Published Ahead of Print on April 16, 2012 as /JCO J Clin Oncol by American Society of Clinical Oncology INTRODUCTION

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1 Published Ahead of Print on April 16, 2012 as /JCO The latest version is at JOURNAL OF CLINICAL ONCOLOGY O R I G I N A L R E P O R T Validating the Interval to Biochemical Failure for the Identification of Potentially Lethal Prostate Cancer Mark K. Buyyounouski, Tom Pickles, Larry L. Kestin, Roger Allison, and Scott G. Williams Mark K. Buyyounouski, Fox Chase Cancer Center, Philadelphia, PA; Tom Pickles, British Columbia Cancer Agency, Vancouver, British Columbia, Canada; Larry L. Kestin, Michigan Healthcare Professionals/21st Century Oncology, Farmington Hills, MI; Roger Allison, Royal Brisbane Hospital, Brisbane; and Scott G. Williams, Peter MacCallum Cancer Center, Melbourne, Australia. Submitted February 1, 2011; accepted February 16, 2012; published online ahead of print at on April 16, Presented at the 51st Annual Meeting of the American Society for Radiation Oncology, Chicago, IL, November 1-5, Authors disclosures of potential conflicts of interest and author contributions are found at the end of this article. Corresponding author: Mark K. Buyyounouski, MD, MS, Fox Chase Cancer Center, 333 Cottman Ave, Philadelphia, PA 19111; mark.buyyounouski@ fccc.edu by American Society of Clinical Oncology X/12/3099-1/$20.00 DOI: /JCO A B S T R A C T Purpose To validate the interval to biochemical failure (IBF) as a prognostic factor at the time of biochemical failure for prostate cancer mortality (PCM) following radiotherapy (RT). Patients and Methods From a collaborative data set of men with clinically localized prostate cancer treated with RT from four institutions in three countries, we identified 1,722 men with biochemical failure (BF; prostate-specific antigen nadir 2 ng/ml). The IBF was defined as the time interval from completion of treatment to the date of BF. The primary outcome measure was discriminatory power in the form of the concordance index (c-index). Results Seventeen percent of men had an IBF 18 months. Median potential follow-up beyond the time of BF was 67 months. There were 290 deaths from prostate cancer. The IBF was the most discriminating individual prognostic factor overall, with a sensitivity of IBF 18 months to predict PCM within 10 years of 48.4% (95% CI, 43.3% to 54.1%); the specificity was 86.1% (95% CI, 84.5% to 87.7%), equating to a c-index of (95% CI, to 0.647). The 5-year cumulative incidence of PCM for IBF more than 18 months versus IBF 18 months was 9.4% (95% CI, 7.7% to 11.5%) versus 26.3% (95% CI, 21.2% to 31.8%); corresponding 10-year estimates were 26.2% (95% CI, 21.5% to 30.8%) versus 55.9% (95% CI, 48.9% to 63.0%), respectively (P.001 for both). IBF exhibited minimal change in performance across various follow-up durations. Conclusion IBF is the single most robust prognostic factor for PCM following RT without androgen deprivation therapy. This external validation demonstrates that patients and clinicians can use this information to make decisions about subsequent treatments. J Clin Oncol by American Society of Clinical Oncology INTRODUCTION Prostate-specific antigen (PSA) is the gold standard for monitoring prostate cancer following treatment. Cancer progression defined by PSA, otherwise known as biochemical failure (BF), is almost always the earliest sign of recurrent prostate cancer and can predate clinical manifestations of disease by months to years. Following radiotherapy (RT), the current and universally accepted definition of BF is a PSA level of 2 ng/ml above the post-treatment PSA nadir (ie, PSA nadir plus 2 ng/ml or the Phoenix or American Society for Radiation Oncology [ASTRO] definition). 1 The PSA nadir plus 2 ng/ml definition is preferred because it correlates with clinical failure, 2-6 has no apparent length of follow-up bias, 2,7-9 is associated with fewer misclassifications when neoadjuvant/adjuvant androgen deprivation therapy (ADT) is used, 10,11 requires a shorter time to diagnosis, 2 and provides a BF risk estimate that remains proportional over time, with or without ADT. 2,8 The most valuable and highly desired function of PSA, however, is to predict for clinically meaningful outcomes. After all, there is no more clear and pressing question for the patient once BF is diagnosed than What are the chances of dying from this cancer? Unfortunately, there is no current standard method of answering this question. The post-treatment PSA nadir (PSAn) and PSA doubling time (PSADT) have been proposed, but there is no consensus as to their use. It is unclear whether the global PSAn 12 or PSAn at a predetermined time point (eg, 12 or 24 months) 13,14 is more important and what cut point (eg, 1 or 2 ng/ml) is most prognostic. PSADT less than 3 months has shown the greatest promise, 15 but it usually identifies a rather small high-risk subgroup 16,17 and can be miscalculated. 18, by American Society of Clinical Oncology 1 Copyright 2012 by American Society of Clinical Oncology

