bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential responses to systemic therapy among patients who are financially fragile and receiving Medicaid: Results from ePRO and biometric monitoring study.
Authors: Ramsey Scott David , Yu Kaiyue , Shankaran Veena , Bansal Aasthaa , Kreizenbeck Karma L. , Glascock Morgan , Watabayashi Kate , Benitez Alejandra , Wilson Richa , Yu Elaine 
Published: June 2023

1527 Background: Cancer patients with Medicaid insurance have a 50% higher risk of unplanned ED admissions during systemic chemotherapy compared to commercially insured cancer patients. In a prospective study of an ePRO app and smartwatch to remotely monitor patients receiving anti-cancer therapy, we compared symptoms and biometric data among financially fragile (able vs. not to come up with $2000 in 30 days for an unexpected expense) Medicaid enrollees and commercially insured patients with solid tumor malignancies. Methods: The study was conducted at 3 community oncology practices in WA state. (ML41539, ISRCTN25569053) The ePRO had 15 common treatment-related symptoms from the PRO-CTCAE survey. 30 patients initiating systemic treatment wore a Samsung Galaxy 3 watch and completed the ePRO daily on study provided smartphones for 2 weeks. EPRO app adherence (ratio of completed to expected entries) was 91%. Smartwatch adherence (ratio of days with any biosensor data to number of days expected) was 86%. Composite symptom scores were calculated from ePRO responses using a published mapping algorithm (Range 0-3). Repeat symptoms, number of unique symptoms scores >1, and average heart rate (HR) were compared. Results: Participants’ average age was 60 (68% female; 75% no comorbidity, 45% metastatic, 10% Medicaid, 13% reported financial fragility). Treatments: chemotherapy only (56%); immunotherapy only (11%); combination therapy (33%). Financially fragile patients had significantly higher average HR, unique symptoms, and repeat symptoms (e.g., >1 day with symptoms). The average composite symptom score over 2 weeks was significantly higher for Medicaid enrollees, and trended higher for financially fragile patients. 16% of daily composite symptom scores recorded by Medicaid patients were 2 or greater, versus 7% for non-Medicaid patients (p<0.001). Conclusions: Medicaid-insured and financially fragile patients may have more adverse responses to systemic therapy compared to more advantaged patients. If supported in larger studies, the findings may have profound implications for research aimed at improving clinical management in financially disadvantaged cancer patients.[Table: see text]
Outpatient practice utilization for CAR-T and T cell engager in patients with lymphoma and multiple myeloma.
Authors: Bansal Radhika , Paludo Jonas , De Menezes Silva Corraes Andre , Megan Spychalla , Khurana Arushi , Hampel Paul Joseph , Durani Urshila , Dingli David , Hayman Suzanne R. , Kapoor Prashant , Wang Yucai , Binder Moritz , Kourelis Taxiarchis , Kumar Shaji , Warsame Rahma M. , Bennani Nabila Nora , Gertz Morie A. , Johnston Patrick B. , Ansell Stephen M. , Lin Yi 
Published: June 2023

1533 Background: FDA-approved chimeric antigen receptor T-cell (CAR-T) and bispecific T cell engager (TCE) therapy are most commonly managed inpatient. Here we report our experience with hospital-based outpatient (HBO) management of patients (pts) receiving FDA-approved CAR-T or TCE and a predictive model for increased risk of early hospitalization (≤3 days post CAR-T). Methods: We reviewed the outcomes of pts who received FDA-approved CAR-T (axi-cel, brexu-cel, ide-cel, cilta-cel) or TCE (teclistamab) in the HBO unit between 3/2021 and 1/2023 at Mayo Clinic, Rochester. Results: HBO is closely integrated with inpatient practice and includes the same specialty trained clinical team. It is the first point of contact 24/7 for pts and triage evaluations. CAR-T and TCE are given on HBO followed by monitoring per REMS and as clinically needed until admission criteria is met. Remote patient monitoring (RPM) tools were used as part of outpatient monitoring. Out of 169 CAR-T pts, 87 (51%) were dosed with new indication/products (follicular lymphoma, mantle cell lymphoma, myeloma). Among