bluuebunny/crossref_metadata_2025_split huggingface dataset:
Racial disparities in patients with ALL according to a national dataset.
Authors: Khan Fayaz , Rahima Kenan 
Published: May 2024

e13733 Background: Racial disparities in healthcare refer to differences in health outcomes, access to healthcare &quality of care among racial or ethnic groups. Aim of study is to investigate the characteristics and clinical outcomes of racial differences in patients admitted with ALL. Methods: We queried the National Inpatient Sample between 2017-2020 for adult patients of different races who were hospitalized with ALL. The primary outcome was inpatient mortality; secondary outcomes were cardiac arrest, invasive mechanical ventilation, length of stay & hospital cost. Multivariable logistic, linear & Poisson regression analyses were used to estimate clinical outcomes with p-value < 0.05 was significant. Results: Total 110999 hospitalizations with ALL. Mean age 46 years & 55.8% male. Among admitted, 59599 (53.7 %) were Caucasian, 9205 (8.3 %) were Black, 27565 (24.8%) were Asian, 4540 (4.1%) were Hispanic, and 10090 (9.1%) were others. Subgroup with Caucasian, Blacks, Asians, Hispanics, and other races had Medicare 34.9% vs 30.2% vs 13.5% vs 17.9% vs 12.5%, Medicaid 13.3% vs 29.7% vs 41.4% vs 19.2 vs 34.8%, Non-insured 2.1% vs 5.1% vs 10.6% vs 4.2% vs 7.7%; DM 19% vs 23.8% vs 24.6% vs 17.4% vs 20.7%; Protein calorie malnutrition 11 % vs 10.6% vs 10.1% vs 12.6% vs 10.2%, respectively. All-cause mortality was 3810, where subgroup with Caucasian, Black, Asian, Hispanic, and others were 2085 (3.5%) vs 410 (4.4%) vs 885 (3.2%) vs 145 (3.2%) vs 285 (2.8%). Conclusions: Among the racial categories, Caucasians comprised the largest portion followed by Asians, Blacks, Hispanics. Mortality and intubation proportion was highest among Blacks followed by Hispanics & Asians. Cardiac arrest proportion was highest among Blacks followed by Hispanics and Asians. LOS was highest among Hispanics followed by Asians & Blacks. Resource utilization was highest in Hispanics followed by Asians & Blacks. Understanding these disparities is essential for improving healthcare equity and ensuring that all patients receive appropriate & equitable care regardless of their racial/ethnic background. Interventions include improving access to healthcare, culturally competent care and addressing social determinants of health that affect racial/ethnic groups. [Table: see text]
Rectal cancer: Demographics and healthcare outcomes in a minority-rich community hospital.
Authors: Cholankeril Michelle , Sankhe Rachel , Salinas Flavio Eduardo , Polyak Andrew , Smith Keia 
Published: May 2024

e13735 Background: Rectal cancer (RC) has seen a decreasing incidence and mortality due to national screening guidelines, innovative therapies and new technology. In recent years, however, we have noted shifts in its demographics pertaining to variation in stage at diagnosis and mortality rates amongst various ethnic groups. Minority populations, namely Hispanic (H) and Black (B) patients (pts), continue to see higher incidence, diagnosis at more advanced stages and poorer survival than White (W) pts. In B pts, mortality rates are higher with an increased likelihood of distant-stage RC creating a significant survival disparity. Current studies involving H and Asians(A) show similar disparities. Compared to other malignancies, RC has improved survival for pts when diagnosed in a timely fashion and therefore, we seek to identify potential patterns within the diverse population we care for. Methods: Trinitas Medical Center RWJBH is an urban, community hospital that predominantly treats a minority population. With institutional IRB approval, we completed a retrospective chart review of 59 pts diagnosed with Stage I-IV RC from 2017- 2023. Pts were treated at our cancer center. We assessed age and stage at diagnosis and demographics such as age, sex and ethnicity. Results: We reviewed 59 pts with the following ethnic distribution: 22 H, 21 W, 11 B and 5 A pts. The median age at diagnosis with RC was 57 in H, 64 in B, 71 in W 71. More males were diagnosed in all groups except A pts. B pts were found to be diagnosed with more advanced disease: 36% at Stage III, 45% at Stage IV. W pts also saw a similar trend with 33% at Stage III and 24% at Stage IV. Our H pts had comparatively fewer distant stage diagnoses: 23% at Stage III, 18% at Stage IV. Common sites of metastasis in B: liver 27%, lung 27%, locoregional lymph nodes 9%. In W pts: liver 24%, locoregional lymph nodes 24%, lung 10% and brain 5%. In H pts, 10 of 22(45%) were diagnosed without metastatic disease, though of the 10 who did, 2 had brain involvement. Mortality was highest in B pts at 55%, 33% for W, 20% for A and 18% for H pts. Conclusions: In our study, we note H pts being diagnosed at an earlier median age, at earlier stages of disease, with higher survival rates. Our B pts were diagnosed younger than W pts, at later stages of disease, with higher mortality rates. Brain involvement, which usually is rare, was seen in both H and W upon recurrence. Despite having a multi specialized cancer center, we note limitations in our access to screening resources and the availability of colorectal surgical expertise to enhance care for our underserved population. The challenge of disentangling disparities within RC will benefit from improved healthcare access and availability of multimodality resources in this disease state where cure is the ultimate goal.
