Literature DB >> 19014779

Determinants of change in prostate-specific antigen over time and its association with recurrence after external beam radiation therapy for prostate cancer in five large cohorts.

Cécile Proust-Lima1, Jeremy M G Taylor, Scott G Williams, Donna P Ankerst, Ning Liu, Larry L Kestin, Kyounghwa Bae, Howard M Sandler.   

Abstract

PURPOSE: To assess the relationship between prognostic factors, postradiation prostate-specific antigen (PSA) dynamics, and clinical failure after prostate cancer radiation therapy using contemporary statistical models. METHODS AND MATERIALS: Data from 4,247 patients with 40,324 PSA measurements treated with external beam radiation monotherapy in five cohorts were analyzed. Temporal change of PSA after treatment completion was described by a specially developed linear mixed model that included standard prognostic factors. These factors, along with predicted PSA evolution, were incorporated into a Cox model to establish their predictive value for the risk of clinical recurrence over time.
RESULTS: Consistent relationships were found across cohorts. The initial PSA decline after radiation therapy was associated with baseline PSA and T-stage (p < 0.001). The long-term PSA rise was associated with baseline PSA, T-stage, and Gleason score (p < 0.001). The risk of clinical recurrence increased with current level (p < 0.001) and current slope of PSA (p < 0.001). In a pooled analysis, higher doses of radiation were associated with a lower long-term PSA rise (p < 0.001) but not with the risk of recurrence after adjusting for PSA trajectory (p = 0.63). Conversely, after adjusting for other factors, increased age at diagnosis was not associated with long-term PSA rise (p = 0.85) but was directly associated with decreased risk of recurrence (p < 0.001).
CONCLUSIONS: We conclude that a linear mixed model can be reliably used to construct typical patient PSA profiles after prostate cancer radiation therapy. Pretreatment factors along with PSA evolution and the associated risk of recurrence provide an efficient and quantitative way to assess the impact of risk factors on disease progression.

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Year:  2008        PMID: 19014779      PMCID: PMC2757130          DOI: 10.1016/j.ijrobp.2008.01.056

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  30 in total

1.  Rate of PSA rise predicts metastatic versus local recurrence after definitive radiotherapy.

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Journal:  Int J Radiat Oncol Biol Phys       Date:  1997-07-15       Impact factor: 7.038

2.  Consensus statement: guidelines for PSA following radiation therapy. American Society for Therapeutic Radiology and Oncology Consensus Panel.

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Journal:  Int J Radiat Oncol Biol Phys       Date:  1997-03-15       Impact factor: 7.038

3.  Penile bulb dose and impotence after three-dimensional conformal radiotherapy for prostate cancer on RTOG 9406: findings from a prospective, multi-institutional, phase I/II dose-escalation study.

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4.  Radiation therapy for clinically localized prostate cancer: a multi-institutional pooled analysis.

Authors:  W U Shipley; H D Thames; H M Sandler; G E Hanks; A L Zietman; C A Perez; D A Kuban; S L Hancock; C D Smith
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5.  Individualized predictions of disease progression following radiation therapy for prostate cancer.

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6.  Prostate specific antigen doubling time as a surrogate end point for prostate cancer specific mortality following radical prostatectomy or radiation therapy.

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8.  Both pretreatment prostate-specific antigen level and posttreatment biochemical failure are independent predictors of overall survival after radiotherapy for prostate cancer.

Authors:  Scott G Williams; Gillian M Duchesne; Jeremy L Millar; Gary R Pratt
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9.  Prostate-specific antigen for pretreatment prediction and posttreatment evaluation of outcome after definitive irradiation for prostate cancer.

Authors:  D A Kuban; A M el-Mahdi; P F Schellhammer
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10.  Prostate-specific antigen and radiation therapy for clinically localized prostate cancer.

Authors:  G K Zagars; A Pollack; V S Kavadi; A C von Eschenbach
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  21 in total

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2.  Individualized dynamic prediction of prostate cancer recurrence with and without the initiation of a second treatment: Development and validation.

Authors:  Mbéry Sène; Jeremy Mg Taylor; James J Dignam; Hélène Jacqmin-Gadda; Cécile Proust-Lima
Journal:  Stat Methods Med Res       Date:  2014-05-20       Impact factor: 3.021

3.  Confirmation of a low α/β ratio for prostate cancer treated by external beam radiation therapy alone using a post-treatment repeated-measures model for PSA dynamics.

Authors:  Cécile Proust-Lima; Jeremy M G Taylor; Solène Sécher; Howard Sandler; Larry Kestin; Tom Pickles; Kyoungwha Bae; Roger Allison; Scott Williams
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4.  Estimation of the optimal regime in treatment of prostate cancer recurrence from observational data using flexible weighting models.

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6.  Stochastic functional data analysis: a diffusion model-based approach.

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7.  Outcome of patients with localized prostate cancer treated by radiotherapy after confirming the absence of lymph node invasion.

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8.  Patient-Level DNA Damage and Repair Pathway Profiles and Prognosis After Prostatectomy for High-Risk Prostate Cancer.

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9.  Real-time individual predictions of prostate cancer recurrence using joint models.

Authors:  Jeremy M G Taylor; Yongseok Park; Donna P Ankerst; Cecile Proust-Lima; Scott Williams; Larry Kestin; Kyoungwha Bae; Tom Pickles; Howard Sandler
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10.  Joint modelling of longitudinal and multi-state processes: application to clinical progressions in prostate cancer.

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