those, 80 (92%) pts were dosed outpatient, among whom 21 (27%) were never hospitalized. CRS and ICANS incidences were comparable to that reported in registration studies. Median time to first admission from CAR-T infusion was 1 day (range, 0-9), with 31% (n=18/59) of admissions after day 3 post infusion. The most common cause of hospitalization was fever (n=40, 59%). Median length of hospital stay was 4 days (range, 1-49). Median time to tocilizumab (n=45, 80%), steroid (n=1, 2%), escalation of oxygen support (n=7, 12%), vasopressor (n=2, 3%), ventilator (n=1, 2%), hemodialysis (n=1, 2%) and ICU transfer (n=3, 5%) was 1 day (range, 0-31) after first admission. Use of bridging therapy, elevated CRP and LDH were predictive of early admission (ROC AUC 0.62). Four pts received teclistamab on HBO and enrolled in RPM. Data from more pts will be reported at ASCO. Conclusions: Our expanded study in CAR-T and TCE confirms that HBO is feasible and that CAR-T and TCE can be safely dosed outpatient. Approximately 31% of pts were admitted after 3 days from CAR-T infusion, and 27% of our pts were never admitted. Variables associated with aggressive disease can predict early hospitalization in pts receiving FDA-approved CAR-T. Extension of HBO practice to TCE is feasible.[Table: see text]
Overcoming barriers and improving genetic testing completion rate for hereditary cancer in an underserved population at a large safety net hospital.
Authors: Vara Autumn , Patel Tejal Amar 
Published: June 2023

1538 Background: Genetic testing is a routine practice in oncology care as outcomes of germline testing may impact surgical recommendations, open therapeutic options, as well as inform patients and family members of their cancer risks. Lyndon B. Johnson Hospital (LBJ) is a safety-net hospital that mainly serves low income and uninsured patients (pts), and LBJ oncology clinic is staffed by MD Anderson Medical Oncology faculty and fellows. Pre-test counseling with a certified genetic counselor was offered once a week by referral and transitioned to virtual template at the start of the COVID-19 pandemic. This transition in addition to barriers unique to the underserved population led to a decrease in test completion rates and introduced a backlog as patients were re-referred for completion of testing. We discuss our strategies in decreasing a 9-month backlog over the course of one year. Methods: Re-introduction of an on-site general oncology genetic counselor twice a week was implemented in addition to maintaining the virtual platform once a week. The on-site genetic counselor was embedded in the physician’s clinic and rotated to ensure coverage for all clinic days. Manual chart review was conducted by on-site genetic counselor and patients were rescheduled to in-person template in conjunction with other same day appointments to improve no-show rate. Patients electing to proceed with germline testing signed appropriate written consent, patient assistance financial forms, and submitted samples prior to leaving clinic. Results: From January 2019 through December 2022, a total of 1716 patients including re-referrals were scheduled and 728 patients seen. When genetic counseling service was available as referral outside of oncology clinic, the completed visit rate was 48%, which decreased to 26% in 2020 after COVID- 19 transition to virtual. The visit completion rate did improve to 36% in 2021 but the most improvement was seen with genetic counselor embedded in physician clinic with 69% in 2022. The number of genetic testing also increased with 79 ordered in 2021 to 211 ordered in 2022. Of those patients who met national criteria for germline testing and expressed verbal consent, 47% completed germline testing in 2021 which improved to 83% in 2022. Conclusions: In our experience, telehealth genetic services is not ideal in the underserved population as there are unique barriers. On-site embedded genetic counseling helps eliminate barriers by allowing patients to complete all steps necessary prior to leaving clinic, leading to successful test completion rates and improved quality of care.[Table: see text]
Antineoplastic and immunomodulating agent effects on immunization outcomes.
