bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of enrollment in Medicare Advantage plans versus fee-for-service in patients with a late-stage diagnosis of gynecologic cancer.
Authors: Zhang Elyse Xinyue , Ward Kevin C , Meisel Jane Lowe , Switchenko Jeffrey M. , Lipscomb Joseph 
Published: June 2024

11140 Background: In the United States, uterine cancer is the most common gynecologic (GYN) cancer; and ovarian cancer causes more deaths each year than any other GYN cancer. There are currently no recommended population-wide screening tests for ovarian or uterine cancer, which are heavily concentrated in older women. Medicare is the primary health insurer for 97% of Americans aged 65 years and older. This study is the first to examine the association between Medicare enrollment plan – Medicare Advantage (MA) versus fee-for-service (FFS) – and stage at diagnosis among older women newly diagnosed with ovarian or uterine cancer. Methods: Using the linked Surveillance, Epidemiology, and End Results (SEER) registries and Medicare enrollment data, we identified 101,193 women aged 65 years and older with newly diagnosed ovarian or uterine cancer between 2007-2019. We categorized patients into two groups: 1) those continuously enrolled in Medicare MA for six months prior to their diagnosis, through the diagnosis month, and the month following diagnosis; 2) those continuously enrolled in Medicare FFS within the same eight-month window. Late-stage was defined as “Distant” stage (with “Local” and “Regional” stages representing an earlier-stage diagnosis) using the SEER Summary Stage variable. The association between Medicare enrollment plan and stage was examined through multivariable logistic regression modeling that adjusted for sociodemographic characteristics. The influence of each predictor on the difference in the probability of late stage was summarized as an adjusted marginal effect (ME). Results: Among uterine cancer patients, 37% had MA insurance. Compared with Medicare FFS enrollees, the adjusted percentage of late-stage diagnosis was 0.6 percentage points (ppt) lower for MA enrollees (95% CI = -1.1-(-0.1); P<0.05). Notably, patients were more likely to have a late-stage uterine diagnosis if they were: non-Hispanic Black or Hispanic (vs. non-Hispanic White); age 75 and older (vs. between 65 -74); and residing in a lower SES neighborhood. Among ovarian cancer patients, 34% had MA insurance. We found no significant difference between Medicare MA and FFS enrollees in ovarian cancer stage at diagnosis. Of note, Non-Hispanic Black patients were significantly more likely to be diagnosed with late-stage disease compared to Non-Hispanic White, and likewise for patients aged 75 and older (vs. between 65-74). Conclusions: Among Medicare beneficiaries (age 65+) diagnosed with uterine cancer, those enrolled in an MA plan were significantly less likely to be diagnosed at a later stage. In similar analyses for ovarian cancer, there was no such MA - FFS difference in the probability of late-stage. As enrollment in Medicare Advantage plans continues to grow, it becomes increasingly important to identify whether there are significant outcome differences between MA and FFS plans.
Knowledge, attitudes, and current practices toward lung cancer palliative care management in China: A national survey.
Authors: Chen Mengting , Yu Huiqing , Zhang Junhui , Yang Hong , Yang Liejun , Tian Ling , Wang Sixiong 
Published: June 2024

11143 Background: To demonstrate the status and differences in knowledge, attitudes, and practices (KAP) of lung cancer palliative care (LCPC) management, and to measure patient controlled analgesia (PCA) in cancer pain management in of China. Methods: A questionnaire on LCPC management was used in this study, which involved a total of 2093 participants from 706 hospitals in China. Seven major components make up the questionnaire, including chi-square tests or Fisher exact probabilities to measure the differences in KAP between hospitals grades. Comparing distributions of ordered data between groups was done using the Kruskal-Wallis H test or the Mann-Whitney U test. Multiple choice questions use multiple response cross analysis. Correlation was evaluated by the Spearman correlation coefficient. Results: 84.2% participants believed that anti-tumor therapy is equally important as palliative care. The satisfaction rate of participants from grade 3 hospitals, which was significantly higher than that of grade 2 and grade 1 hospitals (χ²=27.402, P=0.002). The most common symptoms requiring LCPC was pain. The major barriers toward to LCPC were “Patients and families are concerned about the safety of long-term use of palliative care related drugs”. The most common reasons for the use of PCA treatment were 31.1% participants thought “Patients with systemic application of large doses of opioids or adverse reactions to opioids that cannot be tolerated”. The top three barriers toward PCA treatment of cancer pain were (i) worry about adverse reactions of drug overdose, (ii) worry about opioid addiction, and (iii) increase of patients' economic burden. In the past 24 months, 33.9% of the participants had not participated in online or offline training related to palliative care of lung cancer. Conclusions: Chinese healthcare workers are in need of training for lung cancer palliative care and, in particular, for controlling cancer pain symptoms.
Breaking through barriers: Unraveling challenges in clinical trial participation among oncologic patients in a developing country.
Authors: Bushatsky Erika , Cândido Andressa Liz , Vasquez Quispe Daniel Agustin , Paiola Rafaela , Machado Barata Tavares Alessandra Cristina , Cruz Felipe Melo , Arruda Lilian Martins 
Published: June 2024