Impact of racial disparities in adjuvant treatment of triple negative breast cancer (TNBC) among American Indians/Alaskan Natives (AI/AN) and non-Hispanic Whites (NHW) on overall survival (OS).
Authors: Gaba Anu G. , Cao Li , Renfrew Rebecca , Sahmoun Abe Eric , Goel Sanjay , Crosby Ross 
Published: May 2024

e13736 Background: There are significant differences in patient and tumor characteristics among AI/AN and NHW breast cancers (BC) which adversely impact overall survival in AI/AN. Prior studies have also shown higher Mortality: Incidence ratio for BCs in AI/AN as compared to NHW. The aims of this study are to 1) investigate disparities in adjuvant treatment of TNBC between the two races adjusting for age, stage, and year of diagnosis; and 2) Assess differences in OS. Methods: This was a hospital based, retrospective cohort study using the National Cancer Database. AI/AN and NHW women with TNBC, greater than or equal to 18 years of age, diagnosed with BC between the years 2010 through 2019, stages I, II, and III were included. Propensity score matching in a 1:3 ratio was used for age, year, and analytical stage at diagnosis. Primary endpoint was time to first treatment and compliance with recommended treatment. Secondary endpoint was OS. Results: A total of 489 AI/AN and 1465 matched NHW women with TNBC were identified. AI/AN women traveled longer distances for cancer care (p<.01), resided in lower median income zip codes at the time of diagnosis (p<.001), had a higher Charlson-Deyo (CD) comorbidity score (p<.001), and were less likely to have private insurance (p<.001). There was no difference in the rates of chemotherapy, surgery, and radiation therapies that were recommended and received by the two races. Time to first treatment was significantly longer for AI/AN as compared to NHW women (Mean ± SD: 35 ± 27 days vs. 39 ±27 days; p=.005). Multivariable analysis revealed that longer time to first treatment was associated with only higher CD score (p=.013) and non-private insurance (p=.027), but no longer associated with race (p=.324). Compliance with recommended treatment was similar between AI/AN and NHW women (93.5% vs 92.9%, p=.096). Compliance was significantly associated with only insurance status (p < .001) with Medicare/Medicaid having the lowest compliance. OS did not differ by race (p=.299, HR=1.132; 95% CI: 0.90-1.43). Cancer stage, CD score, insurance status, and treatment compliance were associated with worse OS. Conclusions: In patients with TNBC, there was no difference in time to treatment, compliance with recommended treatment or OS among AI/AN in comparison to White women when matched for age, stage, and year of diagnosis. Medicare/Medicaid insurance was associated with prolonged time to treatment, lower compliance with recommended treatment and decreased survival when compared with other insurances. Higher comorbidities adversely impacted time to treatment and overall survival. In order to improve BC mortality, it is important to manage comorbid conditions and improve detection of cancer at earlier stages. Prospective studies comparing outcomes by race are needed to confirm these findings.
Advancing team science and health equity in clinical oncology using the All of Us Research Program dataset.
