Drugs for preventing postoperative nausea and vomiting in adults after general anaesthesia: a network meta-analysis.

Postoperative nausea and vomiting (PONV) is a common adverse effect of anaesthesia and surgery. Up to 80% of patients may be affected. These outcomes are a major cause of patient dissatisfaction and may lead to prolonged hospital stay and higher costs of care along with more severe complications. Many antiemetic drugs are available for prophylaxis. They have various mechanisms of action and side effects, but there is still uncertainty about which drugs are most effective with the fewest side effects. • To compare the efficacy and safety of different prophylactic pharmacologic interventions (antiemetic drugs) against no treatment, against placebo, or against each other (as monotherapy or combination prophylaxis) for prevention of postoperative nausea and vomiting in adults undergoing any type of surgery under general anaesthesia • To generate a clinically useful ranking of antiemetic drugs (monotherapy and combination prophylaxis) based on efficacy and safety • To identify the best dose or dose range of antiemetic drugs in terms of efficacy and safety SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), the World Health Organization International Clinical Trials Registry Platform (WHO ICTRP), ClinicalTrials.gov, and reference lists of relevant systematic reviews. The first search was performed in November 2017 and was updated in April 2020. In the update of the search, 39 eligible studies were found that were not included in the analysis (listed as awaiting classification). Randomized controlled trials (RCTs) comparing effectiveness or side effects of single antiemetic drugs in any dose or combination against each other or against an inactive control in adults undergoing any type of surgery under general anaesthesia. All antiemetic drugs belonged to one of the following substance classes: 5-HT₃ receptor antagonists, D₂ receptor antagonists, NK₁ receptor antagonists, corticosteroids, antihistamines, and anticholinergics. No language restrictions were applied. Abstract publications were excluded. A review team of 11 authors independently assessed trials for inclusion and risk of bias and subsequently extracted data. We performed pair-wise meta-analyses for drugs of direct interest (amisulpride, aprepitant, casopitant, dexamethasone, dimenhydrinate, dolasetron, droperidol, fosaprepitant, granisetron, haloperidol, meclizine, methylprednisolone, metoclopramide, ondansetron, palonosetron, perphenazine, promethazine, ramosetron, rolapitant, scopolamine, and tropisetron) compared to placebo (inactive control). We performed network meta-analyses (NMAs) to estimate the relative effects and ranking (with placebo as reference) of all available single drugs and combinations. Primary outcomes were vomiting within 24 hours postoperatively, serious adverse events (SAEs), and any adverse event (AE). Secondary outcomes were drug class-specific side effects (e.g. headache), mortality, early and late vomiting, nausea, and complete response. We performed subgroup network meta-analysis with dose of drugs as a moderator variable using dose ranges based on previous consensus recommendations. We assessed certainty of evidence of NMA treatment effects for all primary outcomes and drug class-specific side effects according to GRADE (CINeMA, Confidence in Network Meta-Analysis). We restricted GRADE assessment to single drugs of direct interest compared to placebo. We included 585 studies (97,516 randomized participants). Most of these studies were small (median sample size of 100); they were published between 1965 and 2017 and were primarily conducted in Asia (51%), Europe (25%), and North America (16%). Mean age of the overall population was 42 years. Most participants were women (83%), had American Society of Anesthesiologists (ASA) physical status I and II (70%), received perioperative opioids (88%), and underwent