ArticlePloS one2017
Association between biomarkers and clinical characteristics in chronic subdural hematoma patients assessed with lasso regression.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 54 citations in OpenAlex.
- Prediction of lithium treatment response in bipolar depression using 5-HTT and 5-HTEuropean journal of nuclear medicine and molecular imaging · 2020Trial
- Estimating Ejection Fraction from the 12 Lead ECG among Patients with Acute Heart Failure.medRxiv : the preprint server for health sciences · 2024Article
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- Screening of genes characteristic of pancreatic cancer by LASSO regression combined with support vector machine and recursive feature elimination, and immune correlation analysis.The Journal of international medical research · 2024Article
- Multi-classification model incorporating radiomics and clinic-radiological features for predicting invasiveness and differentiation of pulmonary adenocarcinoma nodules.Biomedical engineering online · 2023Article
- Biofluid Biomarkers in the Prognosis of Chronic Subdural Hematoma: A Systematic Scoping Review.Diagnostics (Basel, Switzerland) · 2023Article
- Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas.Neurotrauma reports · 2023Article
- Controversies in the Surgical Treatment of Chronic Subdural Hematoma: A Systematic Scoping Review.Diagnostics (Basel, Switzerland) · 2022Article
- Serum Levels of MMP-8 and MMP-9 as Markers in Chronic Subdural Hematoma.Journal of clinical medicine · 2022Article
- Factors correlated with the postoperative recurrence of chronic subdural hematoma: An umbrella study of systematic reviews and meta-analyses.EClinicalMedicine · 2022Article
- Immunoexpression of MMP-8 and MMP-9 in chronic subdural hematoma.Frontiers in neurology · 2022Article
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- A stable gene set for prediction of prognosis and efficacy of chemotherapy in gastric cancer.BMC cancer · 2021Article
- Atorvastatin combined with low-dose dexamethasone for vascular endothelial cell dysfunction induced by chronic subdural hematoma.Neural regeneration research · 2021Article
- Relevant Characteristics Analysis Using Natural Language Processing and Machine Learning Based on Phenotypes and T-Cell Subsets in Systemic Lupus Erythematosus Patients With Anxiety.Frontiers in psychiatry · 2021Article
- Clinicopathological Characteristics and Prognosis of Nasopharyngeal Lymphoepithelial Carcinoma: A Population-Based Retrospective Study.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Identification of Serum-Based Metabolic Feature and Characteristic Metabolites in Paraquat Intoxicated Mouse Models.Frontiers in physiology · 2020Article
- Age-dependent co-dependency structure of biomarkers in the general population of the United States.Aging · 2019Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic subdural hematoma (CSDH) is characterized by an "old" encapsulated collection of blood and blood breakdown products between the brain and its outermost covering (the dura). Recognized risk factors for development of CSDH are head injury, old age and using anticoagulation medication, but its underlying pathophysiological processes are still unclear. It is assumed that a complex local process of interrelated mechanisms including inflammation, neomembrane formation, angiogenesis and fibrinolysis could be related to its development and propagation. However, the association between the biomarkers of inflammation and angiogenesis, and the clinical and radiological characteristics of CSDH patients, need further investigation. The high number of biomarkers compared to the number of observations, the correlation between biomarkers, missing data and skewed distributions may limit the usefulness of classical statistical methods. We therefore explored lasso regression to assess the association between 30 biomarkers of inflammation and angiogenesis at the site of lesions, and selected clinical and radiological characteristics in a cohort of 93 patients. Lasso regression performs both variable selection and regularization to improve the predictive accuracy and interpretability of the statistical model. The results from the lasso regression showed analysis exhibited lack of robust statistical association between the biomarkers in hematoma fluid with age, gender, brain infarct, neurological deficiencies and volume of hematoma. However, there were associations between several of the biomarkers with postoperative recurrence requiring reoperation. The statistical analysis with lasso regression supported previous findings that the immunological characteristics of CSDH are local. The relationship between biomarkers, the radiological appearance of lesions and recurrence requiring reoperation have been inclusive using classical statistical methods on these data, but lasso regression revealed an association with inflammatory and angiogenic biomarkers in hematoma fluid. We thus suggest that lasso regression should be a recommended statistical method in research on biological processes in CSDH patients.
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