bluuebunny/crossref_metadata_2025_split huggingface dataset:
Priority levels in cancer patients admitted to medical intensive care at a safety net hospital.
Authors: Epistola Raisa , Shodiya Michael Olufemi , Epistola Jordan , Chang Dong , Yeh James Jen-Chi 
Published: June 2021

e18599 Background: Admissions of cancer patients to intensive care units (ICU) are increasing with improved mortality. While ICU care can be lifesaving, its higher cost does not always result in reduced mortality. Moreover, timely goals of care (GOC) discussions correlate with less ICU use in those with certain cancers. We investigate if hospital mortality and disposition outcomes for cancer patients correlate to triage by ICU providers. Methods: This subgroup analysis of a prospective cohort of 808 patients admitted to the ICU from 1 July 2015- 15 June 2016 at an academic safety net hospital included 106 patients diagnosed with cancer. Medical records were reviewed by ICU physicians, who assigned priority ranks using Society of Critical Care Medicine guidelines: 1: critically ill, needing treatment/monitoring not provided outside of ICU, 2: not critically ill, but requiring close monitoring/potentially immediate intervention, 3: critically ill patients with reduced likelihood of recovery, 4: not appropriate for ICU, equivalent outcomes achieved with non-ICU care. We did a chart review for factors like prior therapy and documentation of GOC discussions. Statistical tests were conducted to examine if priority levels correlate with disposition, mortality, and length of stay (LOS). Results: χ2-tests revealed priority rank correlated with disposition after hospitalization (p<.05) with group 3 having the highest proportion of deaths and lowest proportion of discharges home. It revealed that mortality rate differed by group (p<.05) with logistic regression showing that priority 3 predicted increased mortality (p<.05). ANCOVA indicated ICU LOS differed by priority group (p<.05), with priority 3 averaging the longest LOS. While priority 3 had the most in-hospital GOC discussions, relatively few were documented pre-hospitalization. Conclusions: Overall, our patients were accurately triaged, with worse mortality and discharge outcomes among priority 3 and a dearth of pre-hospitalization GOC documentation for all groups. Our data show the importance of triaging patients and having early, frequent GOC discussions to minimize ICU admission given increasing demand and costs. GOC discussions are associated with less aggressive medical care near death and better patient quality of life. Thus, holding these talks with our sickest patients prior to potential ICU admission is an area to improve cost-effective high quality care.[Table: see text]
The effect of neoadjuvant chemotherapy on quality of life for patients with muscle invasive bladder cancer (MIBC) undergoing cystectomy.
Authors: Sossenheimer Christina , Cizik Amy , Lenherr Sara , O Neil Brock , Dechet Christopher B. , Sanchez Alejandro , Tward Jonathan David 
Published: June 2021

e18614 Background: To examine the relationship between neoadjuvant chemotherapy (NAC) clinical risk factors, and patient reported quality of life in patients with MIBC undergoing cystectomy. Methods: cT2-T4, N0, M0 MIBC patients who underwent radical cystectomy were identified from a prospectively maintained institutional outcomes database. PROMIS-Ca surveys (physical function (PF), pain interference, fatigue, depression, and anxiety domains) were administered at consultation and follow-up as part of routine clinical care. Patients were stratified as receiving NAC vs. none and surveys were anchored to date of cystectomy. Non-parametric kernel regressions with variance-covariance matrix bootstrapping were used to estimate the mean effect of covariates on each domain T-score with 95% confidence intervals. Covariates were: body mass index, smoking history, age, Charlson comorbidity score, pT and pN stage, urinary diversion-type, and survey time relative to the cystectomy date. T-score changes over time were modeled by including univariable parameters with a P<=0.1 in a multivariable model (MVA) for each domain and predicting the marginal means at date of cystectomy, 6 and 12 months postop. Results: The median age was 68 (IQR 60-73) years. NAC was received by 69/134 patients (40 Gem/Cis, 24 MVAC, 5 unknown). On univariate analyses NAC significantly reduces PF (mean change in t-score, 95%CI; -2.4, -3.7 to -0.8, p=0.001), trends toward more pain (0.94, -0.20 to 1.78, p=0.074), but does not influence fatigue, depression or anxiety. Other covariates with p<0.05 reducing PF were BMI (-0.31, -0.53 to -0.03), pT4 vs pT1-2 (-0.31, -0.53 to -0.03), Charlson 1 vs 0 (-0.31, -0.53 to -0.03), age (-0.31, -0.53 to -0.03), and days from surgery (-0.31, -0.53 to -0.03). Table shows how t-scores predicted from the MVA change over time. Conclusions: MIBC patients have mild to moderate impairment in physical function, fatigue, and pain before and after cystectomy, suggesting a need for increased focus on rehabilitation and wellness programs. Although the univariable analysis implies there may be differences in PF and Pain for those receiving NAC vs none, future studies with increased power are needed to properly adjust for the interplay of other significant covariates.[Table: see text]
Impact of cancer on emergency department outcomes.
Authors: Qian Alexander S. , Qiao Edmund M. , Nalawade Vinit , Voora Rohith S. , Kotha Nikhil V. , Dameff Christian , Coyne Christopher John , Murphy James Don 
Published: June 2021

