Nomogram for overall survival of patients with progressive metastatic prostate cancer after castration

Prostate cancer nomograms and their application in Asian men: a review

Nomograms help to predict outcomes in individual patients rather than whole populations and are an important part of evaluation and treatment decision making. Various nomograms have been developed in malignancies to predict and prognosticate clinical outcomes such as severity of disease, overall survival, and recurrence-free survival. In prostate cancer, nomograms were developed for determining need for biopsy, disease course, need for adjuvant therapy, and outcomes. Most of these predictive nomograms were based on Caucasian populations. Prostate cancer is significantly affected by race, and Asian men have a significantly different racial and genetic susceptibility compared to Caucasians, raising the concern in generalizability of these nomograms. We reviewed the existing literature for nomograms in prostate cancer and their application in Asian men. There are very few studies that have evaluated the applicability and validity of the existing nomograms in these men. Most have found significant differences in the performance in this population. Thus, more studies evaluating the existing nomograms in Asian men or suggesting modifications for this population are required.

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Real-world outcomes of abiraterone and enzalutamide in first-line treatment of metastatic castration-resistant prostate cancer: which patients benefit most?

OBJECTIVES

Abiraterone and enzalutamide are two oral novel androgen receptor axis-targeted agents approved for the treatment of castration-resistant prostate cancer (mCRPC). Despite the availability of multiple treatments, there is a need to improve the knowledge and management of these drugs in the real-world setting, especially in patient groups under-represented in clinical trials. Our aim was to review the outcome of patients with chemotherapy-naïve mCRPC treated with abiraterone or enzalutamide in routine clinical practice in order to identify factors that are predictive for response.

METHODS

This observational retrospective study was performed in a Spanish tertiary hospital and included men with chemotherapy-naïve mCPRC who started treatment with abiraterone or enzalutamide between September 2012 and November 2018. The study end date was 30 October 2020.

RESULTS

Ninety patients with mCRPC were included, 57 with abiraterone and 33 with enzalutamide. Median overall survival (OS) was 26.87 months (95% CI 19.68 to 34.05), with no difference found between the two treatment groups. Nine variables were related to increased OS in the univariate analysis: Eastern Cooperative Oncology Group (ECOG) performance status (0-1 vs 2), pain (need of opioids for cancer pain), visceral disease, ≥3 bone lesions, exclusively lymph node metastases, baseline prostate specific antigen (PSA) (<50 vs ≥50 ng/dL and <20 vs ≥20 ng/dL), haemoglobin (<12 vs ≥12 g/dL) and alkaline phosphatase (≤116 vs >116 IU/L). A PSA response >50% was observed in 65 patients (76.5%). In the multivariate analysis, ECOG performance status, pain, visceral disease and alkaline phosphatase provided independent prognostic information. Median OS by Kaplan-Meier analysis was significantly longer for patients with a PSA response (32.1 vs 17.9 months; HR 0.46, 95% CI 0.27 to 0.78; p=0.003).

CONCLUSIONS

This study assessed the efficacy of abiraterone and enzalutamide in a real-world setting, including patients under-represented in pivotal studies. Some clinical factors were correlated with improved OS in chemotherapy-naïve men with mCPRC treated with these drugs.

External Validation of a Prognostic Model of Overall Survival in Men With Chemotherapy-Naïve Metastatic Castration-Resistant Prostate Cancer

PURPOSE

We have previously developed and externally validated a prognostic model of overall survival (OS) in men with metastatic, castration-resistant prostate cancer (mCRPC) treated with docetaxel. We sought to externally validate this model in a broader group of men with docetaxel-naïve mCRPC and in specific subgroups (White, Black, Asian patients, different age groups, and specific treatments) and to classify patients into validated two and three prognostic risk groupings on the basis of the model.

METHODS

Data from 8,083 docetaxel-naïve mCRPC men randomly assigned on seven phase III trials were used to validate the prognostic model of OS. We assessed the predictive performance of the model by computing the time-dependent area under the receiver operating characteristic curve (tAUC) and validated the two-risk (low and high) and three-risk prognostic groups (low, intermediate, and high).

RESULTS

The tAUC was 0.74 (95% CI, 0.73 to 0.75), and when adjusting for the first-line androgen receptor (AR) inhibitor trial status, the tAUC was 0.75 (95% CI, 0.74 to 0.76). Similar results were observed by the different racial, age, and treatment subgroups. In patients enrolled on first-line AR inhibitor trials, the median OS (months) in the low-, intermediate-, and high-prognostic risk groups were 43.3 (95% CI, 40.7 to 45.8), 27.7 (95% CI, 25.8 to 31.3), and 15.4 (95% CI, 14.0 to 17.9), respectively. Compared with the low-risk prognostic group, the hazard ratios for the high- and intermediate-risk groups were 4.3 (95% CI, 3.6 to 5.1; P < .0001) and 1.9 (95% CI, 1.7 to 2.1; P < .0001).

CONCLUSION

This prognostic model for OS in docetaxel-naïve men with mCRPC has been validated using data from seven trials and yields similar results overall and across race, age, and different treatment classes. The prognostic risk groups are robust and can be used to identify groups of patients for enrichment designs and for stratification in randomized clinical trials.

C-reactive protein levels could be a prognosis predictor of prostate cancer: A meta-analysis

BACKGROUND

The relationship between the C-reactive protein (CRP) and prognosis in prostate cancer (PCa) has been widely discussed over the past few years but remains controversial.

MATERIAL AND METHODS

In our meta-analysis, we searched 16 reliable studies in the PubMed, Embase, and Cochrane Library databases. Otherwise, we have successfully registered on the INPLASY. We also performed random- and fixed-effects models to evaluate the hazard ratio (HR) and 95% confidence interval (CI), respectively.

RESULT

The result of our meta-analysis shows that elevated CRP levels were related to worse overall survival (OS) (HR = 1.752, 95% CI = 1.304-2.355, p = 0.000), cancer-specific survival (CSS) (HR = 1.663, 95% CI = 1.064-2.6, p = 0.026), and progression-free survival (PFS) (HR = 1.663, 95% CI = 1.064-2.6, p = 0.026) of PCa patients. There was significant heterogeneity, so we performed a subgroup analysis according to the staging of the disease and found the same result. Furthermore, the heterogeneity was also reduced, and no statistical significance.

CONCLUSION

Our study shows that the level of CRP could reflect the prognosis of prostate cancer patients. We find that PCa patients with high levels of CRP often have worse OS, CSS, and PFS, although the stages of the patients' disease are different. More studies are needed to verify this idea.

Development and validation of a nomogram for predicting survival time and making treatment decisions for clinical stage IA NSCLC based on the SEER database

Background

The aim of this study was to establish and validate a nomogram model for accurate prediction of patients' survival with T1aN0M0 none small cell lung cancer (NSCLC).

Methods

The patients, diagnosed with the stage IA NSCLC from 2004-2015, were identified from the Surveillance, Epidemiology and End Results (SEER) database. The variables with a P-value < 0.05 in a multivariate Cox regression were selected to establish the nomogram. The discriminative ability of the model was evaluated by the concordance index (C-index). The proximity of the nomogram prediction to the actual risk was depicted by a calibration plot. The clinical usefulness was estimated by the decision curve analysis (DCA). Survival curves were made with Kaplan-Meier method and compared by Log-Rank test.

Results

Eight variables, including treatment, age, sex, race, marriage, tumor size, histology, and grade were selected to develop the nomogram model by univariate and multivariate cox regression. The C-index was 0.704 (95% CI, 0.694-0.714) in the training set and 0.713 (95% CI, 0.697-0.728) in the test set, which performed significantly better than 8th edition AJCC TNM stage system (0.550, 95% CI, 0.408-0.683, P < 0.001). The calibration curve showed that the prediction ability of 3-years and 5-years survival rate demonstrated a high degree of agreement between the nomogram model and the actual observation. The DCA curves also proved that the nomogram-assisted decisions could improve patient outcomes.

Conclusion

We established and validated a prognostic nomogram to predict 3-years and 5-years overall survival in stage IA NSCLC.

A novel prognostic model predicting overall survival in patients with metastatic castration-resistant prostate cancer receiving standard chemotherapy: A multi-trial cohort analysis

PURPOSE

Generalizable, updated, and easy-to-use prognostic models for patients with metastatic castration-resistant prostate cancer (mCRPC) are lacking. We developed a nomogram predicting the overall survival (OS) of mCRPC patients receiving standard chemotherapy using data from five randomized clinical trials (RCTs).

METHODS

Patients enrolled in the control arm of five RCTs (ASCENT 2, VENICE, CELGENE/MAINSAIL, ENTHUSE 14, and ENTHUSE 33) were randomly split between training (n = 1636, 70%) and validation cohorts (n = 700, 30%). In the training cohort, Cox regression tested the prognostic significance of all available variables as a predictor of OS. Independent predictors of OS on multivariable analysis were used to construct a novel multivariable model (nomogram). The accuracy of this model was tested in the validation cohort using time-dependent area under the curve (tAUC) and calibration curves.

RESULTS

Most of the patients were aged 65-74 years (44.5%) and the median (interquartile range) follow-up time was 13.9 (8.9-20.2) months. At multivariable analysis, the following were independent predictors of OS in mCRPC patients: sites of metastasis (visceral vs. bone metastasis, hazard ratio [HR]: 1.24), prostate-specific antigen (HR: 1.00), aspartate transaminase (HR: 1.01), alkaline phosphatase (HR: 1.00), body mass index (HR: 0.97), and hemoglobin (≥13 g/dl vs. <11 g/dl, HR: 0.41; all p < 0.05). A nomogram based on these variables was developed and showed favorable discrimination (tAUC at 12 and 24 months: 73% and 72%, respectively) and calibration characteristics on external validation.

CONCLUSION

A new prognostic model to predict OS of patients with mCRPC undergoing first line chemotherapy was developed. This can help urologists/oncologists in counseling patients and might be useful to better stratify patients for future clinical trials.

Translation of Prognostic and Pharmacodynamic Biomarkers from Trial to Non-trial Patients with Metastatic Castration-resistant Prostate Cancer Treated with Docetaxel

AIMS

We conducted a pooled analysis of four randomised controlled trials and a non-trial retrospective dataset to study the changes in serum prostate-specific antigen (PSA) concentrations during treatment and its impact on survival in men treated with docetaxel for metastatic castration-resistant prostate cancer. We also compared the outcomes and pre-treatment prognostic factors between trial and non-trial patients.

MATERIALS AND METHODS

Data were obtained from four randomised controlled trials and a non-trial cohort from a tertiary cancer centre. The PSA kinetics covariates chosen were absolute value (PSAT), best percentage change (BPCH) and tumour growth rate (K). The association between the covariates collected and overall survival was assessed within a Cox proportional hazards model. How well a covariate captured the difference between trial and non-trial patients was assessed by reporting on models with or without trial status as a covariate.

