Clinical Trials In Cancer Research Research Articles

A Grant-Based Experiment to Train Clinical Investigators: The AACR/ASCO Methods in Clinical Cancer Research Workshop.

To address the need for clinical investigators in oncology, American Association for Cancer Research (AACR) and American Society for Clinical Oncology (ASCO) established the Methods in Clinical Cancer Research Workshop (MCCRW). The workshop's objectives were to: (i) provide training in the methods, design, and conduct of clinical trials; (ii) ensure that clinical trials met federal and international ethical guidelines; (iii) evaluate the effectiveness of the workshop; and (iv) create networking opportunities for young investigators with mentoring senior faculty. Educational methods included: (i) didactic lectures, (ii) Small Group Discussion Sessions, (iii) Protocol Development Groups, and (iv) one-on-one mentoring. Learning focused on the development of an Institutional Review Board (IRB)-ready protocol, which was submitted on the last day of the workshop. Evaluation methods included: (i) pre- and postworkshop tests, (ii) students' workshop evaluations, (iii) faculty's ratings of protocol development, (iv) students' productivity in clinical research after the workshop, and (v) an independent assessment of the workshop. From 1996 to 2014, 1,932 students from diverse backgrounds attended the workshop. There was a significant improvement in the students' level of knowledge from the pre- to the postworkshop exams (P < 0.001). Across the classes, student evaluations were very favorable. At the end of the workshop, faculty rated 92% to 100% of the students' protocols as ready for IRB submission. Intermediate and long-term follow-ups indicated that more than 92% of students were actively involved in patient-related research, and 66% had implemented five or more protocols. This NCI-sponsored MCCRW has had a major impact on the training of clinicians in their ability to design and implement clinical trials in cancer research.

Longitudinal health-related quality of life analysis in oncology with time to event approaches, the STATA command qlqc30_TTD

Background and objectiveHealth-related quality of life (HRQoL) has become one relevant and available alternative endpoint of clinical trials in cancer research to evaluate efficiency of care both for the patient and health system. HRQoL in oncology is mainly assessed using the 30-item European Organisation for Research and Treatment of Cancer Quality of Life—Questionnaire Core 30 (EORTC QLQ-C30). The EORTC QLQ-C30 questionnaire is usually assessed at different times along the clinical trials in order to analyze the kinetics of HRQoL evolution and to fully assess the impact of the treatment on the patient's HRQoL level. In this perspective, the realization of a longitudinal HRQoL analysis is essential and the time to HRQoL score deterioration approach is a method which is more and more used in clinical trials. MethodUsing the Stata software, we developed a QLQ-C30 specific command, qlqc30_TTD, which implements longitudinal strategies based on the time to event methods by considering the time to HRQoL score deterioration. This user-written command providing automatic execution of the Time To Deterioration (TTD) and Time Until Definitive Deterioration (TUDD) methods. ResultThe program implements all published definitions and provides the Kaplan–Meier curves for each dimension (by group) and a table with the Hazard Ratio and Log-Rank test. ConclusionThe longitudinal analysis of HRQoL data in cancer clinical trials remains complex with only few programs like ours computed. This program will be of great help and will allow a more systematic and quicker analysis of the HRQoL data in clinical trials in oncology.

ACGT newsletter (Farewell article).

ACGT newsletter (Farewell article).

Recruitment of minority ethnic groups into clinical cancer research trials to assess adherence to the principles of the Department of Health Research Governance Framework: national sources of data and general issues arising from a study in one hospital trust in England

BackgroundThis article describes the issues encountered when designing a study to evaluate recruitment of minority ethnic groups into clinical cancer research in order to monitor adherence to the principles for...

Bayesian biostatistics and diagnostic medicine broemeling Lyle D (2007) ISBN 1584887672; 216 pages; £42.99, $83.95 Chapman &amp; Hall/CRC; http://www.crcpress.com/

