8 oktober 2021: Bron: Journal of Urology 1 oktober 2021

Het is al eerder in studies aangetoond dat intermitterende hormoontherapie (androgeendeprivatietherapie) (IADT) bij prostaatkanker dezelfde resultaten geeft op ziekteprogressietijd en overall overleving in vergelijking met doorlopend hormoontherapie (ADT). Uit Canadees onderzoek onder 8544 mannen ouder dan 65 jaar met prostaatkanker blijkt dat het gebruik van deze strategie in de praktijk niet goed bekend is en niet heel vaak wordt toegepast (16 tot 25 procent). Althans in Canada. Of dat ook geldt voor Nederland en België durf ik niet te zeggen. Ik ken wel mannen waarbij intermitterende hormoontherapie wordt toegepast, maar ik vermoed dat ze er zelf om moeten vragen. Dit staat er in de richtlijnen

Een interessante studie naar de effecten van inmitterende hormoontherapie is deze studie waarbij de onderzoekers onderzochten wat het effect is van hormoontherapie op de kankerstamcellen. Elke individuele patiënt uit een studie met totaal 70 patiënten werden jarenlang gevolgd wat voor invloed de intermitterende hormoontherapie had op hun PSA en de tijd tot zich weer progressie van de ziekte voordeed door PSA stijging. Deze studie is niet voor leken maar artsen en wetenschappers begrijpen denk ik wel wat er met deze studie is onderzocht en aangetoond (abstract staat onderaan artikel):

Prostate-specific antigen dynamics predict individual responses to intermittent androgen deprivation

a–d Treatment times for a Bruchovsky trial data and simulations of b extrapolated IADT with induction, c IADT without induction, and d continuous ADT. Red and black denote when treatment is on and off, respectively. e Kaplan–Meier estimates of progression comparing IADT with induction (black curve) against IADT without induction (blue) and continuous ADT (gray) (double S indicates predictive model simulation). With and without induction period, IADT TTP increases when compared with continuous therapy TTP. Red symbols denote patients who experienced an adverse event/death prior to the conclusion of the trial. Statistical significance was determined using logrank test (IADT w/o induction vs. continuous: p = 0.073, IADT w/induction vs. continuous: p = 0.129, IADT w/induction vs. w/o induction: p = 0.795). f TTP comparison between IADT with induction (black), continuous therapy (gray), and IADT without induction (blue). Open circles denote end of simulation (EOS). Red dots denote patients who experienced an adverse event/death prior to the conclusion of the trial. Solid lines denote mean TTP (67.11, 57.25, and 71.87 months for IADT with induction, continuous therapy, and IADT without induction, respectively). The average TTP is longer with IADT without induction, compared with IADT with induction and continuous ADT. g Simulation results for Patient 054 (IADT with induction (black curve), without induction (blue curve), and continuous ADT (gray)). With IADT with induction, the patient became resistant after 49 months. Simulating continuous ADT would result in progression after 24 months. Simulating IADT without the induction would increase TTP by 5 months. PCaSC dynamics show that treatment selects for PCaSC population, accelerating resistance development. Dashed curve represent time when ADT is off.

De auteurs van de retrospectieve studie evalueerden 8544 mannen ouder dan 65 jaar met prostaatkanker en die hormoontherapie (ADT) ondergingen. De gemiddelde follow-up was 8,3 jaar. IADT werd gebruikt bij 16,4% van de bevolking. Mannen met een grotere kans om IADT te ondergaan, waren onder meer degenen met eerdere lokale therapie en degenen in het hoogste inkomenskwintiel. Op het niveau van de zorgverlener gebruikten radiotherapeut-oncologen vaker IADT, net als zorgverleners met meer dan 10 jaar ervaring.

Het studierapport van deze studie is tegen betaling in te zien. Klik op de titel van het abstract.

