Intermittent Androgen Suppression Therapy Research Articles

Selection of prostate cancer therapy strategy under early androgen suppression treatment

Intermittent androgen suppression therapy is increasingly employed as an alternative method of advanced prostate cancer. However, it remains controversial whether intermittent therapy is superior to continuous therapy in controlling cancer progression. In this paper, we study the mathematical model for early treatment of prostate cancer that incorporates the individual differences and the pharmacodynamics of drugs. The mathematical criteria for selection of better treatment are established on the basis of stability of periodic solution induced by treatment. Numerical results further explore the optimal design of intermittent treatment. The results provide valuable insights for clinical practice.

An adaptive information-theoretic experimental design procedure for high-to-low fidelity calibration of prostate cancer models.

The use of mathematical models to make predictions about tumor growth and response to treatment has become increasingly prevalent in the clinical setting. The level of complexity within these models ranges broadly, and the calibration of more complex models requires detailed clinical data. This raises questions about the type and quantity of data that should be collected and when, in order to maximize the information gain about the model behavior while still minimizing the total amount of data used and the time until a model can be calibrated accurately. To address these questions, we propose a Bayesian information-theoretic procedure, using an adaptive score function to determine the optimal data collection times and measurement types. The novel score function introduced in this work eliminates the need for a penalization parameter used in a previous study, while yielding model predictions that are superior to those obtained using two potential pre-determined data collection protocols for two different prostate cancer model scenarios: one in which we fit a simple ODE system to synthetic data generated from a cellular automaton model using radiotherapy as the imposed treatment, and a second scenario in which a more complex ODE system is fit to clinical patient data for patients undergoing intermittent androgen suppression therapy. We also conduct a robust analysis of the calibration results, using both error and uncertainty metrics in combination to determine when additional data acquisition may be terminated.

Can fractional differentiation improve stability results and data fitting ability of a prostate cancer model under intermittent androgen suppression therapy?

• This work verifys the advantageous side of fractional differentiation from the perspective of data ftting and stability analysis. • A prospective model in the recent prostate cancer literature is handled to be rebuilt in the context of fractional calculus . • Stability analyses of the reconstructed models release stronger outcomes. • Numerical simulations and mean square error values also show better data fitting results. In this paper, we compare the ordinary and fractional versions of a prospective model in the prostate cancer literature to be able to verify the hypothesis that fractional differentiation can improve stability results and data fitting ability of the ordinary version. For that, the mean square error values for androgen and prostate-specific antigen for the first 1.5 cycles of intermittent androgen suppression therapy administered to 62 selected patients from the Vancouver Prostate Center are computed. Stability analyses of the fractional models are also studied and showed how the fractional differentiation contributes to improve the stability results of an ordinary prostate model. Additionally, our findings are supported by PSA and androgen simulations of three different class of patients. Finally, with a conclusion part, which hints for future works should be taken into account are pointed out.

The Impact of Intermittent Androgen Suppression Therapy in Prostate Cancer Modeling

Previous studies on prostate cancer modeling under hormonal therapy successfully fit clinical serum androgen data, under the assumption that the levels of intracellular and serum androgen are similar. However, such an assumption may not hold throughout the course of treatment. In this paper, we propose a model that directly accounts for serum androgen and its interaction with intracellular androgen. We establish biological links between the model and clinical data, and discuss in detail parameter ranges and the initialization of model variables. We further investigate parameter sensitivity over time, which gauges the maximum effect of varying each parameter and allows us to fix some parameters, to increase the robustness of the parameter fitting process. By relying on the characteristics of intermittent androgen suppression therapy (IAS), we employ a two-part weighted error function for fitting. We also carry out mathematical analyses to study the dynamic aspects of the system with different androgen thresholds. We find that the proposed model shows superior forecasting ability, compared to its predecessor. Furthermore, we demonstrate the impact of androgen on the dynamics of the androgen-dependent and -independent cancer cells, which suggests the discrete description of androgen dependency may not give a realistic characterization of the cancer population. We show that IAS has certain characteristics that need to be considered for parameter estimation. Our results demonstrate that the model and the fitting scheme are viable for similar applications of prostate cancer modeling under hormonal therapy.

