bluuebunny/crossref_metadata_2025_split huggingface dataset:
Monitoring COVID-19 initiatives and safety concerns at a comprehensive cancer center.
Authors: Gonzalez Carmen E. , Burns LaTasha , Bingham John , Newman Alana , Dawson Tammy , Thompson Lulu , Browning Doug , Baker Ellen , Beno Jeff , Black Michael , Decarlo Randy , House Charmetria 
Published: October 2020

247 Background: The COVID-19 pandemic brought national and local concerns, particularly to a comprehensive cancer center. Cancer patients’ clinical immunosuppressed status puts them in a vulnerable position for serious complications from COVID-19, including a higher risk of death. The institution developed five operational priorities (OP) to minimize exposure to the virus and contain and mitigate COVID-19 transmission and saw the need to monitor and evaluate those priorities. The project aim was to develop a monitoring system to promote timely identification of system threats and failures of the multiple safety processes implemented by engaging and empowering the front line workforce and area leaders to report concerns through a reporting tool. Methods: The COVID-19 Safety Control Center was developed, which consisted of a triage controller, SharePoint tool for front-line and area managers to report concerns or questions using handheld devices and a telephone hotline for urgent/emergent issues. Delegates from each were designated to review and respond to the reports within 24 hours. Metrics were developed for each of the initiatives. An interactive dashboard was built to communicate to leadership the status and trends of safety concerns. Project leadership met weekly to evaluate its’ efficiency and efficacy. Results: During the first 60 days, 476 events were reported and, on average, closed within 19 hours. The highest entries were related to policy and procedures of the hospital entry points, COVID-19 testing, and patient care. No high harm events were reported. A decreasing trend in entries was observed coinciding with the institution providing timely information to employees through daily COVID-19 briefings, weekly town hall meetings and increased familiarity with institutional COVID-19 processes. Conclusions: When multiple interventions are instituted and compliance to these measures are required in a rapid time frame, there needs to be a platform to monitor the process changes and address safety concerns quickly. Providing timely resolution to concerns of the front line staff serve to identify the threats, decrease the potential failures and provide opportunities to improve processes. The steps taken by the institution are a part of the journey toward high reliability.
Prospective validation of a clinical tool developed with machine learning to identify high-risk patients with cancer and reduce emergency department visits.
Authors: Coombs Lorinda A , Orlando Abigail , Adamson Blythe J.S. , Griffith Sandra D. , Lakhtakia Shreyas , Rich Alexander , Shaw Pooja , Wang Xiaoliang , Miksad Rebecca A. , Mooney Kathi 
Published: October 2020

254 Background: Clinicians in oncology are often challenged to identify when patients with cancer are at high risk for adverse outcomes and would benefit from more intensive clinical care. Preemptive identification of these patients may improve efficiency and improve patient care. The objective of this quality improvement pilot was to prospectively validate a machine learning (ML)-based clinical tool designed to identify patients with cancer who are at high risk for an emergency department (ED) visit, and whether they met eligibility criteria for clinical services at home, such as Huntsman at Home (H@H). Methods: Patients with cancer who received care at Huntsman Cancer Institute (HCI) between Jan. 4 and Feb. 7, 2020 were included in the analysis. For patients with HCI contact in a given week, the ML-based tool predicted the probability of an ED visit in the next 60 days to identify “high risk” patients using real-time structured EHR data (e.g. demographic characteristics, vital signs, and laboratory values). Risk of an ED visit was used as a proxy for eligibility for H@H. Patients were randomized to two cohorts to assess eligibility precision and outcome forecast precision. Eligibility precision was defined as the percentage of ML-classified high risk patients who were confirmed by a nurse practitioner to be eligible for admission to H@H. Outcome forecast precision was defined as the percentage of ML-classified high risk patients who experienced a future ED event within 60 days and was compared to the baseline prevalence of ED visits within 60 days during the same time period. The IRB determined this to be a quality improvement project. Results: This quality improvement pilot included 1,236 patients; 53% were women, median age was 65 years, and 84% were Caucasian. The most common cancers, excluding non-melanoma, were breast, prostate, lung, and myeloma. The observed prevalence of an ED visit within 60 days was 7%. The tool classified 9% of patients as high risk. The eligibility precision was 0.76 (95% CI: 0.62-0.89), demonstrating concordance with clinician assessment among patients classified as high risk. Compared to a baseline of 0.07, the outcome forecast precision was 0.22 (95% CI: 0.12-0.34) for future ED events. Conclusions: This quality improvement pilot demonstrates the potential application of an ML-based tool to identify patients with cancer who may benefit from further support through the H@H program. The approach creates a framework for ML-based tools to enhance clinical services at home.
Provision of smartphones in a symptom monitoring program of gynecologic and breast cancer patients during active therapy.
Authors: Naughton Michelle Joy , Moon Jennifer , Loyan Hibaq , Peng Juan , DeGraffinreid Cecilia , Paskett Electra D. 
Published: October 2020

