bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cancer ontology understanding among community oncologists: Insights from a survey linked to implementation of mCODE-informed electronic health record (EHR).
Authors: Dienstmann Rodrigo , Christtanini Koyama Fernanda , Costa e Silva Matheus , Mega Livia , Laloni Mariana , Ferreira Carlos G. M. , Ferrari Bruno Lemos 
Published: June 2023

e18860 Background: Real-world data (RWD) will help recognize the gaps between evidence and practice, re-shaping clinical assessments. Data collected at the source in oncology-tailored EHRs are expected to facilitate generation of high-quality RWD. In the process of implementing a new EHR informed by mCODE standards in our network of oncology clinics, we defined mandatory variables amenable to structured data capture. However, medical knowledge about cancer ontology has not been methodically investigated. Methods: Online survey with 4 multiple-choice questions that illustrate in clinical cases the most important concepts and terminologies related to cancer diagnosis, treatment, and patient outcome. The questionnaire was shared with ~ 300 medical oncologists from our institution through mobile messaging app in December 2022. Physicians signed electronic informed consent for anonymized data analysis. Results: In total, 203 oncologists agreed to participate and 152 completed the survey. Most oncologists (75%) correctly define “therapy intent” (palliative versus curative) and corresponding “treatment line”. Many (51%) do not understand that “disease stage” is static (defined at the time of diagnosis) and does not change to stage IV if patient presents with relapsed/recurrent disease. A significant proportion of oncologists (66%) wrongly define “response status” to a given therapy as stable/progressive disease in a patient that had major clinical/radiological response but presents with unconfirmed tumor marker increase and no clear change in bone metastases by imaging. However, most oncologists (88%) can correctly define “reason for therapy discontinuation” as “planned interruption” in the end of adjuvant chemo-immunotherapy. When stratifying physicians according to self-defined knowledge of disease ontology, we found that 27% of those with moderate/deep understanding of mCODE scored 4 correct answers in the questionnaire as compared to 8% with 4 correct answers if mCODE knowledge was null or vague (P value < 0.001, odds ratio 5.1, CI95% 1.8-15.8). Conclusions: Overall understanding of cancer-specific data dictionaries is low among community oncologists. With the new EHR system we are nudging physicians not to update the “stage at diagnosis” status at the time of disease relapse/recurrence by creating a “current cancer status” element with mandatory completion (linked to prescriptions/ pharmacy claims). Also, “response status” as assessed by physicians must be cross-checked with other data sources (tumor markers, imaging results, physician notes and reason for therapy discontinuation) given inconsistent definition of “clinical benefit versus progressive disease” among physicians. In addition, we will constantly educate oncologists and monitor their EHR data entry behavior for successful execution of RWD projects.
Real-world experience of checkpoint inhibitors across India: CRSF 2020-01.
Authors: Goyal Gautam , Chandrasekharan Arun , Avaronnan Manuprasad , Talreja Vikas , Bhosale Bharatsinha Baburao , Kothari Rushabh , Mondal Tanmoy , Pande Nikhil , Talele Avinash , Poladia Bhavesh Pradip , Agarwala Vivek , Karpe Ashay 
Published: June 2023

e18862 Background: There are limited data available from India on the real-world use of checkpoint inhibitors. Hence we did this analysis across India to study the pattern of use and outcomes with checkpoint inhibitors. Methods: This was a retrospective multicentric protocol. Patients who received immunotherapy from January 2016 to October 2021 were included. The baseline demographic, previous treatment, response, date of progression, date of death and status were noted. SPSS version 20 was used for analysis. Descriptive statistics were performed. Kaplan Meier method was used for estimation of progression-free survival (PFS) and overall survival (OS). COX regression model was used to identify factors impacting OS. Results: We identified 308 patients in the study. The median age was 58.5 years (Interquartile range 51-66 years) and there was a male preponderance (249, 80.8%). The 3 commonest sites of use were head and neck cancer in 144 patients (46.8%), lung cancer in 81 (26.3%) and renal cell carcinoma in 31(10.1) patients. The ECOG PS was 0-1 in 215 (70%), 2 in 71 (23.1), 3-4 in 21(6.8%) and not documented in 1(0.3%) patient. The two most common checkpoint inhibitors used were nivolumab and pembrolizumab 255 (82.8%) and 37(12%) patients respectively. These were used in curative setting in 6 patients (1.9%) and palliative in rest all. 43(14%) patients received them as first-line in, 129 (41.9) as second-line and beyond the second line in 130 (42.2%) patients. The response rate was 24% (n = 74). The median PFS was 4.067 (95%CI 3.45-4.67) and the median OS was 10.0 months (95%CI 6.2-13.8). Among the factors tested for impact on OS the ECOG PS 0-1 ( HR-0.493 95%CI 0.324-0.749; P = 0.001), non head and neck site of the disease (HR-2.134 95%CI 1.164-3.911) and reception of immunotherapy in first line setting (HR -0.533 95%CI 0.295-0.963: P = 0.037) had an favorable impact on OS. Conclusions: Checkpoint inhibitors provide similar efficacy as those seen in pivotal studies in real-world settings.
