Lalan S. Wilfong

Adrenal insufficiency after stereotactic body radiation therapy for bilateral adrenal metastases

The adrenal (suprarenal) glands are paired retroperitoneal organs that consist of 2 functionally discrete regions with distinct embryologic and physiological functions, the adrenal cortex and the adrenal medulla. The adrenal cortex is composed of 3 zones: the zona glomerulosa, the zona fasiculata, and zona reticularis, which release aldosterone, cortisol, and sex steroids, respectively. Given the vital function of the adrenal glands, a rich vascular supply provides a fertile environment for trapping and growth of hematogenous metastases. Surgery is the standard of care for resectable adrenal metastases, but stereotactic body radiation therapy (SBRT) is increasingly being used as an alternative ablative technique, with high rates of local control.1 Unilateral metastases predominate, with the incidence of bilateral adrenal metastases ranging between 4% and 20% in surgical and SBRT series.2-4

Abstract 5314: A proteomic signature predicts response to a therapeutic vaccine in pancreas cancer; analysis from the GI-4000-02 trial

Background: We have previously reported that adjuvant treatment with a therapeutic vaccine targeting the mutated Ras oncogene product generated mutation-specific T cell responses associated with a trend toward improved survival in patients with post-operative residual disease (R1 resections) but no improvement in the overall population 1 . Initial analysis of 90 pretreatment plasma samples using matrix assisted laser desorption ionization time of flight (MALDI-TOF) mass spectrometry (MS) showed the potential to predict improved RFS and OS for treatment with GI-4000/gemcitabine, but not placebo/gemcitabine. Methods: We have developed a novel technique, combining methods used in recent advances in learning theory (‘deep learning’) with newly-refined MS techniques that allow exploration deeper into the proteome to create diagnostic tests. Using 500,000 laser shot Deep MALDI spectra 2 more than 700 mass spectral features were identified. A subset of these was used to create many multivariate classifiers that were filtered for performance and combined using dropout regularization. This method allows the use of smaller training sets and so left a test set with which performance of the signature could be independently assessed. This new methodology was used to create a test (BDX-001) to identify patients likely to benefit from the addition of GI-4000 to gemcitabine. Results: Using BDX-001 for stratification, subjects who are BDX-001(+) demonstrated a 499 day advantage in median OS when treated with GI-4000/gemcitabine vs. placebo/gemcitabine. Additionally, these subjects demonstrated a 351 day improvement in median RFS. BDX-001 did not predict response for placebo/gemcitabine treated subjects. These results were obtained using only test set data, and although the small sample size prohibited statistical significance, it should give an unbiased test performance estimate to be validated independently. Conclusions: BDX-001 is a test developed using novel proteomic and learning theory methods that appears to predict treatment response to GI-4000 in resected pancreas cancer patients, potentially identifying patients with improved RFS and OS in the GI-4000/gemcitabine arm. We plan to prospectively validate BDX-001 as a companion diagnostic in a future study of GI-4000 in pancreas cancer. References 1. Richards et al, ESMO GI. Annals of Oncology, June 2012 23 (suppl 4) 2. Duncan et al, ASMS 2013, http://asms.inmerge.com/Proceedings/2013Proceedings.aspx. Citation Format: Donald A. Richards, Peter Muscarella, Tanios Bekaii-Saab, Lalan S. Wilfong, Vic Velanovich, Julian Raynov, Patrick J. Flynn, William E. Fisher, Samuel H. Whiting, Constana Timcheva, Tom Holmes, Claire Coeshott, Alicia Mattson, Heinrich Roder, Joanna Roder, Allen Cohn, Timothy C. Rodell. A proteomic signature predicts response to a therapeutic vaccine in pancreas cancer; analysis from the GI-4000-02 trial. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5314. doi:10.1158/1538-7445.AM2014-5314

Changing physician compensation and implementing new technology to enhance pathways compliance.

187 Background: Pathways have shown to decrease cost of care while maintaining efficacy of treatment. In 2005, The US Oncology Network, which includes Texas Oncology, P.A. (TOPA) developed physician-led clinical pathways based on national guidelines, cost and efficacy. This abstract reviews the impact of changes TOPA initiated to improve pathway compliance Methods: Since 2011, TOPA has assessed pathways compliance using the iKnowMed (iKM) electronic medical record. Individual compliance was reported to each physician, but no incentives were tied to this. In 2015, the TOPA annual productivity bonus structure (2% of compensation) was changed to introduce pathways compliance and exception documentation thresholds, with penalties for sub-threshold performance. Additionally, TOPA sought to improve on iKM-based data collection and assessment. Previously, there were data challenges with pathways assessed retrospectively, offering limited visibility at the time of decision-making. In September 2015, new technology (Clear Value Plus - CVP) was embedded within iKM, which allowed prospective pathways assessment and provided real-time compliance reporting. RESULTS Introduction of individual incentives and improved decision support increased pathways compliance. For the initial yearly bonus measurement period, TOPA pathways compliance was 78%. After implementation of the new bonus structure, compliance increased significantly to 83% (p<0.0001). Implementation of CVP further improved pathway compliance for comparable reporting periods from 78% in September 2014 to 90% in September of 2015 (p<0.0001) Conclusions: We have shown that even a small change in compensation significantly influences physician pathways compliance. Additionally, technology to assist physicians with documentation and real-time assessment also significantly improves pathway compliance. [Table: see text] [Table: see text].

