PMID- 10561267
OWN - NLM
STAT- MEDLINE
DCOM- 20000607
LR  - 20170210
IS  - 0732-183X (Print)
IS  - 0732-183X (Linking)
VI  - 17
IP  - 7
DP  - 1999 Jul
TI  - Nuclear morphometry and prognosis in favorable histology Wilms' tumor: A 
      prospective reevaluation.
PG  - 2123-6
AB  - PURPOSE: This study was designed to evaluate the ability of a previously 
      published nuclear morphometry discriminant function to predict disease-free 
      survival in patients with Wilms' tumor. PATIENTS AND METHODS: We identified 218 
      patients with stage I-IV Wilms' tumor of favorable histology who were entered 
      onto the National Wilms' Tumor Study (NWTS) between January 1, 1990 and April 15, 
      1994. The nuclear morphometry score was calculated for each patient as follows: 
      MV(f) = (0.02 x AGE) + (1.17 x SNRF) + (90.6 x LEFD) - 94, with AGE denoting age 
      at diagnosis in months, SNRF the skewness of the nuclear roundness factor, and 
      LEFD the lowest value of nuclear ellipticity as measured by the feret diameter 
      method. Relative risks of relapse were estimated for the total score and for each 
      of its components. Sensitivity and specificity were determined for the criterion 
      of "MV(f) is greater than -0.35" as a predictor of relapse. RESULTS: By contrast 
      with previously published results, neither the SNRF nor the LEFD made any 
      contribution to the prediction of disease-free survival. Sensitivity and 
      specificity of the criterion of "MV(f) is greater than -0.35" were 71% and 56%, 
      respectively. CONCLUSION: Re-evaluation of a published nuclear morphometry score 
      showed that it did not predict disease-free survival in patients with Wilms' 
      tumor. The earlier study very likely overestimated the predictive power of 
      nuclear morphometry by using the same data set both to develop the score and to 
      evaluate its properties. Because of the huge number of combinations of nuclear 
      morphometry measurements that may enter into the multivariate discriminant 
      function, use of appropriate statistical methods is essential to estimate 
      accurately the sensitivity and specificity.
FAU - Breslow, N E
AU  - Breslow NE
AD  - Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, 
      USA.
FAU - Partin, A W
AU  - Partin AW
FAU - Lee, B R
AU  - Lee BR
FAU - Guthrie, K A
AU  - Guthrie KA
FAU - Beckwith, J B
AU  - Beckwith JB
FAU - Green, D M
AU  - Green DM
LA  - eng
GR  - CA42326/CA/NCI NIH HHS/United States
PT  - Journal Article
PT  - Research Support, U.S. Gov't, P.H.S.
PL  - United States
TA  - J Clin Oncol
JT  - Journal of clinical oncology : official journal of the American Society of 
      Clinical Oncology
JID - 8309333
SB  - IM
MH  - Child
MH  - Discriminant Analysis
MH  - Disease-Free Survival
MH  - Humans
MH  - Kidney Neoplasms/mortality/*pathology/therapy
MH  - Logistic Models
MH  - Multivariate Analysis
MH  - Neoplasm Recurrence, Local/epidemiology
MH  - Prognosis
MH  - Proportional Hazards Models
MH  - Prospective Studies
MH  - Retrospective Studies
MH  - Sensitivity and Specificity
MH  - United States/epidemiology
MH  - Wilms Tumor/mortality/*pathology/therapy
EDAT- 1999/11/24 09:00
MHDA- 2000/06/10 09:00
CRDT- 1999/11/24 09:00
PHST- 1999/11/24 09:00 [pubmed]
PHST- 2000/06/10 09:00 [medline]
PHST- 1999/11/24 09:00 [entrez]
AID - 10.1200/JCO.1999.17.7.2123 [doi]
PST - ppublish
SO  - J Clin Oncol. 1999 Jul;17(7):2123-6. doi: 10.1200/JCO.1999.17.7.2123.