ß-Endorphin mediates radiation therapy fatigue.

Fatigue is a common adverse effect of external beam radiation therapy in cancer patients. Mechanisms causing radiation fatigue remain unclear, although linkage to skin irradiation has been suggested. ß-Endorphin, an endogenous opioid, is synthesized in skin following genotoxic ultraviolet irradiation and acts systemically, producing addiction. Exogenous opiates with the same receptor activity as ß-endorphin can cause fatigue. Using rodent models of radiation therapy, exposing tails and sparing vital organs, we tested whether skin-derived ß-endorphin contributes to radiation-induced fatigue. Over a 6-week radiation regimen, plasma ß-endorphin increased in rats, paralleled by opiate phenotypes (elevated pain thresholds, Straub tail) and fatigue-like behavior, which was reversed in animals treated by the opiate antagonist naloxone. Mechanistically, all these phenotypes were blocked by opiate antagonist treatment and were undetected in either ß-endorphin knockout mice or mice lacking keratinocyte p53 expression. These findings implicate skin-derived ß-endorphin in systemic effects of radiation therapy. Opioid antagonism may warrant testing in humans as treatment or prevention of radiation-induced fatigue.

Comparison of 3D Conformal Proton Therapy, Intensity-Modulated Proton Therapy, and Intensity-Modulated Photon Therapy for Retroperitoneal Sarcoma.

Background: External beam radiation therapy (RT) for retroperitoneal sarcoma often requires treatment of large target volumes close to critical normal tissues. Radiation may be limited by adjacent organs at risk (OAR). Intensity-modulated radiation therapy has been shown to improve target coverage and reduce doses to OAR. Objectives: To compare target coverage and dose to OAR with 3D conformal proton therapy (3D CPT), intensity-modulated proton therapy (IMPT), and intensity-modulated photon therapy (IMXT). Methods: We performed a comparative study of treatment plans with 3D CPT, IMPT, and IMXT for ten patients with retroperitoneal sarcomas. RT was delivered to 50.4 Gy to the clinical target volume (CTV), the structures considered at risk for microscopic disease. Results: CTVs ranged from 74 to 357 cc (mean 188 cc). Dose conformity was improved with IMPT, while 3D CPT provided better dose homogeneity. Mean dose to the liver, small bowel, and stomach was reduced with IMPT compared with 3D CPT or IMXT. Conclusions: IMPT, 3D CPT, and IMXT provide excellent target coverage for retroperitoneal sarcomas. OAR dose is lower with IMPT and 3D CPT, and IMPT achieves the closest conformity. These techniques offer the opportunity for further dose escalation to areas with positive margins.

A note on point estimation and interval estimation of the relative treatment effect under a simple crossover design.

To increase power or reduce the number of patients needed for a parallel groups design, the crossover design has been often used to study treatments for noncurable chronic diseases. However, in the presence of carry-over effect caused by treatments, the commonly-used estimator which ignores the carry-over effect leads to a biased estimator for estimating the treatment effect difference. A two-stage test approach aimed to address carry-over effect proposed was found to be potentially misleading. In this paper, we propose a weighted average of the commonly-used estimator and an unbiased estimator that uses only the first period of the data. We derive an optimal weight that minimizes the mean squared error (MSE) and its modified estimator. We apply Monte Carlo simulation to evaluate the performance of the proposed estimators in a variety of situations. In the simulations, we examine the estimated MSE (EMSE), percentile interval length, and coverage probability calculated from the percentile intervals among considered estimators. Simulation results show that our proposed weighted average estimator and its modified estimator lead to smaller EMSEs on average comparing to the two commonly used estimators. The coverage probabilities using our proposed estimators are reasonably close to the nominal confidence level and the interval lengths are shorter comparing to the use of the unbiased estimator that uses only the first period of the data. We apply an example that was to evaluate the efficacy of two type of bronchodilators for asthma treatment to demonstrate the use of the proposed estimators.