gynaecologic (32%) or gastrointestinal surgery (19%) under general anaesthesia using volatile anaesthetics (88%). In this review, 44 single drugs and 51 drug combinations were compared. Most studies investigated only single drugs (72%) and included an inactive control arm (66%). The three most investigated single drugs in this review were ondansetron (246 studies), dexamethasone (120 studies), and droperidol (97 studies). Almost all studies (89%) reported at least one efficacy outcome relevant for this review. However, only 56% reported at least one relevant safety outcome. Altogether, 157 studies (27%) were assessed as having overall low risk of bias, 101 studies (17%) overall high risk of bias, and 327 studies (56%) overall unclear risk of bias. Vomiting within 24 hours postoperatively Relative effects from NMA for vomiting within 24 hours (282 RCTs, 50,812 participants, 28 single drugs, and 36 drug combinations) suggest that 29 out of 36 drug combinations and 10 out of 28 single drugs showed a clinically important benefit (defined as the upper end of the 95% confidence interval (CI) below a risk ratio (RR) of 0.8) compared to placebo. Combinations of drugs were generally more effective than single drugs in preventing vomiting. However, single NK₁ receptor antagonists showed treatment effects similar to most of the drug combinations. High-certainty evidence suggests that the following single drugs reduce vomiting (ordered by decreasing efficacy): aprepitant (RR 0.26, 95% CI 0.18 to 0.38, high certainty, rank 3/28 of single drugs); ramosetron (RR 0.44, 95% CI 0.32 to 0.59, high certainty, rank 5/28); granisetron (RR 0.45, 95% CI 0.38 to 0.54, high certainty, rank 6/28); dexamethasone (RR 0.51, 95% CI 0.44 to 0.57, high certainty, rank 8/28); and ondansetron (RR 0.55, 95% CI 0.51 to 0.60, high certainty, rank 13/28). Moderate-certainty evidence suggests that the following single drugs probably reduce vomiting: fosaprepitant (RR 0.06, 95% CI 0.02 to 0.21, moderate certainty, rank 1/28) and droperidol (RR 0.61, 95% CI 0.54 to 0.69, moderate certainty, rank 20/28). Recommended and high doses of granisetron, dexamethasone, ondansetron, and droperidol showed clinically important benefit, but low doses showed no clinically important benefit. Aprepitant was used mainly at high doses, ramosetron at recommended doses, and fosaprepitant at doses of 150 mg (with no dose recommendation available). Frequency of SAEs Twenty-eight RCTs were included in the NMA for SAEs (10,766 participants, 13 single drugs, and eight drug combinations). The certainty of evidence for SAEs when using one of the best and most reliable anti-vomiting drugs (aprepitant, ramosetron, granisetron, dexamethasone, ondansetron, and droperidol compared to placebo) ranged from very low to low. Droperidol (RR 0.88, 95% CI 0.08 to 9.71, low certainty, rank 6/13) may reduce SAEs. We are uncertain about the effects of aprepitant (RR 1.39, 95% CI 0.26 to 7.36, very low certainty, rank 11/13), ramosetron (RR 0.89, 95% CI 0.05 to 15.74, very low certainty, rank 7/13), granisetron (RR 1.21, 95% CI 0.11 to 13.15, very low certainty, rank 10/13), dexamethasone (RR 1.16, 95% CI 0.28 to 4.85, very low certainty, rank 9/13), and ondansetron (RR 1.62, 95% CI 0.32 to 8.10, very low certainty, rank 12/13). No studies reporting SAEs were available for fosaprepitant. Frequency of any AE Sixty-one RCTs were included in the NMA for any AE (19,423 participants, 15 single drugs, and 11 drug combinations). The certainty of evidence for any AE when using one of the best and most reliable anti-vomiting drugs (aprepitant, ramosetron, granisetron, dexamethasone, ondansetron, and droperidol compared to placebo) ranged from very low to moderate. Granisetron (RR 0.92, 95% CI 0.80 to 1.05, moderate certainty, rank 7/15) probably has no or little effect on any AE. Dexamethasone (RR 0.77, 95% CI 0.55 to 1.08, low certainty, rank 2/15) and droperidol (RR 0.89, 95% CI 0.81 to 0.98, low