Authors: Watson Karriem S , Baskir Rubin , Smith JoAnn , Mitiku Anna , Aschebrook-Kilfoy Brisa , Tossas Katherine Y , Collins Yvonne 
Published: May 2024

e13741 Background: The All of Us Research Program ( All of Us) is one of the largest, most diverse health databases developed to expedite medical breakthroughs and is a resource for cancer researchers. The size and diversity of participants along with data types within the program, coupled with the program’s cloud based data analytics platform, encourage both team science and equitable health research outcomes. All of Us is dedicated to advancing the science of health equity with a focus on populations underrepresented in biomedical research and workforce, and embedding health equity across all aspects of the program. Methods: All of Us uses a centralized protocol where participants may elect to 1) enroll, consent, and authorize EHR, 2) answer surveys, 3) provide physical measurements, 4) provide biosamples, and 5) share data from wearables. High levels of participant diversity was achieved through an Engagement Ecosystem of outreach leaders, participants, and engagement awardees. Outreach, engagement, enrollment, and retention efforts are strategically directed by a Community and Participant Engagement Framework and a Health Equity Strategic Plan. Results: As of January 2024, health data from 413,450+ participants is available, including eight survey types from 337,500+ participants, electronic health records (EHR) from 287,000+ participants, wearable data from 15,600+ participants and whole genome sequencing from 245,350+ participants. Over 75% of participants self-identify as underrepresented in biomedical research, and about 45% self-identify as racial and ethnic minority groups. Cancer data includes history at enrollment as well as incident ascertainment via EHR (N = 26,323 total cancers and 13,067 incident cancers, from 7,544 participants assigned female at birth and 5,264 participants assigned male at birth). As of February 2024, All of Us data has been used in more than 221 publications. Of these, 35% (78) discuss cancer or oncology. More than 10% of active workspaces (921 out of 8000+ as of January 2024) include “cancer” in workspace descriptions. Commonly studied cancer types include breast, prostate, lung, ovarian, and colorectal. Conclusions: All of Us has established itself as a resource for cancer researchers. This database has the potential to provide insights into the development of treatment guidelines and emerging indicators for screening and early detection guided by health equity built on participant engagement, diversity, and broad data availability. Finally, the breadth of All of Us data also offers potential insight into cancer etiology and opportunities for prevention.
Feasibility of universal breast cancer risk assessment in a diverse, publicly insured obstetrician gynecology clinic.
Authors: Enriquez Allan , Weiss Jessica M. , Chandler Isabelle , Brewer Jesse T. , Webster Emily M. , Ahsan Muhammad Danyal , Wang Ann , McDougale Auja , Sharaf Ravi N. , Frey Melissa Kristen 
Published: May 2024

e13759 Background: Breast cancer is the most diagnosed cancer among women in the United States. Established breast cancer risk assessment (BCRA) tools can estimate a woman’s lifetime risk and inform the need for enhanced breast screening which can improve cancer-associated morbidity and mortality. Currently, critical disparities exist both in breast cancer prognosis and screening uptake. We aimed to evaluate the feasibility of routine BCRA in a diverse, publicly insured obstetrician gynecology clinic. Methods: All patients presenting to the obstetrician gynecology clinic were offered a BCRA using the Tyrer Cuzick (TC) risk model. Patients completed paper surveys and the information was input into the TC model to generate lifetime risk estimates. Printed evidence-based management guidelines were reviewed with and provided to those at ≥ 20% lifetime breast cancer risk and shared with the patient’s provider. Results: Between June 2023 and February 2024, 300 patients were approached and 208 (69.3%) completed the survey. One hundred seven (51.4%) survey respondents were presenting for obstetrical care and 101 (48.6%) for gynecologic care. Respondents had a median age of 33 years (IQR: 12). Ninety-six (46.2%) responding patients self-identified as Hispanic, 45 (21.6%) as Black, 25 (12.0%) as Asian, 28 (13.5%) as Non-Hispanic White, and 14 (6.7%) did not identify in these categories. One hundred eighty-nine (90.9%) survey respondents were publicly-insured. Ten (4.8%) patients were assisted by an interpreter. Overall, 12 (5.8%) patients had an elevated lifetime breast of breast cancer, defined as ≥ 20% based on the TC model (6 (50.0%) among obstetrical patients and 6 (50.0%) among gynecology patients). All patients at elevated risk were referred to a genetics clinic for counseling on options for enhanced breast surveillance. Conclusions: As leaders in women’s cancer care, gynecologic oncologists can lead and support programs to identify those women at highest risk for cancer, especially among historically underserved populations. Our feasibility study demonstrated that 69.3% of patients were willing to complete a BRCA and this tool identified 5.8% of patients to have a significantly elevated lifetime breast cancer risk. Providers should consider incorporating such tools in gynecologic oncology and obstetrical/gynecology clinics.