255 Background: With advances in technology, smartphones are being used for multiple research and clinical care functions. However, not all patients have these devices, leading to disparities in participation. We report on a quality improvement program that provided smartphones to patients without these devices. Methods: Gynecologic (n = 120) and breast (n = 193) cancer patients under active treatment were enrolled in a 12-month text-based symptom monitoring program to facilitate communication and optimize patient management. Patients without a smartphone were provided with an iPhone through a partnership with a U.S. wireless company. The company provided smartphone devices at zero cost, and program funds paid for 12 months of phone service. Program staff helped patients set up the iPhones, and provided basic education and ongoing phone support. After 12 months, patients were able to keep their iPhones, but had to secure their own phone plan for calling and texting functions. Results: iPhones were provided to 42 (13.4%) patients across all cancer types. Patients who received iPhones, compared with those who had a smartphone, had incomes below $50,000/year (p = 0.03) and an educational level of < high school (p < 0.0001). Program staff had few difficulties training patients to operate the phones or in patients’ adherence to symptom monitoring after receiving the iPhones. Phone service charges averaged $40 per month or $500 per person for 12 months. Greater than 90% of patients believed the phones enabled them to better communicate with their health care team and family/support networks, and 95% believed the phones had a positive impact on their life. However, only 70% planned on getting a phone service plan at the end of the 12 months, due to cost or believing a smartphone was not a necessity. Conclusions: Providing smartphones to patients enabled them to better communicate with their health care team and families, and participate in remote symptom monitoring during active treatment. Programs such as these are needed to reduce disparities in patient care, and support quality improvement efforts using electronic devices.
Pilot randomized controlled trial (RCT) in women with non-small cell lung cancer (NSCLC) to assess the feasibility of delivering group-based psychosocial care via videoconference.
Authors: Milbury Kathrin , Higgins Hannah M , Chen Aileen B. , Antonoff Mara , Li Yisheng , Tsao Anne S. , Bruera Eduardo 
Published: October 2020

257 Background: Women with lung cancer are vulnerable to psychological distress and social isolation, which may be related to the smoking-related stigma of the disease. We developed a group-based psychosocial intervention seeking to address the specific needs of this understudied patient population. The goal of this pilot RCT was to examine the feasibility and acceptability of delivering group-based psychosocial care via videoconference (i.e., Zoom). Methods: Women with NSCLC within 3 months of diagnosis completed baseline measures of their computer literacy and were then randomized to a group-based psychosocial intervention receiving coping skill training or a group-based attention control (AC) arm receiving psychoeducation. Both arms involved five, 60 min. videoconference sessions (groups of 3-5 patients) that were led by a master-level counselor. Participants completed one Zoom “practice run” prior to starting the group sessions. After the last session, they rated the overall experience of the intervention delivery and the specific software. Results: Seventy patients (mean age = 66 yrs with 54% over age 65; 71% non-Hispanic White; 50% college educated; 75% advanced stage) consented (63% consent rate) and 65 were randomized (intervention: N = 33; AC: N = 32). At baseline, 47% indicated that they use a computer daily while 50% said they rarely or never use a computer. Attendance was high in both arms (means: intervention = 3.18; AC = 3.56 with 63% attended all sessions). Across arms, 89% preferred a group-delivery and 92% preferred online delivery. The majority used a smartphone or tablet to participate (72%). Regarding the Zoom software, 71% said it was easy to use, 65% of women would recommend it to others, and 41% felt comfortable with it after one use (but 26% said they felt never comfortable with it). Only 44% thought that the sessions via Zoom were the same as they would have been in-person. Conclusions: It seems to be feasible and acceptable to deliver group-based psychosocial interventions via videoconference in women with NSCLC undergoing treatment. Challenges regarding scheduling the group sessions and familiarizing infrequent computer users with the technology were encountered but were resolved over the course of the trial. Clinical trial information: NCT03731585 .
Perception of patients regarding telemedicine at times of COVID-19: Did they miss the personal touch?
Authors: Peleg Hasson Shira , Waissengrin Barliz , Hodruj Marah , Shachar Eliya , Pelles Sharon , Wolf Ido 
Published: October 2020

