Vitamin E supplementation for adults with diabetes mellitus

  • Protocol
  • Intervention

Authors

  • Anna Selva Olid,

    Corresponding author
    1. Biomedical Research Institute Sant Pau (IIB-Sant Pau), Iberoamerican Cochrane Centre, Barcelona, Spain
    • Anna Selva Olid, Iberoamerican Cochrane Centre, Biomedical Research Institute Sant Pau (IIB-Sant Pau), C. Sant Antoni Maria Claret 167, Pavelló 18 I Planta 0, Barcelona, 08025, Spain. ASelva@santpau.cat.

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  • Dolors Ramírez i Tarruella,

    1. Bellvitge University Hospital, Preventive Medicine Department, L'Hospitalet de Llobregat, Barcelona, Spain
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  • Dimelza Osorio,

    1. Biomedical Research Institute Sant Pau (IIB-Sant Pau), Iberoamerican Cochrane Centre, Barcelona, Spain
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  • Antonio Jesús Blanco Carrasco,

    1. Hospital Clínic, Endocrinology and Nutrition Department, Barcelona, Barcelona, Spain
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  • Ivan Solà

    1. CIBER Epidemiología y Salud Pública (CIBERESP), Iberoamerican Cochrane Centre, Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Catalunya, Spain
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Abstract

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the effects of vitamin E supplementation for adults with diabetes mellitus.

Background

Description of the condition

Diabetes mellitus is a metabolic disorder resulting from a defect in insulin secretion, insulin action, or both. A consequence of this is chronic hyperglycaemia (that is elevated levels of plasma glucose) with disturbances of carbohydrate, fat and protein metabolism. Long-term complications of diabetes mellitus include retinopathy, nephropathy and neuropathy, and the risk of cardiovascular disease is increased.

Hyperglycaemia increases free radical production leading to oxidative stress, which is defined as a persistent imbalance between the production of highly reactive molecular species (oxygen and nitrogen) and antioxidant defences (Evans 2003). Oxidative stress can directly oxidise and damage cellular components such as deoxyribonucleic acid (DNA), proteins and lipids, and indirectly induces damage to tissues by activating cellular stress-sensitive pathways. Hyperglycaemic state increases oxidative stress by different pathways: 1) by non-enzymatic glycosylation reaction (glycation); 2) by the mitochondrial electron transfer system and 3) by the hexosamine pathway that is enhanced in the diabetic state (Kawahito 2009).

Many studies have indicated that oxidative stress may be a key event in causing both macrovascular and microvascular complications (Baynes 1999; Brownlee 2001; Brunner 2009; Rosen 2001). In addition, oxidative stress reduces insulin biosynthesis and secretion, and it increases insulin resistance, which aggravates diabetic state (Evans 2003; Kawahito 2009).

Description of the intervention

Vitamins are organic compounds and most of them, except vitamin D, should be ingested because humans cannot synthesise them (Fairfield 2002). Vitamin E is the major fat-soluble antioxidant in the cell antioxidant defence system. It works by donating the hydrogen from its hydroxyl (-OH) group on its ring structure to free radicals, making them unreactive (WHO 2004). The principal biological role of vitamin E is to protect polyunsaturated fatty acids (PUFAs) and other components of cell membranes and low-density lipoprotein (LDL) from oxidation. In addition to its activities as an antioxidant, vitamin E is involved in immune function and cell signalling, regulation of gene expression and other metabolic processes (Traber 2006).

Vitamin E is a family of eight naturally occurring homologues: four tocopherol homologues (α, β, γ and Δ) and four tocotrienols. α-Tocopherol is the most abundant and biologically active ( WHO 2004), and it is available commercially in its natural form (labelled with a d- prefix) or in a synthetic form (all racemic form or labelled with a dl- prefix). The recommended dietary allowances (RDAs) for vitamin E are 15 mg or 22 international units (IU) for people of 14 years or older from natural-source vitamin E or 33 IU of the synthetic form (IOM 2000).

Adverse effects of the intervention

High doses of α-tocopherol supplements can cause haemorrhage and interrupt blood coagulation in animals, and in vitro data suggest that high doses inhibit platelet aggregation (NIH 2013). Some randomised controlled trials (RCTs) in humans have reported low incidence of adverse events such as gastrointestinal symptoms and fatigue (Bendich 1988). One meta-analysis found that high doses of vitamin E supplements (≥ 400 IU/day) may increase all-cause mortality and also found a dose-response relationship with increased risk with doses greater than 150 IU/day (Miller 2005). The tolerable upper intake levels (ULs) for vitamin E from supplements are based on the potential for haemorrhagic effects. For people aged 19 years or older, the ULs are 1000 mg/day of α-tocopherol or 1500 IU/day of natural-source vitamin E or 1100 IU of its synthetic form (IOM 2000).

