bluuebunny/crossref_metadata_2025_split huggingface dataset:
Atrial flutter in a patient population with cancer: Comparison of incidence, mortality, and readmission rates.
Authors: Afzal Muhammad Sohaib , Farooq Faryal , Kumar Manoj , Sultan Muhammad , Nasir Bilal , Devarkonda Vishal , Byreddi Laxman Yashwant , Atluri Sundeep , Ali Shafaqat 
Published: June 2024

e23079 Background: Cardiac tachyarrhythmias are common in cancer patients. Much has been studied regarding atrial fibrillation, but the impact of atrial flutter (AFL) in different malignancies is under-studied. We aim to compare the occurrence of atrial flutter (AFL), its mortality, and readmission rates in cancer patients stratified by different types. Methods: The National Readmission Database (2016-2020) was queried to identify all-cause admissions for patients with active malignancy of any origin. The study population was divided into six subgroups based on the type of cancer (colorectal, renal, lung, breast, prostate, and hematological). Multivariate regression analysis was utilized for adjusted odds of mortality. A propensity score matching (PSM) model matched malignancy of interest with other malignancies to obtain incidence rates. Results: Among 10.6 million all-cause cancer-related hospitalizations, about 0.4% developed AFL. After propensity matching, when compared to other malignancies, AFL had the highest incidence in hospitalizations associated with lung malignancies (0.75%), followed by hematological (0.66%), prostrate (0.57%), renal (0.49%), colorectal (0.38%) and breast (0.31%) malignancies [p < 0.05]. Moreover, cancer hospitalizations complicated by AFL were associated with higher mortality. AFL was associated with the highest odds of mortality in colorectal malignancies (aOR:2.80), followed by hematological (aOR:2.67), renal (aOR:2.66), lung (aOR:2.22), breast (aOR:2.12), & prostate (aOR:1.76) malignancies [p < 0.001]. AFL was also associated with frequent readmissions in cancer patients. The rates of 30-day AFL-related recurrent admission were highest in lung malignancies (18.3%), followed by hematological (18%), renal (16.6%), prostate (15.1%), colorectal (14.7%) & breast (14.2%) malignancies [p < 0.05]. Conclusions: The incidence of AFL in nationwide hospitalizations among cancer patients was ~ 0.4%. AFL was found to have the highest incidence and readmission rates in lung malignancies, while AFL-related mortality was highest in colorectal malignancies.
The outcome of COVID-19 infection among Saudi oncology patients.
Authors: Badran Ahmed Ali , Arabi Tarek , Ba Theeb Ahmed , Ba Wazir Abdulmalik , Ateya Heba Aly , Shaheen Amgad , Sabbah Belal Nedal , Tlayjeh Mohamed , Aldabbagh Ziyad , Alaswad Marwan , Elshenawy Mahmoud Abdelsatar , Nofal Marwa , Badran Judy , Bazarbashi Shouki 
Published: June 2024

e23085 Background: Little data are available surrounding the outcomes and risk factors of COVID-19 in Saudi oncological patients. This study aims to elucidate the outcomes of COVID-19 infection among Saudi oncology patients and associated risk factors. Methods: We retrospectively reviewed the medical files of oncology patients who were diagnosed with COVID-19 at the King Faisal Specialist Hospital and Research Centre. The time from a positive PCR until death or last follow-up was calculated as COVID-specific survival. A p-value less than 0.05 was selected as the threshold for statistical significance. Results: 161 oncological patients were included in our analysis. The mean age was 53.83±15.81. 85 (52.8%) patients were female, 17 (10.6%) had a positive history of smoking, and 57 (35.4%) were obese. 70 (43.5%) patients had diabetes mellitus, 64 (39.8%) had hypertension, and 25 (15.5%) had dyslipidemia. The most common cancer in the group was breast cancer, which was present in 24 (14.9%), followed by non-Hodgkin lymphoma, colon cancer, and acute leukemia, respectively. 57 (35.4%) patients had no evidence of disease (NED) at presentation. Furthermore, 65 (40.4%) patients had received antineoplastic therapy within 30 days before infection. 25 (15.5%) patients had stage A COVID-19, 59 (36.6%) had stage B, 48 (29.8%) had stage C, and 29 (18%) had stage D. There was no difference between active and no NED patients in remission in regard to the stages of COVID-19 infection at presentation (p = 0.05). However, the stages of COVID were less severe in patients who received antineoplastic therapy (p = 0.02). 32 (19.9%) patients received tocilizumab during the acute phase of infection. Only 5 (3.1%) patients suffered COVID-specific death. Therefore, the median COVID-specific survival was not reached. Tocilizumab (p = 0.34), corticosteroids (p = 0.77), ACE inhibitors (p = 0.45) had no impact on COVID-specific death in our patient population. In patients who received steroid treatment, the duration of corticosteroid had no impact on survival (HR: 0.76, p = 0.39). Ventilation also had no impact on survival (p = 0.55). There was no difference between patients who received antineoplastic therapy within 30 days from infection and those who did not (p = 0.99). Finally, we noted no difference in survival between patients with active disease and NED patients (p = 0.17). Conclusions: COVID-related mortality is lower in Saudi oncology patients compared to other countries. Early management and admission of oncological patients may result in overall improved outcome. In line with some studies, antineoplastic therapy can reduce COVID-19 severity, possibly due to reduced ACE receptor expression.
Oral oncolytics medically integrated dispensing: Impact on medical spending compared to non-integrated dispensing.
Authors: Urick Ben , Marshall Landon , Gleason Patrick P. , Atherton Brady , Leach Joseph W. 
Published: June 2024

