Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer
•MiCheck® Prostate was developed to identify men with clinically significant prostate cancer.•The MiCheck® algorithm combines three blood marker results and a DRE result to give a risk score.•The test has AUC 0.85, sensitivity 95% and specificity 50% for clinically significant prostate cancer. There...
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Published in | Urologic oncology Vol. 41; no. 11; pp. 454.e9 - 454.e16 |
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Main Authors | , , , , , , , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
01.11.2023
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Abstract | •MiCheck® Prostate was developed to identify men with clinically significant prostate cancer.•The MiCheck® algorithm combines three blood marker results and a DRE result to give a risk score.•The test has AUC 0.85, sensitivity 95% and specificity 50% for clinically significant prostate cancer.
There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer.
To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set.
About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.
Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm.
Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer.
The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10.
The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis. |
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AbstractList | •MiCheck® Prostate was developed to identify men with clinically significant prostate cancer.•The MiCheck® algorithm combines three blood marker results and a DRE result to give a risk score.•The test has AUC 0.85, sensitivity 95% and specificity 50% for clinically significant prostate cancer.
There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer.
To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set.
About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.
Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm.
Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer.
The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10.
The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis. BACKGROUNDThere is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer.OBJECTIVESTo further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set.DESIGN, SETTINGS, AND PARTICIPANTSAbout 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP.METHODSSerum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm.OUTCOME MEASUREMENTS AND STATISTICAL ANALYSISLogistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer.RESULTSThe MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10.CONCLUSIONSThe MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis. There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant prostate cancer (CSCaP). We have previously reported the development of the MiCheck® Test for clinically significant prostate cancer. Here, we report MiCheck's further development and incorporation of the Roche Cobas standard clinical chemistry analyzer. To further develop and adapt the MiCheck® Prostate test so it can be performed using a standard clinical chemistry analyzer and characterize its performance using the MiCheck-01 clinical trial sample set. About 358 patient samples from the MiCheck-01 US clinical trial were used for the development of the MiCheck® Prostate test. These consisted of 46 controls, 137 non-CaP, 62 non-CSCaP, and 113 CSCaP. Serum analyte concentrations for cellular growth factors were determined using custom-made Luminex-based R&D Systems multi-analyte kits. Analytes that can also be measured using standard chemistry analyzers were examined for their ability to contribute to an algorithm with high sensitivity for the detection of clinically significant prostate cancer. Samples were then re-measured using a Roche Cobas analyzer for development of the final algorithm. Logistic regression modeling with Monte Carlo cross-validation was used to identify Human Epidydimal Protein 4 (HE4) as an analyte able to significantly improve the algorithm specificity at 95% sensitivity. A final model was developed using analyte measurements from the Cobas analzyer. The MiCheck® logistic regression model was developed and consisted of PSA, %free PSA, DRE, and HE4. The model differentiated clinically significant cancer from no cancer or not-clinically significant cancer with AUC of 0.85, sensitivity of 95%, and specificity of 50%. Applying the MiCheck® test to all evaluable 358 patients from the MiCheck-01 study demonstrated that up to 50% of unnecessary biopsies could be avoided while delaying diagnosis of only 5.3% of Gleason Score (GS) ≥3+4 cancers, 1.8% of GS≥4+3 cancers and no cancers of GS 8 to 10. The MiCheck® Prostate test identifies clinically significant prostate cancer with high sensitivity and negative predictive value (NPV). It can be performed in a clinical laboratory using a Roche Cobas clinical chemistry analyzer. The MiCheck® Prostate test could assist in reducing unnecessary prostate biopsies with a marginal number of patients experiencing a delayed diagnosis. |