How the intervention might work

On the basis of its antioxidant action, it is thought that vitamin E supplementation may be useful against oxidative stress diseases such as diabetes mellitus, cancer and cardiovascular disease.

It is thought that vitamin E can prevent atherosclerotic disease by its antioxidant effect, inhibitory effects upon smooth muscle proliferation and platelet adhesion (Fairfield 2002). Some cohort studies have found that high doses of vitamin E supplements produced a reduction in coronary heart disease (Rimm 1993; Stampfer 1993); however, RCTs found no protective effect of vitamin E in preventing myocardial infarction or deaths from heart disease among individuals with heart disease or people at high risk for it (GISSI 1999; Lonn 2005; Yusuf 2000). However, evidence has shown a reduction in coronary heart disease in certain subgroups, for example people with type 2 diabetes (Milman 2008).

One systematic review and meta-analysis of nine prospective cohort studies reported that the consumption of vitamin E was associated with a reduction in the risk of type 2 diabetes (Hamer 2007). However, RCTs have not observed significant effects of vitamin E on the incidence of type 2 diabetes either in healthy or at-risk women (Liu 2006; Song 2009).

Although some studies have found that vitamin E supplementation may reduce fasting glucose and glycosylated haemoglobin in people with both type 1 and type 2 diabetes (Ceriello 1991; Gokkusu 2001), RCTs have observed no statistically significant effect of vitamin E supplementation on serum glucose, glycosylated haemoglobin A1c (HbA1c) or glycosylated plasma proteins (Fuller 1996; Gomez-Perez 1996). Some publications have pointed out that vitamin E supplementation may prevent and retard diabetic chronic complications, leading to an improvement in morbidity, mortality and health-related quality of life of these people (Ceriello 2004; Ceriello 2009).

Why it is important to do this review

Some systematic reviews have been performed to assess the antioxidant effects of vitamin E supplementation on different health problems (Bjelakovic 2011; Farina 2012; Kleijnen 1998; Mathew 2012; Soares-Weiser 2011). One systematic review focusing on people with type 2 diabetes found that vitamin E supplementation does not improve HbA1c (Suksomboon 2011). However, studies have been undertaken in recent years that may provide new evidence. In addition, it is necessary to determine the effects of vitamin E supplementation on patient-relevant outcomes, such as prevention of complications.

Objectives

To assess the effects of vitamin E supplementation for adults with diabetes mellitus.

Methods

Criteria for considering studies for this review

Types of studies

All RCTs of vitamin E, allocating people with diabetes individually or by cluster, and with a follow-up of at least six months. Non-randomised and quasi-randomised controlled trials will not be eligible for inclusion.

Types of participants

Participants aged 18 years or older, with type 1 or 2 diabetes mellitus without diabetic chronic complications (nephropathy, neuropathy, retinopathy, cardiovascular events).

Diagnostic criteria (diabetes mellitus)

To be consistent with changes in classification and diagnostic criteria of diabetes mellitus through the years, the diagnosis should be established using the standard criteria valid at the time of the beginning of the trial (e.g. ADA 1999; ADA 2008; WHO 1998). Ideally, diagnostic criteria should have been described. If necessary, we will use authors' definition of diabetes mellitus. We plan to subject diagnostic criteria to a sensitivity analysis.

Types of interventions

We plan to investigate the following comparisons of intervention versus control/comparator where the same letters indicate direct comparisons.

Intervention

(a) Any type of vitamin E supplementation, either in its natural or synthetic form, at any dose and duration, either in monotherapy or in combination with other antioxidants (i.e. lipoic acid, vitamin C).

Comparator

(a1) No intervention.

(a2) Placebo.

(a3) Other antioxidants.

(a4) Mineral supplementation.

In case of combination therapy, we will only include studies in which the effects of vitamin E can be depicted. Therefore, additional interventions have to be the same between intervention and comparator groups.

Types of outcome measures

Primary outcomes
  • Diabetic complications.

  • HbA1c.

  • Adverse events.

Secondary outcomes
  • All-cause mortality.

  • Lipid profile.

  • Blood pressure.

  • Health-related quality of live.

  • Socioeconomic effects.

Method and timing of outcome measurement
  • Diabetic complications: diabetic complications are defined as nephropathy, neuropathy, retinopathy and cardiovascular events (myocardial infarction, stroke or peripheral vascular disease) measured at least at six months.