A schematic case episode format to aid in “Choosing Wisely."

181 Background: The recommendations of the Choosing Wisely campaign are evidence -based strategies to reduce cost without sacrificing outcomes. Yet tying the recommendations to indicators of use at the physician and case level has been challenging. As practices become responsible for total cost of care, an easy to use analytic method to determine appropriate use will be critical. We here describe a tool for rapid assessment of individual cases to achieve that objective. METHODS The population was a payer defined cohort of lung cancer patients treated at Texas Oncology (TxO). TxO maintains a payer patient list, updated daily with demographics and diagnosis details for all enrolled patients. The list of lung cancer patients was cross-referenced against billing data from TxOs financial data warehouse (FDW). The FDW data is generated monthly, based on billing details from TxOs practice management system, and includes procedure codes and dates of service. Radiation therapy, chemotherapy, and GCSF administrations for each enrolled lung cancer patient were identified in the FDW data based on CPT codes. SAS software (version 9.4 for Windows) was used to generate a time series plot for each patient, based on date of service for each procedure. The time series plots were inserted into an Excel report template, along with general patient information, using a Visual Basic script, for review by TxOs medical director and quality committees. RESULTS Each patient-specific time series schematic displays elapsed weeks on the x-axis, beginning with week 1 to end of treatment. Three variables are displayed on the y-axis, using distinct colors and symbols: dates of radiation therapy (orange #), dates of GCSF administration (red x), and dates of chemotherapy administration (green ^). Each of the three y-axis variables is assigned a constant value that is plotted along a straight line. A graphic representation for a patient with stage III lung cancer could look as shown in the Table. CONCLUSIONS Treatment episodes can be distilled into a meaningful format that allows rapid case review and the opportunity for continuous learning. Additional diseases and graphics will be available for presentation. [Table: see text].

Time stamps used to measure the patient's clinic experience.

150 Background: In 2013, a patient reported satisfaction survey indicated 19% of patients waited 20-40 minutes, 8% 40-60 minutes and 4% over 1 hour. We initiated a project to objectively quantify the components of wait times to investigate opportunities for improvement. METHODS Utilizing existing technology in the practice management system, clinic staff use the Day List feature to capture time stamps as patients move through the clinic. We focused on provider appointments but these visits could also include business office, labs, infusion and diagnostics. It was important to define where the wait(s) occurred. The Time Stamp durations measured are as follows: Arrival to Depart - duration of each appointment; Arrival to site to Exam Start - duration of activity until ready to be seen by the provider, includes rooming, labs and business office activity. Used to compare to the patient satisfaction survey responses; Exam Start to Depart - the provider portion of the office visit, includes patient wait plus exam time. Three reports are generated: Time Stamp Error Report indicating the completeness of data collection; Average Wait Times Report with appointment counts by physician by site and average durations; Provider Wait Times Report with office visit counts, Wait Time Category counts ( < 10 min, 10-20, 20-40, 40-60, and > 1 hour ) and average durations. RESULTS There was a correlation calculation to the patient satisfaction survey of .779, with long wait times more likely to be underreported by patients. Site and physician data were available for review at site Quality Committees. The data can be used by the site to improve processes, such as lab and infusion room scheduling. Time stamps are used to communicate patient readiness for next steps in the office visit. The time stamps provide objective data to discuss patient complaints with staff. CONCLUSIONS Patient wait times are a valued measure of patient satisfaction and quality. Full utilization of the Day List and supporting technology allows us to objectively monitor and improve this aspect of patient care. Table 1: Sample Provider Report [Table: see text].

Improvements in communication and engagement of advance care planning in adults with metastatic cancer through a targeted team approach.

14 Background: Advance care planning (ACP) continues to be a vital part of comprehensive, person-centered cancer care. A large community oncology practice performed a targeted approach to improve patient engagement of ACP. A process improvement project with three goals was set: increasing ACP referrals, ACP counseling visits and completed Values Assessment (VA) instrument. A leadership team consisting of practice director, physician, nurse manager, and nurse practitioner was developed with ownership of roles and responsibilities. METHODS The ACP leadership team outlined workflows to be tested, followed by evaluating outcomes of each goal over 107 days. Barriers and challenges were identified; ACP education was taught to staff. NP and RNs introduced ACP to patients during ChemoTeaching. Eligible patients were identified weekly by infusion RNs on C1D1, and patients were given the VA. Desk RNs would speak with patients on C1D2 to review symptoms and VA responses. RNs would offer ACP visits to patients. Referrals were made for patients to have one-on-one counseling with NP. Staff was educated about EMR documentation by RN manager. Weekly team phone meetings were held to discuss project status. RESULTS During the first 53 days of the project, 20 patients were identified at C1D1, 5 VA were completed and 15 ACP visits occurred. After evaluation, weekly communication with clinical staff increased to daily huddles. Daily communication allowed for RNs to identify C1D1 patients and communicate to the full team. During the second 54 days, 94 patients were identified at C1D1, 46 VA were completed, and 27 ACP visits occurred. A 5-fold increase occurred in patient identification; a 9-fold increase in VA completion occurred, and approximately 2-fold increase occurred in ACP counseling. CONCLUSIONS By developing a focused and concerted process on ACP, the cancer center was able to show that patient engagement in the ACP process markedly improved. A navigation process for identifying patients who would benefit from ACP counseling was vital in increasing in the counseling visits. Continual quality improvement by refining processes in the ACP program will benefit patients.