bluuebunny/crossref_metadata_2025_split huggingface dataset:
Biomarker testing patterns in patients with stage IV non-small cell lung cancer (NSCLC) in U.S. community-based oncology practice setting.
Authors: Sireci Anthony , Krein Peter M , Hess Lisa M. , Khan Taha , Willey Joanne P. , Ayars Michael , Deyoung Kathryn , Bhaskhar Sandya , Mumuney Ganiat , Coutinho Anna D. 
Published: September 2021

300 Background: This study evaluated rates of biomarker testing for patients with stage IV non-squamous NSCLC, which is known to have a ̃40% biomarker-positive rate (AMP, 2020), in a community-based oncology practice setting in the United States (US). Methods: A retrospective study was performed using data from a US electronic medical record database of patients aged ≥18 years with an initial diagnosis (index dx) of stage IV non-squamous NSCLC between Jan 1, 2015 and Dec 31, 2019. Unstructured data on molecular biomarker testing (single-gene and next-generation sequencing [NGS]-based) were abstracted from patient charts utilizing Natural Language Processing for EGFR mutation, ALK rearrangement, BRAF mutation, ROS1 rearrangement, MET exon14 mutation, RET fusion, NTRK fusion, and PD-L1 expression. Systemic therapy was obtained from structured data. Data were summarized using descriptive statistics. This study received a waiver of consent from Advarra IRB. Results: Of 646 patients identified in the database, 500 met all inclusion criteria and are included in this analysis. The majority (73.8%) were diagnosed in 2018 (n = 162; 32.4%) and 2019 (n = 207; 41.4%). Mean age (SD) was 70.0 (10.1) years, with 53.2% female. A total of 447 (89.4%) were tested for at least one biomarker after index diagnosis of which 81.2% (n = 406) had at least one single-gene test; 54.8% (n = 274) had an NGS test and 66.8% were tested for PD-L1. Single-gene or NGS-based testing was > 85% of patients across all index years. The use of NGS-based tests ranged from 35.0% among patients whose first diagnosis was in 2015 to 59.4% in 2019. Overall, 85.4% (n = 427) of the cohort received first-line treatment with chemotherapy (53.6%), immunotherapy (48.2%), or targeted therapy (14.2%). Among patients who received biomarker tests, 15.4% received targeted treatment and 49.7% received immunotherapy treatment, including checkpoint inhibitors, during first-line treatment. Conclusions: NGS testing utilization increased during the study period and by 2019, 59% of patients received NGS-based testing. Opportunities persist for practices to improve testing and achieve guideline recommendations. PD-L1 biomarker testing was performed amongst the highest proportion of patients in this study and nearly 50% of all patients received immunotherapy, including checkpoint inhibitors. Targeted therapy was used in 14.2% of this population, suggesting that patients with actionable biomarkers may not be receiving targeted treatment for their disease, potentially due to gaps in testing among patients in this dataset.
Real-world patterns of pain medication use among patients with metastatic pancreatic ductal adenocarcinoma (mPDAC).
Authors: Laursen Ashley Ann , Surinach Andy , Wang Shu , Cockrum Paul , George Ben 
Published: September 2021

302 Background: Helping patients manage cancer-related pain is an important aspect of supportive care. 80% of patients with mPDAC suffer from abdominal and/or back pain. Pancreatic cancer-related pain is typically treated pharmaceutically using pain medicines, which include opioids or narcotics. Previous studies have found that the presence of pain was associated with impaired survival in pancreatic cancer patients. The goal of this study was to assess the treatment patterns of pain medication usage and their association with duration of therapy (DOT) among patients with mPDAC treated in the real-world setting. Methods: This retrospective observational study utilized the IBM MarketScan Commercial and Medicare supplemental claims data. Data were analyzed for adult patients who were diagnosed with mPDAC and received treatment between January 2015 and March 2020. Patient characteristics and DOT were assessed. Opioid use during treatment including the number of prescriptions filled and average daily dose in morphine equivalents were summarized. Yearly and regional trends of opioid use were assessed. Results: There were 2,841 patients (median age: 61 years, IQR: 56-66) included in the study treated with first line (1L) therapies of interest. 55.6% (n = 1,579) of patients were male and 72.0% (2,046) had commercial insurance. The overall DOT in 1L was 78 days (IQR: 38 – 157). 54.3% of patients filled at least one prescription for opioids during treatment. The mean number of prescriptions filled during treatment was 2.2 (SD: 4.0) and the mean daily dose was 39.5mg morphine equivalents (SD: 134.6) The median DOT among patients who received at least one pain prescription was 92 days (IQR: 44 – 176) while those who did not receive pain medication experienced a DOT of 64 days (IQR: 29 – 135). Among the 1,248 patients who received second line treatment the median DOT was 60.5 days (IQR: 29 – 127). 50.6% (n = 632) filled at least one opioid prescription during treatment. Median DOT among patients who received pain medication was 73.5 days (IQR: 42 – 141) and 47.5 days (IQR: 15 – 103.5) among those who did not. Across lines of therapy opioid use remained stable during the study period ranging from 54.2% among patients treated in 2015 to 51.1% among those who initiated treatment in 2019. No regional differences were observed in prescription patterns within the four US census regions (range: 50.2 – 54.4%). Conclusions: In this real-world cohort of patients with mPDAC nearly half were prescribed at least one opioid during treatment. Patients who received opioids experienced a longer duration of therapy compared to those who did not. Further studies are needed to understand the association of pain control with improved clinical outcomes among patients with mPDAC.