certainty, rank 6/15) may reduce any AE. Ondansetron (RR 0.95, 95% CI 0.88 to 1.01, low certainty, rank 9/15) may have little or no effect on any AE. We are uncertain about the effects of aprepitant (RR 0.87, 95% CI 0.78 to 0.97, very low certainty, rank 3/15) and ramosetron (RR 1.00, 95% CI 0.65 to 1.54, very low certainty, rank 11/15) on any AE. No studies reporting any AE were available for fosaprepitant. Class-specific side effects For class-specific side effects (headache, constipation, wound infection, extrapyramidal symptoms, sedation, arrhythmia, and QT prolongation) of relevant substances, the certainty of evidence for the best and most reliable anti-vomiting drugs mostly ranged from very low to low. Exceptions were that ondansetron probably increases headache (RR 1.16, 95% CI 1.06 to 1.28, moderate certainty, rank 18/23) and probably reduces sedation (RR 0.87, 95% CI 0.79 to 0.96, moderate certainty, rank 5/24) compared to placebo. The latter effect is limited to recommended and high doses of ondansetron. Droperidol probably reduces headache (RR 0.76, 95% CI 0.67 to 0.86, moderate certainty, rank 5/23) compared to placebo. We have high-certainty evidence that dexamethasone (RR 1.00, 95% CI 0.91 to 1.09, high certainty, rank 16/24) has no effect on sedation compared to placebo. No studies assessed substance class-specific side effects for fosaprepitant. Direction and magnitude of network effect estimates together with level of evidence certainty are graphically summarized for all pre-defined GRADE-relevant outcomes and all drugs of direct interest compared to placebo in http://doi.org/10.5281/zenodo.4066353. We found high-certainty evidence that five single drugs (aprepitant, ramosetron, granisetron, dexamethasone, and ondansetron) reduce vomiting, and moderate-certainty evidence that two other single drugs (fosaprepitant and droperidol) probably reduce vomiting, compared to placebo. Four of the six substance classes (5-HT₃ receptor antagonists, D₂ receptor antagonists, NK₁ receptor antagonists, and corticosteroids) were thus represented by at least one drug with important benefit for prevention of vomiting. Combinations of drugs were generally more effective than the corresponding single drugs in preventing vomiting. NK₁ receptor antagonists were the most effective drug class and had comparable efficacy to most of the drug combinations. 5-HT₃ receptor antagonists were the best studied substance class. For most of the single drugs of direct interest, we found only very low to low certainty evidence for safety outcomes such as occurrence of SAEs, any AE, and substance class-specific side effects. Recommended and high doses of granisetron, dexamethasone, ondansetron, and droperidol were more effective than low doses for prevention of vomiting. Dose dependency of side effects was rarely found due to the limited number of studies, except for the less sedating effect of recommended and high doses of ondansetron. The results of the review are transferable mainly to patients at higher risk of nausea and vomiting (i.e. healthy women undergoing inhalational anaesthesia and receiving perioperative opioids). Overall study quality was limited, but certainty assessments of effect estimates consider this limitation. No further efficacy studies are needed as there is evidence of moderate to high certainty for seven single drugs with relevant benefit for prevention of vomiting. However, additional studies are needed to investigate potential side effects of these drugs and to examine higher-risk patient populations (e.g. individuals with diabetes and heart disease).

Weibel S ，Rücker G ，Eberhart LH ，Pace NL ，Hartl HM ，Jordan OL ，Mayer D ，Riemer M ，Schaefer MS ，Raj D ，Backhaus I ，Helf A ，Schlesinger T ，Kienbaum P ，Kranke P ... -  《Cochrane Database of Systematic Reviews》

Antiemetics for adults for prevention of nausea and vomiting caused by moderately or highly emetogenic chemotherapy: a network meta-analysis.

