bluuebunny/crossref_metadata_2025_split huggingface dataset:
Remote patient monitoring using smart phone derived patient reported outcomes and Fitbit data to enable longitudinal predictive modeling in prostate cancer: Feasibility results and lessons on platform development.
Authors: Laccetti Andrew L. , Slack Tidwell Rebecca , Sheth Nipa P , Logothetis Christopher , VanAlstine Michael 
Published: May 2019

e18068 Background: Wearable activity trackers and frequent interrogation of remote patient reported outcomes (PROs) have the potential to revolutionize oncology clinical trial design, therapeutic sequencing and patient (pt) safety. Established feasibility and novel systems of data processing are necessary to substantiate value for these methods. Methods: Expanding upon our clinical research data platform, Prometheus, we have developed a HIPPA compliant, remote pt monitoring system capable of collecting minute-by-minute step count and heart rate (via Fitbit) in addition to smart phone derived symptom surveys. To pilot this program, a cohort of metastatic castration resistant prostate cancer (mCRPC) pts participated in continuous Fitbit monitoring and thrice weekly NCI-PRO-CTCAE survey for 26 weeks. Pre-specified interim feasibility results were examined with a focus on pt characteristics, treatment and compliance. Qualitative assessment of barriers to pt enrollment and device use was performed. Results: 15 mCRPC pts completed our pilot program: mean age 63.1 years (range 48-79), pre-treatment PSA 33.2 ng/mL (range 0.3 – 499.9), 80.0% stage M1b, ECOG 0 or 1. All pts were treated per protocol NCT02703623: abiraterone/prednisone/apalutamide for 8 weeks followed by continuation of therapy (5 pts), cabazitaxel/carboplatin (6 pts) or addition of ipilimumab (2 pts). 33.3% of pts reported grade 3 clinician interpreted adverse events. 14 pts had data available for compliance analysis. Mean Fitbit compliance was 62.6% (STD 35.5%) with rates trending down over the study duration (week 1 vs 26 = 86.7% vs 33.3%; p= 0.002; R2= 0.716). Mean smart phone derived NCI-PRO-CTCAE survey completion rate was 37.1%. Barriers to pt enrollment included slow Fitbit app download times, incompatible smart phones and the need for extensive device use education/counseling. Barriers to data collection were missed survey text prompts and inconsistent use of Bluetooth. Conclusions: MD Anderson’s novel, home-grown, remote pt monitoring platform, utilizing Fitbit and smart phone derived PROs, is feasible in function and pt use. Automated compliance checks, streamlined enrollment and pt education are critical to future application. This foundational work will facilitate longitudinal signal variation benchmarked against standard monitoring methods, ultimately aiming to improve outcomes and support of discovery through enriched access to pt experience.
Emergency oncology: The situation of acute general hospital in Japan.
Authors: Onishi Yoshitaka , Miyakawa Takashi , Minematsu Mari , Natsuaki Shimpei , Ogawa Masari , Nagata Toshinori 
Published: May 2019

e18069 Background: The need for supportive and palliative care services for cancer patients is well established. Our hospital is acute general hospital with 602 beds, 20 ICU beds, radiation unit, chemotherapy unit and with emergency department(ED) 24hours and 365 days open, locates close to one of the national cancer center. In this situation, we have many acutely unwell patients with newly diagnosed cancer in emergency department(emergency oncology). Methods: We reviewed the records of the patients with newly diagnosis of cancer and treated by surgery, radiation and or chemotherapy and of the patients transfered by ambulance at ED in 2017, 2018 and 2019, retrospectively and consecutively. Results: In this three years, we have 1626 patients with first diagnosis of cancer, 268 patients visited after clinic-hour and 130 patients needed ambulance with critical symptoms. Of those, 145 had gastro-intestinal, 34 hepato-billiary, 25 urological, 24 lung, 16 gynecology, 9 breast and 23 other cancer. During this period, total 30027 patients were transported by ambulance to our ED. Conclusions: Although there are many cancer centers in Japan, there are only one unit in Japan.(National Cancer Center Hospital(Tokyo) )that provide urgent care to cancer patients. In this situation, acute hospitals have to have a role for emergency oncology. We need varying models of emergency and acute care development (e.g., acute cancer net-work system, regionalization, education for the physicians and patients, organize the emergency oncology unit in acute hospital or cancer center) with cooperation of oncologist and non-oncology emergency physicians in Japan as they are trying and developing in the USA and UK.
ChemoPalRx: Development and implementation of a chemotherapy mobile provider order entry system in a safety net hospital.
Authors: Hung Kin Wai (Tony) , Banerjee Natasha 
Published: May 2019