Authors: New Jacob , Cham Jason , Puglisi Leah , Smith Lana , Hong Lee , Fielding Russel , Kurian Sunil , Pandey Amitabh , Nicholson Laura 
Published: June 2023

1539 Background: Oncologists face a challenge in advising patients on the infection risk associated with antineoplastic and immunomodulating medications, as the extent of risk posed by each medication is not well understood. The rapid administration of COVID-19 immunizations across the population provides an opportunity to assess the influence of immunosuppressing medications on infection outcomes post-vaccination. This study evaluated the effect of antineoplastic and immunomodulating medications as classified by the World Health Organization Anatomical Therapeutic Chemical Classification System (WHO ATC) on post-vaccination risk of COVID-19 infection and antibody response to multiple SARS-CoV-2 epitopes using serial serologic assessments. Methods: At a large, tertiary healthcare system in San Diego, we conducted an observational cohort study from December 11, 2020, to September 22, 2022, comparing vaccinated adult patients taking WHO ATC-classified immunosuppressing medications (“immunosuppressed” group) with matched control patients not prescribed these medications (“immunocompetent” group) for the outcome of PCR+ COVID-19 infection. A subset of immunosuppressed and immunocompetent individuals was consented to provide serial assessments of antibody response to multiple SARS-CoV-2 epitopes using the Genalyte serologic platform. Results: 12,709 vaccinated immunosuppressed patients and 197,151 immunocompetent controls were identified for matched analysis. Receiving an immunosuppressing medication conferred increased risk of COVID-19 infection post-immunization (HR: 1.5, 95% CI: 1.38 – 1.63, p < 0.0001). Among immunosuppressing medications, PD1/PD-L1 inhibiting monoclonal antibodies and calcineurin inhibitors were associated with increased risk of COVID-19 infection (HR: 2.33, 95% CI: 1.35 – 4.04, p = 0.0038; HR 2.72, 95% CI: 1.78 – 4.16, respectively). Receiving three and four COVID-19 immunizations reduced this risk, except in patients taking calcineurin inhibitors. Among 87 consented participants, 218 samples from multiple timepoints revealed a decreased antibody response to both spike S1 and S2 subunits following third and fourth immunization. Despite decreased seroconversion, this study found medications like CD20 inhibiting monoclonal antibodies and folic acid analogs did not increase the post-immunization risk of COVID-19. Conclusions: These results help elucidate the relationship between antineoplastic and immunomodulating medications and COVID-19 immunization outcomes. In our patients, seroconversion efficacy did not always correspond to post-immunization infection, consistent with COVID-19 disease risk being multifactorial. The findings of this study inform oncologists’ shared decision-making process in advising patients of the risk of infection associated with immunomodulating medications and the potential impact on their vaccination response.
Distribution of alternate site infusion providers in the US.
Authors: Revol Cindy , Patton Catherine , Jain Sanjula , Oakes Allison H 
Published: June 2023

1542 Background: Spurred by the pandemic, chemotherapy treatments provided by alternate site infusion providers have been increasing. This diversification has the potential to increase access to care and improve patient satisfaction. However, it is currently unknown how equitably distributed these non-traditional infusion settings are, and whether these newer entrants are entering markets with need or markets with ample supply. In addition, many community oncologists are concerned about the ability to retain control over a patient’s treatment and preserve the profits earned from drug infusions. Further, there are concerns regarding the lack of robust data on the safety of alternate site chemotherapy infusions. Industry analysts anticipate steady expansion in US markets for alternate site infusion with chemotherapy being a strong driver of growth. The objective of this study was to examine the distribution of alternate site infusion services across the US. Methods: Leveraging the Medicare home health infusion (MHHI) provider database from CMS, we calculated the rate of MHHI providers per 1000 Medicare beneficiaries in each US state. We reviewed company information to determine the geographic footprint of 3 alternate site infusion providers. Results: The median MHHI rate was 0.013 per 1000 beneficiaries (CO), the average rate was 0.031, with a minimum of 0 (ND, SD, WY) and a maximum of 0.202 (IL). ND, SD, WY, IN, KY, and OK have the lowest concentration of MHHI providers, whereas OR, KS, WA, NE, CA, and IL have the highest concentration. 3 alternate site infusion providers are Option Care, UnitedHealth’s Optum Infusion Pharmacy, and Coram, CVS Specialty Infusion Services. Option Care has 162 in-person infusion centers located in 45 states. Option Care’s presence is highest in CA (24), FL (9), WA (9), OH (8), VA (8), and TX (7). UnitedHealth’s Optum Infusion Pharmacy has 30 in-person infusion suites located in 20 states, primarily concentrated in FL (6) and CA (4), but also provides home infusions in all 50 states. Like MHHI providers, neither of these alternate-site providers have locations in ND, SD, or WY. Coram announced a pilot with Cancer Treatment Centers of America in 2021 to provide home chemotherapy to patients in GA, but it is unclear if that pilot is ongoing; Coram provides home infusion therapy in 49 states. Conclusions: MHHI and alternate site infusion providers are in markets across the US. If alternate site chemotherapy infusion continues to grow, health system-owned and 3rd party entrant alternate site infusion providers are likely to prosper. Conversely, physician-owned practices could face competition and loss of important drug infusion revenue leading to increased consolidation among independent oncology providers. More research is needed to determine the impact on cost and patient outcomes of alternate site chemotherapy infusions – insights that will impact reimbursement and the rate at which these services continue to grow.