e23098 Background: Medically integrated dispensing, consisting of multidisciplinary care teams dispensing drugs within clinics, has been associated with reduced medical spending for members receiving oral oncolytics (OO). However, there is little understanding of how medical spending differs across sites of care by dispensing channel. Objective: To compare 6-month pre/post all-cause medical spending by site of care between integrated and non-integrated dispensing channels among commercially insured members initiating OO therapy. Methods: Prime Therapeutics’ integrated pharmacy and medical claims database was used to identify members newly initiating an OO of interest between 1/1/2019 and 12/1/2022. Members were required to be continuously enrolled 6 months before and after index, had a cancer diagnosis, and had > $0 medical spending. Dispensing channel Integrated Health System Specialty Pharmacy (Int-HSSP), Integrated Physician Office (Int-Phys), Non-Integrated (Non-Int) was assigned using index OO fill. The primary outcomes were change in all-cause medical spending, medical drug spending, and non-drug medical spending divided into five site of care categories: inpatient, outpatient facility, emergency department, provider office visits, and other. Regression analysis was used to compare change in spending across channels, adjusting for demographics, health status, and cancer type. Results: A total of 30,928 (Int-HSSP: N = 5,500; Int-Phys: N = 2,550; Non-Int: N = 22,878) commercially insured members met all study criteria. Mean age ranged from 53.9 (Int-HSSP) to 56.1 years (Int-Phys). Compared to Non-Int (Unadjusted All Medical Pre: $56,214, Post: $67,050), significant cost savings were observed in the Int-Phys (Unadjusted All Medical Pre: $64,794 Post: $64,670; adj. diff -$5,672 [-9,384 to -1,960; p = 0.003]). Across categories of medical spending, the largest decreases were observed for inpatient medical spending (adj. diff -$2,663 [-5,000 to -326; p = 0.026]) and medical drug spending (adj. diff -$2,082 [-$4,248 to 84; p = 0.060]) with the remaining $927 in savings coming from differences across all other sites of care combined. No significant differences were observed for other medical spending categories or for Int-HSSP compared to Non-Int. Conclusions: Int-Phys dispensing channel for OO drugs was associated with a $5,672 reduction in medical spending compared to Non-Int, nearly half of which was driven by changes in inpatient non-drug medical spending alone. These findings support managed care models which include integrated oncology dispensing as a potential opportunity to reduce medical spending. Future work should assess the impact of dispensing channel on total cost of care and differences in healthcare utilization and in patient care experiences by dispensing channel.
Hospitalization risk in multiple myeloma episodes of care.
Authors: Liu Haibei , Indurlal Puneeth , Ye Ping , Turnwald Brian , Garey Jody S. 
Published: June 2024

