Relative Effectiveness of Osteoporosis Treatments to Reduce ......in patients with non-metastatic...
Transcript of Relative Effectiveness of Osteoporosis Treatments to Reduce ......in patients with non-metastatic...
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Relative Effectiveness of Osteoporosis Treatments to Reduce Hip Fractures in Patients with Prostate Cancer on Continuous Androgen
Deprivation Therapy:
Systematic Review, Network Meta-Analysis and Cost-Effectiveness Analysis
by
Yeesha Poon
A thesis submitted in conformity with the requirements
for the degree of Doctor of Philosophy
Department of Pharmaceutical Sciences
University of Toronto © Copyright by Yeesha Poon, 2018
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Relative Effectiveness of Osteoporosis Treatments to Reduce Hip Fractures in Patients with
Prostate Cancer on Continuous Androgen Deprivation Therapy:
Systematic Review, Network Meta-Analysis and Cost-Effectiveness Analysis
Yeesha Poon
Doctor of Philosophy
Department of Pharmaceutical Sciences
University of Toronto
2018
Abstract
Background: Androgen deprivation therapy (ADT) is widely used in men with advanced prostate
cancer, and can lead to loss of bone mineral density (BMD) and fractures.
Osteoporosis treatments are effective in improving BMD, and reducing risk of hip fractures.
Given the potential benefits, risks, and widely varying costs of osteoporosis treatments in our
population, we assessed the effects and cost-effectiveness of treatments.
Methods: A systematic review and a network meta-analysis were conducted using randomized
controlled trials (RCT) that evaluated bisphosphonates, denosumab, toremifene, and raloxifene
in patients with non-metastatic prostate cancer on ADT. Outcomes included percentage change
in BMD from placebo at different bone sites and incidence rates of any fractures.
A cost-utility model was developed using a state transition model simulating the progression of
prostate cancer, the incidence of hip fractures and an adverse event from osteoporosis treatments.
The risk of fracture was conditional on BMD changes, which were modeled as the means of
determining the effect of treatment on health and cost outcomes. The outcomes were predicted
hip fracture incidence, quality-adjusted life years (QALYs), expected costs, and incremental
cost-effectiveness ratios.
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Results: Thirteen RCTs were included for analysis. The largest BMD improvement compared to
placebo at 12-month at femoral neck site was risedronate 6.77% (95% CrI:-6.87-20.27%). Two
studies reported fractures; toremifene and denosumab studies reported improved incidence of
new vertebral fracture outcome vs placebo (2.5% vs 4.9%;p
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Acknowledgments
Completing this thesis took tremendous amount of time, effort and perseverance. I would not
have been able to achieve such accomplishment without acknowledging the following people.
Dr. Murray Krahn was instrumental in guiding me through these years. His support, trust,
encouragement and patience during some turbulence time throughout this process were
characteristics of a true mentor.
I also would like to thank Dr. Shabbir Alibhai, who responded to my relentless questions on
clinical practice and Dr. Petros Pechlivanoglou on network meta-analysis. Knowing their times
were precious, I always felt their willingness to help. I also appreciated the support and advice
received from Dr. David Naimark, Dr. Jeffrey Hoch and Dr. Manny Papadimitropoulos. All of
them have pushed me to go that extra mile and get the most out of the learning process.
Last, but not least, I thank my husband, Paul, and our children, Caitlin, Brandon and Lucas, who
put up with my numerous nights and weekends on completing this thesis. Without their support
and understanding, none of this would have been possible.
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Table of Contents
Acknowledgments ..................................................................................................................... iv
Table of Contents ........................................................................................................................v
List of Tables ............................................................................................................................ ix
List of Figures .............................................................................................................................x
List of Appendices .................................................................................................................... xi
1. Introduction .............................................................................................................................1
1.1 Background – Prostate Cancer.......................................................................................1
1.2 Treatments for Prostate Cancer .....................................................................................2
1.3 Hip Fractures ................................................................................................................3
1.3.1 Gender Differences in Risk of Hip Fractures ..........................................................3
1.3.2 ADT as a Risk Factor for Hip Fractures .................................................................3
1.3.3 BMD and Age as Risk Factors for Hip Fractures ....................................................4
1.3.4 Screening for Fracture Risks ..................................................................................5
1.4 Treatments for ADT-Induced Osteoporosis ...................................................................6
1.5 Rationale for Analyses ..................................................................................................7
2. Literature Review ....................................................................................................................9
2.1 Cost-effectiveness Analysis of Screening for Osteoporosis in Men with Prostate
Cancer .....................................................................................................................................9
2.2 Current Gaps ............................................................................................................... 10
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3. Methods ............................................................................................................................... 12
3.1 Systematic Review - Background .............................................................................. 12
3.2 Steps of the Systematic Review ................................................................................. 12
3.2.1 Research Question .............................................................................................. 12
3.2.2 Data Sources and Searches .................................................................................. 12
3.2.3 Study Selection ................................................................................................... 13
3.2.4 Quality of Study and Risk of Bias Appraisal ....................................................... 16
3.3 Network Meta-Analysis .............................................................................................. 17
3.3.1 Network Meta-Analysis - Background ................................................................. 17
3.3.2 Objective of the NMA .......................................................................................... 18
3.3.3 Analysis ............................................................................................................... 18
3.3.4 Evidence Presentation .......................................................................................... 20
3.4 Cost-Effectiveness Analysis ........................................................................................ 20
3.4.1 Cost-Utility Analysis – Background ..................................................................... 20
3.4.2 Economic Assumptions ........................................................................................ 21
3.4.3 Population ............................................................................................................ 21
3.4.4 Treatment Strategies ............................................................................................ 22
3.4.5 Model Structure ................................................................................................... 22
3.4.6 Model Parameters ................................................................................................ 23
3.4.7 Adverse Effects .................................................................................................... 25
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3.4.8 Mortality .............................................................................................................. 25
3.4.9 Quality of Life ..................................................................................................... 25
3.4.10 Costs .................................................................................................................... 26
3.5 Analysis and Outcomes ............................................................................................... 26
3.5.1 Expected Value of Perfect Information................................................................ 27
4. Results .................................................................................................................................. 30
4.1 Network Meta-Analysis ............................................................................................. 30
4.1.1 Data Synthesis and Analysis ................................................................................ 30
4.1.2 BMD Percentage Change Compared to Placebo .................................................. 31
4.1.3 BMD Percentage Change Between Active Treatments ........................................ 32
4.1.4 Fracture Risk ....................................................................................................... 32
4.2 Cost-Effectiveness Analysis ........................................................................................ 33
4.2.1 Model Validation ................................................................................................. 33
4.2.2 Base Case Analysis .............................................................................................. 34
4.2.3 Uncertainties ........................................................................................................ 36
4.3 Sensitivity Analyses ................................................................................................ 37
4.3.1 Deterministic Sensitivity Analyses ..................................................................... 37
4.4 Expected Value of Perfect Information ...................................................................... 38
5. Discussion and Conclusions .................................................................................................. 40
5.1 Network Meta-Analysis .......................................................................................... 40
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5.1.1 Strengths and Limitations..................................................................................... 42
5.2 Cost-Effectiveness Analysis ..................................................................................... 43
5.2.1 Strengths and Limitations..................................................................................... 45
5.2.2 Implications for Practice ...................................................................................... 46
5.2.3 Implications for Research ..................................................................................... 46
