The Cancer of the Prostate Risk Assessment (CAPRA) score predicts biochemical recurrence in intermediate-risk prostate cancer treated with external beam radiotherapy (EBRT) dose escalation or low-dose rate (LDR) brachytherapy

Validation of the Combination Gleason Score as an Independent Favorable Prognostic Factor in Prostate Cancer Treated With Dose-Escalated Radiation Therapy

PURPOSE

Prognostic factors for prostate cancer include tumor, node, metastases stage, pretreatment prostate-specific antigen, and pathology (via Gleason score [GS] or grade group). Of these, GS yields the largest effect on prostate cancer specific mortality. It was previously determined that those with cores with a mix of higher and lower GS at biopsy (which was termed a "ComboGS") had decreased risk for prostate cancer specific mortality after either surgical or radiation treatment. We validate the effect of ComboGS in an independent cohort of patients with prostate cancer treated with definitive dose-escalated radiation therapy (DE-RT) at 2 institutions.

METHODS AND MATERIALS

DE-RT was administered to 2539 men, of which 687 men had a ComboGS. To further ascertain the ComboGS effect we employed the modified Cancer of the Prostate Risk Assessment (mCAPRA) score. Rates of biochemical event-free survival and distant metastasis-free survival were compared across CAPRA scores, with and without modification, and the prognostic value of the CAPRA scores was compared using Harrel's concordance index.

RESULTS

On univariate analysis in Gleason 7 to 10 patients the presence of ComboGS improved 10-year biochemical event-free survival from 76.6% to 82.4% (hazard ratio [HR], 0.75; confidence interval [CI], 0.59-0.96; P = .021), 10-year distant metastasis-free survival from 89.3% to 93.2% (HR, 0.57; CI, 0.39-0.85; P = .005), 10-year prostate cancer specific survival from 93.9% to 97.4% (HR, 0.39; CI, 0.21-0.7; P = .001), and 10-year overall survival from 65.7% to 75.6% (HR, 0.69; CI, 0.57-0.83; P < .001). Multivariable analysis also supported that ComboGS is protective for biochemical failure (HR, 0.64; CI, 0.50-0.83; P < .001), distant metastasis (HR, 0.42; CI, 0.28-0.63; P < .001), death from prostate cancer (HR, 0.32; CI, 0.17-0.58; P < .001), and overall mortality (HR, 0.65; CI, 0.54-0.79; P < .001). Additionally, adjusting the mCAPRA score for ComboGS decreased the risk of biochemical failure by nearly 30% (HR, 0.70; 95% CI, 0.55-0.88; P = .003) and by 50% (HR, 0.54; 95% CI, 0.37-0.80; P = .002) for distant metastasis.

CONCLUSIONS

ComboGS is a useful and readily available independent prognostic factor for all clinical endpoints evaluated. Moreover, the ComboGS can be used in conjunction with the extensively validated CAPRA scoring to better risk stratify patients being treated with definitive DE-RT for GS 7 to 10 disease.

Prediction of prostate cancer recurrence after radiation therapy using multiparametric magnetic resonance imaging and spectroscopy: assessment of prognostic factors on pretreatment imaging

BACKGROUND

To assess whether data from pre-therapeutic multiparametric magnetic resonance imaging (mpMRI) combined with three-dimensional magnetic resonance spectroscopy (3D MRS) provide prognostic factors of biochemical relapse in patients with localized prostate cancer treated by external radiotherapy or brachytherapy.

METHODS

In our single institution observational retrospective study we included a cohort of 230 patients treated by external radiotherapy or brachytherapy who had an initial mpMRI with 3D MRS from January 2008 to December 2015 for newly diagnosed localized prostatic cancer, proven histologically. Three trained radiologists recorded tumor characteristics, MRI T-stage and metabolic abnormalities from 3D MRS data. Univariate and multivariate Cox analyzes explored the relationship between clinical and imaging variables to highlight prognostic factors for recurrence, using biochemical relapse as the primary endpoint.

