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Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 BJU+Int 2012 ; 109 (11): 1600-6 Nephropedia Template TP
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Impact of pathological tumour characteristics in patients with sarcomatoid renal cell carcinoma #MMPMID22221668
BJU Int 2012[Jun]; 109 (11): 1600-6 PMID22221668show ga
OBJECTIVE: Patients with sarcomatoid renal cell carcinoma (sRCC) are known to have poor prognosis and response to systemic therapy.We set out to examine the influence of pathological tumour characteristics on survival to aid prognostication and clinical trial design. PATIENTS AND METHODS: A single-centre database was reviewed to identify all patients with sRCC.Clinical variables and pathological information, including histology, necrosis, percentage of sarcomatoid features (PSF) and microvascular invasion (MVI), were recorded and correlated to outcome. RESULTS: Analyses of 104 patients with sRCC found that the median (range) size of tumours was 9.5 cm (2.5?30), 65% of patients had areas of clear cell histology, and 69.2% had metastatic disease at presentation.The PSF did not influence tumour size, stage, necrosis, MVI, nodes or metastasis.A total of 85 patients (81.7%) died during the follow-up period with a median (95% confidence interval [CI]) survival of 5.9 months (4.7?8.9).In the overall cohort, Eastern Cooperative Group performance status (ECOGPS), tumour size and metastatic disease were independent predictors of poor survival. MVI, PSF and percentage necrosis were strongly associated with outcome but were not independent predictors of outcome.A multivariate risk model was established that incorporated six covariates (tumour size, MVI, ECOGPS, PSF, necrosis, and metastatic disease) to produce a predictive tool. CONCLUSIONS: Both patients with localized and metastatic sRCC have very poor survival outcomes.Pathological features MVI, PSF and necrosis are important predictors of survival and could be used in a prognostic model while grade and histology do not influence prognosis.A prognostic model, if validated, could aid in patient counselling and/or clinical trial design.