An Assessment of Novel Biomarkers in Bone Metastatic Disease Using Multiplex Measurement and Multivariate Analysis

Aim: Current diagnostics of bone metastatic disease is not satisfactory for early detection or regular process monitoring. The combination of biomarkers and the multiparametric approach was described as effective in other oncology diagnoses. The aim of the study was to improve the difference diagnostics between bone-metastatic disease and solid tumors using mutivariate logistic regression model. Methods: We assessed the group of 131 patients with the following diagnoses: prostate cancer, breast cancer, lung cancer, and colorectal cancer. According to the results of scintigraphy, the cohort was divided into 2 groups based on the occurrence of bone metastases. Group 0 was a control group of 75 patients with no signs of bone metastases and group 1 included 56 patients with bone metastases. Results: We used stepwise selection multivariate logistic regression for choosing the multimarker formula for calculation of risk score for bone metastases diagnostics. For detection of bone metastasis, it was shown to be most effective measurement of 3 biomarkers: procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin and combining with calculation of risk score by designating measured concentrations in mathematical formula: bone risk score = procollagen type 1 N-terminal propeptide × 0.0500 + growth differentiation factor-15 × 1.4179 + osteonectin × 0.00555. Conclusion: We identified growth differentiation factor-15 as the best individual marker for bone metastasis diagnostics. The best formula for risk score includes levels of 3 biomarkers—procollagen type 1 N-terminal propeptide, growth differentiation factor-15, and osteonectin. The new score has better performance described by higher area under the curve than individual biomarkers. A further study is necessary to confirm these findings incorporating a larger number of patients.