Prostate-specific Antigen Evolution Research Articles

763 - Evolution of prostate specific antigen according to prostate volume after photoselective vaporization of the prostate with GreenLight XPS 18W: A five-year experience

763 - Evolution of prostate specific antigen according to prostate volume after photoselective vaporization of the prostate with GreenLight XPS 18W: A five-year experience

Mechanistic modelling of prostate-specific antigen dynamics shows potential for personalized prediction of radiation therapy outcome.

External beam radiation therapy is a widespread treatment for prostate cancer. The ensuing patient follow-up is based on the evolution of the prostate-specific antigen (PSA). Serum levels of PSA decay due to the radiation-induced death of tumour cells and cancer recurrence usually manifest as a rising PSA. The current definition of biochemical relapse requires that PSA reaches nadir and starts increasing, which delays the use of further treatments. Also, these methods do not account for the post-radiation tumour dynamics that may contain early information on cancer recurrence. Here, we develop three mechanistic models of post-radiation PSA evolution. Our models render superior fits of PSA data in a patient cohort and provide a biological justification for the most common empirical formulation of PSA dynamics. We also found three model-based prognostic variables: the proliferation rate of the survival fraction, the ratio of radiation-induced cell death rate to the survival proliferation rate, and the time to PSA nadir since treatment termination. We argue that these markers may enable the early identification of biochemical relapse, which would permit physicians to subsequently adapt patient monitoring to optimize the detection and treatment of cancer recurrence.

Reirradiation for isolated local recurrence of prostate cancer: Mono-institutional series of 64 patients treated with salvage stereotactic body radiotherapy (SBRT).

To evaluate high-precision external beam reirradiation (re-EBRT) for local relapse of prostate cancer (PCa) after radiotherapy. This retrospective study included patients with biochemical failure and evidence of isolated local recurrence of PCa after radical/salvage EBRT or brachytherapy that received salvage stereotactic body radiation therapy (SBRT, re-EBRT). Biopsy was not mandatory if all diagnostic elements were univocal (prostate specific antigen evolution, choline-positron emission tomography or magnetic resonance imaging). Salvage SBRT (re-EBRT) was delivered with image-guided radiation therapy (RapidArc®, VERO® and CyberKnife®). Data of 64 patients were included, median age at salvage SBRT was 73.2 years, median pre-salvage SBRT prostate specific antigen was 3.89 ng ml-1 . Median total dose was 30 Gy in five fractions, biologically effective dose (BED) of 150 Gy. One acute G3 genitourinary event and one late G3 genitourinary event were observed. No G ≥ 3 bowel toxicity was registered. At the median follow-up of 26.1 months, tumor progression was observed in 41 patients (64%). 18 patients (28%) experienced local relapse. 2-year local control, biochemical and clinical relapse free survival rates were 75, 40 and 53%, respectively. With BED ≥130 Gy 1-year biochemical and clinical progression-free survival rate were 85 and 90%, respectively. Salvage SBRT (re-EBRT) for isolated local PCa recurrence is a safe, feasible and noninvasive salvage treatment. Further investigation is warranted to define the optimal patient selection, dose and volume parameters. Salvage SBRT reirradiation for the locally recurrent PCa offer a satisfactory tumor control and excellent toxicity profile, if BED ≥130 Gy is administered.

Prostate-Specific Antigen Evolution After Photoselective Vaporization of the Prostate

Prostate-specific antigen (PSA) variations after photoselective vaporization of the prostate are an unsolved question. We included prospectively 323 patients who underwent GreenLight® prostate vaporization for prostatic hyperplasia between 2005 and 2013. We excluded patients with prostate cancer and those with concomitant prostate biopsies. Serum PSA levels were measured before and after the procedure at 1, 6, 12, 24, 36, and 48 months. The median preoperative PSA level was 4.50 ng/mL; it decreased to 2.41 ng/mL at 1 month (47% reduction), 2.17 ng/mL at 6 months (52% reduction), 2.30 ng/mL at 1 year (49% reduction), 2.40 ng/mL at 2 years (47% reduction), 2.31 ng/mL at 3 years (49% reduction), and 2.54 ng/mL at 4 years (44% reduction) (P values were all <0.0001). The median PSA nadir at 6 months was significantly different from the median PSA level at 1, 2, 3, and 4 years (respectively P=0.0046, P=0.0017, P=0.0006, and P=0.01). Patients who received ≤3000 J/cc had a significant trend to a PSA reascension after 6 months. Patients who received ≥4000 J/cc did not show any significant PSA reascension during the 4 years after procedure. Energy was correlated with the PSA reascension in univariate and multivariate analysis. The PSA level significantly decreased by half 1 month after the procedure, reached its nadir at 6 months, and showed a slight progressive reascension during the 4 following years. Applying an energy rate ≥4000 J/cc of prostate induced PSA stability over time whereas energy ≤3000 J/cc induced a reascension of the PSA level after 6 months.

