4.3 Article

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

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INTERNATIONAL JOURNAL OF CLINICAL ONCOLOGY
卷 20, 期 1, 页码 156-163

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SPRINGER JAPAN KK
DOI: 10.1007/s10147-014-0695-1

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Prognosis; Upper urinary tract urothelial carcinoma; Nephroureterectomy; Sodium; Hemoglobin

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  1. Novartis Pharma
  2. Pfizer Pharmaceutical

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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.

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