260 Background: The patient-oncologist relationship is cultivated from the first clinic visit, trust and assurance established throughout the follow up period until the end of life. In March 2020, with the break of the COVID-19 pandemic, social distancing restrictions were implement throughout Israel. The adoptions of telemedicine services were incorporate as a response at our institution. Almost all ambulatory activity in the oncology division in Tel Aviv Medical Center was converted to telemedicine services. Several studies report favorable results regarding patient preference and cost effectiveness of telemedicine. Methods: We conducted a telephone interview questionnaire assessing patient satisfaction. Inclusion criteria included solid tumor patients over 18 years who utilized the telemedicine platform at Tel Aviv Sourasky Medical Center between March 2020 - May 2020. We aimed to evaluate patient's perspectives and preferences regarding telemedicine and assess whether this virtual communication affects the patient-doctor relationship. Results: Following the COVID-19 outbreak, 400 telephone calls were made to patients, 100 patients agreed to participate and surveyed. Fifty-two percent were female. The majority of patients independently downloaded the telemedicine application and did not encounter technical constraints (67%). Family members and friend attended 45% of telemedicine visits. Patients cancer diagnosis included colorectal cancer (47%), breast cancer (18%), genitourinary cancer (18%), sarcoma (9%) lung malignancies (6%), gynecological cancer (1%) and CNS tumors (2%). Visit intent included post-treatment follow up (40%), active treatment follow (53%), and first visit intake (7%). The majority of patients felt their emotional needs were met (88%) and felt that their treatment was not harmed due to absence of a physical visit (84%). Almost all patients (99%) felt their privacy was maintained. Ninety-five percent of patients affirmed that the virtual visit relieved their worries regarding treatment interruption. Importantly, 75% of patients affirmed their interest to continue telemedicine regardless of COVID-19 pandemic. Conclusions: Telemedicine is an acceptable platform that may replace follow up visits without comprising patients’ experience. Our data call for research and development of tools enabling long-term implementation of remote telemedicine and assess the patient-physician relationship and quality of care among oncology patients.
Implementing teleoncology in a safety-net hospital during the COVID-19 pandemic.
Authors: Wiele Andrew James , Patel Tejal Amar , Russo Kristyn-Mae , Rizvi Sarah , De Los Rios Patricia , Hester Robert Harrison , Smith-Graziani Demetria Joy , Ma Hilary Y. , Rieber Alyssa G. 
Published: October 2020

