Stereotactic body radiation therapy for low- to intermediate-risk prostate cancer has potential cost savings and may improve access to radiation, increase convenience, and boost quality of life.
The purpose of this study is to compare the cost-effectiveness of 2 external beam radiation therapy techniques for treatment of lowto intermediate-risk prostate cancer: stereotactic body radiation therapy (SBRT) and intensitymodulated radiation therapy (IMRT).
Materials and Methods:
A Markov decision analysis model with probabilistic sensitivity analysis was designed with the various disease states of a 70-year-old patient with organ-confined prostate cancer to evaluate the cost-effectiveness of 2 external beam radiation treatment options.
The Monte Carlo simulation revealed that the mean cost and quality-adjusted life-years (QALYs) for SBRT and IMRT were $22,152 and 7.9 years and $35,431 and 7.9 years, respectively. The sensitivity analysis revealed that if the SBRT cohort experienced a decrease in quality of life of 4% or a decrease in efficacy of 6%, then SBRT would no longer dominate IMRT in cost-effectiveness. In fact, with these relaxed assumptions for SBRT, the incremental cost-effectiveness ratio of IMRT met the societal willingness to pay threshold of $50,000 per QALY.
Compared with IMRT, SBRT for lowto intermediate-risk prostate cancer has great potential cost savings for our healthcare system payers and may improve access to radiation, increase patient convenience, and boost quality of life for patients. Our model suggests that the incremental cost-effectiveness ratio of IMRT compared with SBRT is highly sensitive to quality-oflife outcomes, which should be adequately and comparably measured in current and future prostate SBRT studies.
(Am J Manag Care. 2012;18(5 Spec No. 2):e186-e193)The American Cancer Society estimates 241,740 patients newly diagnosed with prostate cancer, with 28,174 prostate cancer—related deaths, in 2012.1 The National Institutes of Health estimate that the overall direct cost of cancer in the United States in 2010 was $102.8 billion, with prostate cancer being the fifth most costly cancer, accounting for more than $12 billion in annual cost in 2010 and $19 billion projected in 2020.1,2 The rapidly increasing cost of prostate cancer treatment, driven by a combination of advanced surgical, radiation, and pharmaceutical treatment technologies, has catalyzed increased scrutiny regarding current treatment approaches for prostate cancer.3-5 In fact, prostate cancer has been described as the litmus test for healthcare spending reform efforts.6
Hayes et al7 recently examined a random-effects meta-analysis for patients with low-risk prostate cancer through a decision analysis, concluding active surveillance would be more effective than initial treatment options based on a quality-adjusted life expectancy end point. However, this study comparing initial treatment versus active surveillance did not include the emerging treatment option of stereotactic body radiation therapy (SBRT).
The traditional initial treatment options for low- and intermediaterisk prostate cancer have been prostatectomy, external beam radiation, or brachytherapy. Most recently, the external beam technique of 3-dimensional conformational radiation therapy was replaced by the more conformal technique of intensity-modulated radiation therapy (IMRT), which has allowed for dose escalation.8 Similar to IMRT, SBRT is a form of highly conformal external beam radiotherapy, employing the use of advanced technologies including unique beam arrangements, stable patient immobilization, motion assessment and control, and daily image guidance. However, SBRT delivers a higher dose of radiation per fraction and at our institution includes additional patient immobilization (stereotactic body frame), motion control (rectal balloon), and motion assessment (intrafraction image guidance). This technique has been successfully applied in early-stage lung cancer and liver metastasis.9-11 Prostate cancer may be uniquely appropriate for treatment with hypofractionation (large dose per fraction) because of a lower α-to-β ratio (approximately 1.5 to 3.0), which is similar to normal tissue late effects.12-15 Stanford University treated patients at a dose of 36.25 Gy in 5 fractions, with no patient experiencing biochemical failure at 33-month follow-up.16 Our institution recently published the toxicity rates of a phase I dose-escalation study of SBRT for prostate cancer, which compare favorably with acute toxicity reported in historical IMRT dose-escalation studies ().17-32 In addition to several promising early outcome reports, Freeman et al22 and King26 recently published their 5-year biochemical progression-free survival (PFS) of 93%, with favorable rates of early and late toxicity compared with IMRT dose-escalation trials as well (Table 1).22,23,26 Thus, on the basis of these results and the α-to-β ratio of prostate cancer, there seems to be a firm hypothesis that SBRT would be comparable to or better than IMRT from a biochemical control standpoint. However, by the same rationale, the late effects of normal tissue could potentially be worse and thus negatively affect the quality of life (QoL) of patients undergoing treatment with SBRT. To that end, this model aims to further describe the cost-effectiveness of SBRT while using a sensitivity analysis to establish the thresholds at which late effects as measured by utility may prove SBRT to be less cost-effective than IMRT.
