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Nomograms in oncology: more than meets the eye
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Summary Nomograms are commonly used tools to estimate prognosis in oncology and medicine. With the ability to generate an individual numerical probability of a clinical event by integrating diverse prognostic and determinant variables, nomograms fulfill our desire for biologically and clinically integrated models and our drive towards personalized medicine. Rapid computation through user friendly digital interfaces, together with increased accuracy, and more easily understood prognoses compared to conventional staging, allow for seamless incorporation of nomogram derived prognosis to aid in clinical decision making. This has lead to the ubiquitous appearance of nomograms on the internet and in medical journals, and increasing nomogram use by patients and physicians alike. However, the statistical foundations of nomogram construction, their precise interpretation, and evidence supporting their use is commonly misunderstood, leading to an under appreciation of the inherent uncertainties regarding nomogram use. We provide a systematic, practical approach to evaluating and comprehending nomogram derived prognoses, with particular emphasis on clarifying common misconceptions and highlighting limitations.
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Huang, Y.-Q., Liang, C.-H., He, L., Tian, J., Liang, C.-S., Chen, X., Ma, Z.-L., & Liu, Z.-Y. (2016) · Journal of Clinical Oncology · doi:10.1200/jco.2015.65.9128 · Cited by 1,765
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Self-citationFrom past to future: Bibliometric analysis of global research productivity on nomogram (2000–2021)
Wang, X., Lu, J., Song, Z., Zhou, Y., Liu, T., & Zhang, D. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.997713 · Cited by 140
Metadata
- Authors
- Balachandran, V. P., Gonen, M., Smith, J. J., & DeMatteo, R. P.
- Venue
- The Lancet Oncology
- Publisher
- Elsevier BV
- Published
- 2015-04
- Volume
- 16
- Issue
- 4
- Pages
- e173-e180
- ISSN
- 1470-2045 (ISSN-L)
- OpenAlex
- W2153505392
- Cited by
- 3,292
- References
- 0
- FWCI
- 40.88
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- Funders
- National Institutes of Health ((NIH P30 CA008748 and NIH R01 CA102613))
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