Citations

40 Background: Previously we have reported enrollment disparities in PCa clinical trials. Funding source can influence minority representation in clinical trials. Hence, we aimed to evaluate the impact of source of funding on enrollment disparities in PCa clinical trials. Methods: MEDLINE and EMBASE were searched to identify phase II/III PCa trials. All relevant trials reporting age by 65 years were considered eligible for inclusion. Trials recruiting from the United States (US) were considered eligible for analysis by race and ethnicity. The trial proportions of age, or racial/ethnic subgroup category and the global incidence in the corresponding age subgroup (from the global burden of disease database), or the US-population-based incidence in the corresponding racial/ethnic subgroup (from SEER 21 database) were used to compute enrollment incidence ratio (EIR) at each trial. EIRs with corresponding 95% confidence intervals (CI) were then meta-analyzed using a random-effects model and stratified by sources of funding (industry, US-government, and others [academic and non-US govt]). A univariate meta-regression was conducted to assess the temporal changes in EIR by each funding category. Results: Of 127 trials recruiting from the US, 89 (70%) reported race, and 35 (27%) reported ethnicity. Among those, 57 (64%), 14 (16%), and 18 (20%) trials reported industry, US-government, and other sources of funding, respectively. Of those reporting ethnicity, 23 (66%), 4 (11%), and 8 (23%) trials reported industry, US-government, and other sources of funding, respectively. Among the 287 eligible trials, 49 trials (17%) reported age by 65 years. Of those, 36 (73%), 6 (12%), and 7 (13%) reported industry, US-government, and other sources of funding, respectively. In terms of racial/ethnic enrollment, Black patients were significantly under-represented in industry funded trials (0.33; 0.27-0.41). No significant disparity was observed in US-government funded trials (0.75: 0.57-1.00). The P-value of interaction was <0.0001. Hispanics were significantly under-represented in industry funded clinical trials (0.56; 0.43-0.74). The number of US-government funded trials reporting Hispanics were small (<10) which precluded any meaningful statistics. No significant disparity was observed in terms of older adults (EIR: 1.00; 95% CI: 0.95; 1.05) overall and by funding sources. Black patients’ representation in industry funded PCa trials has significantly decreased over the last three decades. No significant change was observed in US-government funded PCa trials over the last three decades (P:0.004). Conclusions: Black and Hispanic men with PCa are likely to be under-represented in industry sponsored clinical trials. Black patients’ representation in industry sponsored trials has declined over time, thus widening the cancer-care inequities in these patients.

195 Background: Preliminary data suggests that patients with metastatic castration-sensitive prostate cancer (mCSPC) who achieve deep prostate-specific antigen (PSA) response may have improved survival. This finding may have implications for developing treatment de-escalation strategies. Thus, we assessed the overall survival by deep PSA response in mCSPC patients receiving intensified treatments. Methods: MEDLINE and EMBASE were systematically searched from each database’s inception through 1st October 2022. Trials assessing androgen deprivation therapy intensification (doublets, triplets) and reporting overall survival (OS) by deep PSA response were considered eligible for inclusion. Deep PSA response was defined as the PSA level of less than 0.1 or 0.2 ng/ml within eight months after initiation of intensified treatment. Precomputed effect estimates of OS (deep PSA response vs no deep PSA response) were pooled using an inverse-variance approach after logarithmic transformation; a random-effects meta-analysis was conducted within the Bayesian framework using empirical informative priors for heterogeneity parameter as specified by Turner et al. Summary effect was expressed as hazard ratios (HR) with the corresponding 95% credible intervals (CrI). A sensitivity analysis was conducted using the Der Simonian-Lairds random-effects meta-analysis with Hartung-Knapp (HK) adjustment. Results: Five RCTs (PEACE-1, ARASENS, CHAARTED, LATITUDE, TITAN) with 2533 patients were included in this systematic review. A total of 1335 patients experienced a deep PSA response, while 1218 did not achieve a deep PSA response after the initiation of intensified treatment. The pooled incidence of deep PSA response was 49.45% (95% confidence interval: 37.75-61.18). Bayesian meta-analysis showed significantly improved OS in overall mCSPC patient population who achieved a deep PSA response after intensified treatment with either triplet or doublet therapy as compared to those who did not achieve a deep PSA response (HR: 0.39; 95% CI: 0.30-0.50) as shown. The results were consistent with HK adjustment. Conclusions: Excellent overall survival in patients with deep PSA response may offer an opportunity to guide treatment de-escalation trials in carefully selected mCSPC patients. [Table: see text]

