S2,3PSA% as a predictor of reclassification of 1st protocol biopsy on active surveillance for early-stage prostate cancer patients: From the PRIAS-JAPAN study.

T Takuma Kato T Tohru Yoneyama (Hirosaki University Graduate School of Medicine, Hirosaki, Japan) S Shingo Hatakeyama Y Yoichiro Tohi (Kagawa University, Kita-Gun, Japan) R Ryuji Matsumoto (Hokkaido University, Sapporo-Shi, Japan) T Takuma Sato K Katsuyoshi Hashine T Takahiro Kimura T Toshiki Tanikawa (Niigata Cancer Center Hospital, Niigata, Japan) T Takayuki Goto M Masaharu Inoue (Saitama Cancer Center, Saitama, Japan) K Kohei Hashimoto C Chikara Ohyama M Mikio Sugimoto (Kagawa University, Kagawa, Japan)

Abstract

358 Background: Recently, α2,3-sialylated prostate-specific antigen (S2,3PSA)% has been developed as a new serum biomarker for Prostate cancer (PCa). So, we aimed to investigate S2,3 PSA% to predict reclassification of the first repeat protocol biopsy (1st re-PBx) on Active surveillance (AS) for PCa patients. Methods: Patients who participated in PRIAS-JAPAN and its ancillary studies from August 2013 to January 2022 and met the following criteria were included: clinical stage: T1c/T2, PSA: <10ng/ml, PSA density: <0.2ng/ml/cc, number of positive cores: <2, Gleason score: <6. All participants were required to receive a blood sampling test on a protocol visit at inclusion and at the 1st re-PBx. Significant predictors of reclassification in 1st re-PBx were investigated in univariate and multivariate analyses by logistic regression analysis. Then, to assess the predictive power and thresholds for reclassification, we plotted Receiver Operating Characteristic (ROC) curves. Further, a decision curve analysis (DCA) was conducted to identify net benefits. Results: A total of 188 patients were analyzed. Reclassification was shown in 61 patients (32.4%). Both univariate and multivariate analysis by logistic regression analysis showed that S2,3PSA% at diagnosis and before 1st re-biopsy were both significant predictors of reclassification. In ROC analysis, S2,3 PSA% at diagnosis and before 1st re-biopsy had comparable predictive power. The AUC for S2,3PSA% before 1st re-biopsy was 0.63, with a sensitivity of 0.41 and specificity of 0.87. Analysis of the net benefit of PSA doubling time (PSADT) and S2,3PSA% with DCA using PSA, prostate volume, and age as the base model showed that S2,3PSA% had a higher net benefit than PSADT. Conclusions: S2,3PSA% before 1st re-PBx has a high net benefit for reclassification and is a useful tool for clinical decision making. Result of ROC curve analysis and decision curve analysis about S2,3PSA% for reclassification at 1st repeat biopsy. ROC curves about reclassification for differences in S2,3PSA% between baseline and before the 1st repeat PBx Variable AUC Standard Error p value (for AUC) 95% CI Optimal cut off point Sensitivity Specificity p value (vs baseline) S2,3PSA%(baseline) 0.65 0.05 <0.001 0.56 - 0.74 44.3 54.1% 75.6% - S2,3PSA%(before 1yr PBx) 0.63 0.05 0.0065 0.54 - 0.72 1.64 41.0% 87.4% 0.33 Decision curve analysis for reclassification at 1st repeat biopsy High Risk Threshold 0 0.1 0.2 0.3 0.4 0.5 Baseline model* 1 0.769 0.488 0.222 0.044 -0.016 Baseline model+PSADT** 1 0.77 0.492 0.29 0.011 -0.016 Baseline model+S2, 3PSA%** 1 0.769 0.504 0.215 0.186 0.131 *Baseline model is composed of age, prostate volume and PSA before 1yr PBx. **The value of PSADT and S2,3PSA% are calculated by the data before 1yr PBx.

Article Details

Volume / Issue Vol. 43, Issue 5_suppl
Published February 10, 2025
Pages 358-358
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (14)

T

Takuma Kato

T

Tohru Yoneyama

Hirosaki University Graduate School of Medicine, Hirosaki, Japan

S

Shingo Hatakeyama

Y

Yoichiro Tohi

Kagawa University, Kita-Gun, Japan

R

Ryuji Matsumoto

Hokkaido University, Sapporo-Shi, Japan

T

Takuma Sato

K

Katsuyoshi Hashine

T

Takahiro Kimura

T

Toshiki Tanikawa

Niigata Cancer Center Hospital, Niigata, Japan

T

Takayuki Goto

M

Masaharu Inoue

Saitama Cancer Center, Saitama, Japan

K

Kohei Hashimoto

C

Chikara Ohyama

M

Mikio Sugimoto

Kagawa University, Kagawa, Japan