.

Wells GA ，Hsieh SC ，Peterson J ，Zheng C ，Kelly SE ，Shea B ，Tugwell P ... -  《Cochrane Database of Systematic Reviews》

Screening for the primary prevention of fragility fractures among adults aged 40 years and older in primary care: systematic reviews of the effects and acceptability of screening and treatment, and the accuracy of risk prediction tools.

To inform recommendations by the Canadian Task Force on Preventive Health Care, we reviewed evidence on the benefits, harms, and acceptability of screening and treatment, and on the accuracy of risk prediction tools for the primary prevention of fragility fractures among adults aged 40 years and older in primary care. For screening effectiveness, accuracy of risk prediction tools, and treatment benefits, our search methods involved integrating studies published up to 2016 from an existing systematic review. Then, to locate more recent studies and any evidence relating to acceptability and treatment harms, we searched online databases (2016 to April 4, 2022 [screening] or to June 1, 2021 [predictive accuracy]; 1995 to June 1, 2021, for acceptability; 2016 to March 2, 2020, for treatment benefits; 2015 to June 24, 2020, for treatment harms), trial registries and gray literature, and hand-searched reviews, guidelines, and the included studies. Two reviewers selected studies, extracted results, and appraised risk of bias, with disagreements resolved by consensus or a third reviewer. The overview of reviews on treatment harms relied on one reviewer, with verification of data by another reviewer to correct errors and omissions. When appropriate, study results were pooled using random effects meta-analysis; otherwise, findings were described narratively. Evidence certainty was rated according to the GRADE approach. We included 4 randomized controlled trials (RCTs) and 1 controlled clinical trial (CCT) for the benefits and harms of screening, 1 RCT for comparative benefits and harms of different screening strategies, 32 validation cohort studies for the calibration of risk prediction tools (26 of these reporting on the Fracture Risk Assessment Tool without [i.e., clinical FRAX], or with the inclusion of bone mineral density (BMD) results [i.e., FRAX + BMD]), 27 RCTs for the benefits of treatment, 10 systematic reviews for the harms of treatment, and 12 studies for the acceptability of screening or initiating treatment. In females aged 65 years and older who are willing to independently complete a mailed fracture risk questionnaire (referred to as "selected population"), 2-step screening using a risk assessment tool with or without measurement of BMD probably (moderate certainty) reduces the risk of hip fractures (3 RCTs and 1 CCT, n = 43,736, absolute risk reduction [ARD] = 6.2 fewer in 1000, 95% CI 9.0-2.8 fewer, number needed to screen [NNS] = 161) and clinical fragility fractures (3 RCTs, n = 42,009, ARD = 5.9 fewer in 1000, 95% CI 10.9-0.8 fewer, NNS = 169). It probably does not reduce all-cause mortality (2 RCTs and 1 CCT, n = 26,511, ARD = no difference in 1000, 95% CI 7.1 fewer to 5.3 more) and may (low certainty) not affect health-related quality of life. Benefits for fracture outcomes were not replicated in an offer-to-screen population where the rate of response to mailed screening questionnaires was low. For females aged 68-80 years, population screening may not reduce the risk of hip fractures (1 RCT, n = 34,229, ARD = 0.3 fewer in 1000, 95% CI 4.2 fewer to 3.9 more) or clinical fragility fractures (1 RCT, n = 34,229, ARD = 1.0 fewer in 1000, 95% CI 8.0 fewer to 6.0 more) over 5 years of follow-up. The evidence for serious adverse events among all patients and for all outcomes among males and younger females (<65 years) is very uncertain. We defined overdiagnosis as the identification of high risk in individuals who, if not screened, would never have known that they were at risk and would never have experienced a fragility fracture. This was not directly reported in any of the trials. Estimates using data available in the trials suggest that among "selected" females offered screening, 12% of those meeting age-specific treatment thresholds based on clinical FRAX 10-year hip fracture risk, and 19% of those meeting thresholds based on clinical FRAX 10-year major osteoporotic fracture risk, may be overdiagnosed as being at high risk of fracture. Of those identified as being at high clinical FRAX 10-year hip fracture risk and who were referred for BMD assessment, 24% may be overdiagnosed. One RCT (n = 9268) provided evidence comparing 1-step to 2-step screening among postmenopausal females, but the evidence from this trial was very uncertain. For the calibration of risk prediction tools, evidence from three Canadian studies (n = 67,611) without serious risk of bias concerns indicates that clinical FRAX-Canada may be well calibrated for the 10-year prediction of hip fractures (observed-to-expected fracture ratio [O:E] = 1.13, 95% CI 0.74-1.72, I2 = 89.2%), and is probably well calibrated for the 10-year prediction of clinical fragility fractures (O:E = 1.10, 95% CI 1.01-1.20, I2 = 50.4%), both leading to some underestimation of the observed risk. Data from these same studies (n = 61,156) showed that FRAX-Canada with BMD may perform poorly to estimate 10-year hip fracture risk (O:E = 1.31, 95% CI 0.91-2.13, I2 = 92.7%), but is probably well calibrated for the 10-year prediction of clinical fragility fractures, with some underestimation of the observed risk (O:E 1.16, 95% CI 1.12-1.20, I2 = 0%). The Canadian Association of Radiologists and Osteoporosis Canada Risk Assessment (CAROC) tool may be well calibrated to predict