Cost-effectiveness analysis (CEA) using Markov modeling is a well-documented economic technique used to assess relative benefits of treatments, quality-adjusted life-years (QALYs), and costs of various treatment options for a given health condition. In 2009, in response to an ever-increasing percentage of our national gross domestic product spent on healthcare costs, $1.1 billion of the $787 billion stimulus package was allocated for comparative clinical effectiveness research. Thus, it is clear that CEA will increasingly be applied to economically evaluate alternative treatment options in our healthcare system.33,34 To our knowledge, this is the first report that uses Markov CEA with Monte Carlo probabilistic sensitivity analysis to explore the cost-effectiveness of SBRT for patients with low- or intermediate-risk prostate cancer as compared with IMRT from the payer perspective.
Materials and MethodsDecision Model
To evaluate a hypothetic clinical trial design, we developed a Markov decision tree using TreeAge Pro Healthcare 2011 (Tree-Age Software, Williamstown, Massachusetts) to capture the various disease states of a 70-year-old man with organconfined prostate cancer (). Similar to past and ongoing studies evaluating SBRT, the patient was assumed to have a Gleason score <7 and/or prostate-specific antigen <15, with limited organ-confined prostate cancer (<pT2b). Given that the median age of diagnosis of prostate cancer in the United States is 68 years, and the average actuarial life expectancy of men is 78 years, the base case involved a 70-year-old man with low- or intermediate-risk disease treated with either IMRT or SBRT with a 10-year follow-up horizon.1,35 The model captured the disease states a patient with prostate cancer could potentially experience after radiation: no evidence of disease, progression with response to hormonal therapy (hormone therapy), progression in a patient with hormone-refractory prostate cancer (chemotherapy), and death. Markov simulations allow hypothetic patient cohorts to transition between health states in defined increments of time.33 In this model, the patient spends 1 year in a given disease state before the Monte Carlo simulation allows for a probabilistic transition to another state. Annual transition probabilities were calculated assuming rates using the formula: annual probability = 1 — exp(- annual rate/N), where the annual rate = [–lN(1 – P)/N], when P is the probability of biologic failure, and N is the number of years over which the rate is measured.36
Markov cost-effectiveness models require assumptions of the efficacy, utility, and cost of treatment options. The assumptions of the model and the probability distributions applied to these variables are noted in Table 1. These probabilities were extracted from an extensive literature review as well as a recent random-effects meta-analysis.3,7
The Phoenix definition (nadir +2) of biologic PFS (bPFS) was used, because this is the definition used in the recent SBRT 5-year study by King et al,25 which reported 93% bPFS at 5 years. However, given the still-maturing body of research investigating SBRT for prostate cancer, we conservatively assumed equal efficacy of SBRT as compared with IMRT. This variable was heavily scrutinized under sensitivity analysis. The risk of a patient becoming unresponsive to hormonal therapy was based on previous reports.27,37 A patient refractory to hormonal therapy was assumed to transition to the state of chemotherapy with a 1-year average life expectancy.28,38 The model captured othercause mortality through the application of actuarial life tables.35 Although there are several newly available treatments for patients with castrate-resistant prostate cancer, including sipuleucel- T and abiraterone acetate, their use is not standardized, and none are curative, with an average extension of life expectancy of approximately 4 months.39,40 We did not include them in our analysis, because they affect such a small fraction of patients; we did not feel they would have a significant impact on our model.