e18618 Background: Cancer patients frequently utilize the Emergency Department (ED) for a variety of diagnoses, both related and unrelated to their cancer. Patients with cancer have unique risks related to their cancer and treatment which could influence ED-related outcomes. A better understanding of these risks could help improve risk-stratification for these patients and help inform future interventions. This study sought to define the increased risks cancer patients face for inpatient admission and hospital mortality among cancer patients presenting to the ED. Methods: From the National Emergency Department Sample (NEDS) we identified patients with and without a diagnosis of cancer presenting to the ED between 2016 and 2018. We used International Classification of Diseases, version 10 (ICD10-CM) codes to identify patients with cancer, and to identify patient’s presenting diagnosis. Multivariable mixed-effects logistic regression models assessed the influence of cancer diagnoses on two endpoints: hospital admission from the ED, and inpatient hospital mortality. Results: There were 340 million weighted ED visits, of which 8.3 million (2.3%) occurred in patients with a cancer diagnosis. Compared to non-cancer patients, patients with cancer had an increased risk of inpatient admission (64.7% vs. 14.8%; p < 0.0001) and hospital mortality (4.6% vs. 0.5%; p < 0.0001). Factors associated with both an increased risk of hospitalization and death included older age, male gender, lower income level, discharge quarter, and receipt of care in a teaching hospital. We identified the top 15 most common presenting diagnoses among cancer patients, and among each of these diagnoses, cancer patients had increased risks of hospitalization (odds ratio [OR] range 2.0-13.2; all p < 0.05) and death (OR range 2.1-14.4; all p < 0.05) compared to non-cancer patients with the same diagnosis. Within the cancer patient cohort, cancer site was the most robust individual predictor associated with risk of hospitalization or death, with highest risk among patients with metastatic cancer, liver and lung cancers compared to the reference group of prostate cancer patients. Conclusions: Cancer patients presenting to the ED have high risks for hospital admission and death when compared to patients without cancer. Cancer patients represent a distinct population and may benefit from cancer-specific risk stratification or focused interventions tailored to improve outcomes in the ED setting.
Tazemetostat (TAZ) in relapsed/refractory (R/R) follicular lymphoma (FL): Propensity-score matched analysis of E7438-G000-101 trial outcomes.
Authors: Proudman David , Gupta Deepshekhar , Nellesen Dave , Wong Alex , Yang Jay , Kamp Beth , Mamlouk Khalid 
Published: June 2021

