June 2015
Volume 56, Issue 7
Free
ARVO Annual Meeting Abstract  |   June 2015
Tumor diameter contributes prognostic information that enhances the accuracy of gene expression profile molecular classification in uveal melanoma
Author Affiliations & Notes
  • Scott Walter
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, FL
  • Daniel L Chao
    Department of Ophthalmology, UCSF School of Medicine, San Francisco, CA
  • Joyce C Schiffman
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, FL
  • William J Feuer
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, FL
  • J. William Harbour
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, FL
    Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL
  • Footnotes
    Commercial Relationships Scott Walter, None; Daniel Chao, None; Joyce Schiffman, None; William Feuer, None; J. William Harbour, Castle Biosciences (C), Castle Biosciences (P)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2015, Vol.56, 4334. doi:
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    • Get Citation

      Scott Walter, Daniel L Chao, Joyce C Schiffman, William J Feuer, J. William Harbour; Tumor diameter contributes prognostic information that enhances the accuracy of gene expression profile molecular classification in uveal melanoma. Invest. Ophthalmol. Vis. Sci. 2015;56(7 ):4334.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

Molecular classification using gene expression profiling (GEP) is currently the most accurate single predictor of mortality from uveal melanoma. The purpose of this study was to determine whether clinical or cytopathologic features may provide independent prognostic value in assessing mortality risk.

 
Methods
 

336 consecutive cases of uveal melanoma were analyzed using Kaplan-Meier survival analysis and Cox regression. The primary outcome measure was 5-year all cause mortality. Dependent variables included GEP molecular classification (class 1 vs. 2), patient age and sex, tumor thickness and basal diameter, ciliary body involvement and cell type.

 
Results
 

After controlling for GEP molecular classification, no clinicopathologic features provided independent prognostic information except basal tumor diameter (p=0.002, Cox regression). For both class 1 and class 2 tumors, the best dichotomous cutoff for basal tumor diameter was <12mm (small) vs. ≥12mm (large). The risk of mortality relative to small class 1 tumors was 8.6 for large class 1 tumors, 9.1 for small class 2 tumors, and 78.1 for large class 2 tumors (all p<0.05). Similar results were demonstrated for melanoma-specific mortality. The model-based predicted 5-year survival was 98% for small class 1 tumors, 85-87% for large class 1 and small class 2 tumors, and 16% for large class 2 tumors.

 
Conclusions
 

For both class 1 and class 2 uveal melanomas, basal tumor diameter was the only clinicopathologic factor that provided additional prognostic information that enhanced the accuracy of GEP molecular classification. Basal tumor diameter, in combination with GEP, may be a useful metric for risk stratification, especially for tumors less than 12mm in diameter.  

 
Figure 1: Reverse Kaplan-Meier plot of all cause mortality over time for patients with class 1 (A) and class 2 (B) uveal melanoma by gene expression profiling. Results are stratified according to basal tumor diameter <12mm (blue line) or ≥12mm (green line). Vertical steps represent mortality events. Vertical notches represent patients alive at last follow-up.
 
Figure 1: Reverse Kaplan-Meier plot of all cause mortality over time for patients with class 1 (A) and class 2 (B) uveal melanoma by gene expression profiling. Results are stratified according to basal tumor diameter <12mm (blue line) or ≥12mm (green line). Vertical steps represent mortality events. Vertical notches represent patients alive at last follow-up.

 
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