Statin and metformin use and outcomes in patients with castration-resistant prostate cancer treated with enzalutamide: A meta-analysis of AFFIRM, PREVAIL and PROSPER

Castration-resistant prostate cancer; Metformin; Overall survivalCàncer de pròstata resistent a la castració; Metformina; Supervivència globalCáncer de próstata resistente a la castración; Metformina; Supervivencia globalBackground: Statins and metformin are commonly prescribed for patients, including those with prostate cancer. Preclinical and epidemiologic studies of each agent have suggested anti-cancer properties. Methods: Patient data from three randomised, double-blind, placebo-controlled, phase III studies evaluating enzalutamide (AFFIRM, PREVAIL and PROSPER) in patients with castration-resistant prostate cancer were included in this analysis. This post hoc, retrospective study examined the association of statin and metformin on radiographic progression-free survival (rPFS), metastasis-free survival (MFS), toxicity and overall survival (OS). After adjusting for available clinical prognostic variables, multivariate analyses were performed on pooled data from AFFIRM and PREVAIL, all three trials pooled, and each trial individually, to assess differential efficacy in these end-points associated with the baseline use of these medications. Results: In the multivariate analysis of the individual trials, OS and rPFS/MFS were not significantly influenced by statin or metformin use in AFFIRM or PROSPER. However, in PREVAIL, OS was significantly influenced by statin (hazard ratio [HR] 0.72; 95% confidence interval [CI] 0.59-0.89) and rPFS was significantly influenced by metformin (HR, 0.48; 95% CI 0.34-0.70). In pooled analyses, improved OS was significantly associated with statin use but not metformin use for AFFIRM+PREVAIL trials (HR 0.83; 95% CI 0.72-0.96) and AFFIRM+PREVAIL+PROSPER (HR 0.75; 95% CI 0.66-0.85). Conclusions: The association between statin or metformin use and rPFS, MFS and OS was inconsistent across three trials. Analyses of all three trials pooled and AFFIRM+PREVAIL pooled revealed that statin but not metformin use was significantly associated with a reduced risk of death in enzalutamide-treated patients. Additional prospective, controlled studies are warranted.This study was sponsored by Pfizer Inc. (New York, NY, USA) and Astellas Pharma, Inc. (Northbrook, IL, USA), the co-developers of enzalutamide. Medical writing and editorial support funded by the sponsors were provided by Stephanie Vadasz, PhD, and Dena McWain of Ashfield MedComms (an Ashfield Health company), Lauren Rainer, BSc, and Julie B. Stimmel, PhD, of Onyx (a Prime Global agency)

Effects of metformin and statins on outcomes in men with castration-resistant metastatic prostate cancer: Secondary analysis of COU-AA-301 and COU-AA-302

Abiraterone acetate; Metastatic castration-resistant prostate cancer; MetforminAcetato de abiraterona; Cáncer de próstata metastásico resistente a la castración; MetforminaAcetat d'abiraterona; Càncer de pròstata resistent a la castració metastàtic; MetforminaBackground The associations of metformin and statins with overall survival (OS) and prostate specific antigen response rate (PSA-RR) in trials in metastatic castration-resistant prostate cancer remain unclear. Objective To determine whether metformin or statins ± abiraterone acetate plus prednisone/prednisolone (AAP) influence OS and PSA-RR. Design, setting and participant COU-AA-301 and COU-AA-302 patients were stratified by metformin and statin use. Cox proportional hazards models were used to estimate hazards ratio (HR) stratified by concomitant medications, and a random effects model was used to pool HR. We compared PSA-RR using Chi χ2 test. Results In COU-AA-301-AAP, metformin was associated with improved PSA-RR (41.1% versus 28.6%) but not prolonged OS. In COU-AA-301-placebo-P, there was no association between metformin and prolonged OS or PSA-RR. In COU-AA-302-AAP, metformin was associated with prolonged OS (adjHR 0.69, 95% CI 0.48–0.98) and improved PSA-RR (72.7% versus 60.0%). In COU-AA-302-P, metformin was associated with prolonged OS (adjHR 0.66, 95% CI 0.47–0.93). In pooled analysis, OS was prolonged among those treated with metformin (pooled HR 0.77, 95% CI 0.62–0.95).In COU-AA-301-AAP, statins were associated with an improved OS (adjHR 0.76, 95% CI 0.62–0.93), while there was no difference in COU-AA-301-P. There was no association with statins and OS in either COU-AA-302 groups. When pooling HR, OS was prolonged among those treated with statins (pooled HR 0.78, 95% CI 0.68–0.88). Conclusion Within the limitations of post-hoc sub-analyses, metformin and statins are associated with a prolonged OS and increased PSA-RR, particularly in combination with AAP

Application of a single-objective, hybrid genetic algorithm approach to pharmacokinetic model building.

