Racial Disparities in Cancer Stage at Diagnosis and Survival for Adolescents and Young Adults.

Importance: There are limited studies assessing stage at diagnosis and risk of death among all 5 federally defined races in the US among adolescent and young adult (AYA) patients with cancer. Objective: To identify racial disparities in stage at diagnosis and survival among AYA patients with cancer. Design, Setting, and Participants: This retrospective cohort study used data from a US national hospital-based oncology database on AYA patients, aged 15 to 39 years, with the 10 deadliest cancers among AYA patients who received a diagnosis from January 1, 2004, to December 31, 2017, with 6 months or more of follow-up. Analyses by race were categorized by the 5 federally defined races in the US: American Indian or Alaska Native, Asian, Black, Native Hawaiian or Other Pacific Islander, and non-Hispanic White (hereafter, White). White patients served as the majority reference group. Statistical analysis was performed from November 2022 to September 2023. Main Outcomes and Measures: The primary end points were late stage at diagnosis (logistic regression with adjusted odds ratios [AORs] and 95% CIs) and overall survival (log-rank tests and Cox proportional hazards regression with adjusted hazard ratios [AHRs] and 95% CIs). Results: A total of 291 899 AYA patients (median age, 33 years [IQR, 28-37 years]; 186 549 female patients [64%]; 189 812 [65%] with stage I or II cancers) were evaluated. The cohort included 1457 American Indian or Alaska Native patients (1%), 8412 Asian patients (3%), 40 851 Black patients (14%), 987 Native Hawaiian or Other Pacific Islander patients (0.3%), and 240 192 White patients (82%). Cancers included breast (n = 79 195 [27%]), lymphoma (n = 45 500 [16%]), melanoma (n = 36 724 [13%]), testis (n = 31 413 [11%]), central nervous system (n = 26 070 [9%]), colon or rectum (n = 22 545 [8%]), cervix (n = 20 923 [7%]), sarcoma (n = 14 951 [5%]), ovary (n = 8982 [3%]), and lung (n = 5596 [2%]). Risk of late-stage diagnosis was higher for Asian (AOR, 1.20; 95% CI, 1.14-1.26), Black (AOR, 1.40; 95% CI, 1.36-1.43), and Native Hawaiian or Other Pacific Islander (AOR, 1.34; 95% CI, 1.16-1.55) patients compared with White patients. Overall survival differed by race for all cancer sites, except cancers of the central nervous system and ovary. Risk of death was higher for American Indian or Alaska Native (AHR, 1.15; 95% CI, 1.02-1.30), Black (AHR, 1.22; 95% CI, 1.19-1.26), and Native Hawaiian or Other Pacific Islander (AHR, 1.25; 95% CI, 1.09-1.44) patients but lower for Asian patients (AHR, 0.90; 95% CI, 0.85-0.95) compared with White patients. Conclusions and Relevance: This cohort study of AYA patients suggests that stage at diagnosis and survival varied across races for the 10 deadliest AYA cancers. These results support the need for tailored interventions and informed public policy to achieve cancer care equity for all races.

Race and Ethnicity Representation in Phase 2/3 Oncology Clinical Trial Publications: A Systematic Review.