Patient-reported outcome (PRO) instruments used in various studies have included the Expanded Prostate Cancer Index Composite, American Urological Association
scale, Sexual Health Inventory for Men, and EuroQoL EQ-5D, among many others. Unfortunately, comparing utility of patients treated with IMRT or SBRT is difficult because of the lack of uniformity of these instruments in these studies and the fact that of the PRO instruments mentioned here, only the Euro-QoL measures utility. Because of the similarity among reported treatment-related toxicity, the base patient case assumed equal utility for IMRT and SBRT. The treatment-related utility of 0.90, which is used in the model, is consistent with several previous reports of utility scores for patients with prostate cancer treated with radiation.29,41 The utility of hormonal therapy was 0.68, as reported by Bayoumi et al30 and similar to that reported by Stewart et al.29 The utility of chemotherapy was estimated to be 0.4, which was based on reported QoL among patients with metastatic prostate cancer.30,31
The calculated costs reported by the model herein are the mean costs of the entire cohort analyzed in the model. For simplicity, mean costs will be referred to as costs. Costs were based on the 2010 ambulatory payment classification to estimate the technical component of treatment. The expected reimbursement from physician cost was calculated based on resource-based relative value units multiplied by the 2010 conversion factor, which estimates Medicare allowable costs. Thus, given these assumptions, the analysis took the perspective of the payer (Medicare). The annual cost of hormonal therapy with a luteinizing hormone—releasing hormone agonist was calculated based on the average wholesale price from the Drug Red Book. The cost of the last year of life, which also included the cost of chemotherapy in this model, was adapted from the literature and estimated to be $24,000.32 Costs and utilities were discounted at a rate of 3% per year as recommended by the Panel on Cost-Effectiveness in Health and Decision Making.42
Sensitivity analysis is used in cost-effective models to investigate the effect of adjusting base case assumptions such as costs, efficacy outcomes (ie, bPFS), utility measures (ie, QoL), and willingness-to-pay (WTP) thresholds. One- and 2-way sensitivity analyses were performed to investigate the impact on the model when adjusting the base case assumptions. Monte Carlo simulation with second-order probabilistic sensitivity analysis was performed to address the uncertainty inherent in the model assumptions. For radiation cost estimates, a triangular distribution was assumed using the average cost as the likeliest value with a ± 30% increment to define the range.43 All other costs were modeled using reported mean values, with standard deviations (SDs) to define normal distribution. A total of 5000 patients were used in the Monte Carlo simulation for probabilistic sensitivity analysis. This simulation was performed based on the ranges of values and distributions as noted in the model assumptions listed in Table 1. Treatment options that are both equally or more effective (higher QALYs) and less costly are described as dominating alternative treatment strategies. If, however, a treatment option is more effective but also more costly, then the medical benefit is reported as the incremental cost-effectiveness ratio (ICER).
Under the assumptions of the base case analysis, patients treated with SBRT had a mean QALY of 7.9 (SD, 0.47) and mean cost of $22,152, as compared with a mean QALY of 7.9 (SD, 0.47) and mean cost of $35,431 for a patient treated with IMRT. As expected, given the model assumptions of equal efficacy and utility, the model predicted equal effectiveness. The results from the probabilistic sensitivity analysis and acceptability curve revealed that SBRT dominated IMRT as a treatment strategy, and an ICER of <$50,000 per QALY was obtained in 66% of the model iterations.