  • Glycaemic control will be measured by HbA1c at least at six months.

  • Adverse effects of the intervention: for example toxicity, haemorrhage, gastrointestinal effects.

  • All-cause mortality: defined as death from any cause.

  • Lipid profile: defined as blood levels of high-density lipoprotein (HDL)-cholesterol, LDL-cholesterol and triglycerides measured at least at six months.

  • Blood pressure: systolic and diastolic blood pressure, measured at least at six months.

  • Health-related quality of life: measured by validated instruments such as Diabetes Quality of Life Measure (DQOL), 36-item Short Form (SF-36) V2, EQ-5D.

  • Socioeconomic effects: direct medical costs or direct medical resource use.

'Summary of findings' table

We will establish a 'Summary of findings' table using the following outcomes listed according to priority.

  1. Diabetic complications.

  2. Adverse events.

  3. Health-related quality of life.

  4. All-cause mortality.

  5. HbA1c.

  6. Socioeconomic effects.

Search methods for identification of studies

Electronic searches

We will search the following sources from inception to the present.

  • The Cochrane Library.

  • MEDLINE.

  • EMBASE.

  • CINAHL (EBSCO Host).

  • ISI Web of Science.

  • PubMed Dietary Supplement Subset, which succeeds the Information on Dietary Supplements (IBIDS).

We will search the OpenSIGLE database to identify grey literature and the ProQuest Dissertations and Theses to retrieve theses related to our topic of interest.

We will also search trial registers including ClinicalTrials.gov (clinicaltrials.gov/), metaRegister of Controlled Trials (www.controlled-trials.com/mrct/), the EU Clinical Trials register (www.clinicaltrialsregister.eu/), and the World Health Organization (WHO) International Clinical Trials Registry Platform Search Portal (apps.who.int/trialsearch/).

For detailed search strategies, see Appendix 1. We will continuously apply PubMed's 'My NCBI' (National Center for Biotechnology Information) email alert service to identify newly published studies using a basic search strategy (see Appendix 1). Four weeks before we submit the final review draft to the Cochrane Metabolic and Endocrine Disorders Group (CMED) for editorial approval, we will perform an updated search on all specified databases. If we identify new studies for inclusion, we will evaluate these and incorporate findings in our review before submission of the final review draft (Beller 2013).

If we detect additional relevant key words during any of the electronic or other searches, we will modify the electronic search strategies to incorporate these terms and document the changes. We will place no restrictions on the language of publication when searching the electronic databases or reviewing reference lists of identified studies.

We will send results of electronic searches to the CMED for databases that are not available at the editorial office.

Searching other resources

We will try to identify other potentially eligible trials or ancillary publications by searching the reference lists of retrieved included trials, (systematic) reviews, meta-analyses and health technology assessment reports.

Data collection and analysis

Selection of studies

We will manage the citations using a reference management software (ProCite). Two review authors (AS, DO) will independently scan the title, abstract or both sections of every record retrieved to select the studies to be assessed further. The review authors will not be blinded about study authors or the name of the publication. We will review all potentially relevant articles as full-text versions. If AS and DO do not agree about selecting a study, a third review author (DR) will resolve the disagreement. If disagreement persists, we will add the article to an 'awaiting assessment list' for further clarification by study authors. We will attach an adapted PRISMA (preferred reporting items for systematic reviews and meta-analyses) flow-chart of study selection (Figure 1) (Liberati 2009).

Figure 1.

Study flow diagram.

Data extraction and management

For studies that fulfil inclusion criteria, two review authors (AS, DO) will independently abstract relevant information about population and intervention characteristics using standard data extraction templates (for details see Table 1; Appendix 2; Appendix 3; Appendix 4; Appendix 5; Appendix 6; Appendix 7; Appendix 8; Appendix 9; Appendix 10; Appendix 11; Appendix 12; Appendix 13). We will resolve any disagreements by discussion, or, if required, by consultation with a third review author (DR).

Table 1. Overview of study populations
  1. aAccording to power calculation in study publication or report

    bDuration of intervention or follow-up, or both, under randomised conditions until end of study

    "-" denotes not reported

    C: comparator; I: intervention; ITT: intention-to-treat; N/A: not applicable

CharacteristicIntervention(s) and comparator(s)Sample sizeaScreened or eligible
[N]
Randomised
[N]
Safety
[N]
[N] ITTFinishing study
[N]
Randomised finishing study
[%]
Follow-upb
(1) Study IDI1: vitamin E        
I2:        
C1:        
C2:        
  total:      
 
Grand total All interventions    ...    ...   
All comparators    ...    ...   
All interventions and comparators    ...    ...   

