bluuebunny/crossref_metadata_2025_split huggingface dataset:
Use of patient-reported outcomes (PROs) to predict treatment outcomes in patients with advanced cancer.
Authors: Parikh Aparna Raj , Van Seventer Emily E. , Fish Madeleine , Fosbenner Kathryn , Kanter Katie , Mojtahed Amirkasra , Allen Jill N. , Blaszkowsky Lawrence Scott , Clark Jeffrey William , Du Bois Jon S. , Franses Joseph Wang , Giantonio Bruce J. , Goyal Lipika , Klempner Samuel J , Roeland Eric , Ryan David P. , Weekes Colin D. , Horick Nora K. , Corcoran Ryan Bruce , Nipp Ryan David 
Published: October 2020

186 Background: PROs assessing quality of life (QOL) and physical symptoms often correlate with clinical outcomes in patients (pts) with cancer. Yet, data are lacking about the use of PROs to predict treatment response. We evaluated associations of baseline PROs with treatment response, healthcare use, and survival among pts with advanced gastrointestinal cancer. Methods: We prospectively enrolled pts with metastatic gastrointestinal cancer prior to initiating chemotherapy at Massachusetts General Hospital. At baseline (start of treatment), pts reported their QOL (Functional Assessment of Cancer Therapy General [FACT-G], subscales assess QOL across 4 domains: functional, physical, emotional, social well-being) and symptom burden (Edmonton Symptom Assessment System [ESAS]). Higher scores on FACT-G indicate better QOL, while higher scores on ESAS represent a greater symptom burden. We used regression models to examine associations of baseline PRO scores with treatment response (clinical benefit [CB] or progressive disease [PD] at the time of first scan based on clinical documentation), healthcare use (unplanned hospital admissions), and survival. Results: From 5/2019-3/2020, we enrolled 112 of 131 (85.5% enrollment) consecutive pts (median age = 62.8, 61.6% male, 45.5% pancreatobiliary cancer). For treatment response, 64.3% had CB and 35.7% had PD. Higher ESAS-physical (B = 1.04, p = .027) and lower FACT-G functional (B = 0.92, p = .038) scores at baseline were significant predictors of PD. On the specific ESAS items, pts who experienced PD were more likely to report moderate/severe poor well-being (57.9% vs 29.7%; p = .001), pain (44.7% vs 25.0%; p < .050), drowsiness (42.1% vs 20.3%; p = .024), and diarrhea (23.7% vs 4.7%; p = .008) at baseline. Lower FACT-G total (HR = 0.96, p = .003), FACT-G physical (HR = 0.89, p < .001), FACT-G functional (HR = 0.87, p < .001), and higher ESAS-physical (HR = 1.03, p = .028) scores at baseline were significantly associated with greater risk of hospital admission. Lower FACT-G total (HR = 0.96, p = .009), FACT-G emotional (HR = 0.87, p = .014), as well as higher ESAS-total (HR = 1.03, p = .018) and ESAS-physical (HR = 1.03, p = .040) scores at baseline were significantly associated with greater risk of death. Conclusions: We found that baseline PROs predict treatment response in pts with advanced cancer, namely physical symptoms and functional QOL, in addition to healthcare use and survival outcomes. These findings further support the use of PROs to predict important clinical outcomes, including the novel finding of treatment response.
Trends in short-term, long-term, and high-risk opioid use among older cancer patients.
Authors: Salans Mia A , Riviere Paul , Vitzthum Lucas , Nalawade Vinit , Murphy James Don 
Published: October 2020

