bluuebunny/crossref_metadata_2025_split huggingface dataset:
The impact of COVID-19 and missed diagnosis of breast cancer.
Authors: Rohatgi Atharva , Liao Cheng-I , Johnson Caitlin Ruth , Kapp Daniel Stuart , Chan John K 
Published: June 2024

1118 Background: To evaluate the impact of COVID-19 pandemic on breast cancer diagnosis based on age, race, and regions within the US. Methods: Data on breast cancer incidence were obtained from the United States Cancer Statistics (USCS) program from 2001-2020. SEER*Stat 8.4.1.2 and Joinpoint regression program 5.0.2 were used to calculate estimated and actual incidence rates per 100,000 females. Rates were age-adjusted as appropriate. We compared actual breast cancer incidence rates in the year 2020 to estimated rates based on trends from 2001-2019 with sub-analyses for age, race, and region. Results: From 2001 to 2019, there were 4,005,763 identified cases of breast cancer in the United States. In 2019, prior to the pandemic, the incidence rate of breast cancer was 162.87 per 100,000 in females in the US. Based on the data from 2001 to 2019, breast cancer increased by 1.32% per year (p<0.001). Using these prior trends, it was expected that the incidence of breast cancer to be 165.02 per 100,000 adults (265,206 total cases) in 2020. However, the reported incidence was only 147.77 per 100,000 (237,471). Thus, there were 10.46% (27,735) less breast cancer cases than expected. The missed diagnosis rate was more pronounced in older age groups with 15.89%, 14.75%, and 13.27% cases missed for the age groups 85+, 80-84, and 70-74 respectively. Based on racial and ethnic groups, we found that Hispanic females had the greatest number of missed cases at 13.04% compared to 12.68%, 10.57%, and 8.94% of Non-Hispanic Asians and Pacific Islander (NHAPI), Non-Hispanic White (NHW), and Non-Hispanic Black (NHB) females respectively. The discrepancy between expected and actual number of cases by U.S. region ranged from the highest in the Northeast (11.90%) followed by 11.83%, 10.60%, and 9.49% in the West, South, and Midwest regions respectively. An intersectionality analysis showed that 40–44-year-old Hispanic females residing in the Midwest region had the largest discrepancy at 27.01%. Conclusions: The reported breast cancer cases significantly declined during the pandemic. Older age, Hispanic race and ethnicity, and those residing in the Northeast region had the greatest number of missing cases. As breast cancer is the most common cancer in the United States, more mitigating factors are needed to improve the access to care for patients in these at-risk groups to improve detection of breast cancer and its associated mortality.
Early combination with mycophenolate mofetil for immune-related hepatitis in patients with solid tumors treated with immune checkpoint inhibitors.
Authors: Igawa Yukiko Shimoda , Yoshida Tatsuya , Yoshinami Yuri , Hibino Yukiko , Arima Takamichi , Sato Jun , Maruki Yuta , Shoji Hirokazu , Namikawa Kenjiro , Sudo Kazuki , Honma Yoshitaka , Hashimoto Hironobu , Yamazaki Naoya , Okusaka Takuji , Yonemori Kan , Yamamoto Noboru , Ohe Yuichiro , Kato Ken 
Published: June 2024

12133 Background: Hepatitis, as an immune-related adverse event (irAE), occurs in 2%-10% of patients treated with immune checkpoint inhibitors (ICIs). Although guidelines recommend the use of mycophenolate mofetil (MMF) for steroid-refractory and steroid-resistant ir-hepatitis, there has been no evidence on the efficacy of MMF. Methods: We retrospectively reviewed consecutive patients with solid tumors who developed grade 2 or higher ir-hepatitis requiring systemic steroids after ICIs (nivolumab, pembrolizumab, atezolizumab, avelumab, durvalumab and ipilimumab) between January 2015 and August 2023. The changes in aspartate aminotransferase (AST), alanine aminotransferase (ALT), and total bilirubin level, according to the CTCAE version 5.0, were used to assess ir-hepatitis. ALT improvement was calculated as the ratio of the change in ALT values from onset to day 7, normalized by the ALT values at onset. Results: Among 4405 patients treated with ICI during the study period, 130 patients (3%) developed grade 2 or higher ir-hepatitis requiring systemic steroids. The median age was 62 (range: 19-85) years-old, and 122 patients (94%) had an ECOG performance status (PS) 0/1. These patients included 67 (52%) with melanoma, 35 (27%) with lung cancer, 7 (5%) with esophageal cancer, and 21 (16%) with other cancers. Among 123 