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Metabolomics for improving pregnancy outcomes in women undergoing assisted reproductive technologies

Background

In order to overcome the low effectiveness of assisted reproductive technologies (ART) and the high incidence of multiple births, metabolomics is proposed as a non‐invasive method to assess oocyte quality, embryo viability, and endometrial receptivity, and facilitate a targeted subfertility treatment.

Objectives

To evaluate the effectiveness and safety of metabolomic assessment of oocyte quality, embryo viability, and endometrial receptivity for improving live birth or ongoing pregnancy rates in women undergoing ART, compared to conventional methods of assessment.

Search methods

We searched the Cochrane Gynaecology and Fertility Group Trials Register, CENTRAL, MEDLINE, Embase, CINAHL and two trial registers (Feburary 2018). We also examined the reference lists of primary studies and review articles, citation lists of relevant publications, and abstracts of major scientific meetings.

Selection criteria

Randomised controlled trials (RCTs) on metabolomic assessment of oocyte quality, embryo viability, and endometrial receptivity in women undergoing ART.

Data collection and analysis

Pairs of review authors independently assessed trial eligibility and risk of bias, and extracted the data. The primary outcomes were rates of live birth or ongoing pregnancy (composite outcome) and miscarriage. Secondary outcomes were clinical pregnancy, multiple and ectopic pregnancy, cycle cancellation, and foetal abnormalities. We combined data to calculate odds ratios (ORs) for dichotomous data and 95% confidence intervals (CIs). Statistical heterogeneity was assessed using the I² statistic. We assessed the overall quality of the evidence for the main comparisons using GRADE methods.

Main results

We included four trials with a total of 924 women, with a mean age of 33 years. All assessed the role of metabolomic investigation of embryo viability. We found no RCTs that addressed the metabolomic assessment of oocyte quality or endometrial receptivity.

We found low‐quality evidence of little or no difference between metabolomic and non‐metabolomic assessment of embryos for rates of live birth or ongoing pregnancy (OR 1.02, 95% CI 0.77 to 1.35, I² = 0%; four RCTs; N = 924), live birth alone (OR 0.99, 95% CI 0.69 to 1.44, I² = 0%; three RCTs; N = 597), or miscarriage (OR 1.18, 95% CI 0.77 to 1.82; I² = 0%; three RCTs; N = 869). A sensitivity analysis excluding studies at high risk of bias did not change the interpretation of the results for live birth or ongoing pregnancy (OR 0.90, 95% CI 0.66 to 1.25, I² = 0%; two RCTs; N = 744). Our findings suggested that if the rate of live birth or ongoing pregnancy was 36% in the non‐metabolomic group, it would be between 32% and 45% with the use of metabolomics.

We found low‐quality evidence of little or no difference between groups in rates of clinical pregnancy (OR 1.11, 95% CI 0.85 to 1.45; I²= 44%; four trials; N = 924) or multiple pregnancy (OR 1.50, 95% CI 0.70 to 3.19; I² = 0%; two RCTs, N = 180). Rates of cycle cancellation were higher in the metabolomics group (OR 1.78, 95% CI 1.18 to 2.69; I² = 51%; two RCTs; N = 744, low quality evidence). There was very low‐quality evidence of little or no difference between groups in rates of ectopic pregnancy rates (OR 3.00, 95% CI 0.12 to 74.07; one RCT; N = 417), and foetal abnormality (no events; one RCT; N = 125). Data were lacking on other adverse effects. A sensitivity analysis excluding studies at high risk of bias did not change the interpretation of the results for clinical pregnancy (OR 1.03, 95% CI 0.76 to 1.38; I² = 40%; two RCTs; N = 744).

The overall quality of the evidence ranged from very low to low. Limitations included serious risk of bias (associated with poor reporting of methods, attrition bias, selective reporting, and other biases), imprecision, and inconsistency across trials.

Authors' conclusions

According to current trials in women undergoing ART, there is no evidence to show that metabolomic assessment of embryos before implantation has any meaningful effect on rates of live birth, ongoing pregnancy, miscarriage, multiple pregnancy, ectopic pregnancy or foetal abnormalities. The existing evidence varied from very low to low‐quality. Data on other adverse events were sparse, so we could not reach conclusions on these. At the moment, there is no evidence to support or refute the use of this technique for subfertile women undergoing ART. Robust evidence is needed from further RCTs, which study the effects on live birth and miscarriage rates for the metabolomic assessment of embryo viability. Well designed and executed trials are also needed to study the effects on oocyte quality and endometrial receptivity, since none are currently available.

PICOs

Population
Intervention
Comparison
Outcome

The PICO model is widely used and taught in evidence-based health care as a strategy for formulating questions and search strategies and for characterizing clinical studies or meta-analyses. PICO stands for four different potential components of a clinical question: Patient, Population or Problem; Intervention; Comparison; Outcome.

See more on using PICO in the Cochrane Handbook.

Metabolomics for improving pregnancy outcomes

Review question

Cochrane researchers reviewed the evidence about the effectiveness of metabolomics as an evaluation tool to improve the rates of ongoing pregnancy, live birth, and miscarriage in women who were undergoing assisted reproductive technology (ART).

Background

Metabolomics is the scientific study of the chemical 'fingerprints' that biological cells, tissues, or organs produce after various cellular processes. They have been proposed as a powerful non‐traumatic method to assess the quality of oocytes, viability of embryos, and receptivity of the endometrium in subfertile women undergoing ART. The final aim of their use is to overcome the high incidence of multiple births and to enhance the performance of ART. However, evidence on their use remains contradictory. Therefore, it was important to evaluate the current evidence on the effectiveness of metabolomics versus conventional techniques (such as the assessment by morphology only) in providing sufficient information on the adequacy of the physiology and function of embryos, oocytes and endometrium, to facilitate targeted subfertility treatments.

Study characteristics

We found four randomised controlled trials, with a total of 924 women, that compared metabolomic profile assessment with morphology assessment of embryos. The women were an average age of 33 years old. All studies were conducted between 2011 and 2013; length of follow‐up was not specified in any of them. The evidence is current to 26 Feburary 2018.

Study funding sources

One study was supported by an unconditional grant from a biotechnology company (Molecular Biometrics Inc.). The very low conditional superiority for the primary outcome and premature termination of the trial were potentially associated with the funder's interest in the results. One study received funding from a national health organisation, but the equipment was provided by Molecular Biometrics Inc., one was self‐funded, while the source of funding was not stated in the fourth study.

Key results

We found low‐quality evidence of no meaningful difference between the intervention and control groups in rates of live birth, ongoing pregnancy, miscarriage, or clinical pregnancy, and multiple pregnancy. We found very low‐quality evidence of no meaningful difference between the groups for ectopic pregnancy, and low‐quality evidence that cancellation rates were higher in the intervention group. Our findings suggest that if the rate of live birth or ongoing pregnancy was 36% in the non‐metabolomic group, it would be between 32% and 45% with the use of metabolomics. Data were lacking on other adverse effects. No properly designed studies reported metabolomic assessment of oocyte quality or endometrium receptivity.

Quality of evidence

The overall quality of evidence ranged from low to very low. Limitations included serious risk of bias (associated with poor reporting of methods, attrition bias, selective reporting and other bias), imprecision, and inconsistency across trials.