RESULTS

We reviewed individual datasets of 2282 patients. The median overall survival for trial patients was 20.4 (95% confidence interval 19.6-22.2) months and for the non-trial cohort was 12.4 (10.7-14.7) months (P < 0.001). Of the pre-treatment factors, we found that only lactate dehydrogenase fully captured the difference in prognosis between the trial and non-trial cohorts. All PSA kinetic metrics appeared to be prognostic in both the trial and non-trial patients. However, the effect size was reduced in non-trial versus trial patients (interaction P < 0.001). Of the time-dependent covariates, we found that BPCH best captured the difference between trial and non-trial patient prognosis.

CONCLUSIONS

The analysis presented here highlights how data from open-source trial databases can be combined with emerging clinical practice databases to assess differences between trial versus non-trial patients for particular treatments. These results highlight the importance of developing prognostic models using both pre-treatment and time-dependent biomarkers of new treatments.

Effect of chemotherapy in metastatic prostate cancer according to race/ethnicity groups

BACKGROUND

No North-American study tested the survival benefit of chemotherapy in de novo metastatic prostate cancer according to race/ethnicity. We addressed this void.

METHODS

We identified de novo metastatic prostate cancer patients within the Surveillance, Epidemiology, and End Results database (2014-2015). Separate and specific Kaplan-Meier plots and Cox regression models tested for overall survival differences between chemotherapy-exposed versus chemotherapy-naïve patients in four race/ethnicity groups: Caucasian versus African-American versus Hispanic/Latino vs Asian. Race/ethnicity specific propensity score matching was applied. Here, additional landmark analysis was performed.

RESULTS

Of 4232 de novo metastatic prostate cancer patients, 2690 (63.3%) were Caucasian versus 783 (18.5%) African-American versus 504 (11.8%) Hispanic/Latino versus 257 (6.1%) Asian. Chemotherapy rates were: 21.3% versus 20.8% versus 21.0% versus 20.2% for Caucasians versus African-Americans versus Hispanic/Latinos versus Asians, respectively. At 30 months of follow-up, overall survival rates between chemotherapy-exposed versus chemotherapy-naïve patients were 61.5 versus 53.2% (multivariable hazard ratio [mHR]: 0.76, 95 confidence interval [CI]: 0.63-0.92, p = 0.004) in Caucasians, 55.2 versus 51.6% (mHR: 0.76, 95 CI: 0.54-1.07, p = 0.11) in African-Americans, 62.8 versus 57.0% (mHR: 1.11, 95 CI: 0.73-1.71, p = 0.61) in Hispanic/Latinos and 77.7 versus 65.0% (mHR: 0.31, 95 CI: 0.11-0.89, p = 0.03) in Asians. Virtually the same findings were recorded after propensity score matching within each race/ethnicity group.

CONCLUSIONS

Caucasian and Asian de novo metastatic prostate cancer patients exhibit the greatest overall survival benefit from chemotherapy exposure. Conversely, no overall survival benefit from chemotherapy exposure could be identified in either African-Americans or Hispanic/Latinos. Further studies are clearly needed to address these race/ethnicity specific disparities.

Efficacy and Safety of Autologous Dendritic Cell-Based Immunotherapy, Docetaxel, and Prednisone vs Placebo in Patients With Metastatic Castration-Resistant Prostate Cancer: The VIABLE Phase 3 Randomized Clinical Trial

IMPORTANCE

DCVAC/PCa is an active cellular immunotherapy designed to initiate an immune response against prostate cancer.

OBJECTIVE

To evaluate the efficacy and safety of DCVAC/PCa plus chemotherapy followed by DCVAC/PCa maintenance treatment in patients with metastatic castration-resistant prostate cancer (mCRPC).

DESIGN, SETTING, AND PARTICIPANTS

The VIABLE double-blind, parallel-group, placebo-controlled, phase 3 randomized clinical trial enrolled patients with mCRPC among 177 hospital clinics in the US and Europe between June 2014 and November 2017. Data analyses were performed from December 2019 to July 2020.

INTERVENTIONS

Eligible patients were randomized (2:1) to receive DCVAC/PCa (add-on and maintenance) or placebo, both in combination with chemotherapy (docetaxel plus prednisone). The stratification was applied according to geographical region (US or non-US), prior therapy (abiraterone, enzalutamide, or neither), and Eastern Cooperative Oncology Group performance status (0-1 or 2). DCVAC/PCa or placebo was administered subcutaneously every 3 to 4 weeks (up to 15 doses).

MAIN OUTCOMES AND MEASURES

The primary outcome was overall survival (OS), defined as the time from randomization until death due to any cause, in all randomized patients. Survival was compared using 2-sided log-rank test stratified by geographical region, prior therapy with abiraterone and/or enzalutamide, and Eastern Cooperative Oncology Group performance status.

RESULTS

A total of 1182 men with mCRPC (median [range] age, 68 [46-89] years) were randomized to receive DCVAC/PCa (n = 787) or placebo (n = 395). Of these, 610 (81.8%) started DCVAC/PCa, and 376 (98.4%) started placebo. There was no difference in OS between the DCVAC/PCa and placebo groups in all randomized patients (median OS, 23.9 months [95% CI, 21.6-25.3] vs 24.3 months [95% CI, 22.6-26.0]; hazard ratio, 1.04; 95% CI, 0.90-1.21; P = .60). No differences in the secondary efficacy end points (radiological progression-free survival, time to prostate-specific antigen progression, or skeletal-related events) were observed. Treatment-emergent adverse events related to DCVAC/PCa or placebo occurred in 69 of 749 (9.2%) and 48 of 379 (12.7%) patients, respectively. The most common treatment-emergent adverse events (DCVAC/PCa [n = 749] vs placebo [n = 379]) were fatigue (271 [36.2%] vs 152 [40.1%]), alopecia (222 [29.6%] vs 130 [34.3%]), and diarrhea (206 [27.5%] vs 117 [30.9%]).

CONCLUSIONS AND RELEVANCE

In this phase 3 randomized clinical trial, DCVAC/PCa combined with docetaxel plus prednisone and continued as maintenance treatment did not extend OS in patients with mCRPC and was well tolerated.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02111577.

Nomogram for predicting the overall survival of patients with early-onset prostate cancer: A population-based retrospective study

Background

The incidence of early‐onset prostate cancer (PCa) has increased significantly over the past few decades. It is necessary to develop a prognostic nomogram for the prediction of overall survival (OS) in early‐onset PCa patients.

Methods

A total of 23,730 early‐onset PCa patients (younger than 55 years old) between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled for the current study, and randomly separated into the training cohort and the validation cohort. 361 eligible early‐onset PCa patients from The Cancer Genome Atlas‐Prostate Adenocarcinoma (TCGA‐PRAD) cohort were obtained as the external validation cohort. Independent predictors were selected by univariate and multivariate Cox regression analysis, and a prognostic nomogram was constructed for 1‐, 3‐, and 5‐year OS. The accurate and discriminative abilities of the nomogram were evaluated by the concordance index (C‐index), receiver operating characteristic curve (ROC), calibration plot, net reclassification index (NRI), and integrated discrimination improvement (IDI).

Results

Multivariate Cox analysis showed that race, marital status, TNM stage, prostate‐specific antigen, Gleason score, and surgery were significantly associated with poor prognosis of PCa. A nomogram consisting of these variables was established, which had higher C‐indexes than the TNM system (training cohort: 0.831 vs. 0.746, validation cohort: 0.817 vs. 0.752). Better AUCs of the nomogram than the TNM system at 1, 3, and 5 years were found in both the training cohort and the validation cohort. The 3‐year and 5‐year AUCs of the nomogram in the TCGA‐PRAD cohort were 0.723 and 0.679, respectively. The calibration diagram, NRI, and IDI also showed promising prognostic value in OS.

Conclusions

We developed an effective prognostic nomogram for OS prediction in early‐onset PCa patients, which will further assist both the precise clinical treatment and the assessment of long‐term outcomes.

Identification and validation of the prognostic impact of metastatic prostate cancer phenotypes

INTRODUCTION

Castration-sensitive metastatic prostate cancer is heterogeneous. Our objective is to identify metastatic prostate cancer phenotypes and their prognostic impact on survival.

MATERIALS AND METHODS

The National Cancer Database was queried. The Surveillance, Epidemiology, and End Results database was used for validation. Patterns were split into: nonregional lymph node, bone only, and visceral (any brain/liver/lung). Hazard ratios (HR) with 95% confidence intervals (CI) were calculated for the univariate and multivariate Cox proportional hazards regression models, odds ratios were calculated, Kaplan-Meier curves were generated, and a nomogram of the multivariate regression model was created.

RESULTS

The training set included 13,818 men; bone only was most common (n = 11,632, 84.2%), then nonregional lymph node (n = 1388, 10.0%), and any visceral (brain/liver/lung; n = 798, 5.8%). Risk of death was increased by metastases to a visceral organ versus nonregional lymph node (HR = 2.26; 95% CI [2.00, 2.56]), bone only metastases versus nonregional lymph node (HR = 1.57; 95% CI [1.43, 1.72]), T-stage 4 versus 1 (HR = 1.27; 95% CI [1.17, 1.36]), Grade Group 5 versus 1 (HR = 1.93; 95% CI [1.61, 2.31]), PSA > 20 ng/mL versus < 10 ng/mL (HR = 1.32; 95% CI [1.23, 1.42]), and age ≥ 80 versus < 50 (HR = 1.96; 95% CI [1.69, 2.29]). On internal validation, the model had C-indices 20.5%, 22.7%, and 14.6% higher than the current staging system for overall survival, 1-year, and 5-year survival, respectively.

CONCLUSION

We developed and validated prognostic metastatic prostate cancer phenotypes that can assist risk stratification to potentially personalize therapy. Our nomogram (https://tinyurl.com/prostate-met) may be used to predict survival.

