Health care costs for prostate cancer patients receiving androgen deprivation therapy: treatment and adverse events

Original Articles

Urologic Oncology

Health care costs for prostate cancer patients receiving androgen deprivation therapy: treatment and adverse events


M.D. Krahn , MD MSc * ,,, § , # , K.E. Bremner , BSc , * , J. Luo , MSc # , S.M.H. Alibhai , MD MSc * ,

*Toronto General Research Institute, Toronto General Hospital, Toronto, ON.
Department of Medicine, Toronto General Hospital, Toronto, ON.
Faculty of Pharmacy, University of Toronto, Toronto, ON.
§ Department of Medicine, University of Toronto, Toronto, ON.
Toronto Health Economics and Technology Assessment Collaborative, Toronto, ON.
# Institute for Clinical Evaluative Sciences, Toronto, ON.


doi: http://dx.doi.org/10.3747/co.21.1865


ABSTRACT

Background

Serious adverse events have been associated with androgen deprivation therapy ( adt ) for prostate cancer ( pc a), but few studies address the costs of those events.

Methods

All pc a patients (ICD-9-CM 185) in Ontario who started 90 days or more of adt or had orchiectomy at the age of 66 or older during 1995–2005 ( n = 26,809) were identified using the Ontario Cancer Registry and drug and hospital data. Diagnosis dates of adverse events—myocardial infarction, acute coronary syndrome, congestive heart failure, stroke, deep vein thrombosis or pulmonary embolism, any diabetes, and fracture or osteoporosis—before and after adt initiation were determined from administrative data. We excluded patients with the same diagnosis before and after adt , and we allocated each patient’s time from adt initiation to death or December 31, 2007, into health states: adt (no adverse event), adt - ae (specified single adverse event), Multiple (>1 event), and Final (≤180 days before death). We used methods for Canadian health administrative data to estimate annual total health care costs during each state, and we examined monthly trends.

Results

Approximately 50% of 21,811 patients with no pre- adt adverse event developed 1 or more events after adt . The costliest adverse event state was stroke ($26,432/year). Multiple was the most frequent ( n = 2,336) and the second most costly health state ($24,374/year). Costs were highest in the first month after diagnosis (from $1,714 for diabetes to $14,068 for myocardial infarction). Costs declined within 18 months, ranging from $784 per 30 days (diabetes) to $1,852 per 30 days (stroke). Adverse events increased the costs of adt by 100% to 265%.

Conclusions

The economic burden of adverse events is relevant to programs and policies from clinic to government, and that burden merits consideration in the risks and benefits of adt .

KEYWORDS: Prostatic neoplasms , androgen deprivation therapy , costs , adverse events , cost analysis

1. INTRODUCTION

Prostate cancer ( pc a) is the most common cancer in men in developed countries1. Many patients receive androgen deprivation therapy ( adt ) as primary therapy for all stages of disease or in addition to primary surgery or radiotherapy25. Luteinizing hormone–releasing hormone ( lhrh ) agonists and anti-androgens are now the main types of adt ; bilateral orchiectomy and estrogen are less popular57.

Recently, adt has been viewed less favourably because of an awareness about its potential harms and its costs. Associated adverse events include hot flashes, sexual dysfunction, gynecomastia, increase in fat mass810, and of greater concern, decline in bone mineral density, with a potential risk of fracture1113. Also concerning is that adt has been associated with a type of metabolic syndrome (increased cholesterol, triglycerides, and insulin resistance)14, diabetes, and possibly myocardial infarction ( mi ) and sudden cardiac death1416. Androgen deprivation therapy is costly: in 2013, one 3-month depot preparation of lhrh agonist cost approximately CA$1,100 in Ontario17, and many patients are treated for years. Additional costs can be incurred to prevent or treat adverse events. One study reported an increase of $13,807 (2004 U.S. dollars) in 3-year adt costs for fracture treatment18.

The purpose of the present study was to estimate total health care costs in pc a patients receiving adt in the province of Ontario, and to quantify the additional costs associated with the frequently-documented, serious, and potentially costly adverse events associated with adt .

2. METHODS

2.1  Ethics

The study was approved by the Research Ethics Board of the University Health Network, Toronto, Ontario.

