tbuckley/cabot-search huggingface dataset:
Independent validation of 30-day emergency department visit after initial chemotherapy A-PROACCT model.
Authors: Thomas T. Maroney, Yusen He, Srujankumar Dhannapuneni, Nikita C. Shah, Amy Iarrobino Laughlin, Tomas Dvorak
Journal: Journal of Clinical Oncology (2024)

e23243 Background: This study assessed model performance and, more importantly, the clinical usefulness of the PROACCT model created by Grant et al. (JAMA, 2019), refined as A-PROACCT by Stein et al. (JOP, 2023) with data from Orlando Health. The predictive performance of models anticipating acute care events within thirty days (ACE30) of initial chemotherapy administration (ICA) were evaluated. Methods: Stein et al. models classified high-risk patients as those whose model output risk score was at or above the 90 th percentile. They studied 5153 ICAs between July and November of 2021, of which 559 (10.8%) had an ACE30. Their first model used drug category, age group, ED visits and hospitalizations in the prior year, and cancer type, and had sensitivity (Sen), specificity, (Spec), C-Statistic (C-Stat), and positive predictive value (PPV) of 0.28, 0.93, 0.79 and 0.18 respectively. Their second model added insurance category, number of anti-cancer agents, race, and BMI category and reported Sen, Spec, C-Stat, and PPV of 0.30, 0.94, 0.80 and 0.23 respectively. Of the high-risk patients, 33.6% and 34.1% had an ACE30 respectively. Of the low-risk patients, 8.3% and 8.1% had an ACE30 respectively. Our data were propagated through the two models. Results: Between February of 2012 and April 2021, Orlando Health had 15,483 distinct patient visits with ICAs. Overall, 2046 (13.2%) had an ACE30. Model one had Sen, Spec, C-Stat, and PPV of 0.19, 0.92, 0.65 and 0.27 respectively. Model two had Sen, Spec, C-Stat, and PPV of 0.19, 0.91, 0.65 and 0.25 respectively. Both models had an accuracy of 0.82. This demonstrated our data fit the Stein model. Of the 1460 ICAs identified as high-risk by model one, 387 (26.5%) had an ACE30, and of the 14,023 ICAs identified as low-risk, 1659 (11.8%) had an ACE30. Of the 1549 ICAs identified as high-risk by model two, 393 (25.4%) had an ACE30, and of the 13,934 ICAs identified as low-risk, 1653 (11.9%) had an ACE30. The difference of ACE30 rates between high risk and low risk groups were statistically significant (p &lt; 0.0001) in both models. This demonstrated both models were clinically useful in identifying chemotherapy patients at high risk of acute care events. Conclusions: These models allowed for clinically relevant stratification of patients into meaningful high-risk and low-risk groups (26.5% vs 11.8% with our data) for risk of acute care events within 30 days of initial chemotherapy administration. Nevertheless, only 26.5% of these high-risk patients actually had an acute care event within thirty days of initial chemotherapy administration. Further research is needed to improve the precision of identifying high-risk patients, by potentially adding more clinical variables, using alternative sampling methods, and employing nonlinear and more complex machine learning methodologies.
EHR documentation of cost discussions and financial interventions for a cohort of patients with advanced cancer: Findings from a retrospective chart review-based study.