Impact of antibiotic (ATB) exposure prior to immune checkpoint inhibitor (ICI) treatment on overall survival (OS): A population-based study.
Authors: Eng Lawson , Sutradhar Rinku , Niu Yue , Liu Ning , Liu Ying , Kaliwal Yosuf , Powis Melanie Lynn , Liu Geoffrey , Peppercorn Jeffrey M. , Bedard Philippe L. , Krzyzanowska Monika K. 
Published: September 2021

303 Background: ICIs are a common therapeutic option for many solid tumors. While prior studies have shown that ATB exposure may negatively impact ICI outcomes through gut microbiome changes, many were small studies with heterogeneity in ATB classes and exposure windows. Here, we performed a population level retrospective cohort study to evaluate the impact of ATB exposure prior to ICI on OS. Methods: We used administrative data to identify a cohort of cancer patients > 65 years of age receiving ICIs from June 2012 to October 2018 in Ontario, Canada and deterministically linked with databases to obtain socio-demographic and clinical co-variates and ATB prescription claims. Multivariable cox-proportional hazard models evaluated the impact of ATB exposure both within 1 year and 60 days prior to starting ICI on OS, adjusted for age, gender, body mass index, comorbidities, autoimmune history, hospitalization in the past year and treatment facility level at start of ICI therapy. Results: Among 2737 patients, median age 73; 43% received Nivolumab, 41% Pembrolizumab and 13% Ipilimumab; 53% were lung cancer, 34% melanoma. Median ATB treatment duration for patients receiving ATB within 1 year (59%) and 60 days (19%) prior to ICI were 14 days (SD = 32) and 9 days (SD = 13) respectively. Median OS estimate was 306 days. Any ATB exposure within 1 year prior to ICI was associated with worse OS (aHR = 1.12 95% CI [1.12-1.23] p = 0.03). A non significant dose effect was seen based on weeks of ATB exposure 1 year prior to ICI (aHR = 1.01 per week [1.00-1.02] p = 0.10). ATB class analysis identified fluoroquinolone exposure within 1 year (aHR = 1.26 [1.13-1.40] p < 0.001) and 60 days before ICI (aHR = 1.20 [0.99-1.45] p = 0.06) were associated with worse OS; with a dose effect based on total weeks of exposure over 1 year (aHR = 1.07 per week [1.03-1.11] p < 0.001) and 60 days (aHR = 1.12 per week [1.03-1.23] p = 0.01). Subgroup analysis showed similar results for patients receiving anti-PD1 ICIs, where patients exposed to fluoroquinolone both 1 year (aHR = 1.28 [1.15-1.44] p < 0.001) and 60 days (aHR = 1.19 [0.98-1.44] p = 0.08) before ICIs had poorer OS with dose effects observed based on weeks of fluoroquinolone exposure. Similarly, subgroup analyses based on disease site identified that lung cancer patients exposed to fluoroquinolones 1 year before starting ICIs (aHR = 1.22 [1.06-1.39] p = 0.005) and melanoma patients exposed to fluoroquinolones 60 days before starting ICIs (aHR = 1.66 [1.12-2.47] p = 0.01) had poorer OS. Conclusions: Exposure to ATBs and specifically fluoroquinolones prior to ICI therapy is associated with worse OS. Interventions aimed at altering the gut microbiome may be required to help improve outcomes for patients on ICIs with prior ATB exposure.