Combining liquid biopsy and functional imaging analysis in metastatic castration-resistant prostate cancer helps predict treatment outcome

Plasma tumour DNA (ptDNA) is a potential early noninvasive biomarker of treatment outcome in metastatic castration-resistant prostate cancer (mCRPC). Herein, we investigated whether pretreatment ptDNA levels reflect metabolic tumour burden in mCRPC and better predict treatment outcome in combination with functional imaging. Targeted next-generation sequencing was performed to estimate the ptDNA fraction from 102 mCRPC patients receiving abiraterone or enzalutamide. The maximum standardized uptake value (SUVmax), total lesion activity (TLA) and metabolic tumour volume (MTV) were evaluated on 18 F-fluorocholine positron emission tomography/computed tomography. We assessed a Weibull multiple regression model to determine the combined impact of clinical, molecular and imaging characteristics on overall survival (OS) and progression-free survival (PFS), and to obtain prognostic scores. A significant association was seen between ptDNA and SUVmax, MTV and TLA. For survival analysis, patients were randomly allocated into a training (n = 68) and a validation (n = 34) set. In the training set, multivariable analyses showed that ptDNA, MTV and serum lactate dehydrogenase together with visceral metastasis were independent predictors of both OS and PFS. Prognostic scores were generated, with the identification of three groups of patients with significantly different median OS (29.2, 15.9 and 8.7 months) and PFS (13.3, 7.7 and 3.2 months) probabilities. The differences in median survival between risk groups were confirmed in the validation cohort for both OS and PFS. In our study, we showed that integrating plasma DNA analysis with functional imaging may improve prognostic risk stratification and treatment selection in mCRPC.

Effect of Chemotherapy on Overall Survival in Contemporary Metastatic Prostate Cancer Patients

Introduction

Randomized clinical trials demonstrated improved overall survival in chemotherapy exposed metastatic prostate cancer patients. However, real-world data validating this effect with large scale epidemiological data sets are scarce and might not agree with trials. We tested this hypothesis.

Materials and Methods

We identified de novo metastatic prostate cancer patients within the Surveillance, Epidemiology, and End Results (SEER) database (2014-2015). Kaplan-Meier plots and Cox regression models tested for overall survival differences between chemotherapy-exposed patients vs chemotherapy-naïve patients. All analyses were repeated in propensity-score matched cohorts. Additionally, landmark analyses were applied to account for potential immortal time bias.

Results

Overall, 4295 de novo metastatic prostate cancer patients were identified. Of those, 905 (21.1%) patients received chemotherapy vs 3390 (78.9%) did not. Median overall survival was not reached at 30 months follow-up. Chemotherapy-exposed patients exhibited significantly better overall survival (61.6 vs 54.3%, multivariable HR:0.82, CI: 0.72-0.96, p=0.01) at 30 months compared to their chemotherapy-naïve counterparts. These findings were confirmed in propensity score matched analyses (multivariable HR: 0.77, CI:0.66-0.90, p<0.001). Results remained unchanged after landmark analyses were applied in propensity score matched population.

Conclusions

In this contemporary real-world population-based cohort, chemotherapy for metastatic prostate cancer patients was associated with better overall survival. However, the magnitude of overall survival benefit was not comparable to phase 3 trials.

Impact of Serum γ-Glutamyltransferase on Overall Survival in Men with Metastatic Castration-Resistant Prostate Cancer Treated with Docetaxel

Simple Summary

γ-Glutamyltransferase (GGT) is a biomarker of oxidative stress and its elevation in the serum is linked to poor survival in various malignancies; however, reports on metastatic castration-resistant prostate cancer (mCRPC) are scarce. Moreover, the source of serum GGT in men with mCRPC is largely unknown. The aims of this study were to determine the impact of serum GGT on overall survival in men with mCRPC receiving docetaxel therapy, and to examine the association between systemic and local GGT levels using immunohistochemistry. Of note, high serum GGT was associated with adverse overall survival as were low hemoglobin and high prostate-specific antigen levels. Additionally, tissue GGT expression status in prostate specimens was moderately positively associated with serum GGT. We demonstrated that pre-therapeutic serum GGT was an independent prognosticator in men with mCRPC receiving docetaxel therapy, and that overexpression of GGT in cancer cells might be responsible for the elevation of serum GGT.

Abstract

Background: Reports on the prognostic significance of serum γ-glutamyltransferase (GGT) in men with metastatic castration-resistant prostate cancer (mCRPC) are limited. In addition, GGT expression status in cancer tissues has not been well characterized regardless of cancer types. Methods: This retrospective study included 107 consecutive men with mCRPC receiving docetaxel therapy. The primary endpoints were associations of serum GGT with overall survival (OS) and prostate-specific antigen (PSA) response. The secondary endpoint was an association of serum GGT with progression-free survival (PFS). Additionally, GGT expression status was immunohistochemically semi-quantified using tissue microarrays. Results: A total of 67 (63%) men died during follow-up periods (median 22.5 months for survivors). On multivariable analysis, high Log GGT was independently associated with adverse OS (HR 1.49, p = 0.006) as were low hemoglobin (HR 0.79, p = 0.002) and high PSA (HR 1.40, p < 0.001). In contrast, serum GGT was not significantly associated with PSA response or PFS. Moreover, incorporation of serum GGT into established prognostic models (i.e., Halabi and Smaletz models) increased their C-indices for predicting OS from 0.772 to 0.787 (p = 0.066) and from 0.777 to 0.785 (p = 0.118), respectively. Furthermore, there was a positive correlation between serum and tissue GGT levels (ρ = 0.53, p = 0.003). Conclusions: Serum GGT may be a prognostic biomarker in men with mCRPC receiving docetaxel therapy. GGT overexpression by prostate cancer cells appears to be responsible for the elevation of GGT in the serum.

Prognostic role of the duration of response to androgen deprivation therapy in patients with metastatic castration resistant prostate cancer treated with enzalutamide or abiraterone acetate

BACKGROUND

Our retrospective study aims to evaluate the prognostic role of duration of response to androgen deprivation therapy (ADT) in metastatic castration resistant prostate cancer (mCRPC) patients treated with enzalutamide (E) or abiraterone acetate (AA).

MATERIALS AND METHODS

Data about ADT start and duration were available in 255 (82%) of 311 patients treated with AA or E. Patients were divided in three groups according to ADT response (group 1 [G1]: <12 months; group 2 [G2]: 12-36 months; group 3 [G3]: >36 months). Outcome measures were progression-free survival (PFS) and overall survival (OS).

RESULTS

Patients with longer ADT response had better OS (median 17.3 months G1, 19.9 months G2, 31.6 months G3; HR G3 vs G1 0.41, 95% CI 0.25-0.64; p = 0.001) and better PFS (median 5.9 months G1, 8.8 months G2, 11.7 months G3; HR G3 vs G1 0.41, 95% CI 0.41-0.27; p < 0001). In docetaxel-naive patients, median OS was 18.8 in G1, 35.2 in G2, and not reached in G3 (HR G3 vs G1 0.33, 95% CI 0.14-0.78; p = 0.038), median PFS was 7 months G1, 9.3 months G2, and 20 months G3 (HR G3 vs G1 0.31, 95% CI 0.15-0.62; p = 0.003). In postdocetaxel patients, median OS was 13.1 months in G1, 17.2 months in G2, and 21.4 months in G3 (HR G3 vs G1 0.52, 95% CI 0.29-0.94; p = 0.082), while median PFS was 5.2 months in G1, 6.8 months in G2, and 8.3 months in G3 (HR G3 vs G1 0.54, 95% CI 0.32-0.91; p = 0.067).

CONCLUSIONS

Duration of ADT response is an independent prognostic factor of outcome with AA or E.

Prognostic Score and Benefit from Abiraterone in First-line Metastatic, Castration-resistant Prostate Cancer

BACKGROUND

Most available prognostic nomograms in metastatic castration-resistant prostate cancer (mCRPC) are derived from datasets not representative of the current treatment landscape. A prognostic nomogram for first-line mCRPC treatment was developed from patients treated in the PREVAIL study.

OBJECTIVE

To validate the Armstrong model in the COU-AA-302 trial.

DESIGN, SETTING, AND PARTICIPANTS

A post hoc analysis of mCRPC patients treated in the COU-AA-302 trial was carried out (NCT00887198).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

The Armstrong prognostic model was applied to patients treated in COU-AA-302. A continuous risk score was derived from coefficients from the original model. Time-dependent area under the curve (tAUC) was used to evaluate the overall predictive ability of the model. Patients were categorized according to the number of risk factors present into those at a low (three or fewer risk factors), intermediate (four to six risk factors), and high (seven to ten risk factors) risk. The association with survival was assessed with Cox regression models. Interaction tests were used to assess the impact of treatment arm in each of the prognostic groups.

RESULTS AND LIMITATIONS

A total of 1088 patients were analyzed. The risk score was associated with overall survival (OS; tAUC 0.733). Most patients were at a low (49%) or intermediate (41%) risk. Risk category was significantly associated with OS (hazard ratio [HR]: 2.3; 95% confidence interval [CI]: 1.9-2.4; p < 0.001), radiographic progression-free survival (rPFS; HR: 1.7; 95% CI: 1.5-1.8; p < 0.001), and prostate-specific antigen progression-free survival (HR: 1.7; 95% CI: 1.5-1.9; p < 0.001). A significant interaction between risk group and OS (p = 0.007) and rPFS (p = 0.009) was observed. Survival was superior in low-risk patients (HR: 0.73; 95% CI: 0.59-0.89; p = 0.009), but similar in intermediate-risk (HR: 0.97; 95% CI: 0.79-1.21; p = 0.9) and high-risk (HR: 1.35; 95% CI: 0.80-2.28; p = 0.5) patients. Two-year OS rates in abiraterone versus placebo were 82% versus 74% in low-risk, 55% versus 52% in intermediate-risk, and 28% versus 31% in high-risk patients.

CONCLUSIONS

We validate the prognostic value of the Armstrong risk model in patients treated with first-line androgen receptor signaling inhibitors. Abiraterone provided a greater benefit in low-risk patients with less aggressive disease. Further research is needed to establish the role of Armstrong risk groups for treatment selection in mCRPC patients.

PATIENT SUMMARY

In this report, we validated the Armstrong nomogram in the COU-AA-302 trial population. We found a similar prognostic performance to that of the original model. Good-risk patients received the greatest benefit from abiraterone.

Clinicopathologic factors that influence prognosis and survival outcomes in men with metastatic castration-resistant prostate cancer treated with Radium-223

Background

In men with metastatic castration‐resistant prostate cancer (mCRPC) with primarily bone metastases, radium‐223 (²²³Ra) improves overall survival (OS). However, the selection of ²²³Ra is not guided by specific validated clinicopathologic factors, and thus outcomes are heterogeneous.

Patients and methods

This retrospective survival analysis was performed in men with mCRPC treated with ²²³Ra at our cancer center. Demographics and disease characteristics were collected. OS was calculated using the Kaplan–Meier method (log‐rank). The potential prognostic factors were determined using both univariable (UVA) and multivariable analysis (MVA) (Cox‐regression) methods.

