Better access to information about clinical trials

Characteristics of Artificial Intelligence Clinical Trials in the Field of Healthcare: A Cross-Sectional Study on ClinicalTrials.gov

Artificial intelligence (AI) has driven innovative transformation in healthcare service patterns, despite a lack of understanding of its performance in clinical practice. We conducted a cross-sectional analysis of AI-related trials in healthcare based on ClinicalTrials.gov, intending to investigate the trial characteristics and AI's development status. Additionally, the Neo4j graph database and visualization technology were employed to construct an AI technology application graph, achieving a visual representation and analysis of research hotspots in healthcare AI. A total of 1725 eligible trials that were registered in ClinicalTrials.gov up to 31 March 2022 were included in this study. The number of trial registrations has dramatically grown each year since 2016. However, the AI-related trials had some design drawbacks and problems with poor-quality result reporting. The proportion of trials with prospective and randomized designs was insufficient, and most studies did not report results upon completion. Currently, most healthcare AI application studies are based on data-driven learning algorithms, covering various disease areas and healthcare scenarios. As few studies have publicly reported results on ClinicalTrials.gov, there is not enough evidence to support an assessment of AI's actual performance. The widespread implementation of AI technology in healthcare still faces many challenges and requires more high-quality prospective clinical validation.

The multiple dimensions of expanded access to health information: Don Lindberg and the U.S. National Library of Medicine

When Donald A. B. Lindberg M.D. became Director of the U.S. National Library of Medicine in 1984, trained searchers, primarily librarians, conducted less than three million searches of NLM databases. They paid for their fair share of the commercial telecommunications costs to reach NLM's computer system. In 2015 when Lindberg retired, millions of scientists, health professionals, patients, members of the public, and librarians conducted billions of free searches of NLM's greatly expanded electronic resources via the Internet. Lindberg came to NLM intending to expand access to biomedical and health information along multiple dimensions: reaching more users, providing more types and volumes of information and data; and improving the conceptual, technical, and organizational connections needed to provide information to users when and where it is needed. By any measure he and NLM were spectacularly successful. This chapter discusses some key decisions and developments that contributed to that success.

Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov

Although advances in machine-learning healthcare applications promise great potential for innovative medical care, few data are available on the translational status of these new technologies. We aimed to provide a comprehensive characterization of the development and status quo of clinical studies in the field of machine learning. For this purpose, we performed a registry-based analysis of machine-learning-related studies that were published and first available in the ClinicalTrials.gov database until 2020, using the database’s study classification. In total, n = 358 eligible studies could be included in the analysis. Of these, 82% were initiated by academic institutions/university (hospitals) and 18% by industry sponsors. A total of 96% were national and 4% international. About half of the studies (47%) had at least one recruiting location in a country in North America, followed by Europe (37%) and Asia (15%). Most of the studies reported were initiated in the medical field of imaging (12%), followed by cardiology, psychiatry, anesthesia/intensive care medicine (all 11%) and neurology (10%). Although the majority of the clinical studies were still initiated in an academic research context, the first industry-financed projects on machine-learning-based algorithms are becoming visible. The number of clinical studies with machine-learning-related applications and the variety of medical challenges addressed serve to indicate their increasing importance in future clinical care. Finally, they also set a time frame for the adjustment of medical device-related regulation and governance.

Cardiovascular Informatics: building a bridge to data harmony

The search for new strategies for better understanding cardiovascular disease is a constant one, spanning multitudinous types of observations and studies. A comprehensive characterization of each disease state and its biomolecular underpinnings relies upon insights gleaned from extensive information collection of various types of data. Researchers and clinicians in cardiovascular biomedicine repeatedly face questions regarding which types of data may best answer their questions, how to integrate information from multiple datasets of various types, and how to adapt emerging advances in machine learning and/or artificial intelligence to their needs in data processing. Frequently lauded as a field with great practical and translational potential, the interface between biomedical informatics and cardiovascular medicine is challenged with staggeringly massive datasets. Successful application of computational approaches to decode these complex and gigantic amounts of information becomes an essential step toward realizing the desired benefits. In this review, we examine recent efforts to adapt informatics strategies to cardiovascular biomedical research: automated information extraction and unification of multifaceted -omics data. We discuss how and why this interdisciplinary space of Cardiovascular Informatics is particularly relevant to and supportive of current experimental and clinical research. We describe in detail how open data sources and methods can drive discovery while demanding few initial resources, an advantage afforded by widespread availability of cloud computing-driven platforms. Subsequently, we provide examples of how interoperable computational systems facilitate exploration of data from multiple sources, including both consistently-formatted structured data and unstructured data. Taken together, these approaches for achieving data harmony enable molecular phenotyping of cardiovascular (CV) diseases and unification of cardiovascular knowledge.

Registering Study Analysis Plans (SAPs) Before Dissecting Your Data—Updating and Standardizing Outcome Modeling

Public preregistration of study analysis plans (SAPs) is widely recognized for clinical trials, but adopted to a much lesser extent in observational studies. Registration of SAPs prior to analysis is encouraged to not only increase transparency and exactness but also to avoid positive finding bias and better standardize outcome modeling. Efforts to generally standardize outcome modeling, which can be based on clinical trial and/or observational data, have recently spurred. We suggest a three-step SAP concept in which investigators are encouraged to (1) Design the SAP and circulate it among the co-investigators, (2) Log the SAP with a public repository, which recognizes the SAP with a digital object identifier (DOI), and (3) Cite (using the DOI), briefly summarize and motivate any deviations from the SAP in the associated manuscript. More specifically, the SAP should include the scope (brief data and study description, co-investigators, hypotheses, primary outcome measure, study title), in addition to step-by-step details of the analysis (handling of missing data, resampling, defined significance level, statistical function, validation, and variables and parameterization).

Characteristics of COVID-19 Clinical Trials in China Based on the Registration Data on ChiCTR and ClinicalTrials.gov

Objective

This study aimed to evaluate the fundamental characteristics of coronavirus disease (COVID-19) clinical trials registered in China.

Methods

COVID-19 clinical trials registered in China were analyzed from databases on ChiCTR and ClinicalTrials.gov. The study designs, samples, primary end points, and intervention measures were evaluated.

Results

In total, 262 intervention clinical trials were retrieved on March 10, 2020. Overall, 181 (69.1%) trials involved two groups, 200 (76.3%) trials were randomized parallel trials, 24 (9.2%) trials were double blind, and 60.3% of trials included ≤100 participants. Sixty (22.9%) trials considered symptom improvement as the primary endpoint and 43 (16.4%) trials considered the rate or time at which the subjects became virus-free as the primary endpoint. Of 262 intervention studies, chemical drugs and biological products were studied in 105 (40.1%) intervention studies, of which antiviral drugs accounted for 15.3% and malaria drugs accounted for 8.4% of the studies. Among all trials, 27.9% of the studies used traditional Chinese medicine (TCM), 10.3% used cell therapy, and 5.0% used plasma therapy.

