bluuebunny/crossref_metadata_2025_split huggingface dataset:
Barricades to aiding cascading: Patient-reported barriers to uptake in the context of clinician-facilitated cascade testing for hereditary cancer syndromes.
Authors: Chandler Isabelle , Grant Benjamin , Epstein Emily , Brewer Jesse T , Larosa Taylor , Kalyan Alissa , Schulman Sarah , Llenas Ashley , Cantillo Evelyn , Holcomb Kevin , Chapman-Davis Eloise , Sharaf Ravi N. , Frey Melissa Kristen 
Published: May 2024

e13533 Background: Cascade testing extends genetic testing to relatives of individuals with known pathogenic variants. Cascade testing can prompt lifesaving cancer surveillance, however, up to two thirds of at-risk relatives do not complete recommended genetic testing. Previous studies suggest that a clinician-mediated approach of direct relative contact can increase testing rates. As part of an ongoing clinician-facilitated cascade testing intervention, we investigated the barriers to completion of cascade testing. Methods: All patients with a known cancer-associated germline mutation presenting to a gynecologic oncology clinic from 11/2023-2/2024 were offered clinician-facilitated cascade testing, an intervention whereby the genetics team was granted permission to contact designated at-risk relatives by telephone, review the familial mutation, and assist with accessing genetic testing. Patients that declined were asked about their decision and responses were analyzed using the socio-ecological model. Results: Ninety patients were offered clinician-facilitated cascade genetic testing and 50 (55%) declined. Of the patients that declined: median age was 45 (range 23-84), 41 (82%) self-identified as non-Hispanic, 38 (76%) as White, 23 (46%) were of Ashkenazi Jewish heritage, 23 (46%) had a personal history of cancer. There were no significant differences in any of the above variables when comparing those that declined and accepted the intervention. Twenty-nine (58%) patients declined because all family members were already tested. The most common barriers were “limited access to care” (5, 10%) at the healthcare community level, and “perceived readiness of relatives” (5, 10%) at the interpersonal relationship level. While these were the most common, most barriers were at the individual level including “perceived lack of responsibility” (3, 6%), “limited knowledge” (2, 4%), and “emotional burden” (2, 4%) (Table). Stated barriers were not associated with any demographical group. Conclusions: Although clinician-facilitated cascade testing has been shown to increase rates of relative testing uptake, several barriers persist at all levels of the socio-ecological model. While facilitated interventions should be individualized, our findings suggest that future interventions should focus efforts at all socio-ecological levels. Clinical trial information: NCT04613440 . [Table: see text]
Effect of a comprehensive cancer care pathway and a navigation cancer program on breast cancer care in a middle-income country.
Authors: Escobar Marilen , Bravo Maria A , Cervera Sergio , Osorio Ana M , Caicedo Jose Joaquin , Franco Sandra Ximena , Mantilla William Armando 
Published: May 2024

e13536 Background: Breast cancer (BC) is the most common cancer in women globally and in Colombia, with around 16.000 new cases estimated in 2022. Mortality associated with BC has decreased for 2 main reasons: screening that leads to early diagnosis and improved treatment of BC. However, BC related mortality remains stable in Colombia, with a 5-year overall survival of 74%, lower than other countries on the continent. This difference could be explained, among other things, by delays, barriers, and fragmentation of cancer care. Luis Carlos Sarmiento Angulo Cancer Treatment and Research Center (CTIC) is an institution designed for comprehensive cancer care, with specialized patient care through cancer clinics dedicated to a single disease (breast cancer, lung cancer, etc.). Every cancer clinic is associated with a cancer navigation program and has clinical care pathways with metrics that seek to monitor and reduce the time to diagnosis and treatment, among others. This study aims to describe the results of the comprehensive breast cancer care program and cancer navigation support in time to breast cancer diagnosis and treatment access. Methods: This descriptive study was carried out by retrospective reviewing of the navigation database from the breast cancer unit of the CTIC, sociodemographic information, clinical characteristics, and time to diagnosis (from first appointment to pathology report) and treatment were collected and described. A comparison between patients with comprehensive and fragmented care was done. Results: Since August 2022, 600 patients with confirmed breast cancer have been evaluated by the BC clinic, 401 (66.8%) patients were admitted through the cancer navigation program, 436 (72.6%) cases presented with a previously established diagnosis of breast cancer, and 164 (27.3%) were the novo cases. Of the novo cases, 37 (23.3%) cases received comprehensive care from diagnosis, with a time to diagnosis of 14 days, and time to treatment of 30.5 days, patients who did not receive comprehensive care presented a time to treatment of 68.1 days. Conclusions: A comprehensive cancer care and support from a navigation program significantly reduce the time to treatment in breast cancer patients. A comprehensive care model in Colombia has the opportunity to generate a better opportunity for access to diagnosis (14 days) and treatment (30.5 days) compared to the time to treatment data reported in the high-cost account (CAC) (27 and 52 days respectively). [Table: see text]
Impact of staffing an inpatient oncology consult service with dedicated hospital-based oncologists.