Real-World Practice Patterns and Predictors of Continuous versus Intermittent Androgen Deprivation Therapy Use for Prostate Cancer in Older Men

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https://doi.org/10.1097/JU.0000000000001876

Abstract

Purpose:

Phase-III randomized control trial evidence suggests intermittent androgen deprivation therapy (IADT) is not significantly inferior to continuous androgen deprivation therapy (ADT) for patients with prostate cancer (PC). However, clinical practice and guidelines differ in their recommendations. We evaluate real-world utilization and practice patterns of IADT.

Materials and Methods:

Ontario men ≥65 years of age with PC who initiated ADT for ≥3 months were identified (1997–2017). Lapses in ADT ≥6 months (initial gap) and ≥3 months (subsequent gaps) were used to classify IADT. Neoadjuvant/adjuvant therapy was excluded. Disease stage adjustment was completed for patients with likely metastatic disease based on de novo presentation with ADT. Patient and physician predictors of IADT were analyzed using multivariable logistic regression.

Results:

We identified 8,544 patients with 1,715 having previously received local therapy. Among all patients, 16.4% received IADT. This ranged from 11.4%–24.8% across health-planning regions and increased to 26.6% in those with previous local therapy. Mean followup was 8.3 years. Patients with prior local therapy (OR 1.85, 95% CI 1.59–2.17, p <0.001) and those in the highest income quintile (OR 1.32, 95% CI 1.08–1.60, p=0.005) had increased odds of receiving IADT. Radiation oncologists were more likely to use IADT than urologists (OR 1.99, 95% CI 1.59–2.50, p <0.001), as were physicians with more experience (≥10 years in practice: OR 1.44, 95% CI 1.11–1.88, p=0.007). In specialty-stratified analyses, case volume was significantly associated with IADT for radiation oncologists (highest quartile: OR 1.73, 95% CI 1.14–2.62, p=0.009).

Conclusions:

IADT remains underutilized for patients with PC who ≥65 years of age with only 1 in 4 to 1 in 6 eligible patients receiving this form of care. Clinical, sociodemographic and physician characteristics play an important role in treatment selection.

Funding: This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). This study also received funding from the Princess Margaret Cancer Foundation and the Urologic Oncology Research and Innovation Fund provided by Astellas Pharma Canada, Inc. and jointly established by Astellas Pharma Canada, Inc. and The University of Toronto. Parts of this material are based on data and information compiled and provided by MOHLTC, Cancer Care Ontario, and the Canadian Institute for Health Information. The analyses, conclusions, opinions and statements expressed herein are solely those of the authors and do not reflect those of the funding or data sources; no endorsement is intended or should be inferred.

Prostate-specific antigen dynamics predict individual responses to intermittent androgen deprivation

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Published: 09 April 2020

Prostate-specific antigen dynamics predict individual responses to intermittent androgen deprivation

Nature Communications volume 11, Article number: 1750 (2020) Cite this article

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Abstract

Intermittent androgen deprivation therapy (IADT) is an attractive treatment for biochemically recurrent prostate cancer (PCa), whereby cycling treatment on and off can reduce cumulative dose and limit toxicities. We simulate prostate-specific antigen (PSA) dynamics, with enrichment of PCa stem-like cell (PCaSC) during treatment as a plausible mechanism of resistance evolution. Simulated PCaSC proliferation patterns correlate with longitudinal serum PSA measurements in 70 PCa patients. Learning dynamics from each treatment cycle in a leave-one-out study, model simulations predict patient-specific evolution of resistance with an overall accuracy of 89% (sensitivity = 73%, specificity = 91%). Previous studies have shown a benefit of concurrent therapies with ADT in both low- and high-volume metastatic hormone-sensitive PCa. Model simulations based on response dynamics from the first IADT cycle identify patients who would benefit from concurrent docetaxel, demonstrating the feasibility and potential value of adaptive clinical trials guided by patient-specific mathematical models of intratumoral evolutionary dynamics.

