Prostate Specific Antigen‐Growth Curve Model to Predict High‐Risk Prostate Cancer. Issue 2 (4th October 2016)
- Record Type:
- Journal Article
- Title:
- Prostate Specific Antigen‐Growth Curve Model to Predict High‐Risk Prostate Cancer. Issue 2 (4th October 2016)
- Main Title:
- Prostate Specific Antigen‐Growth Curve Model to Predict High‐Risk Prostate Cancer
- Authors:
- Shoaibi, Azza
Rao, Gowtham A.
Cai, Bo
Rawl, John
Haddock, Kathlyn Sue
Hébert, James R. - Abstract:
- Abstract : PURPOSE: To investigate if a prostate specific antigen (PSA)‐derived growth curve can predict the occurrence of high‐risk prostate cancer (PrCA). METHODS: Data from 38, 340 men randomized to the PrCA screening arm in the prostate, lung, colorectal, and ovarian cancer screening trial (PLCO) were used to develop a PSA growth curve model to estimate PSA rate of change. The model was then used to predict high‐risk PrCA in clinical data available from 680, 390 veterans seeking routine care. The PSA growth curve was modeled using non‐linear mixed regression and the PSA rate was estimated by taking the 1st derivative of the growth curve equation at 1 year prior to diagnosis/exit. RESULTS: In the PLCO, PrCA incidence was 8.1%; ≈19% of whom had high‐risk PrCA. Overall, a PSA rate threshold of 0.37 ng/ml/year had the best combination of sensitivity (97.2%) and specificity (97.3%) for detecting high‐risk PrCA. In the VA data; 7, 347 men were diagnosed with PrCA; of these 4, 315 (58.7%) were diagnosed with high‐risk PrCA. The PLCO optimal threshold of 0.37 ng/ml/year produced sensitivity = 95.5% and specificity = 85.2%. An optimal threshold of 0.99 ng/ml/year in AA produced sensitivity = 89.1% and specificity = 80.0%. PSA rate was a better predictor than the single last PSA value. CONCLUSIONS: PSA growth curves predicted high‐risk PrCA in the PLCO data. Fitting the same algorithm in the VA data produced lower specificity. Although encouraging, this finding underlines the needAbstract : PURPOSE: To investigate if a prostate specific antigen (PSA)‐derived growth curve can predict the occurrence of high‐risk prostate cancer (PrCA). METHODS: Data from 38, 340 men randomized to the PrCA screening arm in the prostate, lung, colorectal, and ovarian cancer screening trial (PLCO) were used to develop a PSA growth curve model to estimate PSA rate of change. The model was then used to predict high‐risk PrCA in clinical data available from 680, 390 veterans seeking routine care. The PSA growth curve was modeled using non‐linear mixed regression and the PSA rate was estimated by taking the 1st derivative of the growth curve equation at 1 year prior to diagnosis/exit. RESULTS: In the PLCO, PrCA incidence was 8.1%; ≈19% of whom had high‐risk PrCA. Overall, a PSA rate threshold of 0.37 ng/ml/year had the best combination of sensitivity (97.2%) and specificity (97.3%) for detecting high‐risk PrCA. In the VA data; 7, 347 men were diagnosed with PrCA; of these 4, 315 (58.7%) were diagnosed with high‐risk PrCA. The PLCO optimal threshold of 0.37 ng/ml/year produced sensitivity = 95.5% and specificity = 85.2%. An optimal threshold of 0.99 ng/ml/year in AA produced sensitivity = 89.1% and specificity = 80.0%. PSA rate was a better predictor than the single last PSA value. CONCLUSIONS: PSA growth curves predicted high‐risk PrCA in the PLCO data. Fitting the same algorithm in the VA data produced lower specificity. Although encouraging, this finding underlines the need for further research to prospectively test the algorithm, especially for African‐American men, the population group at highest risk of aggressive PrCA. Prostate 77:173–184, 2017 . © 2016 Wiley Periodicals, Inc. … (more)
- Is Part Of:
- Prostate. Volume 77:Issue 2(2017)
- Journal:
- Prostate
- Issue:
- Volume 77:Issue 2(2017)
- Issue Display:
- Volume 77, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 77
- Issue:
- 2
- Issue Sort Value:
- 2017-0077-0002-0000
- Page Start:
- 173
- Page End:
- 184
- Publication Date:
- 2016-10-04
- Subjects:
- PSA rate -- prostate cancer screening -- mixed modle
Prostate -- Diseases -- Periodicals
616 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0045 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/pros.23258 ↗
- Languages:
- English
- ISSNs:
- 0270-4137
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6935.194000
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- 518.xml