2 Buyyounouski et al In a study of 221 men who experienced BF following RT at Fox Chase Cancer Center, a shorter time interval between the completion of treatment and BF (ie, interval to BF [IBF]) was related to the development of distant metastasis (DM) and prostate cancer mortality (PCM) independent of Gleason score (GS), PSA, T stage, RT dose, PSAn, and PSADT. 16 Importantly, men who had BF within the first 18 months postradiotherapy experienced a 5-year actuarial PCM incidence of 36% versus 6% for those with BF beyond 18 months (P.001). To prove credible and functional to the wider community, a putative prognostic factor must be demonstrated to have satisfactory efficacy in patients from an independent cohort. This study represents an international, multicenter, external validation analysis of the utility of IBF in predicting PCM at the time of BF. Performance will be compared with conventional factors. PATIENTS AND METHODS Patient Selection To be eligible for this study, all patients were required to have previously been treated by external beam RT (EBRT) for clinically localized prostate adenocarcinoma and have been subsequently diagnosed with biochemical recurrence by using a PSAn 2 ng/ml definition. 1 In all. 1,722 eligible patients with BF were identified within a collaborative data set of patients treated between 1989 and 2000 at four institutions: British Columbia Cancer Agency (BCCA), Peter MacCallum Cancer Center (PMCC), Royal Brisbane Hospital (RBH), and William Beaumont Hospital (WBH). EBRT had been the primary management method in the cohort, with surveillance and/or watchful waiting methods used in less than 5% of the patients. Table 1 details the distribution of prognostic, therapeutic, and follow-up characteristics. The RT techniques have been reported previously. 2,8,20-22 In summary, RT was given via computed tomography (CT) planned-conformal or intensity-modulated techniques without image guidance, and whole pelvic RT was not routinely used. Planned ADT given in combination with RT was an exclusion criterion for this study because of the difficulty of accurately identifying the date of treatment completion (the date of testosterone recovery). IBF was calculated from the date of finishing RT to the date of BF. The PSADT was calculated via the slope of an ordinary least squares regression line (assuming first-order PSA kinetics) by using all the PSA data between the last nonrising PSA value and the time of BF call. PSAn was defined as the lowest PSA recorded between the date of finishing therapy and the date of BF. The disease risk was classified according to National Comprehensive Cancer Network (NCCN) criteria, 23 with high risk being T3 or more, initial prostate-specific antigen (ipsa) more than 20 ng/ml, or GS 8 to 10; low risk being T2a or less, ipsa 10 ng/ml, or GS 6; and intermediate risk being all the remainder. The eligibility criteria and follow-up data for all patients were derived from the institutional medical record. In general, patients were reviewed clinically at approximately 3- to 6-month intervals after EBRT. Death was coded as due to prostate cancer when the death certificate attribution of death was to prostate cancer and the patient having known progressive metastatic prostate cancer as determined by the medical record. Censoring was at the date of last clinical follow-up in those not known to be deceased. Universally, patients with progressive cancer undertook salvage therapy in the form of ADT Characteristic BCCA (n 202) Table 1. Patient Characteristics PMCC (n 132) Institution RBH (n 988) WBH (n 400) Combined (N 1,722) No. % No. % No. % No. % No. % Age at BF, years Median Range ipsa, ng/ml Median Range Gleason score T stage , NCCN risk group Low Intermediate High RT dose, Gy Median Range Follow-up, months Median Range Abbreviations: BCCA, British Columbia Cancer Agency; BF, biochemical failure; ipsa, initial prostate-specific antigen; NCCN, National Comprehensive Cancer Network; PMCC, Peter MacCallum Cancer Center; RBH, Royal Brisbane Hospital; RT, radiotherapy; WBH, William Beaumont Hospital by American Society of Clinical Oncology JOURNAL OF CLINICAL ONCOLOGY