e18627 Background: Oncology drug development often requires the use of non-randomized, open-label, phase 2 basket studies to better understand the early activity and safety of a potential new therapy. As such, baseline demographics and disease characteristics may differ between cohorts which can impact the perception of efficacy between cohorts. TAZ, a first-in-class, oral enhancer of zeste homolog 2 (EZH2) inhibitor was approved by the US FDA after demonstrating single-agent, antitumor activity in a phase 2 study in adults with wild-type (WT) or mutant (MT) EZH2 R/R FL who had received ≥2 prior systemic therapies (NCT01897571). Differences between the cohorts in baseline characteristics known to be prognostic for clinical outcomes were noted, with the WT EZH2 cohort enrolling more patients with poor-risk features. This analysis assessed outcomes in the 2 groups after minimizing differences in baseline characteristics by creating a matched sample of directly comparable WT and MT patients. Methods: Propensity scores for each WT (n = 54) and MT (n = 45) EZH2 patient in the study were generated, based on the likelihood of being selected given their baseline characteristics. Characteristics identified for inclusion in the model were chosen if they were prognostic based on peer-reviewed literature and where larger differences were observed between cohorts at baseline: ECOG performance status, number of prior lines of anticancer therapy, progression of disease within 24 months, double refractory status, and prior history of hematopoietic stem cell transplant. Patients were matched 1:1 on propensity score, using a nearest-neighbor approach with caliper restrictions. Baseline covariates between the two matched groups were found to be sufficiently balanced. Objective response rate (ORR) point estimates were measured for the matched WT and MT EZH2 groups, and progression-free survival (PFS) was described using Kaplan-Meier analyses. Results: The propensity-matched sample included 56 patients (28 WT and 28 MT). Prior to matching, ORR was 35% (95% CI [22%, 48%]) in the WT and 69% (95% CI [55%, 83%]) in MT EZH2 groups; after matching, the ORR was 50% (95% CI [31%, 69%]) and 71% (95% CI [54%, 88%]), respectively. Median PFS was 11.1 months (95% CI [5.4, 16.7]) in the WT and 13.8 months (95% CI [11.1, 22.1]) in the MT EZH2 groups prior to matching, and 14.3 months (95% CI [11.1, inf]) and 14.8 (95% CI [10.7, inf]) months in the WT and MT EZH2 matched groups, respectively. Conclusions: As expected, efficacy remained higher in the MT EZH2 group; however, after adjustment, the ORR and PFS improved in the WT EZH2 group. This hypothesis-generating analysis suggests that outcomes in patients with WT EZH2 R/R FL treated with TAZ may have been more similar to those in the MT EZH2 group in the phase 2 trial had the baseline disease characteristics been more equally matched.
Biomarker testing in non-small cell lung cancer (NSCLC): An assessment of current practices in precision oncology in the community setting—A trial of the ECOG-ACRIN cancer research group (EAQ161CD).
Authors: Trosman Julia Rachel , Sicks Jorean , Weldon Christine B. , Tsongalis Gregory J. , Rapkin Bruce , Weaver Kathryn E. , Cohen Gary Irvin , Lad Thomas E. , Dressler Emily Van Meter , Stanfield Bill , Hopkins Judith O. , Hancock Judy , Kehn Heather , Steen Preston D. , Wagner Lynne I. , Carlos Ruth 
Published: June 2021

e18649 Background: Molecular biomarker testing is integral to NSCLC cancer care, but adoption and testing practices in the community are varied and often suboptimal. Testing practices, such as standard testing protocols and results turnaround time (TAT), impact timely treatment decisions. We examined adoption and testing practices for guideline recommended NSCLC biomarkers among National Cancer Institute Community Research Program (NCORP) sites. The study was conducted in collaboration with Wake Forest NCORP Research Base. Methods: An online survey was administered to onsite labs affiliated with NCORP sites April 2019 – June 2020. We assessed testing practices for 7 NCCN recommended biomarkers, including 3 with category 1 recommendation (EGFR, ALK, PD-L1) and 4 with category 2 recommendations (BRAF, ROS1, MET, RET). Guideline concordant result TAT was defined as return of EGFR and ALK results in ≤ 10 days (Lindeman 2018) (see Table for other outcomes). We used proportions, including two-sided Fischer exact tests, to compare outcomes by site characteristics (safety net, practice size). Results: The survey response rate was 69% (58/85). All responding labs offered testing for category 1 biomarkers (EGFR, ALK and PD-L1); only 10% conducted these tests in-house (Table). The majority of labs also tested for category 2 biomarkers (67%). TAT varied, with most labs returning results in ≤ 10 days for EGFR and ALK (69%, but only a minority meet this TAT for all biomarkers. Larger practice size (> 1400 new cancer cases a year) was associated with in-house testing of EGFR, ALK, PD-L1 (p=0.03) and having standard testing protocols (p<0.001). Safety net affiliation did not significantly impact practices. Conclusions: We found universal adoption of NCCN category 1 biomarkers among the labs affiliated with NCORP sites, with the majority meeting guideline concordant results TAT. There is opportunity for improvement in adoption of category 2 biomarkers and result TAT, for example, by using standard testing protocols. Reassuringly, no difference in testing practices was detected by safety net affiliation.[Table: see text]
Clinical treatment pathways utilization in an outpatient academic cancer center.
Authors: Chen Anna , Park Seojin , Csik Valerie Pracilio , Maio Vittorio , Walsh Karen , Binder Adam F 
Published: June 2021

