Chen N, et al. – Keeping the objective in mnd, researchers illustrated that analyzing blood serum applying surface–enhanced Raman spectroscopy (SERS) combined with prostate cancer (PCa)–LDA diagnostic algorithms is a promising clinical tool for prostate cancer (PCa) diagnosis and assessment.

Methods

• Researchers enrolled a sum of 240 SERS spectra from blood serum from 40 PCa subjects and 40 BPH subjects who had all received prostate biopsies and were given a pathological diagnosis.

Results

• They applied multivariate statistical techniques, including principal component analysis (PCA) and linear discriminant analysis (LDA) diagnostic algorithms to analyze the spectra data of serum from patients in control (CTR), PCa and BPH groups; results offered a sensitivity of 97.5%, a specificity of 100.0%, a precision of 100.0% and an accuracy of 99.2% for CTR; a sensitivity of 90.0%, a specificity of 97.5%, a precision of 94.7% and an accuracy of 98.3% for BPH; a sensitivity of 95.0%, a specificity of 93.8%, a precision of 88.4% and an accuracy of 94.2% for PCa.
• It was considered that this technique can significantly differentiate low- and high-risk PCa with an accuracy of 92.3%, a specificity of 95% and a sensitivity of 89.5%.