Introduction

Prostate cancer (PCa) is the most common type of cancer in American men and the second leading cause of cancer mortality1. Following surgery or radiation, the standard treatment for hormone-sensitive PCa is continuous androgen deprivation therapy (ADT) at the maximum tolerable dose (MTD) with or without continuous abiraterone acetate (AA) until the tumor becomes castration resistant2. Importantly, advanced PCa is not curable because PCa routinely evolves resistance to all current treatment modalities. Continuous treatment approaches fail to consider the evolutionary dynamics of treatment response where competition, adaptation, and selection between treatment sensitive and resistant cells contribute to therapy failure3. In fact, continuous treatment, by maximally selecting for resistant phenotypes and eliminating other competing populations, may actually accelerate the emergence of resistant populations—a well-studied evolutionary phenomenon termed competitive release4.

In part to address this issue, prior trials have used intermittent ADT (IADT) to reduce toxicity and potentially delay time to progression (TTP). However, these trials were typically not designed with a detailed understanding of the underlying evolutionary dynamics. For example, a prospective Phase II trial of IADT for advanced PCa included an 9-month induction period in which patients were treated at MTD prior to beginning intermittent therapy5. We have previously postulated that only a small number of ADT-sensitive cells would typically remain after the induction period, thereby significantly reducing the potential of intermittent treatment to take advantage of the evolutionary dynamics3.

Fully harnessing the potential of intermittent PCa therapy requires identifying ADT resistance mechanisms, predicting individual responses, and determining potentially highly patient-specific, clinically actionable triggers for pausing and resuming IADT cycles. Progress in integrated mathematical oncology may make such analysis possible. Many mathematical models based on a variety of plausible resistance mechanisms have been proposed to simulate IADT responses3,6,7,8,9,10,11,12,13,14. Although these models can fit clinical data, they often rely on numerous model variables and parameters that in combination fail to adequately predict responses and outcomes for individual patients10. We hypothesize that PCa cells with stem-like properties (PCaSCs) may be, at least in part, responsible for tumor heterogeneity and treatment failure owing to their self-renewing, differentiating and quiescent nature15,16,17. Here, we define PCaSCs to be a population of cells that are less sensitive to low testosterone environments but still somewhat dependent on androgen receptor pathways. Simulating longitudinal prostate-specific antigen (PSA) levels in early IADT treatment cycles could help identify patient-specific PCaSC dynamics to computationally forecast individual disease dynamics and reliably predict IADT response or resistance in subsequent treatment cycles.

The first evidence of stem cells in the prostate was provided by Isaacs and Coffey18, who used androgen cycling experiments in rodents to show that castration resulted in involution of the prostate, whereas restored androgen levels resulted in complete regeneration of the prostate. These findings demonstrated that the normal prostate depends on androgens for maintenance. A small population of androgen-independent stem cells within the prostate epithelium divide to give rise to amplifying cells, which do not directly depend on androgen for their continuous maintenance, but respond to androgens by generating androgen-dependent transit cells. Approximately 0.1% of cells in prostate tumors express the stem cell markers CD44+/α2β1hi/CD133+19. A pre-clinical study by Bruchovsky et al. showed ADT selects for murine PCaSCs20. Analogously, Lee et al.21 demonstrated increased PCaSCs populations after ADT in patient-derived PCa cell lines, which can be reverted by the addition of functional AR. Combined, these results suggest evolution of or selection for pre-existing androgen-independent PCaSCs as a plausible explanation of the development of ADT resistance.

The purpose of this study is to evaluate individual PSA dynamics in early IADT treatment cycles as a predictive marker of response or resistance in subsequent treatment cycles. We hypothesize that patient-specific PCaSC division patterns underlie the measurable longitudinal PSA dynamics, and that a mathematical model of PCaSCs can be trained to predict treatment responses on a per-patient basis. Here, we present an innovative framework to simulate and predict the dynamics of PCaSCs, androgen-dependent non-stem PCa cells (PCaCs), and blood PSA concentrations during IADT. Our mathematical model of PCaSC enrichment is calibrated and validated with longitudinal PSA measurements in individual patients to identify model dynamics that correlate with treatment resistance. The model’s predictive power to accurately forecast individual patients’ responses to IADT cycles is evaluated in an independent patient cohort. These analyses suggest that PCaSC and PSA dynamics may potentially be used to personalize IADT, maximize TTP, and ultimately improve PCa outcomes. The calibrated and validated model is then used to generate testable hypotheses about patients that may benefit from concurrent chemotherapy.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The clinical data used to conduct this study are available in a public repository at http://www.nicholasbruchovsky.com/clinicalResearch.html. A reporting summary for this article is available as a Supplementary Information file.

