A Medicare Claims Analysis of Racial and Ethnic Disparities in the Access to Radiation Therapy Services.

PURPOSE: Reduced access and utilization of radiation therapy (RT) is a well-documented healthcare disparity observed among racial and ethnic minority groups in the USA and a contributor to the inferior health outcomes observed among Black, Hispanic, and Native American patient groups. What is less understood are the points during the process of care following RT consultation at which patients either fail to complete their prescribed treatment or encounter delays. Identification of those points where significant differences exist among different patient groups may help identify opportunities to close gaps in the access of clinically indicated RT. METHODS AND MATERIALS: This analysis examines 261,559 RT episodes abstracted from Medicare claims and beneficiary data between 2016 and 2018 to determine rates of treatment initiation following planning and timeliness of treatment completion for different racial groups. RESULTS: Failure to initiate treatment was observed to be 29.3% relatively greater for Black, Hispanic, and Native American patients than for White and Asian patients. Among episodes for which treatment was initiated, Black and Hispanic patients were observed to require a significantly greater number of calendar days (when adjusted for fraction number) for completion than for White, Asian, and Native American patients. CONCLUSIONS: There appears to be a patient cohort for which RT disparities may be more marginal in their effects-allowing for access to consultation and treatment prescription but not for treatment initiation or timely completion of treatment-and may therefore permit effective solutions to help address current differences in cancer outcomes.

Radiation Oncology Alternative Payment Model and Large Urban Academic Centers: Future Implications for Patients and Providers.

The radiation oncology alternative payment model (RO-APM) was developed by the Center for Medicare and Medicaid Innovation, a part of the Centers for Medicare & Medicaid Services, as a vehicle to optimize value for patients undergoing radiation therapy. By shifting reimbursement away from fee-for-service and toward a prospective bundled payment system, the RO-APM is intended to bend the cost curve in radiation oncology while preserving or even enhancing outcomes. As with prior large-scale policy initiatives, the nature and magnitude of the RO-APM's impact on care delivery will vary substantially depending on a host of local factors, including practice setting. Urban academic centers play a key role in radiation oncology by spearheading innovation, managing the most complicated cases, training the next generation of radiation oncologists, and often caring for vulnerable patient populations. Thus, to protect patients' access to this high-quality cancer care, it will be crucial to characterize the RO-APM's projected impact on large urban academic institutions before its implementation, including possible unintended adverse consequences. Here, we provide an overview of this seismic change in radiation oncology reimbursement and discuss its unique potential implications for large urban academic institutions as a means to facilitate necessary preparations and inform future revisions to the model.

Disproportionate Negative Impact of the Radiation Oncology Alternative Payment Model on Rural Providers: A Cost Identification Analysis of Medicare Claims.

PURPOSE: The Radiation Oncology Alternative Payment Model (APM) is a Medicare demonstration project that will test whether prospective bundled payments to a randomly selected group of physician practices, hospital outpatient departments, and freestanding radiation therapy centers reduce overall expenditures while preserving or enhancing the quality of care for beneficiaries. The Model follows a complicated pricing methodology that blends historical reimbursements for a defined set of services made to professional and technical providers to create a weighted payment average for each of 16 cancer types. These averages are then adjusted by various factors to determine APM payments specific to each participating provider. METHODS: This impact study segregates APM participants into rural and urban groups and analyzes the effect of the Radiation Oncology Alternative Payment Model on their fee-for-service reimbursements. RESULTS: The main findings of this study are (1) the greater net-negative revenue impact on rural facilities versus urban facilities that would have participated in the Model this year and (2) the relative lack of high-value treatment services (ie, stereotactic radiotherapy and brachytherapy) delivered by rural facilities that exacerbates their negative impact. CONCLUSION: As such, rural providers participating in the Model in its current form may face greater risk to their economic viability and greater difficulty in funding technology improvements necessary for the achievement of high-quality care compared with their urban counterparts.

Impact of the Coronavirus Disease of 2019 Pandemic on Radiation Oncology Clinical Decision Making in a High-Prevalence Environment.

PURPOSE: This study aimed to define how the coronavirus disease of 2019 (COVID-19) pandemic affected the role, timing, and delivery of radiation therapy (RT) in a high-prevalence region at the height of the initial U.S. outbreak. METHODS AND MATERIALS: We performed a retrospective review of all patients seen at 3 radiation oncology departments within the Rutgers Robert Wood Johnson Barnabas Health system in New Jersey during the initial COVID-19 surge. The primary endpoints were to define and quantify COVID-related, radiation-specific care changes, and identify predictive factors of experiencing COVID-related care changes. RESULTS: A total of 545 patients with cancer were seen during the study period, 99 of whom (18.1%) experienced ≥1 COVID-related care change. RT delays were the most common, accounting for 51.5% of all care changes. Physician-directed delays accounted for 41.2% of RT delays, and patient fears, COVID testing, and access barriers were responsible for 27.5%, 17.6%, and 13.7%, respectively. Patient age (P = .040), intent of treatment (P = .047), and cancer type (P < .001) were significantly associated with experiencing a COVID-related care change, as we found that older, curative intent and patients with rectal cancer were more likely to experience care changes. On multivariate analysis, patient age remained significant when controlling for treatment intent and cancer type. CONCLUSIONS: Our study provides a perspective on how care was adapted to protect patients with cancer during a pandemic while maximizing disease control. The positive correlation between age and likelihood of care changes may reflect extra precaution taken with older patients given their vulnerability to severe COVID illness. The lower observed likelihood of COVID-related care changes among patients undergoing palliative RT may reflect either the more urgent needs addressed by palliative RT or simply be logistical, because palliative radiation is often delivered in short courses with less exposure risk. Assessing adaptations others have implemented and monitoring how they affect patient outcomes will be crucial.

