Browse Articles

The impact of Duration of Untreated Psychosis on functioning and quality of life over one year of Coordinated Specialty Care (CSC)

Background This study examined the relationship between the Duration of Untreated Psychosis (DUP) and functional outcomes at baseline, 6 months, and 12 months after admission to Coordinated Specialty Care (CSC). Methods A total of 246 participants from two U.S. public-sector CSC programs were categorized into Low and High DUP groups using two criteria: (i) a median split of the DUP distribution and (ii) the World Health Organization (WHO) aspirational standard of 3 months. Changes in global functioning (GAF), social functioning (GF: Social), and occupational functioning (GF: Role), symptom severity (PANSS), and quality of life (QoL) were assessed using a Linear Mixed Model Repeated Measures (MMRM) analysis across the three time points. A Generalized Linear Model (GLM) with a logit link function was applied to analyze binary outcomes, specifically the status of being Neither in the Labor Force, Education, or Training (NLFET). Both models adjusted for time and site as covariates and used an unstructured variance-covariance matrix to account for within-subject correlations in repeated measures. The difference-in-differences method was employed to estimate the impact of DUP on outcomes over time, with results reported as least square means for continuous outcomes, odds ratios for binary outcomes, and 95% confidence intervals (CI) for both Low and High DUP groups. Results No significant differences were observed between the Low and High DUP groups at baseline. By 6 months, participants in the Low DUP group (DUP < 3 months) exhibited significantly greater improvements (reduction) in NLFET status (3-month OR = 3.25, p = 0.03; median split OR = 2.25, p = 0.03) and global functioning, GF: Role, and GF: Social. By 12 months, the Low DUP group continued to show significantly greater NLFET status improvement (3-month OR = 3.59, p = 0.03; median split OR = 3.40, p = 0.0032). Improvements in global functioning were sustained at 12 months, while social and occupational functioning gains were not. No significant differences were observed between groups for quality of life or symptom severity over time. Conclusion Shorter DUP is linked to more rapid functional recovery within the first year after CSC admission.

Research on the properties of polymer stabilized coal gangue materials in rubber powder slag base

Comprehensive bladder cancer molecular profiling and monitoring based on mutational, epigenomic, and expression data from real-world patients.

860 Background: Bladder cancer poses considerable therapeutic challenges, particularly in the context of bladder preservation strategies that aim to balance maintaining quality of life with achieving optimal survival outcomes. Traditional treatments, such as radical cystectomy, often have profound impact on patient morbidity. However, recent advances in molecular profiling -- including mutational, epigenomic, and gene expression analyses -- offer promising avenues for personalized cancer treatment approaches. Despite these advances, comprehensive studies leveraging detailed analysis of molecular profiling and urine-based monitoring in bladder cancer are lacking. Methods: A cohort of 30 real-world patients with bladder and upper tract urothelial carcinoma (UTUC) of various subtypes were included in this study. Standard treatment modalities employed were neoadjuvant chemotherapy, trimodality therapy (TMT) for bladder preservation, and systemic chemotherapy or immunotherapy in the metastatic setting. PredicineCOMPLETE is an integrated assay that interrogates genomic alterations such as mutations, copy number variations (CNVs), and gene fusions – as well as DNA methylation and transcriptomic profiles. All samples had previously undergone the PredicineBEACON urine MRD test, which covers mutation/CNV/fusion analysis. We further performed whole-transcriptome sequencing (WTS) on baseline urine cell pellet (UCP) samples, and the PredicineEPIC DNA methylation assay on all the follow-up timepoint samples. Results: The PredicineCOMPLETE assay generated significantly more comprehensive data compared to mutational panels alone, providing a rich molecular landscape of each patient’s tumor biology. Comprehensive correlation analysis between DNA methylation and RNA expression were conducted. Strong correlation was observed for some bladder cancer biomarker genes such as TERT and TP53. An AI model was trained using patients’ treatment decision (bladder preservation versus surgery), clinical features, and the comprehensive molecular data obtained. The trained AI model accurately matches the physician’s choices over 90% of the validation cases. Conclusions: This study demonstrates that comprehensive molecular profiling using the PredicineCOMPLETE assay helps us understand the underlying disease biology. Combined with machine learning and AI modeling, it can effectively assist in treatment decision-making for bladder cancer patients. While these initial results are encouraging, the limited sample size necessitates further validation in larger, independent cohorts to confirm the model’s efficacy and generalizability.

Non-muscle invasive bladder cancer treatment selection in an emerging treatment era: A patient preference study.

