Clinicians are already taking the suggestions and guidelines from the National Comprehensive Cancer Network (NCCN) and the American Joint Committee on Cancer (AJCC) into account, Dr. Beal says. The NCCN may be more comprehensive, but both bodies agree on histology and size to be high-risk factors as well as anatomical location. According to Dr. Beal, most clinicians intuitively think in the pattern classification model when processing the characteristics of the tumor in question, which is formatted as a decision tree or twenty questions. However, as far as risk stratification, the S2+ model or even the sum score method might be the better fit. Also for staging purposes, these models can help in trying to figure out what combination of the high risk factors are more important in a given scenario.
“In my opinion, the S2+ model is likely the one that you would go to as far as the ease in which one can pull the variables of the tumor together in a brief clinical note. This can assist the clinician in assessing the status of the SCC under scrutiny and can help in deciding on the appropriate therapy according to the level of metastatic risk,” Dr. Beal says.
Although the data showed that the S2+ model had a lower SN, Dr. Beal says that the model would be easier to implement as clinicians would only have to sum the high-risk factors. The S2+ model may be the best method to use for conceptualization and utility in a fast-paced dermatology clinic, he suggests.
“Much research has been done on high risk cSCC and this study is part of the larger effort. However, if we really want to improve the management of high risk cSCC patients, we are going to need more multicenter collaboration, the same way it is already done with other cancers. As a basic rule, if you have more than two to three high risk factors when assessing an SCC, you should probably take a closer look at that patient and just slow down and think more carefully about appropriate management,” Dr. Beal says.
1. Fosko SW, Chu MB, Beal BT, et al. Development of a metastatic risk model for cutaneous squamous cell carcinoma. Skin: The journal of cutaneous medicine. 2017; 1(1): 1-7