Results

In total, 150 patients with a median age of 74 years (52–93) received ²²³Ra between May 2015 and July 2018, and 58% had 6–20 bone metastases. Ninety‐four (63%) patients received >4 ²²³Ra doses, and 56 (37%) received ≤4. The following pre‐treatment factors were analyzed (median [range]): eastern cooperative oncology group performance status (ECOG PS), (1 [0–3]); Albumin (ALB), (39 g/L [24–47]); alkaline phosphatase (ALP), (110 U/L [35–1633]); and prostate‐specific antigen (PSA), (49 µg/L [0.83–7238]). The median OS for all patients was 14.5 months (95% CI: 11.2–18). These factors were associated with poor survival outcomes in UVA and MVA: ALB <35 g/L, ALP >150 U/L, ECOG PS 2–3, and PSA >80 µg/L. By assigning one point for each of these factors, a prognostic model was developed, wherein three distinct risk groups were identified: good, 0–1 (n = 103); intermediate, 2 (n = 30); and poor risk, 3–4 points (n = 17). The median OS was 19.4, 10.0, and 3.1 months, respectively (p < 0.001).

Conclusions

Pre‐treatment ALB, ALP, ECOG, and PSA, were significantly correlated with OS and could guide treatment selection for men with mCRPC by identifying those who are most or least likely to benefit from ²²³Ra. Validation in an independent dataset is required prior to widespread clinical utilization.

Impact of Time to Castration Resistance on Survival in Metastatic Hormone Sensitive Prostate Cancer Patients in the Era of Combination Therapies

BACKGROUND

To evaluate the impact of time to castration resistance (TTCR) in metastatic hormone-sensitive prostate cancer (mHSPC) patients on overall survival (OS) in the era of combination therapies for mHSPC.

MATERIAL AND METHODS

Of 213 mHSPC patients diagnosed between 01/2013-12/2020 who subsequently developed metastatic castration resistant prostate cancer (mCRPC), 204 eligible patients were analyzed after having applied exclusion criteria. mHSPC patients were classified into TTCR <12, 12-18, 18-24, and >24 months and analyzed regarding OS. Moreover, further OS analyses were performed after having developed mCRPC status according to TTCR. Logistic regression models predicted the value of TTCR on OS.

RESULTS

Median follow-up was 34 months. Among 204 mHSPC patients, 41.2% harbored TTCR <12 months, 18.1% for 12-18 months, 15.2% for 18-24 months, and 25.5% for >24 months. Median age was 67 years and median PSA at prostate cancer diagnosis was 61 ng/ml. No differences in patient characteristics were observed (all p>0.05). According to OS, TTCR <12 months patients had the worst OS, followed by TTCR 12-18 months, 18-24 months, and >24 months, in that order (p<0.001). After multivariable adjustment, a 4.07-, 3.31-, and 6.40-fold higher mortality was observed for TTCR 18-24 months, 12-18 months, and <12 months patients, relative to TTCR >24 months (all p<0.05). Conversely, OS after development of mCRPC was not influenced by TTCR stratification (all p>0.05).

CONCLUSION

Patients with TTCR <12 months are at the highest OS disadvantage in mHSPC. This OS disadvantage persisted even after multivariable adjustment. Interestingly, TTCR stratified analyses did not influence OS in mCRPC patients.

Whole blood GRHL2 expression as a prognostic biomarker in metastatic hormone-sensitive and castration-resistant prostate cancer

Background

As potent systemic therapies transition earlier in the prostate cancer disease course, molecular biomarkers are needed to guide optimal treatment selection for metastatic hormone-sensitive prostate cancer (mHSPC). The value of whole blood RNA to detect candidate biomarkers in mHSPC remains largely undefined.

Methods

In this cohort study, we used a previously optimised whole blood reverse transcription polymerase chain reaction assay to assess the prognostic utility [measured by seven-month undetectable prostate-specific antigen (PSA) and time to castration-resistance (TTCR)] of eight prostate cancer-associated gene transcripts in 43 mHSPC patients. Transcripts with statistically significant associations (P<0.05) were further investigated in a metastatic castration-resistant prostate cancer (mCRPC) cohort (n=119) receiving contemporary systemic therapy, exploring associations with PSA >50% response (PSA₅₀), progression-free survival (PFS) and overall survival (OS). Clinical outcomes were prospectively collected in a protected digital database. Kaplan-Meier estimates and multivariable Cox proportional-hazards models assessed associations between gene transcripts and clinical outcomes (mHSPC covariates: disease volume, docetaxel use and haemoglobin level; mCRPC covariates: prior exposure to chemotherapy or ARPIs, haemoglobin, performance status and presence of visceral disease). Follow-up was performed monthly during ARPI treatment, three-weekly during taxane chemotherapy, and three-monthly during androgen deprivation therapy (ADT) monotherapy. Serial PSA measurements were performed before each follow-up visit and repeat imaging was at the discretion of the investigator.

Results

Detection of circulating Grainyhead-like 2 (GRHL2) transcript was associated with poor outcomes in mHSPC and mCRPC patients. Detectable GRHL2 expression in mHSPC was associated with a lower rate of seven-month undetectable PSA levels (25% vs. 65%, P=0.059), and independently associated with shorter TTCR (HR 7.3, 95% CI: 1.5–36, P=0.01). In the mCRPC cohort, GRHL2 expression predicted significantly lower PSA₅₀ response rates (46% vs. 69%, P=0.01), and was independently associated with shorter PFS (HR 3.1, 95% CI: 1.8–5.2, P<0.001) and OS (HR 2.9, 95% CI: 1.6–5.1, P<0.001). Associations were most apparent in patients receiving ARPIs.

Conclusions

Detectable circulating GRHL2 was a negative prognostic biomarker in our mHSPC and mCRPC cohorts. These data support further investigation of GRHL2 as a candidate prognostic biomarker in metastatic prostate cancer, in addition to expanding efforts to better understand a putative role in therapeutic resistance to AR targeted therapies.

Prognostic role of platelet-to-lymphocyte ratio and neutrophil-to-lymphocyte ratio in patients with metastatic castration resistant prostate cancer treated with Abiraterone or Enzalutamide

BACKGROUND

Platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) are markers of systemic inflammation associated with poor outcome in several solid tumours. We retrospectively investigated the prognostic role of PLR and, secondly, NLR in mCRPC patients treated with Abiraterone Acetate (AA) or Enzalutamide (E), both in pre- and post-docetaxel setting.

MATERIALS AND METHODS

225 mCRPC patients treated with AA or E with basal blood count were divided in three groups according to PLR (PLR1 <128; PLR2 128-190; PLR >190) and in two groups according to NLR (<3 vs ≥3). Outcome measures were progression-free survival (PFS) and overall-survival (OS). Univariate and multivariate analyses were performed.

RESULTS

110 patients were in PLR1, 58 in PLR2 and 57 in PLR3. Median OS was 22.0, 20.6 and 21.2 months in PLR1, PLR2 and PLR3 (PLR2 vs PLR1: HR 0.97, 95%CI 0.62-1.52, p=0.90; PLR3 vs PLR1: HR 1.37, 95%CI 0.90-2.08, p=0.14). Median PFS was 9.2, 12.7 and 8.5 months in PLR1, PLR2 and PLR3 (PLR2 vs PLR1: HR 0.87, 95%CI 0.59-1.27, p=0.47; PLR3 vs PLR1: HR 1.15, 95%CI 0.80-1.66, p=0.45). 142 patients were in NLR<3 and 83 in NLR≥3. Median OS was 26.5 months in NLR<3 and 17.0 months in NLR≥3 (HR 1.75, 95%CI 1.22-2.51, p=0.02). Median PFS was 10.1 months in NLR<3 and 7.6 months in NLR≥3 (HR 1.37, 95%CI 1.00-1.88, p=0.05).

CONCLUSIONS

In this retrospective analysis of mCRPC patients treated with AA or E we did not identify a prognostic role of baseline PLR, while we found a significant prognostic role of baseline NLR.

Factors predicting biochemical response and survival benefits following radioligand therapy with [177Lu]Lu-PSMA in metastatic castrate-resistant prostate cancer: a review

Background

Prostate cancer (PC) is one of the most common cancers in men. Although the overall prognosis is favorable, the management of metastatic castration-resistant prostate cancer (mCRPC) patients is challenging. Usually, mCRPC patients with progressive disease are considered for radioligand therapy (RLT) after exhaustion of other standard treatments. The prostate-specific membrane antigen (PSMA) labeled with Lutetium-177 ([¹⁷⁷Lu]Lu-PSMA) has been widely used, showing favorable and successful results in reducing prostate-specific antigen (PSA) levels, increasing quality of life, and decreasing pain, in a multitude of studies. Nevertheless, approximately thirty percent of patients do not respond to [¹⁷⁷Lu]Lu-PSMA RLT. Here, we only reviewed and reported the evaluated factors and their impact on survival or biochemical response to treatment to have an overview of the potentialprognostic parameters in [¹⁷⁷Lu]Lu-PSMA RLT.

Methods

Studies were retrieved by searching MEDLINE/PubMed and GoogleScholar. The search keywords were as follows: {(“177Lu-PSMA”) AND (“radioligand”) AND (“prognosis”) OR (“predict”)}. Studies discussing one or more factors which may be prognostic or predictive of response to [¹⁷⁷Lu]Lu-PSMA RLT, that is PSA response and survival parameters, were included.

Results

Several demographic, histological, biochemical, and imaging factors have been assessed as predictive parameters for the response to thistreatment; however, the evaluated factors were diverse, and the results mostly were divergent, except for the PSA level reduction after treatment, which unanimously predicted prolonged survival.

Conclusion

Several studies have investigated a multitude of factors to detect those predicting response to [¹⁷⁷Lu]Lu-PSMA RLT. The results wereinconsistent regarding some factors, and some were evaluated in only a few studies. Future prospective randomized trials are required to detect theindependent prognostic factors, and to further determine the clinical and survival benefits of [¹⁷⁷Lu]Lu-PSMA RLT.

Survival outcomes in patients with chemotherapy-naive metastatic castration-resistant prostate cancer treated with enzalutamide or abiraterone acetate

Objective

Evaluation of the comparative effectiveness of enzalutamide and abiraterone in patients with metastatic castration-resistant prostate cancer (mCRPC) is limited to meta-analyses of randomized trials that exclude patients with significant comorbidities. We evaluated overall survival (OS) in patients with chemotherapy-naive mCRPC treated with enzalutamide or abiraterone acetate (abiraterone) in a real-world single payer setting.

Methods

A retrospective analysis (4/1/2014–3/31/2018) of the Veterans Health Administration (VHA) database was conducted. Patients with mCRPC had ≥1 pharmacy claim for enzalutamide or abiraterone (first claim date = index date) following disease progression on surgical/medical castration, without chemotherapy <12 months prior to index date. Patients had continuous VHA enrollment for ≥12 months pre-index date and were followed until death, disenrollment, or end of study. Kaplan–Meier analysis and multivariable Cox proportional hazards regression models examined the OS treatment effect.