Despite the initial 5-year bPFS of 93% as reported by King et al25 for SBRT, we acknowledge the data for SBRT efficacy are still maturing. The factors that affect cost-effectiveness are cost, utility (QoL), and efficacy (bPFS). One-way sensitivity analyses for bPFS and utility show that small changes in these variables can have a significant impact on the incremental cost-effectiveness ratio. We then proceeded with a 2-way sensitivity analysis, relaxing the assumptions regarding the efficacy (bPFS) and utility of SBRT, as summarized in Table 2. At interval decreases in efficacy of 2%, the 2-way sensitivity analysis revealed that at a near-6% decrease in the bPFS for SBRT, the IMRT ICER is $52,918, which approaches the widely accepted WTP value of $50,000 (). Similarly, if SBRT results in lower QoL than IMRT by 4.0%, then the ICER of IMRT reaches $49,979. Thus, Table 2 allows comparison of ICER assuming varying differences in bPFS and QOL between SBRT and IMRT.
We have shown under a wide range of assumptions varying efficacy, utility, and cost that SBRT for patients with lowor intermediate-risk prostate cancer would potentially be an attractive alternative to IMRT from the cost-effectiveness perspective of the payer. One- and 2-way sensitivity analyses showed that the model was most sensitive to QoL outcomes or PROs. As such, evaluating QoL is critical to assessing the cost-effectiveness of SBRT. PFS is also important but has a lesser impact on cost-effectiveness. The reason for this discrepancy is the fact that QoL outcomes affect all patients who receive treatment, yet differences in recurrence rates still affect only a small fraction. For example, a 5% decrease in QoL for 1 treatment results in an absolute decrease in QoL of 5%. On the other hand, a 50% increase in recurrence only affects an additional 1% of patients from 2% to 3%.
Although this decision analysis took the perspective of the payer, from a societal standpoint, the costs associated with treating prostate cancer are significant, with more than $12 billion per year being spent to treat patients with prostate cancer. 1 More than 100,000 patients per year are diagnosed with organ-confined prostate cancer, and 35% to 46% elect to undergo radiation therapy. At a savings of $13,000 per patient, if 50% of these patients were eligible for SBRT and treated with SBRT instead of IMRT, then a conservative societal-level savings would approach $250 million per year.1 In addition, from the patient perspective, the indirect cost savings of this hypofractionated treatment option, such as time lost from work and the treatment-related costs of transportation and housing, are substantial. Thus, the use of SBRT as an initial treatment option could potentially have a profound economic impact from both societal and individual patient perspectives as well.
This model builds on several studies that have evaluated the cost-effectiveness of radiation treatment options for patients with low- and intermediate-risk prostate cancer. These analyses have all been based on the decision analysis first modeled by Fleming et al.44 In a prior analysis, 3-dimensional conformational radiation therapy was compared with IMRT, with the conclusion that IMRT is a cost-effective treatment option given a societal WTP threshold of $50,000 per QALY, especially given the ability for improved dose escalation and sparing of normal structures.24 In a recently published robust analysis of initial treatment options for low-risk prostate cancer, Hayes et al7 examined several initial treatment options for low-risk prostate cancer including brachytherapy, IMRT, and prostatectomy as compared with active surveillance. This comparative effectiveness analysis concluded that active surveillance would be more effective than initial treatment based on a quality-adjusted life expectancy end point. Despite its emergence as a well-tolerated, noninvasive, efficacious treatment option, SBRT was not included in the model reported by Hayes et al. Given the impressive recent 5-year bPFS data reported by Freeman et al22 and King et al,26 with an accumulation of early toxicity data from several phase I and II SBRT trials showing highly comparable toxicity data, it is clear that SBRT warrants consideration as a cost-effective initial treatment option for patients with organ-confined prostate cancer.