We will provide information including trial identifier about potentially relevant ongoing studies in the table 'Characteristics of ongoing studies' and in the appendix 'Matrix of study endpoints (trial documents)'. We will try to find the protocol of each included study, either in trial registers, in publications of study designs, or both, and specify data in the appendix 'Matrix of study endpoints (trial documents)'.

We will send an email to all study authors of included studies to enquire whether they are willing to answer questions regarding their trials. We will present the results of this survey in Appendix 14. Thereafter, we will seek relevant missing information on the trial from the primary author(s) of the article, if required.

Dealing with duplicate publications and companion papers

In the event of duplicate publications, companion documents or multiple reports of a primary study, we will maximise yield of information by collating all available data. In case of doubt, we will give priority to the publication reporting the longest follow-up associated with our primary or secondary outcomes.

Assessment of risk of bias in included studies

Two review authors (AS, DO) will assess each trial independently and will resolve possible disagreements by consensus, or with consultation of a third party. In case of disagreement, we will consult the rest of the group and make a judgement based on consensus.

We will assess risk of bias using The Cochrane Collaboration's tool (Higgins 2011a; Higgins 2011b). We will assess the following criteria:

  • Random sequence generation (selection bias).

  • Allocation concealment (selection bias).

  • Blinding (performance bias and detection bias), separated for blinding of participants and personnel, and blinding of outcome assessment.

  • Incomplete outcome data (attrition bias).

  • Selective reporting (reporting bias).

  • Other bias.

We will judge risk of bias criteria as 'low risk', 'high risk' or 'unclear risk' and evaluate individual bias items as described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will provide a 'Risk of bias' figure and a 'Risk of bias summary' figure.

We will assess outcome reporting bias (Kirkham 2010) by integrating the results of 'Examination of outcome reporting bias' (Appendix 7), 'Matrix of study endpoints (trial documents)' (Appendix 6) and section 'Outcomes (outcomes reported in abstract of publication)' of the 'Characteristics of included studies' table. This analysis will form the basis for the judgement of selective reporting (reporting bias).

We will assess the impact of individual bias domains on study results at endpoint and study levels.

For blinding of participants and personnel (performance bias), detection bias (blinding of outcome assessors) and attrition bias (incomplete outcome data), we intend to evaluate risk of bias separately for subjective and objective outcomes (Hróbjartsson 2013). We will consider the implications of missing outcome data from individual participants.

We define the following endpoints as subjective outcomes.

  • Adverse events.

  • Health-related quality of life.

We define the following outcomes as objective outcomes.

  • Diabetic complications.

  • Glycaemic control.

  • All-cause mortality.

  • Lipid profile.

  • Blood pressure.

  • Socioeconomic effects.

Measures of treatment effect

We will express dichotomous data as odds ratios (ORs) or risk ratios (RRs) with 95% confidence intervals (CIs). We plan to evaluate the risk reduction and use it to estimate the number needed to treat for an additional beneficial outcome (NNTB) whenever it is possible. We will assess continuous outcomes (e.g. blood pressure) using mean difference (MD) or standardised mean difference (SMD) depending on whether the outcomes are measured using the same scales, with 95% CIs. If information is provided in the articles, we will perform an intention-to-treat (ITT) analysis.

Unit of analysis issues

We will take into account the level at which randomisation occurred, such as cross-over trials, cluster-randomised trials and multiple observations for the same outcome.

Dealing with missing data

We will deal with missing data following guidance in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a). We will try to obtain relevant missing data from authors, and assess reasons for missing data from published studies. If data are likely to be 'missing at random', we will perform an available data analysis. If data do not seem to be 'missing at random' we will assume that participants with missing values have poor outcomes regardless of the group they were allocated.

Assessment of heterogeneity

In the event of substantial clinical, methodological or statistical heterogeneity, we will not report study results as meta-analytically pooled effect estimates.

We will identify heterogeneity by visual inspection of the forest plots and by using a standard Chi2 test with a significance level of α = 0.1, in view of the low power of this test. We will examine heterogeneity using the I2 statistic, which quantifies inconsistency across studies to assess the impact of heterogeneity on the meta-analysis (Higgins 2002; Higgins 2003), where an I2 statistic of 75% or more indicates a considerable level of inconsistency (Higgins 2011a).

When we find heterogeneity, we will attempt to determine potential reasons for it by examining individual study and subgroup characteristics.

We expect the following characteristics to introduce clinical heterogeneity.

  • Sex.

  • Age.

  • Duration of diabetes.

