bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visualizing treatment patterns and survival in metastatic breast cancer.
Authors: Gilbert Aidan , Williams Courtney , Kandhare Pravinkumar , Nakhmani Arie , Meersman Stephen C. , Garrett-Mayer Elizabeth , Kaltenbaugh Melinda , Azuero Andres , Ingram Stacey A. , Burkard Mark E. , Bhatia Smita , Kenzik Kelly , Rocque Gabrielle Betty 
Published: October 2019

316 Background: Optimal treatment sequencing (i.e., the order in which drugs are given) for metastatic breast cancer (MBC) is unknown. We aimed to develop an approach to visualize treatment patterns and survival in MBC. Methods: This retrospective study utilized ASCO’s CancerLinQ Discovery® database generated from electronic health records. Subjects included 3,312 women aged ≥18 years who were diagnosed with and received treatment for MBC after 1980. Hormone receptor (HR) status was determined by concordant diagnosis and treatment records. Human epidermal growth factor (HER2) status was determined by delivery of HER2-targeted therapy. Ordered and administered treatments were included. We created spatiotemporal plots of treatment patterns for HR+/HER2-, HER2+, and triple negative (TN) MBC. Individuals were represented on the Y-axis, and time on the X-axis with development of MBC aligned at time 0. Treatment classes were identified by colors: hormone therapies in shades of red, chemotherapies in shades of blue, HER2-targeted therapies in shades of green, and novel therapies in shades of orange. Concurrent treatments were represented by split bars. An overlaid Kaplan-Meier curve allowed for observations about the relationship between survival and treatment. Results: We developed a novel visualization approach to simultaneously display heterogeneous, longitudinal treatments and survival. Median survival after first documentation of MBC was 3.1 (IQR 1.4-7.2), 1.3 (IQR 0.6-2.8), and 2.6 (IQR 1.0-5.2) years for HR+/HER2-, TN, and HER2+ MBC, respectively. Patients with longer survival often had long duration of initial therapy, suggesting a more indolent or responsive disease. Substantial heterogeneity in treatment sequencing was observed for HR+HER2- and TN cohorts. In the HER2+ cohort, HER2-targeted therapy was commonly administered for the duration of treatment with more homogeneous sequencing. Conclusions: This novel visualization approach allows for observing the relationship between treatment patterns and survival, which is challenging to demonstrate with traditional quantitative methods. This approach can generate hypotheses regarding impact of treatment patterns on survival.
Utilizing visualization to qualitatively evaluate electronic health record-derived database limitations.
Authors: Gilbert Aidan , Kandhare Pravinkumar , Nakhmani Arie , Meersman Stephen C. , Garrett-Mayer Elizabeth , Kaltenbaugh Melinda , Burkard Mark E. , Williams Courtney , Azuero Andres , Bhatia Smita , Kenzik Kelly , Rocque Gabrielle Betty 
Published: October 2019

317 Background: Electronic health record (EHR) databases are a promising platform for clinical research using real-world data. However, information on potential limitations of these data sources is lacking. We sought to understand how data visualization might be used to identify data inconsistencies and the applicability of previously validated claims-based algorithms used to identify patients with metastatic breast cancer (MBC). Methods: This retrospective study utilized ASCO’s CancerLinQ Discovery database derived from EHR data. Subjects included women ≥18 years treated for MBC diagnosed ≥1980. Subjects with MBC were identified using two billing codes for metastasis on separate dates following primary breast cancer diagnosis. Treatment course sequences were visualized. Patients were represented by a horizontal bar on the Y-axis. Treatments were displayed using colored bars (blue: chemotherapy, red: endocrine therapy, green: HER2 targeted, orange: novel therapy) with time of treatment on the X-axis. Visualizations were qualitatively evaluated, and treatment patterns inconsistent with clinical practice were identified. Results: We identified 4,760 women treated for MBC using billing codes for primary breast cancer diagnosis and distant metastasis. Most patients (96%) had a primary breast cancer diagnosed in 2000 later. Treatment patterns inconsistent with clinical practice identified using the visualization technique included: 1% of patients received adjuvant chemotherapy continuously for ≥1.5 years, suggesting missed coding for metastatic disease; 5% of patients did not receive any treatment in the year following metastasis, suggesting the billing code may have been used in workup and not for confirmed metastatic disease. Among patients with MBC, 50% identified as HR+ across all records had not received hormone therapy, while 39% identified as HR- across all records received hormone therapy. Conclusions: Because previously validated algorithms may not translate well to EHR databases, quality auditing should always be performed. The proposed data visualization can be used for improving algorithms, qualitatively identifying errors, and avoiding biased or inaccurate results.
An NLP tool to identify molecular diagnostic testing in veterans with stage IV NSCLC.
Authors: Lynch Julie Ann , Kelley Michael J. , Lee Kyung Min , Hung Anna , Li Yanhong , Hintze Bradley J , Pendergraft Trudy , Pavilack Melissa , Efimova Olga , DuVall Scott L , Reed Shelby D. 
Published: October 2019