Development of a multiphase patient-reported outcomes dashboard to support population health and drive quality improvement in ambulatory oncology.
Authors: Zhang Sunyi , Manni Michael , Whittaker Sarah , Barwick Paige , Finn Brian , Schindler Mary , Verzino Gabe , Sirohi Niren , Johnson Jason , Haakenstad Ellana K , Lakhani Hakim , Hassett Michael J. , McCleary Nadine Jackson 
Published: June 2023

e18864 Background: The Patient Reported Data (PRD) Program at Dana-Farber Cancer Institute (DFCI) has implemented a portfolio of electronic questionnaires including patient-reported outcome measures (PROMs) and risk screeners in routine practice. Over 141,906 questionnaires have been completed by over 60,158 patients across solid tumor, liquid tumor, and supportive care (see table). We are now prepared to share this data internally in an accessible and actionable format via the development of an Outcomes Dashboard. Methods: PRD and the DFCI Clinical Operations & Business Analytics team created a roadmap for iterative dashboards to be developed with Tableau 2022.1, a business analytics platform. The development team included a business analyst, data scientist, and content experts. The goal of our roadmap was to balance rapid delivery of data with the resources needed to develop more complex dashboards incorporating PRD with other data. The Outcomes Dashboard roadmap consists of four phases. Phase 1 focuses on creating a core dashboard and displaying aggregate PROMs-derived scores and risk scores with filters and stratification by patient demographics and clinical encounter data. Phase 2 adds clinical outcomes data including hospitalizations and treatment adherence. Phase 3 adds non-scored questionnaire data such as social determinants of health. Phase 4 incorporates oncology treatment data including treatment route, goals, class, and other characteristics. Results: Data was generated using Microsoft SQL Server Management Studio and loaded into Tableau to create visualizations with data refreshed daily. Dashboard Phase 1 is complete and will be released in spring 2023. Dashboard users will include executive leaders, operations, clinicians, and others. The dashboard will be used to identify differences and disparities in care delivery and outcomes by disease type, treatment, and other characteristics; highlight opportunities for interventions to improve quality and care delivery; identify areas for future research; and help fulfill emerging regulatory requirements. Conclusions: By making aggregate PRD and associated outcomes available in an accessible format, we aim to drive quality improvement and enable population health management. Future efforts will include educating users, assessing uptake of the dashboard, and partnering with stakeholders to develop clinical interventions to improve outcomes. [Table: see text]
Real-world clinical outcomes in patients (pts) with HR+/HER2- metastatic breast cancer (mBC) treated with chemotherapy (CT) in the United States (US).
Authors: Tolaney Sara M. , Punie Kevin , Kurian Allison W. , Ntalla Ioanna , Verret Wendy , Sadetsky Natalia , Sjekloca Nikoleta , Stokes Michael , Jhaveri Komal L. 
