bluuebunny/crossref_metadata_2025 huggingface dataset:
The global burden of primary liver cancer and underlying etiologies from 1990 to 2021.
Authors: Kocarnik Jonathan M , May Miranda , Acheson Alistair , Bhangdia Kayleigh , Compton Kelly , Dean Frances , Fu Weijia , Penberthy Louise , Pritchett Natalie , Xu Rixing , Bhakta Nickhill , Force Lisa
Published: June 2024

10573

Background: Liver cancer is a leading cause of global health burden, and was the seventh leading cause of cancer death in 2021. The most common type of liver cancer in adults is hepatocellular carcinoma, which can be due to alcohol, hepatitis B, hepatitis C, non-alcoholic steatohepatitis (NASH), or other causes. In children the most common type of liver cancer is hepatoblastoma. Comprehensive and comparative estimation of liver cancer burden can inform policy decisions and public health interventions to reduce incidence, morbidity, and mortality. This study provides updated liver cancer estimates from 1990 to 2021, and for the first time includes hepatoblastoma. Methods: Using estimation methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 (GBD 2021) we comprehensively estimated total liver cancer incidence, mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability adjusted life-years (DALYs). Etiologic proportions from meta-analyses of literature review data were applied to the total. Liver cancers under age 10 were attributed to hepatoblastoma. YLLs were calculated using life expectancy estimates. Prevalence and YLDs were calculated from expected survival, disease sequelae, and disability weights. DALYs were the sum of YLLs and YLDs. Results are presented with 95% Uncertainty Intervals (95% UI). Results: Globally, there were an estimated 529,000 (95% UI 480,000 – 594,000) liver cancer cases and 484,000 (437,000 – 538,000) deaths in 2021, contributing to 12,900,000 (11,600,000 – 14,400,000) DALYs. Since 1990, these represented increases of 114.3% (87.0 – 145.3%) in cases, 102.5% (76.4 – 132.0%) in deaths, and 70.6% (48.7 – 96.8%) in DALYs. For liver cancer etiologies (excluding hepatoblastoma), 37.4% (32.6 – 42.6%) of deaths were due to hepatitis B, 30.3% (26.3 – 34.8%) hepatitis C, 19.1% (15.8 – 22.8%) alcohol, 8.5% (6.9 – 10.3%) NASH, and 4.3% (3.6 – 5.1%) other causes in 2021. Conclusions: These GBD 2021 estimates provide comprehensive estimates of the substantial health burden of liver cancer, highlighting a continued need for public health efforts targeting prevention, vaccination, treatment, or behavioral change.[Table: see text]
Cancer burden in South Asians in the United States: Epidemiologic report using Surveillance, Epidemiology, and End Results (SEER) program.
Authors: Hundal Jasmin , Chen Yanwen , Mustafa Ali Moaath Khader , Jain Akriti Gupta , Advani Anjali S. , Gerds Aaron Thomas , Balderman Sophia , Molina John C. , Carraway Hetty E , Mukherjee Sudipto , Singh Abhay
Published: June 2024

10574

Background: Studying racial-ethnic disparities in cancer risk can help in identifying underlying factors and developing targeted screening and education strategies. South Asian Americans (SAA), Asian Indians and Pakistanis, are a fast-growing ethnic group in the US, but there is limited research on their cancer risks. This study examines cancer prevalence patterns in the SAA population compared to Whites in the US. Methods: We analyzed cancer prevalence in 5,120,423 patients diagnosed with 23 different types of cancer between 2000 and 2018, using data from 18 SEER cancer registries. We compared cancer prevalence between SAA and Whites and examined factors such as cancer types, demographics, socioeconomic status, and urban vs. rural residency. Χ2 test was used to determine statistical significance (p<0.001). Results: Our analysis revealed higher prevalence of breast (19.0% vs. 14.6%) and thyroid (5.9% vs. 2.8%) cancers among SAAs compared to Whites, but lower rates of lung (6.5% vs. 12.0%), colorectal (5.9% vs. 7.4%), and melanoma (0.8% vs. 5.4%) cancers; p<0.001. Demographically, a significantly larger proportion of younger individuals (22.3% vs. 10.0%, ages 00-44) were found in the SAA cohort. The SAA survivor cohort also had a significantly higher percentage of females (50.8% vs. 48.6%) and married individuals than their White counterparts (69.3% vs 55.3%). Lastly, there were significant state-based variances in cancer prevalence. In California, SAAs had a lower cancer prevalence (23%) compared to Whites (38.5%), while in New Jersey, SAAs had a higher cancer prevalence (36.7%) than Whites (12.3%). Conclusions: Our analysis shows a disparity, highlighting the need for culturally attuned healthcare policies to enhance cancer education and screening among diverse groups. The higher prevalence of breast cancer in SAAs suggest possible effective screening, while lower rates of colorectal and lung cancers point to potential awareness gaps or cultural barriers. Addressing these, alongside researching genetic, environmental, and lifestyle influences—particularly given the younger SAA cancer population—is prudent. A focused approach, emphasizing targeted public health initiatives and further research, is necessary to enhance cancer outcomes and ensure health equity.
Association of neighborhood-level superfund sites with atmospheric toxic exposures and increasing cancer risk in the United States: A proof-of-concept geospatial study.
Authors: Hussaini S. M. Qasim , Kamarei Azar Mohammad Abadi
Published: June 2024

