Nuclear morphometry adds significant prognostic information to stage and grade for renal cell carcinoma

Michael A. Carducci, Steven Piantadosi, Charles R. Pound, Jonathan I. Epstein, Jonathan W. Simons, Fray F. Marshall, Alan W. Partin

Research output: Contribution to journalArticlepeer-review

42 Scopus citations


Objectives. Identification of patients with a high probability of recurrence after nephrectomy for renal cell carcinoma (RCC) is required for adjuvant studies of new therapies. Nuclear morphometry predicts prognosis for prostate, bladder, and Wilms' tumors and in RCC according to previous small pilot studies. Methods. To validate this finding, we studied an additional 101 patients who underwent nephrectomy for Stage pT1 to pT3 RCC at our institution from 1977 to 1993 for whom data regarding recurrence or disease- free survival of greater than 60 months were available. Patient records and pathology specimens were reviewed. Of the 101 patients, 66 (65%) did not experience recurrence with greater than 60 months of follow-up, and 35 (35%) had RCC recurrence with a median time to recurrence of 17 months. Nuclear shape descriptors were tested as predictors of disease recurrence after accounting for stage and grade in proportional hazards regression models. Results. Range of ellipticity (hazards ratio 3.39, P = 0.014) was confirmed to be a significant predictor of recurrence. A prognostic model using stage, grade, and range of ellipticity identified three distinct groups: low, moderate, and high recurrence risk groups, with recurrence rates of 4%, 37%, and 63%, respectively, at 5 years of follow-up. Morphometry significantly (P = 0.018) improved prognostication on the basis of stage and grade alone in this multivariate model. Conclusions. Nuclear morphometry is valid and accurate in predicting relapse in early-stage RCC. The model can select patients with RCC for adjuvant therapies.

Original languageEnglish (US)
Pages (from-to)44-49
Number of pages6
Issue number1
StatePublished - Jan 1999

ASJC Scopus subject areas

  • Urology


Dive into the research topics of 'Nuclear morphometry adds significant prognostic information to stage and grade for renal cell carcinoma'. Together they form a unique fingerprint.

Cite this