Treatment initiation with bone-targeting agents among patients with bone metastasis secondary to solid tumors or patients with multiple myeloma.
Authors: Tran Oth , Hatfield Mark , Moynihan Meghan , Shah Neel , Costa Laurie A. , Saad Hossam , Despiegel Nicolas 
Published: September 2021

309 Background: Recent real-world evidence is lacking regarding the initiation of bone-targeting agents (BTAs), and time to treatment with BTAs after a diagnosis of bone metastasis secondary to solid tumors (BM-ST) or multiple myeloma (MM), in both the commercially insured and Medicare Supplemental populations. Methods: Patients aged >18 and newly diagnosed with BM-ST or MM during 11/1/2016-6/30/2019 (earliest diagnosis = index date) were selected from the IBM MarketScan Commercial and Medicare Databases. Patients were continuously enrolled in the 12 months before and 6 months after the index date and had no prior evidence of BTA use, skeletal-related events (SREs), osteoporosis or Paget’s disease. Initiation of and time to BTA treatment (i.e., denosumab, zoledronic acid, ibandronate or pamidronate) were reported during the variable follow-up period. SREs prior to BTA use were reported and included spinal cord compression, pathological fractures, surgery and radiation to bone. Results were stratified by tumor type (BM-ST and MM) and payer (commercial and Medicare). Results: The analysis included 8,769 commercially insured patients (70% BM-ST and 30% MM [mean age 55 and 54]) and 4,100 Medicare patients (74% BM-ST and 26% MM [mean age 76 and 75]). Across payers, the most common comorbidities were pain and hypertension. BTA initiation for BM-ST and MM patients was 46% and 24% among the commercial cohort, and 33% and 18% among the Medicare cohort. Among BM-ST commercial and Medicare cohorts, respectively, the proportion initiating BTA varied by solid tumor type: 64% and 45% of breast, 43% and 37% of prostate, and 47% and 34% of lung. Mean (SD) time to BTA initiation for BM-ST and MM patients was 3.0 (4.2) and 3.7 (5.2) months for the commercial cohort, and 3.1 (4.7) and 2.9 (3.3) months for the Medicare cohort. Among patients with BTA initiation, the proportion of BM-ST and MM patients with SREs prior to BTA treatment was 33% and 31% for the commercial cohort and 23% and 26% for the Medicare cohort. Across payers, the majority of first SREs were radiation to bone for BM-ST patients and pathological fracture for MM patients. Conclusions: For commercial patients, about one-half of BM-ST patients and a quarter of MM patients initiated BTA treatment; for Medicare patients, these proportions decreased to a third and a fifth, respectively. On average, BTA initiation occurred within about 3 to 4 months from first diagnosis. The proportion of commercial and Medicare patients with SREs prior to BTA initiation was a third and a quarter, respectively. Results generated from this study should be supplemented by the evaluation of the relationship between bone protection treatment patterns and outcomes associated with BM-ST and MM.
Validation of self-reported incident cancer diagnoses in the U.S. Health and Retirement Study: A tool for population-based cancer and aging research.