10577

Background: Decades of underinvestment have disproportionately exposed several neighborhoods in the US to hazardous conditions. Superfund is the name given to the environmental program established by the US Congress in 1980, to address abandoned hazardous waste sites. The extent to which Superfund sites have contributed to differences in cancer risk remains unknown. We investigated atmospheric toxic exposures increasing cancer risk by proximity to Superfund sites at the neighborhood level. Methods: In this cross-sectional study of US neighborhoods, census-tract level air toxic cancer risk data from the Environmental Protection Agency for 2019 were linked with census-tract level geolocation data of ~1300 Superfund sites from the Superfund Enterprise Management System database. Linear regression models were utilized to explore association between cancer risk and proximity to Superfunds. Geographically Weighted Regression models explored spatial non-stationarity by modeling spatial relationships that vary across the study area. Bivariate Local Indicators of Spatial Association (LISA) cluster maps were created for superfund site proximity and cancer risk (high-high, low-low, low-high, high-low). Kruskal-Wallis testing compared the distributions of different variables across the four LISA cluster types. Results: Study explored 82,770 census tracts nationwide. For every 10 percentile increase in Superfund proximity, there was an increase of 4% in cancer risk (p < 0.001). This association was strongest in the Intermountain West, South-Southeast, and Northeast regions. High-high clusters (high proximity to Superfund, high cancer risk) had higher percentage of non-White, low-income, unemployed and lower education attainment populations compared to low-low clusters (all p < 0.001). Within high-high clusters, non-White population had the strongest correlation with proximity to Superfunds. Cancer risk was much higher for the top 10% than the bottom 10% of proximity to Superfunds (Table). Conclusions: Our study highlights higher clustering of cancer risk around neighborhoods with existing Superfund sites. Further, we demonstrate the closer a neighborhood is to a Superfund site, the greater the cancer risk is with associated sociodemographic changes. Using a novel approach to geospatial analytics, the results demonstrate the first clear evidence of a dangerous association between Superfunds and healthcare, and encourage the urgent prioritization of Congressional policies that optimize investment in Superfund site clean up for public health. [Table: see text]
Clinical utility of AlphaMissense in predicting pathogenicity of DNA damage repair genes in cancer.
Authors: Yazaki Shu , Pei Xin , Powell Simon N. , Khan Atif J. , Setton Jeremy , Riaz Nadeem
Published: June 2024

10581

Background: Deficiencies in DNA damage repair (DDR) impact cancer predisposition and various treatment responses.Functional implications of missense variants in DDR genes remain elusive.AlphaMissense, a new AI-based method, accurately predicts the pathogenicity of missense variants, but its clinical utility requires validation. We evaluated the accuracy of AlphaMissense predictions by analyzing known mutational signatures, genomic characteristics, and therapeutic vulnerabilities of DDR-deficient tumors. Methods: We analyzed data from TCGA (n=8,178) and MSK-IMPACT targeted panel sequencing (n=56,695) to evaluate the performance of AlphaMissense in predicting clinically actionable DDR genes, including core homologous recombination (HR) genes ( BRCA1/2, PALB2, RAD51C), POLE, and ATM. Missense mutations were classified as known pathogenic by OncoKB or previous literature, newly pathogenic identified with AlphaMisense, or benign. Mutational signatures were computed using SigMA algorithm, classifying each signature as positive at >20%. The irradiated tumor control was evaluated in patients with ATM missense mutations who received radiotherapy. Results: Among 6,743 unique DDR missense mutations from MSK-IMPACT, 372 (3.5%) were known pathogenic, and 1,182 (17.5%) were new pathogenic mutations. In 205 tumors with bi-allelic core-HR missense mutations in breast, ovarian, pancreatic, and prostate cancers, 20 (9.8%) had new pathogenic mutations. Tumors with new pathogenic mutations more frequently exhibited HR-deficient signatures (65%) than wild-type (31.8%, p < .001), similar to tumors with known pathogenic mutations (62.8%, p = 1.0). In TCGA, HR-deficient signatures tended to be more frequent in tumors with new pathogenic missense mutations than in wild-type tumors (41.7% vs. 21.0%, p = .16). Of 1,010 tumors with POLE missense mutations from MSK-IMPACT, 300 (30%) had new pathogenic mutations. The presence of POLE signatures in tumors with new pathogenic mutations (11.9%) was not significantly different from those with benign mutations (4.3%, p = .19) and less frequent than in tumors with known pathogenic mutations (91.0%, p < .001). In MSK-IMPACT, tumors with new pathogenic ATM missense mutations were less likely to have TP53 mutations than benign missense mutations (32.7% vs. 56.6%, p < .001), consistent with bona-fide pathogenicity. Further, patients with new pathogenic ATM missense mutations showed increased radiosensitivity, characteristic of ATM deficiency, and improved irradiated tumor control compared to those with benign missense mutations (Hazard ratio 0.58, 95% Cl 0.35-0.95, p = .03). Conclusions: AlphaMissense can identify previously unknown pathogenic DDR missense mutations, but its accuracy is gene-dependent. AlphaMissense pathogenicity predictions for DDR genes can utilized to help classify mutations, but may not be sufficient on their own.
Correlation of patient HLA class I genotypes with severe immune-related adverse events: A retrospective study in Chinese population.
Authors: Ai Luoyan , Xu Zhenghang , Zhu Mengxuan , Yu Yiyi , Liu Tianshu
Published: June 2024

