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  1. Article ; Online: Evolving challenges in clinical trials design.

    Begg, Colin B

    Clinical trials (London, England)

    2022  Volume 19, Issue 3, Page(s) 237–238

    MeSH term(s) Humans ; Research Design
    Language English
    Publishing date 2022-06-15
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/17407745221101276
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5831: Show issues Location:
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  2. Article ; Online: Clinical trials in Russia.

    Begg, Colin B

    Clinical trials (London, England)

    2021  Volume 18, Issue 3, Page(s) 267–268

    MeSH term(s) Humans ; Russia
    Language English
    Publishing date 2021-04-30
    Publishing country England
    Document type Editorial ; Comment
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/17407745211010780
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: In Defense of

    Begg, Colin B

    JNCI cancer spectrum

    2020  Volume 4, Issue 2, Page(s) pkaa012

    Abstract: Recently, a controversy has erupted regarding the use of statistical significance tests and the ... ...

    Abstract Recently, a controversy has erupted regarding the use of statistical significance tests and the associated
    Language English
    Publishing date 2020-02-26
    Publishing country England
    Document type Journal Article
    ISSN 2515-5091
    ISSN (online) 2515-5091
    DOI 10.1093/jncics/pkaa012
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: The costs of cancer drugs.

    Begg, Colin B

    Clinical trials (London, England)

    2020  Volume 17, Issue 2, Page(s) 118

    MeSH term(s) Antineoplastic Agents/economics ; Antineoplastic Agents/therapeutic use ; Costs and Cost Analysis ; Humans ; Neoplasms/drug therapy ; Randomized Controlled Trials as Topic ; United States ; United States Food and Drug Administration
    Chemical Substances Antineoplastic Agents
    Language English
    Publishing date 2020-02-19
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/1740774520907662
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5831: Show issues Location:
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  5. Article ; Online: Editorial.

    Begg, Colin B

    Clinical trials (London, England)

    2019  Volume 16, Issue 5, Page(s) 446

    Language English
    Publishing date 2019-09-10
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/1740774519871520
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  6. Article ; Online: Predicting Cancer Risk from Germline Whole-exome Sequencing Data Using a Novel Context-based Variant Aggregation Approach.

    Guan, Zoe / Begg, Colin B / Shen, Ronglai

    Cancer research communications

    2023  Volume 3, Issue 3, Page(s) 483–488

    Abstract: Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new direction of research has focused on extracting signals from the contexts ...

    Abstract Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new direction of research has focused on extracting signals from the contexts of germline variants and evidence has emerged that patterns defined by these factors are associated with oncogenic pathways, histologic subtypes, and prognosis. It remains an open question whether aggregating germline variants using meta-features capturing their genomic, nucleotide, and epigenetic contexts can improve cancer risk prediction. This aggregation approach can potentially increase statistical power for detecting signals from rare variants, which have been hypothesized to be a major source of the missing heritability of cancer. Using germline whole-exome sequencing data from the UK Biobank, we developed risk models for 10 cancer types using known risk variants (cancer-associated SNPs and pathogenic variants in known cancer predisposition genes) as well as models that additionally include the meta-features. The meta-features did not improve the prediction accuracy of models based on known risk variants. It is possible that expanding the approach to whole-genome sequencing can lead to gains in prediction accuracy.
    Significance: There is evidence that cancer is partly caused by rare genetic variants that have not yet been identified. We investigate this issue using novel statistical methods and data from the UK Biobank.
    MeSH term(s) Humans ; Exome Sequencing ; Genetic Predisposition to Disease/genetics ; Neoplasms/genetics ; Germ-Line Mutation/genetics ; Genomics
    Language English
    Publishing date 2023-03-22
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ISSN 2767-9764
    ISSN (online) 2767-9764
    DOI 10.1158/2767-9764.CRC-22-0355
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Zero tolerance for acronyms.

    Begg, Colin B

    Clinical trials (London, England)

    2017  Volume 14, Issue 6, Page(s) 561–562

    MeSH term(s) Abbreviations as Topic ; Editorial Policies ; Humans ; Periodicals as Topic/standards
    Language English
    Publishing date 2017-12-02
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/1740774517740570
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 5831: Show issues Location:
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  8. Article ; Online: Editorial.

    Begg, Colin B

    Clinical trials (London, England)

    2016  Volume 13, Issue 6, Page(s) 573

    Language English
    Publishing date 2016-11-14
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/1740774516678809
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5831: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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  9. Article ; Online: Editorial.

    Begg, Colin B

    Clinical trials (London, England)

    2016  Volume 13, Issue 4, Page(s) 371

    Language English
    Publishing date 2016-07-08
    Publishing country England
    Document type Editorial
    ZDB-ID 2138796-5
    ISSN 1740-7753 ; 1740-7745
    ISSN (online) 1740-7753
    ISSN 1740-7745
    DOI 10.1177/1740774516652020
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

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  10. Article: Subsampling based variable selection for generalized linear models.

    Capanu, Marinela / Giurcanu, Mihai / Begg, Colin B / Gönen, Mithat

    Computational statistics & data analysis

    2023  Volume 184

    Abstract: A novel variable selection method for low-dimensional generalized linear models is introduced. The new approach called AIC OPTimization via STABility Selection (OPT-STABS) repeatedly subsamples the data, minimizes Akaike's Information Criterion (AIC) ... ...

    Abstract A novel variable selection method for low-dimensional generalized linear models is introduced. The new approach called AIC OPTimization via STABility Selection (OPT-STABS) repeatedly subsamples the data, minimizes Akaike's Information Criterion (AIC) over a sequence of nested models for each subsample, and includes in the final model those predictors selected in the minimum AIC model in a large fraction of the subsamples. New methods are also introduced to establish an optimal variable selection cutoff over repeated subsamples. An extensive simulation study examining a variety of proposec variable selection methods shows that, although no single method uniformly outperforms the others in all the scenarios considered, OPT-STABS is consistently among the best-performing methods in most settings while it performs competitively for the rest. This is in contrast to other candidate methods which either have poor performance across the board or exhibit good performance in some settings, but very poor in others. In addition, the asymptotic properties of the OPT-STABS estimator are derived, and its root-n consistency and asymptotic normality are proved. The methods are applied to two datasets involving logistic and Poisson regressions.
    Language English
    Publishing date 2023-03-11
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1478763-5
    ISSN 0167-9473
    ISSN 0167-9473
    DOI 10.1016/j.csda.2023.107740
    Database MEDical Literature Analysis and Retrieval System OnLINE

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