RESULTS

mpMRI data analysis allowed to reclassify 21.7% of the patients in a MRI National Comprehensive Cancer Network (NCCN) group higher than their initial clinical T-stage, but also to detect a lesion in 78% of the patients considered as clinically T1c. After a median of follow-up of 8.7 years (IQR, 6.6-10.1) following cancer diagnosis, 36 (16%) patients developed a biochemical relapse. The multivariate Cox analysis demonstrated the existence of 3 independent factors for prediction of biochemical recurrence: extracapsular extension (ECE) (HR =3.33; 95% CI: 1.93-5.73; P<0.01), choline/citrate ratio in healthy tissue in the transition zone (TZ) (HR =2.96; 95% CI: 1.06-8.28; P=0.04) and the NCCN Magnetic Resonance Imaging classification (intermediate versus low-risk, HR =3.06; 95% CI: 1.13-8.30; P<0.01).

CONCLUSIONS

Combination of mpMRI and 3DMRS could aid in the prognostic stratification of localized prostate cancer treated by radiotherapy or brachytherapy, by combining accurate evaluation of tumor extension, and quantification of prostate metabolism.

Validation of the new STAR-CAP prognostic group staging system in prostate cancer patients treated with radiation therapy

PURPOSE

To externally validate the STAR-CAP prognostic system for prostate cancer (PCa) and compare it to the CAPRA score to predict for biochemical recurrence (BCR) after radiation therapy (RTx).

METHODS

We included patients treated with RTx between 2002 and 2021 for non-metastatic PCa at our institution. BCR was defined based on Phoenix criteria. The 5-year BCR-free survival was assessed by univariable Kaplan-Meier analyses and log-rank test. Multivariable Cox regression models tested the independent association of each model for BCR. Performance of both models to predict 5-year BCR-free survival was assessed using the area under the curve (AUC).

RESULTS

The 2768 patients included were treated with high dose rate brachytherapy (13.3%) as a boost to external beam radiation therapy (EBRT), low dose rate seed brachytherapy (50.4%) or EBRT alone (35.9%). 14.4% of patients received concomitant androgen deprivation therapy (ADT). 222 patients experienced BCR (8%), with a median follow-up of 56 months. The 5-year BCR-free survival ranged from 88 (high risk) to 96% (low risk) in the STAR-CAP classification, and from 87 (high risk) to 97% (low risk) in the CAPRA system (p < 0.0001). Multivariate analyses, adjusted for ADT and type of treatment, confirmed the intrinsic ability of risk stratifications within each system to predict BCR (p < 0.001). Finally, AUC for the 5-year BCR prediction was 0.65 for STAR-CAP and 0.68 for CAPRA.

CONCLUSION

Both CAPRA and STAR-CAP prognostic group staging systems provide sufficient stratification and their predictive ability for 5-year BCR-free survival is comparable, with a small advantage for CAPRA (3%).

The CAPRA score versus sub-types of minimal residual disease to predict biochemical failure after external beam radiotherapy

Introduction

External beam radiotherapy is a treatment option for clinically localised prostate cancer; however, some 15% of patients will undergo treatment failure within 5 years. The objective was to compare the Cancer of the Prostate Risk Assessment (CAPRA) score (based on the clinical-pathological findings) and the sub-types of minimal residual disease (MRD) (based on the biological properties of the cancer cells) risk classifications to predict biochemical failure (BF) after external beam radiotherapy.

Methods and Patients

Clinical-pathological findings were obtained from the prostate biopsy to determine the CAPRA score and used to define low-, intermediate- and high-risk patients. Blood and bone marrow were obtained 3 months after radiotherapy; circulating prostate cells (CPCs) and micro-metastasis were detected using immunocytochemistry with anti-prostate specific antigen. CPCs and micro-metastasis were classified as positive if at least one cell was detected in the sample. Three subgroups were formed Group A (MRD negative), Group B (micro-metastasis positive, CPC negative) and Group C (CPC positive)Patients were followed up for 10 years or until biochemical failure. Biochemical failure free survival (BFFS) curves were constructed using Kaplan-Meier (observed), a flexible parameter model (predicted survival) and the restricted mean survival time (RMST) was calculated for each sub-group.

