2043

OBJECTIVES/SPECIFIC AIMS: Peripheral neuropathy is the dose limiting toxicity of paclitaxel treatment. Paclitaxel pharmacokinetics (PK), specifically the Cmax and amount of time the concentration remains above 0.05 µM (Tc>0.05), have been associated with occurrence of severe, clinician-documented neuropathy. The objective of this study was to confirm that paclitaxel PK predicts progression of patient-reported neuropathy. METHODS/STUDY POPULATION: This observational trial enrolled breast cancer patients receiving weekly 1-hour paclitaxel infusions (80 mg/m2×12 cycles) at the University of Michigan Comprehensive Cancer Center. Paclitaxel concentration was measured via LC/MS in plasma samples collected at the end of (Cmax) and 16–24 hours after (Tc>0.05) first infusion. Patient-reported neuropathy was collected (EORTC CIPN20) at baseline and each cycle. The rate of neuropathy severity increase per treatment cycle is being modeled for each patient. Cmax and Tc>0.05 values will be introduced into the model to confirm that PK independently contributes to neuropathy progression. RESULTS/ANTICIPATED RESULTS: PK and neuropathy data have been collected from 60 patients for ongoing analysis. Our initial model will characterize the expected severity of neuropathy after each cycle of paclitaxel treatment. The PK-neuropathy model will include either PK parameter to validate their contribution to the progression of neuropathy severity during treatment. We anticipate, based on our preliminary analysis of the first 16 patients, that both PK parameters will significantly contribute to the model but Tc>0.05 will be more strongly associated with neuropathy progression. DISCUSSION/SIGNIFICANCE OF IMPACT: This project will generate a model that can be used to predict a patient’s neuropathy severity throughout treatment using a single, conveniently collected and easily measured PK sample during their first cycle. The next steps of this project include identifying genetic and metabolomic biomarkers that predict which patients experienced more severe neuropathy than would be anticipated based on their paclitaxel PK, and a planned interventional trial of personalized paclitaxel dosing to enhance efficacy and/or prevent neuropathy.

Download Full-text

Creating an Effort Tracking Tool to Improve Therapeutic Cancer Clinical Trials Workload Management and Budgeting

Journal of the National Comprehensive Cancer Network ◽

10.6004/jnccn.2011.0103 ◽

2011 ◽

Vol 9 (11) ◽

pp. 1228-1233 ◽

Cited By ~ 7

Author(s):

Pam James ◽

Patty Bebee ◽

Linda Beekman ◽

David Browning ◽

Mathew Innes ◽

...

Keyword(s):

Clinical Trials ◽

Clinical Research ◽

Data Management ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

University Of Michigan ◽

Web Based ◽

Workload Management ◽

Effective Cost ◽

The University

Quantifying data management and regulatory workload for clinical research is a difficult task that would benefit from a robust tool to assess and allocate effort. As in most clinical research environments, The University of Michigan Comprehensive Cancer Center (UMCCC) Clinical Trials Office (CTO) struggled to effectively allocate data management and regulatory time with frequently inaccurate estimates of how much time was required to complete the specific tasks performed by each role. In a dynamic clinical research environment in which volume and intensity of work ebbs and flows, determining requisite effort to meet study objectives was challenging. In addition, a data-driven understanding of how much staff time was required to complete a clinical trial was desired to ensure accurate trial budget development and effective cost recovery. Accordingly, the UMCCC CTO developed and implemented a Web-based effort-tracking application with the goal of determining the true costs of data management and regulatory staff effort in clinical trials. This tool was developed, implemented, and refined over a 3-year period. This article describes the process improvement and subsequent leveling of workload within data management and regulatory that enhanced the efficiency of UMCCC's clinical trials operation.