3 Interval to Biochemical Failure Predicts Mortality Table 2. Post-Treatment PSA-Based Factors BCCA (n 334) PMCC (n 249) RBH (n 988) WBH (n 410) Combined (n 2,132) Variable Form No. % No. % No. % No. % No. % PSAn, ng/ml Continuous Median Range PSAn 1 ng/ml Dichotomous IBF, months Continuous Median Range IBF 18 months Dichotomous PSADT, months Continuous Median Range PSADT 3 months Dichotomous Abbreviations: BCCA, British Columbia Cancer Agency; IBF, interval to biochemical failure; PMCC, Peter MacCallum Cancer Center; PSA, prostate-specific antigen; PSADT, PSA doubling time; PSAn, PSA nadir; RBH, Royal Brisbane Hospital; WBH, William Beaumont Hospital. initially with variable usage of further systemic therapy subsequently. No attempt to adjust for the nature or timing of these interventions was made because of the difficulty of performing or interpreting such data. 24 Statistical Plan and Analyses The analytic plan had two phases: first, we undertook an initial examination of the performance of IBF, PSAn, and PSADT individually by using a priori cut points prespecified in the literature (PSADT 3or 6 months, PSAn 1 ng/ml, IBF 18 or 36 months) to establish their validity. 10,12,16 Second, we performed exploratory analyses of each factor or combinations of factors for incremental benefit beyond that of conventional baseline factors (ipsa, GS, T-stage, or NCCN risk group). The primary study end point was duration from BF to PCM, with a secondary end point of BF to death from any cause (overall survival [OS]) duration. Validation of IBF was said to have occurred if IBF, over all other tested metrics, provided the optimal discrimination between those who experienced death resulting from prostate cancer and those who did not. The primary measure of discriminatory power was that of the concordance index (c-index). The c-index has values from 0 to 1, with 0.5 indicating a complete lack of discrimination (purely random) and with 1 (or 0) indicating perfect ability to rank the time to event; the c-index is analogous to the area under the receiver operating characteristic curve. To determine the performance of the c-index at various follow-up durations, the method of Heagerty and Zheng 25 was used. The significance of differences in c-index between the models with and without the new factors was estimated by using the method of Pencina et al. 26 Descriptive data were expressed as either a median value with associated 95th centile range (representing the values at the 2.5th and 97.5th centile) or as counts with associated percentages. Median potential follow-up was estimated by using the method of Schemper and Smith. 27 Model goodness of fit was evaluated by the c-index along with the likelihood ratio tests as required. Overfitting bias correction and 95% CIs were derived by bootstrap resampling. 28 Treatment center was a stratification factor in all analyses. No formal corrections for multiple testing were made. Sensitivity analyses were performed to address the potential impact of informative censoring. In a best-case example, it was assumed that all censored patients were not at risk of death until after the last event time. Alternatively, analyses were repeated by using a worst-case scenario, with all censored patients recorded as having treatment failure the day after censoring. All statistical analyses were conducted in the R statistical language (R Foundation for Statistical Computing, Vienna, Austria). Statistical significance was denoted at the P.05 level and was always two-sided. RESULTS Among the 1,722 patients included in this analysis, there were 290 deaths from prostate cancer and 561 deaths overall. The 10-year cumulative incidence of death resulting from prostate cancer was 34.7% Table 3. C-Index Values for Individual Factors in Relation to Prostate Cancer Mortality Factor Grouping C-Index 95% CI Established factors, cut points Gleason score Trichotomous (2-6, 7, 8-10) to ipsa, ng/ml Trichotomous ( 10, 10-20, 20) to T stage Trichotomous (1, 2, or 3-4) to Radiation dose, Gy Trichotomous ( 64, 64-70, 70) to Post-treatment factors PSADT Dichotomous ( 3 v 3 months) to Dichotomous ( 6 v 6 months) to IBF Dichotomous ( 18 v 18 months) to Dichotomous ( 36 v 36 months) to PSAn Dichotomous ( 1 v 1 ng/ml) to Abbreviations: C-index, concordance index; IBF, interval to biochemical failure; ipsa, initial prostate-specific antigen; PSADT, PSA doubling time; PSAn, PSA nadir by American Society of Clinical Oncology 3

