bluuebunny/crossref_metadata_2025_split huggingface dataset:
Classifying oncologist rurality by practice location and patient population.
Authors: Cornelius Sarah , Wong Sandra L. , Moen Erika L. 
Published: October 2023

136 Background: Geographic variation in the oncology workforce has contributed to reduced access to cancer specialists in rural areas. Workforce studies most often classify provider rurality by their practice location. We hypothesized this approach, given its high specificity, would miss the true extent of providers involved in rural cancer care. In this study, we aim to identify a new method for classifying oncologist rurality. Methods: We created a cohort of Medicare beneficiaries diagnosed with breast, colorectal, or lung cancer in 2018. This informed a cohort of all medical, radiation, and surgical oncologists who treated these patients. Two methods were used to classify oncologists’ rurality using Rural Urban Commuting Area (RUCA) codes: 1) Based on the ZIP Code where they provided the plurality of their care; and 2) Based on the percentage of their patients who reside in a rural ZIP Code. We used sensitivity, specificity, and summary statistics to compare these methods and identify a threshold of rural patients to classify provider rurality. Results: We identified 815 rural oncologists by their practice location and 5,450 by their patient population. We found high concordance between these two definitions (AUC: 0.87), with providers practicing in a rural location treating the highest proportion of rural patients (n=658 [80.7%]). Oncologists practicing in a rural area had a lower patient volume (6.4 [SD: 7.8] vs. 12.2 [SD: 14.2]) and were more likely to be a surgeon (73.1% vs. 51.8%) than their metropolitan counterparts. By categorizing oncologist rurality by their patient panel, we have expanded who is considered a rural oncologist (n=5,450 vs. n=815) and created a continuous measure of oncologist rurality. Oncologists treating a high proportion of rural patients had a higher patient volume than those treating no rural patients (10.9 [SD: 11.6] vs. 8.7 [SD: 10.7]). Conclusions: Special consideration should be made when defining oncologists’ rurality status. Basing rurality on their patient panel results in a broader definition of a rural physician, and could be useful for interventions aiming to improve quality of rural cancer care.[Table: see text]
Mutation-specific costs of advanced non-small cell lung cancer treatment.
Authors: Tan Juanyi , Yang Szu-Chun , Dinan Michaela Ann , Chiang Anne C. , Gross Cary Philip , Wang Shi-Yi 
Published: October 2023

14 Background: Novel immunotherapy and targeted therapies prolong survival, but are associated with substantial costs for patients with advanced non-small cell lung cancer (NSCLC). Because biomarker results can strongly impact treatment options, we explored the relation between biomarker results and NSCLC treatment costs. Methods: Using the Flatiron Health database, we conducted a retrospective cohort study to investigate the association between biomarker test results and medication costs in patients with newly diagnosed advanced NSCLC between 2011 and 2020. To be included, patients had to receive at least one biomarker testing. Patients with two or more actionable gene alterations, without structured/treatment data, or who participated in clinical trials were excluded. Patients with negative actionable gene alterations and no definitive PD-L1 results served as the reference group. We linked medication records to Medicare Spending by Drug Dashboard to calculate the first-year cost. We applied a coarsened exact matching approach to estimate the cost difference compared to the matched reference group. Results: A total of 32,008 patients with advanced NSCLC were identified. The mean first-year medication costs in the overall cohort increased from $29,283 in 2011 to $46,062 in 2020. The unadjusted mean first-year costs varied substantially, from $27,703 for patients with ALK+ NSCLC to $51,047 for patients with RET+ NSCLC ($34,520 for the reference group; details in Table). After coarsened exact matching, the mean medication costs for patients with MET+, RET+, BRAF+, PD-L1≥1%, or PD-L1<1% advanced NSCLC were significantly higher than that for the reference group, whereas patients with ALK+ or EGFR+ tumor had significantly lower mean medication costs than the reference group. There was no significant difference in costs between patients with NTRK+ or ROS1+ tumor and the reference group. Conclusions: Our economic evaluation found that medication costs for advanced NSCLC increased substantially over time and differed by biomarker status, highlighting the importance of using more accurate cost estimates in cost-effectiveness analysis of novel therapies to guide value-based practices. [Table: see text]
Implementation of an academic-community partnership model for equitable access to precision oncology decision support in rural community cancer centers.
Authors: Kumar Anivarya , Owen Jennifer R , Sloat Nicholette , Maynard Elizabeth , Hill Vanessa , Hubbard Christopher , McKinney Matthew , Sutton Linda , McCall Shannon J. , Datto Michael , Ramaker Ryne , Green Michelle , Strickler John H. , Caughey Bennett Adam 
Published: October 2023

