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Marks L.B.,University of North Carolina at Chapel Hill | Adams R.D.,University of North Carolina at Chapel Hill | Pawlicki T.,University of California at San Diego | Blumberg A.L.,Greater Baltimore Medical Center | And 3 more authors.
Practical Radiation Oncology | Year: 2013

This report is part of a series of white papers commissioned for the American Society for Radiation Oncology (ASTRO) Board of Directors as part of ASTRO's Target Safely Campaign, focusing on the role of peer review as an important component of a broad safety/quality assurance (QA) program. Peer review is one of the most effective means for assuring the quality of qualitative, and potentially controversial, patient-specific decisions in radiation oncology. This report summarizes many of the areas throughout radiation therapy that may benefit from the application of peer review. Each radiation oncology facility should evaluate the issues raised and develop improved ways to apply the concept of peer review to its individual process and workflow. This might consist of a daily multidisciplinary (eg, physicians, dosimetrists, physicists, therapists) meeting to review patients being considered for, or undergoing planning for, radiation therapy (eg, intention to treat and target delineation), as well as meetings to review patients already under treatment (eg, adequacy of image guidance). This report is intended to clarify and broaden the understanding of radiation oncology professionals regarding the meaning, roles, benefits, and targets for peer review as a routine quality assurance tool. It is hoped that this work will be a catalyst for further investigation, development, and study of the efficacy of peer review techniques and how these efforts can help improve the safety and quality of our treatments. © 2013 American Society for Radiation Oncology.


Peng Y.,Queens University | Peng Y.,Queens Cancer Research Institute | Xu J.,Queens University
Lifetime Data Analysis | Year: 2012

We propose a novel interpretation for a recently proposed Box-Cox transformation cure model, which leads to a natural extension of the cure model. Based on the extended model, we consider an important issue of model selection between the mixture cure model and the bounded cumulative hazard cure model via the likelihood ratio test, score test and Akaike's Information Criterion (AIC). Our empirical study shows that AIC is informative and both the score test and the likelihood ratio test have adequate power to differentiate between the mixture cure model and the bounded cumulative hazard cure model when the sample size is large. We apply the tests and AIC methods to leukemia and colon cancer data to examine the appropriateness of the cure models considered for them in the literature. © 2012 Springer Science+Business Media, LLC.


Milosevic M.,University of Toronto | Parliament M.,University of Alberta | Brundage M.,Queens Cancer Research Institute
Radiotherapy and Oncology | Year: 2012

Purpose: The specialty of radiation oncology has experienced significant workforce planning challenges in many countries. Our purpose was to develop and validate a workforce-planning model that would forecast the balance between supply of, and demand for, radiation oncologists in Canada over a minimum 10-year time frame, to identify the model parameters that most influenced this balance, and to suggest how this model may be applicable to other countries. Methods: A forward calculation model was created and populated with data obtained from national sources. Validation was confirmed using a historical prospective approach. Results: Under baseline assumptions, the model predicts a short-term surplus of RO trainees followed by a projected deficit in 2020. Sensitivity analyses showed that access to radiotherapy (proportion of incident cases referred), individual RO workload, average age of retirement and resident training intake most influenced balance of supply and demand. Within plausible ranges of these parameters, substantial shortages or excess of graduates is possible, underscoring the need for ongoing monitoring. Conclusions: Workforce planning in radiation oncology is possible using a projection calculation model based on current system characteristics and modifiable parameters that influence projections. The workload projections should inform policy decision making regarding growth of the specialty and training program resident intake required to meet oncology health services needs. The methods used are applicable to workforce planning for radiation oncology in other countries and for other comparable medical specialties. © 2012 Elsevier Ireland Ltd. All rights reserved.


Peng Y.,Queens University | Peng Y.,Queens Cancer Research Institute | Taylor J.M.G.,University of Michigan
Statistics in Medicine | Year: 2011

Cure models for clustered survival data have the potential for broad applicability. In this paper, we consider the mixture cure model with random effects and propose several estimation methods based on Gaussian quadrature, rejection sampling, and importance sampling to obtain the maximum likelihood estimates of the model for clustered survival data with a cure fraction. The methods are flexible to accommodate various correlation structures. A simulation study demonstrates that the maximum likelihood estimates of parameters in the model tend to have smaller biases and variances than the estimates obtained from the existing methods. We apply the model to a study of tonsil cancer patients clustered by treatment centers to investigate the effect of covariates on the cure rate and on the failure time distribution of the uncured patients. The maximum likelihood estimates of the parameters demonstrate strong correlation among the failure times of the uncured patients and weak correlation among cure statuses in the same center. Copyright © 2010 John Wiley & Sons, Ltd.


Chander H.,Queens Cancer Research Institute | Truesdell P.,Queens Cancer Research Institute | Meens J.,Queens Cancer Research Institute | Craig A.W.B.,Queens Cancer Research Institute | Craig A.W.B.,Queens University
Oncogene | Year: 2013

Metastatic breast adenocarcinomas display activation signatures for signaling pathways that trigger cell motility and tissue invasion. Here, we report that the adaptor protein transducer of Cdc42-dependent actin assembly-1 (Toca-1) is expressed in highly invasive breast cancers and regulates their metastatic phenotypes. We show that Toca-1 localizes to the filamentous actin-rich core of invadopodial protrusions actively degrading the extracellular matrix (ECM). Toca-1 colocalizes with Cortactin, and we show that this interaction is mediated by the SH3 domain of Toca-1. Stable knockdown (KD) of Toca-1 expression in MDA-MB-231 cells led to a significant defect in epidermal growth factor (EGF)-induced cell migration and invasion. Toca-1 KD cells also showed significant defects in EGF-and Src-induced ECM digestion and formation of invadopodial membrane protrusions. To test the role of Toca-1 in metastasis, we achieved stable Toca-1 KD in both human and rat metastatic breast adenocarcinoma cell lines. Orthotopic tumor xenografting of control and Toca-1 KD cells in natural-killer/B-/T-cell-deficient mice revealed a significant defect in spontaneous lung metastases with Toca-1 silencing in vivo. In contrast, no defects in primary tumor growth or lung seeding following tail vein injection of Toca-1 KD cells was observed, suggesting that Toca-1 functions at an early step in the dissemination of metastatic breast tumor cells. Taken together, our results identify Toca-1 as a proinvasive protein in breast adenocarcinoma and a potential therapeutic target to limit tumor metastasis. © 2013 Macmillan Publishers Limited. All rights reserved.

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