10586

Background: Immune checkpoint inhibitors (ICIs) are effective in multiple tumors. However, about 10% of immune-related adverse events (irAEs) are severe and can have serious or even life-threatening consequences for patients. We investigated whether Human leukocyte antigen (HLA) genes predispose to and thus hold a predictive role of developing of severe irAEs in Chinese population. Methods: In a case/control study, we collected data from patients with metastatic cancer treated with ICIs and developed severe irAEs (Grade ≥3 and required hospitalization). Patients treated with ICIs without any irAEs were used as controls. Data was collected from15th Nov, 2019 until 10th Oct, 2023. HLA typing was performed via next generation sequencing. Results: We enrolled 83 patients with severe irAEs and 286 patients treated with ICIs without any irAEs. We found HLA-B*15:27 (OR=9.1, X21,95 = 7.2, P = 0.008) and HLA-C*04:01 (OR=2.5, X21,95 = 7.0, P =0.008) were significantly associated with severe overall irAEs risk. When assessing irAE individually, a significant association between HLA-B*13:02 and serious myocarditis (OR = 3.4, X21,95 = 6.2, P =0.01) as well as striking enrichment for HLA-A*02:03 haplotypes in severe adrenal insufficiency (OR = 10.0, X21,95 = 19.1, P<0.0001) were observed. Conclusions: Specific HLA alleles were associated with severe irAEs. Consideration of pre-prescription HLA typing and vigilance for serious reactions to ICIs are warranted.
Genetic counseling and subsequent cascade genetic testing for women with a family history of pathogenic BRCA1 mutation: A cost-effectiveness model.
Authors: Walker Allison , Marmelstein Briana , Fillman Corrine , Dillon Monica , Graul Ashley
Published: June 2024

10621

Background: BRCA1 pathogenic mutations significantly increase the lifetime risk for breast and ovarian cancer, but risk reducing interventions such as bilateral salpingo-oophorectomy (RRBSO) and mastectomy (RRM) can improve outcomes. For women with a known family history of pathogenetic mutation, genetic counseling and testing is recommended. We sought to determine the cost-effectiveness (CE) of referral to genetic counseling with subsequent cascade testing. Methods: A decision analytic model was created using TreeAgePro 2023 software to evaluate the strategies of routine genetics consultation with Ambry panel testing versus no referral. It was assumed that known BRCA1 carriers would undergo annual breast cancer screening with mammogram and MRI at 25yo, RRBSO at 35yo, and RRM at 40yo. Non-carriers underwent routine annual mammogram at 40yo. Additionally, women who did not undergo genetic testing initially do so at the time of diagnosis of first cancer (breast of ovary) and subsequently underwent all recommended risk reducing strategies if found to have a pathogenic BRCA1 mutation. Outcomes included cost, quality adjusted life years (QALYs), ovarian and breast cancer cases and deaths. Univariate and multi-variate analyses were used to investigate the impact of the strategies. Results: In a Monte Carlo Microsimulation cohort of 10,000 women with a first degree relative with a pathogenic BRCA1 mutation, referral to genetic counseling with testing was the dominate strategy. This strategy resulted in a similar mean cost ($185,543 vs $185,171), but with 2,322 additional QALYs and incremental CE ratio (ICER) of 1,605 per QALY. This dominant strategy also resulted in 73 fewer ovarian cancer cases and 545 fewer breast cancer cases. Sensitivity analysis for the age of RRM was remarkable for an annual reduction in breast cancer cases by 97 cases and an annual cost savings of 375,658 for year prior to age 40 that mastectomy was performed. Conclusions: Routine genetic counseling and screening for all patients with a known family history of pathogenic BRCA1 mutation reduces breast and ovarian cancer diagnoses by prompting risk-reducing procedures without significant increase in cost when compared to diagnosis-based testing. Routine access to genetic counseling in a high-risk population would help inform earlier counseling and further decrease cancer risk, particularly as earlier RRM may improve outcomes. This is further supported by the low cost to implement. Improvement in identification and early referral could be targeted. [Table: see text]
Shareable artificial intelligence to extract cancer outcomes from electronic health records.
Authors: Kehl Kenneth L. , Jee Justin , Pichotta Karl , Trukhanov Pavel , Fong Christopher , Waters Michele , Nichols Chelsea , Cerami Ethan , Schrag Deb , Schultz Nikolaus
Published: June 2024

11000

Background: Clinical outcomes such as response, progression, and metastasis represent crucial data for observational cancer research, but outside of clinical trials, such outcomes are usually recorded only in unstructured notes in electronic health records (EHRs). Manual EHR annotation is too resource-intensive to scale to large datasets. Individual cancer centers have trained artificial intelligence natural language processing (AI/NLP) models to extract outcomes from their EHRs. However, due to concerns that models trained on protected health information (PHI) might encode private data, such models usually cannot be exported to other centers. Methods: EHR data from Dana-Farber Cancer Institute (DFCI) and Memorial-Sloan Kettering (MSK) collected through the AACR Project GENIE Biopharma Collaborative were used to train and evaluate Bidirectional Encoder Representations from Transformers (BERT)-based NLP models to extract outcomes from imaging reports and oncologist notes annotated with the Pathology, Radiology/Imaging, Signs/Symptoms, Medical oncologist, and bioMarkers (PRISSMM) framework. Document-level outcomes included the presence of active cancer; response; progression; and metastatic sites. ‘Teacher’ models trained on DFCI EHR data were used to label imaging reports and discharge summaries from the public MIMIC-IV dataset. ‘Student’ models trained to use MIMIC documents to predict teacher labels were transferred to MSK for evaluation. Results: Teacher models were trained at DFCI on 30,332 imaging reports for 2609 patients and 32,173 oncologist notes for 2917 patients with non-small cell lung, colorectal, breast, prostate, pancreatic, or urothelial cancer. The models were used to label 217,642 imaging reports and 141,377 discharge summaries from MIMIC for student model training. These DFCI-trained student models were evaluated at MSK, demonstrating high discrimination (AUROC > 0.90) across outcomes. Conclusions: This privacy-preserving “teacher-student” AI/NLP framework could expedite linkage of genomic data to clinical outcomes across institutions, accelerating precision cancer research. [Table: see text]
Efficacy of eSyM: Acute care utilization among patients with cancer who do versus do not report ePROs.
Authors: Hassett Michael J. , Uno Hajime , Tramontano Angela , Cronin Christine , Bian Jessica J , Dizon Don S. , Hazard-Jenkins Hannah W. , Osarogiagbon Raymond U. , Wong Sandra L. , Schrag Deb
Published: June 2024

