Melanoma sentinel node biopsy and prediction models for relapse and overall survival

BACKGROUND:To optimise predictive models for sentinal node biopsy (SNB) positivity, relapse and survival, using clinico-pathological characteristics and osteopontin gene expression in primary melanomas.METHODS:A comparison of the clinico-pathological characteristics of SNB positive and negative cases was carried out in 561 melanoma patients. In 199 patients, gene expression in formalin-fixed primary tumours was studied using Illumina's DASL assay. A cross validation approach was used to test prognostic predictive models and receiver operating characteristic curves were produced.RESULTS:Independent predictors of SNB positivity were Breslow thickness, mitotic count and tumour site. Osteopontin expression best predicted SNB positivity (P=2.4 × 10??), remaining significant in multivariable analysis. Osteopontin expression, combined with thickness, mitotic count and site, gave the best area under the curve (AUC) to predict SNB positivity (72.6%). Independent predictors of relapse-free survival were SNB status, thickness, site, ulceration and vessel invasion, whereas only SNB status and thickness predicted overall survival. Using clinico-pathological features (thickness, mitotic count, ulceration, vessel invasion, site, age and sex) gave a better AUC to predict relapse (71.0%) and survival (70.0%) than SNB status alone (57.0, 55.0%). In patients with gene expression data, the SNB status combined with the clinico-pathological features produced the best prediction of relapse (72.7%) and survival (69.0%), which was not increased further with osteopontin expression (72.7, 68.0%).CONCLUSION:Use of these models should be tested in other data sets in order to improve predictive and prognostic data for patients

Factors Predictive of the Status of Sentinel Lymph Nodes in Melanoma Patients from a Large Multicenter Database

Numerous predictive factors for cutaneous melanoma metastases to sentinel lymph nodes have been identified; however, few have been found to be reproducibly significant. This study investigated the significance of factors for predicting regional nodal disease in cutaneous melanoma using a large multicenter database. Seventeen institutions submitted retrospective and prospective data on 3463 patients undergoing sentinel lymph node (SLN) biopsy for primary melanoma. Multiple demographic and tumor factors were analyzed for correlation with a positive SLN. Univariate and multivariate statistical analyses were performed. Of 3445 analyzable patients, 561 (16.3%) had a positive SLN biopsy. In multivariate analysis of 1526 patients with complete records for 10 variables, increasing Breslow thickness, lymphovascular invasion, ulceration, younger age, the absence of regression, and tumor location on the trunk were statistically significant predictors of a positive SLN. These results confirm the predictive significance of the well-established variables of Breslow thickness, ulceration, age, and location, as well as consistently reported but less well-established variables such as lymphovascular invasion. In addition, the presence of regression was associated with a lower likelihood of a positive SLN. Consideration of multiple tumor parameters should influence the decision for SLN biopsy and the estimation of nodal metastatic disease risk