6. Tables.................................................................................................................................... 48
7. Figures .................................................................................................................................. 57
8. References............................................................................................................................. 69
9. Appendices ........................................................................................................................... 81
9.1 Appendix 1: Search Strategies ..................................................................................... 81
9.2 Appendix 2: Characteristics of Included Studies .......................................................... 83
9.3 Appendix 3: BMD Percentage Change from Baseline ................................................. 85
9.4 Appendix 4: Deterministic Sensitivity Analyses ......................................................... 87
9.5 Appendix 5: Maximum Net Benefit and Average Net Benefit per Strategy ................. 88
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List of Tables
Table 1: Cost-effectiveness Analysis - Model Input Parameters
Table 2: Utility Input Parameters
Table 3: Cost Input Parameters
Table 4: Result of Difference in Mean BMD Change between Active Treatments at Total Hip,
Lumbar Spine, and Femoral Neck Sites
Table 5: Probabilistic Analyses Base Case Results
Table 6: Probabilistic Analyses Base Case – Net Monetary Benefits Results
Table 7: Incidences of Hip Fracture
Table 8: Deterministic Sensitivity Analyses Results
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List of Figures
Figure 1: Cost-effective Analysis Model Schematic
Figure 2: PRISMA Flow Diagram
Figure 3: Network Diagram of Treatments – Total Hip, Lumbar Spine and Femoral Neck Sites
Figure 4: Visual Inspection of Convergence for BMD Change Compared to Placebo at the
Femoral Neck Site
Figure 5: Results (BMD Percentage Change compared to Other Treatments) Total Hip
Figure 6: Results (BMD Percentage Change compared to Other Treatments) Lumbar Spine
Figure 7: Results (BMD Percentage Change compared to Other Treatments) Femoral Neck
Figure 8: Cost-Effectiveness Frontier
Figure 9: Cost-Effectiveness Acceptability Curve – PSA
Figure 10: Expected Value of Perfect Information Graph
Figure 11: Cumulative Distribution on Frequency of Incremental Net Health Benefit for
Probabilistic Analysis Results
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List of Appendices
Appendix 1: Search Strategies
Appendix 2: Characteristics of Included Studies
Appendix 3: BMD Percentage Change from Baseline
Appendix 4: Deterministic Sensitivity Analyses
Appendix 5: Maximum Net Benefit and Average Net Benefit per Strategy
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1. Introduction
1.1 Background – Prostate Cancer
Prostate cancer is the most prevalent cancer in men in most developed countries.[1] Despite its
high prevalence, the prognosis for most diagnosed men is good, with 96% of treated patients
surviving for ≥5 years.[1] Prostate cancer is mainly a disease of older men. It is diagnosed most
frequently in men between 60 and 69 years of age.[1]
The etiology of prostate cancer starts in the early stages of cancerous transformation; in which
small clumps of cancer cells remain confined to the otherwise normal prostate gland. This is
known as localized disease. Over time, the cancer cells multiply and spread to the prostate and
beyond the prostate capsule to form a locally advanced tumour.[2] Localized tumours may
become metastasized, become more aggressive, and begin to invade nearby structures and spread
through the pelvic lymph nodes and, via the bloodstream, to distant parts of the body such as
lungs, bladder, liver, and adrenal glands. Metastatic prostate cancer most commonly affects the
bones.[2]
While localized prostate cancer is often asymptomatic, many patients with locally advanced
disease will suffer from urinary outflow obstruction, hematuria, urinary tract infections and
irritation during bladder voiding.[3] In metastatic disease, patients may suffer from bone pain,
weakness of the lower extremities or paralysis if the spinal cord is compressed by bony
metastases.[4] While these symptoms may be rare, they can have a significant impact on quality
of life.
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However, if prostate cancer is detected early, treatment can be effective. The mortality rate for
prostate cancer has decreased by 3.3% per year since 2001. This is likely due to a combination of
earlier detection using prostate-specific antigen (PSA) tests to screen for prostate cancer and
improved treatment options.[1]
1.2 Treatments for Prostate Cancer
Androgen deprivation therapy (ADT) removes (or suppresses) testosterone from the body to
control prostate cancer. The suppression of testosterone by medication is known as medical
castration.[5] ADT is prescribed as primary, adjuvant, or neoadjuvant treatment [6] in men with
advanced prostate cancer or with biochemical recurrence.[7] It may prolong survival by
decreasing tumor size and activity by suppressing androgens.
ADT including long-acting synthetic luteinizing hormone releasing hormone (LHRH) agonists
were introduced in the 1980s and have improved the treatment of prostate cancer by allowing
effective reduction of testosterone levels without the psychological consequences of orchiectomy
or surgical castration.[8]
Due to the negative psychological effect of surgical castration,[9] LHRH agonists have become
the “gold standard” in many countries. In one study, 78% of patients chose medical castration
over orchiectomy.[10] LHRH agonists are the most commonly prescribed treatment for men with
advanced prostate cancer.[7]
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1.3 Hip Fractures
1.3.1 Gender Differences in Risk of Hip Fractures
The prevalence of osteoporosis and the risk of fracture are both higher in women than in men.
This is partially due to differences in bone mineral density (BMD), bone size, and bone strength
between men and women. Even though women fracture more often, men tend to have worse
outcomes after fractures.[11]
Gender differences in the epidemiology of hip fracture were extensively reported. The following
results were found in meta-analyses:[12, 13]
• men had higher excess annual mortality after hip fracture than in women;
• men were at an average of 4 years younger than women at the time of fracture;
• men are sicker than age-matched controls and women with hip fractures;
• men had substantially higher mortality after hip fracture (i.e., the 1-year mortality for
men ranged from 9.4% to 37.1%, compared to 8.2% to 12.4% in women. At 2 years, mortality in
men was reported as high as 42%, compared to 23% for women.)
1.3.2 ADT as a Risk Factor for Hip Fractures
Androgen suppression can mediate increased rates of bone resorption and impair new bone
formation.[14] This can lead to the loss of BMD and subsequent fractures.[15]
A number of studies have shown that ADT is associated with significant bone loss and increased
osteoporotic fracture risk [16-20] and such risk increases over time with continued use. The
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prevalence of osteoporosis was found to be higher at 49% after 4 years of ADT use and 81%
after 10 or more years compared to 35% for hormone-naive men with prostate cancer after 4
years.[21]
Two Canadian population-based studies in men with prostate cancer found that ADT use is
associated with increased fragility fracture risk compared to men without ADT (HR 1.65).[16,
22] Another study also found within 5 years of ADT initiation, 19.4% of subjects had a clinical
fracture compared to 12.6% of controls (p < 0.001). Moreover, statistically higher rates of
fracture were noted at every site examined, including spine, hip, radius, and skull.[18]
A systematic review that assessed long-term side effects of ADT in patients with non-metastatic
prostate cancer showed that its use was associated with substantial decline in BMD in the first
year, and slower decline in subsequent years, with increased fracture rates within 5 years.[23, 24]
1.3.3 BMD and Age as Risk Factors for Hip Fractures
Low BMD has been recognized as a major risk factor for fractures. Although BMD
measurements can be taken at different sites (i.e., total hip, lumbar spine and femoral neck),
BMD measurement at the femoral neck site is a well-accepted predictor of hip fractures.[25-27]
In fact, BMD measurements, as a measure of risk for hip fracture, have been considered to be
comparable with the measurements of blood pressure to determine risk for cardiovascular
disease.[26] The National Osteoporosis Foundation guidelines recommend initiation of drug
therapy based on the T-Score.[28], which is calculated from the BMD value. However,
prediction of hip fracture can be enhanced by employing other independent risk factors, in
particular, age, which is one of the most important risk factors.[26] As patients age, the risk of
hip fractures increases. This association has been shown to be reproducible in several
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populations. Actual hip fracture rates were compared between Canada, US and Germany, all of
which showed a consistent steep increase in incidence of hip fracture with advancing age in both
men and women.[29]
1.3.4 Screening for Fracture Risks
Clinical practice guidelines on BMD testing in patients with prostate cancer on ADT are
lacking.[30] In Canada, the British Columbia Cancer Agency (BCCA) recommends baseline
BMD if ADT is used for >6 months [31] and Alberta Health Services [32] recommends using the
WHO Fracture Risk Assessment Tool (FRAX®) with BMD. The US Endocrine Society [33],
Ontario Prostate Cancer Guidelines [34] and the National Comprehensive Cancer Network [35]
suggest measuring BMD in men 50-69 with risk factors (e.g., ADT). Such testing identifies
persons with osteoporosis who could benefit from specific therapy.
The most established way of measuring BMD is the use of dual energy x-ray absorptiometry
(DXA) to diagnose for osteoporosis and for fracture risk assessment in men.[36]
The BMD value from white women is a standard reference used to calculate T-score, which is
the number of standard deviation (SD) above or below the mean young adult peak bone density
as the reference group.[37]
1. Normal is a T-score +2.5 to –1.0
2. Low bone mass is a T-score of –1.1 to –2.4 inclusively
3. Osteoporosis is a T-score equal to or less than -2.5.
4. Severe osteoporosis is a T- score equal to or less than -2.5 and a fragility fracture.
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The 2010 Canadian Practice Guidelines recommend that all individuals with a T-score of the
spine or hip ≤-2.5 should be considered as having at least moderate 10-year risk of osteoporotic
fractures.[38]
The BCCA’s Genito-urinary Tumour Group recommends if BMD, history or plain films identify
'osteoporosis' (defined here as a T-score
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shown to modestly increase BMD at the hip and lumbar spine sites and was shown to reduce the
incidence of new vertebral fractures, but no statistical difference was found for hip fractures.[17,
43] Denosumab was also found to reduce pathological fractures in men with metastatic prostate
cancer.[44]
Toremifene, a selective estrogen receptor modulator (SERM), has been studied to reduce fracture
risks in men receiving ADT. It was found that the 2-year incidence of new vertebral fractures
had a significant relative risk reduction of 50%. Also, the incidence in all fractures was 10.1%
(47 patients) with placebo and 6.3% with toremifene, which is a significant relative risk
reduction of 38% (95% CI 2.2 to 60.2, p=0.036).[45] Toremifene is not currently available in
Canada.