11001

Background: Patients (pts) receiving cancer treatment frequently experience burdensome symptoms that compromise outcomes and necessitate acute care. Prior clinical trials have demonstrated that electronic patient-reported outcome (ePRO)-based symptom management programs improve outcomes in controlled settings. Deploying these programs in routine care settings remains challenging. With funding from the Cancer Moonshot IMPACT Consortium, we created eSyM – an ePRO-based, EHR-integrated symptom management program – to facilitate the widespread adoption of active symptom management efforts. Methods: eSyM was deployed across six health systems from September 2019-August 2022 via a modified stepped-wedge cluster randomized pragmatic trial. Pts starting chemotherapy (CHEM) or undergoing surgery (SURG) for a suspected or confirmed thoracic, gastrointestinal, or gynecologic cancer were prompted to complete symptom questionnaires regularly; those reporting symptoms were offered additional supports. To assess eSyM efficacy, we studied pts who were eligible to use the program – comparing those who completed at least one symptom questionnaire to those who did not. Outcomes included emergency department (ED) visits and inpatient encounters (INPT) at 30 and 90-days. Odds ratios with 95% CIs were derived after adjusting to account for the propensity to report ePROs as a function of age, sex, race/ethnicity, employment, marital status, poverty, rurality, insurance, comorbidity, cancer, treatment goal, institution, and calendar time. Results: Among eSyM-eligible pts, 51% (N = 10,454/20,471) completed at least one symptom questionnaire (median 4 reports/patient) – 47% (3815/8187) for CHEM and 54% (6639/12,293) for SURG. Comparing symptom reporters to non-reporters, the proportion of CHEM+SURG pts experiencing an ED event was 5.3% vs. 7.1% at 30 days and 10.0% vs. 12.9% at 90 days; and the proportion experiencing an INPT event was 6.7% vs. 11.3% at 30 days and 14.0% vs. 19.5% at 90 days ( p< 0.001 for all). Adjusted ORs appear in the. Conclusions: After accounting for propensity to report symptoms, completing at least one symptom questionnaire was associated with lower odds of experiencing an ED or INPT encounter among CHEM and SURG pts across six diverse health systems. eSyM engagement reduced acute care utilization. This EHR-integrated symptom management solution is broadly available to health systems that use Epic. Clinical trial information: NCT03850912 . [Table: see text]
Data-driven strategies for enhancing diversity in oncology clinical trials: Optimization of eligibility criteria.
Authors: Griffith Sandra , Benedum Corey M. , Bozkurt Selen , Bhagat Ruma , Richie Nicole , Lavery Bea , Sarkar Somnath
Published: June 2024

11020

Background: Advancing inclusive clinical research is essential to benefit all patients (pts) and is an expectation, and in some cases a requirement, by regulators. Enabling the inclusion of representative populations should begin at protocol design. However, it is not always clear which changes in eligibility criteria (EC) will have the most impact on representativeness and whether the impact will have similar effect across historically underrepresented populations (HUPs; i.e., pts ≥75 yrs, females, non-Latinx[NL] Black, or Latinx pts). We have defined a novel application of scoring to assess implications of EC on inclusion of HUPs in trials. Methods: Using real-world data from the US nationwide Flatiron Health electronic health record-derived de-identified database for aNSCLC as a benchmark (N=50,263), we selected pts who met trial EC and therapy indication criteria for 9 Phase III aNSCLC trials (2012–2018). We quantified representativeness of the eligible cohort via log disparity [LD], a machine learning fairness metric for the odds of selecting a subgroup vs. the rest of the population; 100% represents parity and 80% is sometimes considered a lower bound for representativeness, but higher benchmarks (e.g., 95%) may be more appropriate. We then identified EC drivers of representativeness by removing or modifying EC. Results: Across HUP groups, the majority of trials (≥55%) were below parity. Removing creatinine clearance (CrCl) had a consistently positive impact for older pts (median % Δ [range]: +2 [1, 32]) and NL Black pts (+2 [1, 5]), but the direction of impact differed across trials for female and Latinx pts (increase in representativeness for some trials, decrease for others). The impact of removing ECOG Performance Status (PS) varied across HUPs (positive for older pts, neutral or positive for female pts, trial-dependent for Latinx and NL Black pts); e.g., in Keynote010, removing ECOG PS increased LD for older pts (93% to 99%), but decreased LD for Latinx pts (97% to 93%). Across trials, removing hemoglobin, HIV, and Hepatitis B/C had a consistently positive or neutral impact on LD for NH Black pts (e.g., hemoglobin median % Δ [range]: +3 [2, 5]), however, the impact was negative or trial-dependent for Latinx and older pts. LD scores can also guide modification of cutpoints to optimize representativeness; e.g., for Keynote189, lowering the CrCL cutpoint from 50 to to 37 mL/min could be expected to improve representativeness for older patients (LD: 66% to 80%, the lower bound for representativeness). Conclusions: It is important to consider the complex nature of diversity when designing trials to ensure that optimizing inclusion of one group of pts does not inadvertently reduce representativeness for another group. These findings support a data-driven approach to modifying EC during protocol design to maximize inclusion of HUPs in concert with a robust operational plan.
Underrepresentation of Asian Americans, Native Hawaiians, and other Pacific Islanders (AA & NHPI) in cancer clinical trials that led to FDA approvals in 2010-2022.
Authors: Leong Ruby , Yang Felice , Lee Jennifer J. , Srivastava Geetika , Wedam Suparna B. , Dilawari Asma Ali , Fan Chaohong , Tran Grace , Lee Sso , Andrada Frances , Lee Clara , Fashoyin-Aje Lola A. , Amiri-Kordestani Laleh , Singh Harpreet , Lemery Steven , Pazdur Richard , Rivera Donna , Gao Jennifer , Kim Tamy
Published: June 2024