Importance: The five 1997 Office of Management and Budget races in the US include American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White, with Hispanic ethnicity. Despite the Affordable Care Act mandating Office of Management and Budget-based collecting and reporting standards, race and ethnicity publishing in medical journals is inconsistent, despite being necessary to achieve health equity. Objective: To quantify race and ethnicity reporting rates and calculate representation quotients (RQs) in published oncology clinical trials. Evidence Review: In this systematic review, PubMed and Embase were queried for phase 2/3 clinical trials of the 6 most common noncutaneous solid cancers, published between January 1, 2012, and December 31, 2022, in 4 high-impact journals. Trial characteristics were recorded. The RQs for each race and ethnicity were calculated by dividing the percent of representation in each clinical trial publication by the percent of year-matched, site-specific incident cancers in the US, compared with Kruskal-Wallis tests with Bonferroni correction (BC). Reporting was compared between journal publications and ClinicalTrials.gov. Findings: Among 1202 publications evaluated, 364 met inclusion criteria: 16 JAMA, 241 Journal of Clinical Oncology, 19 Lancet, and 88 New England Journal of Medicine. Publications included 268 209 patients (171 132 women [64%]), with a median of 356 (IQR, 131-800) patients per publication. Reported race and ethnicity included American Indian or Alaska Native in 52 (14%) publications, Asian in 196 (54%), Black or African American in 215 (59%), Hispanic in 67 (18%), Native Hawaiian or Other Pacific Islander in 28 (8%), and White in 254 (70%). Median RQ varied across race (P < .001 BC), with 1.04 (IQR, 0.09-4.77) for Asian, 0.98 (IQR, 0.86-1.06) for White, 0.42 (IQR, 0.12-0.75) for Black or African American, and 0.00 (IQR, 0.00-0.00) for both American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander patients. Sensitivity analyses showed similar findings on subset analysis for US-only clinical trials. There was significantly less race and ethnicity reporting in the clinical trial publications compared with ClinicalTrials.gov documentation for American Indian or Alaska Native (14% vs 45%; P < .001 per McNemar χ2 test with continuity correction [MC]) and Native Hawaiian or Other Pacific Islander (8% vs 43%; P < .001 MC). Conclusions and Relevance: While most phase 2/3 oncology clinical trials published in high-impact journals report race and ethnicity, most did not report American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander racial categories. Our findings support a call to action for consistent journal policies and transparent race and ethnicity reporting, in alignment with Affordable Care Act-concordant race and ethnicity federal reporting requirements.

Site-specific patterns of early-stage cancer diagnosis during the COVID-19 pandemic.

The COVID-19 pandemic caused widespread disruptions in cancer care. We hypothesized that the greatest disruptions in diagnosis occurred in screen-detected cancers. We identified patients (≥18 years of age) with newly diagnosed cancer from 2019 to 2020 in the US National Cancer Database and calculated the change in proportion of early-stage to late-stage cancers using a weighted linear regression. Disruptions in early-stage diagnosis were greater than in late-stage diagnosis (17% vs 12.5%). Melanoma demonstrated the greatest relative decrease in early-stage vs late-stage diagnosis (22.9% vs 9.2%), whereas the decrease was similar for pancreatic cancer. Compared with breast cancer, cervical, melanoma, prostate, colorectal, and lung cancers showed the greatest disruptions in early-stage diagnosis. Uninsured patients experienced greater disruptions than privately insured patients. Disruptions in cancer diagnosis in 2020 had a larger impact on early-stage disease, particularly screen-detected cancers. Our study supports emerging evidence that primary care visits may play a critical role in early melanoma detection.

A Lung Cancer Mouse Model Database.

Lung cancer, the leading cause of cancer mortality, exhibits diverse histological subtypes and genetic complexities. Numerous preclinical mouse models have been developed to study lung cancer, but data from these models are disparate, siloed, and difficult to compare in a centralized fashion. Here we established the Lung Cancer Mouse Model Database (LCMMDB), an extensive repository of 1,354 samples from 77 transcriptomic datasets covering 974 samples from genetically engineered mouse models (GEMMs), 368 samples from carcinogen-induced models, and 12 samples from a spontaneous model. Meticulous curation and collaboration with data depositors have produced a robust and comprehensive database, enhancing the fidelity of the genetic landscape it depicts. The LCMMDB aligns 859 tumors from GEMMs with human lung cancer mutations, enabling comparative analysis and revealing a pressing need to broaden the diversity of genetic aberrations modeled in GEMMs. Accompanying this resource, we developed a web application that offers researchers intuitive tools for in-depth gene expression analysis. With standardized reprocessing of gene expression data, the LCMMDB serves as a powerful platform for cross-study comparison and lays the groundwork for future research, aiming to bridge the gap between mouse models and human lung cancer for improved translational relevance.

Racial Disparities in 30-day Readmissions after Surgery for Head and Neck Cancer.