About 70% to 80% of adults with cancer experience chemotherapy-induced nausea and vomiting (CINV). CINV remains one of the most distressing symptoms associated with cancer therapy and is associated with decreased adherence to chemotherapy. Combining 5-hydroxytryptamine-3 (5-HT₃) receptor antagonists with corticosteroids or additionally with neurokinin-1 (NK₁) receptor antagonists is effective in preventing CINV among adults receiving highly emetogenic chemotherapy (HEC) or moderately emetogenic chemotherapy (MEC). Various treatment options are available, but direct head-to-head comparisons do not allow comparison of all treatments versus another.  OBJECTIVES: • In adults with solid cancer or haematological malignancy receiving HEC - To compare the effects of antiemetic treatment combinations including NK₁ receptor antagonists, 5-HT₃ receptor antagonists, and corticosteroids on prevention of acute phase (Day 1), delayed phase (Days 2 to 5), and overall (Days 1 to 5) chemotherapy-induced nausea and vomiting in network meta-analysis (NMA) - To generate a clinically meaningful treatment ranking according to treatment safety and efficacy • In adults with solid cancer or haematological malignancy receiving MEC - To compare whether antiemetic treatment combinations including NK₁ receptor antagonists, 5-HT₃ receptor antagonists, and corticosteroids are superior for prevention of acute phase (Day 1), delayed phase (Days 2 to 5), and overall (Days 1 to 5) chemotherapy-induced nausea and vomiting to treatment combinations including 5-HT₃ receptor antagonists and corticosteroids solely, in network meta-analysis - To generate a clinically meaningful treatment ranking according to treatment safety and efficacy SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, conference proceedings, and study registries from 1988 to February 2021 for randomised controlled trials (RCTs). We included RCTs including adults with any cancer receiving HEC or MEC (according to the latest definition) and comparing combination therapies of NK₁ and 5-HT₃ inhibitors and corticosteroids for prevention of CINV. We used standard methodological procedures expected by Cochrane. We expressed treatment effects as risk ratios (RRs). Prioritised outcomes were complete control of vomiting during delayed and overall phases, complete control of nausea during the overall phase, quality of life, serious adverse events (SAEs), and on-study mortality. We assessed GRADE and developed 12 'Summary of findings' tables. We report results of most crucial outcomes in the abstract, that is, complete control of vomiting during the overall phase and SAEs. For a comprehensive illustration of results, we randomly chose aprepitant plus granisetron as exemplary reference treatment for HEC, and granisetron as exemplary reference treatment for MEC. Highly emetogenic chemotherapy (HEC) We included 73 studies reporting on 25,275 participants and comparing 14 treatment combinations with NK₁ and 5-HT₃ inhibitors. All treatment combinations included corticosteroids. Complete control of vomiting during the overall phase We estimated that 704 of 1000 participants achieve complete control of vomiting in the overall treatment phase (one to five days) when treated with aprepitant + granisetron. Evidence from NMA (39 RCTs, 21,642 participants; 12 treatment combinations with NK₁ and 5-HT₃ inhibitors) suggests that the following drug combinations are more efficacious than aprepitant + granisetron for completely controlling vomiting during the overall treatment phase (one to five days): fosnetupitant + palonosetron (810 of 1000; RR 1.15, 95% confidence interval (CI) 0.97 to 1.37; moderate certainty), aprepitant + palonosetron (753 of 1000; RR 1.07, 95% CI 1.98  to 1.18; low-certainty), aprepitant + ramosetron (753 of 1000; RR 1.07, 95% CI 0.95 to 1.21; low certainty), and fosaprepitant + palonosetron (746 of 1000; RR 1.06, 95% CI 0.96 to 1.19; low certainty).  Netupitant + palonosetron (704 of 1000; RR 1.00, 95% CI 0.93 to 1.08; high-certainty) and fosaprepitant + granisetron (697 of 1000; RR 0.99, 95% CI 0.93 to 1.06; high-certainty) have little to no impact on complete control of vomiting during the overall treatment phase (one to five days) when compared to aprepitant + granisetron, respectively.  Evidence further suggests that the following drug combinations are less efficacious than aprepitant + granisetron in completely controlling vomiting during the overall treatment phase (one to five days) (ordered by decreasing efficacy): aprepitant + ondansetron (676 of 1000; RR 0.96, 95% CI 0.88 to 1.05; low certainty), fosaprepitant + ondansetron (662 of 1000; RR 0.94, 95% CI 0.85 to 1.04; low certainty), casopitant + ondansetron (634 of 1000; RR 0.90, 95% CI 0.79 to 1.03; low certainty), rolapitant + granisetron (627 of 1000; RR 0.89, 95% CI 0.78 to 1.01; moderate certainty), and rolapitant + ondansetron (598 of 1000; RR 0.85, 95% CI 0.65 to 1.12; low certainty). We could not include two treatment combinations (ezlopitant + granisetron, aprepitant + tropisetron) in NMA for this outcome because of missing direct comparisons.  