Antioxidants for male subfertility
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To determine whether supplementary oral antioxidants improve outcomes for couples with an idiopathic subfertile male partner who were referred to a subfertility clinic and may or may not be undergoing assisted reproduction techniques (ART) such as in vitro fertilisation (IVF), intrauterine insemination (IUI) or intra cyclic sperm injection (ICSI) as compared to placebo.
The main questions to be asked in this review:
1.to determine whether supplemented oral antioxidants improve outcomes for couples with male factor who were referred to a subfertility clinic and may or may not be undergoing assisted reproduction techniques (ART) such as in vitro fertilisation (IVF), intrauterine insemination (IUI) or intra cyclic sperm injection (ICSI) as compared to placebo;
2.to determine whether different types, doses and combined antioxidant therapy given to men have varying effects in this setting.
Background
Description of the condition
Eighty million people worldwide are affected by the inability to have children (Tournaye 2006). Delayed conception affects 15% of couples trying to conceive (Attia 2007) and male factor subfertility accounts for up to 50% of these cases. A review by Tremellen (Tremellen 2008) notes that one man in 20 will be affected by subfertility.
Some 30% to 80% of male factor subfertility cases are said to be due to the damaging effects of oxidative stress (Tremellen 2008). Oxidative stress occurs when reactive oxygen species (ROS) overcome the semen’s natural antioxidant defences and cause cellular damage (Tremellen 2008).
Spermatozoal membranes are rich in poly‐unsaturated fatty acids and are susceptible to oxygen damage from lipid peroxidation (Sheweita 2005). Abnormal spermatozoa and contaminating leukocytes generate ROS (Sikka 1995). There is evidence to suggest that some forms of male factor subfertility may also be associated with a reduced ratio of histone to protamine packaging in spermatozoal DNA (Zini 2007).
Antioxidants naturally found in semen include vitamins E and C, superoxide dismutase, glutathione and thioredoxin (Omu 2008). These antioxidants act as free radical scavengers that help to overcome ROS. Subfertile men have been identified as having lower levels of antioxidants in their semen as compared to fertile men (Tremellen 2007). A prospective study by Bykova (Bykova 2007) showed that ROS levels were significantly higher in infertile sperm samples when compared with healthy controls and that these infertile men may benefit from an antioxidant supplement.
Some studies have suggested that sperm production and quality has decreased over the past few decades (Stankiewicz 2003). The increased levels in ROS are thought to be due to environmental factors such as high temperatures, electromagnetic radiation, pesticides, pollution; and lifestyle factors of advanced age, alcohol consumption, smoking, stress, obesity and poor diet. Other factors include infections, autoimmunity and chronic disease (Aitken 2007; Alvarez 2003; Tremellen 2008).
ROS are thought to cause fertility problems in two ways, firstly by damaging the sperm membrane thus affecting the sperm motility and the ability of the spermatozoa to break down the oocyte membrane; and secondly by altering the sperm DNA. Spermatozoal DNA integrity is one of the major determinants of normal fertilisation and embryo growth in natural and assisted conception (Agarwal 2003; Aitken 2004; Tarozzi 2007). Indeed many men with normal seminal parameters may have a high degree of sperm DNA damage and this correlates with a poor chance of natural conception (Boe‐Hansen 2006).
Sperm DNA damage or integrity can be assessed in a number of ways:
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sperm chromatin structural assay by flow cytometry ‐ (SCSA),
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enzymatic labelling of broken DNA strands ‐ the terminal deoxynucleotidyl transferase‐mediated nick end‐labelling assay (TUNEL), and
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microscopic observations of DNA fragments ‐ the Comet assay.
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The greatest experience and standardisation exists for the SCSA (Aitken 2007; Evenson 2007). Indeed there are advocates who state that this should be part of a standard assessment of the male partner when a couple presents with subfertility (Boe‐Hansen 2006); although it is recognised that the technique has its limitations and hence strict laboratory control and standardisation is required (Boe‐Hansen 2005).