e23101 Background: The Enhancing Oncology Model (EOM) is a total cost of care (TCOC) program that was initiated in July 2023. Participating groups are expected to reduce expenditures while delivering high-quality care. Hospitalization (IP) is an important quality metric and cost driver in TCOC programs such as EOM. Understanding how cancer treatment may impact IP is essential for success. Multiple Myeloma (MM) treatment has transformed with multi-agent treatment as the standard of care (SOC), routinely incorporating 3 or more drugs used concurrently to maximize response. We examined the impact multi-drug treatment had on IP rates in MM patients. Methods: Using Parts A, B and D Medicare claims data from EOM baseline period (January 2019 - June 2022) for 12 participating practices, we extracted a unique count of chemotherapy drugs and IP admissions attributed to 6-month episodes of care. Dexamethasone (dex) was included even if claims were not found. Planned and cancer-surgery related IP were excluded using the Clinical Classifications Software Planned Admission Procedure Categories and per EOM specifications. IPs were dichotomized as Yes/No. A logistic regression model was developed to evaluate the association between the number of unique drugs and the unplanned IP, adjusting for variables: prior chemo, age at episode start, race, and HCC count. A 3-drug regimen was established as the reference (including dex) based on SOC. Results: 11,613 episodes had a primary diagnosis of MM, with at least one IP occurring in 2,382 episodes. The number of episodes (% IP) per drug count group are 1-2: 6636(16.3%); 3: 3772 (23.6%); 4: 863 (30.8%); 5+: 342 (40.9%). Detailed statistics are provided in Table 1. Compared to a 3-drug regimen, 4+ drugs increased the risk of IP, while episodes with 1-2 drugs had a lower risk of IP after adjusting for age, race, HCC count and prior treatment. Conclusions: Our findings can guide the design of care transforming interventions aimed at avoiding unnecessary IP while using guideline concordant SOC treatments for MM, driving TCOC reduction. Identifying patients with a higher likelihood of IP helps practices target patient monitoring programs. To understand why patients with prior treatment had lower IP identifying maintenance following initial treatment and patients receiving 3 or more drugs after failure of prior therapy, are worth exploring further. CMMI Disclaimer: The statements contained in this document are solely those of the authors and do not necessarily reflect the views or policies of CMS. The authors assume responsibility for the accuracy and completeness of the information contained in this document. [Table: see text]
Factors influencing the clinical added value (CAV) in France over more than a decade.
Authors: Duriez Lucas 
Published: June 2024

e23102 Background: The rise of cancer drug prices has raised alarm over the need to base pricing decisions on the clinical added value (CAV). The French National Authority for Health (HAS) is responsible for health technology assessment (HTA) in France. For each indication retained for reimbursement, the HAS assesses the CAV on a 5-point scale ranging from I (Major) to V (absence of clinical added value). This assessment is primarily based on medical evidence. The CAV score is one of the factors contributing to price negotiations between the French ministry and pharmaceutical companies. Methods: A retrospective and descriptive study analysis of all indications in oncology (hematology and solid tumors), excluding accelerated approvals for innovative treatments, was conducted by the HAS comparing the 2010-2015 and 2016-2022 periods. For each assessment, information relative to the level of evidence and the clinical effect of the drug from the HAS opinion were collected and focused on the study’s conclusive endpoints and design. Results: The global distribution of CAV score between the two studied periods (2010-2015 and 2016-2022) was similar. However, the distribution of CAV score based on study design differed between the two periods. Regarding non comparative studies, the proportion of indications that were attributed a CAV score V increased 1.7 times between 2010-2015 and 2016-2022 and those with a CAV score I-III was nearly divided by 3. Differences were equally observed for the distribution of CAV score between the two periods based on the conclusive endpoints in the pivotal study. For the studies with a conclusive endpoint on overall survival, the rate of CAV I-III was multiplied by 1.68 (an increase from 6 to 36 cases). Concerning the cases with a progression-free survival endpoint, an observed increase of 1.3 times was noted for the CAV I-III. Lastly, studies with a conclusive overall response rate (ORR) saw an increase of 1.4 times for the CAV V as well as a decrease of 0.76 times for the CAV I-III. Over the most recent period (2016-2022), the conclusive endpoints identified in the evaluated studies were predominantly the overall response rate (93%, n = 42/45) for phase II studies. For phase III studies, progression-free survival and overall survival were respectively identified in 45% and 30% of the cases. Conclusions: Thisstudy shows that the number of indications evaluated has increased and that the assessment of the CAV is closely correlated with the choices of the study design (comparative or not) and the primary endpoint (clinically relevant or not). However, other elements underpin and qualify its valuation such as the medical need. These elements are reviewed in the HAS Guidance which emphasises overall survival as a primary endpoint and comparative data.
The journey of patients with lung cancer: The gap between symptom onset and treatment.
Authors: Linaras Maistros , Skampardonis Konstantinos , Chantzara Evangelia , Leontopoulou Vasiliki , Christodoulopoulos George , Kotsakis Athanasios , Koinis Filippos 
Published: June 2024