evaluable patients, 46 patients (46/123, 37%) received MMF including 20 patients experiencing steroid-refractory and 26 steroid-resistant. The median duration from the start of systemic steroids to MMF was 11 days (range: 0-113 days). Improvement of hepatitis to grade 1 with MMF was observed in 40 patients (40/46, 87%) with a median time of 18 (range: 3-176) days. Of the patients evaluated for the impact of the timing of MMF on the improvement of ir-hepatitis (n=38), ALT improvement at day 7 after ir-hepatitis onset in patients who initiated MMF within 3 days of ir-hepatitis onset (early combination group, n=8) was significantly higher compared with the patients who initiated MMF after 3 days of ir-hepatitis onset (late combination group, n=30) (72.3% vs. 41.7%, p=0.02). Additionally, among patients evaluable for systemic steroid dosage (n=45), the total systemic steroid dosage in patients in the early combination group (n=8) was significantly less than in the late combination group (n=37) (median: 2120mg vs 4005 mg, p=0.02). Conclusions: MMF was effective for both steroid-refractory and steroid -resistant ir-hepatitis. Early combination with MMF in addition to systemic steroids can lead to a more rapid improvement of ir-hepatitis compared to late combination with MMF consequently reducing the total systemic steroid dosage. [Table: see text]
Social vulnerability and clinical trial enrollment: The next frontier of health equity.
Authors: Perati Shruthi Reddy , Mohayya Sana M. , Shippey Ernie , Hochster Howard S. , Omene Coral Oghenerukevwe , Pitt Henry A. , Eskander Mariam F. 
Published: June 2024

1508 Background: Clinical trials are the basis for novel therapies but may not be representative of disadvantaged groups, particularly low-income individuals. This study assesses how social vulnerability impacts enrollment and explores the interaction between race and social vulnerability among patients with the top five leading causes of cancer death. Methods: The national Vizient Clinical Database was queried for outpatients with lung, breast, prostate, colorectal or pancreas cancer from 2022-2023. This includes data from 98% of academic medical centers and more than 110 cancer hospitals. The exposures of interest were Medicaid insurance and social vulnerability as measured by the Vizient Vulnerability Index (VVI), a novel marker of social drivers of health at the census tract level. Participation in a clinical trial was the primary outcome. A multivariable analysis was performed evaluating the association of social vulnerability quartiles with clinical trial participation. Interaction tests were performed for race and VVI. Results: 2,660,566 patients were identified. Of these, 36,456 (1.4%) enrolled in a clinical trial: 28.6% with breast cancer, 26.3% prostate, 22.8% lung, 12.8% colorectal and 9.5% pancreas. Trial participants were more likely to be young, White, privately insured, have metastatic disease, and live in a less vulnerable census tract.5.3% of trial participants were insured by Medicaid (12.2% of Black participants, 8.5% of Asian participants, and 3.5% of White participants), compared to 6.2% of non-participants (p<0.0001).22.6% of participants lived in highly vulnerable neighborhoods (53.5% of Black participants, 19.7% of White participants, and 5.6% of Asian participants), compared to 25.0% of non-participants (p<0.0001). Living in the most vulnerable VVI quartile was associated with decreased odds of clinical trial enrollment (OR 0.86; 95% CI 0.82-0.91, p=0.0442), as was having Medicaid insurance vs. private insurance (OR 0.76; 95% CI 0.73-0.80, p<0.0001). The highest social vulnerability quartiles in the VVI domains for education, neighborhood resources and transportation were associated with decreased enrollment (Table). High social vulnerability decreased the odds of enrollment for Black patients (OR 0.80; 95% CI 0.68-0.88, p<0.0001) more than White patients (OR 0.88; 95% CI 0.89-0.96, p=0.0028); p=0.0054 for interaction. Conclusions: 1.4% of patients in this contemporary, cross-sectional cohort enrolled in a clinical trial. Patients with Medicaid have a 24% lower odds of enrollment than privately insured patients. Neighborhood social vulnerability is also barrier to enrollment, even more so among Black patients. Interventions to address social determinants of health may increase racial diversity in clinical trials. [Table: see text]
Primary treatment modification strategies among older adults with advanced cancer.