318 Background: ASCO Quality Oncology Practice Initiative (QOPI) encourages hospitals to determine if patients (pts) with stage IV NSCLC adenocarcinoma have activating EGFR mutations. Guidelines recommend tumor testing to identify ALK, BRAF, EGFR, ROS1 and other gene alterations before treatment. Studies have shown EGFR testing underutilization. We developed and tested a tool to identify EGFR tests in Veterans Affairs (VA) electronic health record (EHR). We examined whether Veterans with newly diagnosed NSCLC-IV underwent EGFR testing. We measured EGFR testing trends and analyzed differences by patient, VA Medical Center (VAMC) and region. Methods: VA EHR data identified Veterans with NSCLC-IV diagnosed 2013-2017, who survived 45+ days and had 2+ visits with a VA oncologist within 120 days of diagnosis. All NSCLC histologies were included. Demographics and VAMC were obtained from VA Corporate Data Warehouse. EGFR testing results performed outside VA were from commercial laboratory data. We deployed a natural language processing (NLP) tool to identify EGFR tests in VA EHR clinical notes. Testing rates and characteristics associated with testing were examined by descriptive analysis. Results: Of 3484 pts, 623 (18%) had evidence of EGFR testing. There was a 244% rise in testing. 54 (9%) pts diagnosed in 2013 were tested vs 186 (25%) diagnosed in 2017 ( χ2 82.3, p-value 0.00). No statistically significant differences by sex, race, or urban/rural address existed. Testing decreased as pts aged ( χ2 27, p-value 0.00). 35% of pts age ≤49 and 12% of pts age ≥80 were tested. Testing varied widely by VAMC and region (VAMC χ2 795.6, p-value 0.00; region χ2 90.3, p-value 0.00). 28% of pts in the Pacific were tested vs 10% of pts in the Southeast. The main contributor to regional variation was VAMC differences. VAMCs that conducted EGFR testing within their own laboratories (64% and 53%), or were co-located with the national precision oncology program (NPOP, 59%) tested the most pts. NPOP was temporally associated with increased testing nationally. 9% of pts diagnosed in 2017 were tested using NPOP. Conclusions: EGFR testing underutilization in the VA persists. QOPI and the NLP tool for this initiative will help system-wide quality improvement initiatives.
Enhancing community capacity to deliver value-based cancer care at the end-of-life.
Authors: Patel Manali I. , Ramirez David , Agajanian Richy , Agajanian Hilda H. , Coker Tumaini 
Published: October 2019