a category of risk for 10-year clinical fractures (low, moderate, or high risk; 1 study, n = 34,060). The evidence for most other tools was limited, or in the case of FRAX tools calibrated for countries other than Canada, very uncertain due to serious risk of bias concerns and large inconsistency in findings across studies. Postmenopausal females in a primary prevention population defined as <50% prevalence of prior fragility fracture (median 16.9%, range 0 to 48% when reported in the trials) and at risk of fragility fracture, treatment with bisphosphonates as a class (median 2 years, range 1-6 years) probably reduces the risk of clinical fragility fractures (19 RCTs, n = 22,482, ARD = 11.1 fewer in 1000, 95% CI 15.0-6.6 fewer, [number needed to treat for an additional beneficial outcome] NNT = 90), and may reduce the risk of hip fractures (14 RCTs, n = 21,038, ARD = 2.9 fewer in 1000, 95% CI 4.6-0.9 fewer, NNT = 345) and clinical vertebral fractures (11 RCTs, n = 8921, ARD = 10.0 fewer in 1000, 95% CI 14.0-3.9 fewer, NNT = 100); it may not reduce all-cause mortality. There is low certainty evidence of little-to-no reduction in hip fractures with any individual bisphosphonate, but all provided evidence of decreased risk of clinical fragility fractures (moderate certainty for alendronate [NNT=68] and zoledronic acid [NNT=50], low certainty for risedronate [NNT=128]) among postmenopausal females. Evidence for an impact on risk of clinical vertebral fractures is very uncertain for alendronate and risedronate; zoledronic acid may reduce the risk of this outcome (4 RCTs, n = 2367, ARD = 18.7 fewer in 1000, 95% CI 25.6-6.6 fewer, NNT = 54) for postmenopausal females. Denosumab probably reduces the risk of clinical fragility fractures (6 RCTs, n = 9473, ARD = 9.1 fewer in 1000, 95% CI 12.1-5.6 fewer, NNT = 110) and clinical vertebral fractures (4 RCTs, n = 8639, ARD = 16.0 fewer in 1000, 95% CI 18.6-12.1 fewer, NNT=62), but may make little-to-no difference in the risk of hip fractures among postmenopausal females. Denosumab probably makes little-to-no difference in the risk of all-cause mortality or health-related quality of life among postmenopausal females. Evidence in males is limited to two trials (1 zoledronic acid, 1 denosumab); in this population, zoledronic acid may make little-to-no difference in the risk of hip or clinical fragility fractures, and evidence for all-cause mortality is very uncertain. The evidence for treatment with denosumab in males is very uncertain for all fracture outcomes (hip, clinical fragility, clinical vertebral) and all-cause mortality. There is moderate certainty evidence that treatment causes a small number of patients to experience a non-serious adverse event, notably non-serious gastrointestinal events (e.g., abdominal pain, reflux) with alendronate (50 RCTs, n = 22,549, ARD = 16.3 more in 1000, 95% CI 2.4-31.3 more, [number needed to treat for an additional harmful outcome] NNH = 61) but not with risedronate; influenza-like symptoms with zoledronic acid (5 RCTs, n = 10,695, ARD = 142.5 more in 1000, 95% CI 105.5-188.5 more, NNH = 7); and non-serious gastrointestinal adverse events (3 RCTs, n = 8454, ARD = 64.5 more in 1000, 95% CI 26.4-13.3 more, NNH = 16), dermatologic adverse events (3 RCTs, n = 8454, ARD = 15.6 more in 1000, 95% CI 7.6-27.0 more, NNH = 64), and infections (any severity; 4 RCTs, n = 8691, ARD = 1.8 more in 1000, 95% CI 0.1-4.0 more, NNH = 556) with denosumab. For serious adverse events overall and specific to stroke and myocardial infarction, treatment with bisphosphonates probably makes little-to-no difference; evidence for other specific serious harms was less certain or not available. There was low certainty evidence for an increased risk for the rare occurrence of atypical femoral fractures (0.06 to 0.08 more in 1000) and osteonecrosis of the jaw (0.22 more in 1000) with bisphosphonates (most evidence for alendronate). The evidence for these rare outcomes and for rebound fractures with denosumab was very uncertain. Younger (lower risk) females have high willingness to be screened. A minority of postmenopausal females at increased risk for fracture may accept treatment. Further, there is large heterogeneity in the level of risk at which patients may be accepting of initiating treatment, and treatment effects appear to be overestimated. An offer of 2-step screening with risk assessment and BMD measurement to selected postmenopausal females with low prevalence of prior fracture probably results in a small reduction in the risk of clinical fragility fracture and hip fracture compared to no screening. These findings were most applicable to the use of clinical FRAX for risk assessment and were not replicated in the offer-to-screen population where the rate of response to mailed screening questionnaires was low. Limited direct evidence on harms of screening were available; using study data to provide estimates, there may be a moderate degree of overdiagnosis of high risk for fracture to consider. The evidence for younger females and males is very limited. The benefits of screening and treatment need to be weighed against the potential for harm; patient views on the acceptability of treatment are highly variable. International Prospective Register of Systematic Reviews (PROSPERO): CRD42019123767.

Gates M ，Pillay J ，Nuspl M ，Wingert A ，Vandermeer B ，Hartling L ... -  《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》

Risedronate for the primary and secondary prevention of osteoporotic fractures in postmenopausal women.

Wells G ，Cranney A ，Peterson J ，Boucher M ，Shea B ，Robinson V ，Coyle D ，Tugwell P ... -  《-》