All the treatments are effective in preventing bone loss and increasing bone mass and can help
reduce the risks of fragility fractures such as hip fractures.[43, 46, 47] However, osteoporosis
medications have known adverse effects which include osteonecrosis of the jaw (ONJ) with
bisphosphonate [48] or denosumab use,[49] and venous thromboembolism with long-term use of
SERMs, such as raloxifene.[50] Therefore, the use of osteoporosis treatments require balancing
benefit and risk. Osteoporosis treatments also vary widely in cost, with newer medications being
substantially more costly than older, off-patent medications.
1.5 Rationale for Analyses
The consequences of fracture are grave. Patients with hip fracture have increased morbidity,
mortality and cost. Hip fractures cause the most morbidity [51] and are associated with a higher
risk of death (HR 4.13) in the first year after a hip fracture compared to those without
fractures.[52] Loss of function and independence may be overwhelming, with 40% of affected
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persons unable to walk independently, and 60% requiring assistance a year later.[51] The
economic burden of fractures in Canadian men was estimated at $570 million in the year 2007 to
2008.[53] Hospitalizations following hip fractures were most costly at approximately $20,163
per hospitalization. Over 70% of all fractures occurred in patients older than 70 years with the
highest number of hospitalizations observed in the 81 to 90-year old age group.[53]
There are published reviews on effectiveness of bisphosphonates [54, 55] in improving BMD in
men on ADT. There is, however, no review that includes newer agents (i.e., denosumab) even
though it has been studied in this setting. Furthermore, there is no head-to-head randomized
controlled trial (RCT) comparing two or more active treatments.
The economic attractiveness of reducing the risk of having a hip fracture using different
treatments with varying effectiveness and risks in men with locally advanced prostate cancer
treated with ADT is unknown.
Therefore, from a clinical and policy perspective, there is a potential benefit in treating prostate
cancer patients initiating on ADT who are at risks for osteoporosis; hence reducing risks of
fractures. Although screening of osteoporosis may be recommended in this population, it would
be of interest to treating physicians and policy makers to determine what treatment would be
most effective and cost-effectiveness in reducing hip fractures in prostate cancer patients on
continuous ADT.
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2. Literature Review
Although studies were found on cost-effectiveness analyses of osteoporosis treatment in
reducing risks of fractures, they were mainly studied in women.[56, 57] At the time of the
systematic review, in men with prostate cancer, there was no systematic review that specifically
evaluated the effectiveness of all available osteoporosis treatments in improving BMD or
fracture risks. Recently, the Cancer Care Ontario working group published a systematic review
and a meta-analysis and found that bisphosphonates were found to be effective in increasing
BMD, but no benefit has been shown in preventing fractures among patients with non-metastatic
prostate cancer. Denosumab was shown to improve BMD and reduce the incidence of new
vertebral fractures in men with non-metastatic prostate cancer.[58]
Lastly, there is no cost-effectiveness analysis that was published between no treatment,
bisphosphonates, denosumab and raloxifene.
2.1 Cost-effectiveness Analysis of Screening for Osteoporosis in Men with
Prostate Cancer
There was one cost-effectiveness analysis that examined the prostate cancer population, but it
was related to screening patients. It evaluated the different screening strategies to prevent
fractures in men who were receiving ADT in the US.[59] A Markov state-transition model
simulated the progression of prostate cancer and the incidence of hip fractures was developed
with a hypothetical cohort of men aged 70 years with locally advanced or high-risk localized
prostate cancer starting a 2-year course of ADT after radiation therapy.
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There were three arms to the model; 1) No BMD test or alendronate therapy, 2) a BMD test
followed by selective alendronate therapy for patients with osteoporosis, or 3) universal
alendronate therapy without a BMD test. It was found that in patients starting adjuvant ADT for
locally advanced or high-risk localized prostate cancer, a BMD test followed by selective
alendronate for those with osteoporosis is a cost-effective use of resources.
The incremental cost-effectiveness ratio (ICER) for the strategy of a BMD test and selective
alendronate therapy for patients with osteoporosis and universal alendronate therapy without a
BMD test were $66,800 per QALY gained and $178,700 per QALY gained, respectively.
Therefore, the authors concluded that, among patients who begin adjuvant ADT for locally
advanced or high-risk localized prostate cancer, BMD testing followed by selective alendronate
for those with osteoporosis is cost-effective; in addition, for patients at higher risk for hip
fractures (i.e., older patients and those with histories of fracture or low BMD before ADT),
routine use of alendronate without BMD testing is justifiable.
2.2 Current Gaps
The costs of managing hip fractures is quite significant to the healthcare system and reducing
risks in patients experiencing a hip fracture is important from a quantity and quality of life
perspective. A cost-effectiveness analysis on the use of bisphosphonates, denosumab or
raloxifene on the reduction of hip fracture in men treated with ADT with potential adverse event
from the osteoporosis treatment would be important from the perspective of the Ministry of
Health or treating physicians.
Furthermore, there is no relative effectiveness review on the different osteoporosis treatments in
this population on BMD improvement or reduction in fracture risks. The objective of the project
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was to first, identify and synthesize evidence on the effectiveness of bisphosphonates,
denosumab and raloxifene in reducing the risks of hip fractures and/or having BMD
improvement in patients who were treated with ADT using LHRH agonists for at least 6 months.
A network meta-analysis (NMA) was then conducted, as there is no randomized controlled trial
that evaluated all active treatments in our population. Lastly, a cost-effectiveness analysis was
performed in the same population to inform the Ministry of Health on potential decisions on
reimbursement of these treatments.
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3. Methods
3.1 Systematic Review - Background
A systematic review was completed with the goal of reducing bias by identifying, appraising,
and synthesizing all relevant studies.[60] It provided a detailed and comprehensive plan and
search strategy a priori to identify and synthesize evidence on the efficacy of the use of
bisphosphonates, denosumab and raloxifene in reducing risks of fragility (i.e., hip) fractures in
patients who were treated with ADT using LHRH agonists continuously for at least 6 months of
use. The data gathered was used to conduct a network meta-analysis (NMA).
3.2 Steps of the Systematic Review
3.2.1 Research Question
The research question that guided the study was: What is the most effective fragility fracture
prevention strategy (i.e., IV zoledronic acid, denosumab, oral bisphosphonates or toremifene) in
patients 65 years of age or older with locally advanced prostate cancer (stage T3/4 M0) who
were on adjuvant ADT for at least six months and are progressing through prostate cancer states
until death?
3.2.2 Data Sources and Searches
We developed comprehensive a priori search strategies in conjunction with an information
specialist. We searched MEDLINE (OVID, 1946-September 2015) and EMBASE (1970-
September 2015) for all RCTs assessing interventions of interest in patients with prostate cancer
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(please refer to Appendix 1 for search strategies). No language restriction was applied. Two
reviewers (YP & MEH) independently screened citations from literature search and extracted
data. Conflicts between reviewers were resolved through consensus.
The Preferred Reporting Items for Systematic reviews and Meta-analyses (PRISMA) guided the
analysis [61].
3.2.3 Study Selection
3.2.3.1 Screening criteria
A study was considered to be not relevant if it met one of the following criteria:
• letter, editorial, review, or lay press article
• Non-human studies
• endpoints which did not include evaluation of fragility fractures, or BMD values
Inclusion criteria comprised of RCTs in patients with prostate cancer 18 years of age who
received ADT continuously for ≥6 months. Patients must be randomized to an active treatment
or placebo and have measured BMD at baseline and at end of study.
We excluded RCTs with endpoints which did not include evaluation of fragility fractures, or
BMD evaluation. We also excluded RCTs of patients with metastatic disease or of non-human
studies. Letters, editorials, reviews or other secondary research studies, cross over studies, and
lay press articles were also excluded.
All RCTs that met the eligibility criteria were included in this analysis.
