Citations

6636 Background: Equitable regional enrollment in clinical trials is critical to addressing global inequities in health care outcomes. Therefore, we quantified disparities in regional recruitment in global cancer trials. Methods: Phase II/III clinical trials in prostate (PC), breast (BC), colorectal (CRC) and lung cancer (LC), and reporting regional recruitment were identified from Medline. Global regions were defined as North-(NA) and South- America (SA), Europe (EU), Africa (AF), Asia (AS), and Australia (AU). For multi-regional trials, enrollment incidence ratios (EIR) which compare region-wise trial enrollment against global estimates of region-wise specific cancer incidence obtained from Global Burden of Disease 2019 database. Trial-level EIRs were pooled using random-effects meta-analysis. A pooled EIR of < 1.0 indicates underrepresentation of a particular region in clinical trial enrollment compared to the actual burden of the specific cancer in that region. Statistical analyses were conducted in R v4.1.2. Results: Of the total 2125 trials identified, 1681 (79.1%) trials with 691,800 participants reported information regarding regional recruitment. Among those, only 1400 (65.9%) trials reported proportions of patients from pre-defined regions. A total of 1231 (57.9%) trials were single-regional recruiting patients from EU (589; 47.8%), NA (329; 26.7%), AS (295; 23.9%), AU (10; 0.8%), AF (4; 0.3%), and SA (4; 0.3%). There was significant underrepresentation of patients from AS (EIR: 0.47; 95% CI: 0.41-0.54) in cancer clinical trials. This was consistent across different cancers: PC (0.49; 0.35-0.71), BC (0.63; 0.43-0.94), CRC (0.63; 0.43-0.94), LC (0.39; 0.30-0.50). Similarly, there is a trend of under-representation of patients from AF (0.67; 0.43-1.04). Consistently, patients from were under-represented in PC (0.43; 0.24-0.77) and LC (0.26; 0.09-0.79) trials. Patients from NA (1.27; 1.08-1.51), EU (1.64; 1.57-1.72), and AU (5.41; 3.90-7.51) were significantly over-represented in multi-regional cancer clinical trials. The results are provided in table. Conclusions: There is suboptimal reporting of region-wise enrollment in cancer clinical trials. Representation of Africa and Asia in cancer clinical trials appears to be less than their expected share based on their burden of cancer incidence. [Table: see text]

6559 Background: Recent findings that Black and Hispanic patients were significantly underrepresented in industry-sponsored prostate cancer trials warrant a detailed investigation across cancer types to assess the association between funding source and enrollment disparities. Methods: Phase II/III clinical trials in prostate, breast, colorectal, and lung cancers reporting age, gender, race/ethnicity, and reporting NIH or industry as the funding source were considered eligible for inclusion. For age, and gender analysis, all trials were considered eligible. For race/ethnicity analysis, trials recruiting from the United States (US) were considered eligible. Enrollment-incidence ratios (EIR) comparing trial proportion from age/gender or racial/ethnic subgroups against global cancer incidence in the corresponding group (from Global Burden of Disease) or US-population-based incidence in the corresponding racial/ethnic subgroup (from SEER 22), were computed. Trial-level EIRs were pooled using a random-effects model and subsequently stratified by funding source. A univariate meta-regression was conducted to assess the temporal changes in EIR by each funding category. Results: Of 42,390 studies initially identified, 2234 trials (1989-2021) met the eligibility criteria. Regarding age, 361 (16%) trials reported age categories by 65 years threshold. Of 698 trials recruiting from the US, 498 (71%) reported race, and 198 (28%) reported ethnicity. Regarding representation, older adults were under-represented (EIR: 0.66; 95% CI: 0.62-0.70) in the industry but not in NIH-sponsored clinical trials (0.79; 0.62-1.00). Regarding gender, no significant disparity was observed regarding the enrollment of men and women in colorectal and lung cancer clinical trials. In terms of race, there was a greater under-representation of Black patients in industry sponsored trials (0.29; 0.26-0.32) as compared to NIH-sponsored clinical trials (0.65; 0.57-0.74) [Pint <0.01]. Asian patients were significantly overrepresented in industry sponsored trials (3.17; 2.69-3.74) but not in NIH sponsored clinical trials (1.43; 0.85-2.41) [Pint <0.01]. Hispanic patients were significantly under-represented in both, industry (0.27; 0.22-0.34) and NIH-sponsored clinical trials (0.35; 0.22-0.55) [Pint 0.32]. Secondary analyses including trials recruiting exclusively from the US, and analyses by specific cancer types showed consistent results. Recruitment of older adults, men, and Black patients is decreasing over time. Conclusions: There is a consistent under-representation of older adults in industry-sponsored, and of Black and Hispanic patients in both industry-sponsored and NIH-sponsored clinical trials. The under-representation of Black patients is likely to be greater in industry-sponsored trials, which has worsened over the last three decades.

