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- Moshontz, Hannah, et al.
(author)
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The Psychological Science Accelerator: Advancing Psychology Through a Distributed Collaborative Network
- 2018
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In: Advances in Methods and Practices in Psychological Science. - : SAGE Publications. - 2515-2459 .- 2515-2467. ; 1:4, s. 501-515
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Journal article (peer-reviewed)abstract
- Concerns about the veracity of psychological research have been growing. Many findings in psychological science are based on studies with insufficient statistical power and nonrepresentative samples, or may otherwise be limited to specific, ungeneralizable settings or populations. Crowdsourced research, a type of large-scale collaboration in which one or more research projects are conducted across multiple lab sites, offers a pragmatic solution to these and other current methodological challenges. The Psychological Science Accelerator (PSA) is a distributed network of laboratories designed to enable and support crowdsourced research projects. These projects can focus on novel research questions or replicate prior research in large, diverse samples. The PSA’s mission is to accelerate the accumulation of reliable and generalizable evidence in psychological science. Here, we describe the background, structure, principles, procedures, benefits, and challenges of the PSA. In contrast to other crowdsourced research networks, the PSA is ongoing (as opposed to time limited), efficient (in that structures and principles are reused for different projects), decentralized, diverse (in both subjects and researchers), and inclusive (of proposals, contributions, and other relevant input from anyone inside or outside the network). The PSA and other approaches to crowdsourced psychological science will advance understanding of mental processes and behaviors by enabling rigorous research and systematic examination of its generalizability.
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| 2. |
- Enshaei, Amir, et al.
(author)
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A validated novel continuous prognostic index to deliver stratified medicine in pediatric acute lymphoblastic leukemia
- 2020
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In: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 135:17, s. 1438-1446
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Journal article (peer-reviewed)abstract
- Risk stratification is essential for the delivery of optimal treatment in childhood acute lymphoblastic leukemia. However, current risk stratification algorithms dichotomize variables and apply risk factors independently, which may incorrectly assume identical associations across biologically heterogeneous subsets and reduce statistical power. Accordingly, we developed and validated a prognostic index (PIUKALL) that integrates multiple risk factors and uses continuous data. We created discovery (n = 2405) and validation (n = 2313) cohorts using data from 4 recent trials (UKALL2003, COALL-03, DCOG-ALL10, and NOPHO-ALL2008). Using the discovery cohort, multivariate Cox regression modeling defined a minimal model including white cell count at diagnosis, pretreatment cytogenetics, and end-of-induction minimal residual disease. Using this model, we defined PIUKALL as a continuous variable that assigns personalized risk scores. PIUKALL correlated with risk of relapse and was validated in an independent cohort. Using PIUKALL to risk stratify patients improved the concordance index for all end points compared with traditional algorithms. We used PIUKALL to define 4 clinically relevant risk groups that had differential relapse rates at 5 years and were similar between the 2 cohorts (discovery: low, 3% [95% confidence interval (CI), 2%-4%]; standard, 8% [95% CI, 6%-10%]; intermediate, 17% [95% CI, 14%-21%]; and high, 48% [95% CI, 36%-60%; validation: low, 4% [95% CI, 3%-6%]; standard, 9% [95% CI, 6%-12%]; intermediate, 17% [95% CI, 14%-21%]; and high, 35% [95% CI, 24%-48%]). Analysis of the area under the curve confirmed the PIUKALL groups were significantly better at predicting outcome than algorithms employed in each trial. PIUKALL provides an accurate method for predicting outcome and more flexible method for defining risk groups in future studies.
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| 3. |
- Ostergaard, Anna, et al.
(author)
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The Prognostic Effect of IKZF1 Deletions in ETV6:: RUNX1 and High Hyperdiploid Childhood Acute Lymphoblastic Leukemia
- 2023
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In: HemaSphere. - 2572-9241. ; 7:5, s. 875-875
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Journal article (peer-reviewed)abstract
- IKZF1 deletions are an established prognostic factor in childhood acute lymphoblastic leukemia (ALL). However, their relevance in patients with good risk genetics, namely ETV6::RUNX1 and high hyperdiploid (HeH), ALL remains unclear. We assessed the prognostic impact of IKZF1 deletions in 939 ETV6::RUNX1 and 968 HeH ALL patients by evaluating data from 16 trials from 9 study groups. Only 3% of ETV6::RUNX1 cases (n = 26) were IKZF1-deleted; this adversely affected survival combining all trials (5-year event-free survival [EFS], 79% versus 92%; P = 0.02). No relapses occurred among the 14 patients with an IKZF1 deletion treated on a minimal residual disease (MRD)-guided protocols. Nine percent of HeH cases (n = 85) had an IKZF1 deletion; this adversely affected survival in all trials (5-year EFS, 76% versus 89%; P = 0.006) and in MRD-guided protocols (73% versus 88%; P = 0.004). HeH cases with an IKZF1 deletion had significantly higher end of induction MRD values (P = 0.03). Multivariate Cox regression showed that IKZF1 deletions negatively affected survival independent of sex, age, and white blood cell count at diagnosis in HeH ALL (hazard ratio of relapse rate [95% confidence interval]: 2.48 [1.32-4.66]). There was no evidence to suggest that IKZF1 deletions affected outcome in the small number of ETV6::RUNX1 cases in MRD-guided protocols but that they are related to higher MRD values, higher relapse, and lower survival rates in HeH ALL. Future trials are needed to study whether stratifying by MRD is adequate for HeH patients or additional risk stratification is necessary.
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