Testing the evolution process of prostate-specific antigen in early stage prostate cancer: what is the proper underlying model?

This paper empirically tests a model of stochastic evolutions of prostate-specific antigen (PSA), a trigger for intervention in an early stage prostate cancer surveillance program. It conducts hypothesis testing of the Geometric Browning Motion model based on its attributes of independent increments and linearity of the variance in the increment length versus a wide range of stochastic and deterministic alternatives. These alternatives include the currently accepted deterministic growth model. The paper reports strong empirical evidence in favour of the Geometric Browning Motion model. A model that best describes PSA evolution is a prerequisite to the establishment of decision-making criteria for abandoning active surveillance (i.e. a strategy that involves close monitoring) in early stage prostate cancer. Thus, establishing empirically the type of PSA process is a first step toward the identification of more accurate triggers for abandoning active surveillance and starting treatment while the chances of curing the disease are still high.

A stochastic approach to risk management for prostate cancer patients on active surveillance

Screening for prostate cancer (PC) has led to more cancers being detected at early stages, where active surveillance (AS), a strategy that involves monitoring and intervention when the disease progresses, is an option. Physicians are seeking ways to measure progression of the disease such that AS is abandoned when appropriate. A blood test, prostate-specific antigen (PSA), and the concept of doubling time (PSADT) and PSA kinetics are being used as proxies of disease speed of progression. Studies using these proxies report conflicting results. These studies cast doubts on the current rules for stopping AS and recent research concludes that PSADT and PSA kinetics are unreliable triggers for intervention in an AS program. These findings are consistent with stochastic processes being analyzed as if they were “deterministic” (i.e., current models measure disease progression by PSA’s evolution assuming it to be deterministic). A model that best describes PSA evolution is a pre-requisite to the establishment of decision criteria for abandoning AS. This paper suggests modeling PSA evolutions and kinetics as stochastic processes. Consequently, triggers for stopping AS may be different than PSADT and can result in substantially different recommendations, which are likely to have significant impact on patients and the healthcare system.

Confirmation of a Low α/β Ratio for Prostate Cancer Treated by External Beam Radiation Therapy Alone Using a Post-Treatment Repeated-Measures Model for PSA Dynamics

To estimate the α/β ratio of prostate cancer treated with external beam radiation only by use of a model of long-term prostate-specific antigen (PSA) dynamics. Repeated measures of PSA from 5,093 patients from 6 institutions treated for localized prostate cancer by external beam radiation therapy (EBRT) without planned androgen deprivation were analyzed. A biphasic linear mixed model described the post-treatment evolution of PSA, rather than a conventional model of time to biochemical recurrence. The model was adjusted for standard prognostic factors (T stage, initial PSA level, and Gleason score) and cohort-specific effects. The radiation dose fractionation effect was estimated from the long-term rate of rise of PSA level. Adjusted for other factors, total dose of EBRT and sum of squared doses per fraction were associated with long-term rate of change of PSA level (p = 0.0017 and p = 0.0003, respectively), an increase of each being associated with a lower rate of rise. The α/β ratio was estimated at 1.55 Gy (95% confidence band, 0.46-4.52 Gy). This estimate was robust to adjustment of the linear mixed model. By analysis of a large EBRT-only cohort along with a method that uses all the repeated measures of PSA after the end of treatment, a low and precise α/β was estimated. These data support the use of hypofractionation at fractional doses up to 2.8 Gy but cannot presently be assumed to accurately represent higher doses per fraction.