Conclusion

This study is the first snapshot of the landscape of COVID-19 clinical trials registered in China and provided the basic features of clinical trial designs for the treatment and prevention of COVID-19 to offer useful information to guide future clinical trials on COVID-19 in other countries.

Donald A. B. Lindberg: Inspiring Leader and Visionary in Biomedicine, Healthcare, and Informatics

Background: As Director of the US National Library of Medicine (NLM) for 30 years, Dr. Donald A. B. Lindberg was instrumental in bringing biomedical research and healthcare worldwide into the age of genomic and translational medicine through the informatics systems developed by the NLM. Lindberg opened free access and worldwide public dissemination of all the NLM's biomedical literature and databases, thus helping transform not only biomedical research like the Human Genome Project and its successors, but also the practices of medicine and healthcare internationally. Guiding, leading, and teaching-by-example at national, regional, and global levels of biomedical and healthcare informatics, Lindberg helped coalesce a dynamic discipline that provides a foundation for the human understanding which promotes the future health of our world.

Objectives: To provide historical insight into the scientific, technological, and practical clinical accomplishments of Donald Lindberg, and to describe how this led to contributions in the worldwide interdisciplinary evolution of informatics, and its impact on the biosciences and practices of medicine, nursing, and other healthcare-related disciplines.

Methods: Review and comment on the publications, scientific contributions, and leadership of Donald Lindberg in the evolution of biomedical and health informatics which anticipate the vision, scholarship, research in the field, and represent the deeply ethical humanism he exhibited throughout his life. These were essential in producing the informatics systems, such as the Unified Medical Language System (UMLS), MEDLINE, PubMed, PubMed Central, and ClinicalTrials.gov , which, together with NLM training programs and conferences, made possible the interactions among researchers and practitioners leading to the past quarter-century of rapid and dramatic advances in biomedical scientific inquiry and clinical discoveries, openly shared across the globe.

Conclusion: Dr. Lindberg was a uniquely talented physician and pioneering researcher in biomedical and health informatics. As the main leader in developing and funding innovative informatics research for more than 30 years as Director of the National Library of Medicine, he helped bring together the most creative interdisciplinary researchers to bridge the worlds of biomedical research, education, and clinical practice. Lindberg's emphasis on open-access to the biomedical literature through publicly shared computer-mediated methods of search and inquiry are seen as an example of ethical scientific openness.

Current Status of PSMA-Radiotracers for Prostate Cancer: Data Analysis of Prospective Trials Listed on ClinicalTrials.gov

The recent development of dedicated prostate-specific membrane antigen (PSMA) targeted radioligands shows the potential to change and improve the diagnosis and therapy of prostate cancer. There is an increasing number of prospective trials to further establish these tracers in the clinical setting. We analyzed data from the ClinicalTrials.gov registry including all listed prospective trials with PSMA-ligands for prostate cancer as of October 2019 concerning the different tracers and study characteristics. We found n = 104 eligible studies with a total of n = 25 different tracers in use: most frequently [⁶⁸Ga]Ga-PSMA-11 (32%), followed by [¹⁸F]DCFPyL (24%) and [¹⁷⁷Lu]Lu-PSMA-617 (10%). 85% are single-center, 15% multi-center studies. 95% national and 5% international studies. 34% are phase-II, 24% phase-I, 13% phase-I/-II, 12% phase-II/-III and phase-III and 7% early-phase-I. The primary purpose was classified as diagnostic in 72% of cases and therapeutic in 23% of cases. Most studies were executed in the USA (70%), followed by Canada (13%) and France (6%). This quantitative descriptive registry analysis indicates the rapid and global clinical developments and current status of PSMA-radioligands with emphasis on radiopharmaceutical and organizational aspects. It will be very interesting to see which tracers will prevail in the clinical setting.

Disparities in Breast, Lung, and Cervical Cancer Trials Worldwide

Purpose

As cancer burden has risen worldwide, physicians, patients, and their advocates have become aware that the clinical cancer trial research paradigm is not ubiquitous. Furthermore, the number and characteristics of trials that are registered in low- and middle-income countries (LMICs) compared with that in high-income countries (HICs) are unknown.

Methods

We collected retrospective data on trials for breast, lung, and cervical cancer registered in ClinicalTrials.gov or with the WHO International Clinical Trial Registry Platform between 2010 and 2017. The data were then classified as trials within LMICs or HICs using definitions from the World Bank.

Results

Included in these analyses were 6,710 trials, of which 3,164 (47%) were breast cancer trials, 3,283 (49%) were lung cancer trials, and 263 (4%) were cervical cancer trials. There were 1,951 (29%) trials from LMICs and 4,759 (71%) trials from HICs (P < .001). Although the proportion of phase III trials in HICs versus LMICs was similar (18% v 17%; P = .66), the number of phase I trials in LMICs was significantly lower than that of HICs (20% v 2%; P < .001). For several LMICs with the highest mortality-to-incidence ratios for breast, lung, or cervical cancer, there were no cancer trials registered in the registration data bases searched for this work.

Conclusion

There are differences in access to cancer clinical trials in LMICs compared with HICs. Several factors, such as excessive cost and a lack of infrastructure and expertise, may explain these differences.

Development, acceptability, appropriateness and appeal of a cancer clinical trials implementation intervention for rural- and minority-serving urology practices

Background

Few community urologists offer cancer patients the opportunity to participate in cancer clinical trials, despite national guidelines that recommend it, depriving an estimated 260,000 urological cancer patients of guideline-concordant care each year. Existing strategies to increase urologists’ offer of clinical trials are designed for resource-rich environments and are not feasible for many community urologists. We sought to design an implementation intervention for dissemination in under-resourced community urology practices and to compare its acceptability, appropriateness and adoption appeal among trial-naïve and trial-experienced urologists.

Methods

We used a design-for-dissemination approach, informed by the Theoretical Domains Framework and Behavior Change Wheel, to match determinants of the clinical trial offer to theoretically informed implementation strategies. We described the implementation intervention in evaluation workshops offered at urology professional society meetings. We surveyed participants to assess the implementation intervention’s acceptability and appropriateness using validated instruments. We also measured adoption appeal, intention to adopt and previous trial offer.