Code availability

Code supporting the findings of this study are available at https://github.com/reneebrady/IADT_PCaSC.

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Acknowledgements

We thank participants of the clinical trial and Dr. Bruchovsky for sharing the data. We also thank our patient advocate Mr. Robert Butler for fruitful discussions. This work was supported by NIH/NCI 1R21CA234787-01A1 “Predicting patient-specific responses to personalize ADT for prostate cancer”, and in part by NIH/NCI U54CA143970-05 (Physical Science Oncology Network) “Cancer as a complex adaptive system”, the Ocala Royal Dames for Cancer Research, Inc., and The JAYNE KOSKINAS TED GIOVANIS FOUNDATION FOR HEALTH AND POLICY, a Maryland private foundation dedicated to effecting change in health care for the public good. The opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and not necessarily those of the JAYNE KOSKINAS TED GIOVANIS FOUNDATION FOR HEALTH AND POLICY, its directors, officers, or staff.

Author information

Affiliations

Department of Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA

Renee Brady-Nicholls & Heiko Enderling
Department of Life Sciences, Scottsdale Community College, 9000 E. Chaparral Rd., Scottsdale, AZ, 85256, USA

John D. Nagy
School of Mathematical and Statistical Sciences, Arizona State University, 900 S Palm Walk, Tempe, AZ, 85281, USA

John D. Nagy
Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, 12902 USF Magnolia Drive, Tampa, FL, 33612, USA

Travis A. Gerke
Division of Medical Oncology, Department of Medicine, Duke Cancer Institute, 20 Duke Medicine Cir, Durham, NC, 27710, USA

Tian Zhang
Department of Radiation Oncology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA

Andrew Z. Wang
Department of Genitourinary Oncology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA

Jingsong Zhang
Department of Radiology, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA

Robert A. Gatenby

Contributions

R.B., A.Z.W., T.Z., J.D.N., and H.E. conceptualized the study. R.B, J.D.N, T.A.G., and H.E. performed the modeling and statistical analyses. R.B., J.D.N., T.A.G., T.Z., A.Z.W., J.Z., R.A.G., and H.E. wrote the manuscript.

Corresponding authors

Correspondence to Robert A. Gatenby or Heiko Enderling.

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Competing interests

Provisional patent application entitled “Methods for PCa intermittent adaptive therapy”. Applicants/inventors: Renee Brady-Nicholls, Heiko Enderling; application number: 62/944.804; status: provisionally filed. The patent covers methods related to using the mathematical model to adjust an individual patient’s treatment administration (both timing and alternative treatment options), thereby increasing TTP. T.Z.: Research funding: Acerta, Novartis, Merrimack, Abbvie/StemCentrx, Merck, Regeneron, Mirati Therapeutics, Janssen, Astra Zeneca, Pfizer, OmniSeq, Personal Genome Diagnostics, Seattle Genetics; Speakers Bureau: Genentech/Roche, Exelixis, Sanofi-Aventis, Genomic Health; Advisory Board: Genentech/Roche, Merck, Exelixis, Sanofi-Aaventis, Janssen, Astra Zeneca, Pfizer, Amgen, BMS, Pharmacyclics, Seattle Genetics, Bayer; Consultant: Bayer, Astra Zeneca, Foundation Medicine; Employee: Capio Biosciences, Archimmune Therapeutics (spouse); Stockholder: Capio Biosciences, Archimmune Therapeutics (spouse); A.Z.W.: Cofounder, stockholder and consultant: Capio Biosciences, Archimmune Therapeutics; J.Z.: Consultant: Dendreon, Advisory Board: AstraZeneca, Bayer, Clovis Oncology, Seattle Genetics, Speaker Bureau: Merck, Sanofi. All other authors declare no competing interests.

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