bluuebunny/crossref_metadata_2025_split huggingface dataset:
Acceptability of mobile health technology among cancer patients.
Authors: Potdar Rashmika , Thomas Arun , DiMeglio Matthew , Mohiuddin Kamran , Djibo Djeneba Audrey , Laudanski Krzysztof , Dourado Claudia M. , Leighton John Charles , Ford Jean G 
Published: May 2019

e18139 Background: Advances in wireless technology have led to the increasing use of mobile health platforms. This approach, tele-medicine, enables healthcare providers to communicate remotely with patients, thereby enhancing timeliness and quality of care, and patient engagement. However, few studies address barriers to its implementation, especially in medically under served populations. Methods: A cross-sectional survey of 151 cancer patients was conducted at an academic medical center in North Philadelphia, PA. A trained interviewer performed structured interviews regarding the barriers and facilitators of patients’ current and desired utilization of technology for healthcare services. Statistical significance was defined as p < 0.05 on a two-tailed distribution. Chi-Square test was used for categorical variables. Odds ratios from logistic regression analysis were used to identify the relationship between demographic factors and willingness to utilize a mobile application for health surveillance. Results: Of the 151 patients who completed the survey, 35.8% were male; ages ranged from 21-104 years. Forty-two percent were married, 49.0% were single, and 9% were divorced at the time of the survey. No significant associations existed between the willingness to utilize a mobile health application and gender ( p = 0.73) or marital status ( p = 0.97). After controlling for other demographic variables, patients older than 70 were significantly less likely to utilize a mobile application. Conversely, patients with a college-level education or more were significantly more likely to utilize a mobile application [OR = 2.78, p = 0.01]. Conclusions: Age and education level represent potential barriers to mobile health applications for cancer patients in socioeconomically diverse community. Health networks should consider these factors when launching patient engagement platforms. [Table: see text]
Racial and insurance disparities in multiple myeloma management in a referral center.
Authors: Renteria Anne , Jagannath Sundar , Fei Kezhen , Lin Sylvia , Yagnik Radhi , La Lisa , Lin Jenny J. , Bickell Nina A. 
Published: May 2019

e18140 Background: Multiple Myeloma (MM) management has significantly improved disease-free and overall (OS) survival but disparities among racial groups still exist. After the Affordable Care Act, the extent to which induction, autologous stem cell transplant (ASCT), and maintenance therapies are used are uncertain. We sought to describe underuse of induction, ASCT and maintenance in a large referral center. Methods: Between 2010 and 2014, 3101 patients were diagnosed with MM via ICD-9 code from the Data Warehouse and certified hospital tumor registry. NCCN 2014 and CMS guidelines were used to define the categories of treatment underuse, and define transplant eligibility. Demographics including insurance, Charlson Comorbidity Index and treatments received were determined via chart abstraction. To date, 393 confirmed MM from 697 charts were abstracted. Comparison by groups used Chi-square for categorical variables, t-test and ANOVA for continuous variables. Multivariate logistic regression models were applied to predict underuse of induction, harvest, ASCT, and maintenance. Results: Patients were 62 ±11.3 years-old, with no racial differences in age and insurance coverage. More minorities had Medicaid (Black [B] 13%, White [W] 7%, Hispanic [H] 25%; p = 0.001). Almost all patients (97%) received induction (B 99%, W 96%, H 100%; p = 0.3), with no difference by insurance. Among transplant eligible patients, 93% underwent harvest, 87% underwent ASCT, with no racial differences. Patients with Medicare or self-pay were less likely to undergo harvest compared to patients with Medicaid or private insurance (p = 0.01). No difference in ASCT rates by insurance were noted. B patients were less likely to receive maintenance than non-B (73% vs 86%; p = 0.03), with no difference by insurance. OS was 73%, with no racial differences. In multivariate model, older age predicted induction underuse (aOR = 1.15, 95% CI: 1.06-1.25) (c = 0.9, p = 0.005), and B patients experienced more maintenance underuse (aOR = 2.22, 95% CI: 1.09-4.54) (c = 0.61, p = 0.1), controlling for age and comorbidity. Conclusions: While there were no racial or insurance differences in access to induction therapy, fewer Black patients received maintenance therapy. Interviews are underway to understand reasons for observed differences.
Racial disparities in setting of care in women with breast cancer in South Carolina.
Authors: Sorrell McKenzie , Wickersham Karen , Adams Swann Arp , Heiney Sue P. 
Published: May 2019