Download Full-text

Differential Regulation of Insulin Receptor Substrate-2 and Mitogen-Activated Protein Kinase Tyrosine Phosphorylation by Phosphatidylinositol 3-Kinase Inhibitors in SH-SY5Y Human Neuroblastoma Cells**This work was supported by NIH Grants R29-NS-32843 and R01-NS-36778, grants from the American Diabetes Association and Juvenile Diabetes Foundation (to E.L.F.), and a grant from the Millie Schembechler Adrenal Research Fund of the University of Michigan Comprehensive Cancer Center (to E.L.F. and P.S.L.).

Endocrinology ◽

10.1210/endo.139.12.6348 ◽

1998 ◽

Vol 139 (12) ◽

pp. 4881-4889 ◽

Cited By ~ 12

Author(s):

Bhumsoo Kim ◽

Phillip S. Leventhal ◽

Morris F. White ◽

Eva L. Feldman

Keyword(s):

Kinase Inhibitors ◽

Neuroblastoma Cells ◽

Juvenile Diabetes ◽

Mitogen Activated Protein Kinase ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

University Of Michigan ◽

Human Neuroblastoma ◽

Mitogen Activated Protein ◽

The University

Download Full-text

Assessing the need for improved strategies and medication-related education to increase adherence for oral anticancer medications in the young adult oncology population

Journal of Oncology Pharmacy Practice ◽

10.1177/1078155217703790 ◽

2017 ◽

Vol 24 (5) ◽

pp. 337-342 ◽

Cited By ~ 5

Author(s):

Anupama Divakaruni ◽

Elizabeth Saylor ◽

Alison P Duffy

Keyword(s):

Medication Adherence ◽

Young Adult ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

University Of Maryland ◽

Patient Reported ◽

Adherence Monitoring ◽

The University ◽

Oral Anticancer Medication ◽

Education Process

Rationale Oral anticancer medication adherence is a critical factor in optimizing cancer treatment outcomes and minimizing toxicity. Although potential adherence barriers exist, it is not well understood how these factors impact adherence. Methods This is a prospective, single-center, patient survey-based study conducted at the University of Maryland Greenebaum Comprehensive Cancer Center including 18- to 39-year-old patients who have been actively taking an oral anticancer medication for at least one month from 1 April 2013 to 1 April 2016. The primary objective of this study is to describe institutional practices for medication education and adherence monitoring practices as perceived by young adult patients at the University of Maryland Greenebaum Comprehensive Cancer Center and to describe practice consistency with recommendations from the American Society of Clinical Oncology/Oncology Nursing Society Chemotherapy Administration Safety Standards. The secondary objectives include patient-reported facilitators and barriers to oral anticancer medication adherence. Results Seventeen patients completed the survey; 24% ( n = 4) of patients denied receiving information about what to do in case of a missed dose. The most common facilitators of adherence include understanding of disease and treatment (88%, n = 15), perceived severity of illness (82%, n = 14), and use of oral anticancer medications (82%, n = 14). The most common barriers to adherence are side effects (59% n = 10), forgetfulness (47%, n = 8), and depressive symptoms (35%, n = 6). Conclusion Based on patient-reported guideline adherence, improvement is needed in including family, caregivers, and others in the education process as well as providing education about plan for missed doses and drug–drug and drug–food interactions. The strengths of the current medication education and adherence monitoring practices as perceived by the young adult patient population include education about the purpose and goals of treatment, the planned duration and schedule, side effects, and when to seek medical attention. The data collected from this survey can aid in future development and implementation of interventions aimed at improving medication adherence, such as integrating clinical pharmacy services into oral chemotherapy monitoring and education process.

Download Full-text

Predicting Patient Treatment Deferrals at an Outpatient Chemotherapy Infusion Center: A Statistical Approach

JCO Clinical Cancer Informatics ◽

10.1200/cci.17.00092 ◽

2017 ◽

pp. 1-8

Author(s):

Donald B. Richardson ◽

Seth D. Guikema ◽

Amy E.M. Cohn

Keyword(s):