4 Buyyounouski et al (95% CI, 30.4% to 38.5%), and death from other causes was 28.5% (95% CI, 25.2% to 32.5%). Various post-treatment PSA-based characteristics are listed in Table 2. Thirty-nine percent of patients had a PSAn 1 ng/ml, 17% had an IBF 18 months, and 8% had a PSADT 3 months. Median follow-up beyond the time of BF was 67 months. Univariate Analyses Table 3 provides c-index values for various factors when predicting for PCM. Of the traditional prognostic variables, GS (c-index 0.600) was the most discriminatory; ipsa (c-index 0.516) and RT dose (c-index 0.537) were both poor discriminators of death resulting from prostate cancer. The IBF was the most discriminating individual prognostic factor overall; the sensitivity of IBF 18 months to predict PCM within 10 years was 48.4% (95% CI, 43.3% to 54.1%) and the specificity was 86.1% (95% CI, 84.5% to 87.7%), equating to a c-index of (95% CI, to 0.647). For comparison, the sensitivity and specificity of PSAn 1 ng/ml were 56.7% and 29.1%, and for PSADT 3 months, they were 18.2% and 93.5%, respectively. Figure 1 illustrates prostate cancer specific survival following BF split by IBF 18 months versus more than 18 months. The 5-year cumulative incidence of death resulting from prostate cancer was 9.4% (95% CI, 7.7% to 11.5%) versus 26.3% (95% CI, 21.2% to 31.8%), and the corresponding 10-year estimates were 26.2% (95% CI, 21.5% to 30.8%) versus 55.9% (95% CI, 48.9% to 63.0%), respectively (P.001 for both). Figure 2 illustrates the performance of the PSAn, PSADT, and IBF in discriminating the risk of death resulting from prostate cancer at various time points. Time, on the x-axis, describes the time at which one may desire a PCM prediction. The IBF and PSAn showed only minimal change at differing time points, with the IBF showing the most stable discrimination for predictions across all time points. The PSADT has excellent early-term discriminatory performance, offering the highest performance of all the factors in the first 15 months following BF. It did, however, exhibit substantial time dependence whereby it had steadily declining discrimination that reached virtually negligible (random) predictive performance at approximately 7 years. Sensitivity analysis of alternative informative censoring assumptions showed IBF to vary according to artificial censoring patterns. In the late censoring simulation, the c-index increased to (95% CI, to 0.678), although in the early failure model, it was reduced substantially (0.525; 95% CI, to 0.536). Contrasting with this, each of these simulations reduced the performance of PSADT (0.536 [95% CI, to 0.553] and [95% CI, to 0.572], respectively) and PSAn (0.553 [95% CI, to 0.583] and [95% CI, to 0.548], respectively). Prognostic Factor Combinations Models of combinations of factors were systematically tested in an exploratory manner. With the aim of creating a parsimonious model, we began with the strongest of the prefailure discriminatory factors (GS) as a baseline comparator (c-index, 0.600). Adding the next most reliable factor (T-stage) to this resulted in a c-index of (95% CI, to 0.665), a change that was highly statistically significant (P.001). Beyond this, the addition of ipsa, RT dose, or prior ADT usage data did not improve the c-index by more than 0.001, an improvement that was not statistically significant in any case. Of interest is that the conventional combination of GS, ipsa, and T-stage A Cumulative Incidence of Prostate Cancer Death B Cumulative Incidence of Prostate Cancer Death C Cumulative Incidence of Prostate Cancer Death Time From Biochemical Failure (months) IBF 0-18 months IBF > 18 months Time From Biochemical Failure (months) dt 0-3 months dt > 3 months Time From Biochemical Failure (months) Nadir > 1 ng/ml Nadir 0-1 ng/ml Fig 1. Cumulative incidence plots of prostate cancer specific death following biochemical failure split by (A) interval to biochemical failure (IBF) at 18 months, (B) prostate-specific antigen doubling time (dt) at 3 months, and (C) prostatespecific antigen nadir at 1 ng/ml. Lighter bands indicate 95% CIs. into the NCCN risk categories had substantially worse performance in predicting PCM at the time of BF than the GS or T-stage (c-index, 0.562; 95% CI, to 0.592). Taking the model of GS and T-stage (GS-T model) as the optimal baseline mix of prefailure factors, we introduced the PSA-based