Dynamics and implications of models for intermittent androgen suppression therapy.

In this paper, we formulate a three cell population model of intermittent androgen suppression therapy for cancer patients to study the treatment resistance development. We compare it with other models that have different underlying cell population structure using patient prostate specific antigen (PSA) and androgen data sets. Our results show that in the absence of extensive data, a two cell population structure performs slightly better in replicating and forecasting the dynamics observed in clinical PSA data. We also observe that at least one absorbing state should be present in the cell population structure of a plausible model for it to produce treatment resistance under continuous hormonal therapy. This suggests that the heterogeneity of prostate cancer cell population can be represented by two types of cells differentiated by their level of dependence on androgen, where the two types are linked via an irreversible transformation.

Controllability of hybrid PDE‐ODE systems with structural instability and applications to mathematical models on intermittent hormonal therapy for prostate cancer

Several mathematical models on intermittent androgen suppression (IAS) therapy for prostate cancer are classified into hybrid PDE‐ODE system with structural instability. The purpose of this paper is to give a unified strategy to prove the controllability of the mathematical models on the IAS therapy. For this aim, we prove that (1) a generalized hybrid PDE‐ODE system is controllable for any initial data and (2) the result given by (1) is applicable to the mathematical models on the IAS therapy. Finally, we conclude that the mathematical models on the IAS therapy for prostate cancer are controllable for any initial data.

A nonlinear competitive model of the prostate tumor growth under intermittent androgen suppression

Hormone suppression has been the primary modality of treatment for prostate cancer. However long-term androgen deprivation may induce androgen-independent (AI) recurrence. Intermittent androgen suppression (IAS) is a potential way to delay or avoid the AI relapse. Mathematical models of tumor growth and treatment are simple while they are capable of capturing the essence of complicated interactions. Game theory models have analyzed that tumor cells can enhance their fitness by adopting genetically determined survival strategies. In this paper, we consider the survival strategies as the competitive advantage of tumor cells and propose a new model to mimic the prostate tumor growth in IAS therapy. Then we investigate the competition effect in tumor development by numerical simulations. The results indicate that successfully IAS-controlled states can be achieved even though the net growth rate of AI cells is positive for any androgen level. There is crucial difference between the previous models and the new one in the phase diagram of successful and unsuccessful tumor control by IAS administration, which means that the suggestions from the models for medication can be different. Furthermore we introduce quadratic logistic terms to the competition model to simulate the tumor growth in the environment with a finite carrying capacity considering the nutrients or inhibitors. The simulations show that the tumor growth can reach an equilibrium state or an oscillatory state with the net growth rate of AI cells being androgen independent. Our results suggest that the competition and the restraint of a limited environment can enhance the possibility of relapse prevention.

A new protocol for intermittent androgen suppression therapy of prostate cancer with unstable saddle-point dynamics

Intermittent androgen suppression (IAS) therapy is a class of hormonal treatment for prostate cancer, in which a drug-induced androgen deprivation can reduce the population of prostate cancer cells. In IAS therapy, drugs are administrated only in on-treatment periods that are separated intermittently by off-treatment periods. The presence of off-treatment periods may be beneficial for maintaining the sensitivity of the tumor cells to androgen deprivation. Thus, IAS can be superior to continuous androgen suppression (CAS) for delaying or possibly preventing relapse of a tumor. IAS therapy usually monitors the level of serum prostate-specific antigen (PSA), which is related to the population of tumor cells. Each on-treatment period begins when the PSA level is greater than an upper threshold; treatment results in a decrease in the PSA level. The on-treatment period is suspended when the PSA level falls below a lower threshold; the PSA level then rises again until the beginning of the next on-treatment period. To determine the transitions between on- and off-treatment periods, we propose a new IAS protocol that uses a model-based estimate of the state point in the phase space of the tumor dynamics. We show that the proposed protocol is effective if, in each of the on- and off-treatment periods, the tumor dynamics exhibits a saddle-point instability accompanied by a stable manifold. Mathematical analysis reveals that tumor dynamics can be controlled in a more effective and robust manner with the proposed protocol than with conventional IAS. We also discuss the clinical feasibility of the proposed protocol as an alternative to conventional IAS therapy.