e18071 Background: Computerized provider order entry (CPOE) systems have been shown to enhance the safety and efficiency of prescribing chemotherapy over the handwritten ordering process. However, many institutions lack the financial ability, technological capability, or operational flexibility to invest in and implement such a system. In particular, Olive View-UCLA Medical Center (OVMC), a Los Angeles County safety net hospital, is among these institutions with unique restrictions that preclude the use of chemotherapy CPOE and mandate handwritten orders. Methods: In an effort to bridge the gap for safe chemotherapy prescribing, we aimed to develop and implement an effective, scalable, and sustainable chemotherapy provider order entry solution that was operationally sensitive to institutions without a chemotherapy CPOE. The solution was designed as a mobile application using Xcode, the integrative development environment of Apple Inc., with the Swift programing language. Results: On September 5th, 2018, we launched a free, chemotherapy provider order entry solution on the worldwide Apple App Store – ChemoPalRx. Using ChemoPalRx, providers can search, customize, and print common chemotherapy regimens in prescription format. Along with a reference library of over 120 order set and 450 medications, ChemoPalRx is equipped with the functions to automate dosage calculation, suggest pre-medications and safety parameters, and trigger alerts for missing prescribing information. As a quality improvement initiative, we implemented ChemoPalRx at OVMC. Implementation stages include obtaining administrative buy-in, consulting with multidisciplinary staffs, investing $100 USD for a prescription printer, and encouraging providers to download ChemoPalRx on their own mobile devices. An ongoing prospective cohort study is being conducted to determine ChemoPalRx effectiveness in reducing errors compared to handwritten orders. Conclusions: ChemoPalRx is developed to enhance the safety and efficiency of chemotherapy prescribing. Implementation of this mobile application is feasible in the safety-net hospital setting and has the potential to transform oncology practices globally.
Electronic but overly eclectic: Disciplined EHR data management is needed to automate MIPS reporting.
Authors: Schorer Anna E. , Koskimaki Jacob , Miller Robert S. , Rubinstein Wendy S. , Bernstam Elmer Victor , Krauss John C. , Moldwin Richard , Venepalli Neeta K. , Chen James Lin 
Published: May 2019

e18074 Background: Physician reimbursement for care delivered to Medicare beneficiaries fundamentally changed with the 2015 MACRA legislation, requiring eligible clinicians to report quality measures in the Merit-Based Incentive Payment System (MIPS). To determine whether structured data in electronic health records (EHRs) were adequate to report MIPS results, EHR data ingested by ASCO’s CancerLinQ (CLQ) was analyzed. Methods: Nineteen MIPS measures specified for medical oncology, including 8 shared by other specialties, were retrieved from qpp.cms.gov and systematically evaluated to determine data elements necessary to satisfy each measure. The existence of corresponding data fields and completion of these fields with clinical data was analyzed according to EHR implementation in de-identified and aggregated CLQ data. Results: Five clinician informaticists reviewed the 19 oncology MIPS measures, and identified a consensus list of 52 discrete EHR data elements (DEs) that would be needed. CLQ-processed data from 4 commercial EHR systems implemented at 47 CLQ practices found structured data fields for 84% (43 of 52) of the DE, but fewer than half (46%) of these fields were ever populated and only 32% (17 of 52) of DE were recorded for > 20% of cases. Only 3-5 of 19 MIPS measures could be reliably reported based on data element availability by most practices in this sample set. There were minimal differences between the EHRs ability to encode MIPS DE. Elements most likely to be encoded were those for registration (birthdate, gender), billing (diagnosis, meds), vital signs and smoking status, while those seldom or never encoded related to care plans (tobacco, alcohol, pain management). Other DE rarely encoded were patient events occurring outside the oncology practice (receipt/completion of consultations, dates of hospice enrollment and death), which would be dependent on data exchange between work units and practice entities or, more likely, re-entry by oncology practices. Conclusions: Only a minority of DE required to satisfy MIPS criteria are available as discrete data fields in current EHRs, limiting automated reporting efforts. Improved data quality and completeness is needed to satisfy mandated reporting.
Development of a digital immunohistochemistry records’ management system at the Moi Teaching and Referral Hospital (MTRH), Eldoret, Kenya.
Authors: Patel Kirtika Tushar , Bhamra Ashwinder Singh , Kibet Kibor Keitany , Busakhala Naftali Wisindi , Asirwa Fredrick Chite 
Published: May 2019

