Stross, William C.

PURPOSE: Quality payment programs aim to adjust payments on the basis of quality and cost; however, few quality metrics exist in radiation oncology. This study evaluates and predicts the top spenders (TS) after radiation therapy (RT). MATERIALS AND METHODS: Patient characteristics, cancer details, treatments, toxicity, and survival data were collected for patients treated with RT at Mayo Clinic from 2007 to 2016. Standardized costs were obtained and adjusted for inflation. TSs were identified as those with greater than 93rd percentile costs (≥ $120,812). Prediction models were developed to predict TSs using training and validation sets using information available at consultation, after RT, and at last follow-up. RESULTS: A total of 15,131 patients were included and 1,065 TSs identified. Mean cost overall was $55,290 (median, $39,996) for all patients. Prediction models 1, 2, and 3 had concordance statistics of 0.83 to 0.83, 0.85 to 0.85, and 0.87 to 0.88, respectively in training and validation, indicating excellent prediction of TSs. Factors that were most predictive of TSs included stage N/A and stage 4 ( v stage 0; odds ratio [OR], 18.23 and 8.44, respectively; P < .001); hematologic, upper GI, skin and lung cancers ( v breast; OR, 11.45, 7.69, 3.81, and 2.43, respectively; P < .01); immunotherapy, surgery, and chemotherapy use (OR, 4.36, 2.51, and 1.61, respectively; P < .01); hospitalizations within 90 days of RT (OR, 2.26; P < .01); or death during the episode (OR, 1.56; P < .01). CONCLUSION: This is the first study of its kind to predict with high accuracy the highest spenders in radiation oncology. These patients may benefit from pre-emptive management to mitigate costs, or may require exclusion or adjustment from quality payment programs.

6633 Background: Quality based payment programs in medicine are currently being introduced nationally, aimed to improve care and reduce cost. This study aimed to evaluate the top spenders (TS) after cancer diagnosis and predict TS at two separate time points using predictive analytics. Methods: Patient characteristics, cancer details, treatments, adverse events, and outcomes were collected for patients treated for cancer at Mayo Clinic from 2007 - 2017. Standardized costs over a 2 year period after first treatment were obtained from the Mayo Clinic Cost Data Warehouse with Medicare reimbursements assigned to all services and adjusted to the 2017 GDP Implicit Price Deflator for inflation. TS were identified as those with greater than 93rd percentile costs (≥$113,158) due to a sharp rise in cost at that level. Descriptive statistics and univariate analysis were used for comparison. A prediction model with a training (80%) and validation set (20%) using multivariate selection was used to predict TS and was repeated using information available at 1) the time of consultation and 2) at last follow-up. Results: A total of 80,385 patients were included and 5,626 TS were identified. Mean cost (25th, 75th percentile) overall was $44,953 ($16,776, $51,889). Prediction models at time 1 and 2 had ROC AUC statistics of 0.82 and 0.89 in training and 0.82 and 0.88 in the validation indicating good prediction of high costs. Factors most predictive of TS included need for blood transfusions within 90 days of treatment (OR 5.3), bone marrow transplant (OR 4.0), mild liver disease (OR 3.5), hemiplegia (OR 3.4), weight loss > 10% within 90 days of treatment (OR 3.3), upper GI cancer (OR 3.0), ‘other’ cancer type (OR 2.8), immunotherapy use (OR 2.7), and hospitalizations within 90 days (OR 2.4), all p < 0.001, among others. The largest costs were due to hospital services in the TS and non-TS groups, mean costs $114,258 and $13,185 respectively. Conclusions: This is the first study to predict with high accuracy the top spenders in Oncology. Patient comorbidities and toxicities were among the strongest predictors of high costs, along with certain treatments (bone marrow transplant and immunotherapy). Our findings suggest that quality payment programs should adjust for comorbidities, and that reducing toxicity may be an effective method at reducing costs.