Expanded Genomic Profiling of Circulating Tumor Cells in Metastatic Breast Cancer Patients to Assess Biomarker Status and Biology Over Time (CALGB 40502 and CALGB 40503, Alliance).

Purpose: We profiled circulating tumor cells (CTCs) to study the biology of blood-borne metastasis and to monitor biomarker status in metastatic breast cancer (MBC).Methods: CTCs were isolated from 105 patients with MBC using EPCAM-based immunomagnetic enrichment and fluorescence-activated cells sorting (IE/FACS), 28 of whom had serial CTC analysis (74 samples, 2-5 time points). CTCs were subjected to microfluidic-based multiplex QPCR array of 64 cancer-related genes (n = 151) and genome-wide copy-number analysis by array comparative genomic hybridization (aCGH; n = 49).Results: Combined transcriptional and genomic profiling showed that CTCs were 26% ESR1-ERBB2-, 48% ESR1+ERBB2-, and 27% ERBB2+ Serial testing showed that ERBB2 status was more stable over time compared with ESR1 and proliferation (MKI67) status. While cell-to-cell heterogeneity was observed at the single-cell level, with increasingly stable expression in larger pools, patient-specific CTC expression "fingerprints" were also observed. CTC copy-number profiles clustered into three groups based on the extent of genomic aberrations and the presence of large chromosomal imbalances. Comparative analysis showed discordance in ESR1/ER (27%) and ERBB2/HER2 (23%) status between CTCs and matched primary tumors. CTCs in 65% of the patients were considered to have low proliferation potential. Patients who harbored CTCs with high proliferation (MKI67) status had significantly reduced progression-free survival (P = 0.0011) and overall survival (P = 0.0095) compared with patients with low proliferative CTCs.Conclusions: We demonstrate an approach for complete isolation of EPCAM-positive CTCs and downstream comprehensive transcriptional/genomic characterization to examine the biology and assess breast cancer biomarkers in these cells over time. Clin Cancer Res; 24(6); 1486-99. ©2018 AACR.

Long-term Outcomes after Salvage Stereotactic Radiosurgery (SRS) following In-Field Failure of Initial SRS for Brain Metastases.

PURPOSE: The optimal treatment strategy following local recurrence after stereotactic radiosurgery (SRS) remains unclear. While upfront SRS has been extensively studied, few reports focus on outcomes after retreatment. Here, we report the results following a second course of SRS for local recurrence of brain metastases previously treated with SRS. METHODS: Using institutional database, patients who received salvage SRS (SRS2) following in-field failure of initial SRS (SRS1) for brain metastases were identified. Radionecrosis and local failure were defined radiographically by MRI following SRS2. The primary endpoint was defined as the time from SRS2 to the date of all-cause death or last follow-up [overall survival (OS)]. The secondary endpoints included local failure-free survival (LFFS) and radionecrosis-free survival, defined as the time from SRS2 to the date of local failure or radionecrosis, or last follow-up, respectively. RESULTS: Twenty-eight patients with 32 brain metastases were evaluated between years 2004 and 2015. The median interval between SRS1 and SRS2 was 9.7 months. Median OS was 22.0 months. Median LFFS time after SRS2 was 13.6 months. The overall local control rate following SRS2 was 84.4%. The 1- and 2-year local control rates are 88.3% (95% CI, 76.7-100%) and 80.3% (95% CI, 63.5-100%), respectively. The overall rate of radionecrosis following SRS2 was 18.8%. On univariate analysis, higher prescribed isodose line (p = 0.033) and higher gross tumor volume (p = 0.015) at SRS1 were associated with radionecrosis. Although not statistically significant, there was a trend toward lower risk of radionecrosis with interval surgical resection, fractionated SRS, lower total EQD2 (<50 Gy), and lack of concurrent systemic therapy at SRS2. CONCLUSION: In select patients, repeat LINAC-based SRS following recurrence remains a reasonable option leading to long-term survival and local control. Radionecrosis approaches 20% for high risk individuals and parallels historic values.

A comparative analysis between sequential boost and integrated boost intensity-modulated radiation therapy with concurrent chemotherapy for locally-advanced head and neck cancer.