754 Background: Patients with non-muscle invasive bladder cancer (NMIBC) who become unresponsive to Bacillus Calmette-Guérin (BCG) face preference-sensitive choices between emerging and established bladder-sparing treatments or radical cystectomy (RC). This study elicited 1) the preferences of patients in the United States for bladder-sparing treatments with different benefits and burdens and 2) their choice between these options and RC. Methods: Patients with self-reported NMIBC and BCG experience completed an online survey. A discrete-choice experiment (DCE) elicited preferences for hypothetical bladder-sparing treatments. Evidence-based treatment attributes (and levels) included chance of recurrence of NMIBC (45%-69%) and chance of progression to MIBC 1 year after treatment (2%-30%); administration burden (intravesical every week depending on response or every 3 months for 1 year, or intravenous every 6 weeks for up to 2 years); treatment-related fatigue (none to moderate-severe); chance of discomfort and pain or urinary tract infection (0%-30%); and chance of developing immune-related adverse events (AEs) (0%-25%). Conditional relative importance of attributes and risk tolerance measures were calculated from random parameter logit models. In addition to the DCE, direct-elicitation questions offered choices between fixed profiles of different bladder-sparing treatments and RC. The Shared Decision Making (SDM) Questionnaire (SDM-Q-9) revealed patients’ levels of satisfaction with previous real-world choices. Responses to the fixed-profile questions and SDM-Q-9 were analyzed descriptively. Results: Among the 206 respondents, reduced risks of progression and disease recurrence were the most important attributes given the range of levels included in the DCE. The other attributes—treatment-related AEs and administration burden—were less important and had statistically similar impacts on choices. On average, patients were willing to accept a >25% risk of immune-related side effects requiring oral steroids to achieve the greatest reductions in disease progression and recurrence offered in the survey. With the exception of repeated BCG-like therapy, most patients (>70%) preferred bladder-sparing treatments over RC. Over 25% of respondents disagreed with the statement “My doctor asked me which treatment option I prefer” when reflecting on their SDM experiences. Conclusions: Patients with NMIBC cared most about treatment efficacy and were generally willing to accept clinically relevant levels of treatment-related risks and discomfort to achieve reductions in disease progression and recurrence. Patients demonstrate heterogeneous preferences, and continued efforts to incorporate shared decision-making into treatment decisions are warranted.

Pilot study evaluating duplex sequencing of urinary DNA as a biomarker for recurrence in non-muscle invasive bladder cancer.

865 Background: The detection of tumor-associated urinary DNA (uDNA) as a biomarker for non-muscle invasive bladder cancer (NMIBC) has shown promise, but is significantly limited in sensitivity due to replication errors inherent in next-generation sequencing (NGS). Duplex sequencing is an ultrasensitive/accurate sequencing technology which may provide a solution to this problem. We present a pilot study applying duplex sequencing technique to uDNA in NMIBC for use as a biomarker of recurrence. Methods: Urine samples from a total of 30 patients with NMIBC were collected following complete transurethral resection of bladder tumor and prior to intravesical therapy (pre-tx) and following six weeks of intravesical therapy (post-tx). Detection of ten commonly mutated NMIBC genes was carried out using next generation duplex sequencing. Results were correlated with recurrence of tumor. Results: Median age for our cohort was 71 [41, 88] and 80% were male. A total of 16 (53.3%) of the cohort experienced a recurrence within the first year, with a median time to recurrence of 10 months. Tumor-associated uDNA was successfully detected to variant allele fraction (VAF) below 0.001. Presence of any pathogenic variant in the pre-tx urine >0.006 VAF was associated with a 72.7% sensitivity and 78.9% specificity for recurrence within one year. The highest VAF of pathogenic variant in uDNA trended with time-to-relapse. Post-tx uDNA assessment did not correlate with recurrence. Further analysis is limited by small sample size. Conclusions: This pilot study demonstrates potential utility of ultrasensitive duplex sequencing on NMIBC uDNA in the detection of recurrence.

Developing a deep learning algorithm for automated p53 immunohistochemistry digital image analysis in prostate cancer.

223 Background: p53 immunohistochemistry (IHC) is a prognostic marker in prostate cancer (PCa), but manual scoring by pathologists is time-consuming and prone to variation. Digital image analysis (DIA) offers a potential solution to enhance speed, accuracy, and reproducibility. This study aims to develop a DIA algorithm for scoring p53 IHC in PCa and compare its performance with manual scoring. Methods: Forty patients with adequate archival PCa tissue were randomly selected, and representative sections were stained for p53 IHC. Two pathologists independently scored p53 nuclear expression based on intensity (0, 1+, 2+, 3+) and percentage of expression in tumor cells (0%, < 1%, 1–5%, > 5%). Whole slide images (WSIs) were analyzed using a Visiopharm batch processing workflow. In a training set of 14 samples, each WSI was manually segmented into benign, tumor, and background regions. The algorithm with the highest accuracy for tumor detection was selected for p53 scoring. Artifacts generating false positives, such as surgical ink and pigments, were filtered by an Artifact Detection APP. Problematic segmentation issues, including hemosiderin-laden macrophages and folded tissue sections, were manually excluded. A Tumor Detection APP identified tumor regions of interest. A Nuclei Detection APP identified the tumor nuclei and was calibrated to differentiate 3,3′-diaminobenzidine (DAB) intensity thresholds for scores of 0–3+ on the evaluation set of 40 samples. The final application was applied to the evaluation set, and results were compared with manual pathologist scores. All image analysis algorithms were trained using convolutional neural networks (CNNs) on pathologist-guided training sets within the Visiopharm platform, executed as part of the whole slide analysis protocol. Results: Comparison of automated DIA p53 scores with manual consensus scores (Table) revealed a Kendall’s coefficient of concordance of 0.81 (p = 0.008), indicating strong agreement. The Goodman-Kruskal Gamma coefficient showed a high correlation of 0.8 (95% CI: 0.6-1.0). The estimated Volume Under the ROC Surface (VUS) for the 4-level ordinal score was 0.68 (SE = 0.11), suggesting moderate to high discriminatory power in distinguishing among the four scoring levels based on the percentage of positive nuclei. Conclusions: The strong inter-rater agreement and high correlation between manual and DIA scores suggest that the deep learning algorithm assesses p53 IHC in PCa with moderate to high discriminatory power. Robust slide selection is crucial to minimize false positives. These findings highlight the potential of automated DIA to enhance efficiency and standardization of p53 IHC scoring. Distribution of manual p53 scores (rows) and automated digital image analysis (DIA) p53 scores (columns) by intensity. Manual p53 scores (n) Automated DIA p53 scores (n) 0 1+ 2+ 3+ 0 18 5 1 2 1+ 1 5 3 1 2+ 0 0 2 0 3+ 0 0 0 2

