This phase III trial studies whether adding apalutamide to the usual treatment improves outcome in patients with lymph node positive prostate cancer after surgery. Radiation therapy uses high energy x-ray to kill tumor cells and shrink tumors. Androgens, or male sex hormones, can cause the growth of prostate cancer cells. Drugs, such as apalutamide, may help stop or reduce the growth of prostate cancer cell growth by blocking the attachment of androgen to its receptors on cancer cells, a mechanism similar to stopping the entrance of a key into its lock. Adding apalutamide to the usual hormone therapy and radiation therapy after surgery may stabilize prostate cancer and prevent it from spreading and extend time without disease spreading compared to the usual approach.
PRIMARY OBJECTIVE: I. Compare metastasis-free survival (MFS) of salvage radiation therapy (RT) and gonadotropin releasing hormone (GnRH) agonist/antagonist versus (vs.) RT/GnRH agonist/antagonist with apalutamide for patients with pathologic node-positive prostate cancer after radical prostatectomy with detectable prostate-specific antigen (PSA). SECONDARY OBJECTIVES: I. Compare health-related quality of life (Expanded Prostate Cancer Index Composite \[EPIC\]-26, EuroQol \[EQ\]-5 Dimension \[D\]-5 Level \[L\], Brief Pain Inventory, Patient Reported Outcome Measurement Information System \[PROMIS\]-Fatigue) among the treatment arms. II. Compare overall survival, biochemical progression-free survival, time to local-regional progression, time to castrate resistance, and cancer-specific survival among the treatment arms. III. Compare the short-term and long-term treatment-related adverse events among the treatment arms. EXPLORATORY OBJECTIVES: I. Validate Decipher score for an exclusively node-positive population and use additional genomic information from Affymetrix Human Exon 1.0st array to develop and validate novel prognostic and predictive biomarkers. II. Validate the PAM50-based classification of prostate cancer into luminal A, luminal B, and basal subtypes as prognostic markers and determine whether the luminal B subtype is a predictive marker for having a larger improvement in outcome from the addition of apalutamide. III. To optimize quality assurance methodologies and processes for radiotherapy and imaging with machine learning strategies. OUTLINE: Patients are randomized to 1 of 2 arms. ARM I: Patients receive standard of care hormone therapy per physician discretion for 24 months. Patients also undergo standard of care pelvis and prostate bed radiation therapy 5 days per week over 5-6 or 7-8 weeks beginning within 90 days of randomization in the absence of disease progression or unacceptable toxicity. ARM II: Patients undergo standard of care hormone therapy and radiation therapy as in Arm I. Patients also receive apalutamide orally (PO) once daily (QD) on days 1-90 of each cycle. Cycles repeat every 90 days for 8 cycles in the absence of disease progression or unacceptable toxicity. Patients in both arms may undergo computed tomography (CT), magnetic resonance imaging (MRI), bone scan, and positron emission tomography (PET) as clinically indicated throughout the study. Patients may also undergo blood sample collection throughout the study. After completion of study treatment, patients are followed up every 6 months for 3 years, then annually thereafter.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
586
Given PO
Undergo blood sample collection
Undergo bone scan
Undergo CT
Receive hormone therapy
Undergo MRI
Undergo PET
Ancillary studies
Ancillary studies
Undergo pelvis and prostate bed radiation therapy
Cancer Center at Saint Joseph's
Phoenix, Arizona, United States
RECRUITINGUniversity of Arkansas for Medical Sciences
Little Rock, Arkansas, United States
RECRUITINGKaiser Permanente-Anaheim
Anaheim, California, United States
RECRUITINGKaiser Permanente-Baldwin Park
Baldwin Park, California, United States
Metastasis-free survival (MFS)
Kaplan-Meier curves will be generated and metastasis-free survival compared between the two treatment groups by a logrank test, stratified by prostate specific antigen (PSA) level after prostatectomy (never detectable or rising). Cox regression modeling to assess and adjust for the effects of PSA stratum and other baseline covariates will also be performed. The proportional hazards assumption will be tested using Schoenfeld residuals and graphical methods. Martingale residual plots will be examined to determine the best functional form for incorporating covariates into the model. A competing risks analysis will also be performed with time to distant metastasis or death from prostate cancer as the event of interest and death from other causes as the competing risk. Cumulative incidence curves will be generated along with Fine-Gray's test. Patients alive and metastasis free will be censored as of the time of the last negative examination.
Time frame: From randomization to detection of metastatic disease or death from any cause, assessed up to 7.5 years
Quality of life (QOL) between the two treatment arms
Quality of life scores will be derived by constructing summary measures across domains from the various quality of life instruments (Expanded Prostate Cancer Index Composite-26, EuroQol (EQ)-5 Dimension (D)-5 Level (L), Brief Pain Inventory, and Patient Reported Outcome Measurement Information System-Fatigue). Calculated health utilities will be derived from the EQ-5D-5L instrument and used to produce a quality-adjusted life year survival estimate post-treatment. The area under the curve provides an estimate of the quality-adjusted, restricted mean survival time and will be compared between the two treatment arms as described in Glasziou et al (1990). QOL scores will be analyzed using mixed effects regression for longitudinal data to compare the profiles over time between the two treatment groups (Gibbons and Hedeker, 2000). The models will include treatment, time, and treatment-by-time interaction terms as fixed effects and subjects as a random effect.
Time frame: Up to 3 years post treatment
Overall survival (OS)
Will be summarized by Kaplan-Meier curves and compared between treatment groups via logrank tests and Cox regression modeling.
Time frame: From randomization until date of death or censored at last date known alive, assessed up to 7.5 years
Biochemical progression-free survival (bPFS)
Will be summarized by Kaplan-Meier curves and compared between treatment groups via logrank tests and Cox regression modeling. In addition, competing risks analyses will be performed and cumulative incidence curves generated for bPFS with death from other (i.e., non-prostate cancer) causes treated as a competing event. Patients who die from non-prostate cancer related causes will be censored as of the date of death.
Time frame: From randomization until biochemical recurrence or death from prostate cancer, assessed up to 7.5 years
Time to local-regional progression
Competing risks analyses will be performed and cumulative incidence curves generated for local-regional progression with death from other (i.e., non-prostate cancer) causes treated as a competing event.
Time frame: Up to 7.5 years
Time to castrate resistance
Will be summarized by Kaplan-Meier curves and compared between treatment groups via logrank tests and Cox regression modeling. Patients who die prior to resistance will be censored.
Time frame: Up to 7.5 years
Cancer-specific survival
Will be summarized by Kaplan-Meier curves and compared between treatment groups via logrank tests and Cox regression modeling. In addition, competing risks analyses will be performed and cumulative incidence curves generated for cancer-specific survival with death from other (i.e., non-prostate cancer) causes treated as a competing event. Patients who die from non-prostate cancer related causes will be censored as of the date of death.
Time frame: Up to 7.5 years
Incidence of adverse events
Will be assessed by Common Terminology Criteria for Adverse Events version 5.0. Adverse events will be tabulated by type, level of severity, and attribution for each treatment arm and the rate of events compared between treatment groups using chi-square or Fisher's exact tests.
Time frame: Up to 7.5 years
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Kaiser Permanente-Bellflower
Bellflower, California, United States
RECRUITINGMercy Cancer Center - Carmichael
Carmichael, California, United States
RECRUITINGMercy San Juan Medical Center
Carmichael, California, United States
RECRUITINGMercy Cancer Center - Elk Grove
Elk Grove, California, United States
RECRUITINGKaiser Permanente-Fontana
Fontana, California, United States
RECRUITINGMarin General Hospital
Greenbrae, California, United States
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