11026

Background: About 6% and 0.3% of the total United States (US) population identify as Asian or NHPI alone, respectively. The most commonly diagnosed cancers among AA & NHPI in the US are breast, prostate, lung, thyroid, and colorectal. Liver, gastric, and head and neck cancers occur in higher rates in AA & NHPI vs. non-Hispanic White. Enrollment of Asian & NHPI patients in multiregional cancer clinical trials may provide additional data regarding intrinsic and extrinsic factors (e.g., diet, infections, environmental exposures) impacting the etiology of cancer. We investigated enrollment trends of NHPI and Asian (within and outside of US) patients in cancer clinical trials that led to an FDA approval from 2010-2022. Methods: We analyzed data from ~98,000 patients in 171 cancer therapeutic clinical trials that led to FDA approvals for breast, prostate, lung, thyroid, colorectal, liver, gastric, and head and neck cancer indications from 2010-2022. Separate race categories of Asian and Native Hawaiian and other Pacific Islander were used. Results: Descriptive statistics of NHPI and Asians within and outside of US enrollment in breast, prostate, lung, thyroid, colorectal, liver, gastric, and head and neck cancer trials that led to an FDA approval from 2010-2022 are summarized in the table. Enrollment of Asian patients in the US was <1% (except for liver cancer) and NHPI patients was <0.2%. Conclusions: Although cancer is the leading cause of death for AA & NHPI, AA & NHPI are under-represented in cancer clinical trials, especially when data are further disaggregated into enrollment of NHPI and Asians within and outside of the US. Cancer etiology may vary in Asians in the US vs. Asia due to different intrinsic/extrinsic risk factors, underscoring the importance of enrolling more AA & NHPI into clinical trials to expand the evidence supporting drug approvals in the US and to advance health equity through clinical trial diversity. [Table: see text]
Historic redlining, modern neighborhood structures, and mortality in children, adolescents, and young adults with cancer.
Authors: Karvonen Kristine , Vu Annie , Lin Katherine , Gibbons Joseph , Mendoza Jason , Chow Eric Jessen , Winestone Lena E. , Gomez Scarlett L.
Published: June 2024

11037

Background: Historic redlining, referring to the Home Owners Loan Corporation (HOLC) program’s racially biased risk monitoring maps in the 1930’s, has indelible impacts on modern day neighborhood characteristics and health outcomes. The impact of redlining, a form of structural racism, on children, adolescents, and young adults with cancer (CAYACs) is unknown. This retrospective cohort study evaluates the association between redlining and mortality in CAYACs. Methods: Using the California Cancer Registry, we identified cases <25 years old diagnosed with first primary malignant cancer between 2000-2019. Using merged HOLC maps and U.S. Census data we determined case redlining status (A “Best”, B “Still Desirable”, C “Declining”, D “Hazardous”, and N “Not graded”) by residence at diagnosis. We defined residents of D neighborhoods redlined-exposed and residents of A or B neighborhoods unexposed or referent. Kaplan Meier methods and multivariable Cox proportional hazard models were applied to calculate overall survival. Additional models accounted for census tract-level neighborhood SES (nSES, a composite measure incorporating seven SES domains), neighborhood racial and ethnic composition (or typology) and racialized economic segregation (via index of concentration at the extremes). Results: In total 8,210 cases were HOLC-graded, the median age was 16 years, 46% were female, and 48% had solid tumors. Overall survival at 5 years was inferior for D cases vs. A or B cases (OS 80.2%, 95% CI: 78.5-81.7 vs. OS 88.2, 95% CI: 84.0-91.3). Adjusting for individual clinical characteristics (age, sex, year of diagnosis, and cancer stage), D cases experienced greater mortality (HR 1.32, 95% CI: 1.12-1.55) compared to A or B cases. Additional adjustment for insurance and nSES attenuated the relationship (HR 1.17, 95%CI: 1.00-1.36 and HR 1.07, 95% CI: 0.92-1.24 respectively). Similar patterns were observed in models adjusting for racialized economic segregation (HR 1.07, 95% CI: 0.92-1.24) and typology (HR 1.10, 95% CI: 0.94-1.28) in place of nSES. Conclusions: In this population-based study, redlined-exposed CAYACs experienced greater mortality compared to unexposed CAYACs. Adjusting for insurance and contemporary nSES attenuated the association between redlining and mortality. Findings suggest current neighborhood attributes may be downstream manifestations of structural racism with survival implications for CAYACs.
Characteristics and pregnancy outcomes of pregnant women by cancer diagnosis status.
Authors: Periyanayagam Usha , Popadic Lyuba , Devine Francesca , Wei Yuqin
Published: June 2024