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Active treatments included bisphosphonates (of any strength or route of administration) such as
alendronate, clodronate, etidronate, pamidronate, risedronate or zoledronic acid (ZA), SERMs
such as raloxifene and toremifene, and denosumab.
Screening of articles was based on the titles, abstracts, and keywords of each study. The
screening criteria was applied as broadly as possible to ensure that only irrelevant studies were
excluded. The full-text reports of all potentially relevant articles and of articles that were
designated as “unclear” were retrieved for review.
Screening of articles was based on the titles, abstracts, and keywords of each study. The
screening criteria was applied as broadly as possible to ensure that only irrelevant studies were
excluded. The full-text reports of all potentially relevant articles and of articles that were
designated as “unclear” were retrieved for review.
3.2.3.2 Data Extraction
The data extraction form was tested on three included studies and modified as required. Data
extraction began when agreement was noted between the reviewers. Then the reviewers
independently extracted all of the data using the standardized data extraction form. Data were
stored and managed in Microsoft Excel tables. Discrepancies were resolved by discussion
amongst the reviewers.
From the included RCTs, data extractions were based on:
Study characteristics: year of conduct, sample size, study duration, intervention and comparator,
respective treatment dose and length of treatment
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Patient characteristics: number of patients, mean age and standard deviation, BMD at baseline,
osteoporosis status (T-score), history and type of baseline fracture (if available)
Outcome results: binary outcomes (e.g., fracture or no fracture), or the number of fractures in
each treatment arm was extracted, if available. For continuous data (e.g., lumbar spine, femoral
neck and total hip BMD value), the percentage or absolute change from baseline in all
intervention groups were extracted. If the BMD change from baseline was not provided, then the
value at end of follow-up and the baseline value were used to calculate the change. Standard
errors (SEs) were used to calculate confidence intervals; the 95% confidence interval is equal to
1.96×SE on either side of the mean.
Possible modifiers included the dosages of each intervention, allowed cotreatment (combination
therapies), the length of follow up (1, 5, and 10 years+), duration of ADT treatment, age of
patients, and previous and types of fractures. Therefore, the year of study, interventions, dose,
concomitant therapy (vitamin D and calcium), sample size, duration of ADT use, baseline BMD,
duration of study and patients’ age were abstracted.
The primary outcome was percentage change in BMD compared to baseline or placebo. When
standard error or standard deviation of BMD was not reported, attempts were made to contact the
authors for missing data, and then established methods were used to impute values [62].
Otherwise, data were estimated from graphs, when possible, using WebPlotDigitizer.[63] The
percentage change in BMD was extracted at 12 months to provide consistency in data analysis.
The secondary outcome was fracture rates.
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3.2.4 Quality of Study and Risk of Bias Appraisal
Bias is a systematic error that can be introduced into randomized controlled trials. Bias can occur
at any phase of the study, including study design, data collection, or process of data analysis.
Bias, therefore, can be reduced by rigorously following proper study design process and
implementation. As some degree of bias is nearly always present in a published study, assessing
bias can help determine how they can influence a study's conclusions.
The validity of individual trials was evaluated using the Risk of Bias instrument, endorsed by the
Cochrane Collaboration.[64, 65] This instrument was used to evaluate the following key
domains: 1) randomization generation; 2) allocation concealment; 3) blinding of participants,
personnel and outcome assessors; 4) incomplete outcome data (withdrawal); 5) selective
outcome reporting; and 6) other sources of bias such as potential for industry bias. The risk of
bias instrument was used to assign summary assessments of within study bias; low risk of bias
(low risk of bias for all key domains), unclear risk of bias (unclear risk of bias for one or more
key domains), or high risk of bias (high risk of bias for one or more key domains).
The quality of RCTs was assessed using the Jadad scale.[66] Three criteria: randomization,
blinding and accounting of all patients, were used for assessment. Randomization was evaluated
based on how randomization was generated (e.g., computer, random number list, coin toss or
well-shuffled envelopes); blinding was determined whether it was done appropriately (e.g.,
masking of tablets), and if all patients were accounted for in the study (e.g., discontinued,
dropped out). A high quality study would have a maximum score of five, with maximum of 2
points each for randomization and blinding, and 1 point for accountability for all patients.
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3.3 Network Meta-Analysis
3.3.1 Network Meta-Analysis - Background
To compare outcomes between two interventions for which there is no direct evidence, a
network meta-analysis (NMA) was utilized. A NMA, also known as a multiple-treatment meta-
analysis or mixed-treatment comparison analysis, compares multiple treatments simultaneously
by combining direct and indirect evidence. It is an extension of meta-analysis and is a valuable
statistical tool for decision makers who need to determine the relative effectiveness across a set
of alternatives, rather than from just two treatments. The challenge of a meta-analysis is the lack
of evidence between two active treatments. NMA overcomes this challenge by applying an
evidence network that involves more than two RCTs and more than two interventions. It
incorporates indirect comparisons when there is no direct comparison between the interventions
of interest. By combining both direct and indirect evidence, the objective is to improve the
precision of estimates.[67]
The three underlying assumptions of NMA are similarity, consistency and homogeneity. In
assessing similarity, it was important to determine whether differences among studies may affect
the comparisons of treatments or make some comparisons inappropriate (i.e., patient populations,
dosages etc.) Similarity assumption means that studies should only be combined if they are
considered to be clinically and methodologically similar. For the consistency assumption, the
results of indirect and direct comparisons should be in general agreement. Finally, even though
trials may differ on study and patient characteristics, they can be homogeneous if these
characteristics are not modifiers of the relative treatment effect of different treatments.
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Any kind of variability among studies in a systematic review may be termed heterogeneity.
There can be three different types of heterogeneity: 1) clinical heterogeneity (variability in the
subjects, interventions and outcomes studied); 2) methodological heterogeneity (variability in
study design, blinding, risk of bias); and 3) statistical heterogeneity (variability in the
intervention effects, and is a consequence of clinical or methodological diversity, or both, among
the studies).
3.3.2 Objective of the NMA
We conducted a Bayesian NMA [68] of RCTs to assess relative efficacy of bisphosphonates,
denosumab, raloxifene or toremifene in improving BMD as a surrogate endpoint of reducing
risk of hip fractures in patients treated with ADT for ≥6 months of continuous use. The main
outcome was assumed to be the percentage change in BMD versus placebo.
3.3.3 Analysis
The outcomes were conducted using a Bayesian random effects (RE) model. A RE model was
chosen because we assumed that each study within the analysis has its own true effect given that
the study characteristics may differ across studies.[69] Relative treatment effects assumed to
follow a normal distribution with mean 0 and variance 105. For between-trial standard deviation,
a uniform prior distribution was used with ranges from 0 to 5. Posterior means and 95% credible
intervals (CrI) for the relative effect of treatments on changes to BMD were estimated. A fixed
effects (FE) binomial model was used for fracture risk using WinBUGS (version 1.4.3).[70]
Models were estimated using Markov Chain Monte Carlo (MCMC) simulations, using three
MCMC chains of 150,000 iterations. Each of the three chains assumed different initial values to
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assess sensitivity of the model parameters on the initial values assumed. Non-informative priors
were used throughout the NMA analysis. The included treatments were ranked by using the
surface under the cumulative ranking curve (SUCRA) to determine the treatment with the
highest probability of being most effective in improving BMD. SUCRA ranges between 0 and 1;
where 1 represents 100% of the time treatment is always ranked first versus 0% that the
treatment is always ranked last.
3.3.3.1 Evaluation of Heterogeneity and Similarity
In order to evaluate clinical and methodological heterogeneity, a tabular summary of studies and
patients’ characteristics for each pairwise comparison was completed. Conceptually,
heterogeneity can be assessed via the degree to which differences or similarities in these
characteristics vary and affect the outcomes (i.e., possible effect modifiers) [71].
3.3.3.2 Evaluation of Consistency
Before embarking on further analysis, the consistency assumption had to be met. This was to
evaluate whether the outcomes between direct and indirect comparisons were in concordance.
The structure diagram that was developed from the analysis helped to determine the number of
loops that existed.
In order to test consistency for single loop, the Bucher method could be used.[67] Inconsistency
was evaluated by comparing results of direct estimate with indirect estimate. For example, if
direct evidence existed between denosumab and zoledronic acid, the direct estimate of
denosumab vs zoledronic acid could be compared to the indirect estimate between denosumab vs
placebo and zoledronic acid vs placebo.