  • Metabolic control.

Assessment of reporting biases

We will use funnel plots where we include 10 studies or more for a given outcome to assess small study effects. Owing to several possible explanations for funnel plot asymmetry we will interpret results carefully (Sterne 2011).

Data synthesis

Unless there is good evidence for homogeneous effects across studies, we will primarily summarise low risk of bias data by means of a random-effects model (Wood 2008). We will interpret random-effects meta-analyses with due consideration of the whole distribution of effects, ideally by presenting a prediction interval (Higgins 2009). A prediction interval specifies a predicted range for the true treatment effect in an individual study (Riley 2011). In addition, we will perform statistical analyses according to the statistical guidelines contained in the latest version of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a).

Subgroup analysis and investigation of heterogeneity

We will carry out subgroup analyses and plan to investigate interactions. The following subgroup analyses are planned.

  • Type 1 or type 2 diabetes.

  • Monotherapy vitamin E or combination therapy with other antioxidants.

  • Serum vitamin E levels: below reference ranges (16 µmol/mL or 688 µg/dL) or above (IOM 2000).

Sensitivity analysis

We will perform sensitivity analyses in order to explore the influence of the following factors on effect size.

  • Restricting the analysis to published studies.

  • Restricting the analysis taking into account risk of bias, as specified in the section Assessment of risk of bias in included studies.

  • Restricting the analysis to very long or large studies, to establish how much they influence the results.

  • Restricting the analysis to studies using the following filters: diagnostic criteria, language of publication, source of funding (industry versus other), country.

We will also test the robustness of the results by repeating the analysis using different measures of effect size (RR, OR, etc.) and different statistical models (fixed-effect and random-effects models).

Acknowledgements

To Jordi Pardo Pardo for his help and assessment.

Appendices

Appendix 1. Search strategies

Search terms and databases

Unless otherwise stated, search terms are free-text terms.

Abbreviations: '$': any character; '?': substitutes one or no character; adj: adjacent (i.e. number of words within range of search term); exp: exploded MeSH; MeSH: medical subject heading (MEDLINE medical index term); pt: publication type; sh: MeSH; tw: text word.

The Cochrane Library
#1 MeSH descriptor Diabetes mellitus explode all trees
#2 diabet* in All Text
#3 (IDDM in All Text or NIDDM in All Text or MODY in All Text or T1DM in All Text or T2DM in All Text or T1D in All Text or T2D in All Text)
#4 ((non in All Text and insulin* in All Text and depend* in All Text) or (noninsulin* in All Text and depend* in All Text) or (non in All Text and insulindepend in All Text) or noninsulindepend* in All Text)
#5 ( (insulin in All Text and depend* in All Text) or insulindepend* in All Text)
#6 (#1 or #2 or #3 or #4 or #5)
#7 MeSH descriptor Diabetes insipidus explode all trees
#8 (diabet* in All Text and insipidus in All Text)
#9 (#7 or #8)
#10 (#6 and not #9)
#11 MeSH descriptor Vitamin E explode all trees
#12 ("vitamin* E" in All Text or "vitamin*E" in All Text or (alpha in All Text and tocopherol* in All Text) )
#13 (#11 or #12)
#14 (#10 and #13)  
MEDLINE (OvidSP)
1 exp Diabetes Mellitus/
2 diabet$.tw,ot.
3 (IDDM or NIDDM or MODY or T1DM or T2DM or T1D or T2D).tw,ot.
4 (non insulin$ depend$ or noninsulin$ depend$ or non insulin?depend$ or noninsulin?depend$).tw,ot.
5 (insulin$ depend$ or insulin?depend$).tw,ot.
6 exp Diabetes Insipidus/
7 diabet$ insipidus.tw,ot.
8 or/1-5
9 6 or 7
10 8 not 9
11 exp Vitamin E/
12 (Vit* E or Vit*E or alpha tocopherol).tw,ot.
13 11 or 12
14 10 and 13
15 (animals not (animals and humans)).sh.
16 14 not 15
17 randomized controlled trial.pt.
18 controlled clinical trial.pt.
19 randomi?ed.ab.
20 placebo.ab.
21 clinical trials as topic.sh.
22 randomly.ab.
23 trial.ti.
24 or/17-23
25 Meta-analysis.pt.
26 exp Technology Assessment, Biomedical/
27 exp Meta-analysis/
28 exp Meta-analysis as topic/
29 hta.tw,ot.
30 (health technology adj6 assessment$).tw,ot.
31 (meta analy$ or metaanaly$ or meta?analy$).tw,ot.
32 (search* adj10 (medical databas*or medline or pubmed or embase or cochrane or cinahl or psycinfo or psyclit or healthstar or biosis or current content*)).tw,ot.
33 (systematic adj3 review*).tw,ot.
34 or/25-33
35 24 or 34
36 (comment or editorial or historical-article).pt.
37 35 not 36
38 16 and 37
EMBASE (OvidSP)
1 exp Diabetes Mellitus/
2 diabet$.tw,ot.
3 (non insulin* depend* or noninsulin* depend* or non insulin?depend* or noninsulin?depend*).tw,ot.
4 (insulin* depend* or insulin?depend*).tw,ot.
5 (IDDM or NIDDM or MODY or T1DM or T2DM or T1d or T2D).tw,ot.
6 or/1-5
7 exp Diabetes Insipidus/
8 diabet* insipidus.tw,ot.
9 7 or 8
10 6 not 9
11 (vit* E or vit*E or alpha tocopherol*).tw,ot.
12 *alpha tocopherol/
13 11 or 12
14 10 and 13
15 exp Randomized Controlled Trial/
16 exp Controlled Clinical Trial/
17 exp Clinical Trial/
18 exp Comparative Study/
19 exp Drug comparison/
20 exp Randomization/
21 exp Crossover procedure/
22 exp Double blind procedure/
23 exp Single blind procedure/
24 exp Placebo/
25 exp Prospective Study/
26 ((clinical or control$ or comparativ$ or placebo$ or prospectiv$ or randomi?ed) adj3 (trial$ or stud$)).ab,ti.
27 (random$ adj6 (allocat$ or assign$ or basis or order$)).ab,ti.
28 ((singl$ or doubl$ or trebl$ or tripl$) adj6 (blind$ or mask$)).ab,ti.
29 (cross over or crossover).ab,ti.
30 or/15-29
31 exp meta analysis/
32 (metaanaly$ or meta analy$ or meta?analy$).ab,ti,ot.
33 (search$ adj10 (medical database$ or medline or pubmed or embase or cochrane or cinahl or psycinfo or psyclit or healthstar or biosis or current content$ or systematic$)).ab,ti,ot.
34 exp Literature/
35 exp Biomedical Technology Assessment/
36 hta.tw,ot.
37 (health technology adj6 assessment$).tw,ot.
38 or/31-37
39 30 or 38
40 (comment or editorial or historical-article).pt.
41 39 not 40
42 14 and 41
43 limit 42 to human
Web of Science (Web of Knowledge)