Published: June 2023

e18871 Background: HR+/HER2- mBC remains incurable, despite progress made with endocrine therapy (ET) + CDK4/6i in prolonging survival. After resistance to ET-based treatment, options are limited to CT and a decrease in survival is observed with every subsequent line of treatment received. This study describes real-world outcomes in pts with HR+/HER2- mBC initiating CT or previously treated with CT in the US. Methods: This retrospective, observational cohort study used the ConcertAI Patient360™ curated dataset of electronic medical record data from the US. Pts (≥18 years) diagnosed with HR+/HER2- mBC and initiating their first CT from January 2011 to June 2021 were included. Real-world outcomes were assessed for all pts who initiated treatment with a first CT, and those who were subsequently treated with a second, third, and fourth CT. Index date was defined as the CT start date of each systemic therapy line. Results: In total, 1545 pts met the eligibility criteria and were included for analysis. Pts were primarily female (99%) and White (76%); median age was 61 years (IQR, 52-69) and 68% had visceral metastases. Most pts (80%) were treated in a community setting and 41% received their first CT in 1L; 58% and 44% had prior exposure to ET and CDK4/6i in the mBC setting, respectively. The median time from mBC diagnosis to first CT was 12 months (IQR, 1.4-30.8). Among all pts included, 57%, 31% and 17% were subsequently treated with a second, third, and fourth CT, respectively, during the study period. Capecitabine and paclitaxel were the most used as the first (45% and 29%), second (35% and 30%), and third (25% and 22%) CT, while gemcitabine (22%) and eribulin (20%) were used most as fourth CT. Clinical outcomes assessed are summarized in the table. Median real-world overall survival (rwOS; 95% CI) from time of mBC diagnosis was 48.5 months (45.5-51.5). Median rwOS from first CT treatment start date was 23.3 months (21.3-25.4). In pretreated pts with 1, 2, or 3 prior lines of CT, median rwOS from each index date was 16.5 months (14.8-18.3), 11.8 months (10.4-13.1), and 9.1 months (7.3-11.2), respectively. Conclusions: Among pts with HR+/HER2- mBC in this analysis, CT choice and real-world clinical outcomes per systemic therapy line were comparable to existing literature. Outcomes decreased as pts advanced CT lines, indicating that in this setting the unmet need remains high. More efficacious treatment options are needed for ET-resistant, chemo-naïve pts and pts pretreated with CT with HR+/HER2- mBC. [Table: see text]
Navigating how to choose an oncologist as part of the cancer journey.
Authors: Francis Ann , Teschner Taylor , Warde Prem R. , Johlie Melissa , Buthe Lynn , Johnson Kjel Andrew 
Published: June 2023

e18877 Background: Being diagnosed with cancer and having to navigate what to do next is overwhelming. One of the initial actions that needs to be taken is choosing an oncologist. It is essential that each patient finds an oncologist they trust and who will work with them through their diagnosis and treatment. CVS Health conducted this study to gain insight into 1) how cancer patients select an oncologist and what factors weigh into choosing an oncologist and 2) treatment cost concerns. Methods: In August 2022, we conducted an online survey with consumers selected from a national online panel. Patients (n = 126) were included if they had cancer, employer health insurance and currently undergoing or having completed chemotherapy infusion, oral chemotherapy, hormone therapy or immunotherapy. Patients answered a series of questions designed to understand how they selected their oncologist. Descriptive statistics and percentages are reported. Results: Oncology diagnoses included breast (48%), colon or rectal (8%), leukemia (8%), melanoma (7%), basal cell (6%), ovarian (6%), endometrial (6%), testicular (6%), prostate (5%), lung (4%) and < 3% of other cancers (patients could choose multiple diagnoses). Most (79%) patients completed treatment; 75% received or were receiving chemotherapy infusion, 63% surgery, 60% radiation therapy, 29% hormone therapy and 22% oral chemotherapy. 68% of patients responded that someone suggested/referred them to their oncologist. Of these patients, 43% stated a specialist (other than an oncologist) referred them to their oncologist, 34% said their primary care physician (PCP) referred them, while hospital/treatment center, family member/friend, insurance company and other made up the rest. 38% of respondents received a second opinion. Most (89%) patients remained with the same oncologist throughout their treatment. When selecting an oncologist, most patients identified experience (93%), being a respected oncologist (90%), reputation (86%), being in network (77%), quality measures (74%) and treatment recommendations (73%) as “Very Important” factors when choosing an oncologist. 38% of patients began to worry about medical bills when diagnosed; however, 30% were never concerned. Over half (56%) of patients reported treatment cost as the most concerning bill. 82% of patients reached their deductible during treatment, with half (54%) expecting to hit their deductible less than 3 months into treatment. 75% of respondents reported hitting their out-of-pocket maximum; 39% hit it less than 3 months into treatment. Conclusions: Specialists and PCPs are integral in referring patients to oncologists. While patients are less likely to choose their oncologists directly, they report that experience, reputation, and quality of care are essential qualities in an oncologist. Cost was not an important factor when choosing an oncologist, however, patients are concerned with medical bills, specifically treatment costs.