A proposal of a new intermittent androgen suppression therapy method for prostate cancer with saddle type instability

A proposal of a new intermittent androgen suppression therapy method for prostate cancer with saddle type instability

Parameter estimation and optimal scheduling algorithm for a mathematical model of intermittent androgen suppression therapy for prostate cancer

We propose an algorithm based on cross-entropy to determine parameters of a piecewise linear model, which describes intermittent androgen suppression therapy for prostate cancer. By comparing with clinical data, the parameter estimation for the switched system shows good fitting accuracy and efficiency. We further optimize switching time points for the piecewise linear model to obtain a feasible therapeutic schedule. The simulation results of therapeutic effect are superior to those of previous strategy.

Defining the Optimal Approach to the Patient With Postradiation Prostate-Specific Antigen Recurrence Using Outcome Data From a Prospective Randomized Trial

Following PSA failure, intermittent androgen suppression therapy (AST) has been shown to be non-inferior to continuous AST with respect to survival; however the optimal management remains unknown when considering comorbidity and PSA kinetics at recurrence. To define randomized clinical trials (RCT) to address this issue, we examine factors associated with the risk of death following PSA failure.

A partial differential equation model and its reduction to an ordinary differential equation model for prostate tumor growth under intermittent hormone therapy

Hormonal therapy with androgen suppression is a common treatment for advanced prostate tumors. The emergence of androgen-independent cells, however, leads to a tumor relapse under a condition of long-term androgen deprivation. Clinical trials suggest that intermittent androgen suppression (IAS) with alternating on- and off-treatment periods can delay the relapse when compared with continuous androgen suppression (CAS). In this paper, we propose a mathematical model for prostate tumor growth under IAS therapy. The model elucidates initial hormone sensitivity, an eventual relapse of a tumor under CAS therapy, and a delay of a relapse under IAS therapy, which are due to the coexistence of androgen-dependent cells, androgen-independent cells resulting from reversible changes by adaptation, and androgen-independent cells resulting from irreversible changes by genetic mutations. The model is formulated as a free boundary problem of partial differential equations that describe the evolution of populations of the abovementioned three types of cells during on-treatment periods and off-treatment periods. Moreover, the model can be transformed into a piecewise linear ordinary differential equation model by introducing three new volume variables, and the study of the resulting model may help to devise optimal IAS schedules.

Nonlinear system identification for prostate cancer and optimality of intermittent androgen suppression therapy

These days prostate cancer is one of the most common types of malignant neoplasm in men. Androgen ablation therapy (hormone therapy) has been shown to be effective for advanced prostate cancer. However, continuous hormone therapy often causes recurrence. This results from the progression of androgen-dependent cancer cells to androgen-independent cancer cells during the continuous hormone therapy. One possible method to prevent the progression to the androgen-independent state is intermittent androgen suppression (IAS) therapy, which ceases dosing intermittently. In this paper, we propose two methods to estimate the dynamics of prostate cancer, and investigate the IAS therapy from the viewpoint of optimality. The two methods that we propose for dynamics estimation are a variational Bayesian method for a piecewise affine (PWA) system and a Gaussian process regression method. We apply the proposed methods to real clinical data and compare their predictive performances. Then, using the estimated dynamics of prostate cancer, we observe how prostate cancer behaves for various dosing schedules. It can be seen that the conventional IAS therapy is a way of imposing high cost for dosing while keeping the prostate cancer in a safe state. We would like to dedicate this paper to the memory of Professor Luigi M. Ricciardi.