e18673 Background: Clinical treatment pathway (CTP) tools have been incorporated into oncology practices to help standardize treatment, reduce care variation in cancer patients, and move towards value-based care. CTP tools incorporate the latest guidelines and are developed through multidisciplinary committees. Treatment decisions are prioritized by efficacy, toxicity, and cost to improve quality and value. This is especially important in cancer care which is associated with high drug costs. However, use and implementation of CTP tools has been met with mixed reviews and published data from academic medical centers are limited. Methods: Outpatient treatment decisions for patients across different cancer types, including colorectal, gastroesophageal, and breast cancers from July 2018 to March 2020 at an urban NCI-designated cancer center were evaluated. Every treatment decision was evaluated in relation to physician utilization of CTP tools. Treatment decisions were categorized as choosing a CTP recommended option ( pathways dependent), not choosing a CTP recommended option ( pathways independent), or not using the CTP tool at all ( non-pathways). Descriptive statistics and significance testing were used to explore CTP utilization over time, physician years in practice, cancer type, and cancer stage. Multinomial and binary logistic regression models were used to evaluate associated factors with CTP utilization. Results: During the study period, 1,007 treatment decisions were identified. Of these, 76% were pathways dependent, 13% were pathways independent, and 11% were non-pathways. CTP utilization was statistically significant in association with cancer type, cancer stage, physician years in practice, and year of encounter. In multinomial logistic regression models, physicians with more years in practice were more likely to be pathways independent and non-pathways than pathways dependent. Physicians treating colorectal or gastroesophageal cancer were more likely to be pathways independent [OR 3.27; 95% CI: 1.98-5.42 and OR 2.25; 95% CI: 1.12-4.49, respectively] or non-pathways [OR 2.98; 95% CI: 1.65-5.37 and OR 3.21; 95% CI: 1.58-6.54, respectively] than pathways dependent compared to physicians treating breast cancer. Treatment decisions for patients with either stage 2 and stage 4 cancers were more likely to be pathways independent than stage 1 cancers [OR 4.13; 95% CI: 1.44-11.84 and OR 4.37; 95% CI: 1.27-15.04, respectively]. Conclusions: This study found that a large proportion of treatment decisions for patients across different cancer types were made utilizing CTP tools, but utilization varies according to cancer type, stage, and physician years in practice. Further research is needed to better understand the physician decision making process and implementation of CTP tools to drive improvement in design, education, and training.
Improving admission medication reconciliation at a tertiary cancer center.
Authors: Kheder Ed , Saji Lijo , Zalpour Ali , Swanson Samuel , Mandayam Sreedhar 
Published: June 2021

e18686 Background: Accurate medication reconciliation (MedRec) is a pivotal step ensuring patient safety during transition of care, yet one of the most challenging aspects in healthcare quality and safety. Inaccurate MedRec leads to 40 % of medications errors, 20% of which results in harm. Our aim is to increase rate of accurate MedRec completion at MD Anderson Cancer Center (MDACC), within 24 hours of admission, from 85% to >95% through Best Possible Medication History (BPMH) Methods: During pre-intervention phase, we audited medication review and reconciliation of 50 randomly selected patients within 24 hours from admission to MDACC. Our intervention included: conducting several brain-storming sessions with nursing staff, providers, pharmacists; creating fish bone diagram and process maps; designing educational presentations for nursing staff on how to practice BPMH; educating providers on how to complete medication reconciliation within 24 hours of admissions; assigning nursing champions; and sending email reminders to provider on a daily basis. We audited another 50 patients post intervention. In our project, BPMH accuracy was measured by percentage of patients with zero discrepancies (incorrect dosage, frequency or route; extra medication; discontinued medication not removed from list). Significance was tested for BPMH completion, and MedRec completion using a Binomial Test, while significance for number of discrepancies and audit completion time was tested using a Two Sample t-Test. Results: We collected data on 50 patients pre and 50 post intervention. Our results indicate statistically significant improvement in MedRec rate (100%), reduction of number of discrepancies and audit completion time. Conclusions: Medication review and reconciliation are multi-phased processes. Nurses, Pharmacists and medical providers are the cornerstone of accurate and complete MedRec. Reminder emails to medical providers played a key role in MedRec rate improvement. Additional root cause analysis is needed to further address the medication review completion process in our institution.[Table: see text]
Using randomized trial data to estimate effects of complex treatment regimens in real-world patients.
Authors: Webster-Clark Michael , Sanoff Hanna Kelly , Lund Jennifer Leigh , Sturmer Til , Westreich Daniel , Keil Alexander P. 
Published: June 2021