4 Background: To improve value-based cancer care, we designed an intervention using lay health workers (LHWs) who we trained to assess patient's symptoms. LHWs referred patients to palliative care and/or behavioral health in response to positive assessments. We implemented the intervention in collaboration with a community oncology group and a Medicare Advantage payer for patients with all stages of cancer. At ASCO 2019 we demonstrated the associated reductions in patient-reported symptoms, acute care use, and total costs of care. This study evaluates the effect of the intervention on end-of-life cancer care, specifically healthcare use in the last month of life and total costs of care from diagnosis until death. Methods: We enrolled all newly diagnosed health plan beneficiaries with solid and hematologic malignancies from 11/2016 through 9/2018 and compared outcomes to all patients diagnosed with cancer in the year prior to the intervention (control arm). For all patients who died within 12-months follow-up, we compared risk of death using Cox Models and generalized linear regression to compare healthcare use in the last month of life, and total costs of care from diagnosis until death. All models were adjusted for age, stage, comorbidities, diagnosis, and length of follow-up. Results: 180 patients in the intervention and 156 in the control died during the study. In both groups, the mean age was 80 years; 49% were non-Hispanic White, 40% Hispanic, 5% Asian/Pacific Islander, and 4% black. There were no differences in survival (HR 0.96, p = 0.6). Intervention patients as compared to the control had lower mean inpatient admissions (0.3 +/- 0.04 versus 0.5 +/- 0.07, p = 0.02) and emergency department visits per thousand members per year (0.11 +/- 0.02 versus 0.49 +/- 0.06, p < 0.001) in the last month of life, greater proportion of patients with hospice use (69% versus 48%, p < 0.001), lower proportion of patients with acute care facility deaths (37.5% versus 62.5%, p = 0.02) and lower median total healthcare costs from diagnosis until death ($24,902 versus $33,145, p = 0.02). Conclusions: An LHW intervention significantly improved the value of end-of-life cancer care and may be a solution to improve burdensome and costly care for patients.
Trends in the use of novel hormonal agents at the end of life in metastatic castration-resistant prostate cancer.
Authors: Hu Jason , Aprikian Armen G. , Vanhuyse Marie , Dragomir Alice 
Published: October 2019

40 Background: The approval of novel hormonal agents (NHAs), abiraterone and enzalutamide, have increased the therapeutic arsenal available in metastatic castration-resistant prostate cancer (mCRPC). However, the use of chemotherapy and other antineoplastics at the end of life has been suggested as an indicator of poor quality of care. In this study, we report the use of NHAs at the end of life in men with mCRPC in the province of Quebec, Canada. Methods: Using Quebec public healthcare administrative databases, we identified patients with prostate cancer who used an NHA (abiraterone or enzalutamide) after androgen deprivation therapy and who died between 2012 and 2016. The primary outcome was the use of an NHA in the 30 days before death. Use of an NHA in the 60 and 90 days before dying, and initiation (first prescription) of an NHA in the 30 days before death were evaluated as secondary outcomes. Multivariable analysis of the primary outcome was performed with logistic regression with results reported as odds ratios (OR) with 95% confidence intervals (95%CI). Results: The cohort consists of 1316 patients who used an NHA over the course of their disease and died at a median age of 78 years old, with 292 (22.2%), 464 (35.3%), and 575 (43.7%) having used an NHA in the 30, 60 and 90 days of life, respectively. Use of NHA 30 days before dying decreased over the study period, from 44.8% in 2012 to 17.0% in 2016 (Cochran-Armitage test p-value < 0.001). On multivariable analyses, later years of death remained associated with lower odds of NHA use 30 days before death (OR 0.74, 95%CI 0.66 to 0.81, p < 0.001). Fifty-eight (4.4%) patients initiated a NHA 30 days before dying. Conclusions: Rates of NHA use 30 days before dying were high initially but decreased over the study period. Further assessment of NHA use at the end of life is warranted to examine if the trend will be maintained given the recent approval of additional oral NHAs for prostate cancer.
Primary care providers propensity to order non-recommended surveillance testing after curative breast cancer treatment.
Authors: Wallner Lauren P. , Abrahamse Paul , Radhakrishnan Archana , Hamilton Ann S. , Ward Kevin C. , Hawley Sarah T. , Katz Steven J. 
Published: October 2019

