Journal
CLINICAL CHEMISTRY
Volume 54, Issue 1, Pages 44-52Publisher
AMER ASSOC CLINICAL CHEMISTRY
DOI: 10.1373/clinchem.2007.091470
Keywords
-
Categories
Funding
- NATIONAL CANCER INSTITUTE [P30CA006973, U24CA086359, U01CA084986, U01CA086368, U01CA084968, U01CA085067, P50CA058236, U01CA086402, U24CA086368, U01CA086323] Funding Source: NIH RePORTER
- NCI NIH HHS [U01 CA086402, U01 CA085067, U01 CA086323, CA 86368, P30 CA006973, CA 084986, U24 CA086359, CA 85067, U01 CA084986, CA 84968, P50 CA058236, U24 CA086368, U01 CA086368, CA 86359, CA 86402, CA 86323, U01 CA084968] Funding Source: Medline
Ask authors/readers for more resources
BACKGROUND: This report and a companion report describe a validation of the ability of serum proteomic profiling via SELDI-TOF mass spectrometry to detect prostatic cancer. Details of this 3-stage process have been described. This report describes the development of the algorithm and results of the blinded test for stage 1. METHODS: We derived the decision algorithm used in this study from the analysis of serum samples from patients with prostate cancer (n = 181) and benign prostatic hyperplasia (BPH) (n 143) and normal controls (n = 220). We also derived a validation test set from a separate, geographically diverse set of serum samples from 42 prostate cancer patients and 42 controls without prostate cancer. Aliquots were subjected to randomization and blinded analysis, and data from each laboratory site were subjected to the decision algorithm and decoded. RESULTS: Using the data collected from the validation test set, the decision algorithm was unsuccessful in separating cancer from controls with any predictive utility. Analysis of the experimental data revealed potential sources of bias. CONCLUSION: The ability of the decision algorithm to successfully differentiate between prostate cancer, BPH, and control samples using data derived from serum protein profiling was compromised by bias. (c) 2007 American Association for Clinical Chemistry.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available