Prevalence and associated factors of diabetic ketoacidosis among patients with diabetes mellitus at the University of Gondar Comprehensive and Specialized Referral Hospital Northwest, Ethiopia

Background Diabetes is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. Diabetic ketoacidosis is one of the life-threatening complications in diabetic individuals with, high morbidity and mortality globally. However, the data related to the prevalence and associated factors of diabetic ketoacidosis are limited in the study setting. Objective To assess the prevalence of diabetic ketoacidosis and its associated factors among diabetic mellitus patients at the University of Gondar Comprehensive Specialized Hospital. Methods A hospital-based cross-sectional study was conducted from March 1 to September 30, 2021. A total of 405 diabetic patients aged 20 and above were selected using a systematic random sampling technique. A total of 810 blood and urine samples (each 405) were collected using sterile serum separator tubes and urine collection cups, respectively. Sociodemographic and clinical data was collected using a structured questionnaire. Chemical analysis of urine was done using urine reagent strips to determine urine ketone bodies and PH. BECKMAN COULTER DxC700 AU clinical chemistry analyzer instrument was used to determine electrolytes and metabolites. The data was entered using Epi-Data version 4.6 and transferred to SPSS version 25 for analysis. Bivariable and multivariable logistic regression analyses were used to determine the factors associated with the diabetic ketoacidosis. The results were considered statistically significant if the adjusted odds ratio was reported with a 95% confidence interval and a P-value below 0.05. Results The overall prevalence of diabetic ketoacidosis among diabetic patients was 35/405 (8.6%, 95% CI: 6.0–11.0%). Of these cases, 25 (71.4%) had type 1 diabetes mellitus, while 10 (28.6%) had type 2 diabetes mellitus. Statistically significant factors associated with diabetic ketoacidosis included being a young adult aged 20–29 years (AOR = 2.262; 95% CI = 1.090–4.758; P = 0.013), unemployment (AOR = 2.578; 95% CI = 1.457–6.113; P = 0.017), the presence of infection (AOR = 2.819; 95% CI = 1.138–8.428; P = 0.024), and being T1DM (AOR = 3.106; 95% CI = 1.150–7.273; P = 0.003). Conclusions and recommendations The prevalence of diabetic ketoacidosis among follow-up diabetes patients in this study was high, particularly among those aged 20–29 years, unemployed, or with infections. Increased vigilance, regular monitoring, timely infection management, and comprehensive diabetes education are essential for early detection and prevention of DKA. Social and financial support for unemployed diabetic patients can further enhance access to care and reduce DKA risk.

Predictive value and mediating effect analysis of the AHR-ARNT-CYP1A1 axis for missed abortion related to polycyclic aromatic hydrocarbons exposure

ACCEL: [Ac-225]-PSMA-62 phase Ia/Ib/II clinical trial to characterize efficacy, safety, tolerability, and dosimetry in oligometastatic hormone-sensitive and metastatic castration-resistant prostate cancer.

TPS282 Background: Actinium-225 (Ac-225)-based, prostate-specific membrane antigen (PSMA)-targeted radioligand therapy (RLT) represents a promising treatment modality for prostate cancer. First-generation PSMA-targeting ligands (e.g., PSMA-617 and PSMA-I&T) paired with Ac-225 have been associated with myelosuppression, renal toxicity, and xerostomia (1). LY4181530 (previously PNT2001) pairs Ac-225 with PSMA-62, a next-generation ligand, which was specifically designed to overcome these limitations. It employs an improved linker technology that increases cellular internalization, leading to improved biodistribution, tumor delivery of Ac-225, and efficacy in preclinical models (2). Methods: ACCEL (NCT06229366) is a multi-center, open-label, multiple-arm, Phase Ia/Ib/II study evaluating the safety, tolerability, and efficacy of [Ac-225]-PSMA-62 in patients with oligometastatic hormone-sensitive prostate cancer (OmHSPC) and metastatic castration-resistant prostate cancer (mCRPC). Eligible patients with OmHSPC have metachronous disease, up to 5 PSMA-positive lesions, and have not initiated life-long ADT. Eligible patients with mCRPC have PSMA-positive lesions and have received prior androgen receptor pathway inhibitor, taxane chemotherapy (unless ineligible or declined), and up to 3 prior systemic therapy regimens in the mCRPC setting. Prior PSMA-targeted RLT, baseline Grade ≥1 xerostomia, and Grade ≥1 xerophthalmia are not permitted. In the Phase 1a, dose escalation decisions follow the Bayesian optimal interval (BOIN) design to separately determine the maximum tolerated dose of [Ac-225]-PSMA-62 for each patient population. In the Phase 1b, patients will be randomized to 2 or more arms to optimize dosing/schedule and inform the selection of the recommended Phase II dose of [Ac-225]-PSMA-62 for each patient population. The phase II aims to evaluate the efficacy of [Ac-225]-PSMA-62 compared to best standard of care in patients with mCRPC, with the primary endpoint being radiographic progression-free survival. The study is currently enrolling in Canada with plans to open in other countries. 1. Sathekge MM. et al. Lancet Oncol . 2024 Feb;25(2):175-183. 2. Vito A. et al. EP-039. Presented at EANM Oct 2022, Barcelona, Spain. Clinical trial information: NCT06229366 .