e18146 Background: African American (AA) women with breast cancer (BrCa) suffer a 40% higher mortality burden than White women despite having about equal incidence nationally and lower incidence in South Carolina. Our aim was to describe inpatient and emergency department visits by race and geographic location among BrCa survivors. Methods: We analyzed data from a study (1R15CA179355-01A1; Adams, PI) that combined administrative claims data from South Carolina’s Medicaid Program and a state-based, private-payor health plan to matching BrCA cases from the SC Central Cancer Registry. Race was determined by patient self-report. Geographic location was assigned using designations from the Rural-Urban Commuting Area Codes (RUCA). We used descriptive statistics to characterize the study sample and Chi-square test of independence to compare the descriptive statistics by race and rural/urban continuum. Results: The sample (N = 2723) was 33.6% AA, 91.8% non-Hispanic, primarily married 48.8%, and ranged in age from 14 to 64 years. Most women in the sample lived in an urban area (74.9 %). Most women had Stage I (16.9%), IIA (13.9%), or IIB (7.5%) disease. Women were primarily treated in an outpatient setting; 1.3% (n = 36) were seen in an emergency room and 1.2% (n = 34) were hospitalized. When comparing women living in a rural versus urban area, there were significant differences in TNM stage of disease (by pathology), marital status, race, and setting of care (all p’s ≤ 0.001). When comparing women by race, there were significant differences in age, ethnicity, marital status, stage of disease, and setting of care (all p’s ≤ 0.001). Conclusions: Women with BrCA in SC continue to experience disparities with regard to stage of disease at diagnosis and setting of care. Future research should focus on specific predictors of hospitalization and the relationship of rurality and race with setting of care.
Timeliness of treatment for patients referred urgently with a high suspicion of cancer in New Zealand.
Authors: McNeill Rob 
Published: May 2019

e18147 Background: Delays in diagnosis and treatment have the potential to impact negatively on clinical outcomes for cancer patients. Guidelines for timeliness have been established for many cancer types and national targets have been established in some countries. At the end of 2014 New Zealand introduced a target for patients referred urgently with a high suspicion of cancer, aiming to have 90% of patients from referral to first treatment within 62 days. Methods: Timeliness data from 13,865 patients who were referred for their first specialist appointment in the years 2015-7 were obtained from the Ministry of Health. Z-tests for proportions were used to compare target performance across the time period. Cox regression was used to establish whether age, gender, and ethnicity were associated with timeliness. Results: The proportion of patients meeting the 62 day target increased significantly from 2015 (72.7%, 95%CI: 71.3-74.0; Median: 46 days) to 2016 (80.2%, 95%CI: 79.0-81.3; Median 43 days), but was not significantly higher in 2017 (80.7%, 95%CI: 79.6-81.8; Median 41 days). The Cox regression found that males (HR 0.965; 95% CI, 0.9330.999) and older people (HR 0.996; 95% CI, 0.9950.998) at a small but significantly higher risk of longer times to treatment. Much larger differences in risk of delay were found for Maori (HR 0.789; 95% CI, 0.7480.832), Pacific (HR 0.754; 95% CI, 0.6920.822) and Asian (HR 0.885; 95% CI, 0.8160.960), compared to European/Other ethnic group patients. Conclusions: This research has produced evidence that the introduction of the 62 day target was associated with a significant improvement in timeliness of treatment for this subgroup of patients. The results also highlight the large ethnic disparities in timeliness that exist both in New Zealand and in other countries. These are also reflected in ethnic disparities in outcomes across many cancer types. Further policy, system and practice changes are necessary to try to reduce these.
Comparable survival of African-Americans and Caucasian patients with multiple myeloma: A hospital-based study including 117,926 patients.
Authors: Malek Ehsan , Chamoun Kamal , Caimi Paolo Fabrizio , Gerson Stanton L. , Tomlinson Ben Kent , Patel Seema , De Lima Marcos J.G. , Fu Pingfu 
Published: May 2019

