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      D-dimer levels and cerebral infarction in critically ill cancer patients

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          Abstract

          Background

          D-dimer levels have been used in the diagnosis of a variety of thrombosis-related diseases. In this study, we evaluated whether measuring D-dimer levels can help to diagnose cerebral infarction (CI) in critically ill cancer patients.

          Methods

          We retrospectively evaluated all cancer patients who underwent brain magnetic resonance imaging (MRI) between March 2010 and February 2014 at the medical oncology intensive care unit (ICU) of Samsung Medical Center. Brain MRI scanning was performed when CI was suspected due to acute neurological deficits. We compared D-dimer levels between patients ultimately diagnosed as having or not having CI and analyzed diffusion-weighted imaging (DWI) lesion patterns.

          Results

          A total of 88 patients underwent brain MRI scanning due to clinical suspicion of CI; altered mental status and unilateral hemiparesis were the most common neurological deficits. CI was ultimately diagnosed in 43 (49%) patients. According to the DWI patterns, multiple arterial infarctions (40%) were more common than single arterial infarctions (9%). Cryptogenic stroke etiologies were more common (63%) than determined etiologies. There was no significant difference in D-dimer levels between patients with and without CI ( P = 0.319). Although D-dimer levels were not helpful in diagnosing CI, D-dimer levels were associated with cryptogenic etiologies in critically ill cancer patients; D-dimer levels were higher in the cryptogenic etiology group than in the determined etiology group or the non-infarction group ( P = 0.001). In multivariate analysis, elevated D-dimer levels (> 8.89 μg/mL) were only associated with cryptogenic stroke (adjusted OR 5.46; 95% confidence interval, 1.876–15.857).

          Conclusions

          Abnormal D-dimer levels may support the diagnosis of cryptogenic stroke in critically ill cancer patients.

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          Most cited references22

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          Youden Index and optimal cut-point estimated from observations affected by a lower limit of detection.

          The receiver operating characteristic (ROC) curve is used to evaluate a biomarker's ability for classifying disease status. The Youden Index (J), the maximum potential effectiveness of a biomarker, is a common summary measure of the ROC curve. In biomarker development, levels may be unquantifiable below a limit of detection (LOD) and missing from the overall dataset. Disregarding these observations may negatively bias the ROC curve and thus J. Several correction methods have been suggested for mean estimation and testing; however, little has been written about the ROC curve or its summary measures. We adapt non-parametric (empirical) and semi-parametric (ROC-GLM [generalized linear model]) methods and propose parametric methods (maximum likelihood (ML)) to estimate J and the optimal cut-point (c *) for a biomarker affected by a LOD. We develop unbiased estimators of J and c * via ML for normally and gamma distributed biomarkers. Alpha level confidence intervals are proposed using delta and bootstrap methods for the ML, semi-parametric, and non-parametric approaches respectively. Simulation studies are conducted over a range of distributional scenarios and sample sizes evaluating estimators' bias, root-mean square error, and coverage probability; the average bias was less than one percent for ML and GLM methods across scenarios and decreases with increased sample size. An example using polychlorinated biphenyl levels to classify women with and without endometriosis illustrates the potential benefits of these methods. We address the limitations and usefulness of each method in order to give researchers guidance in constructing appropriate estimates of biomarkers' true discriminating capabilities. Copyright 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
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            Optimal cut-point and its corresponding Youden Index to discriminate individuals using pooled blood samples.

            Costs can hamper the evaluation of the effectiveness of new biomarkers. Analysis of smaller numbers of pooled specimens has been shown to be a useful cost-cutting technique. The Youden index (J), a function of sensitivity (q) and specificity (p), is a commonly used measure of overall diagnostic effectiveness. More importantly, J is the maximum vertical distance or difference between the ROC curve and the diagonal or chance line; it occurs at the cut-point that optimizes the biomarker's differentiating ability when equal weight is given to sensitivity and specificity. Using the additive property of the gamma and normal distributions, we present a method to estimate the Youden index and the optimal cut-point, and extend its applications to pooled samples. We study the effect of pooling when only a fixed number of individuals are available for testing, and pooling is carried out to save on the number of assays. We measure loss of information by the change in root mean squared error of the estimates of the optimal cut-point and the Youden index, and we study the extent of this loss via a simulation study. In conclusion, pooling can result in a substantial cost reduction while preserving the effectiveness of estimators, especially when the pool size is not very large.
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              Stroke and cancer: the importance of cancer-associated hypercoagulation as a possible stroke etiology.

              The importance of cancer-associated hypercoagulability as a possible stroke etiology in patients with cancer has received relatively little attention to date. A recent study has suggested that cancer-associated hypercoagulation may be of special importance in the absence of conventional stroke mechanisms.
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                Author and article information

                Contributors
                lamyud.ryu@samsung.com
                ohyoung.bang@samsung.com
                82-41-550-6577 , lamyud9@gmail.com
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                30 August 2017
                30 August 2017
                2017
                : 17
                : 591
                Affiliations
                [1 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Critical Care Medicine, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; 81 Irwon-ro, Gangnam-gu, Seoul, 135-710 Republic of Korea
                [2 ]ISNI 0000 0001 2181 989X, GRID grid.264381.a, Department of Neurology, Samsung Medical Center, , Sungkyunkwan University School of Medicine, ; 81 Irwon-ro, Gangnam-gu, Seoul, 135-710 Republic of Korea
                [3 ]ISNI 0000 0001 0705 4288, GRID grid.411982.7, Department of Neurology, , Dankook University College of Medicine, ; Anseo-dong San 16-5, Cheonan-si, Chungcheongnam-do 330-715 Republic of Korea
                Article
                3588
                10.1186/s12885-017-3588-7
                5576032
                28854911
                5a8a691c-99dd-4d63-92ed-ac9d1ffa788a
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 17 July 2016
                : 22 August 2017
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Oncology & Radiotherapy
                d-dimer,cerebral infarction,cancer,brain magnetic resonance imaging,intensive care unit

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