Machine learning models predict the progression of long-term renal insufficiency in patients with renal cancer after radical nephrectomy
Among 360 patients with renal cancer who underwent radical nephrectomy included in this study, 185 (51.3%) experienced an upgrade in Chronic Kidney Disease stage 3-year post-surgery. Eleven predictive variables were selected for further construction of the machine learning models. The logistic regression model provided the most accurate prediction, with the highest AUC (0.8154) and an accuracy of 0.787.
Authors
- Haotian Du
- Wei Sun (ORCID: https://orcid.org/0000-0003-2151-6420)
- Yize Guo
- Bin Li (ORCID: https://orcid.org/0000-0002-8979-610X)
- Yongchao Yan
- Qihang Sun (ORCID: https://orcid.org/0000-0002-8449-0726)
- Xinning Wang (ORCID: https://orcid.org/0009-0000-1064-1512)
Institutions
- Qingdao University (CN)
- People’s Hospital of Rizhao (CN)
- Affiliated Hospital of Qingdao University (CN)
- Tongji Hospital (CN)
Publication Details
- Journal
- BMC Nephrology
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1186/s12882-024-03907-1
- Citations
- 3
- Primary Topic
- Renal and Vascular Pathologies
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- Medical and Health Science and Technology Development Project of Shandong Province