BACKGROUND: Native Hawaiians and other Pacific Islanders (NHPI) patients with head and neck cancer are often aggregated with Asian individuals despite evidence of heterogeneous health outcomes and mortality. The aim of this study was to determine the association of race with unplanned 30-day hospital readmission rate after head and neck surgery across the five federally recognized racial categories. METHODS: This retrospective cohort study used a national hospital-based database and included patients ≥18 years old with diagnostically confirmed, nonmetastatic head and neck cancer of any subsite treated surgically between 2004 and 2017. The primary endpoint was unplanned readmission within 30 days of discharge after primary surgery. RESULTS: A total of 365,834 patients were included who were predominantly White (87%), treated at academic cancer centers (47%), lower income (63%), with early-stage disease (60%), and with thyroid (47%) or oral cavity (23%) cancers. Median follow-up duration was 47 months. Of the 10,717 (3%) readmissions, 5,845 (1.6%) were unplanned. Adjusted for confounders and compared with White patients, NHPI patients had the highest likelihood of unplanned (aOR 2.07, 95%CI 1.16-3.40, p = 0.008) readmissions. Within the NHPI group, patients with lower income (aOR 4.27, 95%CI 1.28-20.4, p = 0.035) and those residing in an urban or rural area (aOR 7.42, 95%CI 1.14-49.5, p = 0.034) were more likely to be readmitted. CONCLUSIONS: NHPI patients with head and neck cancers experience significantly higher 30-day readmissions following definitive surgical treatment. These results highlight the importance of racial disaggregation in clinical studies. LEVEL OF EVIDENCE: 4 Laryngoscope, 134:1282-1287, 2024.

Recombination map tailored to Native Hawaiians may improve robustness of genomic scans for positive selection.

Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map) and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score|> 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.

Diversity in Cancer Care: Current Challenges and Potential Solutions to Achieving Equity in Clinical Trial Participation.

ABSTRACT: Access to and participation in cancer clinical trials determine whether such data are applicable, feasible, and generalizable among populations. The lack of inclusion of low-income and marginalized populations limits generalizability of the critical data guiding novel therapeutics and interventions used globally. Such lack of cancer clinical trial equity is troubling, considering that the populations frequently excluded from these trials are those with disproportionately higher cancer morbidity and mortality rates. There is an urgency to increase representation of marginalized populations to ensure that effective treatments are developed and equitably applied. Efforts to ameliorate these clinical trial inclusion disparities are met with a slew of multifactorial and multilevel challenges. We aim to review these challenges at the patient, clinician, system, and policy levels. We also highlight and propose solutions to inform future efforts to achieve cancer health equity.

Rising From Ruin-Revitalizing Native Hawaiian Health.

This Viewpoint offers insight into the health effects of the recent fires in Hawaiʻi and what culturally conscious approaches are needed to ensure the health of Native Hawaiians going forward.

Definitive Treatment of Brain Metastases From a Neuroendocrine Tumor With Peptide Receptor Radionuclide Therapy With 177Lutetium DOTATATE: A Case Report.

Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare malignancies that arise from secretory endocrine cells of the gastroenteropancreatic system. Clinical outcomes have improved for patients with GEP-NETs due to the development and recent FDA approval of 177Lutetium DOTATATE. However, the response of brain metastases from GEP-NETs from 177Lutetium DOTATATE is unreported. We present the case of an 81-year-old man with low-grade small bowel GEP-NET with liver and brain metastases treated with a total of six cycles of 177Lutetium DOTATATE. With over three years of follow-up from his initial treatment, his brain metastases have had complete or partial responses, with no need for brain radiotherapy or radiosurgery.

MGMT Promoter Methylation Predicts Overall Survival after Chemotherapy for 1p/19q-Codeleted Gliomas.

PURPOSE: While MGMT promoter methylation (mMGMT) is predictive of response to alkylating chemotherapy and guides treatment decisions in glioblastoma, its role in grade 2 and 3 glioma remains unclear. Recent data suggest that mMGMT is prognostic of progression-free survival in 1p/19q-codeleted oligodendrogliomas, but an effect on overall survival (OS) has not been demonstrated. EXPERIMENTAL DESIGN: We identified patients with newly diagnosed 1p/19q-codeleted gliomas and known MGMT promoter status in the National Cancer Database from 2010 to 2019. Multivariable Cox proportional hazards regression modeling was used to assess the effect of mMGMT on OS after adjusting for age, sex, race, comorbidity, grade, extent of resection, chemotherapy, and radiotherapy. RESULTS: We identified 1,297 eligible patients, 938 (72.3%) of whom received chemotherapy in their initial course of treatment. The MGMT promoter was methylated in 1,009 (77.8%) patients. Unmethylated MGMT (uMGMT) was associated with worse survival compared with mMGMT [70% {95% confidence interval (CI), 64%-77%} vs. 81% (95% CI, 78%-85%); P < 0.001; adjusted HR (aHR), 2.35 (95% CI, 1.77-3.14)]. uMGMT was associated with worse survival in patients who received chemotherapy [63% (95% CI, 55-73%) vs. 80% (95% CI, 76%-84%); P < 0.001; aHR, 2.61 (95% CI, 1.89-3.60)] but not in patients who did not receive chemotherapy [P = 0.38; HR, 1.31 (95% CI, 0.71-2.42)]. Similar results were observed regardless of World Health Organization grade and after single- or multiagent chemotherapy. CONCLUSIONS: Our study demonstrates an association between mMGMT and OS in 1p/19q-codeleted gliomas. MGMT promoter status should be considered as a stratification factor in future clinical trials of 1p/19q-codeleted gliomas that use OS as an endpoint.