Results

Patients with chemotherapy-naive mCRPC (N = 3174; enzalutamide, n = 1229; abiraterone, n = 1945) had mean ages of 74 and 73 years, respectively. Median follow-up was 18.27 and 19.07 months with enzalutamide and abiraterone, respectively. Enzalutamide-treated patients had longer median treatment duration than abiraterone-treated patients (9.93 vs 8.47 months, respectively, p = 0.0008). After baseline comorbidity adjustment, enzalutamide-treated patients had a 16% reduced risk of death (hazard ratio [HR] = 0.84; 95% CI, 0.76–0.94; p = 0.0012). For patients who remained on first line-therapy only, enzalutamide-treated patients had improved OS versus abiraterone-treated patients (HR = 0.71; 95% CI, 0.62–0.82). Enzalutamide-treated patients who crossed over to abiraterone had a comparable risk of death versus abiraterone-treated patients who crossed over to enzalutamide (HR = 1.10; 95% CI, 0.89–1.35). These results were confirmed by sensitivity analysis, which considered prognostic variables.

Conclusions

Retrospective analysis of the VHA database indicated that chemotherapy-naive patients with mCRPC initiating therapy with enzalutamide had improved survival versus abiraterone.

Clinical value of CTLA4 combined with clinicopathological factors in evaluating the prognosis of breast cancer

Background

Clinical prediction of breast cancer prognosis relies on both clinical-pathological features and biological markers. Many studies have revealed that tumor cytotoxic T lymphocyte antigen 4 (CTLA4) expression may present prognostic predicting value in cancers. We intended to explore the prognostic value of significant clinicopathological parameters and CTLA4 for predicting survival of patients with breast cancer.

Methods

A total of 229 breast cancer patients who had radical surgery treatment between Sep 2009 and April 2011 were enrolled in this study. Immunohistochemical staining was performed to evaluate CTLA4 grade and Ki-67 index in breast cancer tissue. Univariate and multivariate logistic analysis, Kaplan-Meier survival analysis and ROC curve were used to explore the association between CTLA4 or clinicopathological parameters and disease-free survival (DFS). A nomogram was constructed based on the regression model to predict DFS of patients with breast cancer.

Results

CTLA4 grade (OR 1.730, 95% CI: 1.213-2.468, P=0.002), Ki-67 (OR 1.449, 95% CI: 1.069-1.964, P=0.017) and N stage (lymph node metastasis) (OR 2.268, 95% CI: 1.588-3.303, P=0.000) showed significantly association with DFS of breast cancer patients. All these factors were independent predictors for poor survival, as patients with stage N2-3 tumors, high CTLA4 grade and Ki-67 index showed low survival probability (P<0.01). The conjunction of these factors exhibited good discrimination value (AUC 0.815, 95% CI: 0.749-0.882, P=0.000). Nomogram performed based on CTLA4 grade, Ki-67 index and N stage provided an efficient method to predict DFS of patients with breast cancer.

Conclusions

The high expression of CTLA4 and Ki-67 together with lymph node metastasis in breast cancer are independent risk factors that affect the prognosis of breast cancer patients. They have the potentiality to be utilized conjunctively as predictor in clinical practice.

HLA Class I Allele Expression and Clinical Outcome in De Novo Metastatic Prostate Cancer

The prognostic value of human leukocyte antigen (HLA) class I molecules in prostate cancer (PCa) remains unclear. Herein, we investigated the prognostic relevance of the most frequently expressed HLA-A alleles in Greece (A*02:01 and HLA-A*24:02) in de novo metastatic hormone-sensitive PCa (mPCa), which is a rare and aggressive disease characterized by a rapid progression to castration-resistance (CR) and poor overall survival (OS), contributing to almost 50% of PCa-related deaths. We identified 56 patients who had either progressed to CR (these patients were retrospectively analyzed for the time to the progression of CR and prospectively for OS) or had at least three months’ follow-up postdiagnosis without CR progression and, thus, were prospectively analyzed for both CR and OS. Patients expressing HLA-A*02:01 showed poor clinical outcomes vs. HLA-A*02:01⁻negative patients. HLA-A*24:02⁻positive patients progressed slower to CR and had increased OS. Homozygous HLA-A*02:01 patients progressed severely to CR, with very short OS. Multivariate analyses ascribed to both HLA alleles significant prognostic values for the time to progression (TTP) to CR and OS. The presence of HLA-A*02:01 and HLA-A*24:02 alleles in de novo mPCa patients are significantly and independently associated with unfavorable or favorable clinical outcomes, respectively, suggesting their possible prognostic relevance for treatment decision-making in the context of precision medicine.

Prognostic role of early PSA drop in castration resistant prostate cancer patients treated with abiraterone acetate or enzalutamide

BACKGROUND

Previous studies demonstrated a predictive value of prostate-specific antigen (PSA) kinetics for treatment outcome. Our retrospective study evaluates the prognostic role of early PSA drop in metastatic castration resistant prostate cancer (mCRPC) patients receiving abiraterone acetate (AA) or enzalutamide (E).

METHODS

All mCRPC patients treated with AA or E at the San Luigi Hospital in Orbassano between 2010 and 2018 and at the Ordine Mauriziano Hospital in Turin between 2014 and 2018 were included in this retrospective study. Only patients with an early PSA (measured 28-60 days after the beginning of the treatment) were included in the analysis. Patients were divided in early responders and non-early responders according to early PSA response (drop≥50% from baseline). Univariate and multivariate analyses for progression free survival (PFS) and overall survival (OS) were performed.

RESULTS

Of 144 patients with early PSA value, 61 (42.4%) patients received E (docetaxel-naïve 42, post-docetaxel 19) and 83 (57.6%) received AA (docetaxel-naïve 44, post-docetaxel 39). Seventy-five (52.1%) patients achieved early PSA drop. In docetaxel-naïve setting (N.=86), median PFS was 14.9 (with early PSA drop) vs. 8.8 months (without early PSA drop, P=0.001). In post-docetaxel setting (N.=58) median PFS was 11.9 vs. 4.5 months (P<0.001). Globally, median PFS was 14.9 vs. 6.3 months in patients with and without early PSA drop, respectively (P<0.001). In docetaxel-naïve setting, patients with early PSA drop had a median OS of 39.5 vs. 18.8 months (P=0.12). In post-docetaxel setting median OS was 29.6 vs. 10.7 months (P=0.01). Comprehensively, median OS was 31.9 vs. 16.3 (P=0.002) in patients with and without early PSA drop, respectively. At multivariate analysis, early PSA drop confirmed an independent association with PFS (HR 0.21; 95% CI: 0.12-0.38, P<0.001) and OS (HR 0.25; 95% CI: 0.12-0.50, P<0.001).

CONCLUSIONS

mCRPC patients treated with AA or E, in docetaxel-naïve or post-docetaxel setting, with early PSA drop had significantly better OS and PFS.

Using medical claims database to develop a population disease progression model for leuprorelin-treated subjects with hormone-sensitive prostate cancer

Androgen deprivation therapy (ADT) is a widely used treatment for patients with hormone-sensitive prostate cancer (PCa). However, duration of treatment response varies, and most patients eventually experience disease progression despite treatment. Leuprorelin is a luteinizing hormone-releasing hormone (LHRH) agonist, a commonly used form of ADT. Prostate-specific antigen (PSA) is a biomarker for monitoring disease progression and predicting treatment response and survival in PCa. However, time-dependent profile of tumor regression and growth in patients with hormone-sensitive PCa on ADT has never been fully characterized. In this analysis, nationwide medical claims database provided by Humana from 2007 to 2011 was used to construct a population-based disease progression model for patients with hormone-sensitive PCa on leuprorelin. Data were analyzed by nonlinear mixed effects modeling utilizing Monte Carlo Parametric Expectation Maximization (MCPEM) method in NONMEM. Covariate selection was performed using a modified Wald’s approximation method with backward elimination (WAM-BE) proposed by our group. 1113 PSA observations from 264 subjects with malignant PCa were used for model development. PSA kinetics were well described by the final covariate model. Model parameters were well estimated, but large between-patient variability was observed. Hemoglobin significantly affected proportion of drug-resistant cells in the original tumor, while baseline PSA and antiandrogen use significantly affected treatment effect on drug-sensitive PCa cells (Ds). Population estimate of Ds was 3.78 x 10⁻² day^-1. Population estimates of growth rates for drug-sensitive (Gs) and drug-resistant PCa cells (G_R) were 1.96 x 10⁻³ and 6.54 x 10⁻⁴ day^-1, corresponding to a PSA doubling time of 354 and 1060 days, respectively. Proportion of the original PCa cells inherently resistant to treatment was estimated to be 1.94%. Application of population-based disease progression model to clinical data allowed characterization of tumor resistant patterns and growth/regression rates that enhances our understanding of how PCa responds to ADT.

Development and Internal Validation of a Web-based Tool to Predict Sexual, Urinary, and Bowel Function Longitudinally After Radiation Therapy, Surgery, or Observation

BACKGROUND

Shared decision making to guide treatment of localized prostate cancer requires delivery of the anticipated quality of life (QOL) outcomes of contemporary treatment options (including radical prostatectomy [RP], intensity-modulated radiation therapy [RT], and active surveillance [AS]). Predicting these QOL outcomes based on personalized features is necessary.

OBJECTIVE

To create an easy-to-use tool to predict personalized sexual, urinary, bowel, and hormonal function outcomes after RP, RT, and AS.

DESIGN, SETTING, AND PARTICIPANTS

A prospective, population-based cohort study was conducted utilizing US cancer registries of 2563 men diagnosed with localized prostate cancer in 2011-2012.

INTERVENTION

Patient-reported urinary, sexual, and bowel function up to 5 yr after treatment.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient-reported urinary, sexual, bowel, and hormonal function through 5 yr after treatment were collected using the 26-item Expanded Prostate Index Composite (EPIC-26) questionnaire. Comprehensive models to predict domain scores were fit, which included age, race, D'Amico classification, body mass index, EPIC-26 baseline function, treatment, and standardized scores measuring comorbidity, general QOL, and psychosocial health. We reduced these models by removing the instrument scores and replacing D'Amico classification with prostate-specific antigen (PSA) and Gleason score. For the final model, we performed bootstrap internal validation to assess model calibration from which an easy-to-use web-based tool was developed.

RESULTS AND LIMITATIONS

The prediction models achieved bias-corrected R-squared values of 0.386, 0.232, 0.183, 0.214, and 0.309 for sexual function, urinary incontinence, urinary irritative, bowel, and hormonal domains, respectively. Differences in R-squared values between the comprehensive and parsimonious models were small in magnitude. Calibration was excellent. The web-based tool is available at https://statez.shinyapps.io/PCDSPred/.