Authors: Brondfield Sam , Kwon Daniel H , Ko Andrew H. , Wachter Robert M. , Small Eric J. 
Published: May 2024

e13538 Background: No standard care model for hospitalized patients with cancer currently exists. The majority of oncology care is provided in the outpatient setting. Consequently, for many oncologists, inpatient care is a secondary responsibility. To address this issue, several U.S. institutions have changed their inpatient oncology models to include dedicated inpatient oncology-trained attendings (hospital-based oncologists). In this study, we investigate outcomes following such a change on an inpatient solid oncology consult service. Methods: This is a single-institution retrospective study of the University of California, San Francisco (UCSF)’s inpatient solid oncology consult service, which switched from a rotating outpatient oncologist attending model to a dedicated inpatient oncologist model in 2018. Since data prior to the switch were not available, we compared all inpatients who received an oncology consult (n=3974) with a comparison group (CG) of all inpatients with a solid tumor diagnosis who did not receive an oncology consult (n=3200) between fiscal years 2018 and 2023. We analyzed trends in case mix index (case complexity), in-hospital mortality index (observed/expected), 30-day unplanned readmission rate, length of stay index, and direct cost index using the Pearson correlation coefficient. In 2022, we conducted an anonymous retrospective pre/post-switch survey of hospitalists who had worked on the hospital medicine service both before and after the switch and compared mean satisfaction with oncology consultation (5-point scale) using Student’s t test. Results: Following the switch, the number of weeks per year covered by dedicated inpatient oncologists increased from seven (2018) to 39 (2023) out of 52. From 2018 to 2023, we found a significant increase in annual consults (495 to 919, r=0.95, p<0.01) and case mix index (2.30 to 3.30, r=0.90, p=0.01; CG 1.60 to 1.70, r=0.60, p=0.20), and a significant decrease in mortality index (1.59 to 0.70, r=-0.98, p<0.01; CG 0.90 to 0.48, r=-0.66, p=0.15). There were non-significant decreases in 30-day unplanned readmission rate (35.8% to 30.5%, r=-0.77, p=0.07), length of stay index (1.45 to 1.32, r=-0.75, p=0.08), and direct cost index (2.2 to 1.8, r=-0.61, p=0.20), similar to the CG. Mean (standard deviation) satisfaction increased from 3.27 (1.22) pre-switch to 4.53 (0.92) post-switch ( p=0.02, response rate 15/51, 29%). Conclusions: Switching to a dedicated inpatient oncologist model on a consult service was associated with decreased in-hospital mortality and increased satisfaction with oncology consultation despite growing case volume and complexity, while readmission rate, length of stay, and cost remained unchanged. This study adds to growing literature supporting dedicated inpatient oncologist attending models of care and is in line with recent literature from other specialties supporting similar inpatient care models.
Application of multidisciplinary team model based on full-course management in health promotion of patients with breast cancer.