e18075 Background: Cancer diagnosis using immunohistochemistry (IHC) is important for quality care of patients. The utility of IHC services in management of cancer patients in low- middle income countries (LMIC) has gained popularity. Paper-based IHC records storage systems have made it cumbersome to retrieve records and thus impair the management of quality care for patients. We describe here the setup of a digitised records’ management system (RMS) in a LMIC which is user friendly, easy to access, prone to minimal errors and aid in research. Methods: A spreadsheet with blank templates containing key fields was designed and populated along the process until all records to the date of completion of data collection were recorded from January 2012 to November 2017. The complete reported tests were clustered into categories based on the diagnoses reached and frequencies for each cluster were derived. Information collected included patient identifiers, gross, histology, and immunohistochemical markers tested and the diagnosis. A provision is also made to store pictures of stained slides on the RMS. Results: Using RMS, a total of 948 immunohistochemistry staining was performed between January 2012 and November 2017; 677 of these have been reported, 200 were controls and 71 were repeats. Testing for breast cancer was the most common investigation performed (39.9% [n = 270]). Anti-LANA tests for Kaposi Sarcoma closely followed at 15.1% (102), followed by Non-Hodgkin’s lymphoma at 13.4% (n = 91). The RMS brings up the IHC test to be performed after HE diagnosis is entered, helping the technician to prepare and plan for IHC staining. Conclusions: The RMS has made it easier for clinicians taking care of patients to get results and provide quality care. This system is helpful in answering research questions and data analysis. Models such as these are especially useful in LMIC as they can assist technicians to perform IHC as they await the consultant pathologist. RMS will also help incorporation of IHC in telemedicine, aiding transmission of photographs taken by mobile phones in remote setups to pathologists in distant places.
An analysis of growth patterns of targeted therapies (TTs) using keywords from ASCO annual meeting abstracts.
Authors: Gong Yutao , Schneider Julie A , Blumenthal Gideon Michael 
Published: May 2019

e18084 Background: The number of TTs approved to treat cancer patients has increased dramatically in the past decades. We analyzed how frequently 27 oncology targets (and associated therapies) appeared in ASCO meeting abstracts since 2005 to explore if future drug development patterns could be predicted. Methods: We obtained abstracts from the ASCO Center for Research & Analytics. We used keyword abstraction to calculate the percentage of abstracts referencing 27 specific target/drug combinations each year, and we categorized them into high (HV), medium (MV), and low volume (LV) groups based on percentage in 2018. Results: Table shows data since 2012 for the HV group. The percentages of MV (BCR/ABL, CDK4/6, CD20, MEK, CTLA4, iMID, PARP, PI3K, proteasome inhibitors) and LV (BCL2, BTK, CD19, CD30, CD38, HDAC, IDH1, IDH2, and NTRK) in 2018 were less than 1.7%. The HV group was associated with more FDA-approved therapies (41) than the MV (23) and LV (13) groups. The HV and MV groups are likely enriched for more mature targets, as the median date of relevant drug approvals is earlier (11/2012 and 4/2013, respectively) than the LV group (4/2016). Growth patterns are consistent with key regulatory milestones. The number of abstracts with PD-1/PD-L1-related keywords has grown more rapidly than any other drug/target combination. This growth begins soon before FDA approvals for a diversity of relevant indications. Continued growth likely reflects ongoing clinical trials of several other PD-1/PD-L1 inhibitors and combinations. We identified similar growth trends for other targets just prior to key regulatory approvals. Conclusions: Our analysis revealed interesting growth patterns for key oncology target/drug combinations. Future work will explore whether we can extend the analysis to help predict the evolution of development programs for new targets. [Table: see text]
Assessing real-world outcomes in precision oncology by linking clinical genomic testing to electronic medical records.
Authors: Datta Debajyoti , Goldstein Theodore , Butte Atul 
Published: May 2019