193 Background: We maintain a network meta-analysis for the treatment of mCSPC using a living interactive evidence (LIvE) synthesis framework. Recently, the STAMPEDE trial presented evidence regarding a new triplet regimen (enzalutamide-abiraterone-androgen deprivation therapy [E+AAP+ADT]). Hence, in this report we provide the most-up-to-date evidence to inform the choice of optimal therapy in mCSPC patients. Methods: Phase III randomized controlled trials (RCTs) assessing treatment intensification with androgen pathway inhibitors (API), docetaxel (D), or both in patients with mCSPC were included. Mixed treatment comparisons for overall-survival (OS) and progression-free survival (PFS) were made across randomized comparisons using a frequentist network-meta-analysis. Additionally, subgroup data from three trials (ENZAMET, TITAN, ARCHES) by the receipt of docetaxel were abstracted to evaluate the comparative effectiveness of different triplet regimens. Treatment effects were expressed as hazard ratio (HR) and 95% confidence intervals (CI). Relative treatment rankings were evaluated using P-scores and assessed in congruency with the pairwise estimates. Results: This report includes 10 clinical trials (30 references) and over 11500 patients updated as of 1st October 2022. Using randomized data in overall patient population, AAP+D+ADT (rank 1; HR: 0.50; 95% CI: 0.35-0.72) and E+AAP+ADT (rank 4; HR: 0.76; 0.62-0.93) significantly improved PFS compared to D+ADT (rank 7) but not when compared to E+ADT (rank 2) and APA+ADT (rank 3). Similarly, darolutamide (DARO)+D+ADT (rank 1; HR: 0.68; 0.57-0.81), AAP+D+ADT (rank 2; HR: 0.75; 0.59-0.95) significantly improved OS when compared to D+ADT (rank 7). Efficacy by volume of disease and timing of metastatic presentation was consistent with prior update. Using subgroup data by the receipt of docetaxel, a total of five triplet regimens (DARO+D+ADT, AAP+D+ADT, E+D+ADT, apalutamide (APA)+D+ADT, and E+AAP+ADT) were evaluable for comparisons. E+D+ADT (rank 3) improved PFS compared to D+ADT (rank 9; HR: 0.52; 0.41-0.66) and E+AAP+ADT (rank 6; HR: 0.70; 0.52-0.94). Compared to AAP+ADT (rank 7), E+D+ADT (HR: 0.64; 0.49-0.84) and AAP+D+ADT (rank 2; 0.62; 0.42-0.91) significant improved PFS. However, no significant differences were observed among E+D+ADT, AAP+D+ADT, and APA+D+ADT. Similarly, DARO+D+ADT (rank 1) improved OS compared to APA+D+ADT (HR: 0.47; 0.24-0.93). Conclusions: Current evidence favors the use of emerging triplet regimens over docetaxel doublet but not API doublets in overall population. Among different triplets, E+AAP+ADT may not delay progression compared to docetaxel triplets. Hence, access to treatment, toxicity, disease volume and timing of metastases should be carefully considered in mCSPC patients.

116 Background: The impact of socioeconomic status on genitourinary (GU) cancer mortality in the United States (US) is unclear. Hence, we evaluated the association of the socioeconomic status with GU cancer mortality across the US counties. Methods: County-level age-adjusted mortality rates (AAMR) per 100,000 person-years (PY) for populations diagnosed with GU cancers were abstracted from the wide-ranging online data for epidemiological research (WONDER) database. The agency for toxic substances and disease registry (ATSDR) was queried to obtain county-level social vulnerability indices from 2014-2018. Percentile ranking scores (PRS: ranging from 0-1) were computed for each US county and further categorized into quartiles (Q: 1st: 0-0.25 [least vulnerable]; 4th: 0.75-1.00 [most vulnerable]). AAMRs were then linked with quartile rankings. A population-weighted, Poisson regression analysis was conducted to compute rate ratios (RR) of AAMRs between 4th and 1st Q with the corresponding 95% confidence intervals (CI). Results: A total 3142 US counties were included in this analysis. The AAMR for GU cancers was 22.6 overall deaths (OD) and 4.20 premature deaths (PD; defined as death at age <65 years) per 100,000 PY. GU cancer-related mortality increased in a stepwise fashion from the 1st Q to the 4th Q (OD: 21.6 vs 24.1; PD: 3.48 vs 5.19). In terms of OD by specific GU cancers, significantly higher AAMRs were observed in the 4th Q compared to the 1st Q for patients with prostate cancer (RR; 1.19 [95% CI;1.14-1.24]), and renal cell carcinoma (RCC; 1.12 [1.04-1.21]) but not for those with lower urothelial tract cancers (0.92 [0.87-0.96]). Among subgroups, non-Hispanic Blacks (1.19 [1.07-1.33]), and Hispanics (1.28 [1.08-1.51]) with prostate cancer and men with RCC (1.11; 1.03-1.19) in the 4th Q experienced significantly higher overall mortality when compared to those in the 1st Q. With regards to PD, significantly higher AAMRs were observed in the 4th Q vs 1st Q for patients with prostate cancer (1.54 [1.34-1.77]), and RCC (1.28 [1.12-1.45]). Consistently, men with RCC in the 4th Q also experienced higher premature mortality when compared to the 1st Q. Sparsity of mortality data among different ethnic/racial subgroups across the US counties precluded any formal assessment of disparity by specific GU cancers. A sensitivity analysis, conducted using the weighted linear regression approach, showed consistent results. Conclusions: Population level data suggest that socially vulnerable populations, especially Non-Hispanic Black and Hispanic men with prostate cancer, and men with renal cell carcinoma may be at an increased risk of cancer-related mortality. Hence, there is a dire need to address this mortality gap across different socioeconomic subgroups to ensure health-care equity. Investigations at the patient level are required to further ascertain these findings.

