Comment on Borșa et al. Developing New Diagnostic Tools Based on SERS Analysis of Filtered Salivary Samples for Oral Cancer Detection. Int. J. Mol. Sci. 2023, 24, 12125

This comment discusses a recent research paper on the classification of saliva samples with SERS by Borsa et al. The authors suggested utilizing PCA-LDA to detect oral cancer and claimed to achieve an accuracy of up to 77%. Despite the high prediction capability of the proposed approach, the demonstrated findings could be treated as unclear due to possible overestimation of the proposed classification models. Data should be provided for both the training and the validation sets to make sure that there were no repeated data from the same sample in either set. Moreover, the authors proposed to measure opiorphin in saliva with SERS as a potential biomarker of oral cancer. However, opiorphin in saliva is contained in ng/mL concentrations, and the proposed technique is most likely not capable of recording the real concentration of opiorphin.