There are several potential limitations to our model. First, the data on bPFS and long-term toxicity from SBRT for prostate cancer are still maturing; however, recent reports are promising, as shown in Table 1. The results of this study highlight the importance of utility outcomes or PROs, because late effects and toxicities to nearby normal tissues such as the rectum, bladder, and urethra could potentially affect patient-reported QoL as well as increase treatment-related costs in the model. Should late effects for SBRT prove to be higher, the actual impact of these toxicities as measured by PROs would be valuable in determining the cost-effectiveness of SBRT as compared with IMRT. Thus, a major limitation to the study is the lack of long-term utility data available on SBRT for prostate cancer. It is encouraging that a currently enrolling Radiation Therapy Oncology Group study is comparing a 5-fraction SBRT treatment course with a 12-fraction IMRT treatment course, with the primary end point of patient-reported QoL at 1 year. Additionally, Markov decision analyses implicitly require assumptions regarding cost, efficacy, and utility outcomes. Thus, these assumptions raise concerns regarding the accuracy of costs and transition rates given the variability of different practice patterns, local costs, and differences in reported prostate cancer outcomes in clinical trials. To account for these variances, Markov decision models typically employ Monte Carlo simulation, which uses a range of values with characteristic distributions for imputed variables to simulate a large cohort of patients. However, by assuming equal efficacy based on several published reports of 5-year bPFS for IMRT in dose-escalation trials, the model actually conservatively underestimated bPFS compared with the recent SBRT bPFS 5-year report by King et al.25
In conclusion, the recent 5-year bPFS data on SBRT for organ-confined prostate cancer are promising, and as such, the cost-effectiveness of SBRT has great potential in improving the treatment of organ-confined prostate cancer from the payer perspective in addition to patient and societal perspectives. Our study using the Markov decision tree with Monte Carlo simulation found that SBRT is more cost-effective than IMRT, assuming similar outcome measures. SBRT loses its cost-effectiveness with small decreases in QoL or effectiveness. Future studies evaluating SBRT need to focus on both acute and long-term QoL outcomes as well as efficacy.Acknowledgment
Presented at the 53rd Annual Meeting of the American Society of Therapeutic Radiation Oncology, Miami Beach, FL, October 2-6, 2011. We thank David Pistenmaa, MD, PhD, for his contribution and guidance in the preparation of this manuscript.
Author Affiliations: From University of Texas Southwestern (JCH, YL, RB, AB, RDT), Dallas, TX; and Northern Michigan Health (TPB), Petoskey, MI.
Authors’ Disclosures of Potential Conflicts of Interest
Although all authors completed the disclosure declaration, the following author(s) indicated a financial or other interest that is relevant to the subject matter under consideration in this article. Certain relationships marked with a “U” are those for which no compensation was received; those relationships marked with a “C” were compensated. For a detailed description of the disclosure categories, or for more information about ASCO’s conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
Employment or Leadership Position: None. Consultant or Advisory Role: None. Stock Ownership: None. Honoraria: None. Research Funding: Robert D. Timmerman, Varian Medical Systems, Acuray. Expert Testimony: None. Other Remuneration: None.
Conception and design: Joseph C. Hodges, Yair Lotan, Alyson Barrier, Robert D. Timmerman. Administrative support: Thomas P. Boike. Provision of study materials or patients: Yair Lotan, Thomas P. Boike, Rhonda Benton, Alyson Barrier, Robert D. Timmerman. Collection and assembly of data: Joseph C. Hodges, Yair Lotan, Alyson Barrier, Robert D. Timmerman. Data analysis and interpretation: Joseph C. Hodges, Yair Lotan, Rhonda Benton, Alyson Barrier, Robert Dale Timmerman. Manuscript writing: All authors. Final approval of manuscript: All authors.