Accurate clinical staging of bladder cancer aids in optimizing the process of clinical decision-making, thereby tailoring the effective treatment and management of patients. While several radiomics approaches have been developed to facilitate the process of clinical diagnosis and staging of bladder cancer using grayscale computed tomography (CT) scans, the performances of these models have been low, with little validation and no clear consensus on specific imaging signatures. We propose a hybrid framework comprising pre-trained deep neural networks for feature extraction, in combination with statistical machine learning techniques for classification, which is capable of performing the following classification tasks: (1) bladder cancer tissue vs. normal tissue, (2) muscle-invasive bladder cancer (MIBC) vs. non-muscle-invasive bladder cancer (NMIBC), and (3) post-treatment changes (PTC) vs. MIBC.

Importance The effectiveness of triplet therapy compared with androgen pathway inhibitor (API) doublets in a heterogeneous patient population with metastatic castration-sensitive prostate cancer (mCSPC) is unknown. Objective To assess the comparative effectiveness of contemporary systemic treatment options for patients with mCSPC across clinically relevant subgroups. Data Sources For this systematic review and meta-analysis, Ovid MEDLINE and Embase were searched from each database’s inception (MEDLINE, 1946; Embase, 1974) through June 16, 2021. Subsequently, a “living” auto search was created with weekly updates to identify new evidence as it became available. Study Selection Phase 3 randomized clinical trials (RCTs) assessing first-line treatment options for mCSPC. Data Extraction and Synthesis Two independent reviewers extracted data from eligible RCTs. The comparative effectiveness of different treatment options was assessed with a fixed-effect network meta-analysis. Data were analyzed on July 10, 2022. Main Outcomes and Measures Outcomes of interest included overall survival (OS), progression-free survival (PFS), grade 3 or higher adverse events, and health-related quality of life. Results This report included 10 RCTs with 11 043 patients and 9 unique treatment groups. Median ages of the included population ranged from 63 to 70 years. Current evidence for the overall population suggests that the darolutamide (DARO) triplet (DARO + docetaxel [D] + androgen deprivation therapy [ADT]; hazard ratio [HR], 0.68; 95% CI, 0.57-0.81), as well as the abiraterone (AAP) triplet (AAP + D + ADT; HR, 0.75; 95% CI, 0.59-0.95), are associated with improved OS compared with D doublet (D + ADT) but not compared with API doublets. Among patients with high-volume disease, AAP + D + ADT may improve OS compared with D + ADT (HR, 0.72; 95% CI, 0.55-0.95) but not compared with AAP + ADT, enzalutamide (E) + ADT, and apalutamide (APA) + ADT. For patients with low-volume disease, AAP + D + ADT may not improve OS compared with APA + ADT, AAP + ADT, E + ADT, and D + ADT. Conclusions and Relevance The potential benefit observed with triplet therapy must be interpreted with careful accounting for the volume of disease and the choice of doublet comparisons used in the clinical trials. These findings suggest an equipoise to how triplet regimens compare with API doublet combinations and provide direction for future clinical trials.

