Biomarker Discovery and Validation: Statistical Considerations
Biomarkers have various applications including disease detection, diagnosis, prognosis, prediction of response to intervention, and disease monitoring. In this era of precision medicine, having validated biomarkers to inform clinical decision making is more important than ever. In this article, we d...
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| Veröffentlicht in: | Journal of thoracic oncology 2021-04, Vol.16 (4), p.537-545 |
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| container_end_page | 545 |
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| container_issue | 4 |
| container_start_page | 537 |
| container_title | Journal of thoracic oncology |
| container_volume | 16 |
| creator | Ou, Fang-Shu Michiels, Stefan Shyr, Yu Adjei, Alex A. Oberg, Ann L. |
| description | Biomarkers have various applications including disease detection, diagnosis, prognosis, prediction of response to intervention, and disease monitoring. In this era of precision medicine, having validated biomarkers to inform clinical decision making is more important than ever. In this article, we discuss best the practices and potential issues in biomarker discovery and validation. We encourage team science partnerships to bring cutting-edge discovery from bench to bedside, leading to improved patient care and outcomes. |
| doi_str_mv | 10.1016/j.jtho.2021.01.1616 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 1556-0864 |
| ispartof | Journal of thoracic oncology, 2021-04, Vol.16 (4), p.537-545 |
| issn | 1556-0864 1556-1380 |
| language | eng |
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| source | MEDLINE; Alma/SFX Local Collection; EZB Electronic Journals Library |
| subjects | Biomarker Biomarkers Biomedical Research Clinical trial Confirmation analysis Exploratory analysis Humans Lung Neoplasms Precision Medicine Prognosis |
| title | Biomarker Discovery and Validation: Statistical Considerations |
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