Bayesian re-analysis: Comparing radical cystectomy with trimodality therapy in patients with muscle invasive bladder cancer.

737 Background: Randomized trials comparing radical cystectomy (RC) and trimodality therapy (TMT) in muscle invasive bladder cancer (MIBC) have not been feasible. In 2023, Zlotta et al. published a retrospective multi-institutional analysis evaluating metastasis free survival (MFS) and overall survival (OS) outcomes in patients treated with RC or TMT. Zlotta et al. is generally considered the highest quality data available for this comparison, but the results were presented using traditional frequentist statistics which can be challenging to interpret. The purpose of this study was to use Bayesian re-analysis of Zlotta et al. to convert its frequentist summary statistics into outcome probabilities, enabling a more intuitive treatment comparison between RC and TMT. Methods: The Zlotta et al. study results comparing RC and TMT were described by estimating the probability of any benefit (HR<1) or a minimal clinically meaningful (MCR) benefit (HR<0.8). An informative neutral prior distribution was defined by surveying bladder cancer experts on the comparison of RC and TMT use in bladder cancer patients included in Zlotta et al. (cT2–T4N0M0, <7cm, no or unilateral hydronephrosis, no CIS, average age 70). Using a neutral prior of no advantage to either treatment and methods adapted from Wijeysundera et al., we calculated probabilities of a benefit in MFS and OS. We performed sensitivity analyses by varying the strength of the study-specific priors’ neutrality assumption and by using an alternative informative neutral prior developed for oncology comparisons but not specifically for MIBC. Results: The expert-informed informative neutral prior assumption assumed a 70% chance that any differences with respect to any cancer control or overall survival outcome would be less than the minimal clinically significant thresholds. The posterior probabilities of the primary analysis are presented in the table. Sensitivity analyses of the estimates of any benefit for MFS and OS varied by up to 3%, while estimates of a MCR benefit for MFS and OS varied up to 15%. Conclusions: The best available evidence suggests that in selected MIBC patients there is a >96% chance that TMT is associated with any OS advantage over RC but a <59% chance that the benefit reaches a minimal clinically meaningful benefit threshold. There is >65% chance that TMT is associated with any MFS advantage over RC but <13% chance of a minimal clinically meaningful benefit. Bayesian re-analysis of outcome estimate from Zlotta et al. 2023. Probability of any benefit of TMT over RC (HR<1) Probability of any benefit of RC over TMT (HR>1) Probability of a MCR benefit of TMT over RC (HR<0.8) Adjusted MFS Zlotta et al. Outcomes IPTS SHR 0.89 (95% CI 0·67–1·20) 73% 27% 12% PSM SHR 0.93 (95% CI 0.71–1.24) 66% 34% 7% Adjusted OS IPTS SHR 0.70(95% CI 0.53–0.92) 98% 2% 58% PSM SHR 0.75 (95% CI 0.58–0.97) 97% 3% 44%

Genomic characteristics of patients with metastatic hormone-sensitive prostate cancer treated with ARPI-based therapy: A single-center analysis.

244 Background: The addition of androgen receptor pathway inhibitors (ARPI) to androgen deprivation therapy (ADT) has improved survival in patients (pts) with metastatic hormone-sensitive prostate cancer (mHSPC), both as doublets and as triplets with docetaxel. The prognostic role of genomic alterations (GA) is of growing interest in this setting. We evaluated the GA profiling of a population treated with ARPI-based therapy in a single-center institution. Methods: Our retrospective analysis included patients with mHSPC treated at IRCCS San Raffaele Hospital between 2020 (when ARPI were authorized for mHSPC in Italy) and 2023 (when triplets of ARPI + ADT + docetaxel were authorized). Included patients had a diagnosis of mHSPC, tissue biopsy available for genomic profiling, and were treated with ARPI plus ADT (plus or minus docetaxel) within 120 days of initial diagnosis. Comprehensive genomic profiling (CGP) using a commercial hybrid capture-based system (Foundation Medicine) was performed on all pts to evaluate all classes of GA, homologous recombination score (HRDsig), genomic ancestry, and signature. The log-rank test and Cox proportional hazards models compared GA between responders (Rs: defined as non-progressive pts) and not-responders (NRs: pts developing a progressive disease). Kaplan Meier analysis was used to estimate progression-free survival (PFS) and overall survival (OS). Results: 28 patients were included in our analysis. Among them, 25 pts received ARPI + ADT, 3 ARPI + ADT + docetaxel. The median age was 71.8 years (range 53.1-83.9). After a median follow-up of 55.1 months, there were no differences in median PFS (mPFS) between patients treated with triplets and doublets (55.42 vs. 78.0 mos - HR = 1.12; 95%CI, 0.13-9.87; p = 0.92). The median OS (mOS) was not reached in both subgroups, without significant differences in survival rates (HR = 0.32; 95%CI, 0.01-7.33; p = 0.48). The overall response rate was 71.4%, and the disease-control rate was 85.7%. Comparing the CGP profiling between responders and progressive-pts, SPOP mutations were more frequent among Rs than NRs to ARPI (25% vs 0%; p = 0.183). TMPRSS2 - ERG fusions, which tend to be less frequent in SPOP mutated cases, were less frequent in Rs (12.5%) than NRs (20.0% - p = 0.648). There was a similar incidence of other GAs between the two groups of pts, such as PTEN , BRCA1/2 , ATM , and CDK12 (all 12.5% vs. 10.0%; all p > 0.05). Conclusions: In a real-world setting, response to ARPI-based therapy may be associated with characteristic genomic features, such as SPOP mutations, or TMPRSS2 / ERG fusions, both in doublets and in triplet regimens. These findings underscore the importance of larger cohorts to further validate this hypothesis and inspire future research in the treatment selection for mHSPC pts.

