Prostate-specific antigen detection by using a reusable amperometric immunosensor based on reversible binding and leasing of HRP-anti-PSA from phenylb

In recent years, many automated immunoassay analyzers have been developed for accurate diagnosis of various disease states and to improve effective drug administration. Amperometric immunoassay has been increasingly applied to laboratory medicine due to its ease in automation, rapid speed and low detection limits. It is important to develop reusable immunologically-sensitive elements for prostate-specific antigen (PSA) detection.

The strategy for the immunosensor construction is based on the enzyme-conjugated prostate-specific antibody (HRP-anti-PSA) reversible binding with a self-assembled phenylboronic acid monolayer on gold.

After incubating an HRP-anti-PSA modified electrode in a prostate-specific antigen (PSA) solution, a decrease in the electrocatalytic response of the HRP-anti-PSA modified electrode to the reduction of H2O2 is observed. The photometric activity assays show that this decrease of the electrocatalytic response arises from the formation of immunocomplexes of HRP-conjugated anti-PSA and its antigen, not from the loss of bound HRP-anti-PSA from the electrode surface. Analytical performances and optimal conditions of the described immunosensor are also investigated. Under the optimal conditions, the amperometric immunosensor shows a linear increase of the relative intensity in 2 PSA concentration range from 2 to 15 ng/ml and 15 to 120 ng/ml, respectively.

This method could be used for rapid analysis of prostate-specific antigen (PSA) and potentially other antigens.


Negative influence of changing biopsy practice patterns on the predictive value of prostate-specific antigen for cancer detection on prostate biopsy.

BACKGROUND: A correlation between prostate specific antigen (PSA) level and positive prostate biopsy rate was established in an era when biopsy practice patterns were different from what they are today. We evaluated if changes in biopsy practice patterns have affected the ability of PSA to predict cancer detection on prostate biopsy in the current era.

METHODS: Of 3634 prostate biopsies performed from 1993-2005, 1607 met criteria for analysis. Biopsy data were divided into 3 time-cohorts (1993-1997, 1998-2001, and 2002-2005) to assess for practice patterns shifts and correlation between PSA and biopsy results.

RESULTS: Significant changes in biopsy practice patterns included an increase in biopsy cores and more frequent use of PSA 2.5-3.99 ng/mL as a biopsy indication. In men with normal DRE, a moderate correlation between PSA and positive biopsy rate did exist from 1993-1997, but was subsequently lost. On multivariate analysis, prostate specific antigen (PSA) was not a significant predictor of biopsy result in men with normal DRE.

CONCLUSIONS: Early in the PSA era, the predictive power of PSA depended on multiple factors: high prevalence of disease, higher prevalence of high-grade disease, and low likelihood of prostate cancer diagnosis in men with low PSA. Now, beyond the culling effect of increased biopsy incidence and with shifted biopsy practice patterns, the correlation between PSA and biopsy result is lost in men with normal DRE. Diagnosing a higher proportion of tumors in men with a PSA between 2.0-4.0 ng/mL has negatively influenced the predictive value of prostate specific antigen (PSA) for cancer detection.

Hierarchical Changepoint Models for Biochemical Markers Illustratedby Tracking Postradiotherapy Prostate-Specific Antigen Series inMen With Prostate C

PURPOSE: Biomarkers provide valuable information when detecting disease onset or monitoring diseaseprogression; examples include bone mineral density (for osteoporosis), cholesterol (for coronary artery dis-eases), or prostate-specific antigens (PSA, for prostate cancer). Characteristics of markers series can then beused as prognostic factors of disease progression, such as the postradiotherapy PSA doubling time in mentreated for prostate cancer. The statistical analysis of such data has to incorporate the within and be-tween-series variabilities, the complex patterns of the series over time, the unbalanced format of thedata, and the possibly nonconstant precision of the measurements.

METHODS: We base our analysis on a population-based cohort of 470 men treated with radiotherapy forprostate cancer; after treatment, the log2PSA concentrations follow a piecewise-linear pattern. We illus-trate the flexibility of Bayesian hierarchical changepoint models by estimating the individual and popula-tion postradiotherapy log2PSA profiles; parameters such as the PSA nadir and the PSA doubling time wereestimated, and their associations with baseline patient characteristics were investigated. The residual PSA variability was modeled as a function of the prostate-specific antigen concentration. For comparison purposes, two alternative models were briefly considered.

RESULTS: Precise estimates of all parameters of the PSA trajectory are provided at both the individualand population levels. Estimates suggest greater PSA variability at lower PSA concentrations, as well as anassociation between shorter PSAdts and greater baseline PSA levels, higher Gleason scores, and older age.

CONCLUSIONS: The use of Bayesian hierarchical changepoint models accommodates multiple com-plex features of longitudinal data, permits realistic modeling of the variability as a function of the markerconcentration, and provides precise estimates of all clinically important parameters. This type of model should be applicable to the study of marker series in other diseases.