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3.3.3.3 Evaluation of Convergence
Model convergence was assessed visually. When iteration graphs showed a random scatter
around a stable mean value, we inferred that convergence was achieved.
3.3.4 Evidence Presentation
The findings of the NMA were summarized with a network diagram to show the connections
between the different comparators; and the thickness of the lines represented the number of
studies between the comparators. Thicker connecting lines indicated higher numbers of studies
used for comparison. A table summarized the results of the NMA between the different
comparators.
3.4 Cost-Effectiveness Analysis
3.4.1 Cost-Utility Analysis – Background
Under a resource constrained healthcare system, economic evaluations help decision makers
evaluate funding choices. A health economics analysis assesses the expected costs of possible
treatments and resources consumed; i.e., the expected outcomes from each treatment.
A cost-utility analysis (CUA) is recommended by economics guidelines [72] as the primary form
of economic analysis as it estimates the costs and the outcomes of competing treatments
measured as quality-adjusted life-years (QALYs). Unlike cost-effectiveness analysis (CEA),
which documents costs per life saved, CUA captures costs per quality of life. Therefore, a CUA
accounts for both life years gained and the utility or impact of treatments on the quality of those
life years. Utility is a preference measurement, which suggests how much a population would
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prefer to be in one health state (e.g., having locally advanced prostate cancer versus metastatic
prostate cancer). A utility of zero is the preference assigned to death and one applies to perfect
health. Therefore, metastatic prostate cancer health state would likely have a lower utility value
than locally advanced prostate cancer health state.
The final output of a CUA is an incremental cost-utility ratio (ICUR), which evaluates the
incremental costs and incremental utility of a treatment compared to a control or standard of
care. In our analysis, the standard of care is no treatment. There is usually an ICUR value above
which payers will decide not to fund a treatment. This is called the willingness-to-pay (WTP)
threshold. Payers would consider a treatment to be cost-effective when the ICUR is lower than
their pre-defined WTP. Ideally, for payers, the utility of a treatment would be higher and it
would be less costly than the standard of care.
3.4.2 Economic Assumptions
We conducted a cost-utility analysis from a third-party payer perspective. Drug costs and costs
related to prostate cancer and hip fracture were expressed in 2017 Canadian dollars adjusted for
inflation using the Bank of Canada’s Consumer Price Index (CPI). Health outcomes and costs
were discounted at 1.5% per year as per current Canadian guidelines.[73]
3.4.3 Population
We simulated a cohort of men with a mean age of 65, who were diagnosed with locally advanced
prostate cancer (stage T3/4 M0) and who were on continuous ADT. Simulated men entered the
model with no prior fragility fractures. While men were progressing through the prostate cancer
health states, as defined under the Model Structure section, they could also sustain a hip fracture.
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3.4.4 Treatment Strategies
Treatments for ADT-induced bone loss included bisphosphonates, a human monoclonal antibody
(denosumab) and a SERM, e.g., raloxifene. All these treatments are effective in preventing bone
loss and increasing bone mass through different mechanisms of action. They can reduce risk of
hip fractures by improving BMD at the femoral neck site in men on ADT [43] and some have
shown a reduction in fractures in Phase III trials.[45, 47] The specific treatments evaluated in
this analysis were oral bisphosphonates such as alendronate and risedronate, denosumab,
zoledronic acid, raloxifene, and no treatment.
3.4.5 Model Structure
We created a state transition microsimulation model using TreeAge Pro 2017 [Figure 1].[74]
The model consisted of prostate cancer health states, hip fracture states, and adverse events due
to osteoporosis treatments. Patients progressed sequentially through a series of health states
related to prostate cancer:[75] locally advanced disease (T3/4, M0), biochemical failure (three
consecutive PSA increases after the nadir has been reached), metastatic castrate-sensitive cancer
(new metastatic disease that is responsive to hormonal therapy), metastatic castrate resistant
cancer (asymptomatic/minimally symptomatic cancer that has not been treated with
chemotherapy) and death [Figure 1]. Probabilistic analysis was used as a base case.
Deterministic sensitivity analyses were also performed. Variables tested included costs of
treatments, probability of adverse event, starting ages at 55 or 75, BMD percentage change,
utility of having hip fracture, and using BMD percentage change values from total hip site
instead of femoral neck site.
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3.4.6 Model Parameters
Epidemiologic data inputs are described in Table 1.
3.4.6.1 Prostate Cancer Natural History
Prostate cancer progression was based on the natural history of the disease from locally advanced
prostate cancer, to biochemical failure cancer, to metastatic castrate sensitive cancer, to castrate
resistant cancer health states, and ultimately to death.[76-79] The progression rates were
estimated from the following sources: published studies, systematic review and other health
economics studies involving patients who closely resembled our population of patients with
prostate cancer on ADT, and who progressed from one health state to another.[76-79]
3.4.6.2 Incidence of Hip Fracture
Patients could sustain a hip fracture in any of the health states thereby accruing fracture-specific
costs and decrements in quality-of-life.
Patients were simulated with an average starting BMD value at the femoral neck site of 0.794
g/cm2 based on an average starting age of 65 years.[80] Patients could experience a new hip
fracture on a monthly rate based on the 10-year probability of having a hip fracture which were
dependent on the T-score and age.[27]
3.4.6.3 Effectiveness of Osteoporosis Treatments
Both BMD at the femoral neck site and patient age have been shown to be strong predictors of
hip fracture in prospective studies.[26, 81]
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The treatment effects on reduction of BMD were derived from our network meta-analysis
comparing the relative efficacy of osteoporosis treatments on reducing risks of fragility
fractures.[46] BMD loss was modeled to be a function of age and the number of years on
ADT,[82] while osteoporosis treatments mitigated BMD loss. BMD values were updated
monthly based on age, years on ADT and the effect of treatment.[46, 82]
3.4.6.4 T-Score calculation
Monthly BMD value at femoral neck site for each treatment was calculated using a two-stage
approach with posterior samples from the Bayesian simulations [67] of a NMA.[46]
The percentage of BMD change for each treatment was generated from the output of the
Convergence Diagnostics and Output Analysis (CODA) for each iteration from the NMA.[46]
Each CODA represented the percentage of BMD change values for different treatments and they
were incorporated into the model for each simulated patient. The updated monthly BMD value
at the femoral neck site was calculated by accounting for the BMD loss from ADT and the
percentage improvement in BMD from each treatment as derived from the CODA outputs.[67]
Each patient’s T-score was estimated from the difference between the updated monthly BMD
value and the BMD reference (BMDref) divided by the BMD reference standard deviation
(BMDref_SD).[80] The ideal BMD reference was derived from a healthy 30-year old adult
female at the femoral neck site from the National Health and Nutrition Education Survey III
(NHANES III) reference database for white women.[80] The BMD value from white women is
the reference standard for both men and women to calculate the T-score .[37] A T-score of 0
means the BMD is equal to the norm for a healthy, young woman. The more negative the
calculated T-score, the higher the risk of fracture.[83]
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3.4.7 Adverse Effects
Patients could suffer from ONJ while on bisphosphonates or denosumab [84, 85], and venous
thromboembolism with raloxifene [86]. These adverse events were selected because they could
have the most impact on patients’ quality of life and the costs to the healthcare system. The costs
and disutility of an adverse event were assumed to apply for a maximum of one year. Once
patients suffered an adverse event, the osteoporosis treatment was discontinued.
3.4.8 Mortality
Prostate cancer mortality rates were based on the rate of death associated with their respective
prostate cancer states.[75] The mortality rate from hip fractures was based on the hazard ratio
associated with sustaining a hip fracture [87] with the death rate of the normal Canadian male
population serving as the reference.[88]
Death from prostate cancer or hip fracture was possible at any time and in any health state. All
men made monthly transitions between the health states until they died or reached 100 years of
age. The inputs for the model are described below and are found in Table 1.
3.4.9 Quality of Life
Our preference was to use utilities estimated from direct methods such as standard gamble or
time trade off, but due to inconsistencies in measuring utilities, we used utilities values that were
available in the published literature that used standard gamble, EQ5D or values from the Cost-
Effectiveness Analysis Registry [89] for each prostate cancer health state.[90-92] For incident
and subsequent fracture utilities, we extracted information from systematic reviews on utility
values associated with osteoporotic fractures.[93, 94]
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The disutility of experiencing ONJ with bisphosphonates or denosumab and deep vein
thrombosis from raloxifene were derived from studies using time trade off method [95] and
standard gamble [96], respectively. ONJ was defined as stage 3, which meant exposed or
necrotic bone with pain and infection in the jaw and one or more of: pathologic fracture, extra
oral fistula, or osteolysis.[95] The utility inputs for the model are reported in Table 2.
