The consistency of neuropathological diagnoses in patients undergoing surgery for suspected recurrence of glioblastoma.

PURPOSE: Clinical factors and neuro-imaging in patients with glioblastoma who appear to progress following standard chemoradiation are unable to reliably distinguish tumor progression from pseudo-progression. As a result, surgery is commonly recommended to establish a final diagnosis. However, studies evaluating the pathologists' agreement on pathologic diagnoses in this setting have not been previously evaluated. METHODS: A hypothetical clinical history coupled with images of histological sections from 13 patients with glioblastoma who underwent diagnostic surgery for suspected early recurrence were sent to 101 pathologists from 50 NCI-designated Cancer Centers. Pathologists were asked to provide a final diagnosis (active tumor, treatment effect, or unable to classify) and to report on percent active tumor, treatment effect, and degree of cellularity and degree of mitotic activity. RESULTS: Forty-eight pathologists (48%) from 30 centers responded. In three cases > 75% of pathologists diagnosed active tumor. In two cases > 75% diagnosed treatment effect. However, in the remaining eight cases the disparity in diagnoses was striking (maximum agreement on final diagnosis ranged from 36 to 68%). Overall, only marginal agreement was observed in the overall assessment of disease status [kappa score 0.228 (95% CI 0.22-0.24)]. CONCLUSIONS: Confidence in any clinical diagnostic assay requires that very similar results are obtained from identical specimens evaluated by sophisticated clinicians and institutions. The findings of this study illustrate that the diagnostic agreement between different cases of repeat resection for suspected recurrent glioblastoma can be variable. This raises concerns as pathological diagnoses are critical in directing standard and experimental care in this setting.

Temporal trends and racial/ethnic disparity in self-reported pediatric food allergy in the United States.

BACKGROUND: The prevalence of food allergy is thought to be increasing, but data from the United States have not been systematically synthesized. OBJECTIVE: To summarize the data on prevalence of food allergy in the US pediatric population and to estimate the effects of time, race/ethnicity, and method of assessing food allergy on the estimated prevalence. METHODS: Embase, MEDLINE, bibliographies of identified reports, and data from publically available data sets were searched. Studies were limited to those in English with data from the general pediatric US population. Study synthesis was performed by meta-analysis and meta-regression to estimate the effect of study- and participant-level covariates. Meta-regression was limited to nationally representative surveys conducted by the Centers for Disease Control and Prevention. RESULTS: A total of 10,090 publications were identified, from which 27 different survey administrations, representing 452,237 children, were identified, covering the period of 1988 to 2011. Because of heterogeneity among surveys in the estimated food allergy prevalence, a summary estimate of food allergy prevalence was not possible. Meta-regression was performed using 20 of these surveys. Temporal trends were pronounced, with an estimated increased prevalence of self-reported food allergy of 1.2 percentage points per decade (95% confidence interval [CI], 0.7-1.6). The increase per decade varied by race/ethnicity: 2.1% among non-Hispanic blacks (95% CI, 1.5%-2.7%), 1.2% among Hispanics (95% CI, 0.7%-1.7%), and 1.0% among non-Hispanic whites (95% CI, 0.4%-1.6%). CONCLUSION: Self-report of food allergy among US children has sharply increased in the past 2 decades. The increase has been greatest among non-Hispanic black children, a disparity that needs to be investigated.

Enhanced Cohort Methods for HIV Research and Epidemiology (ENCORE): Protocol for a Nationwide Hybrid Cohort for Transgender Women in the United States.

BACKGROUND: In the United States, transgender women are disproportionately impacted by HIV and prioritized in the national strategy to end the epidemic. Individual, interpersonal, and structural vulnerabilities underlie HIV acquisition among transgender women and fuel syndemic conditions, yet no nationwide cohort monitors their HIV and other health outcomes. OBJECTIVE: Our objective is to develop a nationwide cohort to estimate HIV incidence, identify risk factors, and investigate syndemic conditions co-occurring with HIV vulnerability or acquisition among US transgender women. The study is informed by the Syndemics Framework and the Social Ecological Model, positing that stigma-related conditions are synergistically driven by shared multilevel vulnerabilities. METHODS: To address logistical and cost challenges while minimizing technology barriers and research distrust, we aim to establish a novel, hybrid community hub-supported digital cohort (N=3000). The digital cohort is the backbone of the study and is enhanced by hubs strategically located across the United States for increased engagement and in-person support. Study participants are English or Spanish speakers, are aged ≥18 years, identify as transgender women or along the transfeminine spectrum, reside in 1 of the 50 states or Puerto Rico, and do not have HIV (laboratory confirmed). Participants are followed for 24 months, with semiannual assessments. These include a questionnaire and laboratory-based HIV testing using self-collected specimens. Using residential zip codes, person-level data will be merged with contextual geolocated data, including population health measures and economic, housing, and other social and structural factors. Analyses will (1) evaluate the contribution of hub support to the digital cohort using descriptive statistics; (2) estimate and characterize syndemic patterns among transgender women using latent class analysis; (3) examine the role of contextual factors in driving syndemics and HIV prevention over time using multilevel regression models; (4) estimate HIV incidence in transgender women and examine the effect of syndemics and contextual factors on HIV incidence using Poisson regression models; and (5) develop dynamic, compartmental models of multilevel combination HIV prevention interventions among transgender women to simulate their impact on HIV incidence through 2030. RESULTS: Enrollment launched on March 15, 2023, with data collection phases occurring in spring and fall. As of February 24, 2024, a total of 3084 individuals were screened, and 996 (32.3%) met the inclusion criteria and enrolled into the cohort: 2.3% (23/996) enrolled at a hub, and 53.6% (534/996) enrolled through a community hub-supported strategy. Recruitment through purely digital methods contributed 61.5% (1895/3084) of those screened and 42.7% (425/996) of those enrolled in the cohort. CONCLUSIONS: Study findings will inform the development of evidence-based interventions to reduce HIV acquisition and syndemic conditions among US transgender women and advance efforts to end the US HIV epidemic. Methodological findings will also have critical implications for the design of future innovative approaches to HIV research. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59846.