Evolving adjuvant estrogen therapy prescribing among breast oncology workforce.
Authors: Polcari Kayla , Keegan Grace , Sharpe Sarah , Hahn Olwen Mary , Lindau Stacy Tessler , Skolarus Ted , Modi Parth K. , Shubeck Sarah 
Published: June 2023

1546 Background: An oncologist shortage and rising number of breast cancer survivors has created a strained workforce. Care models that incorporate advanced practice providers (APPs) are recommended to meet this rising demand, particularly during survivorship. The objective of this study is to describe the evolving oncology workforce using anti-estrogen prescribing as a surrogate for breast cancer survivorship care. Methods: We used Medicare Part D Public Use Files to identify prescribers of anti-estrogen therapy from 2013 to 2020. We included medications primarily prescribed in the adjuvant setting for estrogen receptor positive breast cancer, including anastrozole, letrozole, exemestane, tamoxifen, raloxifene, fulvestrant, and toremifene. We assessed the volume of physician and APP prescribers and claims by provider type using descriptive statistics and logistic regression. Individual prescribers were included if they had more than 10 claims. Results: The overall number of anti-estrogen claims did not change significantly from 2013 to 2020, with an average of 3,224,361 annually. There was a significant increase in APP prescribers from 7,815 (8.6%) in 2013 to 12,961 (18.3%) in 2020. There was a reduction in physician prescribers by 24,815 (9.7%) over the same period with an overall net decrease of total prescribers of 19,669 (21.7%). The average annual claims per individual prescriber rose from 2013 to 2020 (Physicians: 2013: 37.5 to 2020: 45.2, p < 0.001; APP: 2013: 28.2 to 2020: 37.0, p < 0.001). The percentage of claims attributed to APP prescribers rose substantially from 6.6% in 2013 to 15.5% in 2020. This represents an increase from 220,000 prescriptions in 2013 to over 480,000 in 2020. Conclusions: Our results indicate an ongoing shift in the provider composition responsible for delivering breast cancer survivorship care. Over the time frame analyzed, there was no significant change in number of prescription claims annually, but an overall decrease in providers. Thus, the rise in APP prescribers is not driven by an increased prescribing volume, but rather seems to reflect an evolving surgical oncology workforce. This has significant implications for the future access to and delivery of timely high-quality cancer care.[Table: see text]
Prediction of cancer treatment response from histopathology images through imputed transcriptomics.
