EVALUATION OF INTENSITY MODULATED RADIATION THERAPY (IMRT) DELIVERY ERROR DUE TO IMRT TREATMENT PLAN COMPLEXITY AND IMPROPERLY MATCHED DOSIMETRY DATA

Intensity modulated radiation therapy (IMRT) is a technique that delivers a highly conformal dose distribution to a target volume while attempting to maximally spare the surrounding normal tissues. IMRT is a common treatment modality used for treating head and neck (H&N) cancers, and the presence of many critical structures in this region requires accurate treatment delivery. The Radiological Physics Center (RPC) acts as both a remote and on-site quality assurance agency that credentials institutions participating in clinical trials. To date, about 30% of all IMRT participants have failed the RPC’s remote audit using the IMRT H&N phantom. The purpose of this project is to evaluate possible causes of H&N IMRT delivery errors observed by the RPC, specifically IMRT treatment plan complexity and the use of improper dosimetry data from machines that were thought to be matched but in reality were not. Eight H&N IMRT plans with a range of complexity defined by total MU (1460-3466), number of segments (54-225), and modulation complexity scores (MCS) (0.181-0.609) were created in Pinnacle v.8m. These plans were delivered to the RPC’s H&N phantom on a single Varian Clinac. One of the IMRT plans (1851 MU, 88 segments, and MCS=0.469) was equivalent to the median H&N plan from 130 previous RPC H&N phantom irradiations. This average IMRT plan was also delivered on four matched Varian Clinac machines and the dose distribution calculated using a different 6MV beam model. Radiochromic film and TLD within the phantom were used to analyze the dose profiles and absolute doses, respectively. The measured and calculated were compared to evaluate the dosimetric accuracy. All deliveries met the RPC acceptance criteria of ±7% absolute dose difference and 4 mm distance-to-agreement (DTA). Additionally, gamma index analysis was performed for all deliveries using a ±7%/4mm and ±5%/3mm criteria. Increasing the treatment plan complexity by varying the MU, number of segments, or varying the MCS resulted in no clear trend toward an increase in dosimetric error determined by the absolute dose difference, DTA, or gamma index. Varying the delivery machines as well as the beam model (use of a Clinac 6EX 6MV beam model vs. Clinac 21EX 6MV model), also did not show any clear trend towards an increased dosimetric error using the same criteria indicated above.

Hemodynamic changes associated with manual and automated lateral rotation in mechanically ventilated intensive care patients

Objective: To investigate hemodynamic responses to lateral rotation. ^ Design: Time-series within a randomized controlled trial pilot study. ^ Setting: A medical intensive care unit (ICU) and a medical-surgical ICU in two tertiary care hospitals. ^ Patients: Adult patients receiving mechanical ventilation. ^ Interventions: Two-hourly manual or continuous automated lateral rotation. ^ Measurements and Main Results: Heart rate (HR) and arterial pressure were sampled every 6 seconds for > 24 hours, and pulse pressure (PP) was computed. Turn data were obtained from a turning flow sheet (manual turn) or with an angle sensor (automated turn). Within-subject ensemble averages were computed for HR, mean arterial pressure (MAP), and PP across turns. Sixteen patients were randomized to either the manual (n = 8) or automated (n = 8) turn. Three patients did not complete the study due to hemodynamic instability, bed malfunction or extubation, leaving 13 patients (n = 6 manual turn and n = 7 automated turn) for analysis. Seven patients (54%) had an arterial line. Changes in hemodynamic variables were statistically significant increases ( p < .05), but few changes were clinically important, defined as ≥ 10 bpm (HR) or ≥ 10 mmHg (MAP and PP), and were observed only in the manual-turn group. All manual-turn patients had prolonged recovery to baseline in HR, MAP and PP of up to 45 minutes (p ≤ .05). No significant turning-related periodicities were found for HR, MAP, or PP. Cross-correlations between variables showed variable lead-lag relations in both groups. A statistically, but not clinically, significant increase in HR of 3 bpm was found for the manual-turn group in the back compared with the right lateral position ( F = 14.37, df = 1, 11, p = .003). ^ Conclusions: Mechanically ventilated critically ill patients experience modest hemodynamic changes with manual lateral rotation. A clinically inconsequential increase in HR, MAP, and PP may persist for up to 45 minutes. Automated lateral rotation has negligible hemodynamic effects. ^

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Frequencies and risk factors for bisphosphonate-related osteonecrosis of the jaw in cancer patients: A matched case-control study

Bisphosphonates represent a unique class of drugs that effectively treat and prevent a variety of bone-related disorders including metastatic bone disease and osteoporosis. High tolerance and high efficacy rates quickly ranked bisphosphonates as the standard of care for bone-related diseases. However, in the early 2000s, case reports began to surface that linked bisphosphonates with osteonecrosis of the jaw (ONJ). Since that time, studies conducted have corroborated the linkage. However, as with most disease states, many factors can contribute to the onset of disease. The aim of this study was to determine which comorbid factors presented an increased risk for developing ONJ in cancer patients.^ Using a case-control study design, investigators used a combination of ICD-9 codes and chart review to identify confirmed cases of ONJ at The University of Texas M. D. Anderson Cancer Center (MDACC). Each case was then matched to five controls based on age, gender, race/ethnicity, and primary cancer diagnosis. Data querying and chart review provided information on variables of interest. These variables included bisphosphonate exposure, glucocorticoids exposure, smoking history, obesity, and diabetes. Statistical analysis was conducted using PASW (Predictive Analytics Software) Statistics, Version 18 (SPSS Inc., Chicago, Illinois).^ One hundred twelve (112) cases were identified as confirmed cases of ONJ. Variables were run using univariate logistic regression to determine significance (p < .05); significant variables were included in the final conditional logistic regression model. Concurrent use of bisphosphonates and glucocorticoids (OR, 18.60; CI, 8.85 to 39.12; p < .001), current smokers (OR, 2.52; CI, 1.21 to 5.25; p = .014), and presence of diabetes (OR, 1.84; CI, 1.06 to 3.20; p = .030) were found to increase the risk for developing ONJ. Obesity was not associated significantly with ONJ development.^ In this study, cancer patients that received bisphosphonates as part of their therapeutic regimen were found to have an 18-fold increase in their risk of developing ONJ. Other factors included smoking and diabetes. More studies examining the concurrent use of glucocorticoids and bisphosphonates may be able to strengthen any correlations.^

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^