11038

Background: Given the broad exclusion of pregnant patients from clinical trials, limited evidence exists on the impact of cancer diagnoses on pregnancy outcomes. This study aimed to describe patient characteristics and end of pregnancy events among women with and without a cancer diagnosis before pregnancy. Methods: This retrospective claims study used data from the Komodo Research Dataset between 01/01/2016–08/31/2023 to identify adult women with a known gestation of pregnancy record and end of pregnancy outcome. Eligible members needed to be continuously enrolled in medical and prescription drug plans for both 365 days before (baseline) and after the derived pregnancy start (index date). This pregnancy cohort was then stratified according to cancer status, evidenced by any cancer diagnosis during the baseline period, to allow assessment of pregnancy outcomes. Valid pregnancy outcomes included full or preterm live birth and pregnancy loss such as miscarriage, stillbirth, and elective termination. Only the earliest pregnancy observed for each eligible member was analyzed. Results: Among the 1,921,866 pregnant women included in the analyses, only 0.7% (N=12,723) of patients had any cancer diagnosis in the year prior to pregnancy start. Cancer patients were older than non-cancer patients (mean age: 33.8 and 29.2 years, respectively). Commercial medical insurance was more common (67.7% vs. 58.9%) among cancer vs. non-cancer patients and Medicaid enrollment was less common (30.3% vs. 40.6%) upon pregnancy start. The proportion of patients with a live birth was lower among cancer vs. non-cancer patients (59.7% vs. 67.1%), while the proportion with pregnancy loss was higher (31.6% vs. 25.8%). Medicaid enrollment was more common among patients that had a pregnancy loss relative to live birth for both cancer and non-cancer patients (35.5% vs. 27.5% and 45.7% vs. 38.7%, respectively). The proportion of black patients was higher among patients with a pregnancy loss relative to those with live birth in both cohorts (cancer: 11.1% vs. 8.3%; non-cancer: 16.9% vs. 13.7%), while the proportion of white patients was similar for cancer patients with a pregnancy loss vs. live birth (37.4% vs. 37.1%) and the proportion was lower for non-cancer patients (30.4% vs. 34.4%). Conclusions: Preliminary findings suggest pregnancy loss was more common among cancer patients than non-cancer patients. Regardless of cancer status, differences in insurance coverage and race were observed for patients with a live birth relative to patients with pregnancy loss. Additional research should be conducted to identify factors driving differences in pregnancy outcomes, such as in care management by race and ethnicity, particularly among the vulnerable population of cancer patients.
Comorbid opioid use disorder and resource utilization outcomes in patients with neoplasm-related pain: A population analysis.
Authors: Akhiwu Ted , Freeman Jincong Q. , Atarere Joseph , Ndakotsu Andrew , Omoike Eugene , Edigin Ehizogie , Kanemo Philip Onyekaoso , Gangireddy Mounika
Published: June 2024

11040

Background: Neoplasm-related pain (NRP) is one of the most debilitating sequalae of cancer, affecting patients’ (pts) quality of life. Its intersection with opioid use disorder (OUD) adds a layer of complexity to patient care in the United States (US). As the prevalence of both conditions continues to increase, understanding the association between OUD and NRP becomes important. This study aimed to shed light on this intricate relationship by examining outcomes in resource utilization among OUD pts with NRP. Methods: We analyzed weighted data from the 2016-2020 iterations of the National Inpatient Sample database. We included pts 18 years or older with a principal discharge diagnosis of NRP with or without a secondary diagnosis of OUD. The main outcomes for the study were length of stay (LOS) and total hospitalization charges (THC) adjusted for inflation using the Medicare Hospital Consumer Price Index. Baseline sociodemographic and hospital characteristics as well as comorbidities of patients with and without OUD were compared using χ2 for categorical variables and Student’s t-test for continuous variables. Multivariable Linear regression was used to assess the relationship between comorbid OUD and resource utilization among NRP hospitalizations. Statistical significance was set at p<0.05. Results: There were 120,359 hospitalizations for NRP between 2016 and 2020. Among patients hospitalized for NRP, 3335 (2.78%) had a secondary diagnosis of OUD. The mean age of NRP pts was 60 years. Compared to patients without OUD, OUD pts were male (50.67% vs 45.47%; p = 0.0086), younger (mean age 56 vs 60 years; p<0.0001), more likely to be on Medicaid (37.48% vs 21.00%; p <0.0001) and hospitalized in urban hospitals (94.6% vs 91.37%; p = 0.0040). On multivariable linear regression, OUD was associated with an increased LOS by 0.93 days compared to non-OUD patients (95% CI: 0.265 – 1.600; p = 0.006), as well as increased THC by $9248 (95% CI: 1676.00 – 16820.41; p = 0.017) after adjusting for sociodemographic and hospital covariates. Conclusions: Our study highlights an increased resource utilization among pts with NRP and comorbid OUD. We surmise this could be due to increased tolerance to and dependence on the effects of opioids requiring more intricate multidisciplinary care in managing their pain. Recognizing this association is important for medical oncologists and other health care providers when managing NRP pts with OUD. Incorporating multimodality pain management early on admission could improve patient outcomes while optimizing healthcare resources.
Electronic patient-reported outcome measures (E-Proms): Results of the H2020 CAPABLE project for patients with metastatic renal cell cancer (mRCC).
Authors: Locati Laura D. , Rizzo Mimma , Gabanelli Paola , Quaglini Silvana , Tibollo Valentina , Malovini Alberto , Panzarasa Silvia , Terzaghi Matteo , Lanzola Giordano , Premoli Andrea , Demurtas Sara , Sacchi Lucia
Published: June 2024

