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A framework for the clinical implementation of optical genome mapping in hematologic malignancies.

Brynn LevyRashmi Kanagal-ShamanaNikhil S SahajpalKornelia NevelingKatrina RackBarbara DewaeleDaniel Olde WeghuisMarian Stevens-KroefAnna PuiggrosMar MalloBenjamin CliffordTuomo MantereAlexander HoischenBlanca EspinetRavindra KolheFrancesc SoléGordana RacaAdam C Smith
Published in: American journal of hematology (2024)
Optical Genome Mapping (OGM) is rapidly emerging as an exciting cytogenomic technology both for research and clinical purposes. In the last 2 years alone, multiple studies have demonstrated that OGM not only matches the diagnostic scope of conventional standard of care cytogenomic clinical testing but it also adds significant new information in certain cases. Since OGM consolidates the diagnostic benefits of multiple costly and laborious tests (e.g., karyotyping, fluorescence in situ hybridization, and chromosomal microarrays) in a single cost-effective assay, many clinical laboratories have started to consider utilizing OGM. In 2021, an international working group of early adopters of OGM who are experienced with routine clinical cytogenomic testing in patients with hematological neoplasms formed a consortium (International Consortium for OGM in Hematologic Malignancies, henceforth "the Consortium") to create a consensus framework for implementation of OGM in a clinical setting. The focus of the Consortium is to provide guidance for laboratories implementing OGM in three specific areas: validation, quality control and analysis and interpretation of variants. Since OGM is a complex technology with many variables, we felt that by consolidating our collective experience, we could provide a practical and useful tool for uniform implementation of OGM in hematologic malignancies with the ultimate goal of achieving globally accepted standards.
Keyphrases
  • healthcare
  • primary care
  • high resolution
  • quality improvement
  • mass spectrometry
  • palliative care
  • copy number
  • high throughput
  • chronic pain
  • high density
  • quantum dots
  • data analysis