Results

309 men participated with a median follow-up of 8 years. The risk of biochemical failure increased proportionally with increasing CAPRA score, hazard ratio 1.18 for intermediate and 1.69 for high risk patients. After 10 years, the percentage BFFS and RMST to failure were 74%, 49%, 16% and 9, 7 and 6 years, respectively. The agreement between observed and predicted BFFS was acceptable (Harrell´s C 0.62). The BFFS curves for MRD were different and not proportional, survival curves for men MRD negative and only micro-metastasis were similar up to 5 years, and then there was increasing failure in the micro-metastasis only group. After 10 years, the percentage BFFS and RMST to failure were 95%, 59%, 28% and 10, 9 and 6 years, respectively. The CAPRA score failed to distinguish between Groups A and B, one third of high risk Group C had low risk CAPRA scores. The agreement between observed and predicted BFFS was very good (Harrell´s C 0.92). Minimal residual disease hazard ratios were Group B 1.84 and Group C 4.51.

Conclusions

The MRD prognostic classification is based on the biological characteristics of the tumour cell-microenvironment interaction, to give three groups, MRD negative, only bone marrow micro-metastasis and CPC positive prostate cancer. Differing from the CAPRA score classification the risk of treatment failure changes with time, differentiating between early and late treatment failures and incorporates the concept of dormancy. It proved to be superior to the CAPRA score in predicting biochemical failure and the results need to be confirmed in larger studies.

Downregulation of serum CXCL4L1 predicts progression and poor prognosis in prostate cancer patients treated by radical prostatectomy

Our previous study found that plate factor-4 variant (CXCL4L1) was downregulated in the serum of patients with prostate cancer (PCa). The aim of the present study was to investigate the prognostic value of CXCL4L1 in PCa. In total, 213 PCa patients treated with radical prostatectomy were enrolled and peripheral blood samples of all patients were collected. Expression of serum CXCL4L1 in patients with different tumor stages and grades were measured by enzyme-linked immunosorbent assay (ELISA). The Kaplan–Meier method was applied to estimate the progression to castration-resistant prostate cancer (CRPC), metastasis, biochemical recurrence (BCR)-free survival, and overall survival (OS). Prognostic factors for BCR-free survival and OS were determined by univariate and multivariate analyses using the Cox proportional hazards regression model. The expression of CXCL4L1 was significantly lower in PCa patients with advanced pathological tumor stage, high-grade Gleason score, and metastasis. Moreover, downregulation of CXCL4L1 not only strongly correlated with aggressive clinicopathological features, but also predicted tumor progression and unfavorable outcomes. Finally, multivariate Cox regression analyses identified CXCL4L1 as an independent prognostic factor for both BCR-free survival (hazard ratio [HR]: 2.03, 95% confidence interval [CI]: 1.26–3.27; P = 0.004) and OS (HR: 2.26, 95% CI: 1.07–4.79; P = 0.033). In conclusion, our results indicate that CXCL4L1 might serve as a novel and promising prognostic biomarker for patients with PCa and potential therapeutic target in the future.

Whom to Treat: Postdiagnostic Risk Assessment with Gleason Score, Risk Models, and Genomic Classifier

Management of prostate cancer presents unique challenges because of the disease's variable natural history. Accurate risk stratification at the time of diagnosis in clinically localized disease is crucial in providing optimal counseling about management options. To accurately distinguish pathologically indolent tumors from aggressive disease, risk groups are no longer sufficient. Rather, multivariable prognostic models reflecting the complete information known at time of diagnosis offer improved accuracy and interpretability. After diagnosis, further testing with genomic assays or other biomarkers improves risk classification. These postdiagnostic risk assessment tools should not supplant shared decision making, but rather facilitate risk classification and enable more individualized care.

Prostate-specific antigen percentage: An early predictive tool after iodine-125 interstitial brachytherapy for prostate cancer

BACKGROUND

After interstitial prostate iodine-125 brachytherapy (BT), prostate-specific antigen (PSA) evolution in time could predict overall biochemical relapse, but, considering the single patient, it is influenced by the presentation PSA amount and by the prostatic volume. It is also challenging to differentiate a PSA bounce from a biochemical relapse.

PURPOSE

To determine the usefulness of PSA percentage (PP) defined as the rate between PSA presented by a patient at time "t" and the PSA that the same patient had presented at the time of diagnosis (t0) assumed as 100% in predicting biochemical relapse and in differentiating them from PSA Bounces.

METHODS AND MATERIALS

We included 721 patients from Milan S. Raffaele Turro (399) and Lucca Campo di Marte (then S. Luca) Hospital (322). The mean age of patients was 66.5 years (range, 50-79). Mean followup was 150 months (range, 24-180). For each patient, PSA was recorded before and after iodine-125 BT, and PPs were calculated. Cox regression model, relative operating characteristic curves, and Kaplan-Meier regression model were elaborated, and a cutoff of 20% was defined.