6557 Background: Trials that inadequately include underrepresented minority (URM) populations widen inequities in cancer care. We assessed reporting patterns, representation, and trends of URM representation in breast cancer (BC) trials. Methods: We analyzed all phase 2/3 trials for age disparity and trials recruiting from the US for racial/ethnic disparity amongst BC RCTs (1990-2021). Enrollment-incidence ratios (EIR), which compare trial proportions (TP) from age subgroups against global estimates of incidence in the corresponding age group (from Global Burden of Disease) and racial/ethnic subgroups against US-population-based incidence in the corresponding racial/ethnic group (from SEER 22), were calculated. Individual-trial EIRs were pooled using random-effects meta-analyses. EIRs of <0.80 indicated meaningful underrepresentation, while EIRs >1.20 indicated meaningful overrepresentation. Meta-regression was used to explore associations between key trial characteristics and EIR, and trends in EIR over the last three decades. Results: Of 842 global trials with 490,657 participants, 232 (27.6%) reported the number of participants in specific age strata and 144 (17.1%) reported outcomes by age. Only 60 trials recruited exclusively from the US. Of these, 41 (68.3%) reported race and 24 (40.0%) reported ethnicity, and 2 (3.3%) analyzed outcomes by race. Older adults aged ≥65 years (TP: 24.3%; EIR: 0.53 [95% CI: 0.47-0.60]) and Hispanic women (TP: 5.3%; 0.54; 0.40-0.75) were underrepresented across global trials and US-only trials respectively. Black women were significantly underrepresented in trials that led to FDA approval (0.38; 0.25-0.58) but not in US-only trials. Stratified analysis by BC subtype (with subtype-specific population incidence) showed underrepresentation of Black women in US-only trials for HER2+ BC (0.66; 0.47-0.93), Hispanic women in ER+ BC (0.42; 0.20-0.90), Asians in triple-negative BC (0.24; 0.11-0.53), and older women in HER2+ BC (0.35; 0.31-0.40) and triple-negative BC (0.36; 0.29-0.45). From 1990-2021, the representation of older women declined significantly (meta-regression coefficient for EIR: -0.4 per 10 years), while Black and Hispanic representation showed no significant change. Black (p = 0.02) and Hispanic representation (p = 0.05) worsened significantly in larger trials. Conclusions: Published reports of BC trials do not consistently report the inclusion of URM. Older and Hispanic women were consistently underrepresented, whereas Black women were underrepresented in large, practice-changing trials. [Table: see text]

