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Int J Clin Oncol. 2015 Feb;20(1):156-63. doi: 10.1007/s10147-014-0695-1. Epub 2014 Apr 18.

Preoperative risk stratification for cancer-specific survival of patients with upper urinary tract urothelial carcinoma treated by nephroureterectomy.

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  • 1Department of Urology, Osaka University Graduate School of Medicine, 2-2 Yamada-oka, Suita, Osaka, 565-0871, Japan, kazufujita2@gmail.com.

Abstract

BACKGROUND:

This study aimed to identify preoperative parameters for predicting cancer-specific survival (CSS) in patients with upper urinary tract urothelial carcinoma (UTUC) who have undergone radical nephroureterectomy (RNU).

METHODS:

The preoperative clinical and laboratory records of 357 UTUC patients who underwent RNU at three different institutions were retrospectively reviewed (256, training set; 101, test set). Univariate and multivariate analyses were performed on the training set data to identify preoperative prognostic factors, using which a risk stratification model was developed. The model was validated using test set data.

RESULTS:

In univariate analysis, clinical T stage classification and preoperative concentrations of hemoglobin, C-reactive protein, sodium, and albumin showed significant association with CSS. Multivariate analysis showed that low preoperative sodium and hemoglobin concentrations were significantly associated with a poor prognosis. A risk stratification model was developed using the preoperative sodium (<141 mEq/L) and hemoglobin concentrations (below normal). Three subgroups were formed depending on the presence of no (favorable group), one (intermediate), or two (poor) prognostic factors, and the 5-year CSS estimates were found to be 96.5, 75.5, and 47.0 %, respectively (P < 0.01). The risk model was significantly associated with the adverse pathological findings of stage pT3 or more and lymphovascular invasion (P = 0.005).

CONCLUSION:

We identified low preoperative sodium and hemoglobin concentrations as prognostic factors for patients with UTUC treated with RNU. Our risk stratification model may help physicians design a therapeutic strategy.

PMID:
24740557
[PubMed - in process]
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