11144 Background: Clinical trials are vital for advancing cancer research and treatment development, yet obstacles to participation impede progress, particularly in regions with limited clinical research awareness, such as Brazil. Methods: This study was conducted in a single cancer center in São Paulo, Brazil, between 2020 and 2022. A tailored questionnaire comprising demographic (age, gender, income) and barrier-related sections explored patient-related (10 questions), protocol-related (7 questions), and physician-related (5 questions) barriers. Results: Among 206 oncologic patients enrolled in the study, 43.7% were from the public healthcare system, and 56.3% had private insurance. Patients who self-declared as white were 59.7%, and those who self-declared as brown/black were 35.9%. Patient-related challenges included unfamiliarity with trial participants (84.6%), concerns about daily life disruptions (75.4%), and transportation difficulties (66.2%). Protocol-related obstacles involved fears of unknown side effects (62.3%), inability to choose treatment (47.6%), and potential assignment to a placebo group (46.8%). Physician-related barriers included communication issues, strained doctor-patient relationships (94.7%), and patient deference to doctors' decisions (55.4%). Higher-income patients and those in the public health system demonstrated greater clinical research awareness. Conclusions: The study emphasizes the critical role of patient education in overcoming barriers to clinical trial participation in oncologic patients. Furthermore, it underscores the necessity of addressing disparities among minority populations, such as non-white individuals with lower incomes, to transform clinical research and ensure universal access to newer therapies. Efforts should be directed towards inclusivity, bridging awareness gaps, and fostering a comprehensive understanding of the benefits of clinical trial participation for all cancer patients.
Timing of EGFR or ALK inhibitor initiation and survival among patients with advanced NSCLC.
Authors: Tanvetyanon Tawee , Chen Dung-Tsa , Gray Jhanelle E. 
Published: June 2024

11148 Background: ALK or EGFR inhibitor is an ideal frontline treatment for patients with advanced non-small cell lung cancer (NSCLC) harboring targetable alteration in ALK or EGFR. However, in the real-world setting, frontline treatment may be delayed or unideal. For such patients, the magnitude of survival benefit when initiating ALK or EGFR inhibitor at a much later timepoint remains unclear. Methods: We utilized a nationwide electronic health record-derived, deidentified database collected from diverse oncology practices across the United States to investigate the timeliness of preferred targeted therapy (PTT), defined as osimertinib, lorlatinib, alectinib or brigatinib. Individualized data obtained from patients with stage IV NSCLC at diagnosis treated with PTT during 2018 to 2023 were analyzed. Timing of PTT initiation was modeled as time-varying covariate. Results: Data from 3250 patients were analyzed: 2640 patients (81%) with EGFR mutation and 610 patients (19%) with ALK rearrangement. The median time to PTT was 7 weeks from diagnosis with 26.4% of patients started PTT within 1 month. Landmark analyses using timepoints ranging from 1 to 12 months after diagnosis showed that at all timepoints, patients who had started on PTT had a significantly better survival than those who had not (Table). In a multivariable analysis, time to PTT ≤ 1 month from diagnosis was an independent predictor of survival: HR 0.74 (95% CI: 0.62-0.89), p=0.002. Prolonged time to PTT was significantly associated with advanced age, positive smoking status and genomic class being ALK as compared to EGFR. Conclusions: In this population-based analysis, an initiation of PTT occurring as late as at least 1 year from diagnosis still resulted in a significant survival benefit, though the magnitude of benefit appeared decreased as time passed. [Table: see text]
Differences in baseline characteristics and healthcare costs among insured patients with advanced cancer with vs without clinical trial participation.
Authors: Stockl Karen M , Morin Pamela , Reyes Carolina , Schroeder Brock , Certa Julia M , Tucker Jamie , Hostin Damon , Fox John Leonard 
Published: June 2024