141 Background: Comprehensive genomic profiling (CGP) is an essential tool for selecting cancer therapies and matching patients to clinical trials, however patients in rural community cancer centers are less likely to receive CGP. We developed an academic-community partnership model to expand Duke’s Molecular Tumor Board (MTB) clinical decision-making and trial-matching services to Duke Cancer Network (DCN), a series of affiliated community cancer centers across rural North Carolina. Methods: The Duke Precision Cancer Medicine Initiative created a Molecular Registry of Tumors database to aggregate CGP results from multiple vendors and enable review by a multidisciplinary MTB. Patients treated at DCN sites had their CGP results and relevant clinical data reviewed by the Duke MTB. After review, clinical recommendations were communicated in a standardized note and returned to DCN providers within one week. One year into implementation, DCN providers were anonymously surveyed to identify persistent barriers to utilization of CGP. Results: Between Jan 2022 and June 2023, 96 patients were consented, enrolled, and reviewed by Duke MTB. 29.2% were Black, 19.8% were Native American, and 5 .2% were of Hispanic ethnicity. 57.3% patients were found to have an actionable genomic biomarker. Of these, 14 of 22 (63.6%) received matched FDA-approved therapies and 0 of 17 (0%) with molecular criteria for a clinical trial at Duke successfully enrolled at time of submission. 85% DCN providers reported comfort ordering CGP and 45% reported comfort interpreting the results. Most frequently reported major barriers to clinical trial participation included distance (70%), lack of transportation (55%), and lack of local trials (50%). Conclusions: Our implementation of a novel academic-community partnership serves as a sustainable and reproducible model to expand access to MTB services. Further research and interventions are necessary to mitigate persistent urban versus rural barriers to utilizing CGP, especially those in clinical trial enrollment. By providing MTB support to historically underserved communities and a framework to identify salient barriers in the process, our model can be adopted by academic cancer centers nationally, contributing to improved and equitable outcomes in oncology.[Table: see text]
Access to radiotherapy in Hispanic and Latinx populations in the United States: An update.
Authors: Verdini Nicholas Peter , Santos Patricia Mae Garcia , Vicioso Yorleny M. , Rivera Amanda , Perez Carmen Ana , McClelland Shearwood 
Published: October 2023

142 Background: Radiation therapy (RT) is a mainstay of oncology care and has been shown to optimize outcomes for patients in many settings. Disparities in access to RT therefore represent substandard care. The Hispanic/Latinx population has consistently faced disparities in oncology access and outcomes, with cancer being the leading cause of death in the Hispanic American population. In this study, we aim to evaluate recent research in RT disparities among the Hispanic/Latinx population in the United States since the seminal analysis from 2017 (PMID: 29904731). Methods: A PubMed literature search was conducted for articles published from January 2017 through March 2023. Four term combinations were utilized, including: (1) “Hispanic” and “Radiotherapy” and “Disparities”, (2) “Latino” and “Radiotherapy” and “Hispanic”, (3) “Hispanic” and “Radiation” and “Disparities”, and (4) “Latino” and “Radiation” and “Disparities.” All articles returned from each search were documented and duplicates were removed. Following the initial search, research studies qualifying for inclusion included studies taking place in the United States, examination of radiation oncology care, and examination of health disparities in the Hispanic/Latinx population. Articles meeting criteria were then organized by disparity type that they address. Results: Our initial PubMed search returned 245 articles. Of these articles, 60 met inclusion criteria and spanned 5 disparity-types: (1) Time to Treatment Initiation & Completion, (2) Receipt of Treatment and Guideline-Concordant Care, (3) Geography, (4) RT Clinical Trial Access and (5) Insurance and Treatment Center Type. The most common disparity evaluated (n=23 studies) was receipt of treatment and guideline-concordant care, showing that the Hispanic/Latinx population was found to be less likely to receive any treatment. Another commonly identified disparity (n=10 studies) was the time to treatment initiation and completion, which highlighted that compared to the Non-Hispanic White population, the Hispanic/Latinx population had greater times to initiating RT and decreased likelihood of timely completion. Additionally, the Hispanic/Latinx population faced disparities in RT access due to geography (n=4 studies), RT clinical trial access (n=3 studies), insurance and treatment center access (n=5 studies). Conclusions: Disparities in radiotherapy access and quality care remain prominent for the Hispanic/Latinx population, despite increasing interest in health care disparities research. This population faces disparities in access via a multitude of barriers. Continued health care disparities research with tangible intervention is needed in radiation oncology in order to properly understand and address this problem.
A population-based study of health care system factors associated with receipt of treatment and treatment intent in stage III non-small cell lung cancer.
Authors: Thibodeau Stephane , Nguyen Paul , Robinson Andrew George , Ynoe de Moraes Fabio , Pantarotto Jason R. , Hanna Timothy P. 
Published: October 2023