e18091 Background: With an ever-widening array of targeted therapies for cancer patients, clinical genomic testing has expanded rapidly in recent years. Tumor molecular profiling by next-generation sequencing is now considered a cornerstone of precision oncology, with the potential to offer patients with advanced cancers new therapeutic options. However, the overall impact of this testing remains unclear, and evidence demonstrating improvement in patient outcomes is lacking. The objective of this study is to assess the utility of clinical sequencing on the management of cancer patients. Methods: We present the development of a database that combines results of tumor mutation profiling using various next-generation sequencing panels (both external commercial tests and our institution’s internal sequencing panel), with a variety of data points from a de-identified representation of our institution’s electronic medical record (EMR). Assembling this data from different sources into a common relational database permits efficient retrospective analysis of real-world outcomes in patients with advanced cancers. Results: This study included over 3000 patients seen at UCSF Comprehensive Cancer Center since 2013. With this linked data set we analyzed the rate at which tumor molecular profiling affected clinical decision making, identified barriers to the efficient use of testing, and assessed for disparities in utilization. For example, by measuring patient survival relative to the clinical intervention of genomic testing for the subset of patients with a date of death recorded in our EMR, we found that a small fraction of patients died before results returned and any action could be taken, especially in cases of pancreatic cancer. Conclusions: We demonstrate that a common relational database combining clinical sequencing results with real-world EMR data provides insights into the optimal clinical use of tumor molecular profiling. This provides new opportunities for advancing precision oncology initiatives and improving patient care, such as identifying which cancer patients should get genomic testing and efficiently matching patients to clinical trials.
Generating real-world evidence: Using automated data extraction to replace manual chart review.
Authors: Law Jennifer H. , Pettengell Christopher , Le Lisa W , Aviv Steven , DeMarco Patricia , Merritt David C. , Lau Sally CM , Sacher Adrian G. , Leighl Natasha B. 
Published: May 2019

e18096 Background: Real world evidence is a valuable resource to help guide clinical care beyond evidence generated from clinical trials, for example safety and effectiveness of novel treatments in special populations. Administrative databases often lack sufficient clinical detail to address gaps in the improvement of patient management and quality of care. Detailed clinical data collection and curation are resource intensive, limiting the ability to generate and maintain large informative cancer databases. Darwen, novel technology developed by Pentavere, enables the automation of data abstraction from unstructured hospital electronic medical records and may eliminate the need for manual chart review. Methods: Health records were identified through an institutional cancer registry from patients with stage IIIB/IV lung cancer (NSCLC or SCLC) diagnosed and treated at the Princess Margaret Cancer Centre between 01/01/2015 and 31/12/2017. Cases underwent automated data extraction including demographics, comorbidities, treatment, concurrent medications and outcomes until 30/06/2018. Agreement with data fields extracted using manual data collection in an external validation set of patients is planned. Results: Of 1210 patients identified, 538 were eligible for analysis. From automated data abstraction, 9.9% were reported to have SCLC, 67.5% adenocarcinoma, 11.2% squamous carcinoma, 28% EGFR mutations, 5.8% ALK fusions and 9.3% tumour PDL1 > = 50%. Of the 304 (56.5%) that received systemic therapy, initial treatment was chemotherapy for 55.6%, targeted therapy in 34.2% and immunotherapy in 10.2%. Additional outcome data and agreement with manually curated data fields will be presented. Conclusions: Automated software to extract clinical data is a powerful new tool to generate and maintain databases that yield high quality real world clinical evidence. This is a critical next step to improve clinical decision making, inform evidence-based practice and improve quality of cancer care.
Visualizing real-world outcomes through the lens of a molecular tumor board: Persona-typing pancreatic cancers for clinical decision support.
Authors: Petricoin Emanuel , Barg Daniel , de Arbeloa Patricia Miren , Pishvaian Michael J. , Blais Edik Matthew 
Published: May 2019

