Automated Author ProfileG., Azzi
G., Azzi
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Introduction: Tumor-informed minimal residual disease (MRD) monitoring assays based on plasma circulating tumor DNA (ctDNA) are increasingly integrated into the clinical management of patients with cancer. In the post-surgical curative intent setting and as an adjunct to radiographic imaging for response assessment and surveillance, timely identification of MRD may better guide therapeutic decision-making. The increasing clinical adoption of MRD testing, supported by a growing body of evidence demonstrating its potential utility at critical decision points across diverse tumor histology, has brought attention to the variability in the analytical performance of available ctDNA assays. This variability is becoming increasingly appreciated as a key factor influencing clinical performance. Case Presentations: Here we report a case series in breast and rectal cancer involving treatment monitoring with a novel advanced MRD assay, illustrating its ability to identify subclinical metastasis and disease resolution below the validated limit of detection of a commercially available ctDNA assay in these cases.Conclusion: Results aided medical decision-making and underscored the need for highly sensitive assays in MRD detection. The differences in sensitivity, driven primarily by analytical variables, highlight the importance of selecting an assay that is not only analytically robust but also appropriately matched to the patient’s specific clinical context, to help ensure optimal utility and minimize the risk of misinterpretation.
Authors
- karger, figshare admin ;
- G., Azzi ;
- T., Slavin ;
- J., Izaguirre-Carbonell ;
- H.S., Sloane ;
- D.L., Edelstein ;
- C.X., Ma
Introduction: Tumor-informed minimal residual disease (MRD) monitoring assays based on plasma circulating tumor DNA (ctDNA) are increasingly integrated into the clinical management of patients with cancer. In the post-surgical curative intent setting and as an adjunct to radiographic imaging for response assessment and surveillance, timely identification of MRD may better guide therapeutic decision-making. The increasing clinical adoption of MRD testing, supported by a growing body of evidence demonstrating its potential utility at critical decision points across diverse tumor histology, has brought attention to the variability in the analytical performance of available ctDNA assays. This variability is becoming increasingly appreciated as a key factor influencing clinical performance. Case Presentations: Here we report a case series in breast and rectal cancer involving treatment monitoring with a novel advanced MRD assay, illustrating its ability to identify subclinical metastasis and disease resolution below the validated limit of detection of a commercially available ctDNA assay in these cases.Conclusion: Results aided medical decision-making and underscored the need for highly sensitive assays in MRD detection. The differences in sensitivity, driven primarily by analytical variables, highlight the importance of selecting an assay that is not only analytically robust but also appropriately matched to the patient’s specific clinical context, to help ensure optimal utility and minimize the risk of misinterpretation.
Authors
- karger, figshare admin ;
- G., Azzi ;
- T., Slavin ;
- J., Izaguirre-Carbonell ;
- H.S., Sloane ;
- D.L., Edelstein ;
- C.X., Ma