Exploratory Algorithms to Aid in Risk of Malignancy Prediction for Indeterminate Pulmonary Nodules
In conclusion, a simple reduced algorithm consisting of biomarkers, clinical information, and demographic variables may have value for malignancy prediction of screen-detected IPNs. Upon further validation, this method stands to reduce the need for serial radiographic studies and the risks of diagnostic delay.
Authors
- Akanksha Sharma (ORCID: https://orcid.org/0000-0003-3268-8922)
- Ramya S. Gaddikeri (ORCID: https://orcid.org/0000-0003-2612-1022)
- Gerard J. Davis (ORCID: https://orcid.org/0000-0002-4149-1999)
- Jeffrey A. Borgia (ORCID: https://orcid.org/0000-0002-1520-7966)
- Nicolette Jeanblanc
- Claire Auger (ORCID: https://orcid.org/0000-0002-8287-2982)
- Laurel Jackson (ORCID: https://orcid.org/0000-0002-0491-9079)
- Christopher Jacobson (ORCID: https://orcid.org/0009-0004-6492-6280)
- Susan H. Gawel (ORCID: https://orcid.org/0000-0003-3295-7539)
- Kinnari Pandya
- Nicole Geissen (ORCID: https://orcid.org/0000-0001-7668-4486)
- Hita Moudgalya (ORCID: https://orcid.org/0000-0001-5661-5571)
- Palmi Shah (ORCID: https://orcid.org/0000-0003-2629-2323)
- Christopher W. Seder (ORCID: https://orcid.org/0000-0002-4070-1245)
Institutions
- Rush University Medical Center (US)
- Abbott (United States) (US)
Publication Details
- Journal
- Cancers
- Published
- 2025-04-05
- DOI
- https://doi.org/10.3390/cancers17071231
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Rush University
- Abbott Diagnostics