factors of PSADT, PSAn, and IBF in unison to assess their impact. As an individual variable, the IBF had the largest incremental impact on c-index with an increase of (P.001). This is depicted in Table 4, along with the results for PSADT and PSAn, which were also both statistically significant improvements over the GS-T model. There was also a significant improvement in the performance of the model that incorporated PSAn (c-index, 0.673) over the model that used PSADT (c-index, 0.654; P.001). Similar findings were apparent using NCCN risk categories as the base model, albeit with a concordantly reduced c-index in all (data not shown). The final evaluation was of the role of combination models that incorporated several of the PSAbased variables (described in Table 4). A combined model using all by American Society of Clinical Oncology JOURNAL OF CLINICAL ONCOLOGY

5 Interval to Biochemical Failure Predicts Mortality C-Index PSA nadir Doubling time Time Point of Desired Outcome Prediction (months) Fig 2. Time dependency of the prostate-specific antigen (PSA) nadir, prostatespecific antigen doubling time, and interval to biochemical failure (IBF) for predicting prostate cancer mortality. The time point at which prostate cancer mortality is to be predicted is chosen on the abscissa and the corresponding concordance index (c-index) value for each variable is then able to be determined at that point. three PSA dynamic features was a consistent improvement over all others. OS End Points A secondary analysis was conducted by using OS as an end point. Results were qualitatively similar to those based on a cancer-specific survival end point, with IBF dichotomized at 18 months having the highest c-index at (95% CI, to 0.643). A PSAn divided at 1 ng/ml had a c-index of (95% CI, to 0.630), and a PSADT divided at 3 months had a c-index of (95% CI, to 0.580). The unadjusted estimates of 10-year OS were 24.6% (95% CI, 18.3% to 31.6%) for those with an IBF 18 months and 42.1% (95% CI, 36.3% to 47.3%) for an IBF more than 18 months. In this study, we externally validated the initial results showing the IBF to be a robust prognostic factor for PCM following RT. This validation study is important for ensuring that the statistical value of the IBF was not overestimated in the original Fox Chase report because of data-dependent deficiencies of the statistical modeling or patient selection bias. This study is also important because it demonstrates the geographic portability of the IBF by testing it in a diverse IBF population from various international locations. The temporal stability of the IBF is also established, since the predictive performance of the IBF for PCM was most constant over various time frames compared with PSADT and PSAn. These strengths and findings should increase confidence that the IBF is a useful prognostic tool to predict PCM and OS. A short disease-free interval is a fundamental oncology principal representative of the underlying cancer biology that has been shown to predict worse outcomes in various disease sites, including prostate cancer following radical prostatectomy. 29 However, the disease-free interval has been difficult to characterize following RT for prostate cancer because PSA levels are not expected to become undetectable and can vary considerably over time and among patients. The IBF using the PSAn 2 ng/ml definition of BF provides a standard method for defining the disease-free interval, free of backdating limitations associated with the former ASTRO definition. 1 The IBF is a convenient, practical method for relating the diagnosis of BF to clinical meaningful outcomes such as PSM and OS using routine follow-up serum PSA testing. A major criticism of defining recurrence of prostate cancer with PSA criteria (ie, biochemical failure) has been the anxiety it evokes in patients because its implications on survival were not well understood. Currently, there is no established practice standard to select patients with BF for salvage ADT. 23 Of all the various factors used to guide management, PSADT may be the most commonly used because it has been shown to predict for DM and PCM 30 following RT. This study confirms that PSADT is prognostic for PCM particularly in the shortterm; however, it was outperformed by the IBF. The IBF widely separates thosewitha33% 10-yearriskofPSMfromthosewitha65% riskbasedon a diagnosis of BF 18 versus more than 18 months, respectively, capturing those at risk of both early and late risk of PSM. The greatest discriminatory