Citations

694 Background: The treatment landscape of localized renal cell carcinoma (RCC) is rapidly evolving. Recent trials have demonstrated contrasting efficacy with adjuvant immunotherapy. Therefore, we sought to assess the mixed treatment comparisons among different adjuvant treatment options using updated data from trials and quantified the absolute effect with these treatments stratified by risk categories. Methods: This living network meta-analysis was conducted using the living interactive evidence (LIvE) synthesis framework. We used stratified baseline risks of disease progression from observational data and at 5, 10, 15 years from the Leibovich risk stratification system (based on risk scores ranging from 0 to ≥15). Corresponding intervention risks were then approximated using relative effect estimates (from NMA) and baseline risks. The difference between CIRs and baseline risks were calculated to present absolute risk differences in each risk category. Results: This NMA included eight RCTs with 8480 participants and seven unique treatment options. Pembrolizumab (pembro; rank 1) was associated with improved disease-free survival (DFS) when compared to atezolizumab (atezo; rank 6; hazard ratio: 0.68; 0.49;0.93), and nivolumab-ipilimumab (nivoipi; rank 5; 0.68; 0.48-0.97). However, no statistically significant difference was observed between pembro and atezo for overall survival (0.53; 0.28-1.01). Survival data for nivoIpi was not reported. No new statistically significant differences were observed since last update. The absolute benefit of atezo and nivoipi was minimal with higher T and N patients (Table). The results were similar with increasing Leibovich risk scores. Conclusions: Current evidence favors the use of a risk adapted approach when offering adjuvant immunotherapy. Adjuvant pembrolizumab remains a preferred treatment in patients with RCC who underwent nephrectomy. [Table: see text]

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.

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.

23 Background: Identification of factors associated with enrollment disparities in clinical trials can narrow cancer care inequities. Funding source can influence minority representation in clinical trials. Therefore, we aimed to assess the impact of funding sources on enrollment disparities in colorectal (CRC) clinical trials. Methods: CRC phase II/III randomized controlled trial (RCTs) identified through MEDLINE and EMBASE from each database’s inception through 2022 were considered eligible. Trial level enrollment incidence ratios (EIR) were computed; defined as the ratio of trial proportions of a gender, age, or racial/ethnic subgroup category and the global incidence in the corresponding gender/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). EIRs were then meta-analyzed using a random-effects model for each funding source category (US- government, industry, others). Temporal trends were analyzed using a univariate meta-regression. Results: Using data from 287 RCTs, women were significantly under-represented in the industry sponsored trials (EIR: 0.85 [95% CI: 0.83 - 0.88]) but not in US-government sponsored trials (0.92 [0.84-1.00]). A total of 87 RCTs reported age proportions; older adults (above 65 years) were significantly under-represented in the industry sponsored (0.84 [0.74-0.96]) and as well as in US-government sponsored CRC trials (0.52 [0.44-0.61]). Only 56 and 15 trials reported race and ethnicity, respectively. Limited data on racial/ethnic enrollment revealed significant under-representation of Black (0.45 [0.36 -0.57]) and Hispanic (0.45 [0.31-0.66]) patients across industry sponsored CRC trials. In contrast, no significant disparity was observed in the inclusion of Asian race in the industry sponsored trials. The number of US-government sponsored trials reporting racial/ethnic subgroups were small ( < 10) which precluded any meaningful statistics. Trends show that the representation of women has improved ( P: 0.02) while the representation of Black ( P: 0.007) and Hispanic patients ( P: 0.04) has worsened over the last three decades in industry sponsored CRC trials. Conclusions: The reporting of race/ethnicity is suboptimal in CRC trials especially in those sponsored by US government. Older adults may be under-represented regardless of funding source. Women, Blacks and Hispanics may be under-represented in industry sponsored CRC clinical trials. While representation of women appears to be improving, representation of Black and Hispanic patients has worsened in industry sponsored CRC clinical trials over the last three decades.

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.

Abstract The relative inaccessibility of a patient’s glioma throughout their disease course precludes individualized insights into tumor biology and responses thereof to therapeutic challenge. We propose that serial cerebrospinal fluid (CSF) samples can be used to perform glioma espionage in the form of biomarker discovery for analytes that are sensitive to tumor burden (for monitoring) and candidate therapies (for biological impact). To that end, we are routinely leveraging neurosurgical access to the CNS to collect CSF samples intraoperatively and from chronically implanted Ommaya reservoirs for longitudinal CSF access (NCT04692337, NCT04692324). Global proteomic analysis of CSF was performed on the Somalogic platform – an aptamer-based technology for highly sensitive and specific analysis of over 7,000 proteins. Using each patient’s ranked protein list (glioma vs. 3 control patients), enrichment analysis was performed in a discovery cohort of five patients to identify conserved proteins of glioma. To reveal candidate glioma monitoring, further enrichment analysis was performed to identify proteins that decreased with resection and increased with recurrence, using two sets of paired patient samples. Forty-four proteins met these enrichment criteria; this candidate high-grade glioma proteomic signature was highly significantly enriched in an independent cohort of twelve glioma patients (FDR=0 for all patients). The HGG signature decreased in abundance following resection in serial samples from two other patients, confirming decreased tumor burden. Top proteins included LANC2, DPYL3, Sorcin, Integrin A1B1, and lactate dehydrogenase (FC of glioma vs. control: 145.3x, 113.9x, 78.0x, 71.6x, and 62.7x, respectively). Interestingly, despite having explicitly chosen samples with little-to-no hemoglobin in the discovery cohort, this HGG signature was highly enriched for plasma-like proteins (FDR=0), suggesting a potential biological impact of blood-brain barrier disruption on the glioma extracellular proteome. In conclusion, our data demonstrate that the glioma extracellular proteome can feasibly be accessed to perform biomarker discovery (“espionage”) via serially-acquired CSF samples.