Results

Our design process resulted in a multi-modal implementation intervention, comprised of multiple implementation strategies designed to address six domains from the Theoretical Domains Framework. Evaluation workshops delivered at four meetings, convened five separate professional societies. Sixty-one percent of those offered an opportunity to participate in the implementation intervention indicated intention to adopt. Average implementation intervention acceptability and appropriateness ratings were 4.4 and 4.4 (out of 5), respectively. Acceptability scores were statistically significantly higher among those offering trials compared to those not (p = 0.03). Appropriateness scores did not differ between those offering trials and those not (p = 0.24). After urologists ranked their top three innovation attributes, 43% of urologists included practice reputation in their top three reasons for offering clinical trials; 30% listed practice differentiation among their top three reasons. No statistically significant differences were found between those who offered trials and those who did not among any of the innovation attributes.

Conclusions

LEARN|INFORM|RECRUIT is a promising implementation intervention to address low accrual to clinical trials, poised for implementation and effectiveness testing. The implementation intervention is appealing to its target audience and may have equal uptake among trial-naïve and trial-experienced practices.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3658-z) contains supplementary material, which is available to authorized users.

Curtailing the Use of Preregistration: A Misused Term

Improving the usability of psychological research has been encouraged through practices such as prospectively registering research plans. Registering research aligns with the open-science movement, as the registration of research protocols in publicly accessible domains can result in reduced research waste and increased study transparency. In medicine and psychology, two different terms, registration and preregistration, have been used to refer to study registration, but applying inconsistent terminology to represent one concept can complicate both educational outreach and epidemiological investigation. Consistently using one term across disciplines to refer to the concept of study registration may improve the understanding and uptake of this practice, thereby supporting the movement toward improving the reliability and reproducibility of research through study registration. We recommend encouraging use of the original term, registration, given its widespread and long-standing use, including in national registries.

Accelerated Growth of Cellular Therapy Trials in Musculoskeletal Disorders: An Analysis of the NIH Clinical Trials Data Bank

The purpose of this study was to (1) determine the growth rate and the trends of musculoskeletal cellular therapy trials in the National Institutes of Health Clinical Trials Data Bank; (2) analyze the study design and characteristics; and (3) assess which cellular therapies and disease conditions are studied. A systematic review of musculoskeletal clinical trials from 2005 to 2016 using cell-based therapies as the primary intervention was performed through ClinicalTrials.gov. The number of musculoskeletal cell-based clinical trials is increasing, with most being early stage, phase I/II, and using autologous cells harvested mostly from bone marrow to target cartilage-related diseases. Among the 282 clinical trials identified, only 99 (35.1%) were completed; 62 of the 99 (62.6%) did not list any related publications. [Orthopedics. 2019; 42(2):e144-e150.].

Synthetic lethal combinations of low-toxicity drugs for breast cancer identified in silico by genetic screens in yeast

In recent years, the concept of synthetic lethality, describing a cellular state where loss of two genes leads to a non-viable phenotype while loss of one gene can be compensated, has emerged as a novel strategy for cancer therapy. Various compounds targeting synthetic lethal pathways are either under clinical investigation or are already routinely used in multiple cancer entities such as breast cancer. Most of them target the well-described synthetic lethal interplay between PARP1 and BRCA1/2. In our study, we investigated, using an in silico methodological approach, clinically utilized drug combinations for breast cancer treatment, by correlating their known molecular targets with known homologous interaction partners that cause synthetic lethality in yeast. Further, by creating a machine-learning algorithm, we were able to suggest novel synthetic lethal drug combinations of low-toxicity drugs in breast cancer and showed their negative effects on cancer cell viability in vitro. Our findings foster the understanding of evolutionarily conserved synthetic lethality in breast cancer cells and might lead to new drug combinations with favorable toxicity profile in this entity.

Disparities in Breast, Lung, and Cervical Cancer Trials Worldwide

PURPOSE

As cancer burden has risen worldwide, physicians, patients, and their advocates have become aware that the clinical cancer trial research paradigm is not ubiquitous. Furthermore, the number and characteristics of trials that are registered in low- and middle-income countries (LMICs) compared with that in high-income countries (HICs) are unknown.

METHODS

We collected retrospective data on trials for breast, lung, and cervical cancer registered in ClinicalTrials.gov or with the WHO International Clinical Trial Registry Platform between 2010 and 2017. The data were then classified as trials within LMICs or HICs using definitions from the World Bank.

RESULTS

Included in these analyses were 6,710 trials, of which 3,164 (47%) were breast cancer trials, 3,283 (49%) were lung cancer trials, and 263 (4%) were cervical cancer trials. There were 1,951 (29%) trials from LMICs and 4,759 (71%) trials from HICs ( P < .001). Although the proportion of phase III trials in HICs versus LMICs was similar (18% v 17%; P = .66), the number of phase I trials in LMICs was significantly lower than that of HICs (20% v 2%; P < .001). For several LMICs with the highest mortality-to-incidence ratios for breast, lung, or cervical cancer, there were no cancer trials registered in the registration data bases searched for this work.

CONCLUSION

There are differences in access to cancer clinical trials in LMICs compared with HICs. Several factors, such as excessive cost and a lack of infrastructure and expertise, may explain these differences.

Setting the IMPACT (IMProve Access to Clinical Trial data) Observatory baseline

Introduction

The aim of the IMPACT (IMProving Access to Clinical Trial data) Observatory is to assess the transformation of clinical trials (CT) related to the evolution of sharing of CT data. The objective of this study is to establish a baseline for monitoring CT data sharing by the Observatory.

Materials and methods

In this scoping review we searched for publications that address sharing, dissemination, transparency or reuse of CT data published prior to December 31st 2000. Two authors screened titles and abstracts of 1204 records received by Medline searches and added 47 publications from direct discovery. Four researchers extracted, coded, and analyzed the predefined information from 102 selected papers.

Results

We found a growing recognition of the importance of data sharing prior to 2001. However, there were numerous obstacles including the ambiguity of the concept of data sharing, the absence of specific terminology and the lack of an “open” culture. By the end of 2000, data, metadata, and evidence based medicine were defined. Data sharing, registries, databases and re-analyses of individual patient data (IPD) emerged. The use of systematic reviews and IPD meta-analysis in decision making was promoted. Most arguments for broader data sharing came from oncology, paediatrics, rare diseases, AIDS, pregnancy, perinatal medicine, and media reporting related scandals.

Conclusions

Our findings indicate that the year 2000 could be used as a baseline for monitoring the evolution of CT data sharing as basic prerequisites were set in place, including greater understanding that CT data sharing is essential for decision making and the advancements of the Internet.

