NDLI: Discovery of Prostate Specific Antigen Pattern to Predict Castration Resistant Prostate Cancer of Androgen Deprivation Therapy

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Discovery of Prostate Specific Antigen Pattern to Predict Castration Resistant Prostate Cancer of Androgen Deprivation Therapy

Content Provider	ACM Digital Library
Author	Kim, Yejin Park, Yong Hyun Lee, Ji Youl Choi, In Young Kim, Dong Hyun Yu, Hwanjo
Abstract	We used a longitudinal biomarker, prostate specific antigen (PSA), to discover a new prognostic pattern that predicts castration-resistant prostate cancer (CRPC) after androgen deprivation therapy. PSA is an important biomarker of prostate cancer to monitor the response to the treatment, but existing PSA patterns such as pretreatment PSA level, nadir, time to nadir, and doubling time are computed based on only one or two PSA values before or around nadir, thus PSA has not been fully utilized as a whole sequence. We used 1645 PSA values after nadir from 261 men. We transformed the longitudinal PSA into PSA velocity and discrete sequences of PSA state. We then used frequent sequential pattern mining (PrefixSpan) to find frequent candidate patterns from the sequences. We computed AUC and C-index of the patterns by logistic regression and Cox regression, respectively to find the predictive candidate patterns. Among the candidate patterns, we chose the most informative patterns that were specific and rare because we assumed that the amount of information that a pattern has is large if i) the pattern is not sub-pattern of others, ii) the pattern's interval is shorter (concise) than others, or iii) the frequency of the pattern is less than other patterns. We compared the progression to CRPC of the final predictive and informative pattern with that of pretreatment PSA, nadir, and time to nadir, which are known as prognosis factor of CRPC. We used Kaplan-Meier analysis to test survival difference between patients with and without the pattern. As a result, patients were less likely to be CRPC if, after PSA values reach nadir, the PSA decreases more than 0.048 ng/ml during a month, and the decrease occurs again. After investigating 19 HSPC and 5 CRPC candidate patterns of PSA after nadir, we found that the two declines pattern significantly increased the accuracy of predicting CRPC by supplementing information provided by existing PSA patterns such as pretreatment PSA. The AUC and C-index of this pattern was 0.82 and 0.77, respectively, which was comparably higher than that of other candidate patterns. The occurrence of two substantial declines after PSA nadir implies that PSA fluctuates after nadir. PSA might increase due to some reasons such as intermittent treatment, and decline as sensitively reacting to ADT. This result can help clinicians to stratify men by the risk of CRPC and to determine the patient that needs intensive follow-up.
Starting Page	13
Ending Page	13
Page Count	1
File Format	PDF
ISBN	9781450337878
DOI	10.1145/2811163.2811166
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-10-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Prostate specific antigen Frequent sequential pattern mining Prediction Longitudinal biomarker
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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