Treatment Protocol ◽

Regression Tree ◽

Comprehensive Cancer Center ◽

Patient Specific ◽

Brier Score ◽

Cancer Center ◽

University Of Michigan ◽

Wide Range ◽

Patient Will ◽

The University

Purpose Patients scheduled for outpatient infusion sometimes may be deferred for treatment after arriving for their appointment. This can be the result of a secondary illness, not meeting required bloodwork counts, or other medical complications. The ability to generate high-quality predictions of patient deferrals can be highly valuable in managing clinical operations, such as scheduling patients, determining which drugs to make before patients arrive, and establishing the proper staffing for a given day. Methods In collaboration with the University of Michigan Comprehensive Cancer Center, we have developed a predictive model that uses patient-specific data to estimate the probability that a patient will defer or not show for treatment on a given day. This model incorporates demographic, treatment protocol, and prior appointment history data. We tested a wide range of predictive models including logistic regression, tree-based methods, neural networks, and various ensemble models. We then compared the performance of these models, evaluating both their prediction error and their complexity level. Results We have tested multiple classification models to determine which would best determine whether a patient will defer or not show for treatment on a given day. We found that a Bayesian additive regression tree model performs best with the University of Michigan Comprehensive Cancer Center data on the basis of out-of-sample area under the curve, Brier score, and F1 score. We emphasize that similar statistical procedures must be taken to reach a final model in alternative settings. Conclusion This article introduces the existence and selection process of a wide variety of statistical models for predicting patient deferrals for a specific clinical environment. With proper implementation, these models will enable clinicians and clinical managers to achieve the in-practice benefits of deferral predictions.

Download Full-text

Effort Tracking Metrics Provide Data for Optimal Budgeting and Workload Management in Therapeutic Cancer Clinical Trials

Journal of the National Comprehensive Cancer Network ◽

10.6004/jnccn.2011.0116 ◽

2011 ◽

Vol 9 (12) ◽

pp. 1343-1352 ◽

Cited By ~ 7

Author(s):

Pam James ◽

Patricia Bebee ◽

Linda Beekman ◽

David Browning ◽

Mathew Innes ◽

...

Keyword(s):

Clinical Trials ◽

Data Management ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

University Of Michigan ◽

Workload Management ◽

Aggregated Data ◽

Personnel Costs ◽

Accrual Rate ◽

The University

Clinical trials operations struggle to achieve optimal distribution of workload in a dynamic data management and regulatory environment, and to achieve adequate cost recovery for personnel costs. The University of Michigan Comprehensive Cancer Center developed and implemented an effort tracking application to quantify data management and regulatory workload to more effectively assess and allocate work while improving charge capture. Staff recorded how much time they spend each day performing specific study-related and general office tasks. Aggregated data on staff use of the application from 2006 through 2009 were analyzed to gain a better understanding of what trial characteristics require the most data management and regulatory effort. Analysis revealed 4 major determinants of staff effort: 1) study volume (actual accrual), 2) study accrual rate, 3) study enrollment status, and 4) study sponsor type. Effort tracking also confirms that trials that accrued at a faster rate used fewer resources on a per-patient basis than slow-accruing trials. In general, industry-sponsored trials required the most data management and regulatory support, outweighing other sponsor types. Although it is widely assumed that most data management efforts are expended while a trial is actively accruing, the authors learned that 25% to 30% of a data manager's effort is expended while the study is either not yet open or closed to enrollment. Through the use of a data-driven effort tracking tool, clinical research operations can more efficiently allocate workload and ensure that study budgets are negotiated to adequately cover study-related expenses.

Download Full-text

Enhancing Patient-Provider Communication With the Electronic Self-Report Assessment for Cancer: A Randomized Trial

Journal of Clinical Oncology ◽

10.1200/jco.2010.30.3909 ◽

2011 ◽

Vol 29 (8) ◽

pp. 1029-1035 ◽

Cited By ~ 204

Author(s):

Donna L. Berry ◽

Brent A. Blumenstein ◽

Barbara Halpenny ◽

Seth Wolpin ◽

Jesse R. Fann ◽

...