A limitation in traditional stepwise population pharmacokinetic model building is the difficulty in handling interactions between model components. To address this issue, a method was previously introduced which couples NONMEM parameter estimation and model fitness evaluation to a single-objective, hybrid genetic algorithm for global optimization of the model structure. In this study, the generalizability of this approach for pharmacokinetic model building is evaluated by comparing (1) correct and spurious covariate relationships in a simulated dataset resulting from automated stepwise covariate modeling, Lasso methods, and single-objective hybrid genetic algorithm approaches to covariate identification and (2) information criteria values, model structures, convergence, and model parameter values resulting from manual stepwise versus single-objective, hybrid genetic algorithm approaches to model building for seven compounds. Both manual stepwise and single-objective, hybrid genetic algorithm approaches to model building were applied, blinded to the results of the other approach, for selection of the compartment structure as well as inclusion and model form of inter-individual and inter-occasion variability, residual error, and covariates from a common set of model options. For the simulated dataset, stepwise covariate modeling identified three of four true covariates and two spurious covariates; Lasso identified two of four true and 0 spurious covariates; and the single-objective, hybrid genetic algorithm identified three of four true covariates and one spurious covariate. For the clinical datasets, the Akaike information criterion was a median of 22.3 points lower (range of 470.5 point decrease to 0.1 point decrease) for the best single-objective hybrid genetic-algorithm candidate model versus the final manual stepwise model: the Akaike information criterion was lower by greater than 10 points for four compounds and differed by less than 10 points for three compounds. The root mean squared error and absolute mean prediction error of the best single-objective hybrid genetic algorithm candidates were a median of 0.2 points higher (range of 38.9 point decrease to 27.3 point increase) and 0.02 points lower (range of 0.98 point decrease to 0.74 point increase), respectively, than that of the final stepwise models. In addition, the best single-objective, hybrid genetic algorithm candidate models had successful convergence and covariance steps for each compound, used the same compartment structure as the manual stepwise approach for 6 of 7 (86 %) compounds, and identified 54 % (7 of 13) of covariates included by the manual stepwise approach and 16 covariate relationships not included by manual stepwise models. The model parameter values between the final manual stepwise and best single-objective, hybrid genetic algorithm models differed by a median of 26.7 % (q₁ = 4.9 % and q₃ = 57.1 %). Finally, the single-objective, hybrid genetic algorithm approach was able to identify models capable of estimating absorption rate parameters for four compounds that the manual stepwise approach did not identify. The single-objective, hybrid genetic algorithm represents a general pharmacokinetic model building methodology whose ability to rapidly search the feasible solution space leads to nearly equivalent or superior model fits to pharmacokinetic data

Assessment of Adverse Events From the Patient Perspective in a Phase 3 Metastatic Castration-Resistant Prostate Cancer Clinical Trial

IMPORTANCE Standard adverse event (AE) reporting in oncology clinical trials has historically relied on clinician grading, which prior research has shown can lead to underestimation of rates of symptomatic AEs. Industry sponsors are beginning to implement in trials the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), which was developed to allow patients to self-report symptomatic AEs and improve the quality of symptomatic AE detection. OBJECTIVES To evaluate the feasibility of implementing PRO-CTCAE in a prespecified correlative analysis of the phase 3 COMET-2 trial and enumerate statistically significant between-group differences in symptomatic AEs using PRO-CTCAE and the CTCAE. DESIGN, SETTING, AND PARTICIPANTS This correlative study of 119 men in the randomized, double-blind, placebo-controlled phase 3 COMET-2 trial with metastatic castration-resistant prostate cancer who had undergone at least 2 prior lines of systemic treatment was conducted from March 2012 to July 2014. Participants completed PRO-CTCAE items using an automated telephone system from home prior to treatment and every 3 weeks during treatment. Statistical analysis was performed from May 2018 to June 2019. MAIN OUTCOMES AND MEASURES The proportion of patients who completed expected PRO-CTCAE self-reports was computed as a measure of feasibility. RESULTS Among the 119 men in the study (median age, 65 years [range, 44-80 years]), 534 of 587 (91.0%) expected PRO-CTCAE self-reports were completed, with consistently high rates of completion throughout participation. Rates of self-report adherence were similar between groups (cabozantinib s-maleate, 286 of 317 [90.2%]; and mitoxantrone hydrochloride-prednisone, 248 of 270 [91.9%]). Of 12 measured, patient-reported PRO-CTCAE symptomatic AEs, 4 reached statistical significance when comparing the proportion of patients with at least 1 postbaseline score greater than 0 between groups (differences ranged from 20.1% to 34.1% with higher proportions in the cabozantinib group; all P < .05), and use of a method for accounting for preexisting symptoms at baseline yielded 7 AEs with statistically significant differences between groups (differences ranged from 20.5%to 41.2%with higher proportions in the cabozantinib group; all P < .05). In the same analysis using investigator-reported CTCAE data, no statistically significant differences were found between groups for any symptomatic AEs. CONCLUSIONS AND RELEVANCE PRO-CTCAE data collection was feasible and improved the accuracy of symptomatic AE detection in a phase 3 cancer trial. This analysis adds to mounting evidence of the feasibility and value of patient-reported AEs in oncology, which should be considered for inclusion in cancer trials that incorporate AE evaluation