Author | Bailen, James L. Concepcion, Raoul S. Siddireddy, Jaya Sowjanya Walsh, Bradley J. Henderson, R. Jonathan Wissmueller, Sandra Chan, Daniel W. Shore, Neal D. Le, Thao Ho Gillatt, David A. Lu, Yanling Saltzstein, Daniel R. Levin, Rachel A. Polikarpov, Dmitry M. Deng, Niantao Ruterbusch, Julie J. Campbell, Douglas H. Beebe-Dimmer, Jennifer L. Pieczonka, Christopher M. |
Author_xml | – sequence: 1 givenname: Neal D. surname: Shore fullname: Shore, Neal D. email: nshore@gsuro.com organization: CUSP LLC Research Consortium, Annandale, VA – sequence: 2 givenname: Dmitry M. surname: Polikarpov fullname: Polikarpov, Dmitry M. organization: Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia – sequence: 3 givenname: Christopher M. surname: Pieczonka fullname: Pieczonka, Christopher M. organization: Corporate Director of Research of US Urology Partners and Co-Director of Research of Associated Medical Professionals – sequence: 4 givenname: R. Jonathan surname: Henderson fullname: Henderson, R. Jonathan organization: CUSP LLC Research Consortium, Annandale, VA – sequence: 5 givenname: James L. surname: Bailen fullname: Bailen, James L. organization: CUSP LLC Research Consortium, Annandale, VA – sequence: 6 givenname: Daniel R. surname: Saltzstein fullname: Saltzstein, Daniel R. organization: CUSP LLC Research Consortium, Annandale, VA – sequence: 7 givenname: Raoul S. surname: Concepcion fullname: Concepcion, Raoul S. organization: CUSP LLC Research Consortium, Annandale, VA – sequence: 8 givenname: Jennifer L. surname: Beebe-Dimmer fullname: Beebe-Dimmer, Jennifer L. organization: Barbara Ann Karmanos Cancer Institute and Wayne State University School of Medicine Department of Oncology, Detroit, MI – sequence: 9 givenname: Julie J. surname: Ruterbusch fullname: Ruterbusch, Julie J. organization: Barbara Ann Karmanos Cancer Institute and Wayne State University School of Medicine Department of Oncology, Detroit, MI – sequence: 10 givenname: Rachel A. surname: Levin fullname: Levin, Rachel A. organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 11 givenname: Sandra surname: Wissmueller fullname: Wissmueller, Sandra organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 12 givenname: Thao Ho surname: Le fullname: Le, Thao Ho organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 13 givenname: David A. surname: Gillatt fullname: Gillatt, David A. organization: Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia – sequence: 14 givenname: Daniel W. surname: Chan fullname: Chan, Daniel W. organization: Center for Biomarker Discovery and Translation, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD – sequence: 15 givenname: Niantao surname: Deng fullname: Deng, Niantao organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 16 givenname: Jaya Sowjanya surname: Siddireddy fullname: Siddireddy, Jaya Sowjanya organization: Faculty of Medicine and Health Sciences, Macquarie University, Sydney, Australia – sequence: 17 givenname: Yanling surname: Lu fullname: Lu, Yanling organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 18 givenname: Douglas H. surname: Campbell fullname: Campbell, Douglas H. organization: Minomic International Ltd., Sydney, NSW, Australia – sequence: 19 givenname: Bradley J. surname: Walsh fullname: Walsh, Bradley J. organization: Minomic International Ltd., Sydney, NSW, Australia |
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Snippet | •MiCheck® Prostate was developed to identify men with clinically significant prostate cancer.•The MiCheck® algorithm combines three blood marker results and a... There is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically significant... BACKGROUNDThere is a clinical need to identify patients with an elevated PSA who would benefit from prostate biopsy due to the presence of clinically... |
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SubjectTerms | Biomarker Biopsy Clinical study Clinically significant cancer Humans Male NPV Predictive Value of Tests Prostate Prostate - pathology Prostate-Specific Antigen Prostatic Neoplasms - pathology |
Title | Development and evaluation of the MiCheck® Prostate test for clinically significant prostate cancer |
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