Evidence map›Paper›PMID 26100406›Full record

Trial reportBMC medical genomics2015

Randomized comparison of next-generation sequencing and array comparative genomic hybridization for preimplantation genetic screening: a pilot study.

Zhihong Yang, James Lin, John Zhang, Wai Ieng Fong, Pei Li, Rong Zhao, Xiaohong Liu, William Podevin, Yanping Kuang, Jiaen Liu

Open access · goldAbstract readComparative StudyRandomized Controlled Trial
In one paragraph

Trial report in BMC medical genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
16.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Zhihong YangZytoGen Global Genetics Institute, Timonium, MD, USA. sunmiy31@hotmail.com.
James LinReproductive Fertility Center, Irvine, CA, USA. drlin@reproductivefertilitycenter.com.
John ZhangNew Hope Fertility Center, New York, NY, USA. johnzhang98@yahoo.com.
Wai Ieng FongHospital Conde S. Januário, Macau, P. R. China. fongwi@hotmail.com.
Pei LiJia En De Yun Hospital, Beijing, P. R. China. yucenxlpxw@126.com.
Rong ZhaoJia En De Yun Hospital, Beijing, P. R. China. zz6667@vip.sina.com.
Xiaohong LiuJia En De Yun Hospital, Beijing, P. R. China. liujiaen@126.com.
William PodevinPacific Reproductive Center, Torrance, CA, USA. williampodevin@yahoo.com.
Yanping KuangNinth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, P. R. China. kuangyanp@126.com.
Jiaen LiuJia En De Yun Hospital, Beijing, P. R. China. jiaenliu@hotmail.com.
Hospital Conde S. Januário · CNNew Hope Fertility Center · USPacific Fertility Center · USShanghai Ninth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent advances in next-generation sequencing (NGS) have provided new methods for preimplantation genetic screening (PGS) of human embryos from in vitro fertilization (IVF) cycles. However, there is still limited information about clinical applications of NGS in IVF and PGS (IVF-PGS) treatments. The present study aimed to investigate the effects of NGS screening on clinical pregnancy and implantation outcomes for PGS patients in comparison to array comparative genomic hybridization (aCGH) screening.

methodsThis study was performed in two phases. Phase I study evaluated the accuracy of NGS for aneuploidy screening in comparison to aCGH. Whole-genome amplification (WGA) products (n = 164) derived from previous IVF-PGS cycles (n = 38) were retrospectively analyzed with NGS. The NGS results were then compared with those of aCGH. Phase II study further compared clinical pregnancy and implantation outcomes between NGS and aCGH for IVF-PGS patients. A total of 172 patients at mean age 35.2 ± 3.5 years were randomized into two groups: 1) NGS (Group A): patients (n = 86) had embryos screened with NGS and 2) aCGH (Group B): patients (n = 86) had embryos screened with aCGH. For both groups, blastocysts were vitrified after trophectoderm biopsy. One to two euploid blastocysts were thawed and transferred to individual patients primarily based on the PGS results. Ongoing pregnancy and implantation rates were compared between the two study groups.

resultsNGS detected all types of aneuploidies of human blastocysts accurately and provided a 100 % 24-chromosome diagnosis consistency with the highly validated aCGH method. Moreover, NGS screening identified euploid blastocysts for transfer and resulted in similarly high ongoing pregnancy rates for PGS patients compared to aCGH screening (74.7 % vs. 69.2 %, respectively, p >0.05). The observed implantation rates were also comparable between the NGS and aCGH groups (70.5 % vs. 66.2 %, respectively, p >0.05).

conclusionsWhile NGS screening has been recently introduced to assist IVF patients, this is the first randomized clinical study on the efficiency of NGS for preimplantation genetic screening in comparison to aCGH. With the observed high accuracy of 24-chromosome diagnosis and the resulting high ongoing pregnancy and implantation rates, NGS has demonstrated an efficient, robust high-throughput technology for PGS.

Indexed as

AneuploidyComparative Genomic HybridizationHigh-Throughput Nucleotide SequencingOligonucleotide Array Sequence AnalysisAdultEmbryo ImplantationFemaleFertilization in VitroGenetic TestingHumansPilot ProjectsPregnancyPreimplantation DiagnosisRetrospective Studies

Identifiers

PMID26100406
PMCPMC4477308
OpenAlexW1578004862

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.