Body Fat Distribution, Waist Circumference and Body Mass Index in Permanent Seed Prostate Brachytherapy

Purpose: Recent studies have shown that obesity is associated with more aggressive prostate cancer variants and a higher prostate specific antigen (PSA) recurrence following prostatectomy. The aim of this study is to analyze the influence of body mass index (BMI) and the distribution of adipose tissue on clinical pretreatment variables and PSA evolution post 125I prostate brachytherapy. Materials and Methods: We studied 59 men with low risk or ‘low tier” intermediate risk (maximum one intermediate risk feature) prostate cancer who had undergone 125I radioactive seed implantation as monotherapy. Inclusion criteria were an absence of hormonal therapy or external beam radiotherapy, a minimum of 8 months of followup and at least 3 followup PSA values. We calculated the BMI (kg/m2), waist circumference and the quotient between visceral and subcutaneous fat (VF/SF) measured on computed tomography at the iliac crest level. To analyze the influence of anthropometric measures on post-brachytherapy PSA evolution, we divided the patients into 2 groups: 1) rapid PSA descent post-brachytherapy to <0.5 ng/mL in the first 12 months following brachytherapy (n = 28); 2) slow PSA descent post-brachytherapy to <0.50 ng/mL and a followup of ≥24 months (n = 23) or a PSA bounce of ≥0.50 ng/mL (n = 6). The influence of those anthropometric measures on pretreatment PSA, prostate volume and number of positive biopsies were calculated using Spearman correlation coefficient. Differences between the 3? post-brachytherapy outcome groups were analyzed using the Pearson chi-square and Fisher's exact test. Relative risk estimate was calculated to measure of the strength of the association between the presence of a factor and the occurrence of an event. All tests were two-tailed. Results: There was an influence of the different anthropometric measures on pretreatment characteristics; there was a positive correlation between VF/SF and the PSA before treatment (r = 0.282, p = 0.029); and waist circumference with the number of positive biopsies (r = 0.374, p = 0.004). VS/SF, BMI and waist circumference were not different between both post-brachytherapy PSA-outcome groups (p≥0.439). The following factors were associated with being in the slow descent group: younger patients (less than the median age of 65 years), p = 0.003, relative risk (RR) 2.256 (95% confidence interval (CI), 1.249-4.073) and prostates smaller than the median 41 cc, p = 0.034, RR 0.550 (95%CI, 0.320-0.944). All patients with a waist circumference of >100 cm were in the rapid descent group. Among the patients with a VF/SF >0.9, 83% were in the slow descent group. Conclusions: In this small pilot study, waist circumference and VF/SF were weakly correlated to pretreatment characteristics. There seems to be a tendency that an increase in visceral fat and waist circumference has an influence on the type of PSA response. Larger studies are needed to determine if anthropomorphic measures have a direct influence on post-brachytherapy PSA response.

Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model

Latent class models have been recently developed for the joint analysis of a longitudinal quantitative outcome and a time to event. These models assume that the population is divided in G latent classes characterized by different risk functions for the event, and different profiles of evolution for the markers that are described by a mixed model for each class. However, the key assumption of conditional independence between the marker and the event given the latent classes is difficult to evaluate because the latent classes are not observed. Using a joint model with latent classes and shared random effects, we propose a score test for the null hypothesis of independence between the marker and the outcome given the latent classes versus the alternative hypothesis that the risk of event depends on one or several random effects from the mixed model in addition to the latent classes. A simulation study was performed to compare the behavior of the score test to other previously proposed tests, including situations where the alternative hypothesis or the baseline risk function are misspecified. In all the investigated situations, the score test was the most powerful. The methodology was applied to develop a prognostic model for recurrence of prostate cancer given the evolution of prostate-specific antigen in a cohort of patients treated by radiation therapy.

Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach

Prostate-specific antigen (PSA) is a biomarker routinely and repeatedly measured on prostate cancer patients treated by radiation therapy (RT). It was shown recently that its whole pattern over time rather than just its current level was strongly associated with prostate cancer recurrence. To more accurately guide clinical decision making, monitoring of PSA after RT would be aided by dynamic powerful prognostic tools that incorporate the complete posttreatment PSA evolution. In this work, we propose a dynamic prognostic tool derived from a joint latent class model and provide a measure of variability obtained from the parameters asymptotic distribution. To validate this prognostic tool, we consider predictive accuracy measures and provide an empirical estimate of their variability. We also show how to use them in the longitudinal context to compare the dynamic prognostic tool we developed with a proportional hazard model including either baseline covariates or baseline covariates and the expected level of PSA at the time of prediction in a landmark model. Using data from 3 large cohorts of patients treated after the diagnosis of prostate cancer, we show that the dynamic prognostic tool based on the joint model reduces the error of prediction and offers a powerful tool for individual prediction.