2.2  Patient Selection

From the Ontario Drug Benefit ( odb ) program database (http://www.health.gov.on.ca/en/pro/programs/drugs/odbf_mn.aspx), we selected outpatient prescription records ( n = 60,690) of men who began at least 90 consecutive days of lhrh agonist, estrogen, or antiandrogen from January 1, 1995, to December 31, 2005. The odb program covers the costs of most outpatient prescriptions for Ontario residents 65 years of age and older. We specified 90 days because it is the recommended minimum therapeutic period of adt given for any indication19. Following standard practice, we allowed patients up to 50% of the number of days of drug supplied to refill the prescription20. Thus, a patient had up to 45 days to refill a prescription for a 30-day depot injection of an lhrh agonist or to obtain a new adt prescription.

We combined the foregoing patient records with the records of patients who underwent bilateral orchiectomy as recorded in health care administrative databases during 1995–2005 ( n = 13,561). We combined all records for each patient to obtain a cohort of 52,855 unique adt recipients who received pharmacologic adt , surgical adt , or both. We defined each patient’s index date as the first date of any adt .

We linked those patients to the Ontario Cancer Registry21 and included all patients with an initial diagnosis of pc a (International Classification of Diseases code ICD-9-CM 185), but no other primary cancer, before or within 6 months after their adt index date ( n = 33,141). We excluded patients less than 66 years of age at the index date so that prescription drug data for a full year were available to assess prior adt . Other exclusion criteria were sex coded as female or missing, non-Ontario residence, invalid or missing Ontario Health Insurance Plan ( ohip ) number, missing histology code in the Ontario Cancer Registry, and death within 90 days after the index date. After those exclusions, 29,554 patients remained. Using the odb program database, we then identified and excluded patients who had received any pharmacologic adt before January 1, 1995, and before age 66, and using hospital records, we excluded those who had undergone orchiectomy before January 1, 1995, and as far back as 1988 ( n = 2745).

The final cohort numbered 26,809. After determining pre- and post- adt adverse events, we excluded patients who experienced the same adverse event before and after adt , leaving 21,811 patients for the subsequent analyses. We followed patients from the start of adt until death or until December 31, 2007.

2.3  Data and Costing

All medically necessary health care for permanent residents of Ontario is covered under ohip (http://www.health.gov.on.ca/en/public/programs/ohip). We identified and costed all resources used by each patient and paid by ohip from the patient’s index date (start of adt ) until death or December 31, 2007. Most data were available at the Institute for Clinical Evaluative Sciences, Toronto, Ontario. Radiation therapy and New Drug Funding Program data were obtained from Cancer Care Ontario. Data were linked using the patient’s unique ohip number and anonymized.

Hospital admissions were determined using the Discharge Abstract Database from the Canadian Institute for Health Information (http://www.cihi.ca/cihi-ext-portal/internet/en/document/types+of+care/hospital+care/acute+care/dad_metadata). Outpatient visits, including those to regional cancer centres, were determined using the National Ambulatory Care Reporting System from the Canadian Institute for Health Information (http://www.cihi.ca/CIHI-ext-portal/internet/en/document/types+of+care/hospital+care/emergency+care/NACRS_METADATA). Every record is assigned a resource intensity weight associated with its case-mix group (developed by the Canadian Institute for Health Information22). Using standard costing procedures, we estimated costs by multiplying the resource intensity weight by the cost per weighted case in Ontario for the year of use22,23. We included cancer drugs and costs recorded in the New Drug Funding Program (https://www.cancercare.on.ca/toolbox/drugs/ndfp). That program reimburses cancer centres and hospitals for expensive chemotherapy approved for specific cancers. Costs for pharmacologic adt and other outpatient prescription medications were identified from the odb program database.

We used the ohip Claims History database to identify costs for inpatient and outpatient physician services and outpatient diagnostic tests. Data from the Radiation Oncology Research Unit database were used to identify curative and palliative radiation therapy. In Ontario, many radiation oncologists receive all or a portion of their income through alternative funding plans24. We estimated that income (in addition to ohip claims) from responses on the 2004 and 2007 National Physician surveys (http://nationalphysiciansurvey.ca/).