Authors: Aaron Burkenroad, Sidharth Anand, Sarah F. D'Ambruoso, John A. Glaspy, Anne M. Walling
Journal: Journal of Clinical Oncology (2024)

e23150 Background: Financial Toxicity (FT), the adverse impact of high medical costs on quality of life, notably affects many oncology patients. In a prior initiative to improve quality of life for advanced cancer patients, a palliative care-trained nurse practitioner (PCNP) was embedded in an academic oncology practice. Patients completed the Edmonton Symptom Assessment System (ESAS) and Canadian Problem Checklist (CPC) to gauge physical symptoms, psychosocial issues, and financial concerns. However, the incidence of self-reported financial issues and electronic health record (EHR) documentation of cost discussions and interventions remain unclear for this patient group. Methods: The study included adult oncology patients with advanced cancer seen by the PCNP from January 1, 2020, to January 1, 2022. We assessed incidence of self-reported financial concerns via CPC checklists in this cohort. Ten charts underwent detailed manual review for evidence of cost discussions or referral to finance-related interventions for up to 1 year from the initial consult with the PCNP or until death. During the review, we identified keywords in documentation of cost discussions and finance-related interventions to create a keyword library. We iteratively compared the library to our reference standard manual chart review to ensure 100% sensitivity. We then employed this keyword library to evaluate the remaining charts. Descriptive statistics were employed to assess correlations between self-reported financial concerns, chart documentation of cost discussions or financial interventions, and patient demographics. Results: Out of 109 eligible patients, 71% (77) completed pre-visit questionnaires, with 30% (23) reporting financial issues. Of this group, 43% (10) died during the study period. Average follow-up was 5.0 months among the decedents. Among those reporting financial concerns, 65% (15) had documented cost discussions or financial assistance referrals in the EHR, involving physicians, social workers, and other clinic staff. Most interventions addressed medication costs and referrals to financial assistance as indicated. Patient demographics (age, sex, insurance type) showed no apparent association with chart documentation of cost discussions or financial assistance. Conclusions: We used retrospective chart review to evaluate the extent of documentation of cost discussions and finance-related intervention in a cohort of patients with advanced cancer. In our patient cohort, 30% self-reported financial concerns, a proportion consistent with previously reported incidence of FT among oncology patients. Notably, 35% of the patients with known financial concerns had no other relevant documentation in the EHR. More work is needed to establish best practices for systematic screening for FT and interventions to support patients.
Real-world experience with fostamatinib in patients with immune thrombocytopenia: Results of an observational study (FORTE).
Authors: Ruchika Goel, Waqas Azhar, Robert P. Numerof, Donna Chow, Bhavesh Shah
Journal: Journal of Clinical Oncology (2024)

e23289 Background: Immune thrombocytopenia (ITP) is an autoantibody-mediated disease in which platelets are prematurely phagocytosed by Fcg-receptor-bearing macrophages in a spleen tyrosine kinase (SYK)-dependent signaling pathway. Corticosteroids (CS) are used to suppress the immune response, but long-term use carries a heavy burden of toxicity. Subsequent treatments for ITP include fostamatinib, a potent oral SYK inhibitor approved in 2018 based on two randomized, placebo-controlled, phase 3 trials. In trial patients, who received fostamatinib as second-line therapy following CS with or without immunoglobulins (IVIG), 25 of 32 (78%) patients achieved a platelet response of ≥50,000/µL, which was sustained for a median of 83% of treatment days. Here, we report real-world experience with fostamatinib as second-line therapy for ITP from a multi-center, prospective, observational study. Methods: The study (FORTE; NCT04904276) enrolled adult patients with ITP and an insufficient response to prior CS and/or IVIG. Patients were treated according to their clinician’s discretion, and data were collected for up to 12 months at clinic visits. Results: Sixteen patients were enrolled, and 15 were treated. Of the 15, 9 (60%) were female and the median age was 48 years (range, 20-92). 12 (80%) patients had prior CS and 6 (40%) prior IVIG. 7 (47%) patients completed the study and 8 discontinued treatment due to adverse events (4), lack of efficacy (2), and patient decision (2). After initiation of fostamatinib, 93% (14/15) of patients achieved ≥1 platelet count ≥50,000/μL. Median platelet count increased over time from 43,000/μL (IQR 19,000-105,000) at baseline to 167,000/μL (IQR 96,000-180,000) at Month 12. The median cumulative duration of elevated platelet count was 32 weeks (IQR 6.4-49.4). Concomitant CS were used by 7 (47%) patients at baseline, all of whom were able to taper as early as Month 1 and discontinue their dose by Month 3 in 4 patients, Month 6 in 2 patients, and Month 9 in 1 patient. Five patients had ITP-related AEs (4 Grade 1 and 1 Grade 2): gingival bleeding (2), mucosal haemorrhage (2), fatigue (1), contusion (3), headache (1) and epistaxis (1). There were 3 serious AEs in 2 patients: Grade 3 diarrhea in 1 and Grade 2 dyspnea and chills in 1. Overall safety results were consistent with previous studies of fostamatinib. Conclusions: Real world use of fostamatinib as documented in this observational study demonstrated efficacy and safety as second-line therapy for ITP. Fostamatinib allowed successful tapering and discontinuation of CS while maintaining platelet counts above 50,000/μL. Clinical trial information: NCT04904276 .
Developing a manual clinical trials screening process in a diverse southern gynecologic oncology practice in the Deep South.
