Automated Author ProfileMasters, Elizabeth T.
Masters, Elizabeth T.
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: 0.6 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Supplementary Table 1. 1L treatments received by treatment class (N=501) Supplementary Table 2. Reasons for end of follow-up for patients who did not receive 2L treatment Supplementary Table 3. Subgroup analysis of median OS (N=501) Supplementary Table 4. Adjusted cox regression analysis of treatment outcomes for 1L treatment groups
Background We report real-world treatment patterns and outcomes in patients with PD-L1+ NSCLC. Methods This retrospective, observational study using the ConcertAI Oncology Dataset, included patients with PD-L1+ (≥1% expression) metastatic NSCLC who began first-line (1L) treatment between 2016-2019. Treatment outcomes were assessed by treatment class (immune checkpoint inhibitor [ICI] monotherapy, ICI combinations, or chemotherapy). Results In total, 128 (25.5%), 237 (47.3%) and 136 patients (27.1%) received 1L chemotherapy, 1L ICI monotherapy, and 1L ICI combinations, respectively. ICI combinations and monotherapy had improved clinical outcomes vs chemotherapy. Adjusted analyses showed no significant difference in outcome between ICI monotherapy and ICI combinations. Conclusion ICI-based treatments are being increasingly adopted into clinical practice and were associated with better outcomes vs chemotherapy.
Authors
- Future Science Group, Figshare ;
- Zhang, Xinke ;
- DeClue, Richard W. ;
- Herms, Lisa ;
- Yang, Mo ;
- Pawar, Vivek ;
- Masters, Elizabeth T. ;
- Ruisi, Mary ;
- Chin, Kevin ;
- Velcheti, Vamsidhar
Supplementary Table 1. 1L treatments received by treatment class (N=501) Supplementary Table 2. Reasons for end of follow-up for patients who did not receive 2L treatment Supplementary Table 3. Subgroup analysis of median OS (N=501) Supplementary Table 4. Adjusted cox regression analysis of treatment outcomes for 1L treatment groups
Background We report real-world treatment patterns and outcomes in patients with PD-L1+ NSCLC. Methods This retrospective, observational study using the ConcertAI Oncology Dataset, included patients with PD-L1+ (≥1% expression) metastatic NSCLC who began first-line (1L) treatment between 2016-2019. Treatment outcomes were assessed by treatment class (immune checkpoint inhibitor [ICI] monotherapy, ICI combinations, or chemotherapy). Results In total, 128 (25.5%), 237 (47.3%) and 136 patients (27.1%) received 1L chemotherapy, 1L ICI monotherapy, and 1L ICI combinations, respectively. ICI combinations and monotherapy had improved clinical outcomes vs chemotherapy. Adjusted analyses showed no significant difference in outcome between ICI monotherapy and ICI combinations. Conclusion ICI-based treatments are being increasingly adopted into clinical practice and were associated with better outcomes vs chemotherapy.
Authors
- Future Science Group, Figshare ;
- Zhang, Xinke ;
- DeClue, Richard W. ;
- Herms, Lisa ;
- Yang, Mo ;
- Pawar, Vivek ;
- Masters, Elizabeth T. ;
- Ruisi, Mary ;
- Chin, Kevin ;
- Velcheti, Vamsidhar