We used the Home Care Database and Ontario Home Care Administrative System data to identify home care services, and we obtained average service costs from Community Care Access Centres in Toronto (http://healthcareathome.ca/).

We included stays at complex continuing care facilities. Each stay is assigned a case-mix index indicating the intensity of the required care. We multiplied that index by the length of stay and the provincial average cost per weighted chronic day for the year of stay.

All costs were adjusted to 2009 Canadian dollars using the Consumer Price Index for health23,25,26. We summed all resource costs for each patient to estimate total health care costs.

2.4  Comorbidity and Demographics

We described comorbid illness by categorizing all of the ICD-9 or ICD-9-CM and ICD10 diagnostic codes in hospital records and physicians’ billings data in the year before each patient’s index date into one of nearly 90 adjusted clinical groups, a population–patient case-mix adjustment system27. Being interested in the burden of comorbidity, we classified patients into groups of 0–3, 4–6, 7–9, or 10+ adjusted clinical groups, representing low, moderate, high, and very high comorbidity respectively27.

We used the Statistics Canada Postal Code Conversion file and data from the 2001 Canadian census to assign patient postal codes to standard geographic areas, for which data on neighbourhood-level median household income quintiles and rurality were obtained.

2.5  Adverse Events and Health States

We used diagnosis codes in several of the administrative databases to identify the following serious adverse events that have been associated with adt in the literature: mi , acute coronary syndrome ( acs ), congestive heart failure ( chf ), stroke, deep vein thrombosis or pulmonary embolism, diabetes (any type), and fracture or osteoporosis15. We determined the diagnosis dates of those events in the 3 years before each patient’s index date (before adt ) and any time after each patient’s index date to December 31, 2007, or date of death (after adt ). Patients could experience more than 1 adverse event in each time period.

After excluding patients who had experienced the same event before and after adt , we divided each patient’s post- adt observation time into mutually-exclusive health states, similar to those used in health-state transition models (Markov models)28. Such models characterize the course of a disease, with transitions between health states. A single patient moves from one health state to another, but can be in only one health state at any given time. The three major health states in our study were adt (no adverse events), adt - ae (diagnosis of an adverse event), and Final (date of death and up to 180 days before the date of death).

The adt health state represented time on adt with no adverse events, and before 180 days before death. When and if an adverse event was diagnosed, patients entered the adt - ae state, which was labelled according to the adverse event: mi , acs , chf , stroke, deep vein thrombosis or pulmonary embolism, diabetes, or fracture or osteoporosis. When patients experienced a different adverse event, they entered the Multiple state on the first day of the second type of adverse event. As a hypothetical example, consider a patient who did not die during the study observation period; whose adt index date was March 1, 2000; who was diagnosed with diabetes on December 1, 2000; and who then experienced a mi on June 1, 2001. His sequence of health states would be: adt from March 1, 2000, to November 30, 2000; mi from December 1, 2000, to May 31, 2001; and Multiple from June 1, 2001, to December 31, 2007.

Patients who did not die and experienced no adverse events were in the adt state for all of their observation time. Patients who died were in the Final state for the 180 days before death (but not extending before the start of adt ). The Final state superseded all other states. For example, if the hypothetical patient in the earlier example had died on November 30, 2003, his Multiple state would have ended on June 2, 2003, and he would have been in the Final state from June 3, 2003, to November 30, 2003.

A patient who died within 180 days after his index date spent all of his observation time in the Final state. Because patients might have died within 180 days after December 31, 2007, we looked forward 179 days from December 31, 2007, to check for a date of death. All days between the death date minus 180 days and December 31, 2007, were assigned to the Final state.

2.6  Statistical Methods

We described patient characteristics using means and standard deviations for continuous variables and frequency counts for categorical variables. We counted the number of patients who experienced each adverse event before and after the start of adt and expressed it as a rate per 100 patient–years to account for the longer post- adt period. Based on Poisson distribution, we calculated 95% confidence intervals for the rates; confidence intervals that do not overlap are statistically significant29. After selecting patients with newly-diagnosed post- adt adverse effects and allocating their time into states, we calculated the number of patients with time in each state and the state durations. To describe progression through the states, we examined the cohort cross-sectionally at 1 year, 3 years, and 5 years after the start of adt and determined the number of patients in each health state.