Overall survival in older patients with urologic cancer using G8 and G8m in a Brazilian cancer center.
Authors: Dettino Aldo A. , Modesto Ingrid Felix 
Published: May 2024

e13760 Background: Aging is a significant risk factor for cancer, with a notable incidence among the elderly. To provide better assistance, international societies recommend the Comprehensive Geriatric Assessment (CGA), a multidisciplinary process aimed at developing a personalized treatment plan. However, CGA requires considerable time and specialized human resources, hindering its use in some healthcare systems. Also, CGA is not recommended for all older cancer patients. Current guidelines recommend the use of high-sensitivity screening tools, such as G8 and G8-modified (G8m), to identify those in CGA need. We aimed to verify the one-year overall survival associated with the G8 and G8m scores in patients aged ≥ 60 years with urological tumors. Methods: For this observational and prospective study, sociodemographic data were collected, G8 and G8m were applied to individuals aged ≥ 60 years with urologic cancer diagnosed within 6 months or prior to a change in therapeutic strategy, from Feb22 to Jan23. The occurrence of outcome (overall survival) was assessed in 1 year after these screening tools. Statistical analyzes were performed, such as mean, median, standard deviation and proportions, as well Kappa Coefficient to compare G8 versus G8m scores. Kaplan-Meier method was used to estimate one-year survival curves and Log-rank Test to evaluate the differences according to baseline scores from G8 (normal >14 or abnormal ≤14) and G8m (normal <6 or abnormal ≥6). Results: 58 participants were included, with a median age of 71 years old, and 93.1% of them were men. The most frequent cancer type was prostate (74.1%), followed by bladder cancer (13.8%). 45 patients (77.6%) were changing treatment strategy, and 13 (22.4%) received a diagnosis within 6 months. Most patients (70.7%) were stage IV. The G8 mean score was 13.5 (±2.6) and G8m, 7.9 (±7.2). A moderate agreement (77.8%) was found between normal G8 and G8m scores (Kappa = 0.551 and p <0.001) (Table). 9 individuals (15.1%) died within 1 year and all of whom had scored abnormally in G8 and G8m. The Kaplan-Meier estimator indicated that abnormal G8 and G8m scores impacted the one-year survival (p = 0.002, for both tools). Conclusions: In older patients with urologic cancer, G8 and G8m showed similar results in identifying patients with frailties who would require a CGA. In addition, this study indicates the predictive value of G8 and G8m for one-year overall survival in this setting. Therefore, our findings support the use of these geriatric screening tools in daily practice of Geriatric Oncology, optimizing treatment planning for older patients. [Table: see text]
Treatment outcomes and survival of patients with breast cancer aged 75 and older: A comparative study using propensity score-adjusted analysis.