Recombination map tailored to Native Hawaiians improves robustness of genomic scans for positive selection.

Recombination events establish the patterns of haplotypic structure in a population and estimates of recombination rates are used in several downstream population and statistical genetic analyses. Using suboptimal maps from distantly related populations may reduce the efficacy of genomic analyses, particularly for underrepresented populations such as the Native Hawaiians. To overcome this challenge, we constructed recombination maps using genome-wide array data from two study samples of Native Hawaiians: one reflecting the current admixed state of Native Hawaiians (NH map), and one based on individuals of enriched Polynesian ancestries (PNS map) with the potential to be used for less admixed Polynesian populations such as the Samoans. We found the recombination landscape to be less correlated with those from other continental populations (e.g. Spearman's rho = 0.79 between PNS and CEU (Utah residents with Northern and Western European ancestry) compared to 0.92 between YRI (Yoruba in Ibadan, Nigeria) and CEU at 50 kb resolution), likely driven by the unique demographic history of the Native Hawaiians. PNS also shared the fewest recombination hotspots with other populations (e.g. 8% of hotspots shared between PNS and CEU compared to 27% of hotspots shared between YRI and CEU). We found that downstream analyses in the Native Hawaiian population, such as local ancestry inference, imputation, and IBD segment and relatedness detections, would achieve similar efficacy when using the NH map compared to an omnibus map. However, for genome scans of adaptive loci using integrated haplotype scores, we found several loci with apparent genome-wide significant signals (|Z-score| > 4) in Native Hawaiians that would not have been significant when analyzed using NH-specific maps. Population-specific recombination maps may therefore improve the robustness of haplotype-based statistics and help us better characterize the evolutionary history that may underlie Native Hawaiian-specific health conditions that persist today.

Racial Disparities among Asian American, Native Hawaiian, and Other Pacific Islander Patients with Cancer Who Refuse Recommended Radiation Therapy or Surgery.

Despite radiation therapy (RT) and surgery being the curative treatments, prior work demonstrated that the aggregated Asian American (AA) and Native Hawaiian and Other Pacific Islanders (NHPI) population refuse RT and surgery at a higher rates than other races. Given that AA and NHPI are distinct groups, data disaggregation is necessary to understand racial and ethnic disparities for treatment refusal. We aimed to (1) compare RT and surgery refusal rates between AA and NHPI populations, (2) assess RT and surgery refusal on overall mortality, and (3) determine predictors of refusing RT and surgery using the United States (U.S.) National Cancer Database. Adjusted odds ratios (aOR) and 95% confidence intervals (95%CI) for treatment refusal were calculated using logistic regression. Adjusted hazard ratios (aHR) were calculated for overall survival using Cox proportional hazard models among propensity score-matched groups. The overall rate of RT refusal was 4.8% and surgery refusal was 0.8%. Compared to East AA patients, NHPI patients had the highest risk of both RT refusal (aOR = 1.38, 95%CI = 1.21-1.61) and surgery refusal (aOR = 1.28, 95%CI = 1.00-1.61). RT refusal significantly predicted higher mortality (aHR = 1.17, 95%CI = 1.08-1.27), whereas surgery refusal did not. Predictors of RT and surgery refusal were older patient age, high comorbidity index, and cancer diagnosis between 2011-2017. The results show heterogenous treatment refusal patterns among AA and NHPI populations, suggesting areas for targeted intervention.