bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessing patient engagement levels in clinical cancer research: Development of a novel evaluation tool and comparison between eastern and western countries.
Authors: Gatellier Laureline , Tombal Bertrand F. , Serckx Béatrice , Charvat Hadrien , Katsui Keiko , Majima Yoshiyuki , Higashijima Jin , Suzuki Kazuyuki , Klingmann Ingrid , Nakamura Kenichi , Matsuda Tomohiro 
Published: June 2024

11018 Background: Patient Public Involvement and Engagement (PPIE) is essential in healthcare and cancer research. Currently, there is no objective method to assess at which stage of a clinical trial PPIE is effectively implemented. In this study, we developed a simple method for objectively assessing PPIE with an international scale. Methods: A novel, simple scoring method was developed to evaluate the PPIE implementation in cancer research. It follows the EUPATI Patient Engagement Roadmap and assesses PPIE at eight steps: defining research priorities, fundraising, protocol, informed consent, ethical review, investigator meeting, study results reporting, and application. PPIE level was self-rated by investigators on a five-level engagement scale: no engagement, considered, informed, actively involved, and co-creation. It was submitted to 124 Japanese and 203 European principal investigators (PI) of non-commercial sponsor cancer research clinical trials, conducted between January 2018 and December 2022, identified from publicly available databases (EudraCT, UMIN, jRCT). Results: The questionnaire was answered by 66 (53.2%) and 45 (22.2%) of the Japanese and European PIs, respectively. Overall, the PPIE implementation was low in both regions, with a “no engagement” rate of 61.7% in Europe and even lower, 78.5%, in Japan. Forty percent of the European PIs actively engaged patients (“actively involved” and “co-creation”) in at least one research step, versus only 16.7% of the Japanese PIs. The percentage of PIs answering “no engagement” in all eight steps was 47.0% in Japan and 11.1% in Europe. PPIE was the highest for the informed consent domain, with 73.3% of the European and 20.3% of the Japanese PIs reporting some level of engagement. Similarly, 55.6% of the European and 18.8% of the Japanese PIs involved PPIE in the ethical review domain. PPIE was notably low in the earlier steps of the research. Conclusions: Our innovative PPIE scoring method allowed us to objectively assess PPIE in cancer clinical trials and compare its implementation among different countries. This 2018-2022 snapshot revealed low (EU) to very low PPIE (Japan) levels, especially in the research design. Future assessments should help to monitor the enhancement of PPIE in cancer research on an international scale.
Improving clinical trial performance using adult-learning methods.
Authors: Burke Matthew M. , Kubitschek Trees Carolyn , Maan Mukta , Levonyak Mark , Johnson Lindsay , Koeppen Nicholas , Barrera Victoria , Nemeth Agnes , Reddy Sree , Coleman Robert L. , Franson Paula J. 
Published: June 2024

11025 Background: Timely and efficient accrual to oncology treatment trials is among the most vital components of clinical research. However, more than 80% of trials fail to reach enrollment targets, compromising outcome interpretation and cost. We hypothesized that a novel and customized application of adult-learning methods would enhance clinical trial screening and randomization. Methods: In collaboration with a multinational sponsor, Vaniam Group (VG) introduced a structured set of interventions to sites in 3 global randomized trials. Sites choosing to “opt in” formed the experimental group (EG). EG received tailored interventions: interactive Trial Educational Discussions (iTEDs: 30-min virtual meetings), and/or interactive Trial Acceleration Meetings (iTAMs: 4-hr live workshops of 10-30 investigators), and standard study support. Adult-learning techniques including the Socratic Method, case studies, and teach-back were used. Control group (CG) comprised sites receiving only standard study support. Primary endpoints were screening rate (SR) and randomization rate (RdR) compared atbaseline (6 mos prior to intervention) and 6 mos post-intervention (M6). Nonparametric statistical analyses compared between-group (Mann–Whitney U test) and within-group (Wilcoxon Signed-Rank test) differences. Results: Trial 1, a phase 3 placebo-controlled adjuvant trial had been open for 45 mos (54% enrolled) prior to intervention. At baseline, SR and RdR were similar between groups ( P>0.05). At M6, SR increased 100% and RdR increased 37% in the EG; in the CG, SR did not change and RdR decreased 7%. For both endpoints, EG performed better than CG ( P=0.018, P=0.014). Trial 2, a phase 3 neoadjuvant trial had been open for 49 mos (86% enrolled) with a projected 18 mos to completion. At M6, SR increased 3% in the EG, but decreased 39% in the CG. RdR increased 15% in the EG but decreased 33% in the CG. While changes in performance were not significant between groups ( P >0.05), study met its target enrollment goal with no further delays. Trial 3, a phase 2 recurrence trial was 30% behind enrollment with a projected 51 mos to completion. At M6, increases in SR were recorded in both EG and CG at 116% and 18%, respectively. RdR increased in both EG and CG (90% and 50%, respectively), augmented by protocol amendment. Despite increases in both groups, SR and RdR were significantly enhanced by VG intervention ( P=0.009 and P=0.015). Conclusions: Our novel, site-focused intervention strategy structured upon adult-learning methods significantly enhanced clinical trial performance, as measured by SR and RdR. Future work will expand these findings to different trial designs and outcome measures such as endpoint fidelity and cost. [Table: see text]
Supplemental Nutrition Assistance Program (SNAP) policy changes and mammography use in the United States.
