1. |
- Sherratt, K., et al.
(author)
-
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations
- 2023
-
In: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 12
-
Journal article (peer-reviewed)abstract
- Methods: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1–4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models’ predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models’ forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models’ past predictive performance.Results: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models’ forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models’ forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models’ forecasts of deaths (N=763 predictions from 20 models). Across a 1–4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models.Conclusions: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks.
|
|
2. |
|
|
3. |
|
|
4. |
|
|
5. |
|
|
6. |
- Faraci, M., et al.
(author)
-
Gonadal Function after Busulfan Compared with Treosulfan in Children and Adolescents Undergoing Allogeneic Hematopoietic Stem Cell Transplant
- 2019
-
In: Biology of Blood and Marrow Transplantation. - : Elsevier BV. - 1083-8791. ; 25:9, s. 1786-1791
-
Journal article (peer-reviewed)abstract
- Gonadal impairment is an important late effect with a significant impact on quality of life of transplanted patients. The aim of this study was to compare gonadal function after busulfan (Bu) or treosulfan (Treo) conditioning regimens in pre- and postpubertal children. This retrospective, multicenter study included children transplanted in pediatric European Society for Blood and Marrow Transplantation (EBMT) centers between 1992 and 2012 who did not receive gonadotoxic chemoradiotherapy before the transplant. We evaluated 137 patients transplanted in 25 pediatric EBMT centers. Median age at transplant was 11.04 years (range, 5 to 18); 89 patients were boys and 48 girls. Eighty-nine patients were prepubertal at transplant and 48 postpubertal. One hundred eighteen children received Bu and 19 Treo. A higher proportion of girls treated with Treo in the prepubertal stage reached spontaneous puberty compared with those treated with Bu (P = .02). Spontaneous menarche was more frequent after Treo than after Bu (P < .001). Postpubertal boys and girls treated with Treo had significantly lower luteinizing hormone levels (P = .03 and P = .04, respectively) compared with the Bu group. Frequency of gonadal damage associated with Treo was significantly lower than that observed after Bu. These results need to be confirmed in a larger population. © 2019
|
|
7. |
- Munshi, Pashna N., et al.
(author)
-
American Society of Transplantation and Cellular Therapy, Center of International Blood and Marrow Transplant Research, and European Society for Blood and Marrow Transplantation Clinical Practice Recommendations for Transplantation and Cellular Therapies in Mantle Cell Lymphoma
- 2021
-
In: Transplantation and cellular therapy. - : Elsevier BV. - 2666-6367. ; 27:9, s. 720-728
-
Journal article (peer-reviewed)abstract
- Autologous (auto-) and allogeneic (allo-) hematopoietic cell transplantation (HCT) are accepted treatment modalities in contemporary treatment algorithms for mantle cell lymphoma (MCL). Chimeric antigen receptor (CAR) T cell therapy recently received approval for MCL; however, its exact place and sequence in relation to HCT remain unclear. The American Society of Transplantation and Cellular Therapy, Center of International Blood and Marrow Transplant Research, and the European Society for Blood and Marrow Transplantation jointly convened an expert panel to formulate consensus recommendations for role, timing, and sequencing of auto-HCT, allo-HCT, and CAR T cell therapy for patients with newly diagnosed and relapsed/refractory (R/R) MCL. The RAND-modified Delphi method was used to generate consensus statements. Seventeen consensus statements were generated, with a few key statements as follows: in the first line setting, auto-HCT consolidation represents standard of care in eligible patients, whereas there is no clear role of allo-HCT or CAR T cell therapy outside of clinical trials. In the R/R setting, the preferential option is CAR T cell therapy, especially in patients with MCL failing or intolerant to at least one Bruton's tyrosine kinase inhibitor, while allo-HCT is recommended if CAR T cell therapy fails or is infeasible. Several recommendations were based on expert opinion, where the panel developed consensus statements for important real-world clinical scenarios to guide clinical practice. In the absence of contemporary evidence-based data, the panel found RAND-modified Delphi methodology effective in providing a formal framework for developing consensus recommendations for the timing and sequence of cellular therapies for MCL.
|
|
8. |
- Munshi, Pashna N., et al.
(author)
-
ASTCT, CIBMTR, and EBMT clinical practice recommendations for transplant and cellular therapies in mantle cell lymphoma
- 2021
-
In: Bone Marrow Transplantation. - : Springer Science and Business Media LLC. - 0268-3369 .- 1476-5365. ; 56:12, s. 2911-2921
-
Journal article (peer-reviewed)abstract
- Autologous (auto-) or allogeneic (allo-) hematopoietic cell transplantation (HCT) are accepted treatment modalities for mantle cell lymphoma (MCL). Recently, chimeric antigen receptor (CAR) T-cell therapy received approval for MCL; however, its exact place and sequence in relation to HCT is unclear. The ASTCT, CIBMTR, and the EBMT, jointly convened an expert panel to formulate consensus recommendations for role, timing, and sequencing of auto-, allo-HCT, and CAR T-cell therapy for patients with newly diagnosed and relapsed/refractory (R/R) MCL. The RAND-modified Delphi method was used to generate consensus statements. Seventeen consensus statements were generated; in the first-line setting auto-HCT consolidation represents standard-of-care in eligible patients, whereas there is no clear role of allo-HCT or CAR T-cell therapy, outside of a clinical trial. In the R/R setting, the preferential option is CAR T-cell therapy especially in MCL failing or intolerant to at least one Bruton’s tyrosine kinase inhibitor, while allo-HCT is recommended if CAR T-cell therapy has failed or is not feasible. In the absence of contemporary evidence-based data, the panel found RAND-modified Delphi methodology effective in providing a formal framework for developing consensus recommendations for the timing and sequence of cellular therapies for MCL.
|
|
9. |
|
|
10. |
|
|
11. |
|
|
12. |
|
|
13. |
- Herbst, SA, et al.
(author)
-
Proteogenomics refines the molecular classification of chronic lymphocytic leukemia
- 2022
-
In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 13:1, s. 6226-
-
Journal article (peer-reviewed)abstract
- Cancer heterogeneity at the proteome level may explain differences in therapy response and prognosis beyond the currently established genomic and transcriptomic-based diagnostics. The relevance of proteomics for disease classifications remains to be established in clinically heterogeneous cancer entities such as chronic lymphocytic leukemia (CLL). Here, we characterize the proteome and transcriptome alongside genetic and ex-vivo drug response profiling in a clinically annotated CLL discovery cohort (n = 68). Unsupervised clustering of the proteome data reveals six subgroups. Five of these proteomic groups are associated with genetic features, while one group is only detectable at the proteome level. This new group is characterized by accelerated disease progression, high spliceosomal protein abundances associated with aberrant splicing, and low B cell receptor signaling protein abundances (ASB-CLL). Classifiers developed to identify ASB-CLL based on its characteristic proteome or splicing signature in two independent cohorts (n = 165, n = 169) confirm that ASB-CLL comprises about 20% of CLL patients. The inferior overall survival in ASB-CLL is also independent of both TP53- and IGHV mutation status. Our multi-omics analysis refines the classification of CLL and highlights the potential of proteomics to improve cancer patient stratification beyond genetic and transcriptomic profiling.
|
|
14. |
|
|
15. |
|
|
16. |
|
|
17. |
|
|
18. |
|
|
19. |
|
|
20. |
|
|
21. |
|
|
22. |
|
|