e23119 Background: Prompt access to health care services is a priority in public health policies. The aim of this study was to map the journey of patients (pts) diagnosed with lung cancer (LC) and determine the time interval (TI) from symptom onset (SO) to treatment initiation and assess the impact on survival. Methods: A retrospective cohort study was conducted at the University Hospital of Larissa. Pts’ demographic and disease-related data were captured from medical records. The TI from SO to first doctor visit (StD), SO to first oncologist visit (StO), diagnosis to treatment initiation (DtT) and SO to treatment initiation (StT) were estimated. Overall survival (OS) was defined as the TI between treatment initiation and the date of death or the date of last follow-up. OS were estimated using the Kaplan–Meier analysis and the comparisons were computed with the log-rank test. Results: Overall, 251 sequential pts with metastatic LC were included in the study. Pts’ mean age was 71 years (range 35-88). The majority were men (82%) and 24%, 32%, 28% and 16% were diagnosed with small cell lung cancer (SCLC), squamous cell (SCC), adenocarcinoma (ADC) and large cell (LCC) LC, respectively. The median StD and StO was 32 (0-212) days and 102 (11-608) days, respectively. No difference was detected across genders, age ( > or < 70), family history of cancer or not, and area of residence (rural, urban). The median StT and DtT was 123 (30-851) days and 26 (1-105) days, respectively, with this time intervals being shorter among pts with SCLC compared to pts with non-small cell LC (NSCLC) ( p: 0.006 and p< 0.001, respectively). Pts with sort StT intervals had significantly improved OS, compared to pts with longer StT intervals (SCLC p:0.044, NSCLC p:0.004). Conclusions: To the best of our knowledge, this is the first study aiming to determine specific TI from SO to treatment initiation for pts with LC in Greece and assess the potential impact on OS. Our data revealed a substantially prolonged StT (~4months) that is associated with worse survival rates. This indicates a need to improve public awareness of LC symptoms, enable pts’ access to specialized health care services and facilitate earlier diagnosis and treatment.
Costs and access barriers to ondansetron: A national analysis of Medicare part D and Medicare Advantage plans.
Authors: Jiang Changchuan , Liao Joshua , Hu Xin , Hong Arthur S. , Niyogi Sonali , Mullins Megan A. , Zheng Zhiyuan , Han Xuesong , Nipp Ryan David , Yabroff Robin , Shih Ya-Chen Tina 
Published: June 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 < 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 < 0.01). Median costs for both PDPs and MAPDs were higher than benchmarks (66-155% across formulations; all p < 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 < 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]
Financial toxicity screening preferences in patients with breast cancer.
Authors: Gharzai Laila A. , Liu Yingzhe , Sun Zequn , Mady Leila , Mohn Michelle , Larson Alexis , Kircher Sheetal Mehta , Yanez Betina , Jagsi Reshma , Carlos Ruth C. , Sadigh Gelareh 
Published: June 2024

e23132 Background: Financial toxicity is an important issue for cancer patients that affects quality of life and treatment adherence. Screening can help identify patients at risk but consensus on appropriate timing or methods for screening is lacking. We conducted a survey to assess preferences for financial toxicity screening among a cohort of cancer patients. Methods: An anonymous cross-sectional survey was sent to email newsletter subscribers of a breast cancer-specific philanthropic organization with a nationwide reach in July 2023. Participants were asked about financial toxicity screening preferences; all questions were optional. Frequencies, percentages, means, and standard deviations were calculated for categorical and continuous variables, respectively. Comparative analyses, including chi-square and t-tests, were used to identify differences across demographic groups. Statistical significance was determined at p < 0.05. Results: Of 5774 potential participants who clicked on the email link, 825 respondents with confirmed prior or current cancer diagnosis participated in the survey (14.3% response rate). These participants were 84% female (n = 690) with a median age of 50 years (IQR 44-57), were 51% non-Hispanic White (n = 418), 18% Black or African-American (n = 149), 8.2% Hispanic (n = 68). 84% confirmed a breast cancer (n = 689), and 53% were currently undergoing treatment (n = 441). Most participants were not asked about financial stressors by their care team (52%, n = 429) and most did not receive assistance from their care team (61%, n = 501). Most preferred for their providers to reach out to them regarding financial needs (75%, n = 615). Most wished for these discussions to take place early on in their treatment course (when first diagnosed [40%, n = 334] or when treatment course was selected [33%, n = 275]), and for these questions to be asked frequently (each appointment [38%, n = 312] or once per month [32%, n = 268]). Participants felt most comfortable discussing financial needs with a social worker or patient/financial navigator (82%, n = 679). Most wished to discuss financial concerns in person (67%, n = 553) or via telephone (58%, n = 479). Conclusions: Patients with cancer desire financial screening to occur early, often, and to be initiated by their providers. Patient preferences can guide optimal implementation of financial toxicity screening practices. Continued work refining best practices for financial toxicity screening should incorporate these patient preferences.