e18706 Background: Real-world patients often differ from trial participants in prognostic factors such as age, sex, and cancer substage. New methods combine covariate data from real-world patients (the “target population”) with outcome and covariate data from a trial to estimate treatment effects in the target population that take these differences into account. With some assumptions, these methods can also estimate outcomes under treatment regimens not studied in the trial such as “what if we only gave six cycles of chemotherapy?” or “what if patients all perfectly followed a protocol?” Methods: Data from the MOSAIC trial of 5-fluorouracil (5FU) vs oxaliplatin + 5FU (FOLFOX) were combined with covariate data from a target population of stage III colon cancer patients in the US Oncology Network meeting trial eligibility criteria. We used weighting and G-computation to estimate five-year mortality and treatment-related paresthesia risk in the target population for four regimens: treatment with up to 12 cycles of 5FU, if providers used their discretion on dose reductions and delays (5FU-MD); up to 12 cycles of FOLFOX with similar physician discretion (FOLFOX-MD); up to 6 cycles of FOLFOX, with providers perfectly following a strict and specific protocol of dose reductions and delays (6-cycle FOLFOX-P, “P” for “per protocol”); and up to 12 cycles of FOLFOX, following the same strict protocol (12-cycle FOLFOX-P). Results: Tablepresents five-year all-cause mortality and paresthesia risk under each regimen in the stage III target population estimated from the models built in trial participants. Paresthesia risk increased with cumulative oxaliplatin dose. Estimated 5-year mortality was lowest with 12-cycle FOLFOX-P. Conclusions: In a target population of US Oncology Network patients with stage III colon cancer, strict protocols of 12 cycles of FOLFOX were predicted to improve survival compared to strict 6-cycle FOLFOX regimens or less strict 12-cycle FOLFOX and 5FU regimens at the cost of substantial increases in side effects. While estimates of risk differences in 5-year mortality were imprecise, combining trial and real-world data and then using weights and G-computation allowed estimation of benefits and harms of multiple regimens in a clinically relevant patient population.[Table: see text]
Assessment of differences in demographic characteristics and clinical diagnoses among black and white oncology patients with COVID.
Authors: Bhandari Sudip , Mueller Judith , Whyte Warren , Heilbroner Samuel P. 
Published: June 2021

e18711 Background: Health disparities between black and white COVID-positive patients are well documented. To help address these disparities, clinicians need to understand the specific health challenges faced by black COVID patients compared to their white counterparts. These challenges are understudied in the oncologic setting. Hence, we present the demographic and clinical features of black COVID-positive cancer patients compared to whites. Methods: We used ConcertAI’s database of oncology EMR data, which includes clinical data from CancerLinQ Discovery. We conducted two-sample t-tests and chi-squared tests to measure the differences in black and white COVID-positive cancer patients across age, gender, ethnicity, state, region, ECOG, BMI, all cancer indications, stage, and Charlson comorbidities. COVID positivity was defined using claims data. Only relevant significant results are reported to save space. Results: Table summarizes the differences in 429 black and 980 white cancer patients with COVID. Black patients were younger, more likely to have an elevated BMI, and have a higher prevalence of breast cancer, congestive heart failure, diabetes, multiple myeloma, peptic ulcer disease, and renal disease. They also had less melanoma. Results were statistically significant at 0.05 level. Analyzing only black patients by COVID status shows very similar results. Conclusions: Black cancer patients suffer from multiple comorbid conditions that increase their risk of adverse outcomes when infected with COVID-19. The CDC lists eight comorbidities that put patients at a higher risk of severe COVID infection. Black patients in our cohort have a higher prevalence of four out of eight of these conditions—elevated BMI, renal disease, congestive heart failure, and diabetes. Clinicians should inspect for these comorbidities while treating this at-risk population. [Table: see text]