CONCLUSIONS

Functional outcomes after treatment for localized prostate cancer can be predicted at the time of diagnosis based on age, race, PSA, biopsy grade, baseline function, and a general question regarding overall health. Providers and patients can use this prediction tool to inform shared decision making.

PATIENT SUMMARY

In this report, we studied patient-reported sexual, urinary, hormonal, and bowel function through 5 yr after treatment with radical prostatectomy, radiation therapy, or active surveillance for localized prostate cancer. We developed a web-based predictive tool that can be used to predict one's outcomes after treatment based on age, race, prostate-specific antigen, biopsy grade, pretreatment baseline function, and a general question regarding overall health. We hope both patients and providers can use this tool to better understand expected outcomes after treatment, further enhancing shared decision making between providers and patients.

Age, Gleason Score, and PSA are important prognostic factors for survival in metastatic castration-resistant prostate cancer. Results of The Uroncor Group (Uro-Oncological Tumors) of the Spanish Society of Radiation Oncology (SEOR)

INTRODUCTION

The treatment of metastatic castration-resistant prostate cancer (mCRPC) has changed significantly in recent years. Inhibitors of androgen receptors have shown especially significant benefits in overall (OS) and progression-free survival (PFS), with a good toxicity profile. Treatment selection depends on the patient's individual clinical, radiological, and biological characteristics.

OBJECTIVE

To describe treatment outcomes (efficacy, toxicity) in a cohort of patients with mCRPC in Spain.

MATERIALS AND METHODS

Multicenter, retrospective study of patients with mCRPC included in a database of the Urological Tumour Working Group (URONCOR) of the Spanish Society of Radiation Oncology (SEOR). Metastatic CRPC was defined according to the prostate cancer working group 3 (PCWG3) criteria. The Kaplan-Meier technique was used to evaluate OS and the Common Terminology Criteria for Adverse Events (CTCAE, v.4.0) were used to assess toxicity. Univariate and multivariate Cox regression analyses were performed to identify the factors significantly associated with OS.

RESULTS

A total of 314 patients from 17 hospitals in Spain diagnosed with mCRPC between June 2010 and September 2017 were included in this study. Mean age at diagnosis was 68 years (range 45-89). At a median follow-up of 35 months, OS at 1, 3, and 5 years were 92%, 38%, and 28%, respectively. Grades 1-2 and grade 3 toxicity rates were, respectively, 68% and 19%. No grade 4 toxicities were observed. On the multivariate analysis, the following factors were significantly associated with OS: age (hazard ratio [HR] 0.42, p = 0.010), PSA value at diagnosis of mCRPC (HR 0.55, p = 0.008), and Gleason score (HR 0.61, p = 0.009).

CONCLUSIONS

Age, Gleason score, and PSA at diagnosis of mCRPC are independently associated with overall survival in patients with mCRPC. The efficacy and toxicity outcomes in this patient cohort treated in radiation oncology departments in Spain are consistent with previous reports.

Development of a prognostic model for survival time prediction in castration-resistant prostate cancer patients

BACKGROUND

To identify predictors of survival in patients treated with docetaxel chemotherapy for castration-resistant prostate cancer (CRPC).

METHODS

We retrospectively analyzed clinical data from 186 patients who underwent docetaxel chemotherapy for CRPC from 2005 to 2016 at a single center. Pretreatment baseline variables including demographic and clinicopathological data were reviewed. Disease progression was defined by imaging and/or consecutive prostate-specific antigen (PSA) elevation. The systemic immune-inflammation index (SII), the modified Glasgow Prognostic Score (mGPS), and the neutrophil-lymphocyte ratio (NLR) were calculated. Univariable and multivariable Cox proportional hazards regression analyses reporting hazard ratios assessed the risk for disease progression and overall survival (OS). A survival nomogram was constructed.

RESULTS

Most patients (n = 139, 74.7%) completed at least 6 cycles of docetaxel chemotherapy. 156 patients (82.9%) experienced disease progression during the studied period. Only mGPS was independently associated with disease progression in a multivariable model (P < 0.01). During the studied period, 98 patients (52.1%) died. The built survival nomogram included statistically significant variables for OS in univariable analysis: hemoglobin, PSA, alkaline phosphatase (AP), lactate dehydrogenase, SII, neutrophil-lymphocyte ratio, mGPS, and site of metastases; and had a concordance index of 0.703. At decision curve analysis, the nomogram led to superior outcomes for any decision associated with a threshold probability of above 40%. In multivariable analysis, only AP (P = 0.02), hemoglobin and PSA (P < 0.01, respectively) remained associated with OS.

CONCLUSIONS

PSA, AP, and hemoglobin are independent prognosticators for OS. Although mGPS is a promising marker for tumor progression and SII is a plausible prognostic marker for OS, valid integration of inflammatory indices into a prognostic model requires validation studies. Predictive and prognostic biomarkers are desperately needed to guide physicians in treatment counseling given the heterogeneous nature of CRPC and the plethora of effective therapies.

The value of tumor markers in men with metastatic prostate cancer undergoing [177 Lu]Lu-PSMA therapy

BACKGROUND

Currently, prostate-specific membrane antigen-radioligand therapy (PSMA-RLT) is considered a last-line treatment option in advanced castration-resistant prostate cancer. Despite these patients' poor prognosis, accurate estimation of their overall survival (OS) is essential to determine whether benefits exist from the treatment and whether the loss of valuable time and unnecessary side effects can be avoided. The aim of the present study is to evaluate whether various biochemical markers can predict OS in men undergoing PSMA-RLT and whether the changes assessed after PSMA-RLT correlate with the OS.

METHODS

The tested tumor markers in this retrospective analysis were alkaline phosphatase (ALP), bone-specific alkaline phosphatase (BAP), prostate-specific antigen (PSA), lactate dehydrogenase (LDH), chromogranin A, and pro-gastrin-releasing peptide (pro-GRP). For the evaluation, we performed blood tests before each PSMA-RLT cycle and during follow-up visits (which were 2-3 months apart). All patients were followed up until their deaths. To test the correlations between the tumor markers and survival, we conducted the logrank tests and the multivariate Cox proportional-hazards regression model. The significance level was set at P < .05.

RESULTS

The study included 137 patients who received a total of 487 PSMA-RLT cycles between January 2015 and November 2017. Of the tested biochemical tumor markers, baseline ALP (120 U/L cut-off), LDH (248 U/L cut-off), and PSA (first quartile cut-off) correlated significantly with survival post-PSMA-RLT (P < .001 for ALP and LDH, and P = .007 for PSA). Stable and/or decreased values in most of the initially abnormal parameters were associated with significantly better OS; these parameters were ALP (P = .009), LDH (P = .005), PSA (P < .001), and pro-GRP (P = .013). The BAP and ALP responses also correlated significantly with survival in patients with bone metastases (P = .002 and P < .001, respectively). Furthermore, there was a strong correlation of the kinetic patterns of PSA, ALP, BAP, and LDH with the survival, showing that patients with steadily increasing markers had the shortest OS.

CONCLUSION

Along with the established tumor marker PSA, ALP, LDH, BAP, and pro-GRP were correlated with the OS post-PSMA-RLT in the univariate and multivariate analyses.

Circulating tumor cells and γH2AX as biomarkers for responsiveness to radium-223 in advanced prostate cancer patients

Aim

Radium-223 improves overall survival in patients with metastatic castration-resistant prostate cancer to the bone. Radium-223 causes double-strand DNA breaks and produces γH2AX, a potential biomarker for response. We examined the feasibility of tracking γH2AX positivity and numeration in circulating tumor cells.

Patients & methods

Ten patients with biopsy-confirmed symptomatic M1b castration-resistant prostate cancer received radium-223 as standard of care and were assessed for γH2AX level changes following doses 1, 3 and 6.

Results

Trend tests confirmed that patients with ≥50% increase in circulating tumor cells positive for γH2AX postradium-223 therapy had a lower risk of death (p = 0.035).

Conclusion

Regular interval measurements of γH2AX are feasible. The potential correlation between γH2AX changes and overall survival warrants further investigation.

Factors related to early castration resistance in metastatic prostate cancer. Results from the National Prostate Cancer Registry in Spain

INTRODUCTION

The objective of the study was to determine the factors independently related with the development of castration resistance (CR) in prostate cancer (PC) in the medium term.

MATERIAL AND METHODS

155 patients diagnosed with metastatic PC with a follow-up of up to 39 months. Data taken from the National PC Registry. The evaluated variables were age, PSA, nadir PSA, Gleason, perineural invasion, TNM stages, and ADT type (intermittent/continuous).

RESULTS

Mean follow-up 26,2±13,4 months. 47.1% developed early CR, with mean time until onset of 12,2±8,7 months. Univariate analysis the mean PSA was correlated with CR (290±905,1 ng/mL in non CR, 519,1±1437,2 ng/mL in CR, P<.001), mean age (73,3±8,3 years in non CR, 69,1±9,3 in CR P=.01), mean PSA nadir (15,5±57,3ng/mL in non CR, 15,9±23,7 ng/mL in CR, p<0,001), Gleason (in ≥8, HR:2,11. 95% CI: 1.22-3.65, p=0.006), and T stage (in T3-T4, HR: 2.85. 95% CI: 1.57-5.19, P<.001). Multivariate analysis the independent variables associated to CR are age (HR: 0.96. 95% CI: 0.94-0.99, P=.01), PSA nadir (HR: 1.65. 95% CI: 1,43-1,91, P<.001), and T3-T4 stage (HR: 2.11. 95% CI: 1.10-4.04, P=.02).

CONCLUSIONS

PSA nadir and T3-T4 tumor stage at diagnosis are associated to an increased risk of developing CR. In addition, age at diagnosis is shown as a variable that decreases risk. Therefore, an older age would be associated with lower risk probability of CR in the medium term.

Cost-effective survival prediction for patients with advanced prostate cancer using clinical trial and real-world hospital registry datasets

INTRODUCTION

Predictive survival modeling offers systematic tools for clinical decision-making and individualized tailoring of treatment strategies to improve patient outcomes while reducing overall healthcare costs. In 2015, a number of machine learning and statistical models were benchmarked in the DREAM 9.5 Prostate Cancer Challenge, based on open clinical trial data for metastatic castration resistant prostate cancer (mCRPC). However, applying these models into clinical practice poses a practical challenge due to the inclusion of a large number of model variables, some of which are not routinely monitored or are expensive to measure.

OBJECTIVES

To develop cost-specified variable selection algorithms for constructing cost-effective prognostic models of overall survival that still preserve sufficient model performance for clinical decision making.

