Preanalytical stability of molecular forms of prostate-specific antigen in serum samples (PSA, free PSA, [-2]proPSA) and their impact on fPSA/tPSA ratio and PHI

BACKGROUND

Prostate cancer is a common cancer in men. Detection methods include the measurement of biomarkers: prostate-specific antigen (PSA), free PSA, [-2]proPSA, and the calculated indices: fPSA/tPSA ratio and Prostate Health Index (PHI). Proper preanalytical conditions are crucial for precise measurement and failure to adhere to protocols or regulations can influence the diagnostic algorithm. We assessed the stability of the above-mentioned biomarkers, fPSA/tPSA ratio and PHI, under various pre-analytical conditions.

METHODS

Serum samples from 45 males were collected and stored under specific conditions before tPSA, fPSA, and [-2]proPSA were measured. Subsequently, the fPSA/tPSA and PHI were calculated.

RESULTS

tPSA, fPSA, and [-2]proPSA remained stable during the two freeze-thaw cycles. Storage at 4°C and 22°C resulted in stable tPSA concentrations. However, fPSA levels decreased and [-2]proPSA levels increased over time. The fPSA/tPSA ratio remained stable for 72 h, at which point a decrease was observed in the samples kept at 4°C and 22°C. A gradual increase in PHI was observed in the samples kept at 4°C and 22°C.

CONCLUSIONS

All biomarkers remained stable during two freeze-thaw cycles. tPSA was the most stable analyte when stored at 4°C, as well as at RT. A gradual increase of [-2]proPSA and a slight decrease in fPSA were observed during the storage test. This led to a decrease in the fPSA/tPSA ratio and an elevation in the PHI. We therefore recommend measuring prostate biomarkers promptly following blood collection.

IMPACT

Understanding the pre-analytical stability of prostate biomarkers helps prevent false positive results and improve the accuracy of diagnostics for prostate cancer.

Assessment of factors associated with PSA level in prostate cancer cases and controls from three geographical regions

It is being debated whether prostate-specific antigen (PSA)-based screening effectively reduces prostate cancer mortality. Some of the uncertainty could be related to deficiencies in the age-based PSA cut-off thresholds used in screening. Current study considered 2779 men with prostate cancer and 1606 men without a cancer diagnosis, recruited for various studies in New Zealand, US, and Taiwan. Association of PSA with demographic, lifestyle, clinical characteristics (for cases), and the aldo–keto reductase 1C3 (AKR1C3) rs12529 genetic polymorphisms were analysed using multiple linear regression and univariate modelling. Pooled multivariable analysis of cases showed that PSA was significantly associated with demographic, lifestyle, and clinical data with an interaction between ethnicity and age further modifying the association. Pooled multivariable analysis of controls data also showed that demographic and lifestyle are significantly associated with PSA level. Independent case and control analyses indicated that factors associated with PSA were specific for each cohort. Univariate analyses showed a significant age and PSA correlation among all cases and controls except for the US-European cases while genetic stratification in cases showed variability of correlation. Data suggests that unique PSA cut-off thresholds factorized with demographics, lifestyle and genetics may be more appropriate for prostate cancer screening.

Verification of Harmonization of Serum Total and Free Prostate-Specific Antigen (PSA) Measurements and Implications for Medical Decisions

BACKGROUND

Previous studies have shown that the harmonization of prostate-specific antigen (PSA) assays remained limited even after the introduction of WHO International Standards. This information needs updating for current measuring systems (MS) and reevaluation according to established analytical performance specifications (APS) and the characteristics of antibodies used.

METHODS

Total (tPSA) and free (fPSA) PSA were measured in 135 and 137 native serum samples, respectively, by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM MSs. Passing-Bablok regression and difference plots were used to compare results from each MS to the all-method median values. Agreement among methods was evaluated against APS for bias derived from biological variation of the 2 measurands.

RESULTS

The median interassay CV for tPSA MSs (11.5%; 25-75th percentiles, 9.2-13.4) fulfilled the minimum APS goal for intermethod bias (15.9%), while the interassay CV for fPSA did not [20.4% (25-75th percentiles, 18.4-22.7) vs goal 17.6%]. Considering the all-method median value of each sample as reference, all tPSA MSs exhibited a mean percentage bias within the minimum goal. On the other hand, Alinity (+21.3%) and Access (-24.2%) were out of the minimum bias goal for fPSA, the disagreement explained only in minimal part by the heterogeneity of employed antibodies.

CONCLUSIONS

The harmonization among tPSA MSs is acceptable only when minimum APS are applied and necessitates further improvement. The marked disagreement among fPSA MSs questions the use of fPSA as a second-level test for biopsy referral.