262 Background: In response to the COVID-19 pandemic, telehealth has emerged as a key strategy to ensure the safety of patients and healthcare workers and minimize disease spread. Lyndon B. Johnson Hospital (LBJ) is a safety-net hospital that mainly serves low income and uninsured patients (pts), and MD Anderson Medical Oncology faculty and fellows diagnose and treat over 800 new cancer cases per year in the LBJ Oncology Clinic. We piloted a teleoncology (TO) program to replace in-person visits for pts with clinic appointments (appts) during the COVID-19 pandemic. Methods: A multidisciplinary team was formed to implement TO in the LBJ Oncology Clinic. Fellows and APPs screened their appts in advance and used guidelines to determine pts appropriate for TO. Clinic visits were prioritized for new pts, treatment consents, and symptomatic pts; stable pts on treatment and surveillance had appts changed to TO. Pts were notified when their appts were converted, with integrated video visits preferred over telephone visits. To limit disease exposure, 3 fellows rotated in clinic for one week at a time and cared for the pooled clinic pts; the other 16 fellows and 2 APPs conducted TO and remotely staffed their pts with faculty on their assigned clinic day. We reviewed TO visits during the initial 1-month pilot period and survey results from involved personnel. Results: From 4/13/2020 – 5/8/2020, we identified 251 pts that utilized TO. Median age was 57 years (range, 20-88) and 66% were female; 63% were Hispanic and 21% were African American; 52% spoke Spanish and 46% spoke English. 57% of TO visits were conducted via telephone and 43% via video. 48% of the TO visits were for pts on active treatment, including IV therapy (35%) and oral targeted agents (13%); 15% were surveillance pts with (9%) or without (6%) restaging imaging, 8% were pts on endocrine therapy, and 16% had transitioned to the Survivorship Clinic staffed with APPs. Survey response rate was 100% (5/5) for faculty, 74% (14/19) for fellows, and 100% (2/2) for APPs. 80% of faculty, 57% of fellows, and 100% of APPs were generally satisfied (agree/strongly agree) with the patient care delivered via TO; 100% of faculty, 64% of fellows, and 100% of APPs believe patients were generally satisfied with TO. Conclusions: This study demonstrates that implementing TO in a fellows’ teaching clinic at a safety-net hospital is feasible and effective. Nearly half of the TO visits conducted during this pilot period were for pts on active cancer treatment and the majority of caregivers were satisfied with TO. Pt care via TO is ongoing and pt survey data is currently being collected.
Machine learning to predict tamoxifen adherence among U.S. commercially insured breast cancer patients.
Authors: O'Neill Tyler J. , Sharma Vishakha , Siadimas Athanasios , Babaeian Amir , Yerrapragada Gayathri 
Published: October 2020

276 Background: Adherence to tamoxifen among women diagnosed with hormone receptor positive metastatic breast cancer (mBC) can improve survival and minimize recurrence. Screening for non-adherence at treatment initiation may support personalized care, improve health outcomes, and minimize cost of care. This study aimed to use real world data (RWD) and machine learning (ML) methods to classify tamoxifen non-adherence. Methods: A cohort of women diagnosed with incident mBC from 2012 to 2018 were identified from Truven MarketScan Commercial Claims and Encounters and Medicare supplemental administrative claims databases. Patients with < 80% proportion of days coverage (PDC) in the year following treatment initiation were classified non-adherent. Training and internal validation cohorts were randomly generated (4:1 ratio). Clinical procedures, comorbidity, treatment and healthcare encounter features in the year prior to treatment initiation were used to train logistic regression, boosted logistic regression, random forest, and feed forward neural network models and internally validated based on area under receiver operating characteristic (AUROC) curve. The most predictive ML approach was evaluated to assess feature importance. Results: A total of 3,022 patients were included with 39.9% classified as non-adherent. All ML models had moderate predictive accuracy. Logistic regression (AUROC 0.64) was easily interpreted with sensitivity 94% (95% confidence interval [CI]: 0.89, 0.92) and specificity 0.31 (95% CI: 0.29, 0.33). The model accurately classified adherence (negative predictive value 88.7%) but was non-discriminate for non-adherence (positive predictive value 47.7%). Variable importance identified top predictive factors, including patient features (≥55 years old) and pre-treatment procedures (lymphatic nuclear medicine, radiation oncology, arterial surgery). Conclusions: ML using baseline administrative data predicts tamoxifen adherence. Baseline claims may not be sufficient to predict treatment non-adherence. Further validation with enriched longitudinal data may improve model performance for incorporation of predictions into clinical decision support.
Impact of 12 months of immunotherapy for metastatic cancer patients on oncology workload.
Authors: Andreotti Victoria , Cinausero Marika , Garattini Silvio Ken , Bortot Lucia , Palmero Lorenza , Valent Francesca , Riosa Chiara , Iacono Donatella , Casagrande Mariaelena , Rihawi Karim , Macerelli Marianna , Minisini Alessandro Marco , Fasola Gianpiero 
Published: October 2020