3.4.10 Costs
Drug costs included acquisition costs (i.e., 2018 Canadian Public Drug Programs Formulary [97]
price plus 8% wholesaler mark-up) and the dispensing fee ($6.11). Prostate cancer health state
costs were taken from an Ontario population-based costing study that considered factors such as
physician visits, potential homecare and diagnostic procedures.[6]
The hip fracture costs in the first and subsequent years were derived from Canadian data.[98, 99]
Included costs were hospitalization, homecare and physician services. We assumed that
treatment costs for prostate cancer were independent of hip fracture status. The costs input for
the model is provided in Table 3.
3.5 Analysis and Outcomes
Probabilistic analysis was used as a base case and included uncertainty in treatment effects,
patient characteristics and costs. Five hundred samples of 25,000 hypothetical patients were
performed, in which each input parameter value was drawn from a sampling distribution which
resulted in empirical output distributions of incremental cost and quality-adjusted life
expectancy.
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Deterministic sensitivity analyses were also performed. Variables tested included costs of
treatments, probability of adverse events, starting age at 55 or 75 years, BMD percentage change,
and utility of having a hip fracture. We used BMD percentage change values from total hip site
instead of femoral neck site.
We measured both costs and health outcomes over a lifetime horizon, which provided
cumulative sample estimates of number of hip fractures, costs, life years (LYs) and QALYs. The
model’s main output was the incremental cost-effectiveness ratio or incremental cost-utility ratio.
Incremental net monetary benefit [100] at various willingness-to-pay thresholds was also
calculated to determine the extra net benefit of the different treatments compared to placebo. The
highest incremental net benefit was considered the most cost-effective.
The calculation was based on this formula:
Net benefit (NB) = (QALYs)*Willingness-to-pay - Costs
3.5.1 Expected Value of Perfect Information
Expected Value of Perfect Information (EVPI) was calculated to measure the highest costs of
making the wrong decision based on all parameter uncertainties. EVPI helps decision makers
answer the question on the maximum costs and value associated with funding additional to help
eliminate uncertainty in the decision.[101] The calculation for EPVI per person was dependent
on different willingness-to-pay thresholds, and was calculated as shown in Equation 1:
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Equation 1: EVPI = average of the maximum net benefit for all samples with perfect
information (maximum net benefit) – maximum of the average net monetary benefit for each
treatment strategy with imperfect or present information (expected net benefit).
A simplified example is provided below:
ITERATION Net Benefit (based on willingness-to-pay of $50,000/QALY gained)
Maximum
Net
Benefit
Placebo Zoledronic
Acid Denosumab Risedronate Alendronate Raloxifene
1 $197,790 $180,530 $190,069 $198,573 $198,583 $196,576 $198,583
2 $227,796 $211,546 $220,314 $229,571 $229,694 $227,113 $229,694
…500 $434,818 $416,842 $426,620 $434,835 $435,261 $433,254 $435,261
Expected Net
Benefit $304,389 $286,877 $296,512 $305,057 $305,182 $302,993 $305,215
EVPI = $305,215 - $305,182 = $33 per patient
Population EVPI was determined by using the per patient EVPI, the annual incident of hip
fractures in our population (I), the lifetime horizon of the treatment (t), and the discount rate (r)
(Equation 2).
Equation 2: Population EVPI = EVPI It/(1+r)t t=1,2,3…
It was calculated by multiplying the an incident rate of 110.4 per 100,000 males [1] by the annual
prevalence of men with prostate cancer, which was estimated to be 21,300.[1] A discount rate of
1.5% was used.
The population EVPI was calculated based on three willingness-to-pay thresholds of $50,000,
$100,000 and $125,000 per QALY gained. The results provided information to decision makers
on the maximum value that should be placed on research to gain certainty in the funding
decisions.
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Cumulative distribution plots were created to illustrate the uncertainty in the decision. The
calculations were based on the results of the probabilistic analyses of 500 samples of 25,000
iterations. Each iteration provided an incremental net health benefit based on the difference in
costs, QALY and willingness-to-pay thresholds for treatment options that were on the cost-
effectiveness frontier. By displaying the incremental net health benefit for each iteration, it
showed an overall percentage of times that a wrong decision could have been made. A wrong
decision would be if the incremental net health benefit was negative.
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4. Results
4.1 Network Meta-Analysis
Studies were stratified by BMD test locations: total hip (TH), lumbar spine (LS), femoral neck
(FN) sites. A total of 13 RCTs [102-114] were used for analysis. Eleven studies [102-104, 106,
107, 109-114] evaluated outcomes at the TH site (1618 patients in treatment arm; 1649 patients
in placebo arm). Thirteen studies [102-114] evaluated outcomes at the LS site (1671 patients in
treatment arm; 1699 in placebo arm), of which 11 studies [102-106, 109-114] evaluated
outcomes at the FN site (1527 patients in treatment arm; 1540 patients in placebo arm). The
studies evaluated six (at TH and FN sites) and seven (at LS site) treatments versus placebo.
The PRISMA Flow Diagram is presented in Figure 2. The mutual comparator in the analysis was
placebo to allow us to compare treatments across the trials in the network. The network diagram
is shown in Figure 3.
4.1.1 Data Synthesis and Analysis
The mean age range of patients tested at TH, LS, and FN sites for intervention and placebo
groups ranged from 65 to 76 years. Nine of eleven TH [102-104, 106, 107, 109-111, 113] and
FN studies [102-106, 109-111, 113] and 11 of 13 LS [102-111, 113] studies had patients on ADT
12 months. Two studies that contributed data to all three site analyses had an unknown ADT
duration [112, 114].
At baseline, patients in 5 studies had unknown osteoporosis status [103, 104, 109, 112, 114], 4
studies included patients with normal bone status [102, 106, 110, 113] and 4 included both
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normal and osteopenic patients [105, 107, 108, 110]. All patients were recommended to take
calcium and vitamin D daily, except in one study [103] where intake was unknown. Dosages of
osteoporosis treatments were consistent with their recommended dosages with the exception of
ZA, where four studies used 4mg IV every 3 months [104, 107, 110, 112], one study used 4mg
every 6 months [108] and one used 4mg at 12 months [110]. The characteristics of included
studies are found in Appendix 2.
Although the age, prostate cancer stage and co-treatment with calcium and vitamin D were
similar between the studies, there was some heterogeneity between studies based on duration of
ADT use and different dosing and frequency of zoledronic acid.
Formal testing [115] was not applied to test the consistency assumption since there was no direct
evidence between active treatments to test consistency with indirect evidence. A visual
inspection of iteration plots showed convergence. Figures 4 present visual plots for the BMD
change that compared between treatments and placebo at the femoral neck site.
Based on the Cochrane risk of bias assessment tool, the majority of the trials were at medium
risk of bias, which included those studies that were randomized and double blinded, but did not
discuss or report missing data. Most included studies, except one [106], had a Jadad score of at
least 3.
4.1.2 BMD Percentage Change Compared to Placebo
Overall, patients on active treatment had BMD improvements from baseline (Appendix 3).
Patients on placebo had worsening of their BMD. One exception was an alendronate study,
which reported that patients on placebo had a BMD improvement of 1.18% vs 0.23% (p=0.631)
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for the alendronate arm. Another outlier was a toremifene study, in which BMD declined on
treatment (-0.1% vs -1.44%; p
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33
p=0.004 at 24 months). Other studies reported fractures as adverse events where data were not
systematically gathered. The number of events was small, and statistical significance could not
be determined. One alendronate study [106] reported 1 fragility fracture in each arm vs placebo
and another [109] reported 3 patients had fractures on placebo and 1 patient while on alendronate
(p = 0.44). Israeli [107] reported two traumatic fractures with ZA and 1 with placebo, and
another reported [108] 1 bone fracture in each ZA and placebo arm.
Hence, a NMA was performed with only two studies on vertebral fracture risks, denosumab (679
patients) and toremifene (477 patients) [102, 103] as each treatment was compared to placebo at
24 months. Denosumab was ranked higher than toremifene based on SUCRA of 89.4% of having
lower risk of vertebral fractures.