Serious adverse events We estimated that 35 of 1000 participants experience any SAEs when treated with aprepitant + granisetron. Evidence from NMA (23 RCTs, 16,065 participants; 11 treatment combinations) suggests that fewer participants may experience SAEs when treated with the following drug combinations than with aprepitant + granisetron: fosaprepitant + ondansetron (8 of 1000; RR 0.23, 95% CI 0.05 to 1.07; low certainty), casopitant + ondansetron (8 of 1000; RR 0.24, 95% CI 0.04 to 1.39; low certainty), netupitant + palonosetron (9 of 1000; RR 0.27, 95% CI 0.05 to 1.58; low certainty), fosaprepitant + granisetron (13 of 1000; RR 0.37, 95% CI 0.09 to 1.50; low certainty), and rolapitant + granisetron (20 of 1000; RR 0.57, 95% CI 0.19 to 1.70; low certainty). Evidence is very uncertain about the effects of aprepitant + ondansetron (8 of 1000; RR 0.22, 95% CI 0.04 to 1.14; very low certainty), aprepitant + ramosetron (11 of 1000; RR 0.31, 95% CI 0.05 to 1.90; very low certainty), fosaprepitant + palonosetron (12 of 1000; RR 0.35, 95% CI 0.04 to 2.95; very low certainty), fosnetupitant + palonosetron (13 of 1000; RR 0.36, 95% CI 0.06 to 2.16; very low certainty), and aprepitant + palonosetron (17 of 1000; RR 0.48, 95% CI 0.05 to 4.78; very low certainty) on the risk of SAEs when compared to aprepitant + granisetron, respectively.  We could not include three treatment combinations (ezlopitant + granisetron, aprepitant + tropisetron, rolapitant + ondansetron) in NMA for this outcome because of missing direct comparisons.  Moderately emetogenic chemotherapy (MEC) We included 38 studies reporting on 12,038 participants and comparing 15 treatment combinations with NK₁ and 5-HT₃ inhibitors, or 5-HT₃ inhibitors solely. All treatment combinations included corticosteroids. Complete control of vomiting during the overall phase We estimated that 555 of 1000 participants achieve complete control of vomiting in the overall treatment phase (one to five days) when treated with granisetron. Evidence from NMA (22 RCTs, 7800 participants; 11 treatment combinations) suggests that the following drug combinations are more efficacious than granisetron in completely controlling vomiting during the overall treatment phase (one to five days): aprepitant + palonosetron (716 of 1000; RR 1.29, 95% CI 1.00 to 1.66; low certainty), netupitant + palonosetron (694 of 1000; RR 1.25, 95% CI 0.92 to 1.70; low certainty), and rolapitant + granisetron (660 of 1000; RR 1.19, 95% CI 1.06 to 1.33; high certainty).  Palonosetron (588 of 1000; RR 1.06, 95% CI 0.85 to 1.32; low certainty) and aprepitant + granisetron (577 of 1000; RR 1.06, 95% CI 0.85 to 1.32; low certainty) may or may not increase complete response in the overall treatment phase (one to five days) when compared to granisetron, respectively. Azasetron (560 of 1000; RR 1.01, 95% CI 0.76 to 1.34; low certainty) may result in little to no difference in complete response in the overall treatment phase (one to five days) when compared to granisetron. Evidence further suggests that the following drug combinations are less efficacious than granisetron in completely controlling vomiting during the overall treatment phase (one to five days) (ordered by decreasing efficacy): fosaprepitant + ondansetron (500 of 100; RR 0.90, 95% CI 0.66 to 1.22; low certainty), aprepitant + ondansetron (477 of 1000; RR 0.86, 95% CI 0.64 to 1.17; low certainty), casopitant + ondansetron (461 of 1000; RR 0.83, 95% CI 0.62 to 1.12; low certainty), and ondansetron (433 of 1000; RR 0.78, 95% CI 0.59 to 1.04; low certainty). We could not include five treatment combinations (fosaprepitant + granisetron, azasetron, dolasetron, ramosetron, tropisetron) in NMA for this outcome because of missing direct comparisons.  Serious adverse events We estimated that 153 of 1000 participants experience any SAEs when treated with granisetron. Evidence from pair-wise comparison (1 RCT, 1344 participants) suggests that more participants may experience SAEs when treated with rolapitant + granisetron (176 of 1000; RR 1.15, 95% CI 0.88 to 1.50; low certainty). NMA was not feasible for this outcome because of missing direct comparisons.  Certainty of evidence Our main reason for downgrading was serious or very serious imprecision (e.g. due to wide 95% CIs crossing or including unity, few events leading to wide 95% CIs, or small information size). Additional reasons for downgrading some comparisons or whole networks were serious study limitations due to high risk of bias or moderate inconsistency within networks. This field of supportive cancer care is very well researched. However, new drugs or drug combinations are continuously emerging and need to be systematically researched and assessed. For people receiving HEC, synthesised evidence does not suggest one superior treatment for prevention and control of chemotherapy-induced nausea and vomiting.  For people receiving MEC, synthesised evidence does not suggest superiority for treatments including both NK₁ and 5-HT₃ inhibitors when compared to treatments including 5-HT₃ inhibitors only. Rather, the results of our NMA suggest that the choice of 5-HT₃ inhibitor may have an impact on treatment efficacy in preventing CINV.  When interpreting the results of this systematic review, it is important for the reader to understand that NMAs are no substitute for direct head-to-head comparisons, and that results of our NMA do not necessarily rule out differences that could be clinically relevant for some individuals.