Clinical factors associated with prescribing patterns of bone modifying agents in men with metastatic castration-resistant prostate cancer.
Authors: Kobe Christopher , Nguyen Charles B. , Kumbier Kyle E. , Bauman Jordan , Burns Jennifer A. , Tsao Phoebe A. , Sparks Jordan B. , Caram Megan Veresh 
Published: June 2023

e18878 Background: Bone metastases occur in up to 90% of men with metastatic prostate cancer and cause skeletal-related events (SREs) such as fracture and spinal cord compression. Although bone modifying agents (BMAs) have been shown to decrease the risk of SREs in men with metastatic castration-resistant prostate cancer (mCRPC), BMAs are not widely used in this patient population. In this retrospective study, we report the prescribing patterns of BMAs and predictors of BMA use in a large national cohort. Methods: We used the VA corporate data warehouse to identify patients with mCRPC who were treated with first-line mCRPC therapy (abiraterone, enzalutamide, docetaxel, or ketoconazole) between 2010 and 2017. BMA prescribing frequency and patterns were analyzed. Multivariable regression analysis was used to evaluate clinical and disease-specific factors associated with BMA use which are presented as adjusted odds ratios (OR) with 95% confidence intervals (CI). Results: In the final cohort of 4,079 patients, the median age at mCRPC diagnosis was 73 years (IQR 66-81). 29% of patients in the cohort were Black. Diagnosis codes identified bone metastases at mCRPC diagnosis in 48% of the cohort (ICD-9 and 10 coding for sites of metastases are known to underestimate the actual incidence of metastases). Only 48% of patients received a BMA following initiation of treatment for mCRPC, 47% of which had already received a BMA 6 months prior to mCRPC diagnosis. For those who were new BMA starts, the median time to BMA administration from mCRPC treatment was 3.4 months (IQR 1.2-8.8). Factors associated with BMA use were having an ICD-9 or 10 diagnosis code for bone metastases at time of mCRPC treatment (OR 1.28, 95% CI 1.10-1.48), concurrent corticosteroid use (OR 1.90, 95% CI 1.53-2.38), and docetaxel use as first-line mCRPC therapy (OR 1.78, 95% CI 1.45-2.18). Factors associated with decreased BMA use were Charlson comorbidity index score of ≥ 2 (OR 0.75, 95% CI 0.62-0.90), advancing age (OR 0.86 per 10 years, 95% CI 0.79-0.94), and decreased eGFR (eGFR 30-59, OR 0.81, 95% CI 0.68-0.96; eGFR 0-29, OR 0.23, 95% CI 0.14-0.37). Having a diagnosis code for a SRE before mCRPC diagnosis (e.g., bone fracture and cord compression) did not impact BMA use, but the incidence of those events was low. Conclusions: Less than half of this VA cohort received a BMA after starting therapy for mCRPC. Key factors associated with BMA use were corticosteroid use and first-line docetaxel use, which likely represented more aggressive disease. Notably, patients who were older and had more comorbid conditions were less likely to receive a BMA despite being highest risk for frailty and SREs. Future quality improvement efforts aimed at increasing BMA use may address the needs of the geriatric mCRPC patient population.
Real-world outcomes in patients (pts) with metastatic triple-negative breast cancer (mTNBC) treated with sacituzumab govitecan (SG) in 2L+ in the United States (US).
