Dataset Information

Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data.

ABSTRACT: Each year diagnostic laboratories in the Netherlands profile thousands of individuals for heritable disease using next-generation sequencing (NGS). This requires pathogenicity classification of millions of DNA variants on the standard 5-tier scale. To reduce time spent on data interpretation and increase data quality and reliability, the nine Dutch labs decided to publicly share their classifications. Variant classifications of nearly 100,000 unique variants were catalogued and compared in a centralized MOLGENIS database. Variants classified by more than one center were labeled as "consensus" when classifications agreed, and shared internationally with LOVD and ClinVar. When classifications opposed (LB/B vs. LP/P), they were labeled "conflicting", while other nonconsensus observations were labeled "no consensus". We assessed our classifications using the InterVar software to compare to ACMG 2015 guidelines, showing 99.7% overall consistency with only 0.3% discrepancies. Differences in classifications between Dutch labs or between Dutch labs and ACMG were mainly present in genes with low penetrance or for late onset disorders and highlight limitations of the current 5-tier classification system. The data sharing boosted the quality of DNA diagnostics in Dutch labs, an initiative we hope will be followed internationally. Recently, a positive match with a case from outside our consortium resulted in a more definite disease diagnosis.

SUBMITTER: Fokkema IFAC

PROVIDER: S-EPMC6900155 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data.

Fokkema Ivo F A C IFAC van der Velde Kasper J KJ Slofstra Mariska K MK Ruivenkamp Claudia A L CAL Vogel Maartje J MJ Pfundt Rolph R Blok Marinus J MJ Lekanne Deprez Ronald H RH Waisfisz Quinten Q Abbott Kristin M KM Sinke Richard J RJ Rahman Rubayte R Nijman Isaäc J IJ de Koning Bart B Thijs Gert G Wieskamp Nienke N Moritz Ruben J G RJG Charbon Bart B Saris Jasper J JJ den Dunnen Johan T JT Laros Jeroen F J JFJ Swertz Morris A MA van Gijn Marielle E ME

Human mutation 20190903 12

Each year diagnostic laboratories in the Netherlands profile thousands of individuals for heritable disease using next-generation sequencing (NGS). This requires pathogenicity classification of millions of DNA variants on the standard 5-tier scale. To reduce time spent on data interpretation and increase data quality and reliability, the nine Dutch labs decided to publicly share their classifications. Variant classifications of nearly 100,000 unique variants were catalogued and compared in a cen ...[more]

PMID: 31433103

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Project description:Background:Practices in somatic variant interpretation and classification vary between Canadian clinical molecular diagnostic laboratories, and understanding of current practices and perspectives is limited. To define gaps and future directions, including consensus guideline development, the Somatic Curation and Interpretation Across Laboratories (social) project examined the present state of somatic variant interpretation in Canadian molecular laboratories, including testing volumes and methods, data sources and evidence criteria, and application of published classification guidelines. Methods:Individuals who perform somatic variant interpretation in Canadian centres were invited to participate in an online survey. Invitees included laboratory directors (certified as Fellows of the Canadian College of Medical Geneticists or the American College of Medical Geneticists), md or md and phd molecular pathologists, and other phd experts, including phd specialists in variant annotation or bioinformatics. Current testing methods, volumes, and platforms in next-generation sequencing, use of variant annotation resources and evidence criteria, and preference for variant classification schemes were evaluated. Results:Responses were received from 37 participants in 8 provinces. A somatic variant classification scheme jointly supported by the Association for Molecular Pathology (amp), the American Society of Clinical Oncology (asco), and the College of American Pathologists (cap) was used by 47% of respondents; an alternative guideline or a combination of published guidelines was used by 35% of respondents. The remaining 18% did not use a published scheme. Only 41% of respondents used a published scheme without alteration. Although all respondents indicated that there is a need for Canadian laboratories to adopt a somatic variant classification guideline, only 38% of respondents felt that it should be mandatory to adopt the amp/asco/cap-endorsed guideline. Conclusions:Data from the social project identified high variability in current practice, yet strong support for standardization of solid-tumour somatic variant interpretation across Canadian institutions. Aligning classification methods will reduce variation in cross-institutional classification and reporting practices, aiding in consistent practice nationwide.

Project description:BackgroundHundreds of thousands of surgical arthroscopy procedures are performed annually in the United States (US) based on MRI findings. There are situations where these MRI findings are equivocal or indeterminate and because of this clinicians commonly perform the arthroscopy in order not to miss pathology. Recently, a less invasive needle arthroscopy system has been introduced that is commonly performed in the physician office setting and that may help improve the accuracy of diagnostic findings. This in turn may prevent unnecessary follow-on arthroscopy procedures from being performed.ObjectiveThe purpose of this analysis is to determine whether the in-office diagnostic needle arthroscopy system can provide cost savings by reducing unnecessary follow on arthroscopy procedures.MethodsData obtained from a recent trial and from a systematic review were used in comparing the accuracy of MRI and VisionScope needle arthroscopy (VSI) with standard arthroscopy (gold standard). The resultant false positive and false negative findings were then used to evaluate the costs of follow-on procedures. These differences were then modeled for the US patient population diagnosed and treated for meniscal knee pathology (most common disorder) to determine if a technology such as VSI could save the US healthcare system money. Data on surgical arthroscopy procedures in the US for meniscal knee pathology were used (calendar year [CY] 2010). The costs of performing diagnostic and surgical arthroscopy procedures (using CY 2013 Medicare reimbursement amounts), costs associated with false negative findings, and the costs for treating associated complications arising from diagnostic and therapeutic arthroscopy procedures were assessed.ResultsIn patients presenting with medial meniscal pathology (International Classification of Diseases, 9th edition, Clinical Modification [ICD9CM] diagnosis 836.0), VSI in place of MRI (standard of care) resulted in a net cost savings to the US system of US$115-US$177 million (CY 2013) (use of systematic review and study data, respectively). In patients presenting with lateral meniscus pathology (ICD9CM 836.1), VSI in place of MRI cost the healthcare system an additional US$14-US$97 million (CY 2013). Overall aggregate savings for meniscal (lateral plus medial) pathology were identified in representative care models along with more appropriate care as fewer patients were exposed to higher risk surgical procedures.ConclusionsSince in-office arthroscopy is significantly more accurate, patients can be treated more appropriately and the US healthcare system can save money, most especially in medial meniscal pathology.

Dataset Information

Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data.

Publications

Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data.

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