It is interesting to read this book on Bayesian biostatistics and diagnostic medicine. Even though statistical methods for diagnostic medicine are not new topics in the literatures, this book has several unique features. Based on his research and consulting experiences at the University of Texas MD Anderson Cancer Centre (MDACC) in Houston, the author introduced the widely used statistical methods for diagnostics from solely Bayesian perspective. The concept was described with clear language supported with motivating real life examples. The author also provided readers with Minitab and WinBUGS codes, so that one can apply these methods to solve practical problems. The exercises at the end of each chapter were carefully and prudently constructed to complement and enhance the understanding of the main concept. The other valuable component of this book is the concise description of clinical trials for imaging, from core contents of protocols, the process of protocols review to aims of various phases of clinical trials. A brief overview of the book is as follows. Chapter 1 gives a short introduction and preview of the book. Chapters 2 and 3 succinctly explain the techniques commonly used in disease diagnoses, particularly those on the diagnostic imaging modalities for cancer patients. The usefulness, advantages and disadvantages of each procedure are discussed. Chapter 4 is the only theoretical section of this book. It starts with a general overview of the development of Bayesian methods. The basic Bayesian statistics concept, terminology, and MCMC technique are introduced and illustrated with simple applications. Chapters 5–7 describe how to design diagnostic studies for testing accuracy and agreement among measurements and how Bayesian methods can be utilised to analyse the data from such studies and thereafter make inferences. Chapter 8 provides more detailed description of the three phases of clinical trials in cancer research where imaging techniques are used, that described in Chapter 2. Also introduced in this chapter are the Bayesian sequential methods that are increasingly applied in the cancer trials and the software development for the design and analysis of such trials at MDACC. Finally, in Chapter 9, some advanced statistical techniques in the analysis of clinical data from studies in diagnostic medicine where imperfect procedures or no gold standard situations are encountered. One of the noticeable shortcomings in this book is the lack of introduction and interpretation of informative priors and its impact on the inferences. It is appreciated that in practice, particularly in the clinical trials, prior information is known, rational and adequate usage of such information must be emphasized. The other is that there is little facilitated explanation to the results of the examples, although this weak point can be complemented by numerous exercises given in the relevant chapters. Also, a few sections in Chapter 2 are replicated in Chapter 8. In some places, the entire paragraph is reprinted, for example, the protocol sections in the two chapters are almost identical word by word. Some misspellings are found in the text and in the WinBUGS codes, most of these typos, however, are minor and can be identified without causing readability problems. This book is, as indicated in the preface, written for biostatistics students. It is in my opinion an excellent introductory textbook on Bayesian methods and their application in diagnostic medicine. Non-experienced statisticians may also find that the systematic overview of the classification and purposes of the three phases in clinical trials and the basic Bayesian theory are useful references and would benefit from the program codes, particularly WinBUGS codes. Throughout the book, the author ensures that the minimum theoretical material is kept and effortless language is used. However, the students are expected to have obtained good knowledge of statistical methods commonly used in biomedical area. And the readers should have access to several reference books on statistical methods for diagnostics, for example, the ones by Pepe 1 and Zhou et al. 2 to fully comprehend the primary content of the book, not only because many examples are taken from these references, but also very brief introduction to the examples and little explanation to relate the maximum likelihood and Bayesian results have been given. Finally, it is worth notifying that the protocol review process described in the book and that adopted in pharmaceutical companies may not be exactly the same, but the importance in application of statistical methods in clinical trials and the input and influence of statisticians in writing and reviewing the protocols should be affirmed.

Rate limiting factors in recruitment of patients to clinical trials in cancer research: descriptive study

In 2004 the national cancer research network, established in 2001, will be evaluated on a performance target of increasing recruitment of patients into cancer clinical trials. The national average in...

Minorities, Women, and Clinical Cancer Research: The Charge, Promise, and Challenge

Significant progress has been made since the war against cancer was launched. Discoveries in molecular medicine, genetics, and epidemiology have led to the recognition that certain cancers are potentially preventable and that elements of lifestyle, along with genetic, hormonal, and metabolic factors can be altered to reduce cancer risk. Advances in medical technology have led to the development of new imaging methods and computer technologies that can aid in efforts to detect, diagnosis, and treat cancer. Since the offensive against cancer was initiated, cancer treatments have become more powerful, more precise, less drastic, and safer. As a result, cancer incidence and mortality have begun to decline. Yet, while the nation boasts of the progress being achieved relative to cancer incidence and mortality, and federal research agencies retort that research applies to all populations, it is apparent that the declines do not translate to all populations in the United States. Clinical research is essential to cancer prevention and control. Within the oncology community, clinical cancer research trials are viewed as an efficient and economical way for patients to secure state-of-the-science medical care. Recognizing the need to improve access to state-of-the-science cancer treatment and control programs, minority and female participation in clinical cancer research trials has been encouraged. This recommendation is based on the belief that increased participation in well-designed clinical cancer research trials adhering to strict protocols and quality controls will, not only help validate the application of research findings to minority and female populations, but also result in better patient outcomes. Born out of a commitment to social equity, justice, beneficence, and the desire to ensure that data relevant to cancer prevention and control are both valid and generalizable to populations across the United States, several programs of research aimed toward increasing the representation of women and minorities in clinical cancer research have been pursued by the National Cancer Institute. This issue of the Annals of Epidemiology Minorities, Women, and Clinical Cancer Research presents issues and challenges that face the research community and descriptions of effective models, strategies, and practices that may be used to increase the participation of minorities and women in clinical cancer research trials and facilitate the conduct of research directed toward reducing the cancer burden within the United States.