Address correspondence to: Joseph C. Hodges, MD, MBA, 5801 Forest Park Rd, Dallas, TX 75390; e-mail: email@example.com. American Cancer Society: Cancer facts and figures 2012. http://www.cancer.org/Research/CancerFactsFigures/CancerFactsFigures/cancer-facts-figures-2012
2. Mariotto AB, Yabroff KR, Shao Y, et al: Projections of the cost of cancer care in the United States: 2010-2020. J Natl Cancer Inst 103: 117-128, 2011
3. Ollendorf DA, Hayes J, McMahon P, et al: Management options for low-risk prostate cancer: A report on comparative effectiveness and value. Boston, MA, Institute for Clinical and Economic Review, 2009
4. Centers for Medicare & Medicaid Services, Medicare Evidence Development and Coverage Advisory Committee: Comparative evaluation of radiation treatments for clinically localized prostate cancer: An update. Centers for Medicare & Medicaid Services, Baltimore, MD, 2010
5. Centers for Medicare & Medicaid Services, Medicare Evidence Development and Coverage Advisory Committee: Outcomes of sipuleucel-T therapy. Centers for Medicare & Medicaid Services, Baltimore, MD, 2011
6. Leonhardt D: In health reform, a cancer offers an acid test. New York Times, July 8, 2009:A1
7. Hayes JH, Ollendorf DA, Pearson SD, et al: Active surveillance compared with initial treatment for men with low-risk prostate cancer: A decision analysis. JAMA 304:2373-2380, 2010
8. Nguyen PL, Gu X, Lipsitz SR, et al: Cost implications of the rapid adoption of newer technologies for treating prostate cancer. J Clin Oncol 29:1517-1524, 2011
9. Timmerman R, Paulus R, Galvin J, et al: Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA 303:1070-1076, 2010
10. Rusthoven KE, Kavanagh BD, Burri SH, et al: Multi-institutional phase I/II trial of stereotactic body radiation therapy for lung metastases. J Clin Oncol 27:1579-1584, 2009
11. Schefter TE, Kavanagh BD, Timmerman RD, et al: A phase I trial of stereotactic body radiation therapy (SBRT) for liver metastases. Int J Radiat Oncol Biol Phys 62:1371-1378, 2005
12. Fowler JR, Chappell R, Ritter M: Is alpha/beta for prostate tumors really low? Int J Radiat Oncol Biol Phys 50:1021-1031, 2001
13. Brenner DJ, Hall EJ: Fractionation and protraction for radiotherapy of prostate carcinoma. Int J Radiat Oncol Biol Phys 43:1095-1101, 1999
14. D’Souza WD, Thames HD: Is the alpha/beta ratio for prostate cancer low? Int J Radiat Oncol Biol Phys 51:1-3, 2001
15. Daçu A: Is the alpha/beta value for prostate tumours low enough to be safely used in clinical trials? Clin Oncol (R Coll Radiol) 19:289-301, 2007
16. King CR, Brooks JD, Gill H, et al: Stereotactic body radiotherapy for localized prostate cancer: Interim results of a prospective phase II clinical trial. Int J Radiat Oncol Biol Phys 73:1043-1048, 2009
17. Boike TP, Lotan Y, Cho LC, et al: Phase I dose-escalation study of stereotactic body radiation therapy for low- and intermediate-risk prostate cancer. J Clin Oncol 29:2020-2026, 2011
18. Zietman AL, Bae K, Slater JD, et al: Randomized trial comparing conventional-dose with high-dose conformal radiation therapy in early-stage adenocarcinoma of the prostate: Long-term results from Proton Radiation Oncology Group/American College of Radiology 95- 09. J Clin Oncol 28:1106-1111, 2010
19. Zelefsky MJ, Fuks Z, Hunt M, et al: High-dose intensity modulated radiation therapy for prostate cancer: Early toxicity and biochemical outcome in 772 patients. Int J Radiat Oncol Biol Phys 53:1111-1116, 2002
20. Storey MR, Pollack A, Zagars G, et al: Complications from radiotherapy dose escalation in prostate cancer: Preliminary results of a randomized trial. Int J Radiat Oncol Biol Phys 48:635-642, 2000
21. Kuban DA, Tucker SL, Dong L, et al: Long-term results of the M. D. Anderson randomized dose-escalation trial for prostate cancer. Int J Radiat Oncol Biol Phys 70:67-74, 2008