Targeting ligand-activated ErbB2 signaling inhibits breast and prostate tumor growth

AbstractErbB2 is a ligand-less member of the ErbB receptor family that functions as a coreceptor with EGFR, ErbB3, and ErbB4. Here, we describe an approach to target ErbB2's role as a coreceptor using a monoclonal antibody, 2C4, which sterically hinders ErbB2's recruitment into ErbB ligand complexes. Inhibition of ligand-dependent ErbB2 signaling by 2C4 occurs in both low- and high-ErbB2-expressing systems. Since the ErbB3 receptor contains an inactive tyrosine kinase domain, 2C4 is very effective in blocking heregulin-mediated ErbB3-ErbB2 signaling. We demonstrate that the in vitro and in vivo growth of several breast and prostate tumor models is inhibited by 2C4 treatment

Phase 1/2 multiple ascending dose trial of the prostate-specific membrane antigen-targeted antibody drug conjugate MLN2704 in metastatic castration-resistant prostate cancer

This phase 1/2 study evaluated the dose-limiting toxicity and maximum tolerated dose of MLN2704, a humanized monoclonal antibody MLN591 targeting prostate-specific membrane antigen, linked to the maytansinoid DM1 in patients with progressive metastatic castration-resistant prostate cancer

A novel type of cellular senescence that can be enhanced in mouse models and human tumor xenografts to suppress prostate tumorigenesis

Irreversible cell growth arrest, a process termed cellular senescence, is emerging as an intrinsic tumor suppressive mechanism. Oncogene-induced senescence is thought to be invariably preceded by hyperproliferation, aberrant replication, and activation of a DNA damage checkpoint response (DDR), rendering therapeutic enhancement of this process unsuitable for cancer treatment. We previously demonstrated in a mouse model of prostate cancer that inactivation of the tumor suppressor phosphatase and tensin homolog deleted on chromosome 10 (Pten) elicits a senescence response that opposes tumorigenesis. Here, we show that Pten-loss-induced cellular senescence (PICS) represents a senescence response that is distinct from oncogene-induced senescence and can be targeted for cancer therapy. Using mouse embryonic fibroblasts, we determined that PICS occurs rapidly after Pten inactivation, in the absence of cellular proliferation and DDR. Further, we found that PICS is associated with enhanced p53 translation. Consistent with these data, we showed that in mice p53-stabilizing drugs potentiated PICS and its tumor suppressive potential. Importantly, we demonstrated that pharmacological inhibition of PTEN drives senescence and inhibits tumorigenesis in vivo in a human xenograft model of prostate cancer. Taken together, our data identify a type of cellular senescence that can be triggered in nonproliferating cells in the absence of DNA damage, which we believe will be useful for developing a 'pro-senescence' approach for cancer prevention and therapy

Symptom Monitoring With Patient-Reported Outcomes During Routine Cancer Treatment: A Randomized Controlled Trial

There is growing interest to enhance symptom monitoring during routine cancer care using patient-reported outcomes, but evidence of impact on clinical outcomes is limited

Feasibility of Long-Term Patient Self-Reporting of Toxicities From Home via the Internet During Routine Chemotherapy

Patient-reported outcomes are increasingly used in routine outpatient cancer care to guide clinical decisions and enhance communication. Prior evidence suggests good patient compliance with reporting at scheduled clinic visits, but there is limited evidence about compliance with long-term longitudinal reporting between visits