11154 Background: Despite concerted efforts to improve clinical trial participation (CTP), enrollment remains low. Perceived additional costs to the patient or health plan may be barriers to CTP; low biomarker testing rates may be another. This study assessed differences in characteristics of patients with CTP versus patients without CTP in an insured population with advanced cancer. Methods: A retrospective analysis was conducted using de-identified administrative claims data from commercially insured and Medicare Advantage (MA) enrollees in the Optum Labs Data Warehouse. Patients ≥18y with claims evidence of advanced cancer and systemic therapy between 01/01/2018 and 02/28/2022 were stratified into 2 groups: 1) with CTP: ≥1 claim with a CTP diagnosis (ICD10 Z00.6) and ≥1 claim with a Q modifier on or within 90 days after index date; and 2) without CTP: no claims with a CTP diagnosis or Q modifier. Patients with >1 primary cancer, T-cell therapy, or <360 days baseline or follow-up (unless death) enrollment were excluded. Biomarker testing, targeted therapy use, and healthcare costs per patient per month (PPPM) were assessed in the baseline period. Results: Of 61,490 patients identified, 1753 (3%) had CTP and 59,737 (97%) did not have CTP; 4% of commercial and 3% of MA patients had CTP. Most common tumor types were breast (27%; 2% had CTP), lung (16%; 3% had CTP), digestive tract (15%; 2% had CTP), and prostate (15%; 3% had CTP). Patients with CTP were younger and more frequently had documented biomarker test use in the baseline period than patients without CTP (Table). In unadjusted analyses, the CTP group had higher healthcare costs in the baseline period prior to CTP regardless of insurance type, driven by 51% higher systemic cancer therapy costs and 35% higher ambulatory visit costs. An ongoing propensity score matched analysis will evaluate the impact of CTP on cost of care in the follow-up period. Conclusions: Consistent with prior studies, the overall CTP rate among patients with advanced cancers was low (3%). Baseline costs (prior to CTP) were higher for patients that later enrolled in clinical trials than for patients without CTP. Further research is ongoing to assess differences in follow-up healthcare costs for patients with vs without CTP adjusting for baseline characteristics. [Table: see text]
Integration of a machine learning model-generated surgical risk score into the EHR and preoperative workflow.
Authors: Mahuron Kelly , Chen Chen , Carlin Cameron S , Seth Naini S. , Nelson Rebecca A. , Uranga Carolina , Lai Lily L. 
Published: June 2024

11163 Background: We previously developed a machine learning model (MLM) that accurately predicts postoperative complications (POC) for cancer inpatients. As laborious manual entry of patient data is a barrier for risk calculator use, and risk constantly changes depending on clinical status, we sought to integrate our MLM into the electronic health record (EHR) and preoperative workflow as a readily available surgical risk score (SRS) that is generated using real-time data. Here, we report on the integration process and survey results regarding its functionality and impact on patient care. Methods: A MLM that predicts severe POC (CD Grade ≥3) for cancer inpatients undergoing same-hospitalization operations was previously developed using EHR data. To integrate our MLM into the Epic EHR, we developed a real-time infrastructure (RTI) using the cloud-based platform Azure. EHR data is inputted to RTI and processed in real-time to generate model outputs. These outputs are then sent back to the EHR through the Epic Cognitive Computing Platform to generate each patient’s specific SRS. The SRS is dichotomized as “high” or “low” risk based upon a previously determined threshold and is displayed as a “Best Practice Advisory (BPA)” when a surgical case request is entered. In addition to the automated BPA, the SRS is sent to the primary surgeon as an InBasket Case Message. To elicit feedback of our EHR-integrated SRS, a survey was distributed to surgical providers at our institution. Results: After integration of our MLM into the EHR preoperative workflow, 185 surgeries were completed between November 16, 2021 to July 31, 2023. The 30-day severe POC rate was 27.6%, and our MLM had precision of 44.7% and recall of 74.5%, resulting in AUROC of 0.78 and AUPRC of 0.53. 35 surgical providers (40% primary surgeons, 34% surgical fellows, 26% advanced practice providers) from the divisions of surgical oncology, colorectal surgery, and gynecologic oncology completed our survey in July 2022 and July 2023. 28 (80%) of providers stated that they have interacted with the SRS through either BPA or InBasket Case Messages. Of these providers, 21 (75%) strongly agreed or agreed that the SRS was visible at appropriate times, and 18 (64%) strongly agreed or agreed that the SRS contains relevant information to assess surgical risk. 8 (29%) strongly agreed or agreed that the SRS was used to facilitate preoperative discussion. The 2023 survey additionally asked whether the SRS impacted the decision to operate; among providers who had interacted with the SRS, 4 (36%) strongly agreed or agreed with this statement. Conclusions: Integration of a real-time, MLM-generated SRS into the EHR and preoperative workflow can be successfully performed. While our integrated SRS is visible to surgeons and contains risk assessment felt relevant to the operation, the impact of the SRS on clinical care and decision making remains unclear.
Effect of combination of genomic variation–based machine learning and clinical pathology on accurate diagnosis of tumors: Lung adenocarcinoma and lung squamous cell carcinoma.
Authors: Gu Weiguang , Wang Haitao , Zhuang Mengxia , Hao Qing , Wang Zhizheng , Liu Wenjin , Lu Leilei , Dong Xiaowei , Pang Fei , Qin Hongli , Wang Kai 
Published: June 2024

