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  • 1
    In: JNCI Cancer Spectrum, Oxford University Press (OUP), Vol. 4, No. 1 ( 2020-02-01)
    Abstract: Although uniform colonoscopy screening reduces colorectal cancer (CRC) mortality, risk-based screening may be more efficient. We investigated whether CRC screening based on polygenic risk is a cost-effective alternative to current uniform screening, and if not, under what conditions it would be. Methods The MISCAN-Colon model was used to simulate a hypothetical cohort of US 40-year-olds. Uniform screening was modeled as colonoscopy screening at ages 50, 60, and 70 years. For risk-stratified screening, individuals underwent polygenic testing with current and potential future discriminatory performance (area under the receiver-operating curve [AUC] of 0.60 and 0.65–0.80, respectively). Polygenic testing results were used to create risk groups, for which colonoscopy screening was optimized by varying the start age (40–60 years), end age (70–85 years), and interval (1–20 years). Results With current discriminatory performance, optimal screening ranged from once-only colonoscopy at age 60 years for the lowest-risk group to six colonoscopies at ages 40–80 years for the highest-risk group. While maintaining the same health benefits, risk-stratified screening increased costs by $59 per person. Risk-stratified screening could become cost-effective if the AUC value would increase beyond 0.65, the price per polygenic test would drop to less than $141, or risk-stratified screening would lead to a 5% increase in screening participation. Conclusions Currently, CRC screening based on polygenic risk is unlikely to be cost-effective compared with uniform screening. This is expected to change with a greater than 0.05 increase in AUC value, a greater than 30% reduction in polygenic testing costs, or a greater than 5% increase in adherence with screening.
    Type of Medium: Online Resource
    ISSN: 2515-5091
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 2975772-1
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  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2020
    In:  BMC Medical Research Methodology Vol. 20, No. 1 ( 2020-12)
    In: BMC Medical Research Methodology, Springer Science and Business Media LLC, Vol. 20, No. 1 ( 2020-12)
    Abstract: We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles. Methods We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles. Results A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less. Conclusions CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.
    Type of Medium: Online Resource
    ISSN: 1471-2288
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2041362-2
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  • 3
    Online Resource
    Online Resource
    Oxford University Press (OUP) ; 2020
    In:  International Journal of Epidemiology Vol. 49, No. 4 ( 2020-08-01), p. 1397-1403
    In: International Journal of Epidemiology, Oxford University Press (OUP), Vol. 49, No. 4 ( 2020-08-01), p. 1397-1403
    Abstract: The area under the receiver operating characteristic (ROC) curve (AUC) is commonly used for assessing the discriminative ability of prediction models even though the measure is criticized for being clinically irrelevant and lacking an intuitive interpretation. Every tutorial explains how the coordinates of the ROC curve are obtained from the risk distributions of diseased and non-diseased individuals, but it has not become common sense that therewith the ROC plot is just another way of presenting these risk distributions. We show how the ROC curve is an alternative way to present risk distributions of diseased and non-diseased individuals and how the shape of the ROC curve informs about the overlap of the risk distributions. For example, ROC curves are rounded when the prediction model included variables with similar effect on disease risk and have an angle when, for example, one binary risk factor has a stronger effect; and ROC curves are stepped rather than smooth when the sample size or incidence is low, when the prediction model is based on a relatively small set of categorical predictors. This alternative perspective on the ROC plot invalidates most purported limitations of the AUC and attributes others to the underlying risk distributions. AUC is a measure of the discriminative ability of prediction models. The assessment of prediction models should be supplemented with other metrics to assess their clinical utility.
    Type of Medium: Online Resource
    ISSN: 0300-5771 , 1464-3685
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 1494592-7
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