Background. Acute kidney injury (AKI) is a well-known complication following a transcatheter aortic valve replacement (TAVR) and is associated with higher morbidity and mortality. Objective. We aim to compare the risk of developing AKI after transfemoral (TF), transapical (TA), and transaortic (TAo) approaches following TAVR. Methods. We searched Medline and EMBASE databases from January 2009 to January 2021. We included studies that evaluated the risk of AKI based on different TAVR approaches. After extracting each study’s data, we calculated the risk ratio and 95% confidence intervals using RevMan software 5.4. Publication bias was assessed by the forest plot. Results. Thirty-six (36) studies, consisting of 70,406 patients undergoing TAVR were included. Thirty-five studies compared TF to TA, and only seven investigations compared TF to TAo. AKI was documented in 4,857 out of 50,395 (9.6%) patients that underwent TF TAVR compared to 3,155 out of 19,721 (16%) patients who underwent TA-TAVR, with a risk ratio of 0.49 (95% CI, 0.36–0.66; p < 0.00001 ). Likewise, 273 patients developed AKI out of the 1,840 patients (14.8%) that underwent TF-TAVR in contrast to 67 patients out of the 421 patients (15.9%) that underwent TAo-TAVR, with a risk ratio of 0.51 (95% CI, 0.27–0.98; p = 0.04). There was no significant risk when we compared TA to TAo approaches, with a risk ratio of 0.89 (95% CI, 0.29–2.75; p = 0.84). Conclusion. The risk of post-TAVR AKI is significantly lower in patients who underwent TF-TAVR than those who underwent TA-TAVR or TAo-TAVR.

Genome-wide association studies (GWASs) have identified genetic loci associated with the risk of Alzheimer’s disease (AD), but the molecular mechanisms by which they confer risk are largely unknown. We conducted a metabolome-wide association study (MWAS) of AD-associated loci from GWASs using untargeted metabolic profiling (metabolomics) by ultraperformance liquid chromatography–mass spectrometry (UPLC-MS). We identified an association of lactosylceramides (LacCer) with AD-related single-nucleotide polymorphisms (SNPs) in ABCA7 ( P = 5.0 × 10 −5 to 1.3 × 10 −44 ). We showed that plasma LacCer concentrations are associated with cognitive performance and genetically modified levels of LacCer are associated with AD risk. We then showed that concentrations of sphingomyelins, ceramides, and hexosylceramides were altered in brain tissue from Abca7 knockout mice, compared with wild type (WT) ( P = 0.049–1.4 × 10 −5 ), but not in a mouse model of amyloidosis. Furthermore, activation of microglia increases intracellular concentrations of hexosylceramides in part through induction in the expression of sphingosine kinase, an enzyme with a high control coefficient for sphingolipid and ceramide synthesis. Our work suggests that the risk for AD arising from functional variations in ABCA7 is mediated at least in part through ceramides. Modulation of their metabolism or downstream signaling may offer new therapeutic opportunities for AD.

Background: Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent. Objective: To study the cross-sectional associations of pulmonary function with structural brain variables. Methods: Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses. Results: FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume. Conclusion: In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.

Abstract INTRODUCTION Rapid, detailed feedback is needed to understand the individualized biological impacts of novel glioma therapies. We are performing glioma biomarker discovery by serial cerebrospinal fluid (CSF) sampling from Ommaya reservoirs to determine how the CSF proteome can reveal early longitudinal intelligence regarding glioma status, biology, and therapeutic response. METHODS Global proteomic analysis of CSF was performed on the Somalogic platform − an aptamer-based technology for highly sensitive and specific analysis of over 7,000 proteins. Discovery analysis comprised of the top-500 ranked proteins in CSF from seven patients with high-grade gliomas (HGG) versus non-glioma controls. The top-500 HGG proteins were then preliminarily filtered to include only proteins that met two additional criteria of decrease with resection and increase with recurrence in individual paired patient samples. RESULTS Proteomic enrichment analysis revealed a conserved HGG CSF proteomic signature defined by 79 proteins, including ones known to be over-expressed in solid tumor malignancies, such as retinoblastoma binding protein 4, heat shock protein 90, and sorcin. The HGG proteomic signature was consistently enriched in an independent validation cohort consisting of 13 gliomas diverse in primary versus recurrent status, subtype, and grade, when compared to control CSF samples. Encouragingly, proteins in the HGG signature decreased in the two patients for whom CSF was collected prior to and after resection (both at POD16 and POD18) with decreased tumor burden. CONCLUSION Our preliminary data demonstrate the ability to gain detailed, individualized insights regarding glioma biology, tumor burden, and evolution through global CSF proteomics acquired from longitudinal neurosurgical access to unique gliomas.