Preferred treatment regimens for rare genitourinary (GU) malignancies.

780 Background: Rare GU cancers offer a challenge in determining standard of care therapy. Often data is extrapolated from small patient series or other tumor types to help guide clinicians. There is a lack of prospective data to guide therapy. Methods: We conducted a five-question survey via the Alliance for Clinical Trials in Oncology cooperative group network to identify commonly used and preferred regimens for the treatment of metastatic rare GU malignancies, including bladder squamous cell carcinoma (SCC), bladder adenocarcinoma, small cell bladder carcinoma (SCBC), penile SCC, and sex cord stromal tumors. Each question included 1) number of patients the provider treated per year, and 2) preferred frontline metastatic regimen for the rare tumor (multiple choice options drawn from the literature and selected after a discussion with a panel of experts (Table)). Surveys were emailed to the GU malignancy Alliance members, including academic and NCI Community Oncology Research Program (NCORP) sites. Responses were pooled and analyzed. Results: Fifty-one survey responses were received. One outlier was removed from the analysis leaving 50 responses. Twenty-six sites (52%) were NCORP, 22 sites were academic (44%), 2 sites were other. For the bladder SCC patients, the average number seen per year was 3.6 (range 0-15), 36.7% chose gemcitabine/platinum, 32.7% chose carboplatin/paclitaxel/gemcitabine, and 16.3% chose ITP as their preferred frontline regimen. For the adenocarcinoma bladder patients, the average number seen per year was 2.7 (range 0-10), 47.9% chose FOLFOX/CAPOX, 20.8% chose Gem-FLP, 16.7% chose FOLFOX/CAPOX + Bevacizumab and 6.2% chose ITP. For the SCBC patients, the average number seen per year was 3.1 (range 0-10), 62% chose platinum/etoposide with an immune checkpoint inhibitor compared to 36% who chose platinum/etoposide alone. For the penile SCC patients, the average number seen per year was 2.5 (range 0-10), 71.4% chose TIP,16.3% chose cisplatin/5FU and 10.2% chose immune checkpoint inhibitor. For the sex cord stromal tumor patients, the average number seen per year was 0.9 (range 0-10), 66.0% reported never treated and 19.2% chose BEP. Conclusions: This survey provides information on the most used regimens to treat rare GU malignancies and highlights the need for prospective studies to determine the best frontline therapy. These results are being used to inform the design of a first-line clinical trial to evaluate the most efficacious therapy for these rare GU malignancies. Survey Choices Option 1 Option 2 Option 3 Option 4 Option 5 - write in Bladder SCC ITP CarboTaxolGem GemPlatinum ddMVAC Bladder Adenocarcinoma ITP FOLFOX FOLFOX+bev Gem-FLP SCBC EP EP + ICI IA-EP Penile SCC TIP Cis/5FU ICI Cetuximab Sex Cord Stromal Tumor BEP VIP Never treated ITP - ifosfamide, paclitaxel, and cisplatin; EP – etoposide/platinum; IA-EP – ifosfamide/Adriamycin-EP; Gem-FLP – gemcitabine, 5-FU, leucovorin, cisplatin.

Exploring the science and data foundation for Federal public lands decisions

Public lands provide diverse resources, values, and services worldwide. Laws and policies typically require consideration of science in public lands decisions, and resource managers are committed to science-informed decision-making. However, it can be challenging for managers to use, and document the use of, science and data in their decisions. To better understand science and data use in Federal public lands decisions in the United States, we assessed the number, type, and age of documents cited in 70 Environmental Assessments (EAs) completed by the Bureau of Land Management (BLM) in Colorado from 2015–2019. We focused on the BLM, as they manage the largest area of public lands in the United States. We selected Colorado as our study area, as actions proposed on BLM lands in Colorado are representative of those across the nation. Fifty percent of citations were categorized as science and 23% as data. EAs contained an average of 17 citations (range 0–111), with documents analyzing effects of oil and gas development and recreation actions including the highest and lowest mean number of citations (41 and 6, respectively). Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. Journal articles were the most cited type of document (26% of citations) followed by non-BLM inventories (13%). Forty-seven percent of citations were relatively recent (2010 or later); the oldest citation was from 1927. Commonly analyzed resources with the highest mean number of citations were socioeconomics, mineral resources, and noise. Fourteen of 33 commonly analyzed resources included <1 citation on average. Actions and resources with no or few citations represent opportunities for strengthening the transparent use of science and data in public lands decision-making.