187 Background: While opioids represent a cornerstone of cancer pain management, the timing and patterns of persistent and high-risk opioid use in the context of the ongoing opioid epidemic are not well studied. This study sought to explore longitudinal trends in short-term, long-term, and high-risk opioid use among older cancer patients. Methods: Within a cohort of 84,994 Medicare beneficiaries ≥ 65 years old diagnosed with cancer between 2007 and 2013, we determined the likelihood of being prescribed an opioid after cancer diagnosis (0-6 months, 6-12 months, and 1-2 years post-diagnosis) and of receiving a daily morphine equivalent dose (MED) ≥ 200 mg, a dose associated with higher opioid-related mortality. Multivariable logistic regression models were used to identify patient and cancer risk factors associated with outcomes. Results: The rates of opioid prescription at 0 to 6 months, 6 to 12 months, and 1 to 2 years after diagnosis were 60.7%, 32.7%, and 38.2% respectively. Among patients who were prescribed an opioid, 4.0% received a MED ≥ 200 mg within 2 years of diagnosis. The likelihood of opioid prescription 0 to 6 months after diagnosis increased over the study period (OR = 1.05 per year, CI = 1.04 to 1.06), while the likelihood of opioid prescription 6 to 12 months (OR = 0.98 per year, CI = 0.97 to 0.99) and 1 to 2 years (OR = 0.98 per year, CI = 0.97 to 0.99) after diagnosis decreased over the study period. The probability of receiving a MED ≥ 200 mg decreased over the study period (OR = 0.98 per year, CI = 0.96 to 0.99). On multivariable analysis, Black (OR = 1.14, CI = 1.06 to 1.23) and American Indian/Native Alaskan (OR = 1.46, CI = 1.06 to 2.02) patients were more likely to receive opioids 1 to 2 years after diagnosis. Patients living in areas with higher rates of poverty (OR = 1.40, CI = 1.32 to 1.48) were also more likely to receive an opioid 1 to 2 years after diagnosis. Black (OR = 1.72, CI = 1.59 to 1.86), Asian (OR = 1.46, CI = 1.19 to 1.80), and Hispanic (OR = 1.36, CI = 1.23 to 1.51) patients were more likely to receive a MED ≥ 200 mg. Conclusions: While the rate of short-term opioid use is rising, rates of persistent and high-risk opioid use are declining among cancer patients. This may reflect growing awareness of the dangers of opioid misuse among clinicians treating patients with cancer. Nevertheless, racial and socioeconomic disparities in patterns of opioid use are persistent in the cancer population.
Multisite quality improvement initiative to repair incomplete electronic medical record documentation as one contributor to provider burnout.
Authors: Russo Carolyn , Raney Lauren , McManaman Joanne , Elsaid Mohamed , Morgan Jennifer , Bowman Ronda Marie , Mohamed Ashraf Mahmoud 
Published: October 2020

190 Background: Provider burnout is a challenge adversely affecting the quality, safety, and cost of health care. We measured burnout among pediatric oncology providers in the St. Jude Affiliate network and used a Plan-Do-Study-Act (PDSA) improvement cycle to address one of the factors contributing to burnout. Methods: Within the framework of the American Society of Clinical Oncology (ASCO) Thematic Quality Training Program (QTP) we sent the Mini Z 2.0 Survey to 47 pediatric oncology providers. Applying a fishbone diagram and Pareto chart we analyzed potential causes of provider burnout. Based on the analysis, we used a PDSA approach to address documentation of oral chemotherapy adherence for children with acute lymphoblastic leukemia to mitigate burnout among providers. Results: The burnout survey response rate was 44.6%. Burnout was identified in 42.9% of providers. Documentation in the electronic medical record (EMR) was cited as the second most common contributor to burnout, and it was this issue we chose to address based on a priority matrix. We improved the completeness of oral chemotherapy documentation from a baseline of 13% compliance to 87% compliance within 3 months. The improved compliance was achieved by standardizing the documentation process in the EMR for content and location. Conclusions: The EMR was one of the contributing factors in the burnout survey of the pediatric oncology providers in the St. Jude Affiliate network. A PDSA improvement model to improve clinical research documentation was successful in addressing one of several contributing factors to provider burnout.
The association between clinical trial (CT) participation, pharmaceutical costs, and savings performance in the Oncology Care Model (OCM).
Authors: Adelson Kerin B. , Canavan Maureen , Mun Sophia , Gross Cary Philip , Sinanis Naralys , Davidoff Amy J. 
Published: October 2020