Authors: Kazmi Ali , Hussaini S. M. Qasim , Chino Fumiko , Yabroff Robin , Barnes Justin Michael 
Published: June 2024

11033 Background: The Supplemental Nutrition Assistance Program (SNAP) alleviates food insecurity among low-income households, which has been linked to healthcare access. Several states increased SNAP eligibility by implementing policies that eliminate asset tests and/or broaden income eligibility criteria. This study investigates the associations of SNAP policy changes on mammography use within the past year among low-income females eligible for breast cancer screening. Methods: Income-eligible females ages 40-79 years were identified from the 2006-2019 Behavioral Risk Factors Surveillance System. 28 and 22 states adopted SNAP asset test elimination and income increase policies, respectively. Difference-in-differences analyses compared changes in the percentage of mammography within one year from pre- to post-SNAP policy adoption (asset test elimination or income eligibility increase) between states that did and did not adopt policies expanding SNAP eligibility. The samples were limited to females with household income < 130% and <200% federal poverty level for analyses of asset test elimination and income eligibility increase policies, respectively, to correspond to typical eligibility criteria. Results: A total of 171,684 and 294,647 income-eligible females were included for the asset test elimination and income eligibility increase policy analyses, respectively. Overall, 58.4% reported mammography within 1 year. Adoption of asset test elimination policies was associated with a 2.11 percentage point (95% CI = 0.07 to 4.15, P=0.043) increase in mammography, particularly for non-metropolitan residents (4.14 percentage points, 95% CI = 1.07 to 7.21, P=0.008), those with household income <$25,000 (2.82 percentage points, 95% CI = 0.68 to 4.97, P=0.01), and those residing in states in the South (3.08 percentage points, 95% CI = 0.17 to 5.99, P=0.038) or in states that did not expand Medicaid under the Affordable Care Act (3.35 percentage points, 95% CI = 0.36 to 6.34, P=0.028). There was no significant association between state-level policies broadening SNAP income eligibility and mammography use (-1.07 percentage points, 95% CI = -2.64 to 0.49, P=0.18). Conclusions: This nationwide study suggests that policies eliminating the asset test for SNAP eligibility were associated with increased mammography use within one year, with the most pronounced positive impact observed in Southern states, non-expansion states, non-metropolitan areas, and households with the lowest incomes. Findings highlight the role that states policies have to both meet essential needs and promote health among vulnerable populations.
Relationship between receipt of combined axillary dissection and nodal irradiation and age.