Authors: Kalinsky Kevin , Spring Laura , Yam Clinton , Taylor Aliki , Sjekloca Nikoleta , Kaushiva Alpana , Lai Catherine , Ntalla Ioanna , Nanda Rita 
Published: June 2023

e18879 Background: Pts with mTNBC have poor prognosis and limited treatment options. SG is an anti—Trop-2 antibody-drug conjugate approved in multiple countries for pts with mTNBC who received at least 1 prior systemic therapy and in the US for pts with pretreated HR+/HER2- mBC. In the pivotal phase 3 ASCENT study (NCT02574455), SG demonstrated superior efficacy over single-agent chemotherapy and a manageable safety profile in pts with mTNBCardia A, et al. NEJM. 2021). This study is, to our knowledge, the first to describe real-world treatment patterns and dosing with SG and its impact on clinical outcomes in pts with mTNBC in the US. Methods: This retrospective, observational cohort study used the ConcertAI Patient360™ dataset with additional curated electronic medical record data from the US. Pts (≥18 years) diagnosed with mTNBC as defined according to the current American Society of Clinical Oncology/College of American Pathologists guidelines (HER2 IHC0, 1, or 2/ISH-negative; ER/PR <1%) and initiating treatment with SG (index date) in 2L+ from April 2020 to May 2022 were included. Real-world clinical outcomes with SG and use patterns were assessed. Kaplan-Meier method was used to determine real-world overall survival (rwOS). Results: In total, 230 pts met the eligibility criteria and were included for analysis. All pts were female; 64% were White and 26% Black; median age was 60 years (IQR, 49-69); 71% of pts presented with ECOG performance status ≤1; 71% had visceral metastases and 7% had brain metastases at baseline. The median time from mBC diagnosis to SG treatment initiation was 11.8 months (IQR, 7.6-19.2). Most pts (66%) were treated in a community setting; 34%, 28%, 19%, and 20% of pts were treated with SG in the 2L, 3L, 4L, and 5L+ setting, respectively. Between 2020-2022, there was a trend in the distribution of SG use shifting to earlier line settings, see Table. Median starting dose was 10 mg/kg (IQR, 9.8-10.1). Median follow-up duration was 7.2 months (IQR, 3.9-11.1). Median rwOS (95% CI) from index date was 10 months (8.3-11.1) among all pts. Median rwOS (95% CI) was 13.9 months (9.79-not estimable) and 8.4 months (7.7-10.3) among pts treated with SG in 2L and in 3L+ setting, respectively. Analyses on real-world patterns of SG use are ongoing and additional results will be provided. Conclusions: Pts who were treated with SG in routine clinical practice were older, more ethnically diverse, and presented with worse performance status than pts enrolled in the ASCENT trial but demonstrated a similar survival benefit. The proportion of pts treated with 2L SG increased from 2020 to 2022, reflecting an expected dynamic of post approval drug uptake in routine practice. [Table: see text]
Factors that determine selection of a cancer treatment location.
Authors: Francis Ann , Teschner Taylor , Warde Prem R. , Johlie Melissa , Buthe Lynn , Johnson Kjel Andrew 
Published: June 2023

e18880 Background: Cancer patients, who are already overwhelmed by their diagnosis and other decisions that need to be made, are also confronted with decisions regarding treatment options. Understanding factors that influence a cancer patient’s decision to select a treatment location are needed to optimize treatment decision-making and avoid financial toxicity. This study aimed to gather feedback from cancer patients to understand what factors influence their decision to choose a cancer treatment location. Methods: We conducted an online cross-sectional survey of 126 current and former cancer patients. We asked what factors influenced their decision to select their current or former cancer treatment center. The survey was conducted in 2022; descriptive statistics and percentages are reported. Results: Most patients were White (87%), female (74%), college-educated (70%) and resided in the suburbs (57%); hypertension (32%) was the most common comorbidity. The most common cancers were breast (48%), followed by colon or rectal (8%) and leukemia (8%). Roughly half of the patients selected the location for screening (51%), while someone else selected locations for diagnosis and staging (63%), treatment plans (64%) and treatment (45%). Of those who indicated that someone else chose their screening, diagnosis and staging, treatment plan and treatment locations, most reported their oncologist decided the diagnosis and staging (57%), treatment plan (86%) and treatment locations (90%). The wait time to receive treatment (89%) and distance from home or work (86%) were the two most important factors when selecting a cancer treatment location. Over half (57%) of patients said they would be “very willing” or “somewhat willing” to change treatment locations for a $0 copay/coinsurance offer. However, only 38% of respondents would be willing to change locations for a $0 copay/coinsurance offer if it meant they would have to change oncologists. 48% of patients were willing to drive 41-100 miles to a treatment location for a $0 copay/coinsurance offer. 74% of patients received an infusion as part of treatment; over half (57%) preferred to receive the infusion in a suite at a cancer center/clinic. Conclusions: While primary care physicians and oncologists share almost equally in selecting screening locations, oncologists are most often responsible for recommending a treatment location for the other three steps (diagnosis and staging, treatment plan and treatment) in the cancer treatment journey. When offered a $0 copay/coinsurance program during treatment, patients were willing to change locations, highlighting the impact of cost on selecting a cancer treatment location. However, patients were less likely to change locations if that meant changing their oncologist, highlighting the importance of trust and comfort in one’s oncologist.