| 1. |
|
|
| 2. |
|
|
| 3. |
|
|
| 4. |
- Williams, R. D., et al.
(författare)
-
Seek COVER: using a disease proxy to rapidly develop and validate a personalized risk calculator for COVID-19 outcomes in an international network
- 2022
-
Ingår i: BMC Medical Research Methodology. - : Springer Science and Business Media LLC. - 1471-2288. ; 22:1
-
Tidskriftsartikel (refereegranskat)abstract
- Background: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient’s risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients. Methods: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date. Results: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69–0.81, COVER-I: 0.73–0.91, and COVER-F: 0.72–0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations. Conclusions: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use. © 2022, The Author(s).
|
|
| 5. |
|
|
| 6. |
- Ghaderi, A, et al.
(författare)
-
ROR1 Is Expressed in Diffuse Large B-Cell Lymphoma (DLBCL) and a Small Molecule Inhibitor of ROR1 (KAN0441571C) Induced Apoptosis of Lymphoma Cells
- 2020
-
Ingår i: Biomedicines. - : MDPI AG. - 2227-9059. ; 8:6
-
Tidskriftsartikel (refereegranskat)abstract
- The receptor tyrosine kinase ROR1 is absent in most normal adult tissues, but overexpressed in several malignancies. In this study, we explored clinical and functional inhibitory aspects of ROR1 in diffuse large B-cell lymphoma (DLBCL). ROR1 expression in tumor cells was more often observed in primary refractory DLBCL, Richter’s syndrome and transformed follicular lymphoma than in relapsed and non-relapsed DLBCL patients (p < 0.001). A survival effect of ROR1 expression was preliminarily observed in relapsed/refractory patients independent of gender and stage but not of age, cell of origin and international prognostic index. A second generation small molecule ROR1 inhibitor (KAN0441571C) induced apoptosis of ROR1+ DLBCL cell lines, similar to venetoclax (BCL-2 inhibitor) but superior to ibrutinib (BTK inhibitor). The combination of KAN0441571C and venetoclax at EC50 concentrations induced almost complete killing of DLBCL cell lines. Apoptosis was accompanied by the downregulation of BCL-2 and MCL-1 and confirmed by the cleavage of PARP and caspases 3, 8, 9. PI3Kδ/AKT/mTOR (non-canonical Wnt pathway) as well as β-catenin and CK1δ (canonical pathway) were inactivated. In zebra fishes transplanted with a ROR1+ DLBCL cell line, KAN0441571C induced a significant tumor reduction. New drugs with mechanisms of action other than those available for DLBCL are warranted. ROR1 inhibitors might represent a novel promising approach.
|
|
| 7. |
|
|