Piechotta V ，Adams A ，Haque M ，Scheckel B ，Kreuzberger N ，Monsef I ，Jordan K ，Kuhr K ，Skoetz N ... -  《-》

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》

Drugs for preventing postoperative nausea and vomiting in adults after general anaesthesia: an abridged Cochrane network meta-analysis.

Postoperative nausea and vomiting is a common adverse effect of anaesthesia. Although dozens of different anti-emetics are available for clinical practice, there is currently no comparative ranking of efficacy and safety of these drugs to inform clinical practice. We performed a systematic review with network meta-analyses to compare, and rank in terms of efficacy and safety, single anti-emetic drugs and their combinations, including 5-hydroxytryptamine3 , dopamine-2 and neurokinin-1 receptor antagonists; corticosteroids; antihistamines; and anticholinergics used to prevent postoperative nausea and vomiting in adults after general anaesthesia. We systematically searched for placebo-controlled and head-to-head randomised controlled trials up to November 2017 (updated in April 2020). We assessed how trustworthy the evidence was using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) and Confidence In Network Meta-Analysis (CINeMA) approaches for vomiting within 24 h postoperatively, serious adverse events, any adverse event and drug class-specific side-effects. We included 585 trials (97,516 participants, 83% women) testing 44 single drugs and 51 drug combinations. The studies' overall risk of bias was assessed as low in only 27% of the studies. In 282 trials, 29 out of 36 drug combinations and 10 out of 28 single drugs lowered the risk of vomiting at least 20% compared with placebo. In the ranking of treatments, combinations of drugs were generally more effective than single drugs. Single neurokinin-1 receptor antagonists were as effective as other drug combinations. Out of the 10 effective single drugs, certainty of evidence was high for aprepitant, with risk ratio (95%CI) 0.26 (0.18-0.38); ramosetron, 0.44 (0.32-0.59); granisetron, 0.45 (0.38-0.54); dexamethasone, 0.51 (0.44-0.57); and ondansetron, 0.55 (0.51-0.60). It was moderate for fosaprepitant, 0.06 (0.02-0.21) and droperidol, 0.61 (0.54-0.69). Granisetron and amisulpride are likely to have little or no increase in any adverse event compared with placebo, while dimenhydrinate and scopolamine may increase the number of patients with any adverse event compared with placebo. So far, there is no convincing evidence that other single drugs effect the incidence of serious, or any, adverse events when compared with placebo. Among drug class specific side-effects, evidence for single drugs is mostly not convincing. There is convincing evidence regarding the prophylactic effect of at least seven single drugs for postoperative vomiting such that future studies investigating these drugs will probably not change the estimated beneficial effect. However, there is still considerable lack of evidence regarding safety aspects that does warrant investigation.

Weibel S ，Schaefer MS ，Raj D ，Rücker G ，Pace NL ，Schlesinger T ，Meybohm P ，Kienbaum P ，Eberhart LHJ ，Kranke P ... -  《-》

Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.