BACKGROUND: Planning and delivery of IMRT for locally advanced head and neck cancer (LAHNC) can be performed using sequential boost or simultaneous integrated boost (SIB). Whether these techniques differ in treatment-related outcomes including survival and acute and late toxicities remain largely unexplored. METHODS: We performed a single institutional retrospective matched cohort analysis on patients with LAHNC treated with definitive chemoradiotherapy to 69.3 Gy in 33 fractions. Treatment was delivered via sequential boost (n = 68) or SIB (n = 141). Contours, plan evaluation, and toxicity assessment were performed by a single experienced physician. Toxicities were graded weekly during treatment and at 3-month follow up intervals. Recurrence-free survival, disease-free survival, and overall survival were estimated via Kaplan-Meier statistical method. RESULTS: At 4 years, the estimated overall survival was 69.3% in the sequential boost cohort and 76.8% in the SIB cohort (p = 0.13). Disease-free survival was 63 and 69% respectively (p = 0.27). There were no significant differences in local, regional or distant recurrence-free survival. There were no significant differences in weight loss (p = 0.291), gastrostomy tube placement (p = 0.494), or duration of gastrostomy tube dependence (p = 0.465). Rates of acute grade 3 or 4 dysphagia (82% vs 55%) and dermatitis (78% vs 58%) were significantly higher in the SIB group (p < 0.001 and p = 0.012 respectively). Moreover, a greater percentage of the SIB cohort did not receive the prescribed dose due to acute toxicity (7% versus 0, p = 0.028). CONCLUSIONS: There were no differences in disease related outcomes between the two treatment delivery approaches. A higher rate of grade 3 and 4 radiation dermatitis and dysphagia were observed in the SIB group, however this did not translate into differences in late toxicity. Additional investigation is necessary to further evaluate the acute toxicity differences.

Towards real-time topical detection and characterization of FDG dose infiltration prior to PET imaging.

PURPOSE: To dynamically detect and characterize 18F-fluorodeoxyglucose (FDG) dose infiltrations and evaluate their effects on positron emission tomography (PET) standardized uptake values (SUV) at the injection site and in control tissue. METHODS: Investigational gamma scintillation sensors were topically applied to patients with locally advanced breast cancer scheduled to undergo limited whole-body FDG-PET as part of an ongoing clinical study. Relative to the affected breast, sensors were placed on the contralateral injection arm and ipsilateral control arm during the resting uptake phase prior to each patient's PET scan. Time-activity curves (TACs) from the sensors were integrated at varying intervals (0-10, 0-20, 0-30, 0-40, and 30-40 min) post-FDG and the resulting areas under the curve (AUCs) were compared to SUVs obtained from PET. RESULTS: In cases of infiltration, observed in three sensor recordings (30 %), the injection arm TAC shape varied depending on the extent and severity of infiltration. In two of these cases, TAC characteristics suggested the infiltration was partially resolving prior to image acquisition, although it was still apparent on subsequent PET. Areas under the TAC 0-10 and 0-20 min post-FDG were significantly different in infiltrated versus non-infiltrated cases (Mann-Whitney, p < 0.05). When normalized to control, all TAC integration intervals from the injection arm were significantly correlated with SUVpeak and SUVmax measured over the infiltration site (Spearman ρ ≥ 0.77, p < 0.05). Receiver operating characteristic (ROC) analyses, testing the ability of the first 10 min of post-FDG sensor data to predict infiltration visibility on the ensuing PET, yielded an area under the ROC curve of 0.92. CONCLUSIONS: Topical sensors applied near the injection site provide dynamic information from the time of FDG administration through the uptake period and may be useful in detecting infiltrations regardless of PET image field of view. This dynamic information may also complement the static PET image to better characterize the true extent of infiltrations.

Predicting the Response of Breast Cancer to Neoadjuvant Therapy Using a Mechanically Coupled Reaction-Diffusion Model.

Although there are considerable data on the use of mathematical modeling to describe tumor growth and response to therapy, previous approaches are often not of the form that can be easily applied to clinical data to generate testable predictions in individual patients. Thus, there is a clear need to develop and apply clinically relevant oncologic models that are amenable to available patient data and yet retain the most salient features of response prediction. In this study we show how a biomechanical model of tumor growth can be initialized and constrained by serial patient-specific magnetic resonance imaging data, obtained at two time points early in the course of therapy (before initiation and following one cycle of therapy), to predict the response for individual patients with breast cancer undergoing neoadjuvant therapy. Using our mechanics coupled modeling approach, we are able to predict, after the first cycle of therapy, breast cancer patients that would eventually achieve a complete pathologic response and those who would not, with receiver operating characteristic area under the curve (AUC) of 0.87, sensitivity of 92%, and specificity of 84%. Our approach significantly outperformed the AUCs achieved by standard (i.e., not mechanically coupled) reaction-diffusion predictive modeling (0.75), simple analysis of the tumor cellularity estimated from imaging data (0.73), and the Response Evaluation Criteria in Solid Tumors (0.71). Thus, we show the potential for mathematical model prediction for use as a prognostic indicator of response to therapy. The work indicates the considerable promise of image-driven biophysical modeling for predictive frameworks within therapeutic applications.