We estimated total health care costs during each patient’s observation time, as earlier described, and we then computed the total costs for all resources incurred by each patient during the time spent in each health state. Because each patient spent a variable amount of time in each state, we reported costs per state standardized to 1 year. Within each state, mean cost per year was computed as follows:

Mean cost per year = (total costs for all patients / number of person-days) ) 365.25.

The result was halved for the 6-month Final state. We computed annual costs per state (6-month costs for the Final state) for all patients, for two age groups (66–74 years and 75+ years at the start of the state), and for three comorbidity groups (0–6, 7–9, or 10+ adjusted clinical groups at the patient’s index date). Most of the adverse effects would require intense intervention immediately after diagnosis, with less-intense follow-up. We examined the mean cost in the first 30 days and the mean cost in the remainder of each health state separately.

To estimate time trends, we computed mean total costs for each 30-day period from the first day of each health state to the maximum length of the state. The total cost for all patients who had any time in each 30-day period was divided by the number of patients with time in those 30 days until the maximum length of the state was reached and no patients remained.

All analyses were conducted using the SAS statistical software (version 9.1.3: SAS Institute, Cary, NC, U.S.A.).

3. RESULTS

Table i describes the characteristics of the initial cohort of 26,809 patients and of our selected cohort of 21,811 who did not experience the same adverse event before and after adt . The mean age of the 21,811 patients was 75.4 years, and 56% were 70–79 years of age. Approximately 60% were diagnosed during 1990–1999, and 41% were diagnosed during 2000–2005. By December 31, 2007, 54% of the patients were alive. The 21,811 patients who had experienced new post- adt adverse events had more comorbidities than the entire cohort of 26,809 patients because the adverse events contributed to comorbidity.

TABLE I   Characteristics of the patient cohort at the index date

 

Table ii shows how many of the 26,809 patients experienced each event before and after the start of adt . Diabetes was the most common condition in both time periods, diagnosed in 3574 patients before adt and in 5614 after. The incidence of fracture or osteoporosis—diagnosed in 1199 patients before adt (rate: 1.49 per 100 patient–years) and in 4508 after adt (rate: 3.32 per 100 patient–years)—increased more than any other adverse event. The diagnosis rate of the least-frequent adverse event, acs , showed no significant increase after adt .

TABLE II  Number of patients experiencing each adverse event before and after initiation of androgen deprivation therapy ( adt )

 

Table iii shows the allocation of observation time to health states (after exclusion of patients who had the same adverse event before and after adt ). Almost all patients (98%) had time in the adt state. Approximately 37% of patients ( n = 8095) spent time in at least one adverse event state. Diabetes was the most common and longest adverse event state ( n = 1775; mean duration: 1120 days). Many patients experienced more than one adverse event, and 2336 patients spent time in the Multiple state. The shortest state, chf , had a mean length of 753 days. Thus, many patients died or developed another adverse event after chf .

TABLE III  Summary of each health state for all patients with a new adverse event after androgen deprivation therapy ( adt )

 

Figure 1 shows the proportion of patients in each health state at 1, 3, and 5 years after their index date, excluding patients who died (7%, 30%, and 50% of the entire cohort at 1, 3, and 5 years respectively). After 1 year of adt , only 9.5% of the surviving patients were in an adverse event health state. Over time, the percentage of patients in adt decreased, and patients moved into adverse event states and died. The most common adverse event states 5 years after adt initiation were diabetes and stroke.

 


 

FIGURE 1 Distribution of surviving patients among health states at 1 year, 3 years, and 5 years after the start of androgen deprivation therapy ( adt ). acs = acute coronary syndrome; chf = congestive heart failure; dvt = deep vein thrombosis or pulmonary embolism; Osteo = osteoporosis; mi = myocardial infarction.