Authors: Mullins Megan , Kler Jasdeep , Eastman Marissa , Kabeto Mohammed , Wallner Lauren P. , Kobayashi Lindsay 
Published: September 2021

312 Background: Population aging and improving cancer survival rates are resulting in a growing population of older cancer survivors in the United States (US). As a result, there is an increasing need for longitudinal, population-representative data for interdisciplinary cancer research among older adults. The US Health Retirement Study (HRS) is an ongoing population-representative cohort of US adults over age 50 that contains rich interview and biomarker data on health during aging. Interviews have collected self-reported cancer diagnoses since 1998, but these self-reports have not been validated. We compared first incident cancer diagnoses self-reported in HRS interviews against diagnostic claims from linked Medicare records. Methods: We examined the validity of first incident cancer diagnoses self-reported in biennial HRS interviews from 2000 through 2016 against ICD-9 and ICD-10 diagnostic claim records among 8,242 HRS participants aged ≥65 with 90% continuous enrollment in fee-for-service Medicare, using the claim records as the gold standard. We calculated the sensitivity, specificity, and k for first incident cancer diagnoses (all cancers combined, excluding non-melanoma skin cancer, and each of bladder, breast, colorectal/anal, uterine, kidney/renal, lung/bronchus, and prostate cancers) cumulatively over the follow-up, and at each biennial study interview. Results: Self-reports of first incident cancer diagnosis (agnostic of site) between 2000 and 2016 had 73.2% sensitivity and 96.2% specificity against Medicare claims (k = 0.73). For site-specific self-reports, sensitivities ranged from 44.7% (kidney) to 75.0% (breast), and specificities ranged from 99.2% (prostate) to 99.9% (bladder, uterine, and kidney). Results were similar in sensitivity analyses restricting to individuals with 100% continuous fee-for-service Medicare enrollment and when restricting to individuals with at least 24 months of Medicare enrollment. Conclusions: Self-reported cancer diagnoses in the HRS have reasonable validity for population-based research on cancer and aging across cancer types. Apart from breast cancer, cancer site specific analyses will greatly benefit from the improved validity of self-report with Medicare claim linkage.
Perceptions of barriers to patient financial hardship screening differ by provider role within gynecologic oncology outpatient care.
Authors: Dholakia Jhalak , Pisu Maria , Huh Warner King , Liang Margaret Irene 
Published: September 2021

317 Background: Although approximately half of patients with gynecologic malignancy experience financial hardship (FH) during treatment, best practices to identify and assist patients with FH are lacking. To develop such practices, we assessed oncology provider and staff perspectives about FH screening and provision of assistance. Methods: An anonymous survey was conducted electronically within the Gynecologic Oncology outpatient office at a Comprehensive Cancer Center. Potential barriers to patient FH screening and follow-up were assessed within 2 domains: 1) logistic barriers to incorporating FH screening and follow-up into outpatient workflow and 2) perceived patient barriers to FH screening. Responses were elicited on a 5-point Likert scale from ‘very’ to ‘not at all’ significant and dichotomized into significant and not significant barriers. Results: Of 43 providers approached, 37 responded (86% response rate) of which 14 were physicians (MD)/nurse practitioners (NP) and 23 were other staff members (i.e., clinical and research nurses, social workers, pharmacists, care coordinators, lay navigators, and financial counselors). Altogether, 38% worked in their current position for >5 years (n=14), 11% for 3-5 years (n=4), and 51% for <3 years (n=19). For logistic barriers to implementing FH screening and follow-up, the most frequently reported significant barriers included lack of personnel training (69%) and lack of available staff (62%), training regarding follow-up (72%), and case tracking infrastructure (67%). The most frequent significant perceived patient barriers were lack of knowledge of whom to contact (72%), concerns about impact on treatment if FH needs were identified (72%), and lack of patient readiness to discuss financial needs (62%.) Compared to MD/NP, staff members more often indicated the following as significant barriers: difficulty incorporating FH screening into initial visit workflow (31 % vs. 57%, p=0.03), overstretched personnel (29% vs 73%, p=0.005), and patient concerns about influence on treatment (62% vs 86%, p=0.01). Conclusions: Care team members identified barriers to patient FH screening across logistic and patient-centered domains, although MD/NP less so than other staff possibly reflecting different exposures to patient financial needs during clinical encounters or burden of workflow. Implementation of universal FH screening, dedicated personnel, convenient tracking mechanisms, and multi-disciplinary provider and staff training may improve recognition of patient FH and facilitate its integration into oncology care plans.
Physician satisfaction with electronic medical records (EMRs): Time for an intelligent health record?
Authors: Gajra Ajeet , Simons Dewilka , Jeune-Smith Yolaine , Valley Amy W. , Feinberg Bruce A. 