52 Background: Team-based cancer care models promote primary care providers taking on a larger role in survivorship care. However, little is known about PCP attitudes toward and propensity to order non-recommended surveillance testing. Methods: A stratified random sample of PCPs identified by early-stage breast cancer patients diagnosed in 2013-15 who participated in iCanCare Study (Georgia and Los Angeles SEER registries) were surveyed about their experiences caring for cancer patients (N = 519, 58% response rate). PCPs were asked in a clinical vignette whether they would order non-recommended bone scans, other imaging (i.e. PET) or tumor marker testing (i.e. CA-125) in an asymptomatic, early-stage breast cancer survivor. A composite score was created by averaging their responses to the individual items, and categorized by tertiles into low, selective and high propensity to order non-recommended testing. PCP confidence in their knowledge about appropriate testing was also measured (5 pt. Likert-type scale; not all all-very confident) and compared with propensity to order. Multivariable, weighted, multinomial logistic regression was used to then evaluate PCP-reported factors associated with high and selective propensity to order non-recommended testing (vs. low). Results: In this sample, 32% of PCPs had a low propensity, 40% selective, and 28% a high propensity to order non-recommended surveillance tests. Of the 80% of PCPs who reported they were confident in their knowledge about appropriate testing, 27% had a high propensity to order. PCPs practicing in staff-model HMOs were less likely to have a high or selective propensity to order (vs. low) when compared to PCPs in private practice. (high aOR: 0.4, 95%CI: 0.2-0.7; selective aOR: 0.3, 95%CI: 0.2-0.6). Conclusions: Over a quarter of PCPs had a high propensity to order non-recommended surveillance testing for early-stage breast cancer patients, yet the majority reported they were confident in their knowledge about appropriate surveillance testing. Efforts to increase PCP knowledge about the specifics of breast cancer surveillance may be warranted to reduce the overuse of non-recommended testing during survivorship.
Improving lung cancer screening in the HIV population.
Authors: Galeas Jose Nahun , Grossberg Robert M. , Serrano Maria , Shmukler Anna , Sakalian Susan , Mehta Vikas , Halmos Balazs , Packer Stuart H. 
Published: October 2019

69 Background: Lung cancer screening for high risk populations has a major impact in reducing mortality.In our population, HIV patients are younger (mean age 68.0 vs 56.8, p= 0.014) and have a higher percentage of advanced disease at diagnosis (49% vs 68%, p< 0.001),when compared to non-HIV lung cancer patients.Due to this increased risk and aggressiveness, we embarked on a quality improvement initiative to increase screening in our HIV smoking population. Methods: Data was collected retrospectively from 10/18 to 1/19 in the HIV clinic. A multidisciplinary team was created involving thoracic oncologists, radiologists and HIV physicians to discuss methods to improve screening. We identified areas to be improved and utilized performance improvement tools such as a Pareto chart and PICK chart. Data was then collected prospectively. Results: In the initial 4 month period,among HIV positive patients 55–77 years old with significant smoking history, 13% (total n=54) of patients had a chest CT done for lung cancer screening and only 3.7% were referred for lung cancer screening during that specific period. Main barriers were lack of proper identification of screening candidates, discrepancies in smoking history within the EMR and lack of a consistent system for referral. An algorithm was created in the referral workflow, in which providers would need only to identify patients in the age group of 55-77 years old with any history of smoking and refer to a lung cancer screening program. The screening program would contact the patient and screen as per CMS guidelines. 17 Patients were referred from the HIV clinic from 4/8/19 to 5/2/19. Of these patients, 29% had a lung cancer screening CT scan done or scheduled, 18% of patients did not qualify for screening,and the remaining 53% of referrals are pending to be screened by telephone call. Further data on subsequent PDSAs and results of screening scans will be presented at the meeting. Conclusions: Modifying the screening algorithm for lung cancer in our HIV clinic by adding support from a dedicated screening program increased screening rates by 25% in the first month of intervention. Subsequent interventions include: patient education to reduce the stigma of lung cancer and EMR alerts when a patient meets criteria for screening.
ASCO Quality Training Program: Five-year review.
Authors: Keng Michael Kenneth , Cunningham Gene , Gilmore Terry , Gilligan Timothy D. , Quinn Doris , Kaufman Laura , Bingham John , Guerrier Vedner , Chiang Anne C. , Mohamed Ashraf Mahmoud , Hagemann Jordan 
Published: October 2019