Anti-colorectal cancer activity of constructed oleogels based on encapsulated bioactive canola extract in lecithin for edible semisolid applications

Abstract Globally, colorectal cancer ranks second in women and third in men. Hydrophilic anticancer agents have limited use in lipid systems due to their weak solubility. Therefore, this study aimed to develop oleogels based on pumpkin seed oil (R1) and hydrophilic bioactive canola extract (BCE or R2) that were extracted from canola meal by-products. BCE was effectively dispersed in oleogels through the encapsulation of BCE with various concentrations (0.08, 0.2, and 0.4%) in soy lecithin to form BCE gelling agents. Four formulations (F1 as plain, F2-F4 with different concentrations of BCE) were produced using two gelators (BCE gelling agent and beeswax). The oxidative stability, microstructure, FTIR, antioxidant activity, and time-dependent experiment were investigated. The cytotoxicity against colorectal HCT116 and Caco-2 cancer cell lines in vitro was evaluated. The anti-apoptotic PI3k and COX-2 protein expressions were also assessed. The peroxide, p-anisidine, and total oxidation values of F4 were 7.85, 26.66, and 42.35, respectively, during 60 days at 60 ± 2 °C. The antioxidant activity values of F4 were 74.40% for DPPH, 54.28% for ABTS, and 5.77 mg/g for FRAP. F4 demonstrated the highest significant cytotoxic effects on cancerous cells, particularly in the Caco-2 cells with 1.40- and 1.41-fold increases compared to R2 and the positive control doxorubicin, respectively. PI3k and COX-2 expression levels were down-regulated while iNOS activity was up-regulated in both cells, with very high down-regulation recorded for F4 in Caco-2 cells. This study developed a method for producing stable lipid products loaded with hydrophilic antioxidants that may be used as an anti-colorectal platform.

Real-world analysis of 2IR immune response score in urothelial carcinoma (UC).

739 Background: Immune checkpoint inhibition (ICI) is often used to treat UC, however many patients (pts) exhibit resistance. Using bulk RNA sequencing of pre-treatment tissue from ImVigor 210 and CheckMate 275 trials, an immune response score (2IR) was previously developed to predict ICI response by determining the comparative expression of genes involved in anti-tumorigenic adaptive immune response and pro-tumorigenic inflammation. Here, we evaluated the 2IR score as a prognostic or predictive biomarker in real-world pts with UC. Methods: Specimens from pts with UC (n = 6395) were profiled at Caris Life Sciences (Phoenix, AZ) using next generation sequencing (NGS) of DNA and RNA. 2IR was calculated by comparative RNA expression of 10 adaptive immune genes and 39 pro-tumorigenic genes. Tumors were classified as 2IR-Low (2IR ≤ -0.5), -Mid (-0.5 < 2IR < 0), and -High (2IR ≥ 0) as previously described. Spearman correlation analysis was utilized to compare 2IR with PD-L1 combined proportion score (CPS), tumor mutation burden (TMB), interferon score (IFN) and the tumor microenvironment (TME) cell fractions estimated using quanTIseq. Clinical outcomes included real-world overall survival (OS) from ICI start to last contact and time on treatment (ToT) with pembrolizumab, obtained via matched insurance claims data and calculated using Kaplan-Meier methods while Hazard ratio (HR) was calculated by Cox proportional model. Results: Of the 6395 UC samples, 9.5% (n = 611) were classified as 2IR-High, 42.7% (n=2730) 2IR-Mid, and 47.8% (n=3054) 2IR-Low. In pts with Upper Tract UC primary (UTUC, n = 1104), 2IR was comparatively lower than in pts with bladder cancer primary (BC, n = 4923) (median: -0.53 vs. -0.47, p < 0.001). 2IR shows a positive correlation with TMB (r = 0.23; p < 0.001), IFN score (r = 0.21; p < 0.001) and insignificant correlation with PD-L1 CPS (r = 0.09; p <0.001). 2IR-High positively correlated with mutations in TP53 , RB1 , and ARID1A (all p < 0.0001), amplification of ERBB2 (p < 0.0001), and microsatellite-instability high status (p < 0.0001), but not with FGFR3 mutations or fusions. 2IR positively correlated with immune cell fractions, such as CD4 + T (r = 0.09), CD8 + T (r = 0.22), and dendritic cell (r = 0.18), but negatively correlated with B cells (r = -0.06), M1 macrophages (r = -0.25), M2 macrophages (r = -0.08) and neutrophils (r = -0.12). Pts treated with 2IR-High tumors had longer ToT on pembrolizumab (HR = 0.65 CI 0.55 - 0.77, p <0.001) and OS from ICI start (HR = 0.51, CI 0.41 – 0.62, p < 0.001) compared to pts with 2IR-Low UC. This association held for both primary BC and UTUC. Conclusions: In a real-world cohort, we validate the 2IR score and suggest that it is prognostic for OS and predictive for pembrolizumab ToT, consistent with a positive correlation with known predictors of ICI response. Prospective studies are needed to further validate this biomarker for use in clinical practice, especially given the evolving UC treatment landscape.

Clinical use and outcomes of androgen-receptor pathway inhibitors triplet therapy for metastatic hormone-sensitive prostate cancer (ARAAT).

