By detecting cancer early, patients may have access to preventative measures and proactive treatment. QIAGEN Digital Insights is improving hereditary cancer risk detection.
Testing for hereditary cancers can detect specific, heritable, disease-related gene mutations that may increase the risk of certain cancers allowing an in-depth cancer risk assessment for each patient.
The critical goal is to detect cancer early and to maximize health outcomes for patients. Patient-tailored screening programs, preventive measures and proactive treatment are possible for patients of a high-risk group. Early diagnosis can mean a better overall prognosis through a choice of surgical and non-surgical treatment options.
A new reality is emerging in which genetic testing is transforming our understanding and management of hereditary diseases. But before genetic testing becomes a routine part of clinical care for every patient, we must first address the complexity, cost, and consistency of NGS test interpretation.
In our latest eBook, we explore 3 trends that will change how NGS tests for inherited disorders are analyzed and interpreted in the future.
Multi-gene testing for hereditary cancers is complicated. While the use of larger panels has been shown to improve diagnostic yield and increase the opportunity for cancer prevention, it also increases the rate of uncovering variants of unknown significance (VUS) and places tremendous pressure on downstream data analysis and interpretation.
One of the greatest challenges that arises from multi-gene panel testing in hereditary cancer is that in some cases, additional information may be revealed that clinicians are not looking for specifically. These are known as incidental findings (IFs).
To keep pace with the latest findings emerging from thousands of publications daily, clinical testing labs are turning to automation solutions for variant assessment, interpretation, and reporting. But how accurate are automated pathogenicity and actionability classifications? In a recent study, investigators compared the concordance of software-computed ACMG/AMP classifications to ENIGMA human-derived classifications for 6135 BRCA variants. Results showed that the software-computed classifications were 99.6% concordant with the human-derived classifications with respect to clinical actionability.
Clinical labs looking to develop or install NGS testing in-house today face a number of challenges. Among the greatest obstacles cited is the complexity of interpretation and the challenge of providing meaningful reporting to clinicians. QCI Interpret empowers diagnostic labs to overcome these challenges by simplifying how labs report on their NGS tests.
QCI Interpret generates high-quality clinical reports with a clear overview of test results. Reports can be branded and styled to match your lab’s specifications and include a first-page variant summary table, individual variant interpretations based on ACMG/AMP guidelines, including basic information of variant allele frequencies in reference populations and in silico predictions, potential personalized treatment
The largest, manually curated resource for finding disease-causing mutations
Scalable, cloud-based service for NGS secondary analysis
Clinical decision support software for NGS variant interpretation and reporting
Learn more about QIAGEN’s QIAseq Custom Panels.