Authors: Margaret Klein, Humza Pirzadah, Yasmeen Magharehabed, Andrew G. Chapple, Tara Castellano, Amelia Jernigan
Journal: Journal of Clinical Oncology (2024)

e23209 Background: At this time, there is no standard clinical trial screening process or definition that has been adopted within Gynecologic Oncology. In our low resource, highly diverse Gynecologic Oncology patient population, we sought to create an equitable, adaptable, manual screening process that better reflected our patient population. Our objective is to describe our clinical trial screening process and our success in improving trial enrollment and a matched trial portfolio. Methods: An IRB-approved, QI project was implemented in July 2022 to evaluate trial access for Gyn Onc patients. First, screenable events were defined as: the start of one’s first scheduled visit, bi-monthly tumor boards, weekly pre-op meetings, and by keeping track of on a shared Epic list. Potential patients were those with a screenable event: new patients or diagnoses, regimen changes, progressions, and recurrences. Events were categorized into screen positive or screened no trial available. Screen positives were further categorized as screen fail, screen positive, enrollment failure, or enrolled. Data about patients was collected via weekly research team meetings. Monthly meetings occurred to review progress. This data was compared to trials available, number of patients with trail available, and those that enrolled. Reasons for enrollment fails were tracked to improve access and anticipate barriers. Results: Overall demographic data of patients was collected. The average age of participants was 60.67 years (SD = 13.45), and the average distance to a treatment center was 59.27 miles (SD = 137.43). Other demographics are presented in Table 1. For each month, the percentages of “screen no trial available (SNTA)” events and patients who screened positive and did enroll on trial were recorded. Over time, SNTA rates stayed stable, but enrollment increased. Patient preference accounted for 32.8% of enrollment fails (n = 42), pre-existing symptoms/conditions accounted for 23.4% (n = 30), and distance/location accounted for 21.1% (n = 27). During a time of high employee turnover in the summer months of 2023, there was a rise in enrollment fails due to staffing (n = 6, 4.7%). Conclusions: Through a collaborative quality initiative, we describe an effective process of clearly defining and tracking our patient population and ‘screenable events’ for which all patients are screened and offered trial participation if eligible. We show that we improved understanding of the patient population, built a clinical trial portfolio better matched to population served, exceeded national averages for enrolling patients on trials, and are moving toward improved number eligible over time. [Table: see text]
Costs and access barriers to ondansetron: A national analysis of Medicare part D and Medicare Advantage plans.
Authors: Changchuan Jiang, Joshua Liao, Xin Hu, Arthur S. Hong, Sonali Niyogi, Megan A. Mullins, Zhiyuan Zheng, Xuesong Han, Ryan David Nipp, Robin Yabroff, Ya-Chen Tina Shih
Journal: Journal of Clinical Oncology (2024)

e23126 Background: Seniors living with cancer and receiving prescription drug benefits through Medicare Part D Prescription Drug Plans (PDPs) can face cost and access barriers in the forms of prior authorization and quantity limit policies. While over half of Medicare beneficiaries are now insured with drug benefits through Medicare Advantage, it remains unclear how costs and access barriers compare between PDPs and MA drug plans (MADPs). This study compared plan-level costs and prevalence of prior authorization or quantity limit policies between PDPs and MADPs for oral ondansetron, an essential and widely used antiemetic for patients with cancer. Methods: We used 2023 Q3 MA and PDP data from the Center for Medicare and Medicaid Services, excluding employer-sponsored and Supplemental Need Plans (including dual-eligible plans) and plans with &lt; 10 enrollees. We focused on the four most common generic ondansetron forms: 4mg and 8mg tablets, and 4mg and 8mg orally disintegrating tablets (ODT). To compare medication quantities, we calculated the median (IQR) cost of 30-day supply (90 dosage units), defining plan-level price as the average unit cost for each formulation. Price benchmarks were defined using Mark Cuban Cost-plus Drug Company cash prices, which reflect fixed markup to negotiated wholesale prices. T-test and Chi-square tests were used for comparison. Results: Across 813 PDPs and 3512 MADPs, MAPDs had lower median costs for a 30-day supply of ondansetron than PDP plans (4mg tab: $16.1 vs $29.2; 4mg ODT: $38.0 vs $56.4; 8mg tab: $24.7 vs $35.6; 8mg ODT: $37.2 vs $54.4, all p &lt; 0.01). Median costs for both PDPs and MAPDs were higher than benchmarks (66-155% across formulations; all p &lt; 0.01). PDPs and MAPDs had similarly high prior authorization rates (83.6% vs 83.4%, p = 0.89), but MAPDs used quantity limits more frequently (22.5% vs 16.5%, p &lt; 0.01). There was little variation in prior authorization and quantity limit policies across formulations. Conclusions: Ondansetron costs in both PDPs and MAPDs were higher than benchmarks. Compared to PDPs, MAPDs offered ondansetron at lower costs but used policies creating access barriers for patients either at similar (prior authorization) or higher (quantity limit) frequency, burdening patients, physicians, health systems, and pharmacies. [Table: see text]
Utilizing large language models (LLMs) to pre-label candidate concepts from in conceptual development landscape reviews in oncology.