66 Background: In the pivotal phase 3 ARASENS trial, patients with metastatic hormone-sensitive prostate cancer (mHSPC) who received darolutamide in combination with androgen-deprivation therapy (ADT) + docetaxel (DOC) had longer overall survival (OS) vs ADT+DOC. Triplet therapy with darolutamide or abiraterone is recommended for high-risk patients with mHSPC; however, data on routine clinical use and outcomes of triplet therapy are lacking. Methods: This retrospective cohort analysis used the ConcertAI Patient360 database, a geographically diverse US oncology electronic medical record source. Adult patients with mHSPC who initiated triplet therapy with darolutamide+ADT+DOC (DAR) or abiraterone+ADT+DOC (ABI) from 1/2020–1/2024 were included. Outcomes included the proportion of patients achieving prostate-specific antigen (PSA) response (≥90% decline or undetectable levels <0.2 ng/mL), treatment discontinuation, progression to metastatic castration-resistant prostate cancer (mCRPC), and OS. PSA response during index treatment is reported at 6 and 12 months. Kaplan–Meier (K–M) estimated probability for discontinuation and progression to mCRPC are reported at 18 months. Results: A total of 243 patients initiated DAR (n=141) and ABI (n=102) for mHSPC. The median age was 66 years; 80% had an Eastern Cooperative Oncology Group performance status score of 0/1; and >80% completed ≥6 DOC cycles. The median baseline PSA was 36 ng/mL for DAR vs 20 ng/mL for ABI. Median follow-up duration was 16 months for the DAR cohort and 19 months for the ABI cohort. More patients in the DAR cohort achieved a PSA response at 6 and 12 months compared with those in the ABI cohort (Table). At 18 months, K–M probability of discontinuation was 25% for DAR vs 38% for ABI, and probability of progression to mCRPC was 24% for DAR vs 46% for ABI (Table). At the end of the follow-up period, 91% of patients in the DAR cohort were alive compared with 78% in the ABI cohort. Conclusions: Using a real-world dataset, treatment discontinuation rates, progression to mCRPC, and PSA responses were all favorable in patients with mHSPC receiving triplet therapy with DAR vs ABI. Further investigation is warranted. Key study outcomes. Key outcomes DAR (n=141) ABI (n=102) PSA drop ≥90% from baseline At 6 months* 90 (88.2%) 38 (65.5%) At 12 months † 94 (91.3%) 43 (74.1%) PSA drop to undetectable level (<0.2 ng/mL) At 6 months* 45 (44.1%) 19 (32.8%) At 12 months † 63 (61.2%) 27 (46.6%) K–M probability of treatment discontinuation at 18 months (95% CI) 0.245 (0.177−0.334) 0.376 (0.286−0.484) K–M probability of progression to mCRPC at 18 months (95% CI) 0.244 (0.175−0.335) 0.460 (0.358−0.574) For the PSA response analysis, patients were required to have baseline PSA ≥1 ng/mL and >1 ng/mL PSA test during index treatment. *At 6 months, DAR n=102; ABI n=58. † At 12 months, DAR n=103; ABI n=58. CI, confidence interval.

Patterns of next-generation sequencing and associated next-line systemic therapy use in metastatic prostate cancer.

105 Background: Next-generation sequencing (NGS) testing is used for prognostication and to guide treatment choice in metastatic prostate cancer (mPC). While NGS testing is increasingly available, how its usage has impacted real-world selection of next line therapies including olaparib in mPC is unclear. Methods: We performed a retrospective observational study using the real-world nationwide U.S. Flatiron Health electronic health record-derived de-identified mPC database with patients diagnosed between January 1 st , 2013, and July 30 th , 2024. Due to limitations of follow-up, patients diagnosed with mPC in 2024 were excluded. Rates of patients with documented NGS testing within 6 months of metastatic prostate cancer diagnosis, short-interval changes in systemic therapy defined as initiation of a new therapy within 30 days after NGS testing, and olaparib initiation within 60 days of NGS testing were analysed. Results: A total of 24,222 mPC patients were included, of which 6282 (25.94%)had at least 1 documented NGS test and 1494 (23.78%) of those patients had more than 1 NGS test. NGS test documentation after metastatic diagnosis increased from 0.175% in 2013 to 22.8% in 2023. The median time from metastatic diagnosis to initial NGS testing was 413 days (IQR 76-993). The percentage of NGS tests associated with short-interval initiation of a new line of therapy increased from 14.29% of patients receiving NGS testing in 2014 to 24.19% of patients receiving NGS testing in 2023. The most common therapies initiated within 30 days after NGS testing were abiraterone (37.75%), enzalutamide (13.91%), and docetaxel (10.93%). Among patients with documented NGS testing, the percent who initiated olaparib within 60 days of an NGS test increased from 0.31% in 2015 to 17.34% in 2024, with the greatest year-on-year increase in 2020 corresponding to FDA approval for patients with homologous recombination repair gene alterations. Median time to olaparib initiation after metastatic diagnosis was 798 days (IQR 455-1383). Conclusions: There was a significant increase in rates of documented NGS test for patients diagnosed with mPC over the past decade. Furthermore, systemic therapy change appears to be more frequently influenced by NGS testing, with a significant increase in associated olaparib initiation as next-line therapy.

Evaluation of a variant origin prediction (VOP) algorithm to distinguish clonal hematopoiesis (CH) variants from tumor-derived variants and to predict metastatic castrate resistant prostate cancer (mCRPC) clinical responses.