METHODS

Penalized Cox regression models were used for the survival prediction. For the variable selection, we implemented two algorithms: (i) LASSO regularization approach; and (ii) a greedy cost-specified variable selection algorithm. The models were compared in three cohorts of mCRPC patients from randomized clinical trials (RCT), as well as in a real-world cohort (RWC) of advanced prostate cancer patients treated at the Turku University Hospital. Hospital laboratory expenses were utilized as a reference for computing the costs of introducing new variables into the models.

RESULTS

Compared to measuring the full set of clinical variables, economic costs could be reduced by half without a significant loss of model performance. The greedy algorithm outperformed the LASSO-based variable selection with the lowest tested budgets. The overall top performance was higher with the LASSO algorithm.

CONCLUSION

The cost-specified variable selection offers significant budget optimization capability for the real-world survival prediction without compromising the predictive power of the model.

Applied Informatics Decision Support Tool for Mortality Predictions in Patients With Cancer

PURPOSE

With rapidly evolving treatment options in cancer, the complexity in the clinical decision-making process for oncologists represents a growing challenge magnified by oncologists' disposition of intuition-based assessment of treatment risks and overall mortality. Given the unmet need for accurate prognostication with meaningful clinical rationale, we developed a highly interpretable prediction tool to identify patients with high mortality risk before the start of treatment regimens.

METHODS

We obtained electronic health record data between 2004 and 2014 from a large national cancer center and extracted 401 predictors, including demographics, diagnosis, gene mutations, treatment history, comorbidities, resource utilization, vital signs, and laboratory test results. We built an actionable tool using novel developments in modern machine learning to predict 60-, 90- and 180-day mortality from the start of an anticancer regimen. The model was validated in unseen data against benchmark models.

RESULTS

We identified 23,983 patients who initiated 46,646 anticancer treatment lines, with a median survival of 514 days. Our proposed prediction models achieved significantly higher estimation quality in unseen data (area under the curve, 0.83 to 0.86) compared with benchmark models. We identified key predictors of mortality, such as change in weight and albumin levels. The results are presented in an interactive and interpretable tool ( www.oncomortality.com ).

CONCLUSION

Our fully transparent prediction model was able to distinguish with high precision between highest- and lowest-risk patients. Given the rich data available in electronic health records and advances in machine learning methods, this tool can have significant implications for value-based shared decision making at the point of care and personalized goals-of-care management to catalyze practice reforms.

A prognostic score for overall survival in patients treated with abiraterone in the pre- and post-chemotherapy setting

Background: Therapy resistance remains a serious dilemma in metastatic castration-resistant prostate cancer (mCRPC) with primary or secondary resistance frequently occurring against any given therapy. Available prognostic models for Abiraterone Acetate (AA) are specifically designed for either pre- or post-chemotherapy settings and mostly based on trial datasets not necessarily reflecting real-life.

Results: A score of 0–2 (low-risk) is associated with an OS-probability of 80.0% (95%CI: 71.3–90.6) and 50.5% (95%CI: 38.7–66.0) after 1 and 2 years while a score of 3–4 (high risk) is associated with an OS-probability of 35.3% (95%CI: 22.3–55.8) and 5.7% (95%CI: 1.5–21.8), respectively. The bootstrapping survival analysis of the scoring-system revealed a median c-index of 0.80 (IQR: 0.79–0.82).

Material and Methods: We developed a scoring-system using four real-life parameters 117 mCRPC patients treated with AA either pre- or post-chemotherapy. These parameters were evaluated using COX regression analysis. The scoring-system consists of binary-categorized parameters; when any of these exceeds the given cut-off, one point is added up to a final score ranging between 0–4 points. The final score was stratified by a median threshold of 2 into low- and high-risk groups. We evaluated the discriminative ability of our scoring-system using concordance probability (C-index) and Kaplan–Meier-analysis and applied a 100-times bootstrap for survival analysis.

Conclusions: Our study introduces a novel prognostic scoring-system for OS of real-life mCRPC patients receiving AA treatment irrespective of the line of therapy. The scoring-system is simple and can be easily utilized based on PSA and LDH values, neutrophil to lymphocyte ratio, and ECOG performance status.

A DREAM Challenge to Build Prediction Models for Short-Term Discontinuation of Docetaxel in Metastatic Castration-Resistant Prostate Cancer

Purpose

Docetaxel has a demonstrated survival benefit for patients with metastatic castration-resistant prostate cancer (mCRPC); however, 10% to 20% of patients discontinue docetaxel prematurely because of toxicity-induced adverse events, and the management of risk factors for toxicity remains a challenge.

Patients and Methods

The comparator arms of four phase III clinical trials in first-line mCRPC were collected, annotated, and compiled, with a total of 2,070 patients. Early discontinuation was defined as treatment stoppage within 3 months as a result of adverse treatment effects; 10% of patients discontinued treatment. We designed an open-data, crowd-sourced DREAM Challenge for developing models with which to predict early discontinuation of docetaxel treatment. Clinical features for all four trials and outcomes for three of the four trials were made publicly available, with the outcomes of the fourth trial held back for unbiased model evaluation. Challenge participants from around the world trained models and submitted their predictions. Area under the precision-recall curve was the primary metric used for performance assessment.

Results

In total, 34 separate teams submitted predictions. Seven models with statistically similar area under precision-recall curves (Bayes factor ≤ 3) outperformed all other models. A postchallenge analysis of risk prediction using these seven models revealed three patient subgroups: high risk, low risk, or discordant risk. Early discontinuation events were two times higher in the high-risk subgroup compared with the low-risk subgroup. Simulation studies demonstrated that use of patient discontinuation prediction models could reduce patient enrollment in clinical trials without the loss of statistical power.

Conclusion

This work represents a successful collaboration between 34 international teams that leveraged open clinical trial data. Our results demonstrate that routinely collected clinical features can be used to identify patients with mCRPC who are likely to discontinue treatment because of adverse events and establishes a robust benchmark with implications for clinical trial design.

PSA time to nadir as a prognostic factor of first-line docetaxel treatment in castration-resistant prostate cancer: evidence from patients in Northwestern China

Docetaxel-based chemotherapy remains the first-line treatment for patients with metastatic castration-resistant prostate cancer (mCRPC) in China; however, the prognostic factors associated with effects in these patients are still controversial. In this study, we retrospectively reviewed the data from 71 eligible Chinese patients who received docetaxel chemotherapy from 2009 to 2016 in our hospital and experienced a reduction of prostate-specific antigen (PSA) level ≥50% during the treatment and investigated the potential role of time to nadir (TTN) of PSA. TTN was defined as the time from start of chemotherapy to the nadir of PSA level during the treatment. Multivariable Cox regression models and Kaplan–Meier analysis were used to predict overall survival (OS). In these patients, the median of TTN was 17 weeks. Patients with TTN ≥17 weeks had a longer response time to chemotherapy compared to TTN <17 weeks (42.83 vs 21.50 weeks, P < 0.001). The time to PSA progression in patients with TTN ≥17 weeks was 11.44 weeks compared to 5.63 weeks when TTN was <17 weeks. We found several factors to be associated with OS, including TTN (hazard ratio [HR]: 3.937, 95% confidence interval [CI]: 1.502–10.309, P = 0.005), PSA level at the diagnosis of cancer (HR: 4.337, 95% CI: 1.616–11.645, P = 0.004), duration of initial androgen deprivation therapy (HR: 2.982, 95% CI: 1.104–8.045, P = 0.031), neutrophil-to-lymphocyte ratio (HR: 3.963, 95% CI: 1.380–11.384, P = 0.011), and total PSA response (Class 1 [<0 response] compared to Class 2 [0–50% response], HR: 3.978, 95% CI: 1.278–12.387, P = 0.017). In conclusion, TTN of PSA remains an important prognostic marker in predicting therapeutic outcome in Chinese population who receive chemotherapy for mCRPC and have >50% PSA remission.

External validation and newly development of a nomogram to predict overall survival of abiraterone-treated, castration-resistant patients with metastatic prostate cancer

Abiraterone acetate is approved for the treatment of castration-resistant prostate cancer (CRPC); however, its effects vary. An accurate prediction model to identify patient groups that will benefit from abiraterone treatment is therefore urgently required. The Chi model exhibits a good profile for risk classification, although its utility for the chemotherapy-naive group is unclear. This study aimed to externally validate the Chi model and develop a new nomogram to predict overall survival (OS). We retrospectively analyzed a cohort of 110 patients. Patients were distributed among good-, intermediate-, and poor-risk groups, according to the Chi model. The good-, intermediate-, and poor-risk groups had a sample size of 59 (53.6%), 34 (30.9%), and 17 (15.5%) in our dataset, and a median OS of 48.4, 29.1, and 10.5 months, respectively. The C-index of external validation of Chi model was 0.726. Univariate and multivariate analyses identified low hemoglobin concentrations (<110 g l⁻¹), liver metastasis, and a short time interval from androgen deprivation therapy to abiraterone initiation (<36 months) as predictors of OS. Accordingly, a new nomogram was developed with a C-index equal to 0.757 (95% CI, 0.678–0.836). In conclusion, the Chi model predicted the prognosis of abiraterone-treated, chemotherapy-naive patients with mCRPC, and we developed a new nomogram to predict the overall survival of this group of patients with less parameters.

Relationship between serum markers and volume of liver metastases in castration-resistant prostate cancer

BACKGROUND

Prostate cancer patients with liver metastases have a poor prognosis. To date, no study exists investigating the relationship between liver tumor burden and clinical laboratory markers.

MATERIALS AND METHODS

Metastatic castrate-resistant prostate cancer (mCRPC) patients with radiographic evidence of liver metastases were selected for this study. Volumetric measurements of liver metastases were ascertained for all available patients. Prostate specific antigen (PSA), lactate dehydrogenase (LDH), alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), albumin (ALB), total bilirubin and hemoglobin (HGB) levels were then assessed to coincide with the scan dates. Univariate and multivariate mixed-model regression analysis were performed to evaluate the relationship between laboratory markers and liver lesion volume. Data sets with non-normal distribution were logarithmically transformed. Akaike information criteria (AIC) was used to identify the most reliable multivariate model.

RESULTS

In our heavily pretreated liver-metastatic patient population, univariate analysis demonstrated a statistically significant positive correlation between PSA (p = 0.0002), ALP (p = 0.0305), AST (p < 0.0001), ALT (p = 0.0049), and LDH (p = 0.0019) and liver lesion volume. Additionally, ALB (p = 0.0006) and HGB (p = 0.0103) had statistically significant negative correlation. Multivariate analysis identified AST and hemoglobin assessments as the best predictors of increasing liver lesion burden. Preliminary data on circulating tumor DNA (ctDNA) mutational and amplification findings are also reported.