3.1  Costs per Health State

Overall, the least costly health state was adt . The mean cost per year was $9,959 (Table iii). Adverse events (except for diabetes) increased the cost of adt by approximately 150% ( acs and deep vein thrombosis) to 265% (stroke), over the length of the entire state. The most costly adverse event state was stroke ($26,432 annually); diabetes was the least costly ($9,850 annually). The most costly health state was Final. The mean cost for the 6-month period before death was $26,091, a 524% increase over the cost for the adt state.

Costs for all health states except Final increased with age (Table iii). The mean cost in the 6-month Final state was $28,666 for patients 66–74 years of age and $24,520 for older patients, likely reflecting less-intense end-of-life interventions for the oldest patients. Changes in costs across comorbidity strata were smaller and less consistent. For example, mean mi costs were $17,179 and $19,249 per year for patients with a low and high burden of comorbidity respectively.

3.2  Trends in Costs

Figure 2 shows the mean cost in the first 30 days of each health state and the mean cost in the remaining time. The first 30 days of the adt state cost approximately 4.5 times the mean cost per 30 days for the remainder of the state. The mean cost in the first 30 days of the mi and acs states was, respectively, 15 and 11 times that of the subsequent mean 30-day cost. However, the 30-day cost for the Final state increased as death approached.

 


 

FIGURE 2 Mean health state costs per 30 patients–days in the first 30-day period and in the remainder of each state. cdn = Canadian; adt = androgen deprivation therapy; mi = myocardial infarction; acs = acute coronary syndrome; chf = congestive heart failure; dvt / pe = deep vein thrombosis or pulmonary embolism; Fx/osteo = fracture or osteoporosis; Mult = multiple events.

After the first 30 days, the mean cost per 30-day period in the adt and adverse event states gradually declined until stabilizing at approximately 12 months. Figure 3 shows, for adt and for 4 representative adverse event phases (stroke, osteoporosis or fracture, diabetes, and Multiple) the mean cost for each 30 days after adt initiation, from the 2nd to the 60th period (5 years). By 5 years, 10%–23% of the patients who had started each state were still in that state. To facilitate observation of trends, the data have been smootheda. Patients with stroke and with fracture or osteoporosis incurred high costs for approximately 1 year after onset. Diabetes had the lowest cost of all adverse events. The Multiple state had the highest cost over most of the follow-up time, because it included the costs of 2 or more adverse events (Figure 3).

 


 

FIGURE 3 Mean costs for androgen deprivation therapy ( adt ) and selected representative adverse event health states per 30 days for the first 5 years after the first 30 days. cdn = Canadian; dm = diabetes mellitus; fx = fracture; str = stroke; mult = multiple events. Data have been smoothed for plotting the graph30.

Patients in the Final state incurred higher costs as death approached (data not shown). Mean cost per patient steadily increased from $2,655 in the 6th month before death to $7,616 in the 30 days before death.

4. DISCUSSION

This study, like others, showed that adverse events are common after receiving adt . Approximately 50% of our cohort of pc a patients treated with at least 90 days of adt developed one or more of the adverse events that have been documented as potential side effects. We also showed that the cost of care for individuals who experience one of those adverse events is very substantial. Our study makes the unique contribution of quantifying those economic costs. After the occurrence of adverse events, total health care costs ranged from 99% (diabetes) to 524% (multiple events) of baseline adt costs.

Our study is, to our knowledge, the only one to have examined the health care costs associated with 7 adverse events (and their combinations) that have been documented as side effects of adt . Other studies have examined the overall cost of care in patients receiving adt 3034 or the cost of treating or preventing fragility fractures in this population18,35. Other strengths of our study include the use of a large population-based sample of all pc a patients 66 years of age and older who received adt in a large Canadian province. Our costing approach was comprehensive: the data included all records of the costed resources, and the public health care system covered almost all of the direct costs. In contrast, in the United States, the costs would have been borne by some combination of public insurance (for example, Medicare), private insurance, and the patients themselves. Costs that we did not consider include patient-borne indirect costs for travel and time associated with obtaining health care, which would likely to be higher among patients with adverse effects. We did not examine use of, or costs for, over-the-counter drugs or complementary and alternative medicine, which are not covered by ohip .

We defined a Final state because other studies have shown that end-of-life is an extremely costly period36,37. Extending the adt and adverse event states until death would greatly increase the overall costs of adt and the adverse events. However, adverse events that occurred within 6 months before death are not identified in our study.