Authors: Myers Sara , Partridge Ann H. , Warren Laura Elizabeth , Greenup Rachel Adams , Mittendorf Elizabeth A. , King Tari A. , Kantor Olga 
Published: June 2024

11043 Background: Combined axillary lymph node dissection and regional nodal irradiation (ALND+RNI) is the greatest risk factor for breast cancer-related lymphedema (BCRL), a lifelong ailment that negatively impacts quality of life. As disability from BCRL may be particularly profound for adults <45 yo with longer life expectancy, we examined the association of age and other sociodemographics with receipt of ALND+RNI to further our understanding of patients at greatest risk for BCRL. Methods: The National Cancer Database (NCDB) was used to examine age-based differences in receipt of ALND+RNI in patients with stage I-III breast cancer treated from 2018-2020. Cohort characteristics were compared by age (<45 yo, 45-64 yo, and 65 yo). Multivariable regression examined the association between age and ALND+RNI adjusting for relevant factors. Sensitivity analyses explored associations between covariates and combined ALND+RNI by age group. Results: Of 155,010 patients, 5.4% were <45 yo, 47.2% were 45-64 yo, and 47.4% were 65 yo. Clinical and pathological node (cN, pN) positive disease, and receipt of ALND, RNI, and ALND+RNI were more common in patients <45 yo (Table). Age <45 yo was independently associated with ALND+RNI (<45 yo OR 1.40; 45-64 yo OR 1.26 vs 65, p<0.001). Residing in areas with a high proportion of high-school graduates (%HSG), Hispanic ethnicity but not race, and lower income were also associated with ALND+RNI in adjusted analyses (all p<0.05). Medicare (p=0.02 vs private insurance) was inversely associated with ALND+RNI. Among clinical factors, pN+ was the greatest risk factor for receipt of ALND+RNI (all p<0.001 vs pN0). Higher cT, cN1 and cN2 categories, lobular tumors, mastectomy, not receiving endocrine therapy, and having chemotherapy were also associated with ALND+ RNI (all p<0.05). Sensitivity analyses showed that while sociodemographics influenced receipt of ALND+RNI for women 45 yos, only clinical factors were significant for ALND+RNI for <45 yo. Among 45-64 yo, high %HSG (p<0.001) and low household incomes (p<0.01) were associated with ALND+RNI. In the 65 yo cohort, high %HSG (p=0.028), and Asian race (p=0.011) were more likely to receive ALND+RNI while Medicare patients were less likely to have ALND+RNI (p=0.012). Conclusions: Our findings suggests that clinical factors predominate in axillary treatment decisions for younger patients; while sociodemographic factors are more prominent for those 45 yo. Given their higher odds of receiving ALND+RNI, BCRL screening may be especially important in patients <45 yo. Further studies are needed to understand the interplay between age and sociodemographics on receipt of ALND+RNI. [Table: see text]
Association of frailty assessed by a ten-item frailty index (FI-CGA-10) with health-related quality of life in older adults with cancer.
Authors: Nishijima Tomohiro F. , Shimokawa Mototsugu , Nyrop Kirsten A. , Arimizu Kohei , Esaki Taito , Morita Masaru , Toh Yasushi , Muss Hyman 
Published: June 2024

11047 Background: A 10-item frailty index based on a comprehensive geriatric assessment (FI-CGA-10) is a recently developed measure of frailty in the geriatric oncology setting [Oncologist, 26, e1751 (2021)]. Our objective was to investigate the association between frailty defined by the FI-CGA-10 and health-related quality of life (HRQOL) in older adults with cancer. Methods: This study included 1015 consecutive older adults with cancer who underwent a CGA before cancer treatment decision at a geriatric oncology service in Japan from February 2020 through September 2023. Fitness and frailty level was evaluated using the FI-CGA-10 that assesses 10 domains: cognition, mood, communication, mobility, balance, nutrition, base and instrumental activities of daily living, social support, and comorbidity. Deficits in each domain were scored as 0 (no problem), 0.5 (minor problem), and 1.0 (major problem). FI-CGA-10 scores (range 0-1) were calculated by dividing the sum of the scores for each domain by 10 and then categorized as fit (<0.2), pre-frail (0.2–0.35), and