| 11. |
- Hössjer, Ola, 1964-, et al.
(författare)
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An Information Theoretic Approach to Prevalence Estimation and Missing Data
- 2024
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Ingår i: IEEE Transactions on Information Theory. - 0018-9448 .- 1557-9654. ; 70:5, s. 3567-3582
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Tidskriftsartikel (refereegranskat)abstract
- Many data sources, including tracking social behavior to election polling to testing studies for understanding disease spread, are subject to sampling bias whose implications are not fully yet understood. In this paper we study estimation of a given feature (such as disease, or behavior at social media platforms) from biased samples, treating non-respondent individuals as missing data. Prevalence of the feature among sampled individuals has an upward bias under the assumption of individuals’ willingness to be sampled. This can be viewed as a regression model with symptoms as covariates and the feature as outcome. It is assumed that the outcome is unknown at the time of sampling, and therefore the missingness mechanism only depends on the covariates. We show that data, in spite of this, is missing at random only when the sizes of symptom classes in the population are known; otherwise data is missing not at random. With an information theoretic viewpoint, we show that sampling bias corresponds to external information due to individuals in the population knowing their covariates, and we quantify this external information by active information. The reduction in prevalence, when sampling bias is adjusted for, similarly translates into active information due to bias correction, with opposite sign to active information due to testing bias. We develop unified results that show that prevalence and active information estimates are asymptotically normal under all missing data mechanisms, when testing errors are absent and present respectively. The asymptotic behavior of the estimators is illustrated through simulations.
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| 12. |
- Sandner, Sigrid, et al.
(författare)
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One-month DAPT with ticagrelor and aspirin for patients undergoing coronary artery bypass grafting: rationale and design of the randomised, multicentre, double-blind, placebo-controlled ODIN trial.
- 2024
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Ingår i: EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology. - 1969-6213. ; 20:5
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Tidskriftsartikel (refereegranskat)abstract
- The optimal antiplatelet strategy after coronary artery bypass graft (CABG) surgery in patients with chronic coronary syndromes (CCS) is unclear. Adding the P2Y12 inhibitor, ticagrelor, to low-dose aspirin for 1 year is associated with a reduction in graft failure, particularly saphenous vein grafts, at the expense of an increased risk of clinically important bleeding. As the risk of thrombotic graft failure and ischaemic events is highest early after CABG surgery, a better risk-to-benefit profile may be attained with short-term dual antiplatelet therapy followed by single antiplatelet therapy. The One Month Dual Antiplatelet Therapy With Ticagrelor in Coronary Artery Bypass Graft Patients (ODIN) trial is a prospective, randomised, double-blind, placebo-controlled, international, multicentre study of 700 subjects that will evaluate the effect of short-term dual antiplatelet therapy with ticagrelor plus low-dose aspirin after CABG in patients with CCS. Patients will be randomised 1:1 to ticagrelor 90 mg twice daily or matching placebo, in addition to aspirin 75-150 mg once daily for 1 month; after the first month, antiplatelet therapy will be continued with aspirin alone. The primary endpoint is a hierarchical composite of all-cause death, stroke, myocardial infarction, revascularisation and graft failure at 1 year. The key secondary endpoint is a hierarchical composite of all-cause death, stroke, myocardial infarction, Bleeding Academic Research Consortium (BARC) type 3 bleeding, revascularisation and graft failure at 1 year (net clinical benefit). ODIN will report whether the addition of ticagrelor to low-dose aspirin for 1 month after CABG reduces ischaemic events and provides a net clinical benefit in patients with CCS. (ClinicalTrials.gov: NCT05997693).
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| 13. |
- Van Booven, Derek, et al.
(författare)
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Alcohol use disorder causes global changes in splicing in the human brain
- 2021
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Ingår i: Translational Psychiatry. - : SPRINGERNATURE. - 2158-3188. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- Alcohol use disorder (AUD) is a widespread disease leading to the deterioration of cognitive and other functions. Mechanisms by which alcohol affects the brain are not fully elucidated. Splicing constitutes a nuclear process of RNA maturation, which results in the formation of the transcriptome. We tested the hypothesis as to whether AUD impairs splicing in the superior frontal cortex (SFC), nucleus accumbens (NA), basolateral amygdala (BLA), and central nucleus of the amygdala (CNA). To evaluate splicing, bam files from STAR alignments were indexed with samtools for use by rMATS software. Computational analysis of affected pathways was performed using Gene Ontology Consortium, Gene Set Enrichment Analysis, and LncRNA Ontology databases. Surprisingly, AUD was associated with limited changes in the transcriptome: expression of 23 genes was altered in SFC, 14 in NA, 102 in BLA, and 57 in CNA. However, strikingly, mis-splicing in AUD was profound: 1421 mis-splicing events were detected in SFC, 394 in NA, 1317 in BLA, and 469 in CNA. To determine the mechanism of mis-splicing, we analyzed the elements of the spliceosome: small nuclear RNAs (snRNAs) and splicing factors. While snRNAs were not affected by alcohol, expression of splicing factor heat shock protein family A (Hsp70) member 6 (HSPA6) was drastically increased in SFC, BLA, and CNA. Also, AUD was accompanied by aberrant expression of long noncoding RNAs (lncRNAs) related to splicing. In summary, alcohol is associated with genome-wide changes in splicing in multiple human brain regions, likely due to dysregulation of splicing factor(s) and/or altered expression of splicing-related lncRNAs.
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| 14. |
- Zhou, Lili, et al.
(författare)
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Correcting prevalence estimation for biased sampling with testing errors
- 2023
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Ingår i: Statistics in Medicine. - 0277-6715 .- 1097-0258. ; 42:26, s. 4713-4737
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Tidskriftsartikel (refereegranskat)abstract
- Sampling for prevalence estimation of infection is subject to bias by both oversampling of symptomatic individuals and error-prone tests. This results in naïve estimators of prevalence (ie, proportion of observed infected individuals in the sample) that can be very far from the true proportion of infected. In this work, we present a method of prevalence estimation that reduces both the effect of bias due to testing errors and oversampling of symptomatic individuals, eliminating it altogether in some scenarios. Moreover, this procedure considers stratified errors in which tests have different error rate profiles for symptomatic and asymptomatic individuals. This results in easily implementable algorithms, for which code is provided, that produce better prevalence estimates than other methods (in terms of reducing and/or removing bias), as demonstrated by formal results, simulations, and on COVID-19 data from the Israeli Ministry of Health.
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