Sperm DNA fragmentation does not appear to influence fertilisation in in vitro fertilisation (IVF), although a negative correlation of sperm DNA damage with embryo or blastocyst development has been described (Evenson 2006; Li 2006; Tarozzi 2007). Women undergoing intrauterine insemination with a sperm DNA fragmentation index < 30%, as measured by the SCSA, are seven times more likely to achieve a pregnancy than those couples where the male partner had a higher degree of sperm DNA damage (Evenson 2006). The evidence for the effect of a high degree of sperm DNA damage upon pregnancy outcome is less clear. A meta‐analysis of sperm DNA fragmentation assessed by the SCSA determined that if the sperm DNA fragmentation was < 30% the couple were twice as likely to conceive in an IVF cycle than if it was greater than 30%, though the evidence for a benefit in women undergoing intra‐cytoplasmic sperm injection (ICSI) was unclear (Evenson 2006). However a meta‐analysis of SCSA papers published in the same year demonstrated conflicting results (Li 2006). This meta‐analysis found there was no effect of sperm DNA damage upon the outcome of IVF or ICSI when assessed by the SCSA assay (Li 2006). Furthermore, this meta‐analysis also reviewed the effect of sperm DNA damage as assessed by the TUNEL assay. This demonstrated a reduced pregnancy rate in women undergoing IVF when the male partner had a high degree of sperm DNA damage but no difference if they were undergoing ICSI (Li 2006). It also appears that in women undergoing assisted reproduction miscarriage is more likely when the sperm DNA damage is high (Borini 2006).
Description of the intervention
Antioxidants are both biological (enzymes) and chemical substances that reduce oxidative damage. The chemical antioxidants are both natural and synthetic. These can be derived from nutritional sources and from supplementation (Sikka 1995). The predominant supplementary antioxidants studied in male subfertility clinical trials are vitamin E, vitamin C, carotenoids, ubiquinols and the micronutrients folate and zinc (Eskenazi 2005). Clinical trials have also used treatment combinations of vitamins and micronutrients. A trial by Tremellen (Tremellen 2007) showed a significant improvement in viable pregnancy rate in couples undergoing ICSI or IVF using a combined supplementation.
Polyunsaturated fatty acids (PUFA's) are sources of antioxidants and are commonly taken as nutritional supplements in the community. PUFA's have varying effects in male fertility, they provide antioxidants and also increase the plasma fluidity of the sperm membrane which acts to assist with conception however this fluidity also makes the sperm susceptible to reactive oxygen species and lipid peroxidation that can damage the sperm Wathes 2007 . Wathers states that "It appears that PUFA's are a two edged sword ‐ some are essential, but too many are potentially harmful" (Wathes 2007 page198). An open prospective study by Comhaire attempts to overcome the double edged sword of supplemented essential fatty acids by also treating the subfertile men in their study with the antioxidant supplements of acetylcysteine or beta‐carotene and alpha‐tocopherol (Comhaire 2000).
PUFA's are classified into omega‐3, omega‐6 and omega‐9. Omega 9 is synthesised by animals but omegas‐3 and 6 need to be supplemented to the diet. The main sources of omega‐6 are vegetable oils. Sources of omega‐3 are found in vegetable and fish oils (Wathes 2007).
Adverse effects are uncommon from a high intake of water soluble vitamins. Folic acid may aggravate neurological problems in pernicious anaemia suffers and high doses of vitamin C could increase the risk of kidney stones. Fat soluble vitamins are more dangerous in high levels, for example high doses of vitamin A may cause symptoms such as anaemia, loss of hair and skeletal changes. Large quantities of vitamin D can produce hypercalcemia (Cleveland Clinic 2008).
How the intervention might work
Antioxidants are known to dispose and scavenge ROS, suppress their formation and also act to oppose the actions of ROS (Sikka 1995). The dietary intake of antioxidants has been shown to be critically important for semen quality. Some clinical trials of antioxidant supplementation have shown an increase in fertilisation rates, possibly by reducing oxidative stress, lipid peroxidation potential and ROS levels (Eskenazi 2005).
Why it is important to do this review
Currently there is limited evidence that antioxidant supplementation improves outcomes for subfertile couples. Although supplemented antioxidants have proven benefits in some clinical trials in treating male subfertility there are other trials that fail to demonstrate the same benefit (Agarwal 2004). Tournaye (Tournaye 2006) describes the current consensus on the treatment of unexplained male subfertility with antioxidants as potentially beneficial, but states that there is a need for further evaluation. A meta‐analysis by Isidori (Isidori 2006) found that when using a weighted mean difference carnitine increased sperm motility by 9% (95% CI 3.7 to 14.5); however significant heterogeneity was found in the trials studied, which indicates that further studies are required to clarify the antioxidant response.