279 Background: In the last years, the introduction of immune checkpoint inhibitors (ICI) in clinical practice translated into major changes in oncology workload. We conducted a study aimed to estimate the shift in workload generated, within 1 year of first consultation, by any new metastatic cancer patient receiving ICI at the Oncology Department of the Academic Hospital of Udine, Italy. Methods: We collected from our electronic accountability system data all new cases of metastatic cancer between 01.01.2017 and 31.12.2018, leading to at least a second clinical episode (treatment sessions, unplanned presentations, hospitalizations, re-evaluations, follow-up, and inpatient oncology advices) during the following year. Patients (pts) were divided into those receiving ICI (anti-CTLA4/PD1/PDL1) versus pts receiving other treatments. Mean number per patient and standard deviation were calculated for clinical episodes, and the mean numbers in each group were compared using Student’s t-test (significance p<0.05). Follow-up continued until 31.12.2019. Results: 969 pts were included: 115 were treated with ICI, 854 received other treatments. In the first group a greater number of treatment sessions, re-evaluations and unplanned presentations was generated, with a statistically significant increased workload. On the other hand, pts receiving other treatments generated a greater workload in terms of follow-up. In detail, data are reported in Table. Conclusions: ICI have transformed the oncology landscape, leading to longer lasting treatment period with emerging toxicities. Estimating the workload generated by ICI is crucial for the implementation of more sustainable systems and for planning clinical activities. Mean number of clinical episodes in the first year of treatment with ICI for metastatic disease. Mean number per patient is represented by mean value and standard deviation (SD). Total number of clinical episodes is shown (N=). Data are reported for ICI versus other treatments group. [Table: see text]
Saving the best to the last: Can we wait for second-line?
Authors: Barak Renana , Waissengrin Barliz , Wolf Ido 
Published: October 2020

284 Background: A common perception of some oncologists is that the vast majority of their patients with metastatic disease will receive second-line treatment upon progression. Therefore, “saving” good treatment options for the future may be acceptable. We aimed to examine whether this perception correlates with real-life. Methods: Using an oncology electronic database, consisting of >27,000 patients treated at our institution, we selected consecutive patients with metastatic or locally advanced lung, colon, pancreatic, bile duct and gastric cancers who started standard first-line. We then assessed the correlation between proceeding to second-line therapy and demographic and clinical variables, including age, gender, initial performance status, BMI, hemoglobin, WBC, creatinine, glucose, calcium, as well as duration on first line therapy and survival. Results: A total of 492 patients met the inclusion criteria. Their median age was 67 and 285 were men. Their diagnoses were colon (169), lung (102), pancreas (101), bile duct (65) and gastric (55) cancers. Only 52% (255) received second-line treatment for at least 30 days (36% colon, 26% lung, 18% pancreas, 9% bile duct and 11% gastric). Receipt of second-line therapy was associated with disease site (P=0.001) as well as with age, with patients who received second-line being 5 years younger compared to those who did not (64 vs. 69 years, P=0.004). Patients who reached second-line had better performance status and higher hemoglobin level at presentation, additionally their median duration on first-line chemotherapy was substantially longer (P<0.007 for all comparisons). Survival of patients not starting second-line was significantly shorter across all tumor types (19.8 vs 6.5 months P=0.001). General deterioration and toxicity were the major reasons for avoiding second-line therapy at progression, 43% and 30% respectively. Conclusions: These real-life data indicate that only half of the patients starting standard doublet or triplet treatment for advanced cancers will commence second-line therapy; and this can be hardly predicted in advance using standard clinical and laboratory characteristics. Our data challenge the practice of saving good treatment options for subsequent lines, and call for the development of tools enabling prediction of response and tolerance to treatment, pursuing for better patient selection and patient-tailored therapy.