Refined Analysis of Prostate-specific Antigen Kinetics to Predict Prostate Cancer Active Surveillance Outcomes

被引:37
作者
Cooperberg, Matthew R. [1 ,2 ]
Brooks, James D. [3 ]
Faino, Anna, V [4 ]
Newcomb, Lisa F. [5 ,6 ]
Kearns, James T. [6 ]
Carroll, Peter R. [1 ]
Dash, Atreya [6 ]
Etzioni, Ruth [4 ]
Fabrizio, Michael D. [7 ]
Gleave, Martin E. [8 ]
Morgan, Todd M. [9 ]
Nelson, Peter S. [10 ]
Thompson, Ian M. [11 ]
Wagner, Andrew A. [12 ]
Lin, Daniel W. [5 ,6 ]
Zheng, Yingye [4 ]
机构
[1] Univ Calif San Francisco, Dept Urol, Helen Diller Family Comprehens Canc Ctr, San Francisco, CA USA
[2] Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USA
[3] Stanford Univ, Dept Urol, Stanford, CA 94305 USA
[4] Fred Hutchinson Canc Res Ctr, Publ Hlth Sci, Biostat Program, 1124 Columbia St, Seattle, WA 98104 USA
[5] Fred Hutchinson Canc Res Ctr, Publ Hlth Sci, Canc Prevent Program, 1124 Columbia St, Seattle, WA 98104 USA
[6] Univ Washington, Dept Urol, Seattle, WA 98195 USA
[7] Eastern Virginia Med Sch, Dept Urol, Virginia Beach, VA USA
[8] Univ British Columbia, Dept Urol Sci, Vancouver, BC, Canada
[9] Univ Michigan, Dept Urol, Ann Arbor, MI 48109 USA
[10] Fred Hutchinson Canc Res Ctr, Div Human Biol, 1124 Columbia St, Seattle, WA 98104 USA
[11] CHRISTUS Med Ctr Hosp, San Antonio, TX USA
[12] Beth Israel Deaconess Med Ctr, Div Urol, Boston, MA 02215 USA
关键词
Prostate-specific antigen; Kinetics; Prostate cancer; Active surveillance; Outcomes; FOLLOW-UP; MEN; RECOMMENDATIONS; VELOCITY; BIOPSY; COHORT;
D O I
10.1016/j.eururo.2018.01.017
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Background: For men on active surveillance for prostate cancer, utility of prostate-specific antigen (PSA) kinetics (PSAk) in predicting pathologic reclassification remains controversial. Objective: To develop prediction methods for utilizing serial PSA and evaluate frequency of collection. Design, setting, and participants: Data were collected from men enrolled in the multicenter Canary Prostate Active Surveillance Study, for whom PSA data were measured and biopsies performed on prespecified schedules. We developed a PSAk parameter based on a linear mixed-effect model (LMEM) that accounted for serial PSA levels. Outcome measurements and statistical analysis: The association of diagnostic PSA and/or PSAk with time to reclassification (increase in cancer grade and/or volume) was evaluated using multivariable Cox proportional hazards models. Results and limitations: A total of 851 men met the study criteria; 255 (30%) had a reclassification event within 5 yr. Median follow-upwas 3.7 yr. After adjusting for prostate size, time since diagnosis, biopsy parameters, and diagnostic PSA, PSAk was a significant predictor of reclassification (hazard ratio for each 0.10 increase in PSAk = 1.6 [95% confidence interval 1.2-2.1, p < 0.001]). The PSAk model improved stratification of risk prediction for the top and bottom deciles of risk over a model without PSAk. Model performance was essentially identical using PSA data measured every 6 mo to those measured every 3 mo. The major limitation is the reliability of reclassification as an end point, although it drives most treatment decisions. Conclusions: PSAk calculated using an LMEM statistically significantly predicts biopsy reclassification. Models that use repeat PSA measurements outperform a model incorporating only diagnostic PSA. Model performance is similar using PSA assessed every 3 or 6 mo. If validated, these results should inform optimal incorporation of PSA trends into active surveillance protocols and risk calculators. Patient summary: In this report, we looked at whether repeat prostate-specific antigen (PSA) measurements, or PSA kinetics, improve prediction of biopsy outcomes in men using active surveillance to manage localized prostate cancer. We found that in a large multicenter active surveillance cohort, PSA kinetics improves the prediction of surveillance biopsy outcome. (C) 2018 European Association of Urology. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:211 / 217
页数:7
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