145 Background: Palliative radiation treatment (pRT) is used for symptomatic bone metastases (mets). Several fractionation schedules show equal efficacy for pain relief, and ASTRO’s Choosing Wisely recommends 8Gy x1, 4Gy x5, or 3Gy x10. This study aims to investigate the cost implications of pRT for bone mets. Methods: Patients (Pts) treated with pRT for bone mets at Mayo Clinic from 2007 - 2016 were included in this study. Costs for all services were subdivided into RT and total costs at 30 & 90 days (30D & 90D). Standardized costs were obtained from the Mayo Clinic Cost Data Warehouse and Medicare reimbursements were assigned to all services with cost to charge adjustments and 2017 GDP Implicit Price Deflator for inflation. Cost means were compared via the Kruskal-Wallis test. Results: 538 pts were treated with pRT, 124 receiving 8Gy x1, 204 receiving 4Gy x5, and 210 receiving 3Gy x10. Pts with breast and prostate cancer were most likely to be treated with 3Gy x10 and pts with GI and lung cancer were most likely to be treated with 8Gy x1. RT costs at 30D were $1,497, $1,891, and $1,982 (p=0.03) and RT costs at 90D were $2,602, $2,753, and $3,032 (p=0.08) for initial RT regimens of 8Gy x1, 4Gy x5, and 3Gy x10. Total costs of care at 30D were similar from $15,969 - 17,687 (p=0.6) and total costs at 90D were similar from $22,361 - 23,219 (p=0.7) between arms. A total of 23%, 28%, and 39% of pts were alive 2 years following pRT from each arm (p=0.07). Conclusions: This is the first study of its kind to analyze actual treatment costs for the three most common pRT regimens in bone mets. Single fraction RT was most used for pts with poor prognoses and was associated with lower RT costs at 30D, but similar RT costs at 90D, possibly due to retreatment. RT choice had no impact on overall costs of care at 30D or 90D. pRT remains of high value, representing only 11-13% of total costs.[Table: see text]

126 Background: Palliative radiation treatment (pRT) is a common and effective treatment for patients with symptomatic bone metastases. However, patients receiving RT for bone metastases often may have a poor performance status and are more likely to experience toxicity during or after treatment. This study aims to investigate the number and type of toxicity event occurring during or after pRT for bone metastases. Methods: Patients treated with RT for bone metastases at Mayo Clinic from 2007 to 2016 were included in this study. Demographic, disease, treatment, and toxicity information were collected. Specifically, toxicity events were identified as emergency department (ED) visits and inpatient hospitalization (IH) within 90 days, breaks in treatment >4 days, and excessive 30 day financial toxicity defined as standardized Medicare costs >1 standard deviation above the mean. RT treatment was compared by dose and fractionation via descriptive statistics. Results: A total of 538 patients treated with pRT were identified, 124 receiving 8Gy x1, 204 receiving 4Gy x5, and 210 receiving 3Gy x10. Patients with breast and prostate cancer were most likely to be treated with 3Gy x10 and patients with GI and Lung cancer were most likely to be treated with 8Gy x1. A description of the patient characteristics and toxicities are shown in Table 1. For 8Gy x1, 4Gy x5, and 3Gy x10 breaks in treatment were rare (0%, 2%, and 3.3%), ED visits (15%, 24%, & 28%), IH (12%, 23%, & 19%), and financial toxicity (13%, 18%, & 21%) were common. A total of 22.6%, 27.5%, and 38.6% of patients were alive two years following pRT from each group. Conclusions: Toxicity during or shortly after pRT of bone metastases is common. This study confirms that additional steps should be taken to monitor and mitigate toxicity in this vulnerable patient group. [Table: see text]

147 Background: Prostate cancer patients treated with external beam radiation therapy are instructed to present daily with a full bladder to decrease small bowel and bladder toxicity and to increase reproducibility of treatment. However, older patients may have difficulty presenting with full bladders and variation of bladder volume with treatment is unknown. The objective of this study was to assess bladder filling at the time of radiation treatment (RT) using a bladder ultrasound in patients undergoing treatment for prostate cancer. Methods: Patients with prostate cancer were prospectively enrolled prior to CT simulation from January to August 2017. Bladder volume was recorded during CT simulation and daily immediately prior to RT. Patients were instructed to drink 8-12 ounces of water 30-60 minutes prior to RT. Three bladder volume measurements were recorded daily and averaged at the time of each treatment. Average bladder volume during treatment and the number of treatments with low bladder volumes ( < 50cc, < 60cc, and < 100cc) were reported using descriptive statistics. Results: A total of 13 patients completed a median of 42 days of RT during the study period, resulting in 550 daily bladder volumes. Ten patients were treated definitively and 3 with salvage radiation after prostatectomy. The median age of patients in the study was 72 years. Older patients were statistically more likely to present with low bladder volumes, with percentage of treatments with a bladder volume less than 50cc, 60cc, and 100cc being 29%, 42%, and 66% compared to only 4%, 7%, and 18% in patients aged < 70 (P < 0.01). The average bladder volume at the time of CT simulation was 176cc ± 57cc and the average volume during treatment was 140cc± 93cc, which was not statistically different (P = 0.28). The bladder volume did not significantly change over the course of treatment. Conclusions: Older patients (age 70+) with prostate cancer were more likely to present for RT with low bladder volumes in this prospective study. Our findings suggest that older patients should receive extra counseling about bladder filling and/or may require less bladder filling at the time of CT simulation to provide more accurate bowel dosimetry measurements.