RESULTS

We observed that PP >20% is an independent variable highly associated with relapse risk (p < 0.0001) with a sensitivity of 79.7%, a specificity of 82%, and an hazard ratio of 12.1, since the 6 months of followup. A PSA increase above the nadir should be because of bounce (sensitivity and specificity of 81.4%, p < 0.0001) if patient had experienced at 6 months a PP <20%.

CONCLUSIONS

PP might represent an early and useful tool, predictive of clinical outcome in patients after BT for prostate cancer.

An appraisal of analytical tools used in predicting clinical outcomes following radiation therapy treatment of men with prostate cancer: a systematic review

Background

Prostate cancer can be treated with several different modalities, including radiation treatment. Various prognostic tools have been developed to aid decision making by providing estimates of the probability of different outcomes. Such tools have been demonstrated to have better prognostic accuracy than clinical judgment alone.

Methods

A systematic review was undertaken to identify papers relating to the prediction of clinical outcomes (biochemical failure, metastasis, survival) in patients with prostate cancer who received radiation treatment, with the particular aim of identifying whether published tools are adequately developed, validated, and provide accurate predictions. PubMed and EMBASE were searched from July 2007. Title and abstract screening, full text review, and critical appraisal were conducted by two reviewers. A review protocol was published in advance of commencing literature searches.

Results

The search strategy resulted in 165 potential articles, of which 72 were selected for full text review and 47 ultimately included. These papers described 66 models which were newly developed and 31 which were external validations of already published predictive tools. The included studies represented a total of 60,457 patients, recruited between 1984 and 2009. Sixty five percent of models were not externally validated, 57% did not report accuracy and 31% included variables which are not readily accessible in existing datasets. Most models (72, 74%) related to external beam radiation therapy with the remainder relating to brachytherapy (alone or in combination with external beam radiation therapy).

Conclusions

A large number of prognostic models (97) have been described in the recent literature, representing a rapid increase since previous reviews (17 papers, 1966–2007). Most models described were not validated and a third utilised variables which are not readily accessible in existing data collections. Where validation had occurred, it was often limited to data taken from single institutes in the US. While validated and accurate models are available to predict prostate cancer specific mortality following external beam radiation therapy, there is a scarcity of such tools relating to brachytherapy. This review provides an accessible catalogue of predictive tools for current use and which should be prioritised for future validation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-017-0786-z) contains supplementary material, which is available to authorized users.

Three linked nomograms for predicting biochemical failure in prostate cancer treated with radiotherapy plus androgen deprivation therapy

BACKGROUND

Nomograms were established to predict biochemical recurrence (BCR) after radiotherapy (RT) with a low weight of the characteristic variables of RT and androgen deprivation therapy (ADT). Our aim is to provide a new stratified tool for predicting BCR at 4 and 7 years in patients treated using RT with radical intent.

MATERIALS AND METHODS

A retrospective, nonrandomized analysis was performed on 5044 prostate cancer (PCa) patients with median age 70 years, who received RT-with or without ADT-between November 1992 and May 2007. Median follow-up was 5.5 years. BCR was defined as a rise in serum prostate-specific antigen (PSA) of 2 ng/ml over the post-treatment PSA nadir. Univariate association between predictor variables and BCR was assessed by the log-rank test, and three linked nomograms were created for multivariate prognosis of BCR-free survival. Each nomogram corresponds to a category of the Gleason score-either 6,7, or 8-10-and all of them were created from a single proportional hazards regression model stratified also by months of ADT (0, 1-6, 7-12, 13-24, 25-36, 36-60). The performance of this model was analyzed by calibration, discrimination, and clinical utility.

RESULTS

Initial PSA, clinical stage, and RT dose were significant variables (p < 0.01). The model showed a good calibration. The concordance probability was 0.779, improving those obtained with other nomograms (0.587, 0.571, 0.554) in the database. Survival curves showed best clinical utility in a comparison with National Comprehensive Cancer Network (NCCN) risk groups.

CONCLUSION

For each Gleason score category, the nomogram provides information on the benefit of adding ADT to a specific RT dose.