Published: September 2021

318 Background: EMRs are devised to improve the quality and efficiency of healthcare delivery and to reduce medical errors. Despite the widespread use of EMRs, various factors can limit their effectiveness in improving healthcare quality. General EMR use has been cited as a factor contributing to increased workload and clinician burnout in oncology and other specialties. The objective of this qualitative research study was to identify barriers perceived by medical oncologists and hematologists (mO/H) in utilizing EMR software and factors associated with levels of satisfaction. Methods: Between January and April 2021, mO/H from across the U.S. were invited to complete a web-based survey about various trends and critical issues in oncology care. Demographics about the physicians and characteristics of their practices were captured as well in the survey. Responses were aggregated and analyzed using descriptive statistics. Results: A total of 369 mO/H completed the survey: 72% practice in a community setting; 47% identified as a hospital employee; they have an average of 19 years of clinical experience and spend on average 86% of their working time in direct patient care, seeing 17 patients per day on average on clinic days. Most (99%) of mO/H surveyed use an EMR software at their practice, with Epic (45%) and OncoEMR (16%) being the most common. Regarding satisfaction, 16% and 50% reported feeling highly satisfied and satisfied, respectively, with their current EMR, and 3% and 11% reported feeling very dissatisfied or dissatisfied, respectively. Some (19%) stated that they have considered changing their EMR, and 68% are unsure how EMR licensing fees for their practice are paid. EMR pain points most commonly experienced were: time-consuming, e.g., too many steps/click (70%); interoperability, e.g., difficulty sharing information across institutions or other EMR software (45%); data entry issues, e.g., difficulty entering clinical information, scheduling patient visits and reminders, or ordering multiple labs (38%); and poor workflow support (31%). The most useful aspects/features of their EMR software reported were availability of information, e.g., preloaded protocols, chemotherapy regimens and pathways (64%); data access (64%); and multiple access points, including remote access (37%). Conclusions: Satisfaction with EMR were generally positive among the mO/H surveyed. However, there are multiple deterrents to the efficient use of current EMR systems. This information is essential in the design of next-generation EMR (an Intelligent Medical Records system) to allow for incorporation of aspects most useful to the end-users, such as pathway access, preloaded information on cancer management as well as ease of access and portability, and a user experience that minimizes clicks and reduces physician time with EMR.
Sentiment analysis of tweets on prior authorization.
Authors: Prasanna Shivika , Premnath Naveen , Angraal Suveen , Sedhom Ramy , Khera Rohan , Parsons Helen , Hussaini Syed , Johnson Pamela T , Lou Emil , Beg Muhammad Shaalan , Subbiah Ishwaria Mohan , Rao Praveen , Gupta Arjun 
Published: September 2021

322 Background: Natural language processing (NLP) algorithms can be leveraged to better understand prevailing themes in healthcare conversations. Sentiment analysis, an NLP technique to analyze and interpret sentiments from text, has been validated on Twitter in tracking natural disasters and disease outbreaks. To establish its role in healthcare discourse, we sought to explore the feasibility and accuracy of sentiment analysis on Twitter posts (‘’tweets’’) related to prior authorizations (PAs), a common occurrence in oncology built to curb payer-concerns about costs of cancer care, but which can obstruct timely and appropriate care and increase administrative burden and clinician frustration. Methods: We identified tweets related to PAs between 03/09/2021-04/29/2021 using pre-specified keywords [e.g., #priorauth etc.] and used Twarc, a command-line tool and Python library for archiving Twitter JavaScript Object Notation data. We performed sentiment analysis using two NLP models: (1) TextBlob (trained on movie reviews); and (2) VADER (trained on social media). These models provide results as polarity, a score between 0-1, and a sentiment as ‘’positive’’ (>0), ‘’neutral’’ (exactly 0), or ‘’negative’’ (<0). We (AG, NP) manually reviewed all tweets to give the ground truth (human interpretation of reality) including a notation for sarcasm since models are not trained to detect sarcasm. We calculated the precision (positive predictive value), recall (sensitivity), and the F1-Score (measure of accuracy, range 0-1, 0=failure, 1=perfect) for the models vs. the ground truth. Results: After preprocessing, 964 tweets (mean 137/ week) met our inclusion criteria for sentiment analysis. The two existing NLP models labeled 42.4%- 43.3% tweets as positive, as compared to the ground truth (5.6% tweets positive). F-1 scores of models across labels ranged from 0.18-0.54. We noted sarcasm in 2.8% of tweets. Detailed results in Table. Conclusions: We demonstrate the feasibility of performing sentiment analysis on a topic of high interest within clinical oncology and the deficiency of existing NLP models to capture sentiment within oncologic Twitter discourse. Ongoing iterations of this work further train these models through better identification of the tweeter (patient vs. health care worker) and other analytics from shared content.[Table: see text]