e18170 Background: Multiple Myeloma (MM) counts the most common hematologic malignance among African-Americans with twice the incidence of whites. The outcomes have greatly improved during the last 15 years, however with changing demographics there is an increasing focus on how various subgroups, based on race and ethnicity may be benefiting from survival improvement in MM. Previous studies showed that if access to care is assured, racial disparity-driven differences in outcome may be mitigated. Here, we conducted a study using the National Cancer Data Base (NCDB), which covers more than 70% of cancer pts in the USA, to evaluate survival patterns by race. Methods: MM patients (pts) diagnosed between years 2005 and 2014 and reported to the NCDB were analyzed (n = 117926). Pts were divided in three groups based on the year (y) of diagnosis (2005-07, 2008-10 and 2011-14). Kaplan-Meier method and log-rank test were used for overall survival analysis (OS). The effect size, hazard ratio (HR), of race on OS was estimated by Cox model adjusted by confounders. Results: Median age at diagnosis was 67 y (19 - 90); 55% were males. Median follow up was 30 months (m) (0 - 145). Median OS for white and black pts was 46 m (95% CI: 45.4 - 46.6) and 50.6 m (95% CI: 49.1 - 52.3), respectively (p < 0.0001). Black had longer OS compared to white pts by univariable analysis in all three study periods, noticeably with a trend toward higher survival benefit in most recent years. After adjusting for a variety of factors there was no statistically significant difference between the two racial groups (Table). Conclusions: This large study confirmed that after adjusting for confounding factors survival is similar for white and black MM pts. [Table: see text]
Evaluation of Electronic Activity Monitors (EAMs) during phase I clinical trials.
Authors: Scaranti Mariana , Sundar Raghav , Daly Robert , Collins Dearbhaile Catherine , Dolling David , Gennatas Spyridon , Rao Baikady Bindumalini , Kaye Stan B , Banerji Udai , Lopez Juanita Suzanne , De Bono Johann S. , Minchom Anna Rachel 
Published: May 2019

e18175 Background: EAMs are wearable devices that record aspects of activity, including heart rate and step count. Medical oncologists use performance status (PS) (such as ECOG and Karnofsky) to assess patient’s physical function and to aid treatment decisions. These are subject to patient and physician bias. Our study evaluated the use of EAMs (Fitbit ®) during phase I trials, correlating EAM indices with PS and patient outcomes. Methods: We recruited patients in an academic hospital Drug Development Unit. Patients participating in a phase I trial consented to wear an EAM prior to starting and during the first treatment cycle. Physicians assessed PS at 4 timepoints. Outcomes (progression free survival (PFS), overall survival (OS), adverse events) were recorded. Results: Twenty-five patients were enrolled. At the time of data analysis results were available for 16 patients. Patients wore the EAM for an average of 70.3% (standard deviation 21%) of their time on study, defined as time with recordable heart rate. Mean step count per day varied with ECOG PS although the correlation did not reach statistical significance (co-efficient -1611.1 steps for each change in ECOG PS, p = 0.07, mixed effect regression model). A higher mean step count/day correlated with longer OS (HR0.67, p = 0.01, Cox proportional hazard model). Physician-assessed PS did not correlate with OS (HR2.65, p = 0.37, Cox proportional hazard model). There was no correlation between mean step count and PFS (HR1.7, p = 0.39, Cox proportional hazard model). Conclusions: The use of EAMs is feasible in this patient group. A higher step count correlated with longer OS whereas physician-assessed PS did not. Further research into the potential of EAMs as a means of predicting patient survival to guide decisions on eligibility for phase I trials and the potential for devising a revised Royal Marsden prognostic score incorporating EAM indices is warranted. Clinical trial information: SE536. [Table: see text]
Impact of timing of palliative care team consults in patients with advanced cancer.
Authors: Bemis Thomas , Baratam Praneeth , Seiders Dawn , Ward Kristine Marie , Styler Michael 
Published: May 2019