power for predicting PCM, however, was achieved with a model that included all three post-treatment factors (ie, PSADT, PSAn, and IBF; c-index, 0.705). Therefore, one should not consider the IBF to the exclusion of the PSADT or PSAn. And one would not want to ignore the excellent early-term discriminatory performance of PSADT, which offers the highest performance of all the factors in the first 15 months following BF. Incorporating the IBF in a prognostic model (eg, nomograms) with other risk factors (ie, PSADT, PSA nadir, GS, T-stage, RT dose, and ADT use) is a method that appears to be able to combine these various factors to estimate the risk of PCM on an individual patient basis 31 but will require further validation. Table 4. C-Index Values for Baseline Model Plus Single PSA-Based Variables Relative to Prostate Cancer Mortality Prognostic Factor C-index 95% CI Baseline Model PSAn PSADT P Comparison With: IBF IBF PSAn IBF PSADT GS T (baseline nodel) to PSAn to PSADT to IBF to IBF PSAn to IBF PSADT to IBF PSADT PSAn to Abbreviations: C-index, concordance index; GS, Gleason score; IBF, interval to biochemical failure (dichotomized at 18 months); PSA, prostate-specific antigen; PSADT, PSA doubling time (dichotomized at 3 months); PSAn, PSA nadir (dichotomized at 1 ng/ml); T, T stage by American Society of Clinical Oncology 5

6 Buyyounouski et al Limitations of our study include the inability to control for the nature and timing of salvage therapy. This can have an impact on results through clinical differences in therapeutic efficacy between treatments, or statistically through issues such as informative censoring. With the known difficulty in adjusting for salvage therapy efficacy, we have not attempted to account for or interpret such data. 24 Censoring biases are intractable in observational data; however, in the case of this cohort, they are potentially minimized because of the limited range of salvage therapies available during the study period. Furthermore, although one in six of our cohort was known to have died of prostate cancer and provided robust statistics for early death, we are cognizant of the fact that the median time to PCM is approximately 12 years but median potential follow-up is 5.5 years, which is a common limitation in prostate cancer studies. 32 Simulation using best-case and worst-case scenarios suggest that our performance estimates for IBF are conservative, provided that there is a low likelihood of frequent and early cancer death as the cohort matures. Performance of PSADT and PSAn were overly optimistic in both situations, however. It remains a possibility that late PCM will substantially change the current findings. In conclusion, when considering the natural history of prostate cancer recurrence following RT, the IBF should also routinely be considered. The IBF is the most reliable factor in discriminating both early and late PCM when prognosticating at the time of BF and is relatively time invariant. Both PSADT and PSAn have either reduced or heavily time-dependent performance. Although the overall c-index of for the IBF is relatively low, it does represent the best univariate factor currently available to predict PCM and OS (Table 3). Furthermore, there is always incremental benefit to using the IBF beyond our current prognostic schemas (Table 4). The IBF can be used to counsel patients for early salvage therapy; identify patients for participation in clinical trials; design selection criteria for future experimental protocols; and design prognostic models (eg, nomograms) with other risk factors (ie, PSADT, PSAn, GS, T-stage, RT dose, and ADT use) to estimate risk on a personalized basis. AUTHORS DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST The author(s) indicated no potential conflicts of interest. AUTHOR CONTRIBUTIONS Conception and design: Mark K. Buyyounouski, Scott G. Williams Collection and assembly of data: Tom Pickles, Larry L. Kestin, Roger Allison, Scott G. Williams Data analysis and interpretation: Mark K. Buyyounouski, Scott G. Williams Manuscript writing: All authors Final approval of manuscript: All authors REFERENCES 1. Roach M 3rd, Hanks G, Thames H Jr, et al: Defining biochemical failure following radiotherapy with or without hormonal therapy in men with clinically localized prostate cancer: Recommendations of the RTOG-ASTRO Phoenix Consensus Conference. Int J Radiat Oncol Biol Phys 65: , Buyyounouski MK, Hanlon AL, Eisenberg DF, et al: Defining biochemical failure after radiotherapy with and without androgen deprivation for prostate cancer. Int J Radiat Oncol Biol Phys 63: , Kestin LL, Vicini FA, Martinez AA: Practical application of biochemical failure definitions: What to do and when to do it. 