Authors: Xie Xiuyuan , Liu Fenghe , Fei Yujie , Xu Haiping 
Published: May 2024

e13546 Background: To explore the application effectiveness of the multidisciplinary team model based on full-course management, in advancing the health promotion of breast cancer patients. Methods: This research involved a cohort of 84 breast cancer patients, recruited from the First Affiliated Hospital of Nanjing Medical University, spanning December 2022 and June 2023. These participants were divided into a control group and an intervention group using a convenience sampling method. The control group accepted routine nursing care, while the intervention group was treated with the multidisciplinary team approaches based on full-course management. These approaches included informal pre-admission interventions and multi-dimensional improvements to peri-operative patient comfort, integrated regimens combining Chinese and Western medicine to alleviate chemotherapy complications, diversified and extended nursing care focused on improving patients' quality of life, and facilitating physical and psychological rehabilitation. The two groups of patients were evaluated in satisfaction, comfort, quality of life, psychological state and other aspects. The results were evaluated by self-made satisfaction scale, breast cancer complications during chemotherapy questionnaire, Kolcaba Comfort Scale, Quality of Life Scale (QLQ-C30), self-rating Anxiety Scale (SAS) and self-rating Depression Scale (SDS). Patient outcomes were assessed in terms of satisfaction, comfort, quality of life, and psychological state. The results were evaluated by the self-made satisfaction scale, the breast cancer chemotherapy complications questionnaire, the Kolcaba Comfort Scale, the Quality of Life Scale (QLQ-C30), the Self-Rating Anxiety Scale (SAS), and the Self-Rating Depression Scale (SDS). Results: The intervention group showed statistically significant improvements in patient satisfaction, comfort and quality of life scores compared to the control group (P<0.05). Additionally, they exhibited a lower incidence of chemotherapy complications, severe anxiety and depression during the extended care period (P<0.05). Conclusions: The multi-disciplinary team model based on the full-course management demonstrated significant clinical benefits in the application of the full-course management of breast cancer patients. It effectively reduced chemotherapy-related complications, improved peri-operative comfort, decreased the incidence of severe anxiety and depression during the period of extended care, improved the physical and mental well-being of patients, leading to greater satisfaction and an enhanced quality of life.
Practice patterns in prostate cancer therapy among healthcare professionals: Comparison with expert recommendations from an online tool.
Authors: Becker Marie N. , Rosenthal Kristen M. , Dorff Tanya B. , McKay Rana R. , Schweizer Michael Thomas , VanderWeele David James , Morgans Alicia K. 
Published: May 2024

e13549 Background: The treatment landscape of prostate cancer (PC) is complex, and recent approvals of new agents and regimens further challenge healthcare professionals (HCPs) to select optimal therapy for patients with PC. We sought to identify practice patterns among community HCPs for PC by comparing HCP and key opinion leader (KOL) treatment recommendations using an online decision support tool. Methods: The online decision support tool was developed with 5 KOLs who provided therapy recommendations for 96 patient case scenarios encompassing mHSPC, nmCRPC, and mCRPC based on factors including disease volume and symptoms, comorbidities, previous therapy, and biomarker status. HCPs entered specific patient and disease factors into the tool along with their intended treatment plan and were shown the 5 individual KOL recommendations for the patient case. An analysis of HCP selected therapy compared with KOL recommendations was performed. Results: Between September 2023 and January 2024, 286 patient cases were entered by 100 HCPs. KOL consensus defined as ≥3 in agreement. HCP therapy selection discordance with KOL recommendations was 69% for nmCRPC (n = 64 cases), 42% for mHSPC (n = 125 cases), and 46% for mCRPC (n = 97 cases). The level of discordance was 63% (n = 43 cases) for nmCRPC with a PSADT <10 months and 81% (n = 21 cases) with a PSADT ≥10 months (Table). Regardless of PSADT, selection of therapy for nmCRPC without listed comorbidities was highly discordant 82% (n = 34 cases). In mHSPC, the highest level of discordance was seen in cases with de novo, symptomatic, high-volume disease, and diabetes at 73% (n = 11). Discordance was 54% for de novo mHSPC with symptomatic disease (n = 52 cases). HCP selection of 1L, 2L, or 3L therapy for mCRPC was 44% to 47% discordant with KOL recommendations regardless of prior therapy. Selection of therapy for mCRPC with HRR mutations including BRCA (n = 29) was 48% discordant. Among HCPs who initially selected treatment options that diverged from expert recommendations or were uncertain about therapy selection, 48% (n/N = 75/157) intend to change their therapy selection to align with the experts. Detailed data analysis with KOL recommendations will be presented. Conclusions: This analysis suggests differences in clinical practice between HCPs and KOLs for multiple case scenarios in PC and suggests that use of the decision tool may lead to increased alignment of treatment choices with KOLs. [Table: see text]
Objective acuity measures for infusion therapy staffing: A predictive model approach—Phase I.
