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Does theFMR1 gene affect IVF success?

ABSTRACT: FMR1 CGG trinucleotide repeat expansions are associated with Fragile X syndrome (full mutations) and primary ovarian insufficiency (premutation range); the effect of FMR1 on the success of fertility treatment is unclear. The effect of FMR1 CGG repeat lengths on IVF outcomes after ovarian stimulation was reviewed. PubMed was searched for studies on IVF-related outcomes reported by FMR1 trinucleotide repeat length published between 2002 and December 2017. For women with CGG repeats in the normal (<45 CGG), intermediate range (45-54 CGG), or both, research supports a minimal effect on IVF outcomes, including pregnancy rates; although one study reported lower oocyte yields after IVF stimulation in women with lower CGG repeat lengths and normal ovarian reserve. Meta-analysis revealed no association within subcategories of normal repeat length (<45 CGG) and IVF pregnancy rates (summary OR 1.0, 95% CI 0.87 to 1.15). Premutation carriers (CGG 55-200) may have reduced success with IVF treatment (lower oocyte yield) than women with a normal CGG repeat length or a full mutation, although findings are inconsistent. Direct implications of the repeat length on inheritance and the risk of Fragile X syndrome have been observed. Patients may require clinical and psychological counselling, and further preimplantation genetic testing options should be considered. Thus, there are clinical and psychological counseling implications for patients and potential further patient decisions regarding preimplantation genetic testing options.

SUBMITTER: Pastore LM

PROVIDER: S-EPMC7001757 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Does theFMR1 gene affect IVF success?

Pastore Lisa M LM Christianson Mindy S MS McGuinness Bailey B Vaught Kamaria Cayton KC Maher Jacqueline Y JY Kearns William G WG

Reproductive biomedicine online 20181210 4

FMR1 CGG trinucleotide repeat expansions are associated with Fragile X syndrome (full mutations) and primary ovarian insufficiency (premutation range); the effect of FMR1 on the success of fertility treatment is unclear. The effect of FMR1 CGG repeat lengths on IVF outcomes after ovarian stimulation was reviewed. PubMed was searched for studies on IVF-related outcomes reported by FMR1 trinucleotide repeat length published between 2002 and December 2017. For women with CGG repeats in the normal ( ...[more]

PMID: 30711457

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Project description:Study questionDoes inverse probability weighting (IPW) provide a more valid estimate of the cumulative incidence of live birth after multiple cycles of IVF?Summary answerIPW can provide a more accurate estimate of treatment success for counseling and decision-making regarding IVF.What is known alreadyDifferent approaches have been used to define and calculate IVF success; however, many of these approaches have limitations and potentially violate statistical assumptions. IPW can address potential selection bias that arises when people do not continue IVF treatment after a failed cycle.Study design, size, durationData were derived from a cohort study of women undergoing their first fresh embryo transfer IVF cycle at our institution between 1 January 1995 and 31 December 2014. All autologous cycles (fresh and frozen) were included, up to six total cycles.Participants/materials, setting, methodsWe identified 20 015 women who underwent 47 079 IVF cycles and had 10 031 live births during the study period. The cumulative incidence of live birth was calculated using three approaches. First, we used a standard Kaplan-Meier approach, 'the optimistic approach', censoring women when they dropped out of treatment. Second, we used a 'conservative' Kaplan-Meier approach that assumed women who dropped out of treatment did not achieve a live birth. Finally, we used IPW to calculate the probability of remaining in treatment, while accounting for differences in treatment drop out. IPW up-weights the data of those remaining under observation who resembled the women who dropped out of treatment, thereby decreasing the potential selection bias resulting from loss to follow-up. The IPW was incorporated into a Kaplan-Meier approach.Main results and the role of chanceThe cumulative incidence of live birth was 72.1% (95% CI: 71.0-73.1%) for the optimistic approach, 50.1% (49.4-50.8%) for the conservative approach and 66.8% (65.5-68.1%) for the IPW approach. Among women < 38 years of age, the cumulative incidence of live birth calculated by the IPW was slightly higher than that calculated by the optimistic approach. For women 41-42 years of age, the IPW cumulative incidence of live birth was slightly lower. The IPW was similar to the optimistic approach for the other age groups. The conservative estimate was lowest for all age groups.Limitations, reasons for cautionOnly clinical data recorded by the providers during an IVF cycle were used to generate weights for IPW. Covariates included: age, gravidity and year at the start of the cycle; primary infertility diagnosis; procedure type (i.e. whether a fresh or frozen embryo was transferred); number of mature oocytes retrieved; number of embryos transferred; cycle cancellation; pregnancy loss in the cycle; and insurance status. We were unable to determine exact reasons for treatment drop out (e.g. cessation of IVF treatment, transfer to another institution or spontaneous pregnancy). Our IPW model was moderately predictive based on the c-statistic from the calculation of the denominator of the weight; however, residual selection bias may remain due to the limited range of covariate data.Wider implications of the findingsIPW can be used in a variety of settings to address selection bias introduced by differential loss to follow up or treatment drop out.Study funding/competing interest(s)AMM was supported by National Institutes of Health (NIH) T32 HD052458-Boston University Reproductive, Perinatal and Pediatric Epidemiology Training Program. The authors report no conflicts of interest.Trial registration numberN/A.

Project description:OBJECTIVE:To compare success rates, associated risks and cost-effectiveness between intrauterine insemination (IUI) and in vitro fertilisation (IVF). DESIGN:Retrospective observational study. SETTING:The UK from 2012 to 2016. PARTICIPANTS:Data from Human Fertilisation and Embryology Authority's freedom of information request for 2012-2016 for IVF/ICSI (intracytoplasmic sperm injection)and IUI as practiced in 319 105 IVF/ICSI and 30 669 IUI cycles. Direct-cost calculations for maternal and neonatal expenditure per live birth (LB) was constructed using the cost of multiple birth model, with inflation-adjusted Bank of England index-linked data. A second direct-cost analysis evaluating the incremental cost-effective ratio (ICER) was modelled using the 2016 national mean (baseline) IVF and IUI success rates. OUTCOME MEASURES:LB, risks from IVF and IUI, and costs to gain 1 LB. RESULTS:This largest comprehensive analysis integrating success, risks and costs at a national level shows IUI is safer and more cost-effective than IVF treatment.IVF LB/cycle success was significantly better than IUI at 26.96% versus 11.49% (p<0.001) but the IUI success is much closer to IVF at 2.35:1, than previously considered. IVF remains a significant source of multiple gestation pregnancy (MGP) compared with IUI (RR (Relative Risk): 1.45 (1.31 to 1.60), p<0.001) as was the rate of twins (RR: 1.58, p<0.001).In 2016, IVF maternal and neonatal cost was £115 082 017 compared with £2 940 196 for IUI and this MGP-related perinatal cost is absorbed by the National Health Services. At baseline tariffs and success rates IUI was £42 558 cheaper than IVF to deliver 1LB with enhanced benefits with small improvements in IUI. Reliable levels of IVF-related MGP, OHSS (ovarian hyperstimulation syndrome), fetal reductions and terminations are revealed. CONCLUSION:IUI success rates are much closer to IVF than previously reported, more cost-effective in delivering 1 LB, and associated with lower risk of complications for maternal and neonatal complications. It is prudent to offer IUI before IVF nationally.

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Does theFMR1 gene affect IVF success?

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Does theFMR1 gene affect IVF success?

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