11045

Background: E-Proms were shown to benefit both survival and quality of life (QoL) of cancer patients. So far, E-Proms have been mostly implemented as the electronic version of validated, paper-based questionnaires typically administered at follow-up visits. Benefits of telemedicine systems that put symptom reporting within a wider framework embracing a holistic view of a patient's wellbeing are still under-investigated. Methods: Thirty mRCC patients were enrolled in the CAPABLE project intervention cohort during 2023. They were provided with the CAPABLE smartphone app, and with a smartwatch able to monitor vital parameters, physical activity, and sleep. The app acts as a virtual coach, allowing patients to enter any symptom they experience through an interface inspired by both CTACE and proCTCAE. Immediate feedback on whether to contact or not a doctor is generated according to the symptom severity. Patient’s data are matched with the ESMO guidelines for toxicity management, a selection of which was computerized within CAPABLE, and any generated recommendation is shown to the patient. The app manages the symptom follow up, periodically prompting the patient to report any change, and it also promotes activities aimed at improving patients’ education, mental wellbeing and lifestyle. All the entered data may be visualized by doctors at the hospital. The CAPABLE cohort was compared with a control cohort of 77 mRCC patients, enrolled in 2021/2022, who underwent standard care. All patients filled in a set of questionnaires measuring QoL, satisfaction, nutritional and psychological status at enrollment (T0), after 3 months (T1) and after 6 months (T2). A focus group with the CAPABLE cohort was held close to the end of the study. In this report the primary outcome, i.e. EORTC QLQ-C30 score for QoL, is discussed, together with qualitative results from the focus group. Results: The analysis shows an increase in the average QoL for the CAPABLE cohort (80.7 vs 84.9), and a slight decrease in the controls (80 vs 77), with a statistically significant interaction between time and cohort (p < 0.05). Considering QLQ-C30 subscales, CAPABLE patients showed less fatigue and improved social and role functioning. As from the focus group, the app was perceived as effective and useful. More connection with the patient’s clinical pathway and more personalization according to specific treatments were highlighted as needed improvements. Conclusions: This study shows that E-Proms may be effectively included in a comprehensive and engaging system for remote management of mRCC patients. Clinical trial information: NCT06161233 .
Administrative burden of establishing health care coverage for the uninsured and its impact on timely access to care.
Authors: Wang Laura , Hong Arthur S , Narayan Aman , Sadeghi Navid , Halm Ethan A
Published: June 2024

11050

Background: Although safety net coverage programs like Medicaid exist to fund health care for low-income patients, the administrative burden of the lengthy application limits uptake by eligible individuals. Therefore, many patients do not attempt to enroll until they become ill, which is common among uninsured adults diagnosed with cancer. The literature reports worse cancer outcomes for those with Medicaid, but reasons for this are unclear. The delays in enrollment for patients with uncertain coverage at the time of diagnosis – those in limbo – are understudied and may explain some of this persisting disparity. We estimated the patient and health system burdens for those with uncertain coverage status at the time of cancer diagnosis at Parkland Health, the main provider of cancer treatment for the uninsured in Dallas, Texas. Methods: We assembled the electronic health record financial encounter data of patients with an incident cancer diagnosis in the Parkland tumor registry, diagnosed from 2010 – 2022. We defined patients as being “in limbo” if they had self-pay, pending, or missing insurance plans at the date of diagnosis. We also included patients whose coverage verification date occurred after diagnosis date, since coverage programs can apply retroactively for 90 days. We used plan verification dates to identify when limbo status resolved. We used coarsened exact matching to balance across age, race, Spanish-language preference, Charlson, and screenable cancer type, then multivariate regression to compare patients that were in limbo to those that had established coverage before cancer diagnosis. Results: We identified 17,468 adults newly diagnosed with cancer, 80% of whom were < age 65, 55% female, 73% Hispanic and/or Black, and 30% Spanish-language preferring. The most common cancer types were GI/colorectal (19%), breast (17%), and lung (9%); 23% were advanced stage at diagnosis and 13% died within 180 days of diagnosis. 52.1% were already enrolled in Medicaid/charity care, but one-third (35%) were in limbo at diagnosis, which lasted for a median 31 days (IQR 13 – 126). Over half (55%) of patients in limbo resolved to Medicaid or charity care. Patients who experienced limbo had a median of 596 financial account notes in the first year after diagnosis, 121 more than the comparison group (95% CI 86.7 - 156.1) and began treatment 10 days later (95% CI 7.7 - 12.7). They also had a median of 1 ED visit in the year after diagnosis, 0.2 more than patients never in limbo (95% CI 0.11 - 0.26). Conclusions: The administrative burden of enrolling into coverage programs for the uninsured may impose direct and indirect costs on patients and safety-net health systems and may contribute to worse cancer care outcomes. A more comprehensive accounting of the effects of administrative burdens might suggest ways to redesign coverage enrollment for the uninsured to improve care and reduce costs.
Disrupting how we recruit to cancer clinical trials.
Authors: Bickell Nina A. , May Benjamin , Havrylchuk Ihor , John Jimmy , Lin Sylvia , Yagnik Radhi , Tao Ariana , Hillyer Grace C. , Rapkin Bruce , Tatonetti Nicholas
Published: June 2024