Our study design did not allow inference about causality. We cannot estimate with confidence the rate at which complications increased because of adt therapy. However, we can say how much the adverse effects cost. We provide accurate estimates of the total cost profiles for pc a patients who experienced adverse events that have been documented to be common adt complications, including trends in costs over short time periods and across age and comorbidity strata. We believe that our estimates of the costs associated with adverse effects, in conjunction with estimates of attributable risk drawn from other published studies, will be invaluable in predicting the health and economic consequences of alternative adt strategies for pc a. In particular, such costs are extremely useful for informing pharmacoeconomic and cost-effectiveness models, which are typically state-transition models. They incorporate health states, such as those defined in our study, representing the disease, disease treatment, and treatment outcomes. Our study provides valid and robust estimates of the total cost of health care associated with adt and its most common adverse effects.

5. CONCLUSIONS

Our analysis found that adverse events increased the cost of adt by up to 500% and thus added a considerable economic burden to the care of patients receiving adt . Clinical practice guidelines and reimbursement recommendations should consider the health care costs related to adverse events in the risk–benefit calculation of adt . Our methods can be applied to cohorts of patients who have received new types of adt , including abiraterone and enzalutamide for metastatic castration-resistant pc a38,39, when long-term data are available. To understand the additional total costs associated with adt care, comprehensive analyses matching similar patients who did and did not receive adt should be conducted.

6. ACKNOWLEDGMENTS

This work was supported by the Canadian Cancer Research Society under the Prostate Cancer Research Initiative (grant no. 18090), and the Ontario Public Drug Programs Drug Innovation Fund (grant no. 2008-0100). Other support was provided by the F. Norman Hughes Chair in Pharmacoeconomics (MDK), and a Research Scientist Award from the Canadian Cancer Society (SMHA).

Preliminary results of this study have been presented as a poster (Krahn MD, Bremner KE, Luo J, Alibhai SMH. Using Ontario administrative data to estimate health care costs of drug adverse effects: the case of prostate cancer. Presented at the Ontario Institute for Cancer Research/Cancer Care Ontario Fourth Annual Meeting; Toronto, ON; May 17, 2012) and as an oral presentation (Krahn MD, Bremner KE, Luo J, Alibhai SMH. Using administrative databases to estimate health care costs from adverse drug effects: the case of prostate cancer. Presented at the 14th Biennial European Meeting of the Society for Medical Decision Making; Oslo, Norway; June 10–12, 2012). The abstract has been published online only in Medical Decision Making (doi: 10.1177/0272989X12455402).

7. CONFLICT OF INTEREST DISCLOSURES

The authors have no financial conflicts of interest.

8. REFERENCES

1. Bray F, Jemal A, Grey N, Ferlay J, Forman D. Global cancer transitions according to the Human Development Index (2008–2030): a population-based study. Lancet Oncol 2012;13:790–801.
cross-ref  pubmed  

2. Chang SL, Liao JC, Shingal R. Decreasing use of luteinizing hormone–releasing hormone agonists in the United States is independent of reimbursement changes: a Medicare and Veterans Health Administration claims analysis. J Urol 2009;182:255–60.
cross-ref  

3. Cooperberg MR, Grossfield GD, Lubeck DP, Carroll PR. National practice patterns and time trends in androgen ablation for localized prostate cancer. J Natl Cancer Inst 2003;95:981–9.
cross-ref  pubmed  pmc  

4. Weight CJ, Klein EA, Jones SJ. Androgen deprivation falls as orchiectomy rates rise after changes in reimbursement in the U.S. Medicare population. Cancer 2008;112:2195–201.
cross-ref  pubmed  

5. Krahn MD, Bremner KE, Tomlinson G, et al. Androgen deprivation therapy in prostate cancer: are rising concerns leading to falling use? BJU Int 2011;108:1588–96.
cross-ref  pubmed  

6. Bondy SJ, Iscoe N, Rothwell DM, et al. Trends in hormonal management of prostate cancer: a population-based study in Ontario. Med Care 2001;39:384–396.
cross-ref  pubmed  