Screening and Validation of Molecular Targeted Radiosensitizers.

The development of molecular targeted drugs with radiation and chemotherapy is critically important for improving the outcomes of patients with hard-to-treat, potentially curable cancers. However, too many preclinical studies have not translated into successful radiation oncology trials. Major contributing factors to this insufficiency include poor reproducibility of preclinical data, inadequate preclinical modeling of intertumoral genomic heterogeneity that influences treatment sensitivity in the clinic, and a reliance on tumor growth delay instead of local control (TCD50) endpoints. There exists an urgent need to overcome these barriers to facilitate successful clinical translation of targeted radiosensitizers. To this end, we have used 3-dimensional (3D) cell culture assays to better model tumor behavior in vivo. Examples of successful prediction of in vivo effects with these 3D assays include radiosensitization of head and neck cancers by inhibiting epidermal growth factor receptor or focal adhesion kinase signaling, and radioresistance associated with oncogenic mutation of KRAS. To address the issue of tumor heterogeneity, we leveraged institutional resources that allow high-throughput 3D screening of radiation combinations with small-molecule inhibitors across genomically characterized cell lines from lung, head and neck, and pancreatic cancers. This high-throughput screen is expected to uncover genomic biomarkers that will inform the successful clinical translation of targeted agents from the National Cancer Institute Cancer Therapy Evaluation Program portfolio and other sources. Screening "hits" need to be subjected to refinement studies that include clonogenic assays, addition of disease-specific chemotherapeutics, target/biomarker validation, and integration of patient-derived tumor models. The chemoradiosensitizing activities of the most promising drugs should be confirmed in TCD50 assays in xenograft models with or without relevant biomarker and using clinically relevant radiation fractionation. We predict that appropriately validated and biomarker-directed targeted therapies will have a higher likelihood than past efforts of being successfully incorporated into the standard management of hard-to-treat tumors.

Targeting the DNA replication stress phenotype of KRAS mutant cancer cells.

Mutant KRAS is a common tumor driver and frequently confers resistance to anti-cancer treatments such as radiation. DNA replication stress in these tumors may constitute a therapeutic liability but is poorly understood. Here, using single-molecule DNA fiber analysis, we first characterized baseline replication stress in a panel of unperturbed isogenic and non-isogenic cancer cell lines. Correlating with the observed enhanced replication stress we found increased levels of cytosolic double-stranded DNA in KRAS mutant compared to wild-type cells. Yet, despite this phenotype replication stress-inducing agents failed to selectively impact KRAS mutant cells, which were protected by CHK1. Similarly, most exogenous stressors studied did not differentially augment cytosolic DNA accumulation in KRAS mutant compared to wild-type cells. However, we found that proton radiation was able to slow fork progression and preferentially induce fork stalling in KRAS mutant cells. Proton treatment also partly reversed the radioresistance associated with mutant KRAS. The cellular effects of protons in the presence of KRAS mutation clearly contrasted that of other drugs affecting replication, highlighting the unique nature of the underlying DNA damage caused by protons. Taken together, our findings provide insight into the replication stress response associated with mutated KRAS, which may ultimately yield novel therapeutic opportunities.

Urinary metabolites of furan in waterpipe tobacco smokers compared to non-smokers in home settings in the US.

