The Contribution of Patient Reported Outcome Measures to Shared Decision-Making in Radiation Oncology at a Midwestern Comprehensive Cancer Center

Background. Chronic diseases, such as lung cancer, require a provider-patient relationship developed over time. This relationship fosters shared decision-making (SDM), a collaborative, dynamic information exchange and analysis between provider and patient regarding treatment and desired outcomes. Established benefits to SDM include an improved quality of life and decreased anxiety and depression. Despite established benefits, recent research suggests radiation oncologists are not engaging in SDM. A decision-aid tool utilizing patient reported outcome measures may increase SDM between radiation oncologists and patients with lung cancer. Patient-reported outcome measures, wherein the patient provides direct assessment of their health and quality of life, can inform and initiate SDM. This study investigated the design and implementation of a collaborative decision-aid tool for patients with lung cancer at a Midwestern cancer center as informed by stakeholders, practice considerations, and the evidence base. Objectives. The primary objective was to develop a collaborative decision-aid tool, using patient-reported outcome measures, that can be implemented in an academic radiation oncology clinic. Secondary objectives then assessed the tool’s impact through surrogates of shared decision making (add-on oncology visits, concomitant medication prescriptions), medical management (adverse events, radiation therapy compliance, chemotherapy compliance) and emergent care and its costs (emergency room visits and estimated costs, inpatient admissions and estimated costs). The hypothesized result was a decision aid designed to increase collaborative communication between radiation oncologists and patients will result in improved shared decision making, yielding better medical management and patient outcomes and reducing emergent care costs. Lastly, an implementation roadmap provided information on experienced barriers, facilitators, and considerations for performance objectives. Materials and Methods. A sequential exploratory mixed methods design was employed. The qualitative strand explored how stakeholders, practice considerations, and the evidence base informed the design and installation of an ideal collaborative decision-aid tool. Semi-structured interviews were completed with both patients who completed radiation therapy for lung cancer and their radiation oncologist. Interviews were coded and evaluated for themes. Interviews were transcribed verbatim, coded using Atlas.ti software, and analyzed thematically and visually. The results of this analysis, combined with information from the literature base and implementation stakeholders, was used to inform design of the collaborative decision-aid tool that was installed employing the principles of clinical implementation using the plan-do-study-act (PDSA) implementation cycle model. Simple descriptive analysis was performed on objective measures. Mixed analysis included data display, comparison, and integration. Results. Six patients and six radiation oncologists participated in the semi-structured interviews. Interviews provided insights that patients did not know what to ask of their radiation oncologists, prioritized survival over reduced side effects, and minimized complaints to their radiation oncologists, often to their detriment. Interviews yielded feedback on commonly used patient reported outcome instruments, identifying context as important and the recall timeframe as difficult. Commonly patient-identified adverse events of concern were fatigue, dyspnea, vomiting, and dysphagia. Radiation oncologists identified a patient’s personality as critical to care and translating responses and symptoms to adverse events of treatment. For this reason, numeric scales were not endorsed as they were seen as ambiguous and lacking context. With this feedback, a collaborative decision-aid tool was designed that focused on adverse events of interest (nausea, vomiting, fatigue, dyspnea, chest pain, weight loss). Rather than numeric scales, responses provided granular context that clued physicians to medical needs (i.e., “I cannot walk to my appointment,” “It hurts when I eat,” “I am not vomiting but I’m not hungry”). This tool was implemented as a quality initiative project for pragmatic impact. Four patients were assigned the tool during the first PDSA implementation cycle. The first follow-up evaluation meeting identified four critical outcomes for the next implementation cycle: how to identify which consults require the decision-aid, how the need for the decision-aid on doctor visits is consistently provided to scheduling, how unplanned visits/special complaints are addressed with regard to the decision-aid, and what actions are necessary if the patient leaves prior to the decision-aid being reviewed. Mixed analysis provided direction for next steps in implementation, tool design, and quantitative data measures. The primary concern, increase in time expended per clinic visit, was not supported by the limited data available from the first implementation cycle. Conclusion. Implementation of collaborative decision-aid within the radiation oncology clinic is feasible without disruption of the on-treatment visit time. Radiation oncologists can use the tool as a guide for routine on-treatment visit review, so that it is harmonized with their routine practice. Care should be taken during implementation to ensure all stakeholders are included in the tool’s implementation and that desired outcomes are appropriately identified to truly capture what impact the tool has, if any, on clinical outcomes. Focusing on the patient with the goal of improving their experience will guide collaborative decision-aid tool adaptation, implementation, and uptake

Comparison of response evaluation criteria in solid tumors with volumetric measurements for estimation of tumor burden in pancreatic adenocarcinoma and hepatocellular carcinoma.