Authors: Mohamed Mostafa Refaat , Rich David , Lund Jennifer Leigh , Seplaki Christopher , Flannery Marie Anne , Loh Kah Poh , Culakova Eva , Tylock Rachael , Magnuson Allison , Dunne Richard Francis , Ramsdale Erika E. , Mohile Supriya Gupta 
Published: June 2024

1512 Background: Primary treatment modification (PTM; any change in dose or agents of the planned chemotherapy regimen from the standard guidelines) is a common therapeutic approach among older adults with advanced cancer due to their geriatric vulnerabilities. However, strategies to employ these modifications are understudied. This study compares a PTM strategy based on Geriatric Assessment (PTM-GA) intervention vs. usual care strategy based on oncologist’s impression (PTM-UC) on treatment tolerability in older adults with advanced cancer starting new chemotherapy regimens. Methods: In this subgroup analysis of the GAP 70+ study (NCT02054741; PI: Mohile), we included patients aged ≥ 70 with incurable solid tumors who initiated a chemotherapy course with PTM (n=298). For the first (PTM-GA) group, PTM was guided by GA results and recommendations while for the second (PTM-UC) group, PTM was guided by the treating oncologist's estimate only. Tolerability outcomes were assessed within 3 months of treatment and included: 1) any grade 3-5 clinician-rated toxicity according to National Cancer Institute Common Toxicity Criteria; 2) subsequent dose reduction; 3) Activity of Daily Living (ADL) decline; 4) unplanned hospitalization. We used multivariable, cluster-weighted generalized estimating equations models to examine the association of PTM-GA vs. PTM-UC and outcomes adjusting for confounders. Results: Mean age was 77 years. The most common cancer types were gastrointestinal (37%) followed by lung cancer (26%). PTM-GA versus PTM-UC was associated with reduced risk of grade 3-5 toxicity (relative risk (RR)= 0.77, 95% CI, 0.61- 0.90) and subsequent dose reduction (RR, 0.46; 95% CI, 0.29-0.73). Point estimates suggest that patients with PTM-GA may have a lower risk of unplanned hospitalization but results did not reach statistical significance (RR, 0.69; 95% CI, 0.46–1.02). PTM-GA vs. PTM-UC was not associated with ADL decline (RR, 1.05; 95% CI, 0.74–1.49). Conclusions: Older patients with advanced cancer who had PTM guided by GA recommendations had improved treatment tolerability compared to those who PTM based on oncologist’s estimate only. Integrating GA into treatment dosing decisions may lead to improved outcomes in this vulnerable population.
Human-AI teams to improve accuracy and timeliness of oncology trial prescreening: Preplanned interim analysis of a randomized trial.
Authors: Parikh Ravi Bharat , Guido Matthew , Girard Anthony , Li Yang , Kolla Likhitha , Chen Jinbo , Emanuel Ezekiel J. 
