Lead Investigator: Robert Hamilton, University of Toronto
Title of Proposal Research: Statin use and prostate cancer outcomes in patients treated in the ARAMIS trial
Vivli Data Request: 8602
Funding Source: None
Potential Conflicts of Interest: None
Summary of the Proposed Research:
Prostate cancer (PCa) remains the most commonly diagnosed disease in Canadian men and is the third leading cause of cancer-related death. In 2016, an estimated 21,600 men were diagnosed with prostate cancer and 4000 men died from the disease.
Men with PCa are usually elderly and tend to have other concomitant diseases like high blood pressure, high cholesterol, prior stroke etc. Hence, in addition to their medications to manage PCa, a vast majority require additional medicines like statins. Statins are a group of drugs that act to reduce levels of fats, including triglycerides and cholesterol, in the blood. Statins may also reduce inflammation in the artery walls, which could prevent blockages that damage organs such as the heart and brain. There is increasing interest in statin medications as inhibitors of PCa development and growth. Studies have shown positive associations between statin use and PCa outcomes, though nearly all the studies have been “retrospective” meaning the data had already been collected (perhaps for another reason) and researchers went back to look at the statin-cancer associations.
Metastatic castrate resistant prostate cancer (mCRPC) is a prostate cancer that has spread to other parts of the body, and which keeps growing even when the amount of male hormones in the body are reduced to very low levels. Reducing the male hormones, called androgens, in the body is essential to stop them from fueling prostate cancer cell growth. This can be achieved by either by surgically removing the testes and/or by using newer medicines called Androgen receptor-axis-targeted therapies (ARATs). Our proposal specifically looks at Darolutamide, an ARAT, and statin use because Darolutamide is a newer medicine offering efficacy in controlling PCa and least toxic compared to other ARATs.
In mCRPC disease, the data regarding statins and outcomes are conflicting. It may be that in earlier disease settings, where survival times are longer, more of a benefit attributable to statin use would be observed. A few mechanisms have been suggested that statins may heighten novel androgen receptor inhibitors like darolutamide, including: hampering of steroid hormone production by the tumor itself, inhibition of production of other elements of the cholesterol pathway, as well as inhibition of androgens (male hormone) being brought into the cancer cells. Androgens serve as food for the prostate cancer cells to grow. Recently our group showed giving men with statins prior to surgical removal of prostate lead to signs that the cancer cells were dying and this was more pronounced in men on statins for longer periods.
Darolutamide is the newest and least toxic ARAT approved for delaying metastasis and overall survival in non-metastatic castration sensitive prostate cancer (nmCRPC). nmCRPC is a diverse disease state where the cancer hasn’t spread, male hormone testosterone is not detected in blood with a confirmed rising prostate-specific androgen (PSA) level. PSA test is used to monitor men after surgery or radiation therapy for prostate cancer to see if their cancer has come back.
To date, no prospective clinical trials in PCa have evaluated statin use in combination with other anti-cancer treatments, although our lab remains very interested in the hypothesis of synergy between statins and other drugs that may influence the cholesterol metabolism pathway and other prostate cancer therapies (including androgen axis inhibitors like darolutamide, the subject of the proposed study).
Statistical Analysis Plan:
All 1,509 patients in the intention-to-treat population from the ARAMIS trial will be eligible for the study. To assess the impact of statins on outcomes, a propensity-matched cohort will be derived from this population, as described below
Outcomes
Primary outcome: Metastases-free survival, as defined in the ARAMIS trial
Secondary outcomes:
1. Time to pain progression, as defined in the ARAMIS trial
2. Progression-free survival, as defined in the ARAMIS trial
3. Time to prostate specific antigen (PSA) progression, as defined in the ARAMIS trial
4. Overall survival
Primary Exposure
Statin use at baseline vs. no statin use at baseline
Other Confounders
1. Age (continuous)
2. Gleason Score
3. Charlson Score/Eastern Cooperative Oncology Group (ECOG) performance status
4. Baseline PSA (continuous)
5. Alkaline Phosphatase (continuous)
6. lactate dehydrogenase (LDH) (continuous)
7. Neutrophils/Lymphocyte Ratio (continuous)
8. Hemoglobin (continuous)
9. Number of months of castration-sensitive disease
10. Number of months between diagnosis and metastases
11. Opiate use (yes vs. no)
12. Geographic region
13. Presence of lymph nodes (yes vs. no)
14. PSA doubling time (continuous)
15. Serum testosterone level (continuous)
16. Use of bone-sparing agent (yes vs. no)
17. Previous hormonal therapy agents
18. Race/ethnic group
Propensity Matching
Using all confounders, calculate a propensity score for statin use using a logistic regression model. For each statin user, match 2 non-statin users using the nearest neighbor matching algorithm with a caliper width of 0.2 times the standard deviation of the propensity scores. To ensure the cohort is well-matched, plot the propensity score distribution between the statin and non-statin users, and review the standardized differences of each characteristic between statin and non-statin users.