Évolution des formes moléculaires de l'antigène spécifique de la prostate chez des groupes sérologiques de patients atteints de pathologies prostatiques

The prostate-specific antigen (PSA) is a human tissular kallikrein used as serum tumoral marker of prostate cancer. The Total PSA and its molecular forms were detected at several different proportions in both patients with benign prostatic hyperplasia (BHP) and patients with prostate cancer (PCa). The purpose of the present study was to measure the total PSA in patients with these pathologies and to analyse the free PSA's evolution in each pathology group. Serums were taken from 90 patients with BHP and 23 with PCa. The DPC Immulite assays was used to determine total PSA and free PSA levels. The cut-off total PSA was 4 ng/ml. On a second hand were revelled that total PSA levels were variable in both BPH and PCa patients considering cut-off value. We showed that for BPH patients, 47 out of 90 present total PSA levels between 4–20 ng/ml, 6/90 between 20–100 ng/ml and 2/90 between 10–500 ng/ml. For PCa patients, 6 out of 23 present total PSA levels lower than 4 ng/ml. While, 2/23 of them between 4–20 ng/ml, 11/23 between 20–100 ng/ml and 4/23 between 100–900 ng/ml. Each serological group present a characteristic distribution of free molecular form of PSA, free PSA, marked by progressive free PSA level in related with total PSA. This individual concentration is variable in groups of patients having PSA levels higher than 20 ng/ml. The analysis of percentage free PSA/total PSA in each group of patient's showed characteristic percentages with a significant difference between BHP and PCa patients essentially in group with total PSA level between 4–20 ng/ml ( P = 0,0004), followed a less significant difference less for the group with total PSA between 0–4 ng/ml. Differences are not significant in groups patient's with total PSA higher than 20 ng/ml.

Optimising Hormone Therapy in Advanced Disease

Although most prostate cancer (PCa) patients nowadays are diagnosed at an early stage of disease, unfortunately still a significant number of patients will develop advanced PCa or will be diagnosed at an advanced (or metastatic) stage of disease. The group of patients showing the highest increase in incidence are those with rising prostate specific antigen (PSA) after radical therapy. In the last quarter of 2004, a Medline search has been performed targeting publications on patients diagnosed with advanced PCa, as well as with PSA relapse after previous radical therapy. This review aims at providing guidance to optimise hormone therapy in those selected groups of patients by addressing three pivotal questions; (i) who should receive hormonal treatment, (ii) what type of hormonal therapy should the patient be offered and (iii) what is the best timing of starting hormonal treatment. In patients relapsing after radical therapy, the PSA doubling time (PSA DT) has become a critical instrument to distinguish patients to have innocuous PSA evolution from patients at high risk for disease progression. A PSA DT of 3 months seems to be the cut-off point for identifying patients at risk. Therefore patients with a PSA DT of less than 3 months should be advised to initiate hormonal therapy. Antiandrogen monotherapy may be considered in this setting as it has been shown to delay progression; however, significant survival data are not yet available. Whether luteinising hormone releasing hormone (LHRH) agonists should be given continuously or intermittently (IHT) remains subject of debate. Surgical castration has been the standard of care in patients diagnosed with advanced PCa. Currently, LHRH agonists have become the preferred way of suppressing testosterone. Combination of an antiandrogen and a LHRH agonist (CAB) shows a modest benefit over LHRH agonist monotherapy. As CAB leads to increased side effects and costs, LHRH agonist monotherapy is preferred in the majority of patients. Conflicting data have been published concerning the optimal timing of LHRH agonist therapy. So it is not clear whether LHRH agonist therapy should be started immediately or deferred until appearance of symptoms. When initiating continuous hormone therapy, patients should be carefully monitored for the risk of long term androgen deprivation (anaemia, osteopenia and osteoporosis).