Psoriasis is an immune-mediated disease for which some people have a genetic predisposition. The condition manifests in inflammatory effects on either the skin or joints, or both, and it has a major impact on quality of life. Although there is currently no cure for psoriasis, various treatment strategies allow sustained control of disease signs and symptoms. Several randomised controlled trials (RCTs) have compared the efficacy of the different systemic treatments in psoriasis against placebo. However, the relative benefit of these treatments remains unclear due to the limited number of trials comparing them directly head-to-head, which is why we chose to conduct a network meta-analysis. To compare the efficacy and safety of non-biological systemic agents, small molecules, and biologics for people with moderate-to-severe psoriasis using a network meta-analysis, and to provide a ranking of these treatments according to their efficacy and safety. For this living systematic review we updated our searches of the following databases monthly to September 2020: the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, and Embase. We searched two trials registers to the same date. We checked the reference lists of included studies and relevant systematic reviews for further references to eligible RCTs. Randomised controlled trials (RCTs) of systemic treatments in adults (over 18 years of age) with moderate-to-severe plaque psoriasis or psoriatic arthritis whose skin had been clinically diagnosed with moderate-to-severe psoriasis, at any stage of treatment, in comparison to placebo or another active agent. The primary outcomes of this review were: the proportion of participants who achieved clear or almost clear skin, that is, at least Psoriasis Area and Severity Index (PASI) 90 at induction phase (from 8 to 24 weeks after the randomisation), and the proportion of participants with serious adverse events (SAEs) at induction phase. We did not evaluate differences in specific adverse events. Several groups of two review authors independently undertook study selection, data extraction, 'Risk of bias' assessment, and analyses. We synthesised the data using pair-wise and network meta-analysis (NMA) to compare the treatments of interest and rank them according to their effectiveness (as measured by the PASI 90 score) and acceptability (the inverse of serious adverse events). We assessed the certainty of the body of evidence from the NMA for the two primary outcomes and all comparisons, according to CINeMA, as either very low, low, moderate, or high. We contacted study authors when data were unclear or missing. We used the surface under the cumulative ranking curve (SUCRA) to infer on treatment hierarchy: 0% (treatment is the worst for effectiveness or safety) to 100% (treatment is the best for effectiveness or safety). We included 158 studies (18 new studies for the update) in our review (57,831 randomised participants, 67.2% men, mainly recruited from hospitals). The overall average age was 45 years; the overall mean PASI score at baseline was 20 (range: 9.5 to 39). Most of these studies were placebo-controlled (58%), 30% were head-to-head studies, and 11% were multi-armed studies with both an active comparator and a placebo. We have assessed a total of 20 treatments. In all, 133 trials were multicentric (two to 231 centres). All but two of the outcomes included in this review were limited to the induction phase (assessment from 8 to 24 weeks after randomisation). We assessed many studies (53/158) as being at high risk of bias; 25 were at an unclear risk, and 80 at low risk. Most studies (123/158) declared funding by a pharmaceutical company, and 22 studies did not report their source of funding. Network meta-analysis at class level showed that all of the interventions (non-biological systemic agents, small molecules, and biological treatments) were significantly more effective than placebo in reaching PASI 90. At class level, in reaching PASI 90, the biologic treatments anti-IL17, anti-IL12/23, anti-IL23, and anti-TNF alpha were significantly more effective than the small molecules and the non-biological systemic agents. At drug level, infliximab, ixekizumab, secukinumab, brodalumab, risankizumab and guselkumab were significantly more effective in reaching PASI 90 than ustekinumab and three anti-TNF alpha agents: adalimumab, certolizumab, and etanercept. Ustekinumab and adalimumab were significantly more effective in reaching PASI 90 than etanercept; ustekinumab was more effective than certolizumab, and the clinical effectiveness of ustekinumab and adalimumab was similar. There was no significant difference between tofacitinib