11072

Background: Traditional methods to identify eligible patients for cancer clinical trials rely heavily on manual review, a time-consuming bottle neck limiting access to novel treatments, particularly for underserved populations. This study presents an automated informatics platform designed to simplify and streamline patient identification and trial matching. Methods: Our platform leverages three tools: 1. Parser:Extracts and categorizes trial data based on cancer type, stage, and receptor status from the National Cancer Institute's ClinicalTrials.gov database, storing it in a structured JSON format; 2. Screener: Utilizes Epic Clarity electronic health record data to identify upcoming patients approaching treatment decision points, times when clinical trials are more relevant. Patients are classified as "newly diagnosed" or "potentially progressed" based on progress notes and imaging reports. Eligibility criteria, including stage and receptor status, are assessed using regular expressions; 3. Matcher: Pairs eligible patients with relevant trials based on compatible cancer stage and receptor status. One Cancer Center (CC) is prospectively using the platform to identify patients. The 2nd CC is refining the code using retrospective data. Accuracy was measured comparing automated to manual review by experienced trained abstractors. Results: Implementation across two cancer centers yielded: 1. Reduced manual review burden: Between June 2023 – Jan 2024, of 674 breast cancer patients seen at CC #1, 371 were new patients (N=371) and thus, at a treatment decision point; 3 did not undergo imaging. Of the 300 established patients undergoing imaging studies, the algorithm identified 50/300 (17%) scans as “positive,” and 61 (20%) with mixed disease progression/ regression, requiring manual review and trial matching. 189 scans were read as “negative”: 96% True Negatives; 4% were False Negatives. Automated screening reduced manual review from 300 to 111 patients, significantly alleviating workload on healthcare personnel. 2. Variable staging accuracy: While receptor status classification proved effective, stage accuracy varied between centers, highlighting a need for further refinement in this area. 3. Accurate receptor status classification: The system achieved high accuracy in demonstrating reliable assessment of this vital factor. Conclusions: This automated informatics platform demonstrates significant potential to streamline case identification for cancer clinical trials and thus, foster broader access to novel therapies. Its adaptability makes it suitable for implementation across diverse healthcare settings, empowering wider participation in advancements in cancer care. Ongoing efforts to refine the staging module are underway. Clinical trial information: NCT05146297 . [Table: see text]
Effect of multi-cancer early detection screening on late-stage cancers: A modeling study.
Authors: Chhatwal Jagpreet , Xiao Jade , Merdan Selin , ElHabr Andrew , Tyson Christopher , Cao Xiting , Raoof Sana , Fendrick A. Mark , Ozbay Burak Burak , Limburg Paul J. , Beer Tomasz M. , Deshmukh Ashish , Briggs Andrew
Published: June 2024

11076

Background: Emerging blood-based multi-cancer early detection (MCED) tests can revolutionize early cancer detection. We evaluated the potential impact of MCED screening in reducing risk of late-stage diagnosis of 12 specific cancers which represent 70% of all cancer incidence in the US. Methods: We developed Simulation Model for MCED (SiMCED), a microsimulation model of 12 solid tumor cancer types: breast, colorectal, endometrial, esophageal, gastric, kidney, liver, lung, ovarian, pancreatic, prostate, and urinary bladder. Transitions between cancer stages (I-IV) were driven by cancer type- and stage-specific dwell times, which were synthesized from published literature and empirical estimates. MCED test sensitivity was derived from the PRE-ASCEND study on average-risk American adults. The model was calibrated to reproduce yearly observed cancer incidence diagnosed symptomatically or through screening as captured in the Surveillance, Epidemiology, and End Results (SEER) database, while accounting for unobserved cancer incidence by age, sex, and cancer type and stage. Using a 50-year time horizon, we simulated 100,000 individuals aged 50 to 84 years. Diagnosis of cancer could arise from usual care (UC) or annual MCED screening. Results: Over the 50-year horizon, MCED screening of 100,000 individuals resulted in 1,323 fewer Stage IV (24%) diagnoses relative to UC, with 38% of Stage IV reductions attributed to non-screening-detectable cancer types (i.e., those without recommended screening guidelines). The table displays absolute and percentage reductions in Stage IV diagnoses for the 8 cancer types with the highest absolute reduction in Stage IV diagnoses. The percentage of Stage IV reduction was 21% for screening-detectable cancers and 29% for non-screening-detectable cancers. Conclusions: Our study suggests that MCED screening could be effective for reducing the incidence of Stage IV cancer, which is associated with the worst survival and quality of life. Of note, MCED has the potential to reduce Stage IV cancer incidence for cancers without recommended screening guidelines. However, the real-world impact of MCED tests and their cost-effectiveness require further investigation. [Table: see text]