frail (>0.35). HRQOL was measured by the EQ-5D-5L index score and visual analogue scale (VAS) at the CGA consultation. The minimally important difference (MID) values for the EQ-5D-5L Japan-based index and VAS scores are 0.048 and 7, respectively. Associations between EQ-5D-5L and FI-CGA-10 scores were analyzed by Pearson’s correlation and linear regression models adjusting for covariates (age, sex, cancer type, and stage). Results: Median age was 80 years, 60% were male, and 68% had gastrointestinal cancer. The mean +- SD of the FI-CGA-10 score was 0.35 +- 0.19. The FI-CGA-10 negatively correlated with the EQ-5D-5L index (Pearson’s r = -0.69; 95% CI -0.72 to -0.66; P<.001) and VAS (r = -0.47; 95% CI -0.52 to -0.42; P<.001) scores. After adjusting for the covariates, each 0.1 unit increase in FI-CGA-10 score was associated with 0.070 decrease in EQ-5D-5L index (95% CI -0.075 to -0.066; P<.001) and 4.9 decrease in VAS scores (95% CI -5.5 to -4.4; P<.001). Using the three-level classification, 22% of patients (n = 221) were categorized as fit, 38% (n = 384) as pre-frail, and 40% (n =410) as frail. Overall, the fit group had the highest EQ-5D-5L index and VAS scores followed by the pre-frail and frail groups (table). The score differences between the frailty categories were statistically significant and clinically meaningful according to the MID values. Conclusions: This study demonstrated that frailty assessed by the FI-CGA-10 cross-sectionally correlated with HRQOL measured by the EQ-5D-5L in older Japanese adults with cancer. The observed association further supports construct validity of the FI-CGA-10 as a CGA-based frailty measure. [Table: see text]
Overlapping and non-overlapping indications for checkpoint inhibitors in the US.
Authors: Paul Jeddeo , Mitchell Aaron Philip , Kesselheim Aaron S , Rome Benjamin N 
Published: June 2024

11057 Background: Since the first checkpoint inhibitor was approved in 2014, this class of cancer drug has revolutionized the treatment of several malignancies. As of January 2024, 11 checkpoint inhibitors have been approved by the US Food and Drug Administration (FDA), each with its own particular indications. We assessed the overlap of approved indications, which has implications for competition and price negotiation by payers. Methods: In this cross-sectional study, we evaluated the FDA-approved indications for 11 checkpoint inhibitors as of January 2024. Indications were defined by cancer tissue type (or mutation status for non-tumor-type indications), stage, and line of treatment (first-line, second-line, third-line, or fourth-or-greater-line). Non-overlapping indications were defined as those with only a single drug approved; for overlapping indications, we tabulated the number of approved drugs. Results: The 11 FDA-approved checkpoint inhibitors were associated with 43 distinct indications, ranging from 2 (retifanlimab, toripalimab, and tremelimumab) to 35 (pembrolizumab) indications per drug. Fifteen (43%) indications were non-overlapping. Pembrolizumab had 11 non-overlapping indications (e.g., certain breast, cervical, and urothelial cancers); all other drugs had between 0 and 2 non-overlapping indications (Table). Among the 28 overlapping indications, 15 (54%) had approvals for 2 drugs, 9 (32%) had approvals for 3 drugs, 3 (11%) had approvals for 4 drugs, and 1 (3%; non-small cell lung cancer) had approvals for 7 of the 11 drugs. Conclusions: Checkpoint inhibitors are FDA-approved for a total of 43 different indications, but most indications were included on the labeling of 3 or fewer drugs in this class. Over 1 in 3 indications had only 1 approved drug, most commonly pembrolizumab. This limited overlap of indications suggests that manufacturers may avoid seeking approval for indications that already have multiple approved drugs of the same class, which may decrease competition and lead to sustained high drug prices. To provide patients with better information about the checkpoint inhibitor most appropriate for their cancer, the NIH could fund, and the FDA could encourage, more direct comparative effectiveness trials. [Table: see text]
Accelerating cancer research trial startup in the community setting: A quality-improvement study.