Keyword(s):

Controlled Trial ◽

Clinic Visit ◽

Self Report ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

Control Group ◽

Cancer Symptoms ◽

Patient Reported ◽

Life Issues ◽

Clinic Visits

Purpose Although patient-reported cancer symptoms and quality-of-life issues (SQLIs) have been promoted as essential to a comprehensive assessment, efficient and efficacious methods have not been widely tested in clinical settings. The purpose of this trial was to determine the effect of the Electronic Self-Report Assessment–Cancer (ESRA-C) on the likelihood of SQLIs discussed between clinicians and patients with cancer in ambulatory clinic visits. Secondary objectives included comparison of visit duration between groups and usefulness of the ESRA-C as reported by clinicians. Patients and Methods This randomized controlled trial was conducted in 660 patients with various cancer diagnoses and stages at two institutions of a comprehensive cancer center. Patient-reported SQLIs were automatically displayed on a graphical summary and provided to the clinical team before an on-treatment visit (n = 327); in the control group, no summary was provided (n = 333). SQLIs were scored for level of severity or distress. One on-treatment clinic visit was audio recorded for each participant and then scored for discussion of each SQLI. We hypothesized that problematic SQLIs would be discussed more often when the intervention was delivered to the clinicians. Results The likelihood of SQLIs being discussed differed by randomized group and depended on whether an SQLI was first reported as problematic (P = .032). Clinic visits were similar with regard to duration between groups, and clinicians reported the summary as useful. Conclusion The ESRA-C is the first electronic self-report application to increase discussion of SQLIs in a US randomized clinical trial.

Download Full-text

Changes in fatigue, barriers, and predictors towards physical activity in advanced cancer patients over a period of 12 months—a comparative study

Supportive Care in Cancer ◽

10.1007/s00520-021-06020-3 ◽

2021 ◽

Author(s):

J. Frikkel ◽

M. Beckmann ◽

N. De Lazzari ◽

M. Götte ◽

S. Kasper ◽

...

Keyword(s):

Physical Activity ◽

Cancer Patients ◽

Advanced Cancer ◽

Physical Functioning ◽

Comprehensive Cancer Center ◽

Cancer Center ◽

Advanced Cancer Patients ◽

Psychological Conditions ◽

Patient Reported

Abstract Purpose Physical activity (PA) is recommended to improve advanced cancer patients’ (ACP) physical functioning, fatigue, and quality of life. Yet, little is known about ACPs’ attitude towards PA and its influence on fatigue and depressiveness over a longer period. This prospective, non-interventional cohort study examined ACPs’ fatigue, depression, motivation, and barriers towards PA before and after 12 months of treatment among ACP Methods Outpatients with incurable cancer receiving treatment at a German Comprehensive Cancer Center reporting moderate/severe weakness/tiredness during self-assessment via MIDOS II were enrolled. Fatigue (FACT-F), depression (PHQ-8), cancer-related parameters, self-assessed PA behavior, motivation for and barriers against PA were evaluated (T0). Follow-up data was acquired after 12 months (T1) using the same questionnaire. Results At follow-up, fatigue (p=0.017) and depressiveness (p=0.015) had increased in clinical relevant extent. Physically active ACP did not show significant progress of FACT-F (p=0.836) or PHQ-8 (p=0.799). Patient-reported barriers towards PA remained stable. Logistic regression analyses identified motivation as a positive predictor for PA at both time points (T0, β=2.152, p=0.017; T1, β =2.264, p=0.009). Clinically relevant depression was a negative predictor for PA at T0 and T1 (T0, β=−3.187, p=0.044; T1, β=−3.521, p=0.041). Conclusion Our findings emphasize the importance of psychological conditions in physical activity behavior of ACP. Since psychological conditions seem to worsen over time, early integration of treatment is necessary. By combining therapy approaches of cognitive behavioral therapy and exercise in interdisciplinary care programs, the two treatment options might reinforce each other and sustainably improve ACPs’ fatigue, physical functioning, and QoL. Trial registration German Register of Clinical Trials, DRKS00012514, registration date: 30.05.2017

Download Full-text