7 Background: ASCO introduced a Quality Training Program (QTP) in 2013 with an aim: train oncology professionals to design, implement and lead successful quality improvement (QI) activities and assume leadership positions to champion culture change in their practices. Methods: The QTP is a formal 6-month program taught by QI faculty and mentored by QI coaches over five days of in-person learning across three sessions, and hands-on learning at the participants’ practices. Sessions include seminars, case examples, and small group exercises. Participants attend in multi-disciplinary teams and focus on a problem they wish to solve in their practice. Scheduled conference calls with QI coaches were held between sessions. Participants complete pre and post QTP surveys (10 point Likert scale; 1 - no knowledge/competence to 10 - complete knowledge/competence) and provide direct written feedback. Results: Since its inception, QTP has had 15 courses (10 domestic and 5 international) with 120 teams and 544 total participants. QTP is led by an 8-member steering group with 16 faculty and coaches. All post-survey items had an increase in knowledge and competence. Each item’s score was calculated as the mean difference between ‘before’ and ‘after’ score. Participants stated increase of 46% to 84%: overall mean increase for knowledge 38% and competence 37%. The greatest increase were: methodology and practical tools to make changes in practice (writing an aim statement, implementing rapid improvement, process analysis tools, and flowcharting the process). Most common suggestion for improvement was allowing more time for the project. Participants are encouraged to write articles and present work in poster and plenary sessions. QTP have led to 7 manuscripts and 21 abstract presentations to national meetings. Six QTP alumni currently are now QI coaches and faculty. Conclusions: The QTP is a successful QI course for oncology professionals who need to measure performance, investigate quality and safety issues, and implement change. It is the only oncology-focused QI training, as all faculty and coaches are providers and QI specialists with oncology experience, making this a unique opportunity. The success will provide further momentum to offer QTP domestically and around the world.
Impact of a student pharmacist-directed pilot intervention on influenza vaccination documentation and administration rates in older adults receiving parenteral anticancer therapy.
Authors: Kim E. Bridget , Zangardi Mark , Rostamnjad Leila , Nipp Ryan David , Bartholomay Mimi , White Laura , Blouin Gayle C. 
Published: October 2019

71 Background: Annual influenza vaccination is recommended for individuals 6 months and older. Older adults are at high-risk of developing influenza and complications associated with the virus. However, < 50% of patients with cancer receive the influenza vaccine annually. In previous work at our institution, a quality improvement project identified that only 40% of adult patients initiating parenteral anticancer therapy between September and December 2017 were documented to have received the influenza vaccine. Therefore, a multidisciplinary student pharmacist-directed pilot intervention was developed to improve influenza vaccine documentation and administration rates, and we sought to investigate the impact of this intervention. Methods: All adult patients (≥65 years old) scheduled for parenteral anticancer therapy during November 2018 were screened for influenza vaccination documentation. Patients were identified by reviewing infusion center schedule. Under supervision of board-certified oncology pharmacists, two student pharmacists evaluated influenza vaccination documentation in the institution/network electronic medical record (EMR) and outside records. Patients with unknown vaccination history were identified for interview by pharmacy students. The student pharmacists collaborated with oncology nurses and clinicians to order and administer influenza vaccine to patients who agreed to vaccination. Influenza vaccination status was updated in the EMR following record reviews/interviews. Results: Student pharmacists screened 617 patient EMRs and interviewed 124 patients to verify vaccination status. Furthermore, 33 patients received influenza vaccination as a direct result of student pharmacist intervention. Overall, rate of influenza vaccination status documentation was 60.5%. Conclusions: Compared with historic data, we found promising results for a student pharmacist-directed pilot intervention, which demonstrated the potential to improve influenza vaccination status documentation and administration among older adults receiving parenteral anticancer therapy.