BACKGROUND: Inappropriate quality management of reverse transcription-PCR (RT-PCR) assays for the detection of blood-borne prostate cancer (PCa) cells hampers clinical conclusions. Improvement of the RT-PCR methodology for prostate-specific antigen (PSA) mRNA should focus on an appropriate numeric definition of the performance of the assay and correction for PSA mRNA that is not associated with PCa cells. METHODS AND RESULTS: Repeated (RT-)PCR tests for PSA mRNA in single blood specimens from PCa patients and PCa-free controls, performed by four international institutions, showed a large percentage (approximately equal to 50%) of divergent test results. The best estimates of the mean, lambda (SD), of the expected Poisson frequency distributions of the number of positive tests among five replicate assays of samples from PCa-free individuals were 1.0 (0.2) for 2 x 35 PCR cycles and 0.2 (0.1) for 2 x 25 PCR cycles. Assessment of the numeric value of the mean can be considered as a new indicator of the performance of a RT-PCR assay for PSA mRNA under clinical conditions. Moreover, it determines the required number of positive test repetitions to differentiate between true and false positives for circulating prostate cells. At a predefined diagnostic specificity of > or = 98%, repeated PCRs with lambda of either 1.0 or 0.2 require, respectively, more than three or more than one positive tests to support the conclusion that PSA mRNA-containing cells are present. CONCLUSIONS: Repeated nested PCR tests for PSA and appropriate handling of the data allow numeric quantification of the performance of the assay and differentiation between analytical false and true positives at a predefined accuracy. This new approach may contribute to introduction of PSA RT-PCR assays in clinical practice.
BACKGROUND: Inappropriate quality management of reverse transcription-PCR (RT-PCR) assays for the detection of blood-borne prostate cancer (PCa) cells hampers clinical conclusions. Improvement of the RT-PCR methodology for prostate-specific antigen (PSA) mRNA should focus on an appropriate numeric definition of the performance of the assay and correction for PSA mRNA that is not associated with PCa cells. METHODS AND RESULTS: Repeated (RT-)PCR tests for PSA mRNA in single blood specimens from PCa patients and PCa-free controls, performed by four international institutions, showed a large percentage (approximately equal to 50%) of divergent test results. The best estimates of the mean, lambda (SD), of the expected Poisson frequency distributions of the number of positive tests among five replicate assays of samples from PCa-free individuals were 1.0 (0.2) for 2 x 35 PCR cycles and 0.2 (0.1) for 2 x 25 PCR cycles. Assessment of the numeric value of the mean can be considered as a new indicator of the performance of a RT-PCR assay for PSA mRNA under clinical conditions. Moreover, it determines the required number of positive test repetitions to differentiate between true and false positives for circulating prostate cells. At a predefined diagnostic specificity of > or = 98%, repeated PCRs with lambda of either 1.0 or 0.2 require, respectively, more than three or more than one positive tests to support the conclusion that PSA mRNA-containing cells are present. CONCLUSIONS: Repeated nested PCR tests for PSA and appropriate handling of the data allow numeric quantification of the performance of the assay and differentiation between analytical false and true positives at a predefined accuracy. This new approach may contribute to introduction of PSA RT-PCR assays in clinical practice.
Authors: Giuliana Giribaldi; Simone Procida; Daniela Ulliers; Franca Mannu; Roberta Volpatto; Giorgia Mandili; Laura Fanchini; Oscar Bertetto; Gianruggero Fronda; Luigi Simula; Elena Rimini; Giovanni Cherchi; Lisa Bonello; Milena Maria Maule; Francesco Turrini Journal: J Mol Diagn Date: 2006-02 Impact factor: 5.568
Authors: Sung Han Kim; Weon Seo Park; Sang Jin Lee; Moon Kyung Choi; Seung Min Yeon; Jeong Nam Joo; Ara Ko; Eun Sik Lee; Jae Young Joung; Ho Kyung Seo; Jinsoo Chung; Kang Hyun Lee Journal: Biomed Res Int Date: 2015-10-07 Impact factor: 3.411
Authors: Samar Damiati; Martin Peacock; Stefan Leonhardt; Laila Damiati; Mohammed A Baghdadi; Holger Becker; Rimantas Kodzius; Bernhard Schuster Journal: Genes (Basel) Date: 2018-02-14 Impact factor: 4.096