or apremilast and three non-biological drugs: fumaric acid esters (FAEs), ciclosporin and methotrexate. Network meta-analysis also showed that infliximab, ixekizumab, risankizumab, bimekizumab, secukinumab, guselkumab, and brodalumab outperformed other drugs when compared to placebo in reaching PASI 90. The clinical effectiveness of these drugs was similar, except for ixekizumab which had a better chance of reaching PASI 90 compared with secukinumab, guselkumab and brodalumab. The clinical effectiveness of these seven drugs was: infliximab (versus placebo): risk ratio (RR) 50.29, 95% confidence interval (CI) 20.96 to 120.67, SUCRA = 93.6; high-certainty evidence; ixekizumab (versus placebo): RR 32.48, 95% CI 27.13 to 38.87; SUCRA = 90.5; high-certainty evidence; risankizumab (versus placebo): RR 28.76, 95% CI 23.96 to 34.54; SUCRA = 84.6; high-certainty evidence; bimekizumab (versus placebo): RR 58.64, 95% CI 3.72 to 923.86; SUCRA = 81.4; high-certainty evidence; secukinumab (versus placebo): RR 25.79, 95% CI 21.61 to 30.78; SUCRA = 76.2; high-certainty evidence; guselkumab (versus placebo): RR 25.52, 95% CI 21.25 to 30.64; SUCRA = 75; high-certainty evidence; and brodalumab (versus placebo): RR 23.55, 95% CI 19.48 to 28.48; SUCRA = 68.4; moderate-certainty evidence. Conservative interpretation is warranted for the results for bimekizumab (as well as mirikizumab, tyrosine kinase 2 inhibitor, acitretin, ciclosporin, fumaric acid esters, and methotrexate), as these drugs, in the NMA, have been evaluated in few trials. We found no significant difference between any of the interventions and the placebo for the risk of SAEs. Nevertheless, the SAE analyses were based on a very low number of events with low to moderate certainty for all the comparisons. Thus, the results have to be viewed with caution and we cannot be sure of the ranking. For other efficacy outcomes (PASI 75 and Physician Global Assessment (PGA) 0/1) the results were similar to the results for PASI 90. Information on quality of life was often poorly reported and was absent for several of the interventions. Our review shows that compared to placebo, the biologics infliximab, ixekizumab, risankizumab, bimekizumab, secukinumab, guselkumab and brodalumab were the most effective treatments for achieving PASI 90 in people with moderate-to-severe psoriasis on the basis of moderate- to high-certainty evidence. This NMA evidence is limited to induction therapy (outcomes were measured from 8 to 24 weeks after randomisation) and is not sufficient for evaluation of longer-term outcomes in this chronic disease. Moreover, we found low numbers of studies for some of the interventions, and the young age (mean age of 45 years) and high level of disease severity (PASI 20 at baseline) may not be typical of patients seen in daily clinical practice. Another major concern is that short-term trials provide scanty and sometimes poorly-reported safety data and thus do not provide useful evidence to create a reliable risk profile of treatments. We found no significant difference in the assessed interventions and placebo in terms of SAEs, and the evidence for all the interventions was of low to moderate quality. In order to provide long-term information on the safety of the treatments included in this review, it will also be necessary to evaluate non-randomised studies and postmarketing reports released from regulatory agencies. In terms of future research, randomised trials directly comparing active agents are necessary once high-quality evidence of benefit against placebo is established, including head-to-head trials amongst and between non-biological systemic agents and small molecules, and between biological agents (anti-IL17 versus anti-IL23, anti-IL23 versus anti-IL12/23, anti-TNF alpha versus anti-IL12/23). Future trials should also undertake systematic subgroup analyses (e.g. assessing biological-naïve participants, baseline psoriasis severity, presence of psoriatic arthritis, etc.). Finally, outcome measure harmonisation is needed in psoriasis trials, and researchers should look at the medium- and long-term benefit and safety of the interventions and the comparative safety of different agents. Editorial note: This is a living systematic review. Living systematic reviews offer a new approach to review updating, in which the review is continually updated, incorporating relevant new evidence as it becomes available. Please refer to the Cochrane Database of Systematic Reviews for the current status of this review.

Sbidian E ，Chaimani A ，Garcia-Doval I ，Doney L ，Dressler C ，Hua C ，Hughes C ，Naldi L ，Afach S ，Le Cleach L ... -  《Cochrane Database of Systematic Reviews》