The purpose of this Cochrane review is to assess the effects of antioxidants on men with documented sperm DNA damage and men with impaired semen parameters from appropriate clinical trials that use clinically relevant parameters of live birth and pregnancy, rather than focusing on the surrogate outcomes of sperm parameters. Secondly, the review will assess the effectiveness of different antioxidants and dosages on these outcomes
Objectives
To determine whether supplementary oral antioxidants improve outcomes for couples with an idiopathic subfertile male partner who were referred to a subfertility clinic and may or may not be undergoing assisted reproduction techniques (ART) such as in vitro fertilisation (IVF), intrauterine insemination (IUI) or intra cyclic sperm injection (ICSI) as compared to placebo.
The main questions to be asked in this review:
1.to determine whether supplemented oral antioxidants improve outcomes for couples with male factor who were referred to a subfertility clinic and may or may not be undergoing assisted reproduction techniques (ART) such as in vitro fertilisation (IVF), intrauterine insemination (IUI) or intra cyclic sperm injection (ICSI) as compared to placebo;
2.to determine whether different types, doses and combined antioxidant therapy given to men have varying effects in this setting.
Methods
Criteria for considering studies for this review
Types of studies
Inclusion criteria
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Only randomised controlled trials will be eligible for inclusion. The participants would be randomised to antioxidant versus placebo, an alternative antioxidant, or no treatment.
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Only pre‐crossover data will be used from randomised crossover trials, as achieving outcomes such as pregnancy and live birth would preclude the couples entering the next trial phase (Dias 2006).
Exclusion criteria
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Any quasi‐randomised trials.
Types of participants
Inclusion criteria
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Trials that include men who are part of a couple with male factor subfertility or unexplained subfertility who have been referred to a fertility clinic and may or may not be undergoing assisted reproduction techniques (ART) such as in vitro fertilisation (IVF), intrauterine insemination (IUI) or intra cyclic sperm injection (ICSI) as compared to placebo.
In situations where individuals are re‐randomised following failed cycles the data will not be pooled in a meta‐analysis unless individual data can be excluded.
Exclusion criteria
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Trials that exclusively report on men who have previously had chemotherapy will be excluded
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Trials that exclusively report on men who have previously had other fertility enhancing therapy will be excluded
Types of interventions
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Trials will be included if they investigate any type of oral antioxidant supplementation versus placebo or other antioxidant
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Trials will be included if they investigate individual or combined oral antioxidants versus placebo or other antioxidant
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Trials will be included if they investigate any dose of oral antioxidant versus placebo or other antioxidant
Types of outcome measures
Primary outcomes
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Live birth rate per couple randomised.
Secondary outcomes
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Pregnancy (biochemical and or clinical) rate per couple.
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Level of sperm DNA damage after treatment.
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Miscarriage (biochemical and or clinical) rate per couple, or spontaneous abortion.
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Still birth rate per couple.
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Adverse effects associated with antioxidant supplementation, or as reported by the trial. Withdrawal numbers due to individual adverse effects will be reported.
Search methods for identification of studies
Electronic searches
See the Cochrane Menstrual Disorders and Subfertility Group methods used in reviews as stated in their Module (http://www.mrw.interscience.wiley.com/cochrane/cochrane_clsysrev_crglist_fs.html).
All reports that describe (or might describe) randomised controlled trials of oral antioxidant supplementation for men prior to IVF or ICSI will be found using the following strategy.
(1) The Menstrual Disorders and Subfertility Group Specialised Register of controlled trials will be searched by the Group's trial search coordinator using the terms 'male subfertility' or 'In vitro fertilisation' or 'IVF' or 'Intracytoplasmic sperm injection' or 'ICSI' AND 'antioxidants' or 'vitamin e' or 'vitamin' or 'ascorbic acid' or 'zinc' or 'folate' or 'selenium' or 'gluthatione' or 'ubiquinol' or 'carnitine' or 'astaxanthin' or 'coenzyme Q10' or 'lycopene' or 'Menevit' or "carnitene" or "carnitine" or "ascorbic acid" or "zinc" or "fatty acids" or "oil" or "fish oils" or "plant extracts" in the titles, abstracts and keywords (Appendix 7).
This register also contains unpublished trial abstracts. These are found by handsearching of 20 relevant journals and conference proceedings.
