Online adaptive radiotherapy: Assessment of planning technique and its impact on longitudinal plan quality robustness in pancreatic cancer.

BACKGROUND AND PURPOSE: Planning on a static dataset that reflects the simulation day anatomy is routine for SBRT. We hypothesize the quality of on-table adaptive plans is similar to the baseline plan when delivering stereotactic MR-guided adaptive radiotherapy (SMART) for pancreatic cancer (PCa). MATERIALS AND METHODS: Sixty-seven inoperable PCa patients were prescribed 50 Gy/5-fraction SMART. Baseline planning included: 3-5 mm gastrointestinal (GI) PRV, 50 Gy optimization target (PTVopt) based on GI PRV, conformality rings, and contracted GTV to guide the hotspot. For each adaptation, GI anatomy was re-contoured, followed by re-optimization. Plan quality was evaluated for target coverage (TC = PTVopt V100%/volume), PTV D90% and D80%, homogeneity index (HI = PTVopt D2%/D98%), prescription isodose/target volume (PITV), low-dose conformity (D2cm = maximum dose at 2 cm from PTVopt/Rx dose), and gradient index (R50%=50% Rx isodose volume/PTVopt volume).A novel global planning metric, termed the Pancreas Adaptive Radiotherapy Score (PARTS), was developed and implemented based on GI OAR sparing, PTV/GTV coverage, and conformality. Adaptive robustness (baseline to fraction 1) and stability (difference between two fractions with highest GI PRV variation) were quantified. RESULTS: OAR constraints were met on all baseline (n = 67) and adaptive (n = 318) plans. Coverage for baseline/adaptive plans was mean ± SD at 44.9 ± 5.8 Gy/44.3 ± 5.5 Gy (PTV D80%), 50.1 ± 4.2 Gy/49.1 ± 4.7 Gy (PTVopt D80%), and 80%±18%/74%±18% (TC), respectively. Mean homogeneity and conformality for baseline/adaptive plans were 0.87 ± 0.25/0.81 ± 0.30 (PITV), 3.81 ± 1.87/3.87 ± 2.0 (R50%), 1.53 ± 0.23/1.55 ± 0.23 (HI), and 58%±7%/59%±7% (D2cm), respectively. PARTS was found to be a sensitive metric due to its additive influence of geometry changes on PARTS' sub-metrics. There were no statistical differences (p > 0.05) for stability, except for PARTS (p = 0.04, median difference -0.6%). Statistical differences for robustness when significant were small for most metrics (<2.0% median). Median adaptive re-optimizations were 2. CONCLUSION: We describe a 5-fraction ablative SMART planning approach for PCa that is robust and stable during on-table adaption, due to gradients controlled by a GI PRV technique and the use of rings. These findings are noteworthy given that daily interfraction anatomic GI OAR differences are routine, thus necessitating on-table adaptation. This work supports feasibility towards utilizing a patient-independent, template on-table adaptive approach.

Relationship between insurance status and interhospital transfers among cancer patients in the United States.

BACKGROUND: The relationship between insurance status and interhospital transfers has not been adequately researched among cancer patients. Hence this study aimed for understanding this relationship using a nationally representative database. METHODS: A retrospective analysis was conducted using National Inpatient Sample (NIS) data collected during 2010-2016 and included all cancer hospitalization between 18 and 64 years of age. Interhospital transfers were compared based on insurance status (Medicare, Medicaid, private, and uninsured). Weighted multivariable logistic regressions were used to calculate the odds of interhospital transfers based on insurance status, after adjusting for many covariates. RESULTS: There were 3,580,908 weighted cancer hospitalizations, of which 72,353 (2.02%) had interhospital transfers. Uninsured patients had significantly higher rates of interhospital transfers, compared to those with Medicare (P = 0.005) and private insurance (P < 0.001). Privately insured patients had significantly lower rates of interhospital transfers, compared to those with Medicare (P < 0.001) and Medicaid (P < 0.001). Logistic regression analyses showed that the odds of having interhospital transfers were significantly higher among uninsured (adjusted odds ratio [aOR], 1.57, 95% CI: 1.45-1.69), Medicare (aOR, 1.38, 95% CI: 1.32-1.45) and Medicaid (aOR, 1.23, 95% CI: 1.16-1.30) patients when compared to those with private insurance coverages. CONCLUSION: Among cancer patients, uninsured and Medicare and Medicaid beneficiaries were more likely to experience interhospital transfers. In addition to medical reasons, factors such as affordability and socioeconomic status are influencing interhospital transfer decisions, indicating existing healthcare disparities. Further studies should focus on identifying the causal associations between factors explored in this study as well as additional unexplored factors.