Authors: Egan Alden , Gehrke Daniela , He Bo , Garey Jody S. , Ye Ping , Shapert Debra , Sassano Jennifer , Garnett Ashley , Velador Sonia , Payne-De Bock Judi 
Published: May 2024

e13553 Background: Acuity is a measure of the complexity of patient care and an estimate of nursing workload. The use of acuity tools is shown to improve care standards, nurse satisfaction and productivity. Existing acuity tools have barriers to adoption, including increased nursing workload, estimate variations among different nurses and clinical care settings, and poor understanding of validity of acuity measures. We aim to build a predictive model for prospectively determining acuity levels and staffing requirements in infusion therapy to address these gaps. This project will be implemented with a phased approach. Here we describe Phase I, to establish a standard measure and documentation process for acuity, then collect and analyze a large data set to quantify the relationship of acuity scores to selected patient characteristics. Methods: A US Oncology Network nursing committee developed evidence-based guidelines for acuity measurement and documentation in August 2023. Nine sites from four independent, community oncology practices were selected to perform acuity rating and documentation using the developed guidelines. Multiple training sessions on the guidelines were conducted with nurses from selected sites. Nurses documented acuity scores (level 1~6) and start time for patients’ infusion visits in the EHR 8/30/2023 – 11/30/2023. Acuity documentation rates were calculated and provided to each site weekly to gain feedback and engagement. Acuity scores were extracted from the electronic health record using natural language processing. Structured data on potential predictors including patient demographics, performance status, lab, and treatment-related information were also collected. Results: A total of 14,610 infusion room visits (5,139 distinct patients) with documented acuity scores were reported. The acuity documentation rate from each site was consistent by week and ranged 60 – 96%. Table reports prevalence of select features by acuity score. Conclusions: An operational workflow was successfully implemented to collect and analyze acuity scores and relevant features. Features of interest include chemotherapy Cycle 1 Day 1, five or more drugs and highly emetogenic treatment. In Phase II, the collected acuity scores and clinical features will be used to build a predictive model to objectively estimate acuity. Phase III will focus on the deployment of the predictive model to oncology practices. [Table: see text]
Opportunity cost of oncology subspecialist opinion.
Authors: Barzi Afsaneh , Liang Crystal , Wright Carol , Nathwani Nitya , Wong Debra A. , Sachs Todd M. 