e18100 Background: Despite the molecular diversity of pancreatic adenocarcinoma, standard therapy options remain largely molecularly-untailored except in the context of DNA damage response alterations such as BRCA mutations, NTRK fusions, or microsatellite instability. Methods: To broaden the utility of molecular profiling, we analyzed real-world outcomes and established 12 molecularly-driven clusters, or “persona types” (PTs), across a cohort of 1280 pancreatic cancers with CLIA-grade genomic/proteomic data (commercially available NGS/IHC panels). Patients were consented into Perthera’s precision oncology platform via referrals from advocacy programs and hospital partnerships for case review by a molecular tumor board (MTB). Persona types were generated using unsupervised k-means clustering of molecularly-tailored therapy recommendations formulated by the MTB. Progression-free survival was documented across all lines of therapy. Results: Personas based on multi-omic profiles and expert-driven recommendations were representative of molecular phenotypes reported in previous studies (e.g. DNA damage response deficiencies, BRAF mutations, other non-KRAS-drivers, SWI/SNF alterations, squamous-associated genes, cell cycle regulators, etc.). To streamline the exploration of real-world outcomes, we developed an interactive dashboard that enables users to compare PFS survival curves across Personas for various therapies such as gemcitabine/nab-paclitaxel, FOLFIRINOX, other standard regimens, immunotherapy, PARP inhibitors, RAF/MEK/ERK inhibitors, and more. Persona types associated with increased/decreased sensitivity to several classes of agents were identified (e.g. PD-1/L1 inhibitors in a persona enriched for cell cycle dysregulation, PARP inhibitors in a persona enriched for BRCA mutations). Conclusions: Empowering oncologists with personalized insights into real-world outcomes may promote investigator-initiated trials and augment clinical decision support, particularly when choosing between standard of care regimens or when exploring potential clinical trial options.
Socioeconomic disparities among uninsured cancer patients: A free clinic study.
Authors: MacDonald Madeline , Lu Yuanyuan , Song Ethan , Ayoubi Noura , Robinson Katherine , Todd Amber , Mirza Abu-Sayeef 
Published: May 2019

e18110 Background: Cancer is the second leading cause of death in the United States and approximately 38.4% of Americans will be diagnosed with cancer during their lifetime. Cancer treatment and follow-up care is expensive and uninsured individuals may face barriers to receiving necessary treatments. Minorities may encounter additional barriers to accessing healthcare. There is limited research about socioeconomic disparities in uninsured cancer patients seen at free clinics in the United States. Methods: A retrospective chart review was conducted to collect chronic disease parameters from electronic medical records and paper charts at nine free clinics in the Tampa Bay area in Florida. Demographics were compared between cancer patients and the non-cancer population via chi-square test or independent samples t-test. Results: Between January 2016 and December 2017, 9127 uninsured patients were seen at nine free clinics. 2137 patients were excluded from the study because there was no cancer data in their charts. Of the patients included in the study, 221 (3.2%) had a current or past diagnoses of cancer. Cancer patients were more likely to be female (n = 145, 65.9), p = 0.048, compared to non-cancer patients. Cancer patients were more likely to be Caucasian (n = 106, 89.1%), p < 0.001 compared to non-cancer patients (n = 2489, 69.3%). Cancer patients were less likely to be African American compared to non-cancer patients (n = 6, 5.0% vs. n = 754, 21%), p < 0.001. Cancer patients were significantly older than non-cancer patients (M = 54.1, SD = 12.0) vs. (M = 41.0, SD = 16.7), p < 0.001. Patients who had cancer were more likely to be unemployed compared to non-cancer patients (n = 78, 54.9% vs. n = 1685, 46.6%), p = 0.050. Conclusions: The study revealed that uninsured cancer patients are more likely to be unemployed, female, of older age, and Caucasian compared to non-cancer patients. It appears that uninsured African Americans are not utilizing free clinics for their healthcare and may be lost to follow-up. A variety of factors may have contributed to these disparities in this vulnerable population including lack of transportation, lack of awareness of free resources in the area, and more. This study increases awareness of disparities in uninsured, cancer patients.