The role of nuclear morphometry for predicting disease outcome in patients with localized renal cell carcinoma

Ofer Nativ, Edmond Sabo, Gil Raviv, Ora Medalia, Boaz Moskovitz, Benad Goldwasser

Research output: Contribution to journalArticlepeer-review

Abstract

Background. More than one‐third of patients with localized renal cell carcinoma (RCC) will have disease progression after nephrectomy. Present histopathologic variables cannot accurately predict the outcome of individual patients. Methods. Nuclear morphometry was performed by an image analyzer on histologic sections from 39 specimens of pathologic T1 and T2 classification RCC. All patients underwent radical nephrectomy and were followed for a mean of 7.6 years. A univariate analysis and then a multivariate stepwise regression method were used to correlate results with patients' outcome. Results. The best predictors of disease free interval were mean nuclear elongation factor (MNEF) (P = 0.023), mean nuclear regularity factor (MNRF) (P = 0.034), and mean nuclear area (MNA) (N = 0.038). Univariate analysis identified a significant correlation between patient survival and MNEF (P = 0.009), MNRF (P = 0.020) and MNA (P = 0.023). Combination of MNEF and MNA was even more strongly associated with survival (P = 0.0013). Multivariate analysis revealed that MNA (P = 0.044) and MNEF (P = 0.045) correlated independently with survival. Conclusion. These results suggest that nuclear morphometry provides objective independent prognostic information for patients with localized RCC.

Original languageEnglish
Pages (from-to)1440-1444
Number of pages5
JournalCancer
Volume76
Issue number8
DOIs
StatePublished - 15 Oct 1995
Externally publishedYes

Keywords

  • image analysis
  • nuclear morphometry
  • prognosis
  • renal cell carcinoma

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