2 Background: The OCM is a Centers for Medicare and Medicaid Services (CMS) alternative payment model, which seeks to curb costs while improving care for patients receiving systemic cancer therapy. CMS models the expected spending target for each 6-month episode using historical, geographic and clinical factors, including CTr participation. We evaluated the relationship between CTr participation, drug costs and performance in the OCM. Methods: We used claims for OCM episodes attributed to the Yale Cancer Center between July 2016 and July 2018. We stratified episodes by CTr participation and used t-tests and chi-square tests to compare total cost, drug costs (Part B, Part D and novel cancer therapies) and whether observed episode costs were above or below CMS targets. Analyses were conducted for the total sample and among the most common cancer types. Results: Among 9,387 OCM episodes (5,270 unique patients), 815 (8.7%) episodes involved a CTr. Among non-CTr patients, the mean Medicare cost per episode ($32,909) was modestly higher than the mean episode spending target ($31,746; p < 0.001), while in the CTr group, the mean Medicare cost per episode ($36,590) was substantially lower than the mean episode spending target ($48,124 p < 0.001). CTr episode costs were more likely to be under spending targets than non-CTr episodes (66% vs 56%, p < 0.001) overall and in breast, lung, and myeloma cancers, although only statistically significant for lung cancer (76% CTr vs 48% non-CTr, p < .001). Overall, non-CTr had significantly higher mean Part D drug costs per episode ($8,441 vs $3,893, p < 0.001), which was also noted among patients with lung cancer, ovarian cancer and lymphoma. Non-CTr episodes were also associated with higher mean novel therapies cost ($5,736) compared with CTr patient episodes ($4,346, p = 0.013). When comparing the sum of all other expenditures, CTr episodes were significantly associated with higher non-pharmaceutical expenditures than non-CTr episodes ($20,940 vs. $13,323, p < 0.001) overall. Conclusions: Episodes with CTr participation out-performed non-CTr episodes in achieving savings relative to CMS spending targets. Savings were driven by lower drug costs for the CTr episodes, particularly in the categories of Part D and novel cancer therapies. This suggests that CTr enrollment shifts costs for expensive pharmaceuticals away from CMS and toward the CTr study sponsor. Further research should explore whether this finding is generalizable to other cancer centers and payment models.
Characteristics and outcomes of patients (pts) who developed immune-related adverse events (irAEs) with an initial presentation in the emergency department (ED).
Authors: Holstead Ryan , Kartolo Baskoro , Baetz Tara D. 
Published: October 2020

201 Background: Management of irAEs due to immune checkpoint inhibitors (ICIs) requires a high degree of suspicion, and management of severe irAEs require timely initiation of corticosteroids (CS). This can be challenging in the ED, where providers may not be aware of an individual pt’s cancer treatment or its toxicities. Methods: We performed a retrospective single-center chart review for pts treated with ICIs in 2018 and 2019 who subsequently presented to ED. New irAEs with first presentation in ED were analyzed and pt outcomes were recorded. Descriptive statistics compared this population to irAEs identified in outpatient setting, as well as rates of ED utilization in pts on doublet ICI (dICI). Results: Of 351 evaluable pts treated with an ICI, 129 (37%) had at least one presentation to ED. Seventeen pts had a first presentation of a new irAE. These pts had received a median 2 cycles of ICI prior to presentation (interquartile range [IQR] 1-3) Twelve of these pts presented with generalized fatigue or pain, twelve required admission, 4 were admitted to intensive care within 30 days, and two died. Toxicities included hypophysitis (5), arthritis (2), colitis (2), myocarditis (2), neuritis (2), pneumonitis (2), adrenalitis (1), hepatitis (1). Median admission was 8.5 days (IQR 2-32), and median time to corticosteroids was 30.5 hours (range 4-269). Grade 3 or higher toxicity was more frequent in the ED pts compared to the total ICI pt population (70.5% vs. 32.2%). Pts on dICI (n = 41) had a higher rate of ED utilization (n = 23, 56.1%) and ED visits were more likely to be for first presentation of a new irAE (n = 7, 30.4% of dICI ED visits) compared to single-agent ICI regimens. Conclusions: Pts with irAEs that first present at the ED often have generalized symptoms, prolonged hospitalizations, and can have long delays to initiation of CS. Development of a protocolized approach for pts on ICI at the point of care in the ED may improve identification of irAEs, ‘door-to-steroid’ time, and patient outcomes.
Comparing cancer survivors' perceptions on lifestyle behaviors between adolescent-young adult (AYA) and middle-aged patients (pts).
Authors: Soberano Spencer , Eng Lawson , Chen RuiQi , Altesha Ashraf , Nagaratnam Subiksha , Rudolph-Naiberg Sarah , Chotai Simren , Wang Wanning , Lu Lin , Xu Wei , Hueniken Katrina , Brown Catherine , Liu Geoffrey 
Published: October 2020