5088 Background: Previous evidence suggests that there may be no additional benefit of triplet therapy in low volume disease based on limited data. Therefore, we investigated the efficacy of triplet therapy as compared to docetaxel (D) and androgen pathway inhibitor (API) doublets by volume of disease using the most up to date results from the ARASENS trial. Methods: Phase III randomized controlled trials (RCTs) assessing treatment intensification with API, and/or D in patients with mCSPC were included. Precomputed hazard ratios (HR) with 95% confidence intervals (CI) for OS were pooled using an inverse-variance approach. A DerSimonian-Laird random-effects meta-analysis was conducted to assess the efficacy of triplet therapy compared to D doublet therapy. P-value of interaction was computed to assess difference between high (HV) and low volume (LV) disease subgroups (Pint <0.1 - statistical significance). Additionally mixed treatment comparisons were computed using network meta-analysis (NMA) to assess the comparative effectiveness of triplet therapy compared to API doublets by volume of disease. Results: Pairwise meta-analysis included a total of 3 RCTs (ARASENS, PEACE-1, ENZAMET) with 2518 patients (HV: 1820; LV: 698) as shown. In patients with HV disease, 385 (43%) and 484 (53%) deaths were observed with triplet therapy, and D doublet, respectively. Triplet therapy significantly improved OS as compared to D doublet in HV (HR: 0.73; 95% CI: 0.64-0.84). In patients with LV disease, 73 (20%) and 94 (28%) deaths were observed with triplet therapy, and D doublet, respectively. Triplet therapy significantly improved OS as compared to D doublet in LV (HR: 0.71; 95% CI: 0.52-0.97). There was no statistically significant interaction by volume of disease for triplet therapy vs. D doublet (Pint: 0.86). NMA including 10 clinical trials and over 11500 patients updated as of 13th Feb 2023 showed that in HV mCSPC, triplet therapy was ranked as potentially the most efficacious treatment option and may improve OS compared to API doublet therapy (HR: 0.83; 95% CI: 0.66-1.03). In LV mCSPC, API doublet therapy was ranked as potentially the most efficacious treatment followed by triplet therapy. There was no significant difference between triplet therapy and API doublet therapy (HR: 1.12; 95% CI: 0.74-1.12). Conclusions: These results underscore that triplet therapy may be preferred in mCSPC patients with HV disease whereas API doublet therapy may be preferred in LV disease. [Table: see text]

Abstract Mitochondria respond to metabolic demands of the cell and to incremental damage, in part, through dynamic structural changes that include fission (fragmentation), fusion (merging of distinct mitochondria), autophagic degradation (mitophagy), and biogenic interactions with the endoplasmic reticulum (ER). High resolution study of mitochondrial structural and functional relationships requires rapid preservation of specimens to reduce technical artifacts coupled with quantitative assessment of mitochondrial architecture. A practical approach for assessing mitochondrial fine structure using two dimensional and three dimensional high‐resolution electron microscopy is presented, and a systematic approach to measure mitochondrial architecture, including volume, length, hyperbranching, cristae morphology, and the number and extent of interaction with the ER is described. These methods are used to assess mitochondrial architecture in cells and tissue with high energy demand, including skeletal muscle cells, mouse brain tissue, and Drosophila muscles. The accuracy of assessment is validated in cells and tissue with deletion of genes involved in mitochondrial dynamics.

Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision‐making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studies employing ML in hypertension research is growing rapidly. In this study, we aimed to survey hypertension research using ML, evaluate the reporting quality, and identify barriers to ML's potential to transform hypertension care. Methods and Results The Harmonious Understanding of Machine Learning Analytics Network survey questionnaire was applied to 63 hypertension‐related ML research articles published between January 2019 and September 2021. The most common research topics were blood pressure prediction (38%), hypertension (22%), cardiovascular outcomes (6%), blood pressure variability (5%), treatment response (5%), and real‐time blood pressure estimation (5%). The reporting quality of the articles was variable. Only 46% of articles described the study population or derivation cohort. Most articles (81%) reported at least 1 performance measure, but only 40% presented any measures of calibration. Compliance with ethics, patient privacy, and data security regulations were mentioned in 30 (48%) of the articles. Only 14% used geographically or temporally distinct validation data sets. Algorithmic bias was not addressed in any of the articles, with only 6 of them acknowledging risk of bias. Conclusions Recent ML research on hypertension is limited to exploratory research and has significant shortcomings in reporting quality, model validation, and algorithmic bias. Our analysis identifies areas for improvement that will help pave the way for the realization of the potential of ML in hypertension and facilitate its adoption.