201 Background: VOPis an algorithm that predicts the cellular origin of variants, currently available on FoundationOneLiquid CDx (F1LCDx) for research use only. IMbassador250 (IM250, NCT03016312) is a completed phase III trial that evaluated the safety and efficacy of atezolizumab in combination with enzalutamide for men with mCRPC who had prior progression on abiraterone. Here, we evaluated the prediction accuracy and demonstrated clinical validity of VOP with IM250 samples. We hypothesized that excluding predicted CH variants from maximum variant allele frequency (maxVAF) calculations would strengthen the association of reduction of maxVAF and clinical outcome and lead to better on treatment risk stratification. Methods: We developed VOP, a machine learning algorithm that classifies short variants into tumor somatic, CH, and germline categories based on fragmentomics and other features. We applied VOP to banked IM250 plasma samples from cycle 1 day 1 (C1D1) and cycle 3 day 1 (C3D1, 6 weeks on treatment) timepoints profiled by F1LCDx, and sequenced matched whole blood (WB) from a subgroup of patients to definevariant origin ground truth for an accuracy assessment. To assess clinical validity of VOP, we calculated maxVAF with and without filtering out CH variants predicted by VOP and assessed its association with clinical outcome. Results: Based on over 2,700 short variants in 221 patients with matched WB as truth, VOP achieved a positive percent agreement (PPA) of 92% and positive predicted value (PPV) of 94% for tumor somatic variant predictions (median VAF 3.6%). PPA and PPV were 90% and 88%, respectively, for CH variant predictions (median VAF 0.7%), and over 98% for germline variant predictions, consistent with past development data based on a pan-cancer cohort. To assess potential clinical impact, we applied VOP to 422 patients with F1LCDx results at both C1D1 and C3D1. Patients with at least 50% decrease in maxVAF were associated with longer overall survival. Importantly, CH-adjusted maxVAF led to better patient stratification (Hazard Ratio (HR) = 0.36 [0.28, 0.47], p = 0.0007) than non-CH-adjusted maxVAF (HR = 0.60 [0.45, 0.81], p < 0.0001). We observed similar results using cutoffs of 90% and 100% (ctDNA clearance) decrease in maxVAF and with radiographic progression-free survival as the endpoint. Conclusions: VOP had strong analytical concordance and clinical applicability in an independent mCRPC cohort (IM250). With the aid of VOP, CH-adjusted maxVAF more effectively identifies patients with better outcomes. The VOP algorithm is accurate, robust, and has potential clinical use in tumor monitoring, clinical outcomes and on treatment patient risk stratification.

Family correlates of behavioral problems among adolescents in Rwanda

Background Globally, 20% of adolescents exhibit behavioral problems. Behavioral problems are associated with individual and environmental factors. However, little is known about the contribution of the nuclear family to the development of behavioral problems in adolescents from sub-Saharan Africa. This study aimed to explore family-based correlates influencing behavioral problems among adolescents in Rwanda. Methods With an institutional-based cross-sectional study design, a convenience sample of 158 participants {107 males and 51 females; Mean age (M) = 16.96, Standard Deviation (SD) = 1.86; age ranging from 13 to 23 years} was selected in secondary schools in the Nyarugenge district. Participants filled out Behavioral Problems Scale (BPS), Child and Adolescent Trauma Screen (CATS), University of California, Los Angeles Loneliness Scale (UCLA Loneliness Scale), Multidimensionality of Perceived Social Support Scale (MSPSS), Multidimensional Neglectful Behavior Scale (MNBS), and Paediatric Quality of Life Enjoyment and Satisfaction Questionnaire (PQ-LES-Q) to record pertinent scores. Socio-demographic information was also collected. SPSS version 24 was used for statistical analysis. Results Females exhibited more behavioral problems than males. Child and adolescent trauma (β = 0.705, t = 8.21, p < .001) and neglect (β = 0.147 t = 2.15, p < .05) were two significant family correlates in our sample. Poor quality of life enjoyment and satisfaction, loneliness, and poor parental perceived social support were not identified as family-based factors that influence behavioral problems in our sample. Conclusions Results highlighted the importance of implementing family and community-based interventions to sustain family well-being, change parenting behaviors, and help children and adolescents adopt positive behaviors.

BO-CLAHE enhancing neonatal chest X-ray image quality for improved lesion classification

Abstract In the case of neonates, especially low birth weight preterm and high-risk infants, portable X-rays are frequently used. However, the image quality of portable X-rays is significantly lower compared to standard adult or pediatric X-rays, leading to considerable challenges in identifying abnormalities. Although attempts have been made to introduce deep learning to address these image quality issues, the poor quality of the images themselves hinders the training of deep learning models, further emphasizing the need for image enhancement. Additionally, since neonates have a high cell division rate and are highly sensitive to radiation, increasing radiation exposure to improve image quality is not a viable solution. Therefore, it is crucial to enhance image quality through preprocessing before training deep learning models. While various image enhancement methods have been proposed, Contrast Limited Adaptive Histogram Equalization (CLAHE) has been recognized as an effective technique for contrast-based image improvement. However, despite extensive research, the process of setting CLAHE’s hyperparameters still relies on a brute force, manual approach, making it inefficient. To address this issue, we propose a method called Bayesian Optimization CLAHE(BO-CLAHE), which leverages Bayesian optimization to automatically select the optimal hyperparameters for X-ray images used in diagnosing lung diseases in preterm and high-risk neonates. The images enhanced by BO-CLAHE demonstrated superior performance across several classification models, with particularly notable improvements in diagnosing Transient Tachypnea of the Newborn (TTN). This approach not only reduces radiation exposure but also contributes to the development of AI-based diagnostic tools, playing a crucial role in the early diagnosis and treatment of preterm and high-risk neonates.