e18182 Background: The 2018 ASCO palliative care guidelines recommend palliative care team (PCT) involvement within 8 weeks for patients with an advanced cancer diagnosis. However, the optimal timing of PCT consults in the inpatient setting has not been established. We investigated whether early PCT involvement for in-patients with an advanced cancer diagnosis affected discharge outcomes. Methods: We queried the Hahnemann University Hospital’s Palliative Care In-patient database between 2015 and 2018 for patients with advanced cancer and an estimated life expectancy of < 6 months. Dates of admission, initial PCT consult and discharge were examined. PCT consults within 7 days of admission were defined as early consults and those > 7 days as late consults. Chi square analysis was used to determine differences in LOS and time from PCT consult to discharge between the two groups. Cost-savings estimates were based on the Kaiser State Health Facts, which list an average cost per inpatient day in US hospitals of $2,289 in nonprofit and $1,791 in for-profit hospitals. Results: The majority of cases (69.7%) had PCT involvement < 7 days from admission and were associated with an overall shorter LOS of 12 days compared to 30 days with consults called > 7 days (p = < 0.001). Furthermore, early PCT involvement led to a 2-day shorter time to discharge (p = < 0.02) for an average cost-savings of at least $4,578 at a non-profit hospital and $3,582 at a for-profit hospital. Conclusions: Our findings show that the majority of patients at our institution with advanced cancer had early PCT involvement, which was associated with reduced hospital length of stay. These findings suggest that PCT involvement may expedite hospital discharge and by extension lead to increased cost-savings and patient quality of life. Future studies will aim to investigate the impact of early PCT involvement on hospital readmission rates and discharge to hospice care among other indicators of improved patient well-being.[Table: see text]
Venous thromboembolism in breast cancer patients receiving cyclin-dependent kinase inhibitors.
Authors: Gervaso Lorenzo , Montero Alberto J. , Jia Xuefei , Khorana Alok A. 
Published: May 2019

e18184 Background: Venous thromboembolism (VTE) complicates several anti-cancer regimens including chemotherapy and anti-angiogenic agents. Cyclin-dependent kinase 4/6 inhibitors (CDKIs) are a new approach for hormone receptor positive (HR+) metastatic breast cancer (mBC). Reported VTE rates in randomized trials range from 0.6% for ribociclib (MONALEESA-2) to 2% for palbociclib (PALOMA-3) and 5% for abemaciclib (MONARCH-3) but these may underestimate actual rates compared to patients in clinical practice who are generally older and have greater comorbidities. Little is known about real world incidence or prevalence of VTE with CDKIs in mBC. The aim of this study was to evaluate rates of VTE in clinical practice and association with outcomes in mBC patients on CDKIs. Methods: We conducted a retrospective cohort study at Cleveland Clinic Taussig Cancer Institute, approved by the institutional review board. We identified consecutive mBC patients who received any of three FDA-approved CDKIs (palbociclib, ribociclib, abemaciclib) from 1/2015 through 12/2017. VTE including deep venous thrombosis (DVT) and pulmonary embolism (PE) were identified by electronic medical record review. Overall survival (OS), progression free survival (PFS) and time to VTE were estimated by the Kaplan-Meier method and evaluated for association with VTE using Cox proportional hazard regression. Results: The study population included 424 patients, with a median age at diagnosis of 54.76 yrs, (range 27 -85). Palbociclib was the most commonly used CDKI (n = 390, 91.8%); 27 patients (6.3%) received more than one drug. VTE during CDKI therapy occurred in 9% of patients (n = 38), including DVT in 52.6% (n = 20), PE in 18.5% (n = 7) and visceral vein thrombosis (VVT) in 15.8% (n = 6). Median time to VTE was 314 days, and 6-months rate was 4.1%. VTE was associated with numerically worse PFS and OS, but this was not statistically significant (PFS [HR 1.25, 95% CI 0.73 – 2.14, p = 0.42], OS [HR 1.60, 95% CI 0.89 – 2.87, p = 0.12]). Conclusions: VTE affected nearly 10% of breast cancer patients receiving CDKIs, 2- to 5-fold greater than reported in registration trials. Further work is necessary to identify pathophysiology, risk factors and benefit of thromboprophylaxis.
Does adding claims to EMR data improve comorbidity burden capture? A Concerto Health AI Definitive Oncology Dataset and Symphony Linkage Study.
Authors: Wong William Bruce , Pal Navdeep , Wu Ning , Chen Li , Sheinson Daniel , Chu Laura Kay 
Published: May 2019