4.1 Cost-Effectiveness Analysis
4.2.1 Model Validation
The incidence rate of hip fracture in the placebo arm was 360/100,000 person-years or 0.0036
per person year. Patients in the simulation generally experienced their first hip fracture between
age 72 to 77. Therefore, the modeled rate lied within the upper and lower bounds of an age-
specific hip fracture rate of 270 to 400 per 100,000 person-years during this age range in actual
patients with prostate cancer [116] The estimated mean overall undiscounted survival within the
placebo strategy of the model was 12.5 years and was within the observed 12 to 19 year life-
expectancy of a 65 year-old Canadian man with prostate cancer.[117]
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4.2.2 Base Case Analysis
4.2.2.1 Hip Fracture
When 25,000 iterations were simulated, analysis showed that patients in the placebo strategy
sustained the most number of hip fractures, followed by those treated with denosumab and
raloxifene. Patients in the zoledronic acid strategy sustained the least number of hip fractures.
However, the differences in the incidence rates were very small, placebo at 0.0036 per person-
year, denosumab at 0.0030 per person-year, and raloxifene at 0.0029 per person-year. Zoledronic
acid had the lowest incidence rate at 0.0018 per person-year. Both alendronate and risedronate
were very similar at around 0.0021 per person-year.[Tables 1 to 3] The relative risk of hip
fracture for denosumab versus placebo was calculated to be approximately 0.80.
4.2.2.2 Osteonecrosis of the Jaw and Quality Adjusted Life Years
The risks of experiencing osteonecrosis of the jaw (ONJ) were highest with zoledronic acid,
followed by denosumab, and lowest with oral bisphosphonates. Hence, patients experienced
further decrements of quality of life and increased costs with the adverse event. The combined
decrements in patients experiencing ONJ and higher number of hip fractures contributed to its
lower quality adjusted life years (QALY) compared to oral bisphosphonates.
Expected QALY of the different treatments ranged from 8.8820 (placebo) to 8.9237 (zoledronic
acid). For all treatment strategies, the undiscounted life years were similar at approximately 12.5
years.
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4.2.2.3 Costs
Although zoledronic acid was the most effective strategy, it also had the highest lifetime costs
($159,310) due to the highest drug cost per month. The factors which contributed to denosumab
having the second highest lifetime costs were: drug cost and ONJ treatment costs. Placebo had
the lowest lifetime costs ($139,712) due to lack of drug costs and lack of costs associated with
adverse events.
Zoledronic acid was effective in reducing the number of hip fractures, but this effect was not
sufficiently large to offset the differences in drug costs. Therefore, even though patients without
osteoporosis treatment experienced a higher number of hip fractures, the hip fracture savings was
smaller than the higher drug (and adverse event) costs.
4.2.2.4 Incremental Cost-Effectiveness Ratio
All treatment strategies were more effective, but more costly than placebo. Although risedronate
was less costly, it was also slightly less effective than alendronate. Hence, alendronate is the
most cost-effectiveness treatment strategy with an incremental cost-effectiveness ratio (ICER) of
$30,400 per QALY gained compared to placebo. Zoledronic acid was the most effective but also
most costly. The ICER for zoledronic acid was $14.8 million compared to alendronate, which
would not be a cost-effective option for a third-party payer. Other treatment arms, including
risedronate, denosumab and raloxifene strategies were all dominated, which meant they were less
effective and more costly than alendronate.[Table 5]
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4.2.2.5 Net Monetary Benefit & Cost-Effectiveness Frontier
Net monetary benefit was also calculated to summarize the value of each treatment in monetary
terms based on the different willingness-to-pay (WTP) thresholds from $50,000 to $100,000
[Table 6]. Alendronate had the highest net monetary benefit for the WTP thresholds from
$50,000 to $100,000.
The cost-effectiveness frontier showed that risedronate, raloxifene and denosumab were not on
the cost-effectiveness frontier; therefore, they were not cost-effective. Alendronate and
zoledronic acid were on the frontier, and therefore were cost-effective options. However,
zoledronic acid had a much higher ICER compared to alendronate.[Figure 8]
4.2.3 Uncertainties
We represented parameter uncertainty in our model at various cost-effectiveness ratios using a
cost-effectiveness acceptability curve (CEAC). It used a joint distribution of costs and effects to
evaluate uncertainty by identifying where the ICER falls in relations to the cost-effectiveness
plane and the cost-effectiveness threshold.[118] The probabilities represented the proportion of
the iterations or scatter plot points that fall to the south and east region of the cost-effectiveness
plane; meaning the proportion of times that the strategy has the highest net benefit at various
levels of willingness-to-pay.[118]
The CEAC [Figure 9] showed that alendronate had 72% probability of being the most cost-
effective treatment in the model iterations at a $50,000 per QALY gained willingness-to-pay
threshold.[117] Results for other willingness-to-pay thresholds are provided in Figure 2. If the
willingness-to-pay threshold was at $30,000 per QALY gained, placebo has 70% probability to
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37
be the most cost-effective strategy, while alendronate reduced to have 25% probability to be the
most cost-effective treatment. Lastly, the $40,000 per QALY gained threshold was the crossover
between placebo and alendronate strategies. At a willingness-to-pay threshold of $40,000, both
alendronate and placebo has about 50% probability of having the highest net benefit.
4.3 Sensitivity Analyses
4.3.1 Deterministic Sensitivity Analyses
One-way deterministic sensitivity analyses were performed varying costs of bisphosphonates and
denosumab, costs of treating hip fracture in the first year, BMD change affected by denosumab
or risedronate, rate of ONJ with denosumab, and utility of experiencing a hip fracture.[Appendix
4] These parameters were selected based on the potential costs and quality of life impact that
patients may experience during treatment. Given that the costs of generic medications can
decrease to 90% [119], and injectable to 65%,[120] reduced costs were tested. There were two
parameter values which made risedronate the most cost-effective strategy over the lifetime
horizon compared to its basecase value: 1) reduction in costs per month by at least 22.5%, which
equated to approximately less than $9.90 per month (included markup and dispensing fee); and
2) improvement of risedronate BMD change by about 45%.
If the BMD percentage change in denosumab was improved by 45% from baseline value, then its
ICER would be $194,000/QALY gained compared to alendronate. A detailed list of parameters
and summary of the results of the deterministic sensitivity analyses is provided in Table 8.
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38
Starting ages of patients entering the model were also varied at 55 and 75 years. At age 55,
alendronate was found to be the most cost-effective strategy. However, at age 75, risedronate
was the most cost-effective strategy.
BMD percentage change from total hip site was used for re-analysis instead of femoral neck site.
A limitation was that in the network meta-analysis, risedronate was not evaluated because of its
lack of evidence at this bone site. The results showed alendronate was still a cost-effective
treatment strategy compared to placebo, followed by raloxifene with extended dominance.
Denosumab and zoledronic acid were also cost-effective, but with ICERs of $6 million and $14
million, respectively.
4.4 Expected Value of Perfect Information
In a budget constraint healthcare system, a decision that is made based on current information
and the payer’s willingness-to-pay threshold, has a cost associated with making the wrong
decision. Expected value of perfect information (EVPI) provided the costs associated with
making a decision if all uncertainties were removed.
For a willingness-to-pay threshold of $50,000, the costs of gaining perfect information was $33
per patient. If the threshold was lowered to $25,000, then the costs would increase to $272 per
patient.[Figure 10] The graph shows the various willingness-to-pay thresholds and the costs
associated with obtaining perfect information in order to make a decision with certainty.
Population expected value of perfect information were calculated to be between $710,000 and
$925,000 for willingness-to-pay thresholds of $50,000 to $125,000.
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39
The full calculations for maximum and average net benefit for 500 samples with 25,000
iterations are presented in Appendix 5. It provided detailed information of maximum net
monetary benefit for each strategy at a $50,000 willingness-to-pay threshold.
The cumulative distribution plots illustrated the uncertainty around making a wrong decision
based on various willingness-to-pay thresholds. We found that at the $50,000 willingness-to-pay
threshold between placebo and alendronate, there was about 13% of the time that a wrong
decision was made to fund i.e., had a negative incremental net health benefit. At $100,000 or
$125,000 willingness-to-pay thresholds, there was no economic value in reducing uncertainty
since none of the sample iterations had a negative incremental net health benefit.[Figure 11]
Similarly, the results for the incremental net health benefit between alendronate and zoledronic
acid found no economic value in reducing uncertainty because no sample iteration showed a
negative incremental net health benefit.