Unreported links between trial registrations and published articles were identified using document similarity measures in a cross-sectional analysis of ClinicalTrials.gov

OBJECTIVES

Trial registries can be used to measure reporting biases and support systematic reviews, but 45% of registrations do not provide a link to the article reporting on the trial. We evaluated the use of document similarity methods to identify unreported links between ClinicalTrials.gov and PubMed.

STUDY DESIGN AND SETTING

We extracted terms and concepts from a data set of 72,469 ClinicalTrials.gov registrations and 276,307 PubMed articles and tested methods for ranking articles across 16,005 reported links and 90 manually identified unreported links. Performance was measured by the median rank of matching articles and the proportion of unreported links that could be found by screening ranked candidate articles in order.

RESULTS

The best-performing concept-based representation produced a median rank of 3 (interquartile range [IQR] 1-21) for reported links and 3 (IQR 1-19) for the manually identified unreported links, and term-based representations produced a median rank of 2 (1-20) for reported links and 2 (IQR 1-12) in unreported links. The matching article was ranked first for 40% of registrations, and screening 50 candidate articles per registration identified 86% of the unreported links.

CONCLUSION

Leveraging the growth in the corpus of reported links between ClinicalTrials.gov and PubMed, we found that document similarity methods can assist in the identification of unreported links between trial registrations and corresponding articles.

A systematic review of the processes used to link clinical trial registrations to their published results

BACKGROUND

Studies measuring the completeness and consistency of trial registration and reporting rely on linking registries with bibliographic databases. In this systematic review, we quantified the processes used to identify these links.

METHODS

PubMed and Embase databases were searched from inception to May 2016 for studies linking trial registries with bibliographic databases. The processes used to establish these links were categorised as automatic when the registration identifier was available in the bibliographic database or publication, or manual when linkage required inference or contacting of trial investigators. The number of links identified by each process was extracted where available. Linear regression was used to determine whether the proportions of links available via automatic processes had increased over time.

RESULTS

In 43 studies that examined cohorts of registry entries, 24 used automatic and manual processes to find articles; 3 only automatic; and 11 only manual (5 did not specify). Twelve studies reported results for both manual and automatic processes and showed that a median of 23% (range from 13 to 42%) included automatic links to articles, while 17% (range from 5 to 42%) of registry entries required manual processes to find articles. There was no evidence that the proportion of registry entries with automatic links had increased (R ² = 0.02, p = 0.36). In 39 studies that examined cohorts of articles, 21 used automatic and manual processes; 9 only automatic; and 2 only manual (7 did not specify). Sixteen studies reported numbers for automatic and manual processes and indicated that a median of 49% (range from 8 to 97%) of articles had automatic links to registry entries, and 10% (range from 0 to 28%) required manual processes to find registry entries. There was no evidence that the proportion of articles with automatic links to registry entries had increased (R ² = 0.01, p = 0.73).

CONCLUSIONS

The linkage of trial registries to their corresponding publications continues to require extensive manual processes. We did not find that the use of automatic linkage has increased over time. Further investigation is needed to inform approaches that will ensure publications are properly linked to trial registrations, thus enabling efficient monitoring of trial reporting.

Systematic review protocol assessing the processes for linking clinical trial registries and their published results

INTRODUCTION

Clinical trial registries are an important source of information for tracking clinical trials from their inception through to their reporting, and have been used to measure publication bias and outcome reporting bias. Our aim is to survey and quantify the processes that have been used to identify links between clinical trial registries and published trial reports in studies that rely on these links to evaluate the completeness and accuracy of trial reporting.

METHODS AND ANALYSIS

We will identify studies that describe a process for identifying the links between a trial registry included in the WHO International Clinical Trial Registry Platform and published trial results, and use those links to evaluate the completeness and accuracy of trial reporting. Information extracted from the studies will include the purpose and application domain of the study, registries used or searched, processes by which the links were identified, the study period and proportions for which links were found. We will summarise what is known about the number and availability of links between clinical trial registries and published results, and examine how automatic linking, inference and inquiry processes have been used to identify links since the introduction of trial registries.

ETHICS AND DISSEMINATION

The systematic review is focused on the analysis of secondary data and does not require ethics approval. The results of the systematic review will be used to inform standard processes used to identify links to and from clinical trial registries in studies that evaluate the completeness and accuracy of clinical trial reports, as well as systematic reviews. Our findings will be disseminated by publishing the systematic review in a peer-reviewed journal, and by engaging with stakeholders from clinical trial registries and bibliographic databases.

DEC-net: the development of the European register of clinical trials on medicines for children

Background The need to register a clinical trial in a public database has been widely discussed in the last few years. Several general clinical trial registers have been developed, but none are dedicated to children. A web-based register of trials on drug therapy in children was therefore developed.

Purpose The general objective of the project, called DEC-NET ( European register of clinical trials on medicines for children - drug evaluation in children) and supported by the European Community, is to provide the scientific community with a flexible tool for promoting communication and collaboration among researchers, disseminating clinical trial results and facilitating patient access and recruitment to trials.

Methods We identified a set of trial data to be collected, including general trial information, recruitment information, eligibility criteria, clinical trial characteristics, location and contact information, study drugs, study sponsor and results. The system was set up to allow authorized users (working in Italy, Spain, France and UK) to enter, handle and monitor the trial information. Medical data dictionaries (ie, ICD-9 and ATC) were used in order to make the data-entry and the search and data analysis procedures easier. A multilingual approach in data handling and presentation made accessing trial information in English and in the language of the country where the study is located feasible. Search and browsing tools were set up to allow investigators, researchers, and citizens to freely search and browse the entire register and access the details of trials meeting the search criteria.

Results The DEC-net register (http://www.dec-net.org) was opened for trial notification and consultation.

Limitations DEC-net currently involves four European countries and is a pilot project.

Conclusions It is hoped that what has been achieved so far represents only the beginning of a long-term project, and the next step will be to extend the register’s use to other European countries.

Characterizing treatment pathways at scale using the OHDSI network

Observational research promises to complement experimental research by providing large, diverse populations that would be infeasible for an experiment. Observational research can test its own clinical hypotheses, and observational studies also can contribute to the design of experiments and inform the generalizability of experimental research. Understanding the diversity of populations and the variance in care is one component. In this study, the Observational Health Data Sciences and Informatics (OHDSI) collaboration created an international data network with 11 data sources from four countries, including electronic health records and administrative claims data on 250 million patients. All data were mapped to common data standards, patient privacy was maintained by using a distributed model, and results were aggregated centrally. Treatment pathways were elucidated for type 2 diabetes mellitus, hypertension, and depression. The pathways revealed that the world is moving toward more consistent therapy over time across diseases and across locations, but significant heterogeneity remains among sources, pointing to challenges in generalizing clinical trial results. Diabetes favored a single first-line medication, metformin, to a much greater extent than hypertension or depression. About 10% of diabetes and depression patients and almost 25% of hypertension patients followed a treatment pathway that was unique within the cohort. Aside from factors such as sample size and underlying population (academic medical center versus general population), electronic health records data and administrative claims data revealed similar results. Large-scale international observational research is feasible.

Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015

BACKGROUND

A 1.5-day interactive forum was convened to discuss critical issues in the acquisition, analysis, and sharing of data in the field of cardiovascular and stroke science. The discussion will serve as the foundation for the American Heart Association's (AHA's) near-term and future strategies in the Big Data area. The concepts evolving from this forum may also inform other fields of medicine and science.

METHODS AND RESULTS

A total of 47 participants representing stakeholders from 7 domains (patients, basic scientists, clinical investigators, population researchers, clinicians and healthcare system administrators, industry, and regulatory authorities) participated in the conference. Presentation topics included updates on data as viewed from conventional medical and nonmedical sources, building and using Big Data repositories, articulation of the goals of data sharing, and principles of responsible data sharing. Facilitated breakout sessions were conducted to examine what each of the 7 stakeholder domains wants from Big Data under ideal circumstances and the possible roles that the AHA might play in meeting their needs. Important areas that are high priorities for further study regarding Big Data include a description of the methodology of how to acquire and analyze findings, validation of the veracity of discoveries from such research, and integration into investigative and clinical care aspects of future cardiovascular and stroke medicine. Potential roles that the AHA might consider include facilitating a standards discussion (eg, tools, methodology, and appropriate data use), providing education (eg, healthcare providers, patients, investigators), and helping build an interoperable digital ecosystem in cardiovascular and stroke science.

CONCLUSION

There was a consensus across stakeholder domains that Big Data holds great promise for revolutionizing the way cardiovascular and stroke research is conducted and clinical care is delivered; however, there is a clear need for the creation of a vision of how to use it to achieve the desired goals. Potential roles for the AHA center around facilitating a discussion of standards, providing education, and helping establish a cardiovascular digital ecosystem. This ecosystem should be interoperable and needs to interface with the rapidly growing digital object environment of the modern-day healthcare system.

Trend and Network Analysis of Common Eligibility Features for Cancer Trials in ClinicalTrials.gov

ClinicalTrials.gov has been archiving clinical trials since 1999, with > 165,000 trials at present. It is a valuable but relatively untapped resource for understanding trial design patterns and acquiring reusable trial design knowledge. We extracted common eligibility features using an unsupervised tag-mining method and mined their temporal usage patterns in clinical trials on various cancers. We then employed trend and network analysis to investigate two questions: (1) what eligibility features are frequently used to select patients for clinical trials within one cancer or across multiple cancers; and (2) what are the trends in eligibility feature adoption or discontinuation across cancer research domains? Our results showed that each cancer domain reuses a small set of eligibility features frequently for selecting cancer trial patients and some features are shared across different cancers, with value range adjustments for numerical measures. We discuss the implications for facilitating community-based clinical research knowledge sharing and reuse.

Inhibiting the RAS-PI3K pathway in cancer therapy

The PI3K pathway is over-activated in the majority of human cancers. This may occur through oncogenic activation of upstream RAS isoforms and tyrosine kinase receptors, or by mutational activation of components of the PI3K pathway themselves. Stimulation of the PI3K pathway enhances growth, survival, and metabolism of cancer cells. Migration, invasion, and angiogenesis are also supported by PI3K signaling. Thus, the PI3K pathway is an attractive candidate for the therapeutic targeting of tumors. Multiple kinases within the PI3Ks, AKT, and mTOR pathway have been selected for inhibition, and dual inhibitors have also been produced. Recently, the development of kinase inhibitors with enhanced specificity and improved pharmacokinetics has facilitated the investigation of PI3K pathway inhibition in clinical trials. Initial reports are encouraging, with tolerable toxicity profiles reported. PI3K inhibitors have provided some benefit as single-agent treatments of advanced solid tumors and the possibilities for enhanced effect with combination treatments look promising. In this chapter, we describe the PI3K inhibitors currently under investigation for the treatment of cancer and discuss the opportunities and obstacles that have been revealed by the latest preclinical and clinical studies.

Feasibility of feature-based indexing, clustering, and search of clinical trials. A case study of breast cancer trials from ClinicalTrials.gov

BACKGROUND

When standard therapies fail, clinical trials provide experimental treatment opportunities for patients with drug-resistant illnesses or terminal diseases. Clinical Trials can also provide free treatment and education for individuals who otherwise may not have access to such care. To find relevant clinical trials, patients often search online; however, they often encounter a significant barrier due to the large number of trials and in-effective indexing methods for reducing the trial search space.

OBJECTIVES

This study explores the feasibility of feature-based indexing, clustering, and search of clinical trials and informs designs to automate these processes.

METHODS

We decomposed 80 randomly selected stage III breast cancer clinical trials into a vector of eligibility features, which were organized into a hierarchy. We clustered trials based on their eligibility feature similarities. In a simulated search process, manually selected features were used to generate specific eligibility questions to filter trials iteratively.

RESULTS

We extracted 1,437 distinct eligibility features and achieved an inter-rater agreement of 0.73 for feature extraction for 37 frequent features occurring in more than 20 trials. Using all the 1,437 features we stratified the 80 trials into six clusters containing trials recruiting similar patients by patient-characteristic features, five clusters by disease-characteristic features, and two clusters by mixed features. Most of the features were mapped to one or more Unified Medical Language System (UMLS) concepts, demonstrating the utility of named entity recognition prior to mapping with the UMLS for automatic feature extraction.

CONCLUSIONS

It is feasible to develop feature-based indexing and clustering methods for clinical trials to identify trials with similar target populations and to improve trial search efficiency.

Evidence for multiple micronutrient effects based on randomized controlled trials and meta-analyses in developing countries

Providing multiple micronutrients via supplements, powders, or fortified ready-to-use foods is increasingly becoming a strategy for simultaneously addressing multiple nutrient deficiencies in developing countries. The pros and cons of the "gold standard" randomized controlled trial (RCT) design and meta-analyses of trials for establishing efficacy of nutritional interventions are discussed. Over the past decade, numerous RCT have been undertaken to test the efficacy of multiple micronutrient supplementation in both pregnant women and young children. Outcomes of interest have ranged from birth weight to child growth, and infant morbidity and mortality to nutrient status and cognitive function. These RCT have also been submitted to meta-analyses for estimating pooled effect sizes for various outcomes. Meta-analyses of antenatal multiple micronutrient supplementation reveal a modest but significant increase in birth weight of 22.4 g (95% CI: 8.3, 36.4 g) and an 11% (95% CI: 3, 19) reduction in low birth weight but no impact on preterm birth or perinatal mortality. In children, small effect sizes of 0.13 (95% CI: 0.06, 0.21) for length/height and 0.14 (95% CI: 0.03, 0.25) for weight have been shown with 3 or more micronutrients compared to fewer micronutrients, but there is limited evidence for an impact on outcomes such as morbidity and cognitive function. Gaps in research and future challenges for programmatic application of this strategy for both pregnant women and young children are discussed.