Authors: Maeda Shigeto , Sugiyama Nozomu , Yoneda Akira , Kitasato Amane , Takeshita Hiroaki , Minami Shigeki , Kuroki Tamotsu 
Published: May 2024

e13763 Background: With an aging society, the incidence of breast cancer among elderly patients is expected to rise. We aimed to explore treatment outcomes in breast cancer patients aged 75 and older at our institution. The lack of consensus on whether adjuvant therapy for elderly breast cancer patients should mimic that for younger patients prompted our investigation. Methods: We conducted a comparative study using data from 1553 breast cancer surgery cases (stage 0-3) treated between April 2007 and August 2021. Patients were divided into two groups: those aged 75 and older (n=184) and those aged 74 and younger (n=1369). Variables investigated included mean age, tumor size, stage, and subtype; surgical procedures and adjuvant therapies; overall survival (OS); and OS in the 75 and older group, considering the presence or absence of hormone therapy, and propensity score-adjusted OS. Results: Comparing the group aged 74 and younger with the group aged 75 and older revealed: Mean age: (55.5 years vs. 79.6 years), tumor size: (2.4 cm vs. 2.3 cm), stage (0/1/2/3) (%): (7.3/43.1/44.1/4/6 vs. 7.6/43.4/43.4/5.7), subtype (Luminal A/Luminal B/TN/HER2) (%): (60.0/16.7/11.3/7.9 vs. 63.5/10.7/15.7/5.7). Except for age, no significant differences were observed. Mastectomy (%): 45.9 vs. 50.8, axillary lymph node dissection (%): 33 vs. 22.3, adjuvant therapy (%): 93.2 vs. 65.7, adjuvant hormone therapy (%): 90 vs. 68, adjuvant chemotherapy (%): 68 vs. 14. The group aged 75 and older received significantly less adjuvant hormone therapy and chemotherapy. Kaplan-Meier 10-year OS rates: 90.3% vs. 77.5%, showing a trend toward lower survival in the group aged 75 and older, albeit not statistically significant. No significant differences were found in overall survival rates by subtype. In the group aged 75 and older, hormone therapy was omitted in 44.6% and administered in 55.4%, resulting in a significant difference in 10-year OS rates (63.5% vs. 84.7%). Following propensity score adjustment for age, stage, and subtype, the hormone therapy-free group exhibited a higher 10-year OS rate of 100%, in contrast to 84.7% in the hormone therapy group. Conclusions: Breast cancer cases in patients aged 75 and older show similar biological characteristics to those aged 74 and younger. The absence of adjuvant therapy does not impact OS, even though elderly patients aged 75 and older are less likely to receive adjuvant hormone therapy and chemotherapy.
Updated safety and efficacy analysis comparing elderly vs nonelderly patients treated with consolidation nivolumab or nivolumab plus ipilimumab after chemoradiation for unresectable stage III NSCLC from the BTCRC LUN 16-081 clinical trial.
Authors: Shahani Shobha , Althouse Sandra K. , Hanna Nasser H. , Durm Greg Andrew 
Published: May 2024

e13770 Background: Lung cancer is the leading cause of cancer related deaths. The median age of those diagnosed with lung cancer continues to increase as the overall population ages. Consolidation immunotherapy after chemoradiation has become the standard treatment for patients with unresectable stage III NSCLC. However, little has been reported regarding the safety and efficacy of this strategy in an elderly patient population. Methods: Data was analyzed from a randomized phase II clinical trial in patients with unresectable stage III non-small cell lung cancer (NSCLC) who were randomized to Nivolumab (N) or Nivolumab/Ipilimumab (NI) after concurrent chemoradiation. We performed an ad-hoc analysis comparing the efficacy and toxicity based on age groups <65 and ≥ 65. A total of 54 patients received N (480mg IV every 4 weeks for up to 6 cycles) and 51 patients received N (240mg IV every 2 weeks) + I (1mg/kg IV every 6 weeks for up to 4 cycles). Results: From 9/2017 to 4/2021, 105 patients were enrolled. Fifty-five were age <65 (26 in N and 29 in NI) and 50 were ≥65 (28 in N and 22 in NI). Patients were matched for baseline characteristics (Table). In the N alone group, pneumonitis was noted in 14 patients: 9 (34.6%) <65 and 5 (17.9%) age ≥ 65 (p=0.16). In the NI group, 19 patients experienced pneumonitis: 9 (31%) were<65 and 10 (45.5%) were ≥ 65 (p=0.29). Hospitalization was noted in 9 patients in the N group: 6 (23.1%) < 65 and 3 (10.7%) ≥ 65 (p=0.28). In the NI group, 20 patients were hospitalized: 9 (31%) were <65 and 11(50%) were ≥ 65 (p=0.16). At 24 months, the PS for all patients <65 was 61.3% and 60.5% for patients ≥65(p=0.62). PFS was 46.8% for <65 and 73.8% for ≥65 (p=0.15) in the N group and 75.4% for <65 and 45.4% for ≥65 in the NI group(p=0.02). OS for patients <65 was 84% at 24 months and 73% for ≥65 for both groups (p=0.466). For individual groups, OS was 72.5% in <65 and 81.4% for ≥65 (p=0.27) in the N group and 92.8% for <65 and 68.2% for ≥65 in the NI group (p=0.029). Conclusions: Adverse events in both age groups were comparable but overall higher in NI arm in both younger and elderly patients. OS estimates were similar for both age groups in N while higher in younger patients compared to older adults in NI. [Table: see text]