Related Articles

The number of scientific publications on semiparametric methods per year has been steadily increasing since the early 1980s. This increased interest has happened in spite of the fact that the novelty of semiparametrics for its own sake has run its course, and semiparametric methods are by now considered classical. The underlying reasons for this continued interest include the genuine scientific utility of semiparametric models combined with the breadth and depth of the many theoretical questions that remain to be answered. Empirical process techniques are an essential research tool for many of these questions. Moreover, both semiparametric methods and empirical processes are playing an increasingly valuable role in high dimensional data analysis and in other emerging areas in statistics. The topics are very fruitful and intriguing for new researchers to engage in. Graduate programs in statistics, biostatistics and econometrics can and should include more empirical processes and semiparametrics in their teaching in order to ensure a sufficient supply of suitably qualified researchers.

Purpose

A sound, scientific base of high quality research is needed to inform service planning and decision making and enable improved policy and practice. However, some areas of health practice, particularly many of the allied health areas, are generally considered to have a low evidence base. In order to successfully build research capacity in allied health, a clearer understanding is required of what assists and encourages research as well as the barriers and challenges.

Participants and methods

This study used written surveys to collect data relating to motivators, enablers, and barriers to research capacity building. Respondents were asked to answer questions relating to them as individuals and other questions relating to their team. Allied health professionals were recruited from multidisciplinary primary health care teams in Queensland Health. Eighty-five participants from ten healthcare teams completed a written version of the research capacity and culture survey.

Results

The results of this study indicate that individual allied health professionals are more likely to report being motivated to do research by intrinsic factors such as a strong interest in research. Barriers they identified to research are more likely to be extrinsic factors such as workload and lack of time. Allied health professionals identified some additional factors that impact on their research capacity than those reported in the literature, such as a desire to keep at the “cutting edge” and a lack of exposure to research. Some of the factors influencing individuals to do research were different to those influencing teams. These results are discussed with reference to organizational behavior and theories of motivation.

Conclusion

Supporting already motivated allied health professional individuals and teams to conduct research by increased skills training, infrastructure, and quarantined time is likely to produce better outcomes for research capacity building investment.

Summary

Systems biology offers cutting-edge tools for the study of complementary and alternative medicine (CAM). The advent of ‘omics’ techniques and the resulting avalanche of scientific data have introduced an unprecedented level of complexity and heterogeneous data to biomedical research, leading to the development of novel research approaches. Statistical averaging has its limitations and is unsuitable for the analysis of heterogeneity, as it masks diversity by homogenizing otherwise heterogeneous populations. Unfortunately, most researchers are unaware of alternative methods of analysis capable of accounting for individual variability. This paper describes a systems biology solution to data complexity through the application of parsimony phylogenetic analysis. Maximum parsimony (MP) provides a data-based modeling paradigm that will permit a priori stratification of the study cohort(s), better assessment of early diagnosis, prognosis, and treatment efficacy within each stratum, and a method that could be used to explore, identify and describe complex human patterning.

Background

During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have appeared in the scientific literature. Most of these methods utilize molecular markers for the inferences, while some are also capable of handling DNA sequence data. In a number of earlier works, we have introduced an array of statistical methods for population genetic inference that are implemented in the software BAPS. However, the complexity of biological problems related to genetic structure analysis keeps increasing such that in many cases the current methods may provide either inappropriate or insufficient solutions.

Results

We discuss the necessity of enhancing the statistical approaches to face the challenges posed by the ever-increasing amounts of molecular data generated by scientists over a wide range of research areas and introduce an array of new statistical tools implemented in the most recent version of BAPS. With these methods it is possible, e.g., to fit genetic mixture models using user-specified numbers of clusters and to estimate levels of admixture under a genetic linkage model. Also, alleles representing a different ancestry compared to the average observed genomic positions can be tracked for the sampled individuals, and a priori specified hypotheses about genetic population structure can be directly compared using Bayes' theorem. In general, we have improved further the computational characteristics of the algorithms behind the methods implemented in BAPS facilitating the analyses of large and complex datasets. In particular, analysis of a single dataset can now be spread over multiple computers using a script interface to the software.

Conclusion

The Bayesian modelling methods introduced in this article represent an array of enhanced tools for learning the genetic structure of populations. Their implementations in the BAPS software are designed to meet the increasing need for analyzing large-scale population genetics data. The software is freely downloadable for Windows, Linux and Mac OS X systems at .

Max von Pettenkofer (1818–1901) belonged to the scientific elite of the 19th century. With his stringent search for the laws of nature and his fight for scientific truth, Pettenkofer was the prototype of a modern researcher. In the field of hygiene, he sought ways and means of preserving health and preventing sickness. With his consistent application of the experimental method to the field of public health, Pettenkofer helped the discipline of hygiene to provide precise and reliable answers to sanitary questions. In his experimental work on hygiene, Pettenkofer sought an answer to every imaginable question concerning the connection between the human organism and its environment.

To proceed in this direction, Pettenkofer combined medical expertise with physics, chemistry, technique and statistics. This even today modern “crossover-thinking” made hygiene to the first interdisciplinary medical field. With his Institute of Hygiene, Pettenkofer established 1879 the first centre of competence for hygiene and environment in the world, opening a new era of environmental observation.

In the framework of hygiene, Pettenkofer turned also to questions of nutrition and the quality of foodstuff. The science of hygiene owes to Max von Pettenkofer not only its development and cartography, but also its introduction as an academic discipline. Finally he regarded hygiene also as an economic and cultural feature. His idea about a clean soil in the cities and his promotion of adequate water supply and sufficient sewage networks are linked to his theory of the cholera. Pettenkofer believed that a battle against this epidemic could be won.

Randomized controlled trials and critical social theory are known not to be happy bedfellows. Such trials are embedded in a positivist view of the world, seeking definitive answers to testable questions; critical social theory questions the methods by which we deem the world knowable and may consider experiments in the biomedical sciences as social artifacts. Yet both of these epistemologically and methodologically divergent fields offer potentially important advances in HIV research. In this paper, we describe collaboration between social and biomedical researchers on a large, publicly funded programme to develop vaginal microbicides for HIV prevention. In terms of critical engagement, having integrated and qualitative social science components in the protocol meant potentially nesting alternative epistemologies at the heart of the randomized controlled trial. The social science research highlighted the fallibility and fragility of trial data by demonstrating inconsistencies in key behavioural measurements. It also foregrounded the disjuncture between biomedical conceptions of microbicides and the meanings and uses of the study gel in the context of users’ everyday lives. These findings were communicated to the clinical and epidemiological members of the team on an ongoing basis via a feedback loop, through which new issues of concern could also be debated and, in theory, data collection adjusted to the changing needs of the programme