Name
Title | ||
|---|---|---|
Assessing the Validity of a a priori Patient-Trial Generalizability Score using Real-world Data from a Large Clinical Data Research Network - A Colorectal Cancer Clinical Trial Case Study. |
Abstract | ||
|---|---|---|
Existing trials had not taken enough consideration of their population representativeness, which can lower the effectiveness when the treatment is applied in real-world clinical practice. We analyzed the eligibility criteria of Bevacizumab colorectal cancer treatment trials, assessed their a priori generalizability, and examined how it affects patient outcomes when applied in real-world clinical settings. To do so, we extracted patient-level data from a large collection of electronic health records (EHRs) from the OneFlorida consortium. We built a zero-inflated negative binomial model using a composite patient-trial generalizability (cPTG) score to predict patients' clinical outcomes (i.e., number of serious adverse events, [SAEs]). Our study results provide a body of evidence that 1) the cPTG scores can predict patient outcomes; and 2) patients who are more similar to the study population in the trials that were used to develop the treatment will have a significantly lower possibility to experience serious adverse events. |
Year | Venue | DocType |
|---|---|---|
2019 | AMIA | Conference |
Volume | ISSN | Citations |
2019 | 1942-597X | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Qian | 1 | 0 | 0.34 |
| Zhe He | 2 | 63 | 19.17 |
| Yi Guo | 3 | 12 | 10.16 |
| Zhang Hansi | 4 | 0 | 0.34 |
| Thomas J. George | 5 | 5 | 2.55 |
| William R. Hogan | 6 | 294 | 53.52 |
| Neil Charness | 7 | 191 | 29.98 |
| Jiang Bian | 8 | 150 | 43.09 |