OBJECTIVE: The clinical value of serum tartrate-resistant acid phosphatase (TRACP), prostate specific antigen (PSA), alkaline phosphatase (ALP), and prostatic acid phosphatase (PACP) for the prediction of bone metastases in prostate cancer were investigated. METHODS: TRACP, PACP, ALP, and PSA serum levels were measured in 215 patients with prostate cancer, including 160 without and 55 with bone metastases. Correlation of serum marker levels with bone metastases was assessed using receiver operating characteristics (ROC) analysis. Sensitivity, specificity, accuracy, positive and negative predictive values were calculated for each serum marker. Multivariate stepwise logistic regression analysis was used to identify independent predictors for the presence of bone metastasis. RESULTS: Mean serum TRACP, PACP, ALP, and PSA levels were significantly elevated in patients with bone metastases compared with those without (P < 0.05). PSA and PACP levels increased significantly with clinical stage of the disease, whereas TRACP and ALP levels only increased significantly in stage D2. Serum TRACP levels correlated significantly with extent of disease on bone scans. ROC analyses showed no significant differences in area under the curve for these markers. Logistic regression analysis demonstrated that PSA, ALP, and TRACP were significant predictors of bone metastasis. Predicted and observed risks of bone metastasis were well correlated when TRACP, ALP, and PSA were combined and bone scan could have been omitted in 70% of patients by assessing these three markers. CONCLUSIONS: Serum TRACP can be considered a useful predictor of bone metastases in prostate cancer. A combination of TRACP, ALP, and PSA can obviate the need for a bone scan in 70% of cases.
OBJECTIVE: The clinical value of serum tartrate-resistant acid phosphatase (TRACP), prostate specific antigen (PSA), alkaline phosphatase (ALP), and prostatic acid phosphatase (PACP) for the prediction of bone metastases in prostate cancer were investigated. METHODS: TRACP, PACP, ALP, and PSA serum levels were measured in 215 patients with prostate cancer, including 160 without and 55 with bone metastases. Correlation of serum marker levels with bone metastases was assessed using receiver operating characteristics (ROC) analysis. Sensitivity, specificity, accuracy, positive and negative predictive values were calculated for each serum marker. Multivariate stepwise logistic regression analysis was used to identify independent predictors for the presence of bone metastasis. RESULTS: Mean serum TRACP, PACP, ALP, and PSA levels were significantly elevated in patients with bone metastases compared with those without (P < 0.05). PSA and PACP levels increased significantly with clinical stage of the disease, whereas TRACP and ALP levels only increased significantly in stage D2. Serum TRACP levels correlated significantly with extent of disease on bone scans. ROC analyses showed no significant differences in area under the curve for these markers. Logistic regression analysis demonstrated that PSA, ALP, and TRACP were significant predictors of bone metastasis. Predicted and observed risks of bone metastasis were well correlated when TRACP, ALP, and PSA were combined and bone scan could have been omitted in 70% of patients by assessing these three markers. CONCLUSIONS: Serum TRACP can be considered a useful predictor of bone metastases in prostate cancer. A combination of TRACP, ALP, and PSA can obviate the need for a bone scan in 70% of cases.
Authors: Adam R Metwalli; Inger L Rosner; Jennifer Cullen; Yongmei Chen; Timothy Brand; Stephen A Brassell; James Lesperance; Christopher Porter; Joseph Sterbis; David G McLeod Journal: Urol Oncol Date: 2014-06-11 Impact factor: 3.498
Authors: Allan Lipton; Robert Uzzo; Robert J Amato; Georgiana K Ellis; Behrooz Hakimian; G David Roodman; Matthew R Smith Journal: J Natl Compr Canc Netw Date: 2009-10 Impact factor: 11.908
Authors: Sakthivel Muniyan; Nagendra K Chaturvedi; Jennifer G Dwyer; Chad A Lagrange; William G Chaney; Ming-Fong Lin Journal: Int J Mol Sci Date: 2013-05-21 Impact factor: 5.923
Authors: Harm Westdorp; Annette E Sköld; Berit A Snijer; Sebastian Franik; Sasja F Mulder; Pierre P Major; Ronan Foley; Winald R Gerritsen; I Jolanda M de Vries Journal: Front Immunol Date: 2014-05-06 Impact factor: 7.561
Authors: Sun Min Lim; Youn Nam Kim; Ki Hyun Park; Beodeul Kang; Hong Jae Chon; Chan Kim; Joo Hoon Kim; Sun Young Rha Journal: BMC Cancer Date: 2016-07-04 Impact factor: 4.430