The NIAID Division of AIDS enterprise information system: integrated decision support for global clinical research programs

The National Institute of Allergy and Infectious Diseases (NIAID) Division of AIDS (DAIDS) Enterprise Information System (DAIDS-ES) is a web-based system that supports NIAID in the scientific, strategic, and tactical management of its global clinical research programs for HIV/AIDS vaccines, prevention, and therapeutics. Different from most commercial clinical trials information systems, which are typically protocol-driven, the DAIDS-ES was built to exchange information with those types of systems and integrate it in ways that help scientific program directors lead the research effort and keep pace with the complex and ever-changing global HIV/AIDS pandemic. Whereas commercially available clinical trials support systems are not usually disease-focused, DAIDS-ES was specifically designed to capture and incorporate unique scientific, demographic, and logistical aspects of HIV/AIDS treatment, prevention, and vaccine research in order to provide a rich source of information to guide informed decision-making. Sharing data across its internal components and with external systems, using defined vocabularies, open standards and flexible interfaces, the DAIDS-ES enables NIAID, its global collaborators and stakeholders, access to timely, quality information about NIAID-supported clinical trials which is utilized to: (1) analyze the research portfolio, assess capacity, identify opportunities, and avoid redundancies; (2) help support study safety, quality, ethics, and regulatory compliance; (3) conduct evidence-based policy analysis and business process re-engineering for improved efficiency. This report summarizes how the DAIDS-ES was conceptualized, how it differs from typical clinical trial support systems, the rationale for key design choices, and examples of how it is being used to advance the efficiency and effectiveness of NIAID's HIV/AIDS clinical research programs.

Dynamic categorization of clinical research eligibility criteria by hierarchical clustering

OBJECTIVE

To semi-automatically induce semantic categories of eligibility criteria from text and to automatically classify eligibility criteria based on their semantic similarity.

DESIGN

The UMLS semantic types and a set of previously developed semantic preference rules were utilized to create an unambiguous semantic feature representation to induce eligibility criteria categories through hierarchical clustering and to train supervised classifiers.

MEASUREMENTS

We induced 27 categories and measured the prevalence of the categories in 27,278 eligibility criteria from 1578 clinical trials and compared the classification performance (i.e., precision, recall, and F1-score) between the UMLS-based feature representation and the "bag of words" feature representation among five common classifiers in Weka, including J48, Bayesian Network, Naïve Bayesian, Nearest Neighbor, and instance-based learning classifier.

RESULTS

The UMLS semantic feature representation outperforms the "bag of words" feature representation in 89% of the criteria categories. Using the semantically induced categories, machine-learning classifiers required only 2000 instances to stabilize classification performance. The J48 classifier yielded the best F1-score and the Bayesian Network classifier achieved the best learning efficiency.

CONCLUSION

The UMLS is an effective knowledge source and can enable an efficient feature representation for semi-automated semantic category induction and automatic categorization for clinical research eligibility criteria and possibly other clinical text.

[Searching clinical trials registries: procedure and documentation]

The identification of unpublished data is an important component in the assessment of drugs for a systematic review. This is why searching in clinical trials registries is indispensable. However, this type of search is not regularly conducted. At present, clinical trials registries that also contain results data are still seldom-used sources, which may be due to a number of reasons. On the one hand, there are a large number of clinical trials registries whose quality is difficult to judge sometimes; on the other hand, their heterogeneity and partly inadequate functionality such as, for example, the lack of export options, complicate searches of these sources. The present paper addresses the features of searches in clinical trials registries and describes the approach taken by the German Institute for Quality and Efficiency in Health Care (IQWiG). Initially, we describe the various types of registries and offer assistance with the selection of the clinical trials registries to be searched. A further focus lies on the description of the search procedure itself, as well as on the selection of the relevant registry entries and the documentation of this process in order to support those planning their own search in clinical trials registries.

MeSHing molecular sequences and clinical trials: a feasibility study

The centralized and public availability of molecular sequence and clinical trial data presents an opportunity to identify potentially valuable linkages across the bench-to-bedside "T1" translational barrier. In this study, we sought to leverage keyword metadata (Medical Subject Heading [MeSH] descriptors) to infer relationships between molecular sequences and clinical trials, as indexed by GenBank and ClinicalTrials.gov. The results of this feasibility study found that approximately 30% of sequences in GenBank could be linked to trials and over 90% of trials in ClinicalTrials.gov could be linked to sequences through MeSH descriptors. In a cursory evaluation, we were able to consistently identify meaningful linkages between molecular sequences and clinical trials. Based on our findings, there may be promise in subsequent studies aiming to identify linkages across the T1 translational barrier using existing large repositories.

Poor reporting of scientific leadership information in clinical trial registers

Background

In September 2004, the International Committee of Medical Journal Editors (ICMJE) issued a Statement requiring that all clinical trials be registered at inception in a public register in order to be considered for publication. The World Health Organization (WHO) and ICMJE have identified 20 items that should be provided before a trial is considered registered, including contact information. Identifying those scientifically responsible for trial conduct increases accountability. The objective is to examine the proportion of registered clinical trials providing valid scientific leadership information.

Methodology/Principal Findings

We reviewed clinical trial entries listing Canadian investigators in the two largest international and public trial registers, the International Standard Randomized Controlled Trial Number (ISRCTN) register, and ClinicalTrials.gov. The main outcome measures were the proportion of clinical trials reporting valid contact information for the trials' Principal Investigator (PI)/Co-ordinating Investigator/Study Chair/Site PI, and trial e-mail contact address, stratified by funding source, recruiting status, and register. A total of 1388 entries (142 from ISRCTN and 1246 from ClinicalTrials.gov) comprised our sample. We found non-compliance with mandatory registration requirements regarding scientific leadership and trial contact information. Non-industry and partial industry funded trials were significantly more likely to identify the individual responsible for scientific leadership (OR = 259, 95% CI: 95–701) and to provide a contact e-mail address (OR = 9.6, 95% CI: 6.6–14) than were solely industry funded trials.