# 1 Topic=(diabet*)

# 2 TS=(IDDM OR NIDDM OR MODY OR T1DM OR T2DM OR T1D OR T2D)

# 3 TI=(non insulin* AND depend* )

# 4 TI=(noninsulin* AND depend* )

# 5 TI=(insulin* AND depend* )

# 6 #5 OR #4 OR #3 OR #2 OR #1

# 7 TS=(diabetesinsipidus)

# 8 #6 NOT #7

# 9 TS=(vitamin e)

# 10 TS=(vit e)

# 11 TS=(alphatocopherol)

# 12 #11 OR #10 OR #9

# 13 #12 AND #8

# 14 TI=(random*)

# 15 TS=(randomised OR randomized)

# 16 TI=(trial)

# 17 TS=(placebo)

# 18 #17 OR #16 OR #15 OR #14

# 19 #18 AND #13

'My NCBI' alert service
("vitamin e"[MeSH Terms] OR "vitamin e"[All Fields]) AND ("diabetes mellitus"[MeSH Terms] OR ("diabetes"[All Fields] AND "mellitus"[All Fields]) OR "diabetes mellitus"[All Fields]) AND Randomized Controlled Trial[ptyp]
PubMed Dietary Supplement subset
"vitamin e" [tiab] AND "diabet*" [tiab]
CINAHL (EBSCO Host)

S1 (MH "DiabetesMellitus+")

S2 TX diabet*

S3 TX (IDDM or NIDDM or MODY or T1DM or T2DM or T1D or T2D)

S4 TX (non insulin* depend* OR noninsulin* depend* OR non insulin?depend* OR noninsulin?depend*)

S5 TI non insulin* AND TI depend*

S6 TI noninsulin* AND TI depend*

S7 TI insulin* AND TI depend*

S8 S1 OR S2 OR S3 OR S4 OR S5 OR S6 OR S7

S9 (MH "DiabetesInsipidus+")

S10 TX diabetesinsipidus

S11 S9 OR S10

S12 S8 NOT S11

S13 (MH "Vitamin E")

S14 TX vitamin E

S15 TX "vit E"