146 Background: Stage III non-small cell lung cancer (NSCLC) is a disease with a spectrum of anatomic extent, patient health status, and treatment approaches. When health care quality is optimal, receipt of treatment and its intent should be independent of health system factors. We investigated whether modifiable health care system-level factors are associated with receipt of treatment and treatment intent in stage III NSCLC. Methods: This was a population-based, retrospective cohort study using health administrative data covering nearly the whole population of Ontario, Canada (15 million) from 2010-2018 for people with AJCC 7 or 8 stage III NSCLC aged ≥20 years. System factors were: treatment era, diagnostic interval, health region of residence, travel distance, and volume of advanced radiotherapy and systemic therapy. The health region is responsible for administering regional cancer care. The relative risk (RR) of (1) any treatment versus no treatment, and (2) palliative-intent versus curative-intent treatment was determined, using multivariable Poisson regression models. We adjusted for patient, disease, and treatment factors, including age, sex, rurality, income quintile, substage, comorbidity, histology, and use of PET imaging. Results: 7,093 people with stage III NSCLC diagnosed between 2010 and 2018 were identified. There were differences between groups in patient, disease, and treatment factors. For example, factors associated with no treatment include advanced age (e.g. adjusted RR [95% confidence interval]: 80+ vs. 20-64, 0.83 [0.80-0.87]), greater Elixhauser comorbidity score (e.g. 3+ vs. 0, 0.88 [0.84-0.92]), dementia (RR: 0.78 [0.70-0.87]), palliative care consultation (RR: 0.92 [0.89-0.94]) and geriatrics consultation (RR: 0.82 [0.71-0.95]) (all p<0.05). On multivariable stepwise analysis adjusting for these factors, no system factors were associated with receipt of treatment versus no treatment. For those treated, patient, disease, and treatment factors associated with palliative intent were similar. Over time, there was increasing utilization of immunotherapy and advanced radiotherapy (e.g., VMAT, IMRT) (treatment eras: 2010-2012 vs. 2013-2015 vs. 2016-2018). The major system factor associated with palliative intent treatment amongst those treated was health region of residence (RR: ranges from 0.88 to 1.67, p<0.001), which remained after stratifying analysis by treatment era. Conclusions: Even with increasing adoption of advanced radiotherapy and systemic therapy over time, health region of residence emerged as the major health system-level factor associated with choice of treatment intent for stage III NSCLC after adjusting for patient, disease, and treatment factors. Our study suggests possible opportunities to improve care outcomes by addressing unexplained regional variation in care.
Treatment (tx) patterns and real-world outcomes among patients (pt) with mantle cell lymphoma (MCL) in the Flatiron database.
Authors: Shah Gunjan L. , Subbiah Krishnaveni , Garrison Sean , Gu Tao , Patwardhan Pallavi 
Published: October 2023