Hospitalization rates for complications due to systemic therapy in the United States.

The aim of this study was to estimate the trends and burdens associated with systemic therapy-related hospitalizations, using nationally representative data. National Inpatient Sample data from 2005 to 2016 was used to identify systemic therapy-related complications using ICD-9 and ICD-10 external causes-of-injury codes. The primary outcome was hospitalization rates, while secondary outcomes were cost and in-hospital mortality. Overall, there were 443,222,223 hospitalizations during the study period, of which 2,419,722 were due to complications of systemic therapy. The average annual percentage change of these hospitalizations was 8.1%, compared to - 0.5% for general hospitalizations. The three most common causes for hospitalization were anemia (12.8%), neutropenia (10.8%), and sepsis (7.8%). Hospitalization rates had the highest relative increases for sepsis (1.9-fold) and acute kidney injury (1.6-fold), and the highest relative decrease for dehydration (0.21-fold) and fever of unknown origin (0.35-fold). Complications with the highest total charges were anemia ($4.6 billion), neutropenia ($3.0 billion), and sepsis ($2.5 billion). The leading causes of in-hospital mortality associated with systemic therapy were sepsis (15.8%), pneumonia (7.6%), and acute kidney injury (7.0%). Promoting initiatives such as rule OP-35, improving access to and providing coordinated care, developing systems leading to early identification and management of symptoms, and expanding urgent care access, can decrease these hospitalizations and the burden they carry on the healthcare system.

Improving Outcomes for Esophageal Cancer using Proton Beam Therapy.

Radiation therapy (RT) plays an essential role in the management of esophageal cancer. Because the esophagus is a centrally located thoracic structure there is a need to balance the delivery of appropriately high dose to the target while minimizing dose to nearby critical structures. Radiation dose received by these critical structures, especially the heart and lungs, may lead to clinically significant toxicities, including pneumonitis, pericarditis, and myocardial infarction. Although technological advancements in photon RT delivery like intensity modulated RT have decreased the risk of such toxicities, a growing body of evidence indicates that further risk reductions are achieved with proton beam therapy (PBT). Herein we review the published dosimetric and clinical PBT literature for esophageal cancer, including motion management considerations, the potential for reirradiation, radiation dose escalation, and ongoing esophageal PBT clinical trials. We also consider the potential cost-effectiveness of PBT relative to photon RT.

Comparison of 1-, 2-, and 3-Dimensional Tumor Response Assessment After Neoadjuvant GTX-RT in Borderline-Resectable Pancreatic Cancer.

BACKGROUND: Facilitation of margin-negative resection is the goal of neoadjuvant therapy regimens used in the treatment of borderline-resectable pancreatic cancer patients. Multiple treatment approaches have shown efficacy in this setting, including neoadjuvant GTX (gemcitabine [Gemzar], docetaxel [Taxotere], and capecitabine [Xeloda]) and radiotherapy (RT). Three-dimensional tumor response may be a more accurate method of assessment compared to traditional 1- and 2-dimensional techniques. We compared these 3 methods in a series of patients who underwent neoadjuvant GTX-RT and surgical resection. MATERIALS AND METHODS: This retrospective review included borderline-resectable pancreatic cancer patients treated with neoadjuvant GTX followed by 5-FU chemoradiotherapy with the intent of downstaging to resectability. Tumor was contoured on computed tomography (CT) scans obtained at the following time points: (A) initial staging, (B) CT simulation, and (C) restaging. These contours were used to determine tumor response according to WHO, RECIST, and volumetric criteria. RESULTS: Fourteen patients all experienced a measurable decrease in tumor volume following neoadjuvant therapy and were deemed suitable for at least surgical exploration. Radiotherapy was delivered to a median 50 Gy (range, 45-52 Gy) in 1.8-2.0 Gy fractions via 3-D conformal (21%) or IMRT (79%). The median percent volume changes before and after CT simulation were -3.4% and -52.6%, respectively. The overall median percent change was -54.5%. The corresponding absolute volume changes were -0.42 cm(3) (range, 9.12 to -12.47), -5.31 cm(3) (range, 2.06 to -15.93), and -6.72 cm(3) (range, 0.53 to -15.47), respectively. Response according to WHO, RECIST, and volumetric methods was identical with the exception of 1 patient. CONCLUSION: This is the first study to quantify volumetric tumor change objectively as a result of neoadjuvant chemoradiotherapy for the treatment of borderline resectable pancreatic cancer. Our data suggest that tumor response to neoadjuvant therapy is essentially equivalent between 1-, 2-, and 3-dimensional assessment methods.