207 Background: Lifestyle behaviours such as smoking, physical activity, and alcohol consumption are important determinants of cancer survivorship. Previous studies have compared the lifestyle behaviours of elderly and middle-aged patients (pts), yet no studies have compared these behavioural perceptions between AYA (aged 18-39 years) to those of middle-aged pts (MA, 40-64 years). Methods: Cancer pts across various tumour types at a comprehensive cancer centre were surveyed with respect to their perceptions of how their well-being was affected by smoking, physical activity and alcohol consumption after diagnosis. Univariate logistic regression models evaluated factors associated with perceptions on the effect of various adverse lifestyle behaviours on health and well-being. Results: Of 200 AYA (57% female, 43% male) and 772 MA (56% female, 44% male) pts, a positive smoking history was reported by 33% of AYA and 48% of MA (P<0.001). At time of diagnosis, 55% of AYA and 59% of MA pts consumed alcohol, 16% of AYA and 16% of MA were ex-drinkers, and 28% of AYA and 25% of MA were never drinkers (P=0.62). Among AYA, 26% exercised compared to 20% in the MA group (P=0.19). The majority (72-92%) of pts perceived that smoking and lack of activity after cancer diagnosis negatively affected quality of life, survival chances, and fatigue; there were no significant differences between age groups. In contrast, both age cohorts displayed misperceptions about how alcohol affects health, which was characterized by perceiving neutral or beneficial influence on their overall well-being: Fifty-seven percent of MA pts had a borderline greater misperception versus 49% of AYA pts (P=0.06). Misperceptions regarding how alcohol affects survival were observed in 49% of AYA pts and 58% of MA pts (P=0.05). Misperception with respect to how alcohol affects fatigue was observed in 40% of AYA pts compared to 52% of MA pts (P=0.005). Furthermore, MA pts had 1.63 (95% CI 1.16–2.29) times the odds to have misperceptions regarding how alcohol affects fatigue, and 1.41 (95% CI 1.01–1.97) times the odds to have misperceptions on how alcohol affects survival compared to AYA pts. Conclusions: Both the AYA and MA population were not adequately informed about how alcohol affects cancer survivorship health; with more misperceptions in MA pts. Results from this study advocate for survivorship programs to implement emphasis on the deleterious effects of alcohol, with particular efforts tailored to the MA group.
Strategies for comprehensive implementation of survivorship care: A qualitative analysis of CoC-accredited cancer programs.
Authors: Hwang Soohyun , Bozkurt Burcu , Huson Tamara , Asad Sarah , Richardson Lauren , Ogbansiegbe Joseph , Viera Laura , Buse Caroline , Mayer Deborah , Shulman Lawrence N. , Birken Sarah A. 
Published: October 2020

209 Background: The Commission on Cancer (CoC) seeks to promote comprehensive approaches to implementing survivorship programs among accredited cancer programs. In practice, cancer programs’ approaches range from cursory (e.g., developing care plans without robust services) to comprehensive (e.g., facilitating follow-up care). This study identified strategies that were unique to cancer programs with comprehensive approaches to implementing survivorship programs. Methods: We sampled 39 CoC-accredited cancer programs with approaches to survivorship program implementation ranging from cursory to comprehensive, as reported in CoC annual surveys. Within sampled cancer programs, we conducted in-depth semi-structured interviews with a total of 42 healthcare professionals (1-2/program). We identified strategies unique to cancer programs with comprehensive approaches by comparing them to cancer programs with cursory approaches. Results: Cancer programs with comprehensive approaches to implementing survivorship programs had formal committees with ample opportunities to evaluate the progress, revise roles, and acquire multiple stakeholders’ support. Keeping a good record system enabled these cancer programs to meet accreditation requirements and improve processes. Buy-in from upper management and key physicians was deemed crucial in leveraging cancer program resources. These programs also had clear roles with shared accountability among multidisciplinary groups. Like cancer programs with comprehensive approaches to implementing survivorship programs, many cancer programs with cursory approaches also had formal committees; however, cancer programs with cursory approaches lacked buy-in from key stakeholders, relying on few staff or a champion for implementation. Cancer programs with cursory approaches had limited resources, cumbersome processes, and team members with unclear roles. Conclusions: Cancer programs with comprehensive approaches to survivorship program implementation gained broad stakeholder buy-in and established clear team member roles with shared accountability. Study findings will inform more than 1500 CoC-accredited US cancer programs’ approaches to implementing survivorship programs. At the conference, we will have results from quantitative and measures validation companion studies.
Factors determining oncology on-call service utilization and implications for quality improvement.
Authors: Wronska Marta Wioleta , Braunstein Marc Justin , Islam Shahidul 
Published: October 2020