Published: May 2024

e13578 Background: The adoption of precision oncology has resulted in a drastic rise in the cost of cancer care in the United States. Payers, providers, and professional organizations are implementing strategies to curb this rising cost. These efforts are mainly focused on the providers patterns of care, such as prescribing behavior and risk assessment for needs such as ER visits and hospitalizations. Most efforts are cross-cutting and intended to work across different tumor types. Yet, with the precision nature of cancer care these cross-cutting efforts have not succeeded. AccessHope (AH) provides an independent subspecialist review of the management cancer as a covered benefit through the employer (Accountable Precision Oncology: APO). The aim of this service is optimizing care delivery to the current and evolving paradigms for each cancer type and sub-type. Here we describe overutilization of treatments and assessments of APO. Methods: AH database was accessed for de-identified cases (with contractual de-identification rights) for this analysis. Cases were completed 1/1/2022 – 12/31/2023. Descriptive statistics was used to describe the observed patterns identified. Results: Among 3644 APOs, 428 (11.7%) had evidence of overutilization. Gastrointestinal, hematological, and thoracic cancers represented 75% of the over utilization cases (Table). Overutilization was categorized by systemic therapy, radiation therapy, invasive procedures, imaging, and testing. Systemic therapy was the most common category (67.8%) and included non-indication use and extended duration of use. This was followed by imaging (22.2%). Systemic agents overutilized varied by cancer site. Bevacizumab and oxaliplatin were commonly overutilized in gastrointestinal cancers; rituximab, imatinib, and dasatinib in hematological malignancies; and check point inhibitors (pembrolizumab, atezolizumab, and durvalumab) in thoracic malignancies. In the imaging category, PET scan overutilization was observed across different tumor types (14.7% of the total volume). We also observed overutilization of molecular testing with ctDNA (Signatera) being at the top of the frequently overutilized tests in cases with no data to support a role for it. Conclusions: This patient centered approach identified areas of overutilization in evaluation and treatment of patients through the expert review process. The reviewer’s depth of knowledge about reported data and limitation of treatments and evaluations is the key to this process. Further analyses of patterns of care and categorization of the overutilization patterns is underway. [Table: see text]
Comparing literature-based cell-free miRNA panels to whole genome miRNA screening for cancer detection.
Authors: Hsieh Tsung-Ting , Lee Ko-Han , Hsieh Jason Chia-Hsun , Chang Yu-Chuan 
Published: May 2024

e13587 Background: Cell-free miRNAs (cf-miRNAs) found in bodily fluids like plasma or serum are adept at detecting cancer. When constructing a cancer detection model with a reasonably sized training sample, it seems logical that employing whole genome screening could enhance prediction performance and unveil novel miRNAs. However, screening all cf-miRNAs could be costly and its potential improvement compared to a curated panel remains uncertain. To evaluate the trade-off between accuracy and cost-effectiveness, our study aims to compare the performance of two approaches: a literature-based cf-miRNA panel and a whole genome screening. We utilized real-world datasets to assess the effectiveness of these two methods in cancer detection. Methods: To curate a cf-miRNA panel, we conducted a comprehensive review of published miRNA-related databases, identifying 27 databases, including dbDEMC 2.0, miRCancer, miRStress, HMDD, and others. Of these, 11 databases were both available and downloadable, yielding 196,839 records (database entries). Focusing on cf-miRNAs, we filtered the records to only include those clearly identified as originating from plasma or serum, resulting in 13,595 cf-miRNA records. Next, to ensure robustness, we employed two strategies: requiring multiple records for a given miRNA and confirming its mention in multiple databases to finalize the cf-miRNA panel. For comparison of prediction performance, we obtained a large-scale dataset from the Gene Expression Omnibus, specifically the GPL21263 platform, for modeling experiments. This dataset comprised 8,174 subjects with 2,565 miRNA targets across seven cancer types derived from various cf-miRNA-based cancer studies. We then trained machine learning models on both the curated panel and the full miRNAs from this dataset to facilitate a comparative analysis. Results: Out of the 13,595 cf-miRNA records, 499 miRNAs had over 4 records, and 612 miRNAs were mentioned in multiple databases. There was an overlap of 339 miRNAs, forming our final cf-miRNA panel. The model accuracy using this panel to distinguish between seven cancer types was 67.62%. In contrast, directly employing machine-learning to model whole genome screening resulted in an accuracy of 93.00%, demonstrating a significant improvement compared to the panel-based results. Conclusions: Our study curated a cost-effective cf-miRNA panel of 395 miRNAs, demonstrating the capability to distinguish multiple cancers. However, while the curated panel exhibited reasonable efficacy in cancer detection, the whole genome screening model displayed superior discriminatory power. Hence, for optimizing cancer detection methods, especially in large-scale datasets, employing whole genome screening appears to be a more promising strategy.