Long-term effects of intermittent androgen suppression therapy on lean and fat mass: a 33-month prospective study

To examine changes to whole body and regional lean mass (LM) and fat mass (FM) over 33 months of intermittent androgen suppression therapy (IAST). Phase II cohort study of 72 prostate cancer patients without metastatic bone disease. Patients received flutamide 250 mg tid and leuprolide 22.5 mg three monthly depot for the 9-month initial treatment phase (iTREAT), at which point patients ceased therapy providing PSA <4 ng ml(-1) with continued monitoring for further 2 years (POST). AST was recommenced when PSA exceeded pretreatment level or ≥ 20 ng ml(-1). Body composition was assessed using dual energy X-ray absorptiometry at baseline, completion of treatment phase, and 1 and 2 years post treatment phase (months 21 and 33). LM decreased by 1.3 kg and FM increased by 2.3 kg (P<0.001) following iTREAT. During the POST period, there were no further adverse effects on LM or FM, but also no recovery to pretreatment levels. Patients who failed to recover testosterone by month 33 experienced a significant increase in FM compared with those who recovered eugonadal levels of testosterone (10 nmol ml(-1); P = 0.019). Change in testosterone was moderately correlated to changes in % FM (r = -0.314, P<0.028) and LM (r = 0.300, P<0.036) during POST phase. Waist circumference progressively increased over time and by 2 years, POST had not recovered to baseline levels. Loss of LM and gain in FM during the 9-month iTREAT was not reversed during 2-year POST, although further deterioration was not observed. Subgroup analysis identified those recovering testosterone showed some body composition improvements. These findings suggest potential benefits of IAST, where testosterone levels are able to recover, to reduce the ongoing adverse effects on body composition, such as the acceleration of sarcopenia and risks associated with metabolic disease.

A clinical data validated mathematical model of prostate cancer growth under intermittent androgen suppression therapy

Prostate cancer is commonly treated by a form of hormone therapy called androgen suppression. This form of treatment, while successful at reducing the cancer cell population, adversely affects quality of life and typically leads to a recurrence of the cancer in an androgen-independent form. Intermittent androgen suppression aims to alleviate some of these adverse affects by cycling the patient on and off treatment. Clinical studies have suggested that intermittent therapy is capable of maintaining androgen dependence over multiple treatment cycles while increasing quality of life during off-treatment periods. This paper presents a mathematical model of prostate cancer to study the dynamics of androgen suppression therapy and the production of prostate-specific antigen (PSA), a clinical marker for prostate cancer. Preliminary models were based on the assumption of an androgen-independent (AI) cell population with constant net growth rate. These models gave poor accuracy when fitting clinical data during simulation. The final model presented hypothesizes an AI population with increased sensitivity to low levels of androgen. It also hypothesizes that PSA production is heavily dependent on androgen. The high level of accuracy in fitting clinical data with this model appears to confirm these hypotheses, which are also consistent with biological evidence.

Mathematically modelling and controlling prostate cancer under intermittent hormone therapy.

In this review, we summarize our recently developed mathematical models that predict the effects of intermittent androgen suppression therapy on prostate cancer (PCa). Although hormone therapy for PCa shows remarkable results at the beginning of treatment, cancer cells frequently acquire the ability to grow without androgens during long-term therapy, resulting in an eventual relapse. To circumvent hormone resistance, intermittent androgen suppression was investigated as an alternative treatment option. However, at the present time, it is not possible to select an optimal schedule of on- and off-treatment cycles for any given patient. In addition, clinical trials have revealed that intermittent androgen suppression is effective for some patients but not for others. To resolve these two problems, we have developed mathematical models for PCa under intermittent androgen suppression. The mathematical models not only explain the mechanisms of intermittent androgen suppression but also provide an optimal treatment schedule for the on- and off-treatment periods.