11174 Background: Non-small cell lung cancer (NSCLC) is the most prevalent form of lung cancer, with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) being the predominant subtypes. Given the significant differences in treatment approaches and clinical outcomes between LUAD and LUSC, accurate identification of these pathological subtypes prior to treatment initiation is crucial. Methods: This study aimed to enhance the diagnostic accuracy for LUAD and LUSC by integrating a machine learning artificial intelligence (AI) model with the expertise of pathologists. The AI model was trained and validated on a cohort of 10,693 and 5,571 cases from the OrigiMed database, each confirmed by at least three pathologists. Targeted sequencing of 450 cancer-related genes was performed. Results: Analysis of the validation set demonstrated an overall accuracy of 89.2% across 28 tumor types, with individual accuracies ranging from 22.2% to 100%. For the top one prediction, the AI model achieved an accuracy of 82.7% for LUAD and 67.9% for LUSC. However, when considering the top three predictions, the accuracy significantly increased to 92.1% for LUAD and 93.0% for LUSC. To further validate the diagnostic capability of the AI model, a large sample of 4,531 LUAD cases and 207 LUSC cases from 4,502 patients was collected for comparative analysis with pathologists' diagnoses. The results indicated that 87.9% of LUAD cases and 83.6% of LUSC cases were consistent with the AI model's diagnosis, while 4.9% of LUAD and 9.7% of LUSC cases showed discrepancies. To investigate these inconsistencies, a subset of 30 LUAD cases and 16 LUSC cases was selected for re-evaluation by independent pathologists. Four poorly differentiated cases from the discrepancy group were ultimately diagnosed as 2 LUADs and 2 LUSCs, supporting the initial AI diagnosis. For instance, Patient 40 was initially diagnosed with LUSC; however, the AI system identified the pathology as LUAD, which may be attributed to the detection of the KIF5B-RET fusion. This diagnosis was subsequently corroborated by an additional pathologist who observed gland-like structures and ambiguous solid mass formations within the tumor tissue, consistent with LUAD histopathology. Conclusions: In summary, we have presented a machine learning AI model that leverages next-generation sequencing (NGS) technology for the auxiliary diagnosis of cancer. By applying this AI model to diagnose LUAD and LUSC and comparing it with the diagnoses made by human pathologists, we have demonstrated that the integration of pathological diagnosis and AI machine learning can significantly enhance and even surpass the diagnostic capabilities of human physicians. This advancement holds great potential in improving the accuracy of tumor diagnosis and the precision of treatment.
Rethinking the impact of pretransplant malignancy on eligibility for double lung transplantation (DLT): An analysis of 23,291 recipients.
Authors: Woo Wongi , Kim Hye Sung , Bharat Ankit , Chae Young Kwang 
Published: June 2024

