Objectives We assessed the inter-method bias of total (tPSA) and free (fPSA) prostate-specific antigen (PSA) immunoassays to establish if tPSA-based risk thresholds for advanced prostate cancer (PCa), obtained from one method (Roche) can be converted into the corresponding concentrations assayed by other methods. Then we evaluated the impact of the bias of tPSA and fPSA on the estimation of the %f/tPSA ratio and performed a re-calibration of the proposed thresholds for the %f/tPSA ratio according to the assay used. Methods tPSA and fPSA were measured in 135 and 137 serum samples, respectively by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM analytical platforms. Scatterplots, Bland-Altman diagrams, Passing-Bablok (PB) were used to inspect and estimate the systematic and proportional bias between the methods. The linear equations with confidence intervals of the parameter estimates were used to transform the tPSA risk thresholds for advanced PCa into the corresponding concentrations measurable by the other analytical methods. To construct a correction coefficient for converting the %f/tPSA ratio from one method to the other, PB and non-parametric boostrapping were used. Results The inter-method bias is not constant but strictly linear allowing the conversion of PSA results obtained from Roche into the other assays, which underestimate tPSA vs. Roche. Siemens and Abbott vs. Roche and Beckman assays, being characterized by a positive and a negative proportional bias for tPSA and fPSA measurements, tend to overestimate the %f/tPSA ratio. Conclusions There is a consistent risk to miss advanced PCa, if appropriate conversion factors are not applied.

Managing the impact of inter-method bias of prostate specific antigen assays on biopsy referral: the key to move towards precision health in prostate cancer management / S. Ferraro, G. Biganzoli, M. Bussetti, S. Castaldi, E.M. Biganzoli, M. Plebani. - In: CLINICAL CHEMISTRY AND LABORATORY MEDICINE. - ISSN 1434-6621. - 61:1(2023), pp. 142-153. [10.1515/cclm-2022-0874]

Managing the impact of inter-method bias of prostate specific antigen assays on biopsy referral: the key to move towards precision health in prostate cancer management

S. Ferraro
Primo
;
G. Biganzoli
Secondo
;
M. Bussetti;S. Castaldi;E.M. Biganzoli
Penultimo
;
2023

Abstract

Objectives We assessed the inter-method bias of total (tPSA) and free (fPSA) prostate-specific antigen (PSA) immunoassays to establish if tPSA-based risk thresholds for advanced prostate cancer (PCa), obtained from one method (Roche) can be converted into the corresponding concentrations assayed by other methods. Then we evaluated the impact of the bias of tPSA and fPSA on the estimation of the %f/tPSA ratio and performed a re-calibration of the proposed thresholds for the %f/tPSA ratio according to the assay used. Methods tPSA and fPSA were measured in 135 and 137 serum samples, respectively by Abbott Alinity i, Beckman Access Dxl, Roche Cobas e801, and Siemens Atellica IM analytical platforms. Scatterplots, Bland-Altman diagrams, Passing-Bablok (PB) were used to inspect and estimate the systematic and proportional bias between the methods. The linear equations with confidence intervals of the parameter estimates were used to transform the tPSA risk thresholds for advanced PCa into the corresponding concentrations measurable by the other analytical methods. To construct a correction coefficient for converting the %f/tPSA ratio from one method to the other, PB and non-parametric boostrapping were used. Results The inter-method bias is not constant but strictly linear allowing the conversion of PSA results obtained from Roche into the other assays, which underestimate tPSA vs. Roche. Siemens and Abbott vs. Roche and Beckman assays, being characterized by a positive and a negative proportional bias for tPSA and fPSA measurements, tend to overestimate the %f/tPSA ratio. Conclusions There is a consistent risk to miss advanced PCa, if appropriate conversion factors are not applied.
cancer; harmonization; immunoassay; predictive value; risk
Settore MED/01 - Statistica Medica
2023
2-nov-2022
Article (author)
File in questo prodotto:
File Dimensione Formato  
10.1515_cclm-2022-0874.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Dimensione 1.33 MB
Formato Adobe PDF
1.33 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/952999
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 4
social impact