ImportanceProstate cancer (PCa) is marked by disparities in clinical outcomes by race, ethnicity, and age. Equitable enrollment in clinical trials is fundamental to promoting health equity.ObjectiveTo evaluate disparities in the inclusion of racial and ethnic minority groups and older adults across PCa clinical trials.Data SourcesMEDLINE, Embase, and ClinicalTrials.gov were searched to identify primary trial reports from each database's inception through February 2021. Global incidence in age subgroups and US population-based incidence in racial and ethnic subgroups were acquired from the Global Burden of Disease and Surveillance, Epidemiology, and End Results 21 incidence databases respectively.Study SelectionAll phase 2/3 randomized PCa clinical trials were eligible for age disparity analyses. Trials recruiting exclusively from the US were eligible for primary racial and ethnic disparity analyses.Data Extraction and SynthesisThis study was reported in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guidelines. Data were pooled using a random-effects model.Main Outcomes and MeasuresEnrollment incidence ratios (EIRs), trial proportions (TPs) of participants 65 years or older or members of a racial and ethnic subgroup divided by global incidence in the corresponding age group, or US population–based incidence in the corresponding racial and ethnic subgroup, were calculated. Meta-regression was used to explore associations between trial characteristics and EIRs and trends in EIRs during the past 3 decades.ResultsOf 9552 participants among trials reporting race, 954 (10.8%) were African American/Black, 80 (1.5%) were Asian/Pacific Islander, and 8518 (78.5) were White. Of 65 US trials, 45 (69.2%) reported race and only 9 (13.8%) reported data on all 5 US racial categories. Of 286 global trials, 75 (26.2%) reported the enrollment proportion of older adults. Outcomes by race and age were reported in 2 (3.1%) and 41 (15.0%) trials, respectively. Black (EIR, 0.70; 95% CI, 0.59-0.83) and Hispanic (EIR, 0.70; 95% CI, 0.59-0.83) patients were significantly underrepresented in US trials. There was no disparity in older adult representation (TP, 21 143 [71.1%]; EIR, 1.00; 95% CI, 0.95-1.05). The representation of Black patients was lower in larger trials (meta-regression coefficient, −0.06; 95% CI, −0.10 to −0.02; P = .002).Conclusions and RelevanceThe results of this meta-analysis suggest that Black and Hispanic men are underrepresented in trials compared with their share of PCa incidence. The representation of Black patients has consistently remained low during the past 2 decades.

e16550 Background: Improved computational power and modern algorithms have generated significant interest in radiomics for cancer diagnosis and staging. Here we assess the performance of deep learning (DL) models as a means for feature extraction in combination with supervised machine learning (ML) algorithms for accurate staging and chemotherapy response assessment of bladder cancer. Methods: Deidentified grayscale CT images from bladder cancer patients scheduled to undergo radical cystectomy were included in this retrospective study. These images were manually annotated with two regional masks (normal region and cancer region). Five DL models- namely, AlexNet, GoogleNet, InceptionV3, ResNet-50, and XceptionNet pre-trained on the ImageNet dataset, a public dataset, were then fine-tuned on our bladder CT scan data to extract features. Through feature selection process, the subset of the features was used to build ML classifiers for classification. The classification was performed using five different ML classifiers, namely k-Nearest Neighbor (KNN), Naïve-Bayes (NB), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Decision Tree (DT). The classification task was performed with 10-fold cross-validation, and each of the experiments contained a different but not mutually exclusive subset of samples. The evaluation metrics include accuracy, sensitivity, specificity, precision, and F1-score. Results: A total of 200 deidentified grayscale CT images of 100 patients with histologically proven bladder cancer, were included in this study. For experiment (1) normal vs. cancer, the LDA classifier on XceptionNet based features provides the best performance with an accuracy of 86.07%, sensitivity of 96.75%, specificity of 69.65%, precision of 83.07%, and F1-score of 89.39%. For experiment (2) non-muscle invasive Cancer (NMIBC) vs. muscle invasive bladder cancer (MIBC), the LDA classifier on XceptionNet based features provided the best performance with an accuracy of 79.72%, sensitivity of 66.62%, specificity of 87.39%, precision of 75.58%, and F1-score of 70.81%. For experiment (3) T0 lesion vs. MIBC, the LDA classifier on XceptionNet based features provides the best performance with an accuracy of 74.96%, sensitivity of 80.51%, specificity of 70.22%, precision of 69.78%, and F1-score of 74.73%. Conclusions: Our proposed model has shown good results in differentiating normal vs cancer and promising performance in differentiating T0 vs MIBC after chemotherapy treatment. We are expanding our dataset to further improve the performance in differentiating T0 vs MIBC. In addition, we will investigate the applicability of GAN for data augmentation to address data limit. We believe the hybrid DL and ML framework may facilitates radiologists' decisions and clinical decision-making in patients with bladder cancer.