11180 Background: The outcomes for double lung transplant recipients with a history of pretransplant malignancy (PreTM) have not been extensively studied in a large, multicenter database. Given the rising need for transplants among older patients with a history of cancer and the improving outcomes of DLT, this study aimed to analyze recipient outcomes in the modern era. Methods: This study evaluated the United Network for Organ Sharing (UNOS) registry for adult DLT performed between 2005 and 2023. Patients with a history of previous or multi-organ transplants, and those with donors who had a history of malignancy, were excluded. Propensity-score matching was used to compare patients with or without PreTM. Posttransplant malignancies (PostTM) were classified into cutaneous and non-cutaneous types. The primary outcomes were overall and PostTM-free survival. Results: Of the 23,291 DLT recipients, 1,870 recipients (8.0%) had a history of PreTM, which was classified into twelve types. Patients with PreTM experienced worse overall (HR 1.20 [95% CI 1.12-1.29], p<0.001) and PostTM-free survival (HR 1.32 [95% CI 1.24-1.41], p<0.001). After propensity-score matching for age, sex, and race, the differences in overall survival between the two groups were diminished (HR 1.05 [95% CI 0.97-1.13], p=0.229). Although PostTM-free survival was still worse in the PreTM group, this difference was not observed after excluding cutaneous PostTM (HR 1.06 [95% CI 0.99-1.15], p=0.116). The incidence of PostTM of the same PreTM type among patients with PreTM was 13.5% (253/1870), which was not higher than the incidence of de novo PostTM incidence among patients without PreTM (p=0.633). Conclusions: Patients with PreTM show similar overall survival rates after DLT as those without PreTM, despite a higher incidence of PostTM, mainly cutaneous. Importantly, there is no increased risk of the original cancer type recurring in PreTM patients compared to the risk of de novo malignancy. These findings highlight the necessity for a more nuanced evaluation of transplant candidacy to prevent premature exclusion of PreTM patients from potentially life-saving surgeries. [Table: see text]
Head and neck cancer survivors: Long-term nutrition impact symptoms, eating problems, and barriers to care impact psychosocial health.
Authors: Saxton M Claire , Ruwala Richa , Jaisle Alyssa , Fearnley Kirstin , Andac-Jones Elif 
Published: June 2024

12044 Background: Head and neck cancer (HNC) survivors experience significant long-term side effects of their treatment, and health-related quality-of-life (HRQoL) assessments of HNC survivors are still early in development. This survey captured long-term nutrition impact symptoms, eating problems, psychosocial impact, and barriers to accessing health care of HNC survivors. Methods: The Cancer Support Community (CSC) conducted an online survey with participants from CSC, Head and Neck Cancer Alliance, and Support for People with Oral and Head and Neck Cancer (SPOHNC). 172 “long-term survivors” (LTS), at least 2 years past initial diagnosis completed the survey. Most respondents were white (94%) & female (58%). The average age was 64. The most common treatments reported were radiation (93%), surgery (66%), and chemotherapy (59%). Results: Physical and psychosocial issues are prevalent and persistent among LTS. Almost all (99%) LTS reported experiencing eating problems since diagnosis, and 92% had symptoms persist into the last 7 days. Dry mouth (85% ever/68% in last week) and problems swallowing (82%/62%) were most common. Prevalence of side effects was independent of stage of cancer and time since initial diagnosis. 42% of LTS reported still not eating a solid food diet (30% “soft” food; 9% feeding tube; 4% liquid or pureed food). 63% ever used a feeding tube. For those no longer using a feeding tube, 71% used it for ≤6 months. Current users had feeding tubes for a median of 39 months. Weaning from a feeding tube was most likely before 14 months. 62% of LTS reported still feeling self-conscious when eating, 45% feeling embarrassed about their eating habits, 44% having their daily activities affected by eating problems, 37% said they avoid going out in public when it involves eating or drinking. Despite this, 27% reported never seeing a health care professional (HCP) or mental health professional (MHP) to manage their eating problems & psychosocial impact. Only 11% of LTS ever met with MHPs to address their distress. Female LTS of younger age and those with Medicare insurance were more likely to meet with HCPs (except dentists for Medicare recipients) and MHPs. Financial, transportation, & logistical concerns were top barriers to receiving care. 19% reported cost of care as a moderate to great barrier to cancer treatment. LTS reported difficulty paying for dental work (29%), supplemental nutrition drinks (11%), and other products to manage eating problems (9%). Conclusions: Although HNC’S are generally considered “curable,” the nature of the disease and the required aggressive treatment regimens leave LTS with a broad range of common physical and psychosocial issues that are rarely addressed. Survey data highlight almost universal, long-term persistence of eating and nutrition problems which cause significant psychosocial impact over LTS’s lifetime.