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Int J Radiat Oncol Biol Phys 64: , Pickles T, Kim-Sing C, Morris WJ, et al: Evaluation of the Houston biochemical relapse definition in men treated with prolonged neoadjuvant and adjuvant androgen ablation and assessment of follow-up lead-time bias. Int J Radiat Oncol Biol Phys 57:11-18, Coen JJ, Chung CS, Shipley WU, et al: Influence of follow-up bias on PSA failure after external beam radiotherapy for localized prostate cancer: Results from a 10-year cohort analysis. Int J Radiat Oncol Biol Phys 57: , D Amico AV, Moul J, Carroll PR, et al: Prostate specific antigen doubling time as a surrogate end point for prostate cancer specific mortality following radical prostatectomy or radiation therapy. J Urol 172:S42-S46, Zietman AL, Christodouleas JP, Shipley WU: PSA bounces after neoadjuvant androgen deprivation and external beam radiation: Impact on definitions of failure. Int J Radiat Oncol Biol Phys 62: , Ray ME, Thames HD, Levy LB, et al: PSA nadir predicts biochemical and distant failures after external beam radiotherapy for prostate cancer: A multi-institutional analysis. Int J Radiat Oncol Biol Phys 64: , Zelefsky MJ, Shi W, Yamada Y, et al: Postradiotherapy 2-year prostate-specific antigen nadir as a predictor of long-term prostate cancer mortality. Int J Radiat Oncol Biol Phys 75: , Alcantara P, Hanlon A, Buyyounouski MK, et al: Prostate-specific antigen nadir within 12 months of prostate cancer radiotherapy predicts metastasis and death. Cancer 109:41-47, D Amico AV, Moul JW, Carroll PR, et al: Surrogate end point for prostate cancer-specific mortality after radical prostatectomy or radiation therapy. J Natl Cancer Inst 95: , Buyyounouski MK, Hanlon AL, Horwitz EM, et al: Interval to biochemical failure highly prognostic for distant metastasis and prostate cancer-specific mortality after radiotherapy. Int J Radiat Oncol Biol Phys 70:59-66, Valicenti RK, DeSilvio M, Hanks GE, et al: Posttreatment prostatic-specific antigen doubling time as a surrogate endpoint for prostate cancerspecific survival: An analysis of Radiation Therapy Oncology Group Protocol Int J Radiat Oncol Biol Phys 66: , Arlen PM, Bianco F, Dahut WL, et al: Prostate Specific Antigen Working Group guidelines on prostate specific antigen doubling time. J Urol 179: , Ramírez ML, Nelson EC, Devere White RW, et al: Current applications for prostate-specific antigen doubling time. Eur Urol 54: , Kestin LL, Goldstein NS, Vicini FA, et al: Percentage of positive biopsy cores as predictor of clinical outcome in prostate cancer treated with radiotherapy. J Urol 168: , Williams SG, Buyyounouski MK, Pickles T, et al: Percentage of biopsy cores positive for malignancy and biochemical failure following prostate cancer radiotherapy in 3,264 men: Statistical significance without predictive performance. 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7 Interval to Biochemical Failure Predicts Mortality study with treatment by indication. Stat Med 29: , Heagerty PJ, Zheng Y: Survival model predictive accuracy and ROC curves. Biometrics 61:92-105, Pencina MJ, D Agostino RB Sr, D Agostino RB Jr, et al: Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond. Stat Med 27: , 2008; discussion Schemper M, Smith TL: A note on quantifying follow-up in studies of failure time. Control Clin Trials 17: , Harrell FE Jr, Lee KL, Mark DB: Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 15: , Freedland SJ, Humphreys EB, Mangold LA, et al: Risk of prostate cancer-specific mortality following biochemical recurrence after radical prostatectomy. JAMA 294: , Lee AK, Levy LB, Cheung R, et al: Prostatespecific antigen doubling time predicts clinical outcome and survival in prostate cancer patients treated with combined radiation and hormone therapy. Int J Radiat Oncol Biol Phys 63: , Buyyounouski M, Kestin L, Duchesne G, et al: A nomogram predicting 5-year probability of cause specific survival from biochemical failure following radiotherapy. Int J Radiat Oncol Biol Phys 81:S389, Stephenson AJ, Kattan MW, Eastham JA, et al: Prostate cancer-specific mortality after radical prostatectomy for patients treated in the prostatespecific antigen era. J Clin Oncol 27: , by American Society of Clinical Oncology 7

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