Authors: Hoang Danh-Tai , Dinstag Gal , Hermida Leandro C. , Ben-Zvi Doreen , Stossel Chani , Patil Tejas , Sammut Stephen-John , Lassoued Wiem , Allen Clint , Beker Tuvik , Jiang Peng , Golan Talia , Sowalsky Adam G. , Pine Sharon R , Caldas Carlos , Gulley James L. , Aldape Kenneth D. , Aharonov Ranit , Stone Eric , Ruppin Eytan 
Published: June 2023

1551 Background: In recent years, the use of tumour molecular profiling within the clinic has allowed for more accurate cancer diagnostics, as well as the delivery of precision oncology. Rapid advances in digital histopathology have allowed the extraction of clinically relevant information embedded in tumor slides by applying machine learning methods, capitalizing on recent advancements in image analysis via deep learning. However, as in many supervised learning approaches, predicting response to therapy using whole slide images (WSI) of tissue stained with hematoxylin and eosin (H&E) requires large datasets comprising matched imaging and response data, severely restricting the applicability of this approach. Methods: To overcome this critical challenge, we introduce here for the first time a generic methodology for generating WSI-based predictors of patients’ response for a broad range of cancer types and therapies, which does not require matched WSI and response data for training. The approach, termed ENLIGHT-DeepPT, consists of: (1) DeepPT, a new deep-learning framework that predicts exome-wide tumor mRNA expression from slides, and (2) ENLIGHT, a recently published response prediction algorithm, applied here to predict response based on the DeepPT predicted expression values, instead of measured values. Results: First, we study the ability to predict tumor expression, showing that DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Second, aligned with our key aim, we analyze six independent clinical trial datasets of patients with different cancer types that were treated with various targeted and immune therapies, on which DeepPT was never trained. We show that ENLIGHT, without any adaptation, can successfully predict the true responders from the expression values imputed by DeepPT, using only H&E images: ENLIGHT-DeepPT successfully predicts true responders in these cohorts with an overall odds ratio of 2.19, increasing the baseline response rate by 38.8% on average among predicted responders. Conclusions: ENLIGHT-DeepPT is the first approach to successfully predict response to multiple targeted and immune cancer therapies directly from H&E slides, without requiring any drug-specific training data. ENLIGHT-DeepPT can provide rapid treatment recommendations without requiring tumor sequencing, bringing precision oncology to low-income countries and other situations where NGS is prohibitive.
Relevance and accuracy of ChatGPT-generated NGS reports with treatment recommendations for oncogene-driven NSCLC.
Authors: Hamilton Zac , Naffakh Noor , Reizine Natalie Marie , Weinberg Frank , Jain Shikha , Gadi Vijayakrishna K. , Bun Christopher , Nguyen Ryan Huu-Tuan 
Published: June 2023

1555 Background: Next-generation sequencing (NGS) is a routine clinical practice in advanced NSCLC. NGS reports are information-dense and clinical interpretation remains a challenge. ChatGPT is a large language model (LLM) AI chatbot that can generate text in response to user-generated prompts. We sought to assess the clinical relevance and accuracy of ChatGPT-generated NGS reports with first-line (1L) treatment recommendations for NSCLC patients with targetable driver oncogenes. Methods: Eight driver oncogenes with FDA-approved targeted treatment for 1L stage IV NSCLC were identified in the latest NCCN Clinical Practice Guidelines available to the AI model (version 5, September 2021). The prompt, “Create a next-generation sequencing report with a list of first-line treatment options for a patient with stage IV non-small cell lung cancer with an [oncogenic driver].” was run in a separate “new chat” 10 times for each driver oncogene (n=80). Each ChatGPT output was recorded and scored. The Relevance Score (RS) awarded 1 point for every NCCN preferred option and 0.5 points for each “other recommended” treatment listed in the AI-generated output, divided by the maximum possible score for the driver oncogene. Spurious recommendations were awarded 0 points. The Accuracy Score (AS) represents reported treatment options listed in NCCN over the total number of treatments in a report. Percentage of reports listing an NCCN-preferred 1L therapy, a clinical trial as an option, and character and word count were also captured. Results: The average length of the AI-generated NGS reports was 117 words (range: 44 – 232). The median number of treatments recommended was 5 (range: 3 – 8). An oncogenic driver-specific preferred 1L treatment was included in 55 reports (68.8%), and a recommendation to explore clinical trials was listed in 43 reports (53.8%). The RS for the total sample was 0.59 (95% CI: 0.52 – 0.65), and the AS was 46.0% (95% CI: 40.2% – 51.8%). Conclusions: ChatGPT can rapidly generate concise NGS reports with treatment options for NSCLC with driver oncogenes. Recommendation relevance was moderate, and accuracy was limited with high variability across oncogenes. Overall, ChatGPT recommendations were promising given the complexity of the task with no prompting or training provided to the AI. As LLM AI platforms mature, they may generate more relevant and accurate NGS reports, offering a potentially valuable tool for NGS report annotation for clinicians, and increased accessibility for patients.[Table: see text]