S16 TX alphatocopherol

S17 S13 OR S14 OR S15 OR S16

S18 S12 AND S17

S19 Limiters - ClinicalQueries: Therapy - HighSensitivity

S20 S18 AND S19

Open Grey

Diabet* AND vitamin*

Diabet* AND antiox*

Diabet* AND tocopherol*

ProQuest Dissertations and Thesis

Diabet* AND vitamin*

Diabet* AND antiox*

Diabet* AND tocopherol*

Appendix 2. Description of interventions

CharacteristicIntervention(s) [route, frequency, total dose/day]

Adequatea intervention

[Yes / No]

Comparator(s) [route, frequency, total dose/day]

Adequatea comparator

[Yes / No]

Study 1Intervention 1 Comparator 1 
Intervention 2 Comparator 2 

Footnotes

"-" denotes not reported

aThe term 'adequate' refers to sufficient use of the intervention/comparator with regard to dose, dose escalation, dosing scheme, provision for contraindications and other features necessary to establish a fair contrast between intervention and comparator

N: no; Y: yes

Appendix 3. Baseline characteristics (I)

CharacteristicIntervention(s) and comparator(s)Duration of intervention (duration of follow-up)Participating populationStudy period [year to year]CountrySettingEthnic groups
[%]
Duration of disease
[mean/range years (SD), or as reported]
Study 1Intervention 1       
Intervention 2       
Comparator 1       
Comparator 2       
     all:  

Footnotes

"-" denotes not reported

SD: standard deviation

Appendix 4. Baseline characteristics (II)

CharacteristicIntervention(s) and comparator(s)Sex
[female %]
Age
[mean/range years (SD), or as reported]
Type of diabetes mellitus
[% type 2 diabetes]
BMI
[mean kg/m2 (SD)]
HbA1c
[mean % (SD)]
Vitamin E plasma levels
[mg/L]
Co-medications / Co-interventionsCo-morbidities
Study 1Intervention 1        
Intervention 2        
Comparator 1        
Comparator 2        
all:        

Footnotes

"-" denotes not reported.

BMI: body mass index; HbA1c: glycosylated haemoglobin A1c; SD: standard deviation

Appendix 5. Matrix of study endpoints (publications)

Study ID 

Endpoint reported

in publication

Endpoint not reported
in publication
Endpoint not
measured
Time of measurementa
Example Review's primary outcomes
Diabetic complications xN/AN/A
HbA1cx 0, 12 mo6, 12 mo
Adverse eventsx  12 mo 12 mo
Review's secondary outcomes
All-cause mortalityx 12 moN/A
Health-related quality of lifex  6, 12 mo6, 12 mo
Blood pressurex 0, 12 mo 
Lipid profilex  6, 12 mo 
Socioeconomic effects xN/AN/A
Other than review's primary/secondary outcomes reported in publication (classification: P/S/O)b
Patient satisfaction (S), safety parameters (O)
Subgroups reported in publication
Age < 65 years vs. ≥ 65 years, cardiovascular risk factors vs. no cardiovascular risk factors, type 1 diabetes vs. type 2 diabetes

Footnotes

aUnderlined data denote times of measurement for primary and secondary review outcomes, if measured and reported in the results section of the publication (other times represent planned but not reported points in time).

b(P) Primary or (S) secondary endpoint(s) refer to verbatim statements in the publication, (O) other endpoints relate to outcomes that were not specified as 'primary' or 'secondary' outcomes in the publication.

HbA1c: glycosylated haemoglobin A1c; mo: months; N/A: not applicable

Appendix 6. Matrix of study endpoints (trial documents)

Study ID (trial identifier)Endpointa Review's primary outcome Review's secondary outcomeTime of measurementSource (FDA document/EMA document/manufacturer's website/design paper/trial protocol document)
E x a m p l e Diabetic retinopathy (P)x 12 mo 
HbA1c (P)x 3, 6, 12 mo
Insulin sensitivity (O)N/AN/AN/A
Blood pressure(S) x6, 12 mo

Footnotes

"-" denotes not reported

a(P) Primary or (S) secondary endpoint(s) refer to verbatim statements in the publication, (O) other endpoints relate to outcomes which were not specified as 'primary' or 'secondary' outcomes in the report

EMA: European Medicines Agency; FDA: Food and Drug Administration (US); HbA1c: glycosylated haemoglobin A1c; mo: months; N/A: not applicable