152 Background: Despite the increasing number of tx options for MCL, data on novel agents and associated OS are scarce. We assessed the tx patterns and estimated OS by line of therapy (LOT) among pts with MCL in the United States (US). Methods: This retrospective observational study using the Flatiron Health database included pts aged ≥ 18 y at initial MCL diagnosis who received first-line (1L) systemic tx for MCL during the index period (01/01/2011–03/31/2022) on the date of 1L tx initiation. Pts who had < 1 mo of data after the index date, received clinical study drug during the study period, or had other primary cancer diagnoses or active primary malignancies were excluded. Time to next tx (TTNT) was calculated from LOT start date to next LOT start date. OS was estimated using Kaplan-Meier methodology. Results: Of 4846 pts diagnosed with MCL, 2072 met all eligibility criteria and were included in the final cohort. The median age was 69 y; pts were mostly male (71%), from the Southern US (43%), had commercial health plan insurance (47%), and had stage IV disease at diagnosis (64%). The median length of follow-up from index was 27.4 mo. The most common 1L tx was bendamustine + rituximab (29%) and ibrutinib was the most common second-line (2L) and third-line or later (3L+) tx (25.5% and 10.5%, respectively); only 17% received a stem cell transplant. Median TTNT and OS were similar across subgroups (Table). Median time to start of LOT, TTNT, and OS for subgroups of pts who (1) received ≥ 2 LOTs, including an alkylating agent, Bruton tyrosine kinase inhibitor, and CD20-targeting agent (TRANSCEND NHL 001, MCL cohort eligibility criteria; n = 508); (2) received second-line or later (2L+) tx (n = 859); and (3) received 3L+ tx (n = 363) are shown in the Table. Conclusions: Bendamustine + rituximab and ibrutinib were the most common tx in 1L and 2L/3L+, respectively, among pts receiving approved tx. For all pts/subgroups,median TTNT was longest for the 1L LOT; median OS was longest from 1L start date. Diminishing TTNT and OS in subsequent LOTs after 1L tx provide benchmarks for future tx.[Table: see text]
Discrimination, medical mistrust, and delaying cancer screenings and other medical care.
Authors: Fiala Mark Aaron 
Published: October 2023

159 Background: Mistrust in the health care system can delay one from seeking needed care and lead to worse health outcomes. For racial/ethnic minorities, medical mistrust may be rooted in past experience of discrimination during clinical encounters. However, few studies have analyzed the relationships between discrimination, medical mistrust, and delaying care, such as cancer screenings. Methods: The study utilized the 2022 Health Information National Trends Survey (HINTS) data, a nationally representative study about knowledge of and attitudes toward cancer- and health-related information. Medical mistrust was assessed by one question “How much do you trust the health care system.” Those reporting “not at all” or “a little” opposed to “somewhat” and “very” were considered to have medical mistrust. Results: Overall, 15% were considered to have medical mistrust. 14% of participants who identified as a racial/ethnic minority reported feeling discriminated against when getting medical care. Participants reporting prior discrimination were 286% (p <0.001) more likely to report medical mistrust after controlling for age, education, income, and race and ethnicity. Interestingly, after controlling for prior discrimination, African American or Black participants were 33% (p = 0.001) less likely to report medical mistrust than their White peers. Overall, 33% of participants reported delaying needed medical care in the past year and 22% reported not being interested in having a cancer screening test in the next year. Participants reporting prior discrimination were 170% (p < 0.001) more likely to report delaying care and those reporting medical mistrust were 83% (p < 0.001) more likely after controlling for age, education, income, race and ethnicity, and insurance coverage. Participants reporting medical mistrust were 37% (p < 0.001) less likely to report being interested in having a cancer screening test after controlling for covariates. There was no independent association between prior discrimination and interest in cancer screenings (p = 0.286). Conclusions: Perceived discrimination during clinical encounters is a mechanism for medical mistrust and medical mistrust is associated with delaying needed care including cancer screenings. Decreasing discrimination may improve trust and reduce disparities in health outcomes.
Using a disparities dashboard to identify racial/ethnic differences in breast cancer treatment: Implications for improving cancer care delivery.
Authors: Edmonds Megan C. , Agarawl Parul , Balija Tara , Bickell Nina A. 
Published: October 2023