213 Background: Most ambulatory oncology practices utilize an on-call service that is essential for continuity of cancer care after office hours, yet there is limited literature about the dynamics of this care delivery model and how to improve it from a quality standpoint. We hypothesize that patients with more advanced cancers are more likely to require the on-call service due to acute symptoms arising during their treatment, and that this information can be used to create a risk model to predict subsequent hospitalization. Methods: We performed a single-center, retrospective review of sequential overnight and weekend calls received by an oncology practice with 16 physicians over a 20-week period from January-May 2020. Calls were classified as being either urgent, requiring immediate attention, or non-urgent, which could be addressed during office hours. Data were summarized using descriptive statistics, continuous and categorical variables were compared using Wilcoxon rank-sum test and Fisher’s exact test, respectively. Multivariate analyses were estimated by logistic regression using the penalized maximum likelihood estimation method. Results: The data set included 236 consecutive calls among 176 patients, with 65% females and median age of 68 (range: 25-87). Of these, 185 calls (78.4%) were deemed urgent, among which 139 (75%) were symptom-related. Among the 202 calls (85%) from patients with cancer, 164 (81%) of them were urgent, mostly due to symptoms (82%). Of these urgent calls, 44 (27%) resulted in admission within 24 hours (P < 0.0001), primarily related to treatment toxicity or disease progression (81%). Patients with stage 4 cancers (42%) or hematologic malignancies (28%) were more likely to use the on-call service. There was no significant difference between call urgency and treatment regimen (P = 0.06). In a multivariable model, advanced age [OR = 1.03(1.0-1.07)] and urgent calls [OR = 33.1(2.7-401.0)] were independently associated with risk of hospitalization. Of note, there were no differences in admissions before or after the peak of the COVID-19 pandemic in New York City (P = 0.49). Conclusions: We identified an association between after-hours calls and more advanced malignancy, which was independent of treatment regimen. The majority of on-call issues were urgent and symptom-related, with advanced age and urgent calls being most likely to result in hospital admission. These results suggest that strategies can be developed to prevent hospitalizations in patients at higher-risk for adverse events based on a multivariable risk model.
The impact of social determinants on receipt of colonoscopy in an under-resourced hospital service area: A retrospective cohort study.
Authors: Dhahri Amina , Azargoon Sam , Gandhi Darshan , Barot Dhruvi , Goli Himan , Mahjoob Homayoon , Tegene Teshome , Ntiri Shana 
Published: October 2020

216 Background: Although colorectal cancer (CRC) screening with colonoscopy reduces the risk of CRC mortality, screening rates remain low among African Americans and low social economic status (SES) patients. However, few studies have assessed CRC screening rates in under-resourced hospital service areas. Using a granular measure of socioeconomic deprivation (SED), we examined the association between social determinants and CRC screening. Methods: We conducted a retrospective cohort study from 2014-2019 to identify primary care patients referred for CRC screening with colonoscopy at an academic hospital system. Patients were assessed at annual visits for completion of colonoscopy. SED was assessed using the area deprivation index (ADI), a composite measure of 17 SED indicators including income, housing, education, and employment at the census block group level. Other social determinants analyzed were race and insurance status. Frequency and multivariable logistic regression were used for statistical analysis. Results: 1040 patients met CRC screening guidelines and were referred for colonoscopy. 136 (13.1%) underwent colonoscopy in the follow-up period. High and low SED made up 655 (63%) and 77 (7.4%) of patients, respectively. SED, race, age, and sex were not associated with higher screening rates. Uninsured patients had a lower rate of screening. After controlling for other social determinants, uninsured patients had the lowest odds of colonoscopy (OR 0.28; 95% CI, 0.08-0.92). Conclusions: In this under-resourced hospital service area, receipt of colonoscopy for CRC screening is significantly lower than previously reported. Furthermore, screening rates were persistently low across strata of SED, race and insurance status, with uninsured patients having the lowest odds of screening. These data suggest that in an under-resourced hospital service area with extensive SED, further research is needed to understand the role of social determinants and behavioral factors to address disparities in CRC screening with colonoscopy. [Table: see text]