Appendix 7. Examination of outcome reporting bias

CharacteristicOutcomeClear that outcome was measured and analyseda [trial report states that outcome was analysed but only reports that result was not significant]Clear that outcome was measured and analysedb [trial report states that outcome was analysed but no results reported]Clear that outcome was measuredc [clear that outcome was measured but not necessarily analysed (judgement says likely to have been analysed but not reported because of non-significant results)]Unclear whether the outcome was measuredd [not mentioned but clinical judgement says likely to have been measured and analysed but not reported on the basis of non-significant results]
Study 1     

Footnotes

'High risk of bias' categories for outcome reporting bias according to the Outcome Reporting Bias In Trials (ORBIT) study classification system for missing or incomplete outcome reporting in reports of randomised trials (Kirkham 2010).

aClassification 'A' (table 2, Kirkham 2010).

bClassification 'D' (table 2, Kirkham 2010).

cClassification 'E' (table 2, Kirkham 2010).

dClassification 'G' (table 2, Kirkham 2010).

N/A: not applicable

Appendix 8. Definition of endpoint measurement (I)

CharacteristicDiabetic complicationsHbA1cHealth-related quality of lifeSocioeconomic effectsLipid profileBlood pressure
Study 1      

Footnotes

HbA1c: glycosylated haemoglobin A1c; N/D: not defined; N/I: not investigated

Appendix 9. Definition of endpoint measurement (II)

Characteristic

Study ID

Mild hypoglycaemiaModerate hypoglycaemiaSevere hypoglycaemiaNocturnal hypoglycaemiaSevere/serious adverse events
Study 1     

Footnotes

N/D: not defined; N/I: not investigated

Appendix 10. Adverse events (I)

CharacteristicIntervention(s) and comparator(s)Randomised or safety population
[N]
Deaths [N]Deaths [%]All adverse events [N]All adverse events [%]Severe/serious adverse events [N]Severe/serious adverse events [%]
Study 1Intervention 1       
Intervention 2       
Comparator 1       
Comparator 2       
all:       

Footnotes

"-" denotes not reported.

Appendix 11. Adverse events (II)

CharacteristicIntervention(s) and comparator(s)Randomised or safety population
[N]
Left study due to adverse events [N]Left study due to adverse events [%]Hospitalisation [N]Hospitalisation [%]Outpatient treatment [N]Outpatient treatment [%]
Study 1Intervention 1       
Intervention 2       
Comparator 1       
Comparator 2       
all:       

Footnotes

"-" denotes not reported

Appendix 12. Adverse events (III)

CharacteristicIntervention(s) and comparator(s)Randomised or safety population
[N]
All hypoglycaemic episodes [N]All hypoglycaemic episodes [%]Severe/serious hypoglycaemic episodes [N]Severe/serious hypoglycaemic episodes [%]Nocturnal hypoglycaemic episodes [N]Nocturnal hypoglycaemic episodes [%]
Study 1Intervention 1       
Intervention 2       
Comparator 1       
Comparator 2       
all:       

Footnotes

"-" denotes not reported

Appendix 13. Adverse events (IV)

CharacteristicIntervention(s) and comparator(s)Randomised or safety population
[N]
Specific adverse events [description]Specific adverse events [N]Specific adverse events [%]
Study 1Intervention 1    
Intervention 2    
Comparator 1    
Comparator 2    
all:    

Footnotes

"-" denotes not reported

 

Appendix 14. Survey of authors providing information on included trials

CharacteristicStudy author contacted
[DD/MM/YY]
Study author replied
[DD/MM/YY]
Study author asked for additional information
[short summary]
Study author provided data
[short summary]
Study 1Yes, date:Yes, date: / No  

Footnotes

N/A: not applicable

Contributions of authors

Anna Selva Olid (AS): protocol draft, search strategy development, acquirement of trial copies, trial selection, data extraction, data analysis, data interpretation, review draft and future review update.

Dolors Ramírez i Tarruella (DT): protocol draft, search strategy development, acquirement of trial copies, trial selection, data extraction, data analysis, data interpretation, review draft and future review update.

Dimelza Osorio (DO): protocol draft, search strategy development, acquirement of trial copies, trial selection, data extraction, data analysis, data interpretation, review draft and future review update.

Antonio Jesús Blanco Carrasco (AC): protocol draft, search strategy development, acquirement of trial copies, trial selection, data extraction, data analysis, data interpretation, review draft and future review update.

Ivan Solà Arnau (IS): protocol draft, search strategy development, review draft and future review update.

Declarations of interest

AS: none known.

DT: none known.

DO: none known.

AC: none known.

IS: none known.

Sources of support

Internal sources

  • Iberoamerican Cochrane Centre, Spain.

    Logistic support

External sources

  • No sources of support supplied

Ancillary