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5. Discussion and Conclusions
5.1 Network Meta-Analysis
We conducted a NMA evaluating all available preventive treatments for osteoporosis in men
with non-metastatic prostate cancer. Our results showed that all treatments were effective in
reducing the rate of bone loss when compared to placebo. Treated patients’ BMD change from
baseline ranged from -1.2% to 6.0%. Some treatments appeared to be supported by stronger
evidence. Denosumab and zoledronic acid showed improvement in BMD across all sites (~3% at
TH and FN, ~6% at LS sites). The lower bound of the 95% CrI did not include zero at all sites
for these two drugs. Similarly, when we used SUCRA to determine treatment rank probability,
we found that ZA consistently ranked amongst the top two treatments at all sites. Denosumab
was ranked amongst the top two at the LS and TH sites.
In the two studies that evaluated the effect of preventive therapy on fracture risk, denosumab and
toremifene were effective in reducing vertebral fracture risk. In a systematic review that
evaluated bisphosphonates to prevent fragility fractures, it was found that there was no evidence
of a difference in effect on fractures between treatments in this class of drugs [121].
Raloxifene was ranked highest based on SUCRA of 0.8628 compared to other treatments at the
total hip site. Although raloxifene was ranked highest, based on the relative comparison, there is
no evidence of significantly better BMD improvement compared to other treatments. A recent
study[122] evaluated the possible reasons for SUCRA’s uncertainty. The reasons for the
uncertainty in ranking raloxifene to be most effective could be that the data between the
comparisons were scarce from the limited number of patients in each arm (20 patients). Another
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explanation could be that the population size is too small and did not have sufficient power to
show statistical difference.
Factors other than treatment efficacy, such as patient preferences, adverse events and costs are
also important when choosing a treatment. However, we did not systematically evaluate these in
this network meta-analysis.
In terms of patient preferences, ZA was given intravenously every several months (3 to 12
months) which required a visit to a hospital or clinic. This included travel, waiting, set up and
monitoring time, and a 15-minute infusion. Denosumab was given subcutaneously every 6
months. The advantage over ZA is that patients can inject themselves. However, some patients
may prefer not to self-administer, and some may need additional education by a healthcare
professional or through homecare. Other bisphosphonates can be taken orally.
The risk of adverse effects can also influence treatment choice. The relative risk of ONJ with
fewer ZA infusions per year (as in our population for prevention of bone loss) versus 4 mg every
4-weeks (for reducing risk of skeletal-related event in metastatic cancer) is 0.002 [123, 124]. The
incidence of ONJ with all frequencies of ZA is 0-90, with oral bisphosphonates is 1.04-69 [125]
and with denosumab is 0-30.2 [125], per 100,000 patient-years.
Out-of-pocket costs borne by patients for infusion therapy (i.e., travelling costs, parking fees,
time lost from work) and other costs assumed by payer (i.e., nursing time, drug costs, ancillary
equipment) should also be considered. With respect to drug costs, in the US [126], ZA 4mg/5mL
costs $60/infusion ($60 to $240/year), denosumab 60mg costs $1075/injection ($2150/year) and
oral risedronate 35mg costs $25/week ($1300/year) or alendronate 70mg costs $0.40/week
($21/year).
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Our analyses suggested that IV ZA was a reasonable alternative, followed by oral
bisphosphonates. Our results did not show that one drug was unequivocally more effective than
another. All drugs appeared to be effective in reducing the rate of bone loss. In fact, they were
almost universally shown to be associated with improved BMD, and credible intervals showed a
significant degree of overlap between agents. Therefore, we believe that the most important
policy implication of this work is that, because preventive therapy is effective, men who are at
risk for fracture should receive some form of osteoporosis treatment. Choosing the optimal drug
should be determined on the basis of efficacy, as reported here, but also on the basis of safety,
patient preferences, patient and health system costs, and local availability.
5.1.1 Strengths and Limitations
Our study has both strengths and limitations. Network meta-analysis facilitates comparison of
treatments that have not been evaluated in head-to-head trials. We used a well-documented
surrogate endpoint (i.e., BMD change) to estimate fracture risk, which allowed more studies to
be included in the NMA than would have been possible had we used fracture as our main
outcome. The limitations are the lack of direct comparisons, and that some of the indirect
comparisons were either based on single trials only or that they included few patients in the
studies. As a result, the credible intervals between comparisons were often wide. Lastly, we were
bound to draw inference on fracture risk based on BMD as a surrogate endpoint.
A comprehensive economic evaluation provided additional evidence supporting decision making
for men with prostate cancer receiving ADT.
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5.2 Cost-Effectiveness Analysis
We conducted a cost-utility analysis that evaluated the cost-effectiveness of alendronate,
risedronate, raloxifene, zoledronic acid, denosumab and no treatment to reduce the number of hip
fractures while experiencing an adverse event with osteoporosis treatments in patients 65 years
or older with prostate cancer who were on continuous ADT. Simulated patients experienced the
most number of incident hip fractures with placebo, and the least number with zoledronic acid,
followed by alendronate. Alendronate was found to be the most cost-effective strategy compared
to placebo. Zoledronic acid had a $14 million/QALY gained compared to alendronate, which is
far above a conventional payer’s willingness to pay. Even though zoledronic acid may be
marginally more effective, its costs seemed to outweigh its benefit. Both denosumab and
raloxifene were less effective and more costly than oral bisphosphonates; hence, these strategies
were dominated.
The major drivers of the model were costs and BMD improvements of risedronate and
denosumab. We tested several variables in one-way sensitivity analyses [Table 3] and
alendronate was no longer the dominant strategy if the monthly cost of risedronate was either
reduced or BMD change was improved within the plausible range. Similarly, when denosumab’s
cost was reduced by 90% to about $7 per month from $67 per month (including markup and
dispensing fee), its ICER was reduced to $57,600/QALY gained compared to alendronate. Since
the effectiveness of the treatments was dependent on the BMD improvements from a NMA,[46]
we tested the BMD change for denosumab as well. If BMD change was improved by at least
45% relative to its baseline value, denosumab had an ICER of $194,000/QALY gained compared
to alendronate.
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We also calculated the relative risk of denosumab in the simulation compared to the published
study.[47] The RCT found that fracture at any site happened in fewer patients in the denosumab
group (38 [5.2%]) than in the placebo group (53 [7.2%]), with a relative risk of 0.72 (95% CI,
0.48 to 1.07). The number of hip fractures in this simulation between placebo and denosumab led
to a calculated relative risk of 0.80 (95% CI 0.74 to 0.87). The relative risk was similar between
this simulation and the RCT. In the sensitivity analysis, we also varied the improvement of
percentage BMD change with denosumab by up to ±90%, and the result remained the same with
alendronate being the most cost-effective strategy.
Canadian and US Guidelines recommend that men who are receiving ADT should be assessed
for fracture risk, and that to prevent fractures, osteoporosis therapy should be considered.[34, 38,
127] Other factors to guide pharmacologic therapy selection is patient preference for
treatment.[38] Alendronate is the most cost-effective treatment and it is convenient to administer.
It is only taken once weekly orally versus denosumab, which is administered subcutaneously
every six months, or zoledronic acid, which was given intravenously every three months (as per
most studies in men with prostate cancer).[128-130] Other concerns for patients are potentially
the time and out of pocket costs (i.e., parking) to have an intravenous injection in a hospital, or
rarely, the fear of injection. However, for patients with potential compliance issues, bedridden
patients where injections are administered by a nurse or caregiver, or patients who cannot
swallow tablets, injections given every 3 months or longer may be preferred. From a patient’s
perspective, treatment convenience is a potentially important consideration.
The older, off-patent drugs such as oral bisphosphonates were most cost-effective. There is very
little efficacy difference between alendronate and risedronate.[46, 131] At the current prices, the
newer drugs such as denosumab or zoledronic acid were not cost-effective.
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5.2.1 Strengths and Limitations
The strength of this analysis was that we evaluated all potential treatment options for reducing
hip fracture incidences, and the potential serious adverse events that could impact quality of life
and costs.
One limitation of this analysis was excluding the impact of vertebral fractures. The calculations
used throughout this analysis were based on BMD at the femoral neck site; however, the use of
BMD at the lumbar spine site to calculate the reduction of vertebral fracture needs more
substantiation. This made it difficult to accurately account for vertebral fractures, especially with
up to one-half of vertebral fractures being radiographically detected but clinically asymptomatic.
Another analysis found alendronate to be cost-effective for reducing incidence of hip fractures,
and concluded that its analysis may have underestimated the benefits of alendronate given that