Authors: Kristian Thorlund, Milad Nourizade, Reza Jafar, Stacie Hudgens
Journal: Journal of Clinical Oncology (2024)

e23198 Background: Labeling and identifying concepts from qualitative studies and patient interviews in oncology can be challenging and time consuming, often requiring several iterations. Large language models (LLMs) may be tailored to serve as a ‘co-pilot’, thus reducing errors and time to completion. We therefore aimed to examine whether utilizing LLMs to pre-label concepts (i.e., how patient’s feel or function) from medical oncology literature text can be done at comparable accuracy as human. To examine whether such LLM pre-labelling can dramatically reduce the time required for manual labor in conceptual development landscape reviews in oncology. Methods: We developed GPT-4 (OpenAI) prompts to pre-label concepts reported in abstracts of qualitative study references. We further developed GPT-4 prompts to categorize each pre-labeled concept into one of the following relevant high-level category: clinician reported symptoms, cognitive impacts, symptoms due to treatment, symptoms due to diagnosis, emotional impacts, impact on caregiver, other impacts, physical appearance, physical function, and social impacts. The prompts were extended to also capture diagnosis, treatments, patient reported outcomes, as well as generic terms or irrelevant terms that would otherwise erroneously be captured under the concept category in the early iterations of the prompt-engineering. The prompts were tested on 48, 37, and 38 (total of 123) eligible references from three conceptual development reviews covering colorectal cancer (CRC), non-small cell lung cancer (NSCLC), and acute myeloid leukemia (AML), respectively. Results: The LLM pre-labelled a total of 153, 131, and 159 candidate concepts across the CRC, NSCLC, and AML reviews, respectively. In all three reviews, clinical reported symptoms, emotional impacts, and social impacts all accounted for 18-25% each of the pre-labelled concepts, whereas physical function and social impact accounted for 5-9% each. A total of 2 (1.3%), 3 (2.3%) and 4 (2.5%) pre-labels were predicted to belong to the wrong high-level category. Incorrectly categorized labels were dispersed across most categories and should have been categorized as ‘other impacts’. In the NSCLC review, one pre-label categorized as impact on caregiver and two as other impacts were erroneously extracted concepts. Conclusions: LLMs are effective at capturing and pre-labelling concepts for further review, evident by the high number of concept labels extracted. Further high-level categorization with LLMs to guide manual reviewers also appears highly accurate.
The integration of big data analytics in examining the effects of mental illness screening on mortality and burden of illness among patients with cancer.