22. Freeman DE, King CR: Stereotactic body radiotherapy for low-risk prostate cancer: Five-year outcomes. Radiat Oncol 6:3, 2011
23. Jabbari S, Weinberg VK, Kaprealian T, et al: Stereotactic body radiotherapy as monotherapy or post-external beam radiotherapy boost for prostate cancer: Technique, early toxicity, and PSA response. Int J Radiat Oncol Biol Phys 82:228-234, 2012
24. Konski A, Watkins-Bruner D, Feigenberg S, et al: Using decision analysis to determine the cost-effectiveness of intensity-modulated radiation therapy in the treatment of intermediate risk prostate cancer. Int J Radiat Oncol Biol Phys 66:408-415, 2006
25. King CR, Brooks JD, Gill H et al: Long-term outcomes from a prospective trial of stereotactic body radiotherapy for low-risk prostate cancer. Int J Radiat Oncol Biol Phys 82:877-882, 2012
26. King C: Stereotactic body radiotherapy for prostate cancer: Current results of a phase II trial. Front Radiat Ther Oncol 43:428-437, 2011
27. Shipley WU, Lu JD, Pilepich MV, et al: Effect of a short course of neoadjuvant hormonal therapy on the response to subsequent androgen suppression in prostate cancer patients with relapse after radiotherapy: A secondary analysis of the randomized protocol RTOG 86-10. Int J Radiat Oncol Biol Phys 54:1302-1310, 2002
28. Beekman KW, Fleming MT, Scher HI, et al: Second-line chemotherapy for prostate cancer: Patient characteristics and survival. Clin Prostate Cancer 4:86-90, 2005
29. Stewart ST, Lenert L, Bhatnagar V, et al: Utilities for prostate cancer health states in men aged 60 and older. Med Care 43:347-355, 2005
30. Bayoumi AM, Brown AD, Garber AM: Cost-effectiveness of androgen suppression therapies in advanced prostate cancer. J Natl Cancer Inst 92:1731-1739, 2000
31. Albertsen PC, Aaronson NK, Muller MJ, et al: Health-related quality of life among patients with metastatic prostate cancer. Urology 49:207- 216; discussion 216-217
32. Piper NY, Kusada L, Lance R, et al: Adenocarcinoma of the prostate: An expensive way to die. Prostate Cancer Prostatic Dis 5:164-166, 2002
33. Sonnenberg FA, Beck JR: Markov models in medical decision making: A practical guide. Med Decis Making 13:322-338, 1993
34. Weinstein MC, Skinner JA: Comparative effectiveness and health care spending: Implications for reform. N Engl J Med 362:460-465, 2010
35. Social Security Administration: Actuarial life table 2010. http://www.ssa.gov/oact/NOTES/as120/LifeTables_Body.html
36. Miller DK, Homan SM: Determining transition probabilities: Confusion and suggestions. Med Decis Making 000000014:52-58, 1994
37. Pound CR, Partin AW, Eisenberger MA, et al: Natural history of progression after PSA elevation following radical prostatectomy. JAMA 281:1591-1597, 1999
38. Oefelein MG, Agarwal PK, Resnick MI: Survival of patients with hormone refractory prostate cancer in the prostate specific antigen era. J Urol 171:1525-1528, 2004
39. de Bono JS, Logothetis CJ, Molina A, et al: Abiraterone and increased survival in metastatic prostate cancer. N Engl J Med 364:1995- 2005, 2011
40. Kantoff PW, Higano CS, Shore ND, et al: Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N Engl J Med 363:411-422, 2010
41. Konski A, Speier W, Hanlon A, et al: Is proton beam therapy cost effective in the treatment of adenocarcinoma of the prostate? J Clin Oncol 25:3603-3608, 2007
42. Gold MR, Siegel JE, Russell LB, et al (eds): Cost-Effectiveness in Health and Medicine. New York, NY, Oxford University Press, 1996, 1-333
43. Meuning P: Cost-Effectiveness in Healthcare: A Practical Approach (ed 2). San Francisco, CA, Jossey-Bass, 2007
44. Fleming C, Wasson JH, Albertsen PE, et al: A decision analysis of alternative treatment strategies for clinically localized prostate cancer: Prostate Patient Outcomes Research Team. JAMA 269:2650-2658, 1993