7. Shaninian VB, Kuo YF, Freeman JL, Orihuela E, Goodwin JS. Increasing use of gonadotrophin-releasing hormone agonists for the treatment of localized prostate carcinoma. Cancer 2005;103:1615–24.
cross-ref  

8. Sharifi N, Gulley JL, Dahut WL. Androgen deprivation therapy for prostate cancer. JAMA 2005;294:238–44.
cross-ref  pubmed  

9. Holzbeierlein JM. Managing complications of androgen deprivation therapy for prostate cancer. Urol Clin North Amer 2006;33:181–90.
cross-ref  

10. Alibhai SM, Gogov S, Allibhai Z. Long-term side effects of androgen deprivation therapy in men with non-metastatic prostate cancer: a systematic literature review. Crit Rev Oncol Hematol 2006;60:201–15.
cross-ref  pubmed  

11. Shahinian VB, Kuo YF, Freeman JL, Goodwin JS. Risk of fracture after androgen deprivation for prostate cancer. N Engl J Med 2005;353:154–64.
cross-ref  

12. Greenspan SL, Coates P, Sereika SM, Nelson JB, Trump DL, Resnick NM. Bone loss after initiation of androgen deprivation therapy in patients with prostate cancer. J Clin Endocrinol Metab 2005;90:6410–17.
cross-ref  pubmed  

13. Alibhai SM, Duong–Hua M, Cheung AM, et al. Fracture types and risk factors in men with prostate cancer on androgen deprivation therapy: a matched cohort study of 19,079 men. J Urol 2010;184:918–23.
cross-ref  pubmed  

14. Saylor PJ, Smith MR. Metabolic complications of androgen deprivation therapy for prostate cancer. J Urol 2009;181:1998–2006.
cross-ref  pubmed  pmc  

15. Alibhai SMH, Duong–Hua M, Sutradhar R, et al. Impact of androgen deprivation therapy on cardiovascular disease and diabetes. J Clin Oncol 2009;27:3452–8.
cross-ref  pubmed  

16. Keating NL, O’Malley AJ, Freedland SJ, Smith MR. Diabetes and cardiovascular disease during androgen deprivation therapy: observational study of veterans with prostate cancer. J Natl Cancer Institute 2010;102:39–46.
cross-ref  

17. Ontario Ministry of Health and Long-Term Care. Ontario Drug Benefit Formulary/Comparative Price Index: Edition 42. Toronto, ON: Queen’s Printer for Ontario; 2013. [Available online at: http://www.health.gov.on.ca/en/pro/programs/drugs/formulary42/edition_42.pdf; cited January 17, 2014]

18. Krupski TL, Foley KA, Baser O, Long S, Macarios D, Li-twin MS. Health care cost associated with prostate cancer, androgen deprivation therapy and bone complications. J Urol 2007;178:1423–8.
cross-ref  pubmed  

19. National Collaborating Cancer for Cancer (ncc-c) for the U.K. National Institute for Health and Care Excellence. Prostate Cancer: Diagnosis and Treatment. Cardiff, U.K.: ncc-c; 2008. [Available online at: http://www.nice.org.uk/nicemedia/live/14348/66232/66232.pdf; cited March 15, 2013]

20. Juurlink DN, Gomes T, Mamdani MM, Gladstone DJ, Kapral MK. The safety of proton pump inhibitors and clopidogrel in patients after stroke. Stroke 2011;42:128–32.
cross-ref  

21. Hall S, Schulze K, Groome P, McKillop W, Holowaty E. Using cancer registry data for survival studies: the example of the Ontario Cancer Registry. J Clin Epidemiol 2006;59:67–76.
cross-ref  

22. Jacobs P, Yim R. Using Canadian Administrative Databases to Derive Economic Data for Health Technology Assessments. Ottawa, ON: Canadian Agency for Drugs and Technologies in Health; 2009.

23. Bushmeneva K, Nikitovic M, Wodchis PW. Guidelines on Case-Costing Using Administrative Databases in Ontario. Toronto, ON: Health System Performance Research Network; 2011.