Abstract Cellular senescence has been identified as a pathological mechanism linked to tau and amyloid beta (Aβ) accumulation in mouse models of Alzheimer's disease (AD). Clearance of senescent cells using the senolytic compounds dasatinib (D) and quercetin (Q) reduced neuropathological burden and improved clinically relevant outcomes in the mice. Herein, we conducted a vanguard open-label clinical trial of senolytic therapy for AD with the primary aim of evaluating central nervous system (CNS) penetrance, as well as exploratory data collection relevant to safety, feasibility, and efficacy. Participants with early-stage symptomatic AD were enrolled in an open-label, 12-week pilot study of intermittent orally-delivered D+Q. CNS penetrance was assessed by evaluating drug levels in cerebrospinal fluid (CSF) using high performance liquid chromatography with tandem mass spectrometry. Safety was continuously monitored with adverse event reporting, vitals, and laboratory work. Cognition, neuroimaging, and plasma and CSF biomarkers were assessed at baseline and post-treatment. Five participants (mean age: 76±5 years; 40% female) completed the trial. The treatment increased D and Q levels in the blood of all participants ranging from 12.7 to 73.5 ng/ml for D and 3.29-26.30 ng/ml for Q. D levels were detected in the CSF of four participants ranging from 0.281 to 0.536 ng/ml (t(4)=3.123, p=0.035); Q was not detected. Treatment was well-tolerated with no early discontinuation and six mild to moderate adverse events occurring across the study. Cognitive and neuroimaging endpoints did not significantly differ from baseline to post-treatment. CNS levels of IL-6 and GFAP increased from baseline to post-treatment (t(4)=3.913, p=008 and t(4)=3.354, p=0.028, respectively) concomitant with decreased levels of several cytokines and chemokines associated with senescence, and a trend toward higher levels of Aβ42 (t(4)=-2.338, p=0.079). Collectively the data indicate the CNS penetrance of D and provide preliminary support for the safety, tolerability, and feasibility of the intervention and suggest that astrocytes and Aβ may be particularly responsive to the treatment. While early results are promising, fully powered, placebo-controlled studies are needed to evaluate the potential of AD modification with the novel approach of targeting cellular senescence.

AbstractBackgroundThe accuracy of the eighth AJCC ypTNM staging system on the prognosis of gastric cancer (GC) patients after neoadjuvant therapy (NAT) is controversial. This study aimed to develop and validate a novel staging system using the log odds of positive lymph nodes scheme (LODDS).MethodsA retrospective analysis of 606 GC patients who underwent radical gastrectomy after neoadjuvant therapy was conducted as the development cohort. (Fujian Medical University Affiliated Union Hospital (n = 183), Qinghai University Affiliated Hospital (n = 169), Mayo Clinic (n = 236), Lanzhou University First Hospital (n = 18)). The validation cohort came from the SEER database (n = 1701). A novel ypTLoddsS (ypTLM) staging system was established using the 3‐year overall survival. The predictive performance of two systems was compared. ResultsTwo‐step multivariate Cox regression analysis in both cohorts showed that ypTLM was an independent predictor of overall survival of GC patients after neoadjuvant therapy (HR: 1.57, 95% CI: 1.30–1.88, p < 0.001). In the development cohort, ypTLM had better discrimination ability than ypTNM (C‐index: 0.663 vs 0.633, p < 0.001), better prediction homogeneity (LR: 97.7 vs. 70.9), and better prediction accuracy (BIC: 3067.01 vs 3093.82; NRI: 0.36). In the validation cohort, ypTLM had a better prognostic predictive ability (C‐index: 0.614 vs 0.588, p < 0.001; LR: 11,909.05 vs. 11,975.75; BIC: 13,263.71 vs 13,328.24; NRI: 0.22). The time‐dependent ROC curve shows that the predictive performance of ypTLM is better than ypTNM, and the analysis of the decision curve shows that ypTLM achieved better net benefits. ConclusionA LODDS‐based ypTLM staging system based on multicenter data was established and validated. The predictive performance was superior to the eighth AJCC ypTNM staging system.