Published: June 2024

1524 Background: Identifying eligible patients for oncology clinical trials (“prescreening”) relies on manual chart review by clinical research coordinators (CRCs), which is time-consuming and often inaccurate. Consequently, 70% of patients with cancer who meet trial eligibility criteria are not offered participation. Natural language processing (NLP) may improve the accuracy and timeliness of prescreening. Methods: This was a preplanned interim analysis of a paired-design noninferiority trial, powered to assess timeliness. We adapted NLP algorithms to identify 13 common eligibility criteria related to cancer type/stage, prior systemic therapy, actionable biomarkers, and response criteria. NLP systems performed optical character recognition, entity and relationship extraction, and natural language inference through deep learning and symbolic AI techniques. Deidentified unstructured electronic health records (EHRs) from real-world patients with non-small cell lung (NSCLC) or colorectal (CrCa) cancer were presented to CRCs via a secure platform. Two CRCs were randomized 1:1 to view blocks of 20 charts each with (Human+AI) or without (Human-alone) NLP annotations. In pre-trial assessment, the CRCs had 86% inter-rater agreement. The primary outcome was overall chart-level accuracy, defined as percent of the 13 CRC-coded eligibility items matching a gold standard set, determined by 2-3 clinicians blinded to experimental arms. Paired t-tests compared overall accuracy (noninferiority margin 5%) and criteria-specific accuracy. Significant differences were assessed for superiority using two-sided paired t-tests. Mann-Whitney tests compared the secondary outcome of timeliness (time per chart review). Results: Among 74 (40 NSCLC; 34 CrCa) of a planned 400 patients, overall accuracy for Human+AI was noninferior to Human-alone (78.7% vs. 76.7%, mean difference 2.0%, p<0.001 rejecting inferiority); both were greater than AI-alone (63.5%). Superiority for Human+AI was demonstrated for RECIST response, but not for overall nor other criteria-specific accuracy (Table). Median time per review was lower for Human+AI than Human-alone (34.1 vs 43.9 min, adjusted p=0.05). Conclusions: Human+AI teams can improve timeliness of trial prescreening with noninferior accuracy. This platform is being used for eligibility assessment in an ongoing clinical trial. [Table: see text]
Food for cancer health equity: The impact of a culturally tailored food voucher intervention on food insecurity among Latinx patients with cancer.
Authors: Hanna Maria T. , Wood Emily Hayes , Villicana Gerardo , Lopez Guzman Lesly , Escobar Kasandra , Reynaga Jajaira , Trotter Chardria , Koontz Zachary M. , Seligman Hilary K. , Patel Manali I. 
Published: June 2024

1544 Background: Food insecurity disproportionately impacts immigrant, low-income, and racial and ethnic minorities with cancer. In our prior qualitative work, Latinx and multiethnic patients with food insecurity emphasized the importance of culturally tailored food assistance interventions that could minimize stigma and maintain self-efficacy and autonomy. In collaboration with Latinx patients and community partners in Monterey County, California, we co-developed a culturally tailored food voucher intervention. In this study, we conducted a pilot of the intervention among multiethnic and Latinx patients with cancer and tested the impact on food insecurity and health-related quality of life. Methods: We recruited low-income, racial and ethnic minority adults >18 years of age who screened positive for food insecurity using the 2-item Hunger Vital Sign while receiving cancer treatment in a clinic in Monterey County, CA between July 2023 until August 2023. All participants who consented to participate received $40 monthly grocery store gift cards redeemable at a variety of local retailers for 6 months in addition to usual care provided by trained community health workers who assisted with other health-related social needs. We conducted validated surveys at baseline (time of enrollment) and 6-month follow-up (post-intervention) assessing demographics, food behaviors, food insecurity, and health-related quality of life. We compared pre- and post-intervention proportions with food insecurity using McNemar's tests and change in health-related quality of life using paired t-tests. Results: Of the 30 study participants enrolled, 27 (90%) were Latinx; 24 (80%) spoke Spanish as their preferred language; 16 (53%) had advanced (stage 3 or 4) cancer; 12 (40%) were retired or unemployed; 10 (33%) were disabled; 20 (67%) reported a household income <$35,000 USD. Of the 26 (87%) participants who completed post-intervention surveys, the proportion with food insecurity decreased from 100% to 65% (95% CI 0.60-0.77; p=0.01); 100% adhered to recommended treatment; and health-related quality of life scores increased by 8 points from 71.9 +/-16.1 to 79.5+/- 10.5 (p=0.02) from baseline. Conclusions: This culturally tailored food voucher intervention was associated with reductions in food insecurity and improvements in health-related quality of life among low-income Latinx patients with cancer. This intervention may represent an effective approach to overcome food insecurity in Latinx and multiethnic patients with cancer.
Clinical impact and financial feasibility of remote oncology pharmacists' roles in community oncology practices.