BACKGROUND: Response evaluation criteria in solid tumors (RECIST) is the accepted method for determining tumor progression. However, RECIST may not estimate disease burden accurately because the axial plane often does not produce the actual longest diameter. Volumetric measurements may be an alternative to better determine tumor size. Our aim was to compare volumetric measurements with RECIST in pancreatic ductal adenocarcinomas (PDA) and hepatocellular carcinomas (HCC). METHODS: RECIST and volumetric measurements were determined in 9 patients with metastatic PDA and 17 patients with HCC who subsequently underwent liver transplantation. Gross pathologic measurements after hepatectomy also were analyzed for volumes. RESULTS: Three-dimensional diameter in volumetric analysis was 38% and 36% higher than RECIST diameter in PDA and HCC, respectively (P \u3c .01). However, RECIST yielded 78% and 23% larger estimated tumor volumes than volumetric analysis in PDA and HCC, respectively (P \u3c .01). Gross pathologic volume in HCC showed a linear correlation with both volumetric analysis (r = .95; P \u3c .01) and RECIST (r = .96; P \u3c .01) but RECIST significantly overestimated gross pathologic volume by an average of 28% (P \u3c .01) whereas volumetric analysis was similar to gross pathologic volume (P = .56). In categorizing treatment response in PDA, RECIST and volumetric analysis were in moderate agreement (κ = .49). CONCLUSIONS: RECIST significantly may overestimate tumor burden compared with volumetric measurements in both PDA and HCC. Volumetric analysis may be the preferred method to detect tumor progression

A CTSA-sponsored program for clinical research coordination: networking, education, and mentoring.

Upon receipt of the National Institutes of Health Clinical and Translational Science Award, the University of Iowa\u27s Institute for Clinical and Translational Science committed to develop an infrastructure for research professionals. Three goals were established: (1) identification of research professionals within the University of Iowa, (2) development of an educational series, including orientation and continuing education, and (3) development of a mentoring system. The purpose of this paper is to describe the process of development, initiation, and outcomes of a successful networking, educational, and mentoring system crafted for research professionals at the University of Iowa

Signaling pathways in adenoid cystic cancers: implications for treatment.

Adenoid cystic cancers (ACC) in the head and neck are rare yet present a clinical dilemma. Although 5-y survivals are excellent, they have a propensity for late recurrences. Most of these cancers are initially treated with surgery followed by radiation. When recurrences happen, treatment options are limited both by the morbidity and low efficacy of re-irradiation and repeated surgical resection. Reported response rates to chemotherapy are low and targeted therapies may be one option. We, therefore, investigated signaling pathways that may be active in adenoid cystic cancers. Tissues from the last nine ACC patients resected at the University of Iowa were immunohistochemically stained with antibodies for EGFR, phosphorylated (P) Akt, and P-MAPK in order to molecularly characterize these tumors. An ACC cell line (ACC3) was also characterized by western blot. We found that seven of the nine tumor samples had strong expression of P-Akt and 5/9 had P-MAPK. None of them had EGFR expression. In the ACC3 cell line, similar data was found in that there was P-Akt and P-MAPK but no EGFR expression. We tested the HIV protease inhibitor nelfinavir (NFV) which has been shown to inhibit Akt signaling to see its effect on ACC3 cells. Both P-Akt and P-MAPK were inhibited with NFV in ACC3 cells and this resulted in growth inhibition and clonogenic death. In patients where re-irradiation or further surgery is not an option, a trial of NFV may be warranted

Accrual Patterns for Clinical Studies Involving Quantitative Imaging: Results of an NCI Quantitative Imaging Network (QIN) Survey.

Patient accrual is essential for the success of oncology clinical trials. Recruitment for trials involving the development of quantitative imaging biomarkers may face different challenges than treatment trials. This study surveyed investigators and study personnel for evaluating accrual performance and perceived barriers to accrual and for soliciting solutions to these accrual challenges that are specific to quantitative imaging-based trials. Responses for 25 prospective studies were received from 12 sites. The median percent annual accrual attained was 94.5% (range, 3%-350%). The most commonly selected barrier to recruitment (n = 11/25, 44%) was that patients decline participation, followed by too few eligible patients (n = 10/25, 40%). In a forced choice for the single greatest recruitment challenge, too few eligible patients was the most common response (n = 8/25, 32%). Quantitative analysis and qualitative responses suggested that interactions among institutional, physician, and patient factors contributed to accrual success and challenges. Multidisciplinary collaboration in trial design and execution is essential to accrual success, with attention paid to ensuring and communicating potential trial benefits to enrolled and future patients