Type I Collagen Synthesis Marker Procollagen I N-Terminal Peptide (PINP) in Prostate Cancer Patients Undergoing Intermittent Androgen Suppression

Intermittent androgen suppression (IAS) therapy for prostate cancer patients attempts to maintain the hormone dependence of the tumor cells by cycles alternating between androgen suppression (AS) and treatment cessation till a certain prostate-specific antigen (PSA) threshold is reached. Side effects are expected to be reduced, compared to standard continuous androgen suppression (CAS) therapy. The present study examined the effect of IAS on bone metabolism by determinations of serum procollagen I N-terminal peptide (PINP), a biochemical marker of collagen synthesis. A total of 105 treatment cycles of 58 patients with prostate cancer stages ≥pT2 was studied assessing testosterone, PSA and PINP levels at monthly intervals. During phases of AS lasting for up to nine months PSA levels were reversibly reduced, indicating apoptotic regression of the prostatic tumors. Within the first cycle PINP increased at the end of the AS period and peaked in the treatment cessation phase. During the following two cycles a similar pattern was observed for PINP, except a break in collagen synthesis as indicated by low PINP levels in the first months off treatment. Therefore, measurements of the serum PINP concentration indicated increased bone matrix synthesis in response to >6 months of AS, which uninterruptedly continued into the first treatment cessation phase, with a break into each of the following two pauses. In summary, synthesis of bone matrix collagen increases while degradation decreases during off-treatment phases in patients undergoing IAS. Although a direct relationship between bone matrix turnover and risk of fractures is difficult to establish, IAS for treatment of biochemical progression of prostate tumors is expected to reduce osteoporosis in elderly men often at high risk for bone fractures representing a highly suitable patient population for this kind of therapy.

Measurement of bone turnover in prostate cancer patients receiving intermittent androgen suppression therapy

PurposeReports on clinical measurements of bone mineral density (BMD) in prostate cancer patients undergoing intermittent androgen suppression therapy (IAS) that allows for hormonal recovery between treatment cycles indicate decreased osteoporosis compared to continuous androgen suppression therapy (CAS). In the present study the effect of IAS on bone metabolism by determinations of CrossLaps, a biochemical marker of collagen degradation, were examined.MethodIn total 100 IAS treatment cycles of 75 patients with prostate cancer stages ≥ pT2 were studied. Clinical data and monthly laboratory tests (testosterone, prostate-specific antigen; PSA) of these patients were monitored together with measurements of C-terminal telopeptide collagen fragments using CrossLaps® ELISA assays.ResultsDuring phases of androgen suppression (AS) lasting for 9 months serum testosterone (<1 ng/mL) and PSA (<2 ng/mL) levels were reversibly reduced, indicating partial growth arrest and apoptotic regression of the prostatic tumors. Serum CrossLaps concentrations peaked at the last 2 months of the AS phases (0.91 ± 0.25 μg/L; mean ± SEM) and were reduced below initial values (0.21 ± 0.43 versus baseline of 0.43 ± 0.06 μg/L) during therapy cessation periods until tumor progression-related increases.ConclusionMeasurements of the serum concentration of CrossLaps in prostate cancer patients receiving IAS indicated that treatment cessation phases rapidly reversed increased bone degradation associated with AS phases, in strong agreement with the clinical observations reporting reduced loss of BMD in IAS when compared to CAS. In terms of clinical outcomes, IAS seems to be as effective as CAS while showing reduced side effects, as demonstrated here by the reduction of androgen-induced bone matrix degradation.

Intermittent versus continuous androgen suppression therapy: do we have consensus yet?

Androgen deprivation therapy (ADT) has been a cornerstone in the management of advanced prostate cancer for more than 50 years, but several aspects of the therapy remain controversial. Research since the mid-1980s has looked at the use of intermittent androgen suppression (IAS) as a way to reduce the side effects and costs of continuous androgen suppression. During that same time, testing for prostate-specific antigen resulted in forward stage migration both at diagnosis and at the time of treatment initiation. Earlier treatment has led to prolonged periods of ADT and increasing recognition of the resultant metabolic complications. With preclinical evidence suggesting a potential benefit for ias in terms of time to androgen independence, with phase II and III studies producing optimistic results, and with the potential for reductions in cost and complications, ias has become a popular modality of therapy around the globe. Large prospective randomized studies, currently ongoing, will ultimately determine the legitimate place of IAS in the treatment of prostate cancer.

Measurement of bone turnover in prostate cancer patients receiving intermittent androgen suppression therapy

Measurement of bone turnover in prostate cancer patients receiving intermittent androgen suppression therapy