Prognostic Value of Comorbidity for Patients with Upper Tract Urothelial Carcinoma after Radical Nephroureterectomy.
Hung-Lung KeChing-Chia LiHsiang-Ying LeeHung-Pin TuYu-Ching WeiHsin-Chih YehWen-Jeng WuWei-Ming LiPublished in: Cancers (2022)
Patients with upper tract urothelial carcinoma (UTUC) have a high prevalence of comorbidities. However, the prognostic impact of comorbidities in these patients is not well studied. We aimed to outline the comorbidity burden in UTUC patients and investigate its relationship with overall survival (OS), cancer-specific survival (CSS), and progression-free survival (PFS). We retrospectively reviewed the clinicopathological data of 409 non-metastatic UTUC patients who received radical nephroureterectomy between 2000 and 2015. The comorbidity burden was evaluated using the Adult Comorbidity Evaluation-27 (ACE-27). Kaplan-Meier survival analysis showed that high ACE-27 grade was significantly associated with worse PFS, CSS, and OS. In multivariate Cox regression and competing risk analyses, we found that ACE-27 grade, tumor stage, and tumor grade were independent prognosticators of OS, CSS, and PFS. We combined these three significant factors to construct a prognostic model for predicting clinical outcomes. A receiver operating characteristic curve revealed that our prognostic model had high predictive performance. The Harrel's concordance indices of this model for predicting OS, CSS, and PFS were 0.81, 0.85, and 0.85, respectively. The results suggest that the UTUC patient comorbidity burden (ACE-27) provides information on the risk for meaningful clinical outcomes of OS, CSS, and PFS.
Keyphrases
- free survival
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- angiotensin ii
- angiotensin converting enzyme
- small cell lung cancer
- squamous cell carcinoma
- prognostic factors
- healthcare
- peritoneal dialysis
- patient reported outcomes
- single cell
- deep learning
- data analysis
- artificial intelligence
- urinary tract