161 Background: Delays in the initiation of breast cancer treatment (e.g., surgery, chemotherapy, adjuvant endocrine therapy) contributes to breast cancer survival disparities. Yet, the use of a cancer dashboard to assess and inform real time assessments of the timing of surgery and systemic treatment by race/ethnicity is unclear. The purpose of this study is to investigate whether a cancer disparities dashboard can be used to assess racial/ethnic differences in the initiation of first line of treatment and timeliness of breast cancer surgery. Methods: A disparities dashboard was built using data from the tumor registry and the electronic medical record’s Data Warehouse. Key fields assessing patient race/ethnicity, cancer stage, receptor status, surgery type, treatments received and dates of surgery. This retrospective analysis included women diagnosed with a new primary breast cancer who underwent definitive surgery at Mount Sinai Hospital (2010-2020). We defined delays as >8 weeks to treatment initiation, and delay to breast surgery as > 6 weeks from diagnosis. Chi-square and t tests were used to assess independent variables (e.g., stage, age) by race/ethnicity. Patient-level multivariable logistic regression was used to evaluate the association between race/ethnicity and delays to initiation of first treatment and surgical delays. Results: Of 8,403 women identified (46.5% non-Hispanic White, 17.7% Black, 16.9% Hispanic), 64.5% had stage I cancer, 80.8% had estrogen receptor cancer. 18.5% of the sample had delays to initial treatment and 42.6% experienced delays to surgery. After adjusting for stage, age and receptor status Black patients compared to non-Hispanic White patients had the greatest likelihood of delayed initial treatment (OR: 3.03; 95% CI:2.6-3.5) or surgery delays (OR:2.45; 95% CI:2.1-2.8). With regards to clinical/sociodemographic factors younger patients (22-39 vs. 40-64; p<0.001), mastectomy surgery type (; p=0.031), higher stage (stage 3 vs.1; p<0.0001), HER2 and TNBC receptor status (vs. ER; p<0.0001),) were more likely to experience surgery delays. Conclusions: Breast cancer treatment delays were more common among minoritized patients compared to White counterparts. A Disparities Dashboard can be used to assess differences in care. These data can be used to inform quality initiatives to improve cancer care delivery for at-risk patient populations who experience worse cancer outcomes.
Sociodemographic differences in treatment and survival for patients who receive genomic tumor testing in a rural state.
Authors: DiBiase Jessica , Scharnetzki Elizabeth , Rueter Jens , Jacobs Elizabeth , Anderson Eric 
Published: October 2023

170 Background: New cancer technologies like genomic tumor testing (GTT) make targeted treatments and improved outcomes possible. However, access to technologies like GTT is often inequitably skewed such that it is most available to urban and socially advantaged individuals, which may contribute to cancer disparities in disadvantaged groups. This study aims to assess the impact of differential resource allocation by examining whether patient rurality, education, or income are associated with whether patients receive genome matched treatment (GMT) and their survival. Methods: Patients with cancer ( n=1,258) enrolled in the Maine Cancer Genomics Initiative, which provided free GTT across a rural state Demographic and clinical data was collected from surveys and electronic medical records. We used multivariable logistic regression models to examine whether receipt of GMT differs by patient rurality, education, and income. Kaplan-Meier survival (KM) curves and multivariable Cox proportional hazards regression were conducted to explore the relationship between 12-month mortality and rurality, education, and income. We fit both unadjusted and adjusted (age, gender, physical quality of life, cancer stage and type) models. Results: After completing GTT, ~16% of patients received at least one GMT. Rurality, education, or income did not predict receipt of GMT. 41.4% of the lower educational level group versus 32.2% of the higher education group died within 365 days of enrollment (unadjusted HR: 1.37; 95% CI: 1.12 to 1.68; p=0.002). This difference was driven by patients who did not receive GMT, where those in the lower education group had increased mortality (unadjusted HR: 1.43, 95% CI: 1.15 to 1.78, p=0.001). For patients who received GMT, there was no difference in mortality between the education groups (unadjusted HR: 1.03, 95% CI: 0.58 to 1.83, p=0.9). No significant differences in mortality were observed for rurality or income. Conclusions: Lower educational attainment was associated with worse survival for patients who did not receive GMT. Education and specialized health care are differentially available to those in urban and rural areas and can cause health disparities. Sustaining initiatives that provide access to novel technologies is critical to address cancer disparities. To account for the intersection of social and psychological factors on cancer disparities, future analyses will include patients’ perceptions of GTT.