e18186 Background: Current commercially available oncology electronic medical record (EMR) databases typically have limited data on patient comorbidities which may limit the ability to accurately include/exclude these patients or adjust for these factors in health outcomes research. The objective of this study was to investigate the impact of identifying comorbidities using both EMR and claims data. Methods: The Concerto Health AI Definitive Oncology Dataset is a deeply curated cohort of patients (pts) derived from a wide range of oncology practices throughout the United States. Concerto Health AI has a co-exclusive partnership with ASCO CancerLinQ and collects data from multiple other sources. These data were deterministically linked to US Symphony Health’s (SH) Integrated Dataverse, an anonymized, HIPAA-compliant data set. Advanced (stage IIIb/IV) non-small cell lung cancer (aNSCLC) pts with data curated via manual review by nurse practitioners and diagnosed after 2011 were included. Comorbidities within 1 year prior to advanced diagnosis were categorized using the Charlson Comorbidity Index (CCI). The impact of the claims linkage on inclusion/exclusion (I/E) criteria was assessed by applying criteria from the IMpower150 clinical study and exploring changes to survival estimates, as calculated using Kaplan-Meier method. Results: A total of 11,373 aNSCLC pts were identified, of which 7,887 pts were linked to SH. Using only Concerto, 278 pts (3.5%) had a CCI score ≥1, whereas 3,033 pts (38.4%) had a CCI score ≥1 using linked Concerto and SH. After applying I/E criteria from IMpower150 using available data elements from Concerto only, 88 pts were identified matching the trial criteria, with a median survival of 15.8 mths (95% CI: 14.4, 21.0). When leveraging Concerto and SH, 8 (9.1%) more patients were excluded (n = 80) based on comorbidities (6 pts) and oral medications (2 pts), with a median survival of 16.6 mths (95% CI: 14.6, 23.4). Conclusions: The addition of claims to EMR enhanced the ability to identify patient comorbidities given the longer history and broader physician specialty of claims data. Future real-world studies should explore linkages across datasets to better capture comorbidities for patient selection and adjustment.
Effect of right censoring bias on survival analysis.
Authors: Barrajon Enrique , Barrajon Laura 
Published: May 2019

e18188 Background: Survival Kaplan-Meier analysis represents the most objective measure of treatment efficacy in oncology, though subjected to potential bias which is worrisome in an era of precision medicine. Independent of the bias inherent to the design of clinical trials, bias may be the result of patient censoring, or incomplete observation. Unlike disease/progression free survival, overall survival is based on a well defined time point and thus avoids interval censoring, but it is our claim that right censoring, due to incomplete follow-up, may still be a source of bias. Methods: The R version 3.5.1 language and the integrated development environment RStudio were used for simulations and survival analysis with the survival package and their available datasets . Survival time was simulated according to a Weibull model with 2 parameters, shape and scale, that determine the event time for every case. Three types of right censoring mechanisms are considered and analyzed independently: 1) case censoring, in which a random number of cases are censored, and the resulting survival time is shortened by a random amount, 2) time censoring, in which a random censoring time variable is applied if and only if it is shorter than the event time, and 3) interim censoring, where a random time variable determines the case inclusion time since the start of trial, and a fixed cutt-off time determines if every case is censored (if the cutt-off time is shorter the the inclusion time plus the event time) or not. For every censoring mechanism, 100 trials was simulated with a 1000 uncensored cases arm and 1000 censored cases arm, in such a way that a censoring Cox hazard ratio (cHR) may be estimated for every trial. An interactive app showing the right censoring effect is presented. Results: A bias index (BI) was buit based on the survival time of event and censored cases. Case censoring was associated with higher BI (mean = 1.75, SD = 0.29) than time censoring (mean = 1.15, SD = 0.19, p = 2.02e-30) and interim censoring (mean = 0.72, SD = 0.21, p = 3.46e-34). It was found an inverse relationship between the censoring proportion and the cHR in case censoring (r = -0.86). Of all the available datasets, the Veterans' Administration Lung Cancer study showed a bias of 1.83, suggesting case censoring bias in both treatment arms. Conclusions: Based in the results of this study it is suggested that: 1) Final results should include all the events in the defined period of interest, 2) a bias index may help in detecting potential bias and correct estimated survival. Censoring bias analysis is planned in recent clinical trials.