Conclusions/Significance

Despite the requirements set by WHO and ICMJE, data on scientific leadership and contact e-mail addresses are frequently omitted from clinical trials registered in the two leading public clinical trial registers. To promote accountability and transparency in clinical trials research, public clinical trials registers should ensure adequate monitoring of trial registration to ensure completion of mandatory contact information fields identifying scientific leadership

The Society for Clinical Trials supports United States legislation mandating trials registration. Position paper

The official position of the Society for Clinical Trials is to support legislation in the United States and internationally that mandates registration of all controlled clinicals trials at or before enrollment of the first participant. The major trial sponsor would be responsible for ensuring contribution of trial information. The mechanism for registering trials would be through research ethics review boards, and registration would be required for ethics approval and before trial initiation. Standardized data and a unique identification number would be available for each registered trial.

Breast cancer patients' attitudes toward clinical trials in the radiation oncology clinic versus those searching for trial information on the Internet

Web-based clinical trials matching systems including breast cancer patients are expanding rapidly. However, limited data exist regarding the demographics and attitudes of breast cancer patients using the Internet to search for clinical trials information. Biases in patient populations could be introduced by recruiting patients to trials through the Internet. This study was designed to compare breast cancer patients in the radiation oncology clinic to those using the Internet to search for clinical trials information. A piloted questionnaire assessing demographics and attitudes regarding clinical trials was offered through the radiation oncology clinic at the University of Pennsylvania and on the OncoLink website (http://www.oncolink.org). The questionnaire consisted of 18 questions and was answered by a total of 157 patients with breast cancer. Breast cancer patients using the Web were more likely to be interested in clinical trials testing new drugs or therapies (71 [53%] versus 4 [17%], p = 0.002). More clinic patients indicated they would need a greater than 50% chance of benefiting from a trial (12 [52%] versus 33 [25%], p = 0.01) and a less than 10% potential for serious toxicity from a trial (15 [65%] versus 51 [38%], p = 0.02) for consideration of enrollment. African Americans were more likely than other races to have never used the Internet to search for cancer-related information (4 [40%] versus 18 [12%], p = 0.01), more likely to indicate that they need a greater than 50% chance of benefit to enroll in clinical trials (8 [80%] versus 37 [25%], p = 0.001), and less likely to be interested in clinical trials testing new drugs or therapies (1 [10%] versus 73 [50%], p = 0.01). Breast cancer patients have different attitudes regarding clinical trials based on race, Internet usage, and previous trial enrollment. Biases may be introduced with recruitment for clinical trials through the Internet. Radiation oncologists must consider these issues when offering clinical trials information through the Internet.

Synthesizing medical evidence: systematic reviews and metaanalyses

Systematic reviews and metaanalyses have become increasingly popular ways of summarizing, and sometimes extending, existing medical knowledge. In this review the authors summarize current methods of performing meta-analyses, including the following: formulating a research question; performing a structured literature search and a search for trials not published in the formal medical literature; summarizing and, where appropriate, combining results from several trials; and reporting and presenting results. Topics such as cumulative and Bayesian metaanalysis and metaregression are also addressed. References to textbooks, articles, and Internet resources are also provided. The goal is to assist readers who wish to perform their own metaanalysis or to interpret critically a published example.

Breaking the Translational Barriers: The Value of Integrating Biomedical Informatics and Translational Research

The conduct of translational health research has become a vital national enterprise. However, multiple barriers prevent the effective translation of basic science discoveries into clinical and community practice. New information technology (IT) applications could help address these barriers. Unfortunately, owing to a combination of organizational, technical, and social factors, neither physician-investigators and research staff nor their clinical and community counterparts have harnessed such applications. Recently, at the request of the Institute of Medicine's Clinical Research Roundtable, a qualitative study of these factors was conducted at several leading academic medical centers. We explore the current status of IT in the translational research domain, describe the qualitative results, and conclude with a proposed set of initiatives to further increase the integration of IT into translational research.

Should nortriptyline be used as a first-line aid to help smokers quit? Results from a systematic review and meta-analysis

OBJECTIVES

The objective of this paper is to evaluate the efficacy of nortriptyline for smoking cessation compared to placebo and bupropion sustained release.

DATA SOURCES

Randomized trials were identified by (1) checking electronic and (2) online publicly accessible registers of clinical trials; (3) searching references of identified studies and screening abstract books of conferences and symposia, and (4) personal communication with the first authors of identified papers.

REVIEW METHODS

We included randomized trials in which nortriptyline was compared to placebo or bupropion hydrochloride SR. The main clinical outcome measure was (at least) 6-month prolonged abstinence, confirmed with a biochemical test. To investigate the efficacy of nortriptyline in time, we calculated the percentage of smokers who relapsed in time.

RESULTS

We identified five randomized trials, including 861 smokers. Compared to placebo medication, nortriptyline resulted in significantly higher prolonged abstinence rates after at least 6 months [relative risk (RR) = 2.4, 95% CI 1.7-3.6; RD = 0.11, 95% CI 0.07-0.15]. The difference in efficacy between nortriptyline and placebo was highest in the first months after the target quit date. However, the number of people who remained abstinent decreased substantially and significantly faster over time in the nortriptyline group. Although bupropion resulted in higher abstinence rates compared with nortriptyline, the difference was not statistically significant (RR = 1.7, 95% CI 0.7-4.1).

CONCLUSION

This systematic review and meta-analysis shows that the use of nortriptyline for smoking cessation resulted in higher prolonged abstinence rates after at least 6 months compared to placebo treatment. Furthermore, the use of nortriptyline for smoking cessation is well tolerated and safe. As a result, we believe health care professionals should be recommended to prescribe nortriptyline as a first-line therapy for smoking cessation, also because of the much lower cost of nortriptyline compared to bupropion SR.

Clinical trials registries: a reform that is past due

Several high-profile episodes have recently thrust drug safety and the pharmaceutical industry's practices into the spotlight. Merck's recall of the drug Vioxx, for instance, was a major news event. GlaxoSmithKline's suppression of data linking suicidal behavior among children to Paxil also galvanized tremendous public attention. What differentiates these events from the usual evolving process of scientific knowledge, and marks them with an aura of “scandal,” are questions about the propriety of corporate behavior. Who knew what, and when did they know it? Concerns are growing about the potential for industry sponsors to suppress negative results from clinical trials research. Scientists, medical journal editors, legislators, and the public have called for greater transparency in the conduct of clinical trials and the drug approval process.