24. Godwin M, Seguin R, Wilson R. Queen’s University alternative funding plan. Effect on patients, staff, and faculty in the Department of Family Medicine. Can Fam Physician 2000;46:1438–44.
pubmed  pmc  

25. Statistics Canada. Consumer Price Index, health and personal care, by province (Ontario) [Web page]. Ottawa, ON: Statistics Canada; n.d. [Most recent version available at: http://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/econ161geng.htm; cited October 15, 2013]

26. Statistics Canada. Your Guide to the Consumer Price Index. Cat. no. 62-557-XPB. Ottawa, ON; Statistics Canada; 1996.

27. Reid RJ, MacWilliam L, Verhulst L, Roos N, Atkinson M. Performance of the acg case-mix system in two Canadian provinces. Med Care 2001;39:86–99.
cross-ref  pubmed  

28. Sonnenberg FA, Beck JR. Markov models in medical decision making: a practical guide. Med Decis Making 1983;13322–8.

29. Asthma Initiative of Michigan. Asthma methods [Web page]. Lansing, MI: Asthma Initiative of Michigan; n.d. [Available at: http://www.getasthmahelp.org/michigan-asthma-statistics-methods.aspx; cited October 15, 2013]

30. Bonzani RA, Stricker HJ, Peabody JO, Menon M. Cost comparison of orchiectomy and leuprolide in metastatic prostate cancer. J Urol 1998;160:2446–9.
cross-ref  pubmed  

31. Mariani AJ, Glover M, Arita S. Medical versus surgical androgen suppression therapy for prostate cancer: a 10-year longitudinal cost study. J Urol 2001;165:104–7.
cross-ref  

32. Sangar VK, Ragavan N, Matanhelia SS, Watson MW, Blades RA. The economic consequences of prostate and bladder cancer in the UK. BJU Int 2005;95:59–63.
cross-ref  pubmed  

33. Snyder CF, Frick KD, Blackford AL, et al. How does initial treatment choice affect short-term and long-term costs for clinically localized prostate cancer? Cancer 2010;116:5391–9.
cross-ref  pubmed  

34. Wilson LS, Tesoro, Elkin EP, et al. Cumulative cost pattern comparison of prostate cancer treatments. Cancer 2007;109:518–27. [Erratum in: Cancer 2007;109:2155]
cross-ref  

35. Ito K, Elkin EB, Girotra M, Morris MJ. Cost-effectiveness of fracture prevention in men who receive androgen deprivation therapy for localized prostate cancer. Ann Intern Med 2010;152:621–9.
cross-ref  pubmed  

36. Brown ML, Riley GF, Schussler N, Etzioni R. Estimating health care costs related to cancer treatment from seer–Medicare data. Med Care 2002;40(suppl):iv-104–17.
cross-ref  

37. Krahn MD, Zagorski B, Laporte A, et al. Health care costs associated with prostate cancer: estimates from a population-based study. BJU Int 2010;105:338–46.
cross-ref  

38. Seal BS, Asche CV, Puto K, Allen PD. Efficacy, patient-reported outcomes (pros), and tolerability of the changing therapeutic landscape in patients with metastatic prostate cancer (mpc): a systematic literature review. Value Health 2013;16:872–90.
cross-ref  pubmed  

39. Bahl A, Masson S, Birtle A, Chowdhury S, de Bono J. Second-line treatment options in metastatic castration-resistant prostate cancer: a comparison of key trials with recently approved agents. Cancer Treat Rev 2014;40:170–7.
cross-ref  


Correspondence to: Karen E. Bremner, Toronto General Hospital, 200 Elizabeth Street, Room EN13– 222A, Toronto, Ontario M5G 2C4. E-mail: kbremner@uhnresearch.ca

(Return to Top)


aCucka J. A macro for efficient and flexible data smoothing. Presented at the Midwest SAS User Group Conference; Chicago, IL, U.S.A.; September 28–30, 1997. [Available online at: http://www2.sas.com/proceedings/sugi22/CODERS/PAPER85.PDF; cited October 15, 2013] ( Return to Text )


Current Oncology , VOLUME 21 , NUMBER 3 , JUNE 2014








Copyright © 2019 Multimed Inc.
ISSN: 1198-0052 (Print) ISSN: 1718-7729 (Online)