JAMA Ophthalmology, March 2020
When it comes to predicting metastasis in patients with uveal melanoma, how do The Cancer Genome Atlas (TCGA) and American Joint Committee on Cancer (AJCC) classification systems compare? Mazloumi et al. set out to answer this question and found that the TCGA provides greater accuracy.
For this retrospective cohort study, the researchers evaluated 642 patients with uveal melanoma who were treated with plaque radiotherapy from Oct. 1, 2008, to Dec. 31, 2018. Patients without complete genetic analysis of both chromosomes 3 and 8 were excluded, as were those with iris melanoma.
Using AJCC classification, the 642 tumors were classified into four categories, 17 subcategories, and four stages (based on tumor largest basal diameter, thickness, location, and extraocular extension). Based on genetic results, they were then grouped into four TCGA classes. The mean follow-up time for the entire cohort was 43.7 months (range, 1.4-159.2 months); the main outcome was the value of the two methods for predicting uveal melanoma–related metastasis.
The researchers used univariate Cox regression and multivariate models to predict the likelihood of metastasis. At five years, TCGA classification showed a higher value for prediction of distant metastasis in all models: With univariate analysis, the Wald statistic was 94.8 for four TCGA classes (hazard ratio [HR], 2.8; 95% confidence interval [CI], 2.3-3.5; p < 0.01) and 67.5 for four AJCC categories (HR, 2.6; 95% CI, 2.1-3.2; p < 0.01). With multivariate analysis, the Wald statistic for TCGA was 61.5 (HR, 2.4; 95% CI, 1.9-2.9; p < 0.01) and 35.5 for AJCC classification (HR, 1.9; 95% CI, 1.5-2.4; p < 0.01).
The authors noted that follow-up data of five or more years were available on only 168 of the 642 patients. Nonetheless, they said, when genetic testing results are available, the TCGA system may be a more accurate way to identify those patients who are at high risk of metastasis.
The original article can be found here.