OBJECTIVES: Determine uptake of furan, a potential human carcinogen, in waterpipe tobacco (WPT) smokers in home settings. METHODS: We analysed data from a US convenience sample of 50 exclusive WPT smokers, mean age 25.3 years, and 25 non-smokers, mean age 25.5 years. For WPT smokers, data were collected at a home visit by research assistants during which participants smoked one WPT head of one brand for a mean of 33.1 min in their homes. Research assistants provided and prepared a WP for participants by weighing and loading 10 g of WPT in the WP head. At the completion of the smoking session, research assistants measured the remaining WPT. Cotinine and six furan metabolites were quantified in first morning urine samples provided on 2 consecutive days for non-smokers, and on the morning of a WPT smoking session and on the following morning for smokers. RESULTS: WPT smokers consumed a mean of 2.99 g WPT. In WPT smokers, urinary cotinine levels increased significantly 26.1 times the following morning; however, urinary metabolites of furan did not increase significantly. Compared to non-smokers, 2 furan metabolites, N-acetyl-S-[1-(5-acetylamino-5-carboxylpentyl)-1H-pyrrol-3-yl]-L-cysteine and N-acetyl-S-[1-(5-amino-5-carboxypentyl)-1H-pyrrol-3-yl]-L-cysteine sulfoxide, were significantly higher in WPT smokers in pre and in post WPT smoking levels. CONCLUSIONS: To enable a more rigorous assessment of furan exposure from WPT smoking, future research should determine furan concentrations in WPT smoke, quantify furan metabolites from users of various WPT brands; and extend the investigation to social settings where WPT smoking is habitually practiced.

Exact Confidence Limits on Some New Measures of Concordance and Discordance in Binary Outcomes.

Using a measure of agreement that does not distinguish the "positive" outcome from the "negative" outcome can be sometimes misleading in assessing resemblance. To alleviate this concern, some new indices, including the "positive" and "negative" conditional synchrony measures (CSM) (or the conditional discordant measures [CDM]), as well as their related measures, have been recently proposed elsewhere. We show that one can easily derive exact confidence limits for these new indices. Using Monte Carlo simulation, we find that the asymptotic interval estimator derived from the score test and these exact interval estimators can all perform well in a variety of situations, while the asymptotic interval estimator based on Wald's statistic can lose accuracy. We use the data taken from a cross-sectional validation study assessing the diagnostic performance of the Whooley questions for major depression disorder (MDD) among older adults to illustrate the use of these interval estimators developed here.

Exact interval estimators for some commonly used measures of binary agreement.

We develop exact interval estimators for some commonly used classical measures of agreement in binary responses. We apply Monte Carlo simulation to evaluate the performance of these estimators. When the measure of agreement is homogeneous, we note that extending the results presented here to accommodate stratified analysis is straightforward. We use the data taken from a survey studying the agreement of religious identifications and the data taken from a study assessing the diagnostic performance of Whooley questions for major depression disorder to illustrate the use of these interval estimators.

Estimation of the relative difference (or relative risk reduction) under the sequential parallel comparison design.

To increase power or reduce the number of patients needed in trials studying treatments for psychiatric or mental disorders with a high placebo response rate, we may consider use of the sequential parallel comparison design proposed elsewhere. Because statistical significance does not necessarily imply that the difference between treatment and placebo is of clinical importance, it is always of importance to quantify the treatment effect in clinical trials. When the patient responses are dichotomous, the treatment and other covariates effects are not likely additive. Thus, using a weighted average of the risk differences over two phases may not be a meaningful summary index to measure the treatment effect. To alleviate this concern, we consider use of the relative difference or relative risk reduction to measure the treatment effect. We derive both point and interval estimators for the relative difference by use of the weighted-least-squares estimator and Mantel-Haenszel type estimator. We employ Monte Carlo simulation to evaluate the finite-sample performance of these estimators in a variety of situations. We also include a procedure for testing the homogeneity of the relative difference between phases under the sequential parallel comparison design. We use the placebo-controlled study to assess the efficacy of a low dose of aripiprazole adjunctive to antidepressant therapy in the treatment of patients with major depressive disorder to illustrate the use of estimators developed here.

Asymptotic and exact interval estimators of the common odds ratio under the sequential parallel comparison design.