Statistical Analysis
To assess the impact of statin use for each outcome, plot two Kaplan-Meier curves for each outcome, the first stratifying results by statin use (i.e. all patients), and the second stratifying results by statin use and treatment arm (darolutamide vs. placebo). Use the log-rank test to compare the survival curves. Report the 1, 2, and 3-year survival probabilities along with their 95% confidence intervals. Report the median survival and its 95% confidence interval where applicable.
Additionally, a multivariate Cox proportional hazards model will be fit for each outcome using the propensity-matched cohort. To account for the matched nature of the data, stratify the model on the matched groups. The following model compositions will be considered:
1. Statin use (reference group = non-users)
2. Statin use + treatment arm (reference group = placebo arm)
3. Statin use + treatment arm + statin x treatment interaction
Depending on the distribution of confounders in the propensity-matched cohort, other
confounders may need to be added to the Cox models.
Subgroup Analyses
To explore the impact of statin use and darolutamide within subgroups, the statistical analyses will be repeated for all subgroups below. Only the primary endpoint, metastases-free survival, will be examined. The subgroups, derived from Fizazi et al. (2019)1, are as follows: Baseline PSA doubling time: >6 months, ≤6 months
1. Osteoclast-targeted therapy at baseline: yes, no
2. PSA level at baseline: >20 ng/ml, >10-20 ng/ml, ≤10 ng/ml
3. Gleason: ≥7, <7
4. Age: <65 years, 65-74 years, 75-84 years, ≥85 years
5. Geographic region: North America, Asia-Pacific, Rest of world
6. Presence of regional pathologic lymph nodes: yes, no
7. ECOG score at baseline: 0, 1
8. Race or ethnic group: White, Asian, Hispanic/Latino, Other
9. Number of previous hormonal therapies: 1, 2+
10. Gleason <7
11. Gleason ≥7
Below is a list of the tables and figures we will generate.
1. Table 1. Baseline characteristics (see confounders list above) of population, stratified by
statin use.
2. Table 2. Baseline characteristics (see confounders list above) of propensity-matched
cohort, stratified by statin use. To ensure that cohort is matched well on baseline
characteristics, include standardized differences.
3. Table 3. Baseline characteristics (see confounders list above) of the propensity-matched
cohort vs. patients who were not matched. To help compare the two cohorts, include
standardized differences.
4. Table 4. Cox proportional hazards model results.
5. Figure 1A. Kaplan-Meier curves for metastases-free survival, stratified by statin use.
6. Figure 1B. Kaplan-Meier curves for metastases-free survival, stratified by statin use and
treatment arm.
7. Figure 2A. Kaplan-Meier curves for time to pain progression, stratified by statin use.
8. Figure 2B. Kaplan-Meier curves for time to pain progression, stratified by statin use and
treatment arm.
9. Figure 3A. Kaplan-Meier curves for progression-free survival, stratified by statin use.
10. Figure 3B. Kaplan-Meier curves for progression-free survival, stratified by statin use and
treatment arm.
11. Figure 4A. Kaplan-Meier curves for time to PSA progression, stratified by statin use.
12. Figure 4B. Kaplan-Meier curves for time to PSA progression, stratified by statin use and
treatment arm.
Additionally, Kaplan-Meier curves for metastases-free survival stratified by
a) statin use, and
b) statin use and treatment arm, for each subgroup analysis described in section 8.
Missing values will be excluded.
Rationale for selecting ARAMIS trial: Potential synergy between statin use and efficacy of ARAT (darolutamide in this case)
Requested Studies:
A Multinational, Randomised, Double-blind, Placebo-controlled, Phase III Efficacy and Safety Study of Darolutamide (ODM-201) in Men With High-risk Non-metastatic Castration-resistant Prostate Cancer
Data Contributor: Bayer
Study ID: NCT02200614
Sponsor ID: 17712
Public Disclosure:
Chavarriaga, J., Lajkosz, K., Sangole, N., Penn, L.Z., Khurram, N. and Hamilton, R.J., 2024, October. Statin use and oncological outcomes in a propensity-matched cohort of nonmetastatic castration resistant prostate cancer patients of the ARAMIS trial. In Urologic Oncology: Seminars and Original Investigations. Elsevier. Doi : 10.1016/j.urolonc.2024.08.023