(2) The following databases will be searched using the Ovid platform:
Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library current Issue) (Appendix 3); MEDLINE (1980 to present) (Appendix 1);
EMBASE (1980 to present) (Appendix 2);
CINAHL (1980 to present) (Appendix 4);
PSYCHINFO (1980 to present) (Appendix 5);
AMED (Allied and Complementary Medicine) (1980 to present) (Appendix 6).
Both indexed and free text terms will be used. The randomised controlled trial filter used here is from the Cochrane Menstrual Disorders and Subfertility Group (MDSG).
Searching other resources
(1) Research registers, such as the National Research Register (www.nrr.nhs.uk) or Clinical Trials Register (www.clinicaltrials.gov) will be searched for appropriate ongoing and recently completed studies.
(2) Citation lists will be searched, from review articles and other relevant publications.
(3) Searches will not be limited to any one language.
(4) Personal communication with manufacturers, experts, and specialists in the field.
Data collection and analysis
Selection of studies
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Two review authors will be responsible for independently selecting the trials. Titles and abstracts from the searches will be scanned.
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One of these individuals will be a content expert.
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Any disagreements will be resolved through consensus or by a third party.
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Studies will be appraised in an unblinded fashion, as recommended by the Cochrane Menstrual and Fertility Disorders Group.
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Further information, where required, will be sought from the authors.
Data extraction and management
The studies that appear to meet the inclusion criteria will be independently assessed by the two review authors using data extraction forms. Any discrepancies will be resolved with discussion.
The data extraction forms will include methodological quality and allocation score information as follows. This information will be included in the review and presented in the characteristics of included and excluded studies tables following the guidance of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2006).
Assessment of risk of bias in included studies
Trial characteristics
(1) Method of randomisation, i.e. computer generated, random number tables.
(2) Trial design, parallel, randomised, placebo controlled.
(3) Assigned groups adequately concealed at allocation.
(4) Number of men enrolled, randomised, excluded post‐randomisation, analysed.
(5) Intention‐to‐treat analysis used.
(6) Outcome assessors blinded to whether a man was in treatment or placebo group.
(7) Comparable treatment and placebo groups at entry.
(8) Men blinded to treatment or placebo status.
(9) Clinicians blinded to treatment or placebo status.
(10) Both groups treated in the same way.
(11) Funding sources reported.
(12) Ethics approval.
(13) Written informed consent.
(14) Power calculation.
(15) Location of the trial, whether single or multicentre.
Characteristics of participants
(16) Baseline characteristics ‐ duration of infertility; age of men and their partners; previous infertility treatment; men's body mass index (BMI); alcohol, drug and cigarette use.
(17) Definition of infertility given by the trials.
(18) Inclusion and exclusion criteria clearly defined.
Types of Interventions
(19) Type of antioxidant.
(20) Is the placebo identical, what is the placebo made up of?
(21) Dose and duration of treatment.
(22) Compliance.
Outcomes
(23) What outcomes were stated in methods and reported in results?
(24) How were outcomes such as pregnancy, miscarriage, or stillbirth defined?
(25) Outcome measures adequate in terms of accuracy, precision, and observer variation (Higgins 2006), i.e. what instrumentation is used to diagnose pregnancy ‐ type of urine test or ultrasound?
(26) Appropriate timing of outcome measurement ‐ when were pregnancy outcomes measured.
(27) How was a self‐reported outcome of adverse effects for men validated?
(28) Length of follow up after the end of antioxidant treatment.
The pregnancy outcomes are considered positive, higher numbers of pregnancy rates are considered a benefit; while the outcomes of miscarriage and adverse events are negative effects of the treatment, higher numbers would be considered harmful. These aspects would have to be considered when assessing the summary graphs (Attia 2007).
A funnel plot will be generated if there is a question of publication bias, resulting from the search strings. A gap on either side of the graph will give a visual indication that some trials have not been found (Higgins 2006). This is often due to the difficulties in locating unpublished trials.
Measures of treatment effect
The dichotomous data for live birth, pregnancy rate, miscarriage, stillbirth, and adverse events will be expressed as odds ratios (OR) with 95% confidence intervals (95% CI) and combined in a meta‐analysis with Rev Man software using the Peto method and a fixed‐effect model (Higgins 2006).
The OR has mathematically sound properties that are consistent with benefit or harm and work well in small samples with rare events. This effect measure is appropriate when considering subfertility
For continuous data (e.g. quality of life scores), weighted mean differences between treatment groups will be calculated, with associated standard deviations. These will be displayed on forest plots if possible.