Publication of clinical trials: accountability and accessibility

Publication of findings from clinical trials is a necessary step in the research continuum, to provide a record of the work done, convey information to the community, and support translation of research into clinical practice. Systematic reviews of randomized controlled trials are now widely regarded as the highest level of evidence in determining the effect of an intervention on an outcome. They largely depend on internationally accessible, published reports of all trials undertaken. Investigators and their institutions or organizations have responsibility for reporting their clinical trials accurately and completely, including disclosure of potential conflicts of interest. To ensure evidence-based health care, issues relating to accessibility and accountability of clinical trial results require immediate action.

Tackling publication bias and selective reporting in health informatics research: register your eHealth trials in the International eHealth Studies Registry

Beginning in July 2005, several major medical journals, including the Journal of Medical Internet Research, will only consider trials for publication that have been registered in a trial registry before they started. This is to reduce publication bias and to prevent selective reporting of positive outcomes. As existing clinical trial registers seem to be unsuitable or suboptimal for eHealth studies, a free International eHealth Study Registry (IESR) has been set up, allowing registration of trials (including non-randomized studies) in the field of health informatics and assigning an International eHealth Study Number (IESN). The IESR should meet the requirements of journal editors for a-priori registration of a study. We hope IESR will become the preferred choice for registration of eHealth studies and, as an secondary benefit, will become an international repository of ongoing eHealth projects, thereby enhancing global collaboration and reducing duplication of effort.

The efficacy of smoking cessation strategies in people with chronic obstructive pulmonary disease: results from a systematic review

Smoking cessation is the most effective way to reduce the risk of developing chronic obstructive pulmonary disease (COPD). It prevents or delays the development of airflow limitation and also reduces its progression. The objective of this study was to systematically review the effects of interventions for smoking cessation in people with COPD. Comprehensive searches of electronic and internet databases were carried out from 1966 to March 2002, using the Cochrane Airways Group search strategy. The reference lists of all selected randomized trials and relevant reviews were inspected for additional published reports and citations of unpublished research. We evaluated the efficacy of behavioural interventions (e.g. counselling), pharmacotherapy (nicotine replacement therapy and non-nicotine therapy such as bupropion), and combinations of both. The main clinical outcome measure was prolonged abstinence after at least 6 months, confirmed by a biochemical test. Five trials comprising 6491 patients with COPD were included. Results of the Lung Health Study show that, by using an intensive behavioural (relapse prevention) programme combined with nicotine replacement therapy, prolonged abstinence rates are not only significantly higher compared with no intervention, but the difference in efficacy was sustained for over 5 years. A 12-week treatment course with bupropion sustained release combined with individual counselling, however, did not result in significantly higher prolonged abstinence rates after 12 months. Present evidence suggests that the most effective intervention for prolonged smoking cessation in patients with COPD is the combination of nicotine replacement therapy, coupled with an intensive, prolonged relapse prevention programme.

From phenotype to genotype: issues in navigating the available information resources

OBJECTIVES

As part of an investigation of connecting health professionals and the lay public to both disease and genomic information, we assessed the availability and nature of the data from the Human Genome Project relating to human genetic diseases.

METHODS

We focused on a set of single gene diseases selected from main topics in MEDLINEplus, the NLM's principal resource focused on consumers. We used publicly available websites to investigate specific questions about the genes and gene products associated with the diseases. We also investigated questions of knowledge and data representation for the information resources and navigational issues.

RESULTS

Many online resources are available but they are complex and technical. The major challenges encountered when navigating from phenotype to genotype were (1) complexity of the data, (2) dynamic nature of the data, (3) diversity of foci and number of information resources, and (4) lack of use of standard data and knowledge representation methods.

CONCLUSIONS

Three major informatics issues arise from the navigational challenges. First, the official gene names are insufficient for navigation of these web resources. Second, navigational inconsistencies arise from difficulties in determining the number and function of alternate forms of the gene or gene product and maintaining currency with this information. Third, synonymy and polysemy cause much confusion. These are severe obstacles to computational navigation from phenotype to genotype, especially for individuals who are novices in the underlying science. Tools and standards to facilitate this navigation are sorely needed.

Internet and information on breast cancer: an overview

In the past few years, many Internet breast cancer resources have appeared, including medical journals and clinical trial registries. Examples of online breast cancer journals are the The Breast, The Breast Journal, and the Breast Cancer Research and Treatment. These have replicated the experience of general medical and cancer journals such as the British Medical Journal and the Journal of Clinical Oncology. One of the most important cancer registries is the Physician Data Query, which provides information on the National Cancer Institute's clinical trials, most of which are related to breast cancer. Medical guideline databases, institutional websites, medical associations, and non-profit breast cancer organizations provide users with information including news, calendars of international breast cancer events, clinical guidelines and abstracts presented at cancer and breast cancer meetings. Finding high-quality breast cancer literature and websites is relatively easy using appropriate indexes such as Cancerlit, MedlinePlus, and Cancerlinks.

Benefits and risks of pharmacological smoking cessation therapies in chronic obstructive pulmonary disease

Smoking cessation is the most effective way to reduce the risk of developing chronic obstructive pulmonary disease (COPD) or to reduce its progression. However, little is known about the efficacy and safety of different pharmacological smoking cessation therapies used for the treatment of patients with COPD who smoke. The aim of this review was to evaluate the benefits and risks of pharmacological smoking cessation therapies in COPD. We conducted an extensive computer-aided literature search which resulted in the identification of four papers that met the inclusion criteria and contributed to this review. In two studies the efficacy of nicotine polacrilex (nicotine gum) was assessed. In one study, which did not have a control group, the efficacy of nicotine nasal spray was evaluated. The fourth study, a placebo-controlled trial, evaluated the efficacy of bupropion sustained release. The results of these studies indicated that nicotine gum, nicotine nasal spray and bupropion have a good safety profile and seem to increase abstinence rates in smokers with COPD. The incidence and nature of specific adverse effects occurring in patients with COPD seem to be comparable with the adverse effects reported by healthy smokers. However, the efficacy seems to depend on the follow-up period used to define success (i.e. abstinence rates decline with longer follow-up), as well as the intensity and duration of the concomitant psychosocial intervention. This review indicates that for a continuation of the effect of pharmacological smoking cessation therapies, the combination of pharmacotherapy (to reduce craving and withdrawal) and a relapse-prevention programme, in which attention is focused on the behavioural aspects of smoking and smoking cessation, seems to increase abstinence, especially when the psychosocial intervention is prolonged for a longer period. Also, the characteristics of the smokers who are motivated to quit must be taken into account in order to increase the number of successful attempts to quit smoking and prevent relapses. We therefore recommend using a holistic approach in which the possible coexistence of multiple problems (which are known to affect the success of smoking cessation strategies) is integrated.