Controlled clinical trials in cancer research.

Knowledge of important aspects of the design and analysis of clinical trials is essential to clinical researchers and readers of medical literature. A brief description of proper trial design, including the contents of a trial protocol, as well as different strategies to avoid bias, is given. The concept of p-values is explained, and some commonly used statistical analysis methods are mentioned. Statistical power is defined, and two useful formulas and examples of estimating sample size are presented. The correct interpretation of trial results is emphasized, and misinterpretations and errors that frequently occur are dealt with. Various issues regarding multiple significance testing, such as interim analyses, multiple endpoints, and subgroup analyses, are addressed.

Clinical trials in cancer therapy: Efforts to improve patient enrollment by community oncologists

A prerequisite for the completion of a clinical trial is the accrual of adequate numbers of patients. It is estimated that over 90-95% of all cancer patients are now treated in their local communities by practicing oncologists and are not seen by primary investigators at teaching hospitals. One risk of this trend is decreased patient enrollment into clinical trials. The private practitioner often lacks the academic oncologist's incentives to participate in clinical research. The Hoosier Oncology Group (HOG) is composed of community medical and radiation oncologists (85%) and Indiana University faculty members (15%). In an effort to improve patient enrollment onto clinical cancer research trials, HOG has attempted to identify 1) the major obstacles to patient enrollment by community oncologists and 2) potential aids to overcome such obstacles. One hundred fourteen members were surveyed and 75 responded (66%). The major obstacles were, in descending order: time demands on both the oncologist and his staff; explaining clinical trials to patients; completing flow sheets; perceived increased cost to the patient; remembering protocols; adhering to a rigid protocol. Aids identified as potentially most helpful were, in descending order: pocket-sized synopses of protocols; computer generated, individualized prompts; the availability of a clinical trials specialist to explain the clinical trial to patients and assist in obtaining informed consent; the availability of a video tape which could be used to explain clinical trials to patients. These aids are being implemented with the attempt to systemically study their impact on patient accrual.

The size of clinical trials in cancer research--what are the current needs? Medical Research Council Cancer Therapy Committee.

Most randomised clinical trials of cancer treatment include a few hundred patients or less. Recent statistical papers advocate that sometimes thousands of patients should be entered. In this paper I show that for certain types of cancer trials the 'thousands policy' is not required while for others it is desirable but not feasible. In the latter case other strategies should be considered, such as two-stage phase III studies or parallel studies leading to overviews. There is, however, an important subset of trials for which application of the thousands policy is both necessary and feasible. The key to progress lies partly in the achievement of greater recruitment rates in trails of common cancers and partly in greater inter-group collaboration.

Clinical trials in cancer research--philosophical and methodological considerations: discussion paper.

Clinical trials in cancer research--philosophical and methodological considerations: discussion paper.

Reporting standards and research strategies for controlled trials: Agenda for the editor

From a study in Part I of many papers using controlled clinical trials in cancer research, we summarize quantitatively the frequency of reporting important statistical and procedural matters: randomization, statistical method, blindness, power, sample size, survival, and informed consent. We recommend that editors set standards for such reporting to improve readers' ability to evaluate trials. New research is needed to provide strategies for planning and analyzing collections of trials. We suggest in Part II the areas of generalizability, design, including size and allocation of sample and of volume of material collected, methods of reporting and analyzing imperfections in execution, and new archival work to take advantage, through reanalysis of trials and through analyzing collections of trials, of the substantial bodies of data already available.

Clinical trials in cancer research.

This is a review paper which gives a discussion of various aspects of clinical trials in cancer research. Since the conduct of the first randomized controlled clinical trial in cancer patients in the mid-1950's, substantial progress has been made in the utilization of the clinical trial technique for the evaluation of therapeutic efficiacy. The important elements of a protocol are given with some discussion of items to be considered in designing a protocol. The types of clinical trial (phase I, II, III) are defined, and the place of each phase of study in the context of the search for new treatments is delineated. A comprehensive discussion is given of the elements in the comparative clinical trial (phase III), including objectives, consierations in planning (comparability of treatment groups stratification of patients, feasibility and size of study, and prospective versus retrospective studies). Brief descriptions are given of designs for comparative clinical trials and a trial in oat cell lung carcinoma is discussed in some detail. Finally, some comments and references are given concerning the analysis of clinical trials.

Clinical Trials in Cancer Research

Clinical Trials in Cancer Research