Unit of analysis issues
Only data that reports outcomes per couple randomised will be pooled in order to avoid analysis errors.
Dealing with missing data
The review authors shall contact the lead authors of the trials where if data clarification is required this contact shall be made by email post and by telephone.
In circumstances where we cannot resolve data issues we shall assume that data is randomly missing and perform a sensitivity analysis to determine the impact of this decision upon our final results, which may mean that we are unable to include a particular study.
If there are outcomes with no data the review will include empty data tables. This will indicate that further clinical trials need to be conducted in this area. It also allows for updating, when new data may be found.
Assessment of heterogeneity
Heterogeneity between the treatment effects of different studies will be studied by looking at the points on the forest plot, the overlap of confidence intervals (a poor overlap indicates heterogeneity), and the Chi2 statistical test for heterogeneity. A low P‐value (or a large Chi2 statistic relative to its degree of freedom) will show evidence of heterogeneity of treatment effects, or that the differences were not likely to be by chance (Higgins 2006). If there are only a small number of trials or they have small sample sizes then a P‐value of 0.10 rather than 0.05 will be used to show heterogeneity. To more formally quantify the variations between the studies the I2 statistic will be used (Higgins 2006). This statistic describes the variation in effect estimates due to heterogeneity rather than by chance as a percentage. If a value over 50% is found we will assume that there is large heterogeneity.
Attia (Attia 2007) notes that while trials in subfertility may be statistically homogeneous, there may be significant differences in clinical parameters because different centres use their own 'methods and materials'. Therefore, if the trials meet the inclusion criteria and use antioxidants as the intervention plus appropriate control it is appropriate to pool the results.
Assessment of reporting biases
We shall attempt to reduce publication and related bias (PRB) through the use of alternative, robust search strategies including handsearching (Hopewell 2007) and the use of the Internet (for example, Google and other search engines), comprehensive search of the grey literature (Hopewell 2007b), alternative sources of data or synthesized evidence, and contacting experts and the research community (Hopewell 2007c).
Graphical, descriptive and analytical methods will be used to detect, and mitigate the problem. Subject to adequate numbers, funnel plots will be constructed to illustrate the effect size versus measure of precision. A visual inspection of the plot(s) will be used to confirm the presence and magnitude of PRB (Song 2002). Further, complex statistical methods will be used to explore for PRB by plotting estimates against corresponding precision for each meta‐analysis as follows: Begg & Mazumdar's rank correlation test (Begg 1994), Egger's regression test (Egger 1997) and the Trim and Fill method (Duval 2000). These alternative methods are necessary because we anticipate that like most reviews, our meta‐analysis may include rather small numbers of studies. Further, the asymmetry observed in the funnel plot may be due to serious methodological flaws (Stuck 1998) or the fact that the intervention is highly effective. These possibilities will be ascertained.
Data synthesis
The presence or absence of heterogeneity will be considered before pooling data from more than one trial.
The pre‐specified potential sources of heterogeneity will be used to explore possible explanations of variation in effect between trials, and to guide interpretation of the findings.
Where is it not appropriate to combine primary studies they will be summarised in a narrative form.
Subgroup analysis and investigation of heterogeneity
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Trials that report on antioxidants (individual and combined) given to men with documented elevated levels of sperm DNA damage, as defined by the trials, who are undergoing fertility treatment (IUI and IVF or ICSI). A minimum of 80% of participants in the trials would have to satisfy this criterion for inclusion. If individual data is available these will be used in preference.
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Trials that report antioxidants (individual and combined) given to men with impaired semen parameters who are undergoing fertility treatment (IUI and IVF/ICSI). A minimum of 80% of participants in the trials would have to satisfy this criterion for inclusion. If individual data are available these will be used in preference.
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Treatment will be divided into the subgroups ‐ individual and combined antioxidants for live birth and pregnancy outcomes.
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Adverse effects will be reported as subgroups. The overall summary statistic will not be pooled as individuals may appear in more than one of the subgroups.
Sensitivity analysis
Sensitivity analysis (using the random‐effects model in RevMan software) will show how sensitive the results are to the way the analysis was done. The analysis will be repeated excluding firstly:
(1) unpublished studies ‐ these studies may not have been peer reviewed and thus be of lower quality;
(2) studies with the lowest allocation score; the allocation score will be based on the assessment of methodological quality (Higgins 2006).