CONCLUSIONS

Analysis identified AST and hemoglobin as optimal predictors of liver lesion volume. These patients have a heavy burden of ctDNA abnormalities. Further studies with a larger patient population are needed to verify these results. Micro Abstract: This study investigates the association between liver lesion burden and clinical laboratory markers in castrate-resistant prostate cancer patients with hepatic metastases. Our univariate analysis identified multiple laboratory markers as significant indicators of worsening hepatic disease. Multivariate analysis demonstrated that AST and hemoglobin were the most effective predictors of change in liver lesion volume.

Three-year follow-up of a phase II study of radium-223 dichloride in Japanese patients with symptomatic castration-resistant prostate cancer and bone metastases

BACKGROUND

Radium-223 is a first-in-class targeted alpha therapy to prolong overall survival (OS) in castration-resistant prostate cancer with bone metastases (mCRPC). The aim of the present analysis was to assess the long-term safety with radium-223 in Japanese patients with mCRPC.

METHODS

Patients with symptomatic mCRPC, ≥ 2 bone metastases and no known visceral metastases received up to 6 injections of radium-223 (55 kBq/kg), one every 4 weeks. Adverse events (AEs) considered to be related to radium-223 were reported until 3 years after the first injection. Pre-specified conditions, such as acute myelogenous leukemia, myelodysplastic syndrome, aplastic anemia, primary bone cancer, or other primary malignancies, were reported regardless of causality.

RESULTS

Of the 49 patients enrolled in the study, 44 (89.8%) entered the survival follow-up period and 33 (67.3%) died. Throughout the entire study, there were no reports of second primary malignancy or other pre-specified conditions. Eight patients (16.3%) experienced post-treatment drug-related AEs, which were all hematological (anemia and decreased lymphocyte, platelet, and white blood cell counts). No serious post-treatment drug-related AEs were reported. Updated median OS was 19.3 months (95% CI: 14.2, 28.5).

CONCLUSIONS

In Japanese patients with symptomatic mCRPC and bone metastases, radium-223 had a favorable long-term safety profile with no second primary malignancies reported. Taken together with median OS, which was comparable to that in the pivotal phase III ALSYMPCA study, these results support continued benefit from radium-223 in Japanese patients with mCRPC.

Association of genetic variation of the six gene prognostic model for castration-resistant prostate cancer with survival

BACKGROUND

We previously identified a blood RNA transcript-based model consisting of six immune or inflammatory response genes (ABL2, SEMA4D, ITGAL, C1QA, TIMP1, and CDKN1A) that was prognostic for survival in cohorts of men with castration-resistant prostate cancer (CRPC). We investigated whether inherited variation in these six genes was associated with overall survival (OS) in men with CRPC.

METHODS

The test cohort comprised 600 patients diagnosed with CRPC between 1996 and 2011 at Dana-Farber Cancer Institute. Genotyping of 66 tagging single nucleotide polymorphisms (SNPs) spanning the six genes was performed on blood derived DNAs. For the top four SNPs (P < 0.05), validation was conducted in an independent cohort of 223 men diagnosed with CRPC between 2000 and 2014. Multivariable Cox regression adjusting for known prognostic factors estimated hazard ratios (HR) and 95% confidence intervals (CI) of the association of genetic variants with OS.

RESULTS

Two thirds of patients in both cohorts had metastases at CRPC diagnosis. Median OS from CRPC diagnosis was 3.6 (95%CI 3.3-4.0) years in the test cohort and 4.6 (95%CI 3.8-5.2) years in the validation cohort. Fifty-nine SNPs in Hardy-Weinberg equilibrium were analyzed. The major alleles of rs1318056 and rs1490311 in ABL2, and the minor alleles of rs2073917 and rs3764322 in ITGAL were associated with increased risk of death in the test cohort (adjusted-HRs 1.27-1.39; adjusted-p <0.05; false discovery rate <0.35). In the validation cohort, a similar association with OS was observed for rs1318056 in ABL2 (adjusted-HR 1.44; 95%CI 0.89-2.34) and rs2073917 in ITGAL (adjusted-HR 1.41; 95%CI 0.82-2.42). The associations did not reach statistical significance most likely due to the small sample size of the validation cohort (adjusted-p = 0.142 and 0.209, respectively). Additional eQTL analysis indicated that minor alleles of rs1318056 and rs1490311 in ABL2 are associated with a lower ABL2 expression in blood.

CONCLUSIONS

These findings corroborate our initial work on the RNA expression of genes involved in immunity and inflammation from blood and clinical outcome and suggest that germline polymorphisms in ABL2 and ITGAL may be associated with the risk of death in men with CRPC. Further studies are needed to validate these findings and to explore their functional mechanisms.

Prognostic models for predicting overall survival in metastatic castration-resistant prostate cancer: a systematic review

PURPOSE

Prognostic models are developed to estimate the probability of the occurrence of future outcomes incorporating multiple variables. We aimed to identify and summarize existing multivariable prognostic models developed for predicting overall survival in patients with metastatic castration-resistant prostate cancer (mCRPC).

METHODS

The protocol was prospectively registered (CRD42017064448). We systematically searched Medline and reference lists up to May 2018 and included experimental and observational studies, which developed and/or internally validated prognostic models for mCRPC patients and were further externally validated or updated. The outcome of interest was overall survival. Two authors independently performed literature screening and quality assessment.

RESULTS

We included 12 studies that developed models including 8750 patients aged 42-95 years. Models included 4-11 predictor variables, mostly hemoglobin, baseline PSA, alkaline phosphatase, performance status, and lactate dehydrogenase. Very few incorporated Gleason score. Two models included predictors related to docetaxel and mitoxantrone treatments. Model performance after internal validation showed similar discrimination power ranging from 0.62 to 0.73. Overall survival models were mainly constructed as nomograms or risk groups/score. Two models obtained an overall judgment of low risk of bias.

CONCLUSIONS

Most models were not suitable for clinical use due to methodological shortcomings and lack of external validation. Further external validation and/or model updating is required to increase prognostic accuracy and clinical applicability prior to their incorporation in clinical practice as a useful tool in patient management.

Development and Validation of a Novel Prognostic Model for Predicting Overall Survival in Treatment-naïve Castration-sensitive Metastatic Prostate Cancer

BACKGROUND

There has been growth in the treatment options for castration-sensitive metastatic prostate cancer (mPCa), but without clear guidance for risk stratification.

OBJECTIVE

To identify clinical parameters associated with overall survival (OS) and establish a prognostic model for use with treatment-naïve castration-sensitive mPCa.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective review of 304 patients treated at Kyoto University Hospital was performed. A prognostic model was created using clinical parameters associated with OS. The model was externally validated in an independent cohort of 520 patients.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Multivariable analysis was performed to identify the clinical parameters associated with OS. Risk scores were calculated using Cox proportional hazards analysis for each combination of risk factors, and patients were grouped into categories based on those scores.

RESULTS AND LIMITATIONS

Over 80% of the cohort had a Gleason sum score ≥8. The median OS was 53mo among patients with CHAARTED high-volume PCa (n=172) and 131mo among those with low-volume PCa (n=100). Independent factors associated with OS were extent of disease score ≥2 or the presence of liver metastasis; lactate dehydrogenase >250U/L; and a primary Gleason score of 5. The median OS for the high-, intermediate-, and low-risk groups according to the new model were 28mo, 59mo, and not reached, respectively; the corresponding values in the validation cohort were 41mo, 63mo, and not reached. Harrell's C-index was 0.649.

CONCLUSIONS

Our simple and reproducible prognostic model for treatment-naïve castration-sensitive mPCa could aid in risk stratification and treatment selection.

PATIENT SUMMARY

We identified clinical parameters associated with prognosis in castration-sensitive metastatic prostate cancer and established a reproducible prognostic model that could be used to guide treatment decisions.

De novo metastatic castration sensitive prostate cancer: State of art and future perspectives

De novo metastatic castration sensitive prostate cancer (mCSPC) accounts for about 4% of all prostate tumors in Western Countries. This condition has a heterogeneous biological e clinical behavior, ranging from indolent to aggressive and rapidly fatal forms. Recently, the therapeutic landscape for mCSPC has been broadly enriched; indeed robust evidence supports the addiction of chemotherapy (docetaxel) or abiraterone acetate to androgen deprivation therapy (ADT), the latter considered for long the unique standard of care. However, the prognostic stratification and the definition of the ideal therapeutic approach for the subpopulation of de novo mCSPC - albeit largely represented in pivotal clinical trials enrolling mCSPC patients - have yet to be prospectively outlined. The aim of this review was to describe the current state of art about clinical presentation, prognostic classification, and different therapeutic options available for de novo mCSPC patients. Furthermore, we shed light on ongoing clinical trials and future perspectives for this disease setting.

Alkaline Phosphatase Kinetics Predict Metastasis among Prostate Cancer Patients Who Experience Relapse following Radical Prostatectomy

Introduction

Metastasis prostate cancer (CaP) occurs in a small fraction of patients. Improved prognostication of disease progression is a critical challenge. This study examined alkaline phosphatase velocity (APV) in predicting distant metastasis-free survival (DMFS).

Materials and Methods

This retrospective cohort study examined CaP patients enrolled in the Center for Prostate Disease Research (CPDR) multicenter national database who underwent RP and experienced BCR (n=1783). BCR was defined as a PSA ≥ 0.2 ng/mL at ≥ 8 weeks post-RP, followed by at least one confirmatory PSA ≥ 0.2 ng/mL or initiation of salvage therapy. APV was computed as the slope of the linear regression line of all alkaline phosphatase (AP) values after BCR and prior to distant metastasis. APV values in the uppermost quartile were defined as “rapid” and compared to the lower three quartiles combined (“slower”). Unadjusted Kaplan Meier (KM) estimation curves and multivariable Cox proportional hazards analysis were used to examine predictors of DMFS.

Results

Of the 1783 eligible patients who experienced post-RP BCR, 701 (39.3%) had necessary AP data for APV calculation. PSA doubling time (PSADT) and APV were strongly associated (p=0.008). No differences in APV were observed across race. In KM analysis, significantly poorer DMFS was observed among the rapid versus slower APV group (Log-rank p=0.003). In multivariable analysis, a rapid APV was predictive of a twofold increased probability of DMFS (HR = 2.2; 95% CI = 1.2, 3.9; p = 0.008), controlling for key study covariates.

Conclusions

Building on previous work, this study found that rapid APV was a strong predictor of DMFS for a broader group of CaP patients, those who undergo post-RP BCR who were enrolled in a longitudinal cohort with long-term follow-up and equal health care access. APV is worth considering as a complementary clinical factor for predicting DMFS.