Tumor Volume Changes on 1.5 Tesla Endorectal MRI During Neoadjuvant Androgen Suppression Therapy for Higher-Risk Prostate Cancer and Recurrence in Men Treated Using Radiation Therapy Results of the Phase II CALGB 9682 Study

D’Amico, Anthony V.; Halabi, Susan; Tempany, Clare M.; Titelbaum, David S.; Philips, George; Loffredo, Marian; McMahon, Elizabeth; Sanford, Ben; Vogelzang, Nicholas J.; Small, Eric J.

doi:10.1016/j.ijrobp.2007.09.033

Cited by 15 publications

(8 citation statements)

References 24 publications

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“…Researchers in some studies have investigated the use of these techniques for prediction of patients' outcome following radiation therapy (27)(28)(29)31,46 ). The results of these studies have suggested that imaging fi ndings can be used to predict treatment response.…”

Section: Discussionmentioning

confidence: 99%

Prostate Cancer: Prediction of Biochemical Failure after External-Beam Radiation Therapy—Kattan Nomogram and Endorectal MR Imaging Estimation of Tumor Volume

et al. 2011

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Purpose:To determine whether magnetic resonance (MR) imaging and MR spectroscopic imaging fi ndings can improve predictions made with the Kattan nomogram for radiation therapy. Materials and Methods:The institutional review board approved this retrospective HIPAA-compliant study. Ninety-nine men who underwent endorectal MR and MR spectroscopy before externalbeam radiation therapy for prostate cancer (January 1998 to June 2007) were included. Linear predictors were calculated with input variables from the study sample and the Kattan original coeffi cients. The linear predictor is a single weighted value that combines information of all predictor variables in a model, where the weight of each value is its association with the outcome. Two radiologists independently reviewed all MR images to determine extent of disease; a third independent reader resolved discrepancies. Biochemical failure was defi ned as a serum prostate-specifi c antigen level of 2 ng/mL (2 m g/L) or more above nadir. Cox proportional hazard models were used to determine the probabilities of treatment failure (biochemical failure) in 5 years. One model included only the Kattan nomogram data; the other also incorporated imaging fi ndings. The discrimination performance of all models was determined with receiver operating characteristics (ROC) curve analyses. These analyses were followed by an assessment of net risk reclassifi cation. Results:The areas under the ROC curve for the Kattan nomogram and the model incorporating MR imaging fi ndings were 61.1% (95% confi dence interval: 58.1%, 64.0%) and 78.0% (95% confi dence interval: 75.7%, 80.4%), respectively . Comparison of performance showed that the model with imaging fi ndings performed signifi cantly better than did the model with clinical variables alone ( P , .001).Overall, the addition of imaging fi ndings led to an improvement in risk classifi cation of about 28%, ranging from approximately a minimum of 16% to a maximum of 39%, depending on the risk change considered important.

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Section: Discussionmentioning

confidence: 99%

Prostate Cancer: Prediction of Biochemical Failure after External-Beam Radiation Therapy—Kattan Nomogram and Endorectal MR Imaging Estimation of Tumor Volume

et al. 2011

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“…A recent study by D'Amico et al ( 84 ) showed that prostate tumor volume changes on 1.5-T endorectal MR images during neoadjuvant androgenincreases the risk of radiation-induced toxicity. The choice of radiation dose that offers the best balance between effi cacy and toxicity remains complex ( 64 ).…”

Section: Review: Mr Imaging Of Treated Prostate Cancermentioning

confidence: 99%

MR Imaging of Treated Prostate Cancer

Vargas

Wassberg²,

Akın³

et al. 2012

Radiology

126

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Many management options are available to patients with newly diagnosed prostate cancer. Magnetic resonance (MR) imaging plays an important role in initial staging of prostate cancer, but it also aids in tumor detection when there is clinical or biochemical suspicion of residual or recurrent disease after treatment. The purpose of this review is to describe the normal appearances of the prostatic region after different kinds of treatment for prostate cancer and to discuss how these appearances differ from those of recurrent and residual disease. Several MR imaging techniques used in evaluating patients with prostate cancer are described, including conventional MR imaging sequences (mainly T1- and T2-weighted sequences), MR spectroscopic imaging, diffusion-weighted imaging, and dynamic contrast agent-enhanced MR imaging. Clinical considerations, together with the different approaches for interpreting serum prostate-specific antigen values in the posttreatment setting, are also presented. All forms of treatment alter the MR imaging features of the prostatic region to a greater or lesser extent, and it is important to be able to recognize expected posttreatment appearances and distinguish them from the features of recurrent or residual cancer to aid subsequent clinical management.

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“…PSA measurements following prostate cancer therapy are recommended to be obtained every 3 months for 2 years and then every 6 months for an additional 3 years and annually thereafter as noted in D'Amico et al (2008a). Therefore, PSA recurrence is always modeled in the medical literature as a continuous time to the event as noted in D'Amico et al (2005) and D'Amico et al (2008b).…”

Section: Motivating Datamentioning

confidence: 99%

A Bayesian multi‐risks survival (MRS) model in the presence of double censorings

et al. 2020

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Semi-competing risks data include the time to a nonterminating event and the time to a terminating event, while competing risks data include the time to more than one terminating event. Our work is motivated by a prostate cancer study, which has one nonterminating event and two terminating events with both semi-competing risks and competing risks present as well as two censoring times. In this paper, we propose a new multi-risks survival (MRS) model for this type of data. In addition, the proposed MRS model can accommodate noninformative right-censoring times for nonterminating and terminating events. Properties of the proposed MRS model are examined in detail. Theoretical and empirical results show that the estimates of the cumulative incidence function for a nonterminating event may be biased if the information on a terminating event is ignored. A Markov chain Monte Carlo sampling algorithm is also developed. Our methodology is further assessed using simulations and also an analysis of the real data from a prostate cancer study. As a result, a prostate-specific antigen velocity greater than 2.0 ng/mL per year and higher biopsy Gleason scores are positively associated with a shorter time to death due to prostate cancer.

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Tumor Volume Changes on 1.5 Tesla Endorectal MRI During Neoadjuvant Androgen Suppression Therapy for Higher-Risk Prostate Cancer and Recurrence in Men Treated Using Radiation Therapy Results of the Phase II CALGB 9682 Study

Cited by 15 publications

References 24 publications

Prostate Cancer: Prediction of Biochemical Failure after External-Beam Radiation Therapy—Kattan Nomogram and Endorectal MR Imaging Estimation of Tumor Volume

Prostate Cancer: Prediction of Biochemical Failure after External-Beam Radiation Therapy—Kattan Nomogram and Endorectal MR Imaging Estimation of Tumor Volume

MR Imaging of Treated Prostate Cancer

A Bayesian multi‐risks survival (MRS) model in the presence of double censorings

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