When studying treatments for psychiatric or mental diseases in a placebo-controlled trial, we may consider use of the sequential parallel comparison design to reduce the number of patients needed through the reduction of the high placebo response rate. Under the assumption that the odds ratio of responses is constant between phases in the sequential parallel comparison design, we derive the conditional maximum likelihood estimator for the odds ratio. On the basis of the conditional likelihood, we further derive three asymptotic interval and an exact interval estimators for the odds ratio of responses. We employ Monte Carlo simulation to evaluate the performance of these interval estimators in a variety of situations. We find that the asymptotic interval and exact interval estimators developed here can all perform well. We use the double-blind, placebo-controlled study assessing the efficacy of a low dose of aripiprazole adjunctive to antidepressant therapy for treating patients with major depressive disorder to illustrate the use of these estimators.

Exact and asymptotic tests under the sequential parallel comparison design.

When one studies treatments for psychological or mental diseases in a double-blind placebo-controlled trial with a high placebo response rate, the sequential parallel comparison design (SPCD) has been proposed elsewhere to improve power. All procedures for testing equality of treatments under the SPCD have been so far derived from large sample theory. If the trial size is small, asymptotic test procedures can be theoretically invalid. Thus, the development of an exact test procedure assuring type I error rate to be less than or equal to the nominal α-level is of use and interest. Using the conditional arguments to remove nuisance parameters, we derive two exact and one asymptotic procedures for testing equality of treatments for the SPCD. On the basis of Monte Carlo simulation, we find that all three test procedures can control type I error rate well in a variety of situations. We use the data taken from a double-blind placebo-controlled SPCD trial to assess the efficacy of a low dose (2 mg/day) of aripiprazole adjunctive to antidepressant therapy in the treatment of patients with major depressive disorder with a history of inadequate response to prior antidepressant therapy to illustrate the use of these test procedures.

Sample Size Determination for a 3-Treatment 3-Period Crossover Trial in Frequency Data.

BACKGROUND: To reduce the number of patients needed or increase the power of hypothesis testing for the parallel groups design, the crossover design has been often employed when one is studying noncurable chronic diseases. This article focuses attention on sample size calculation for testing non-inferiority and equality in frequency data under a 3-treatment 3-period crossover trial. METHOD: Under a multiplicative mixed effects model, this article provides asymptotic sample size calculation procedures for testing non-inferiority of an experimental treatment to a control treatment, as well as for simultaneously testing either of 2 treatments versus a placebo. To improve the performance of these asymptotic procedures in small-sample cases, this article further suggests a simple ad hoc adjustment. RESULTS: On the basis of Monte Carlo simulation, we demonstrate that the asymptotic test procedures proposed here can perform well with respect to Type I error. We find that the asymptotic sample size calculation procedures can generally perform well with respect to power when the resulting sample size is moderate or large. We further find that using the simple ad hoc adjustment can improve the performance of the proposed sample size calculation procedures, which are derived from large-sample theory, in small-sample cases.

Notes on Test and Estimation in Comparison of Three Treatments under A Simple Carry-Over Three-Period Model.

Under the three-treatment three-period crossover design with simple carry-over effects, we derive the least-squares estimators for period effects, treatment effects and carry-over effects, as well as their covariance matrix in closed and explicit expressions. Using Monte Carlo simulation, we compare the test procedure adjusting carry-over with that ignoring carry-over with respect to Type I error and power. We further compare interval estimators adjusting carry-over with those ignoring carry-over with respect to the coverage probability and the average length. When the variation of responses within patients is small, the test procedure and interval estimators ignoring carry-over can lose accuracy in the presence of carry-over effects. When the variation of responses within patients is large, this loss of accuracy may become small or even minimal. We note that the loss of efficiency due to the adjustment of carry-over under the simple carry-over three-period crossover design is moderate, and is much less than that found for a two-period crossover design. We use the double-blind three-period crossover trial comparing formoterol solution aerosol and salbutamol suspension aerosol with a placebo for patients suffering from exercise-induced asthma on the forced expiratory volume in one second (FEV1) to illustrate the use of test procedures and interval estimators discussed here.

Model-free tests of equality in binary data under an incomplete block design.