4594 Background: Cisplatin based neoadjuvant chemotherapy (NAC) followed by definitive therapy improves survival in patients with muscle invasive bladder cancer (MIBC). However, the clinical benefit of NAC might vary with the choice of definitive therapy. Therefore, we assessed the absolute benefit of NAC followed by radical cystectomy or radical radiotherapy separately using the totality of evidence. Methods: MEDLINE and EMBASE were systematically searched to identify randomized trials assessing cisplatin based neoadjuvant chemotherapy followed by either radical cystectomy or definitive radiotherapy in patients with MIBC. Outcomes of interest included overall survival (OS) and disease-free survival (DFS). Treatment effects were expressed as hazard ratios (HR) with 95% confidence interval (CI). Incidence rate ratios were calculated to estimate time to event outcomes for trials not reporting HR. A random-effects DerSimonian-Laird meta-analysis was conducted. Absolute effects were then obtained using baseline risks from the control arm of RCTs. Results: Of 4887 studies identified, 13 trials with 2529 patients were included in this meta-analysis. Most trials included patients with T2-4 and N0 patients and only 3 trials included patients with node positive disease. Total of 180 (47%) DFS events were observed with NAC+RC compared to 213 (56%) events in RC alone (HR: 0.72; 95% CI: 0.59-0.89) and 346 (58%) OS events were observed with NAC+ RC compared to 385 (52%) events in RC alone (HR: 0.80; 95% CI: 0.69-0.92). Total of 186 (70%) DFS events were observed with NAC + radiotherapy compared to 205 (71%) events in radiotherapy alone (HR: 0.91; 95% CI: 0.74-1.12) and 263 (58%) OS events were observed with NAC+ radiotherapy compared to 294 (61%) events in radiotherapy alone (HR:0.93; 95% CI: 0.79-1.08). Conclusions: The choice of definitive therapy after cisplatin-based NAC impacts survival in patients with MIBC. RC after NAC improved DFS (114 fewer events per 1000 events) and OS (76 fewer per 1000 events) whereas radiotherapy after NAC showed no survival benefit. [Table: see text]

4504 Background: C, a multitargeted receptor tyrosine kinase inhibitor (TKI), promotes an immune-permissive environment that may enhance response to immune checkpoint inhibitors (ICIs). COSMIC-021, a multicenter phase 1b study, is evaluating C + A (anti‒PD-L1 therapy) in various solid tumors (NCT03170960). C + A demonstrated encouraging clinical activity in cohort 2 of COSMIC-021 in patients (pts) with UC previously treated with platinum-containing chemotherapy (chemo) (Pal S et al. ASCO 2020. Abstract 5013). Outcomes of C + A from 3 other UC cohorts (C3, C4, C5) are presented. Methods: Pts with inoperable locally advanced/metastatic UC with transitional cell histology and ECOG PS 0‒1 were eligible. Pts enrolled in C3 and C4 had no prior therapy and were cisplatin-based chemo ineligible (C3) or eligible (C4). C5 enrolled pts with one prior ICI and no prior VEGFR-TKI therapy. Pts received C 40 mg PO QD and A 1200 mg IV Q3W. CT/MRI scans were performed Q6W for first year and Q12W thereafter. The primary endpoint is objective response rate (ORR) per RECIST v1.1 by investigator. Other endpoints: safety, duration of response (DOR), PFS, and OS. Results: Thirty pts each were enrolled in C3 and C4, and 31 in C5. Baseline characteristics for C3, C4, and C5, respectively: median age, 74 y, 66 y, 68 y; male, 67%, 73%, 55%; ECOG PS 1, 63%, 57%, 74%; lung/liver metastasis; 33%/17%, 40%/20%, 58%/23%; ≥3 tumor sites, 30%, 43%, 45%; bladder as primary site, 67%, 70%, 71%. As of Nov 30, 2021, the median follow-up for C3, C4, and C5 was 27.9, 19.1, and 32.9 mo, respectively, with 1, 6, and 1 pts on treatment. C + A demonstrated clinical benefit across all cohorts (Table). Most common treatment-related adverse events (TRAEs) of any grade across C3, C4, and C5, respectively, were diarrhea (43%, 33%, 35%), nausea (27%, 17%, 26%), fatigue (27%, 27%, 48%), and decreased appetite (33%, 27%, 39%); grade 3/4 TRAEs occurred in 63%, 43%, and 45%, and there was no grade 5 TRAE. Conclusions: C + A demonstrated encouraging clinical activity with manageable toxicity in inoperable locally advanced/metastatic UC as first-line systemic therapy in cisplatin-based chemo eligible/ineligible pts and as second- or later line in pts who received prior ICI. Clinical trial information: NCT03170960. [Table: see text]