Authors: Roman Andrea , Cho Judy , Jovani Juna , Farag Caroline , Carroll Melissa , Conkling Hilary , Greisl Natalie , Hale Brittney , Kendzierski Daniel , Keisler Meredith , Koselke Beth , Hough Shannon 
Published: June 2024

1545 Background: The clinical and financial impact of oncology-trained pharmacists in the community oncology setting has not been well documented. The US Oncology Network has introduced a novel remote oncology pharmacist model which provides clinical services to oncology community practices to alleviate the burden on oncologists, enhance patient care, and improve workflows. Methods: Oncology-trained pharmacists remotely reviewed chemotherapy regimens across 12 community oncology practices. Pharmacists identified opportunities to modify therapy based on clinical criteria, waste reduction, and/or financial stewardship. These modifications were discussed with the treatment team or implemented in accordance with practice-approved policies. Clinical and financial metrics were tracked to assess the overall impact of the pharmacist interventions and provider time saved. Results: From January 1, 2023, through December 31, 2023, 27,938 reviews were documented for 19,962 patients. Among these reviews, the majority (14,572, 73%) required modification by the pharmacist, and many (3,005, 21%) were deemed clinically significant by the intervening pharmacist. The most common clinically significant interventions included changes to anticancer drug doses (1155, 38%), modifications to supportive care (742, 25%) and recommendations for additional monitoring (426, 14%). Across 12 practices, 63 drug-related workflow policies were implemented allowing pharmacists to autonomously auto-substitute products, order laboratory tests and adjust chemotherapy doses. These policies saved over 600 hours of physician time. Pharmacist involvement resulted in medication-related margin improvements totaling $9.3M. Practices also experienced a $4.3M reduction in the total cost of care in medication expenses. The cost of the pharmacists during this period was $1.4M, equating to a 560% return on investment compared to margin improvement. Conclusions: Community oncology practices operate within a resource-constrained model with limited access to oncology pharmacists. As invaluable members of the care team, pharmacists identified opportunities to significantly enhance clinical care by focusing on medication safety, dosing, and regimen optimization, while demonstrating a tremendous financial impact on small-scale budgets. Oncology-trained pharmacists play a vital role in alleviating care burden of the clinical team by collaboratively developing practice-approved policies and reviewing clinical orders in a high-risk patient population.
Using an artificial intelligence platform to enhance cancer detection rates in primary care.
Authors: Bakshi Bea , Dadhania Seema , Holloway Peter , Corbett Claire , Payling Miles 
Published: June 2024

1560 Background: Patients with cancer who are diagnosed in a primary care setting have the best survival outcomes compared to any other route (e.g. Emergency department, routine referrals, incidental findings etc). This is primarily attributed to detection of cancer at an early stage. In the UK, the Cancer Detection Rate (CDR) metric serves as a measure of this, representing the percentage of cancer diagnoses originating from primary care referral routes. However, detecting cancer presents significant challenges, primarily due to the non-specific nature of cancer presentations, their tendency to overlap with symptoms of other conditions, and their relatively low prevalence. Artificial intelligence (AI) platforms may be able to support this endeavor but are yet to be established. C the Signs is an AI-enabled clinical decision support tool integrated into primary care practices to help clinicians stratify the risk of cancer and advise on which cancer pathway is most appropriate (if at all) for the patient’s presentation and history. Methods: An observational cohort study was undertaken between 1st May 2021 and 31st March 2022 where 35 practices (covering a population of almost 420,000) within the same geographic region in the East of England were offered the use of C the Signs, with the practices opting out as controls. All practices had the same access to referral and cancer diagnostic pathways within the region. The primary end point was to identify if C the Signs had a statistical impact on cancer detection rates in primary care through nationally linked data via Public Health England. Results: In practices utilizing C the Signs the CDR significantly increased from 58.7% in 2020-21 (prior to the implementation of C the Signs) to 66.0% in 2021-22, reflecting a significant increase of 12.3% (p <0.05). In contrast, practices not using C the Signs maintained a stable CDR of 58.4% in both years. There was no statistically significant variance observed in the referral rate between the two groups, indicating no notable increase in diagnostic or referral activities. Conclusions: These findings underscore the importance of integrating cutting-edge technologies into primary care to improve cancer detection rates and facilitate early-stage diagnosis. Implementation of such advancements holds promise for reducing cancer-related mortality rates and enhancing overall patient outcomes.