Authors: Claes Jason Joseph , Maher James F. , Thompson Wayne , Benoit Lisa , Cook Billie , Newbury Patrick , Adams Alyssa , O'Connor Melinda , Ohlhaut Emma , Wirthlin Chelsea 
Published: June 2024

11066 Background: There is a large variation in activation times for cancer clinical trials, delaying the opportunity for patients to benefit from cutting edge treatments. Academic medical centers typically take longer to activate a clinical trial as compared to community settings. Some academic medical centers have adopted quality improvement processes to reduce clinical trial start-up time. Our center, TriHealth Cancer & Blood Institute (TCBI) in the SW Ohio community has also adopted quality improvement processes to further reduce startup time within our oncology research group. Methods: This study encompassed July 2022-June 2023, with baseline data drawn from January 2021 to December 2021 prior to the study period which revealed a mean clinical trial start-up time of 116 days. The research group used a swim-lane process to define the typical process & stakeholders for clinical activation time at our institution prior to the study time. Our group identified three major areas with significant lag-time - contracts, budgets, & IRB/ICF - with the overarching root cause for delays due to lack of organizational process & expertise in these major areas. Using Plan-Do-Study-Act (PDSA), we instituted interventions, which included utilizing a central IRB, identifying a responsible member with extensive research budgeting to review research study budgets, & identified a responsible member with extensive contracts review & negotiations working with Central Legal throughout the contracts negotiation process with sponsor(s). Results: During this 12-month study time, our center demonstrated a 44% reduction in trial start up time (141 days to 79 days), while at the same time doubling the number of active trials. This process change resulted in sustainability that carried into 2023, further reducing start-up time to 70 days. In 2021, we opened 6 studies and after adoption of these process improvements (2022) we doubled the number of studies by 117%, while opening 67% more in 2023 than in 2021. The ability to open more studies has allowed us to shift patient enrollment to more investigational trials while increasing treatment enrollment from 2022 to 2023 by 24%. Through process improvement, more treatment studies are open & available for our community. Conclusions: By implementing interventions to streamline clinical trial activation time, our center was able to significantly & sustainably reduce the time required to start a clinical trial in our community health system in a 12-month period, resulting in our ability to initiate more clinical trials. As a result, more treatment trial patients were able to be enrolled in these clinical trials at TCBI, with the hope of improved outcomes. We anticipate that further adoption of just-in-time studies may help to decrease this activation time further. [Table: see text]
Cost-effectiveness of a circulating tumor fraction molecular biomarker for treatment response monitoring.
Authors: Rivers Zachary , Aggarwal Charu , Matrana Marc Ryan , Feliciano Josephine Louella , Mitra Akash , Nimeiri Halla , Ben-Shachar Rotem , Eng Cathy , Kircher Sheetal Mehta 
Published: June 2024

11082 Background: Clinical validation studies have demonstrated that molecular biomarkers quantifying ctDNA changes in circulating tumor fraction (TF) predict survival outcomes and may be used for treatment response monitoring (TRM). While clinical utility studies to determine the impact on outcomes of molecular biomarker-driven treatment decisions versus standard of care imaging are ongoing, cost-effectiveness has not been evaluated. Here we evaluate the cost-effectiveness of a molecular biomarker, Tempus xM, used for TRM. Methods: xM quantifies changes in TF from baseline and on-treatment liquid biopsies. We use a patient-level Markov simulation to compare xM-guided treatment (intervention) to diagnostic imaging-guided treatment (control) over 24 weeks of therapy. In both arms xM and imaging is assessed at 12 weeks and treatment decisions are made based on xM (intervention) or diagnostic imaging (control). Imaging and xM concordance (Table) was based on a retrospective, real-world (RW) study of 51 patients tested with xM that received rw-imaging that evaluated the association of xM with rw-outcomes in advanced pan-cancer patients treated with immune checkpoint inhibitors (ICIs) +/- chemotherapy (CT). We assume non-responders discontinue ICIs and switch to CT and responders remain on ICIs. Appropriate (inappropriate) therapy was defined as treatment decisions concordant (discordant) with xM results. Costs were calculated from Medicare’s perspective in 2023 USD. Control patients do not accrue the cost of xM. Sensitivity analyses were conducted. Results: Intervention patients saved $4,400 ($63,424 vs. $67,824 in controls) by preventing use of ineffective therapy (4.3 weeks avoided vs 0.2 weeks in controls), a savings of $1076 per week of ineffective therapy avoided. In all sensitivity analyses, xM-guided therapy remained cost effective (Table). The timing of therapy intervention and the cost of therapy had the largest impact on savings. Conclusions: This model demonstrates that xM-guided treatment is cost-saving compared to imaging alone during 24 weeks of treatment. Future work will incorporate variable clinical uptake and long-term outcomes by expanding the time horizon and including treatment discontinuation due to toxicities and mortality. [Table: see text]