Using Prescott's model-free approach, we develop an asymptotic procedure and an exact procedure for testing equality between treatments with binary responses under an incomplete block crossover design. We employ Monte Carlo simulation and note that these test procedures can not only perform well in small-sample cases but also outperform the corresponding test procedures accounting for only patients with discordant responses published elsewhere. We use the data taken as a part of the crossover trial comparing two different doses of an analgesic with placebo for the relief of primary dysmenorrhea to illustrate the use of test procedures discussed here.

Exact tests in binary data under an incomplete block crossover design.

To improve the power of a parallel groups design and reduce the time length of a crossover trial, we may consider an incomplete block crossover design. Under a distribution-free random effects logistic regression model, we derive an exact test and a Mantel-Haenszel Type of summary test procedure for testing non-equality in binary data when comparing three treatments. We employ Monte Carlo simulation to evaluate the performance of these test procedures. We find that both test procedures developed here can perform well in a variety of situations. We use the data taken as a part of the crossover trial comparing the low and high doses of an analgesic with a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of the proposed test procedures.

Testing Equality of Treatments under an Incomplete Block Crossover Design with Ordinal Responses.

The generalized odds ratio (GOR) for paired sample is considered to measure the relative treatment effect on patient responses in ordinal data. Under a three-treatment two-period incomplete block crossover design, both asymptotic and exact procedures are developed for testing equality between treatments with ordinal responses. Monte Carlo simulation is employed to evaluate and compare the finite-sample performance of these test procedures. A discussion on advantages and disadvantages of the proposed test procedures based on the GOR versus those based on Wald's tests under the normal random effects proportional odds model is provided. The data taken as a part of a crossover trial studying the effects of low and high doses of an analgesic versus a placebo for the relief of pain in primary dysmenorrhea over the first two periods are applied to illustrate the use of these test procedures.

Estimation of the treatment effect under an incomplete block crossover design in binary data - A conditional likelihood approach.

A random effects logistic regression model is proposed for an incomplete block crossover trial comparing three treatments when the underlying patient response is dichotomous. On the basis of the conditional distributions, the conditional maximum likelihood estimator for the relative effect between treatments and its estimated asymptotic standard error are derived. Asymptotic interval estimator and exact interval estimator are also developed. Monte Carlo simulation is used to evaluate the performance of these estimators. Both asymptotic and exact interval estimators are found to perform well in a variety of situations. When the number of patients is small, the exact interval estimator with assuring the coverage probability larger than or equal to the desired confidence level can be especially of use. The data taken from a crossover trial comparing the low and high doses of an analgesic with a placebo for the relief of pain in primary dysmenorrhea are used to illustrate the use of estimators and the potential usefulness of the incomplete block crossover design.

Testing equality and interval estimation of the generalized odds ratio in ordinal data under a three-period crossover design.

The crossover design can be of use to save the number of patients or improve power of a parallel groups design in studying treatments to noncurable chronic diseases. We propose using the generalized odds ratio for paired sample data to measure the relative effects in ordinal data between treatments and between periods. We show that one can apply the commonly used asymptotic and exact test procedures for stratified analysis in epidemiology to test non-equality of treatments in ordinal data, as well as obtain asymptotic and exact interval estimators for the generalized odds ratio under a three-period crossover design. We further show that one can apply procedures for testing the homogeneity of the odds ratio under stratified sampling to examine whether there are treatment-by-period interactions. We use the data taken from a three-period crossover trial studying the effects of low and high doses of an analgesic versus a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of these test procedures and estimators proposed here.

Prescott tests of equality in binary data under a three-treatment three-period crossover design.

Three test procedures accounting for patients with tied responses based on Prescott's ideas are developed for comparing three treatments under a three-period crossover trial in binary data. Monte Carlo simulation is employed to evaluate the performance of these test procedures in a variety of situations. The test procedures proposed here are noted to have power larger than those procedures, which utilize only those patients with un-tied responses. The data taken from a three-period crossover trial comparing two different doses of an analgesic with placebo for the relief of primary dysmenorrhea are used to illustrate the use of the test procedures developed here.