Authors: Minu Mohan, Joel Brian Epstein, Naheed Alam, Shaniza Haniff, Roberto Pili, Satheesh Kumar Poolakkad Sankaran
Journal: Journal of Clinical Oncology (2024)

e23083 Background: Cancer patients receiving cancer care in US hospitals undergo notable psychological suffering, characterized by manifestations of multiple psychiatric disorders and a further doubling of healthcare spending each year. The psychological burden of illness (BOI) frequently accompanies the physical obstacles of the disease, hence increasing the intricacy of cancer care. Analysis was conducted on cancer patients admitted to hospitals in the US in 2017 for the treatment of prostate (PC), cancers of the lip, oral cavity, and pharynx (CLOP), lung (LC), and leukemia. The aim was to understand better and compare the differences in mental illness screening (MIS) and its impact on these patients. Methods: We employed generalized linear models to examine the association between MIS and outcomes––BOI, such as cost, total charge, length of stay (LOS), and in-hospital mortality after controlling for clinical and patient variables. Results: Among 224,540 LC, 178,470 patients underwent MIS. This was 151,285 vs. 58,125 among PC; among CLOP, 35,770 vs. 18,495; for leukemia, this was 53,019 vs.18,759. In the adjusted analysis, MIS among the LC cohort was associated with lower length of stay—(coefficient, 0.96, 95% CI, 0.92-0.98), lower total charges, (0.94, 0.92-0.96), and lower mortality (aOR, 0.77, 95% CI, 0.73-0.82). In the LC cohort, when compared to Whites, Blacks (1.11, 1.05-1.17) and Others (Native Americans, Asians, and Others (1.1, 1.02-1.20) had longer LOS. Compared to high-income neighborhoods, low-income neighborhoods showed higher LOS (1.09, 1.03-1.153), and compared to "Central" counties of metro areas of ≥ 1 million population, Not metropolitan or micropolitan counties had a lower LOS (0.86, 0.80-0.92). Private insurance holders had lower total charges than Medicare beneficiaries (0.84, 0.81-0.88). Females, when compared to males, had a lower total charge (0.96, 0.94-0.98), and when compared to Whites, Hispanics (1.35, 1.25-1.45), and Others (1.28, 1.19-1.37) had a higher total-charges. And compared to Whites, Others had a higher in-hospital mortality (aOR, 1.16, 95% CI, 1.03-1.31). Further, the analysis was stratified into surgical and non-surgical cohorts in the LC cohort. Compared to LC, none of the other solid or liquid cancer cohorts, MIS showed no beneficial association with BOI or mortality. Conclusions: The LC cohort showed a positive association between MIS and BOI and in-hospital mortality. To provide holistic treatment for all cancer patients, including MIS as a standard practice is advantageous. This study can offer helpful information for future research on the impacts and implementation of routine mental illness screening among patients with cancer.
The Progress Tracker Breast Cancer Registry: Feasibility of a longitudinal patient-led, patient-reported outcomes (PROM) registry.
Authors: Shaniah Leduc, Amanda Williams Gibson, Michelle Liane Dean, Kimberly Carson, Omar Farooq Khan, Doris Howell
Journal: Journal of Clinical Oncology (2024)

e23169 Background: A breast cancer diagnosis has the greatest disability-adjusted life years lost of all cancers and significant impact on physical, psychoemotional, social and overall global functioning. Directed by Breast Cancer Canada, a registered non-profit patient-led organization and data managed by the University of Calgary’s POET Program, PROgress Tracker uses a novel, peer-to-peer support model for recruitment, engagement and retention, and is the first national longitudinal and non-interventional PROMs registry. Our aim is to demonstrate the feasibility and potential of this registry in centering patient voice and lived experience to transform breast cancer management. Methods: PROgress Tracker, with 10-year enrollment goal of 50,000 Canadians with Stage 0-IV breast cancer, extends a series of validated PROMs (PROMIS, BREAST-Q, FACT-B, GAD, PHQ-9, COST-FACIT, ISI and ESASr-CA) via a digital platform every 3 months for up to 10 years. Dynamic customization of additional PROMs (PRO-CTCAE, BREAST-Q) based on patient and treatment-specific trigger questions assess evolving components of wellbeing, including financial stress, work life and adverse treatment effects. Results: Recruitment began in October 2023. 162 participants from all Canadian regions including remote/rural geographic areas have shared baseline demographic and clinical data including stage, genetic/molecular tumor markers, treatment type(s) and completed an initial series of PROMs. Comprehensive PROMs including sensitive topics (finances, sexuality, mental health) were completed with minimal missing data ( &lt; 5%); 3-month follow-up surveys show a current retention rate of 57%. Preliminary analysis: median age of participants 54 yrs, 95% identify as Caucasian, and 57% are currently working. 46% reported financial stress (99% response rate); 63% reported ongoing symptoms requiring follow-up. 6% were BRCA+ and 19% triple negative, 7% experienced recurrence, 3% Stage IV, 75% received systemic and/or radiation therapy, 38% received targeted therapy. Conclusions: The lived experience of breast cancer is integral to patient-centred change in the era of precision/personalized medicine and is captured by PROgress Tracker using a diverse set of periodic PROMs to understand the evolution of global measures of wellbeing over time. Initial data indicates that this novel peer to peer model via digital administration of comprehensive and longitudinal PROMs is feasible. This initiative demonstrates attaining this scope of data is achievable, has interest and participation from the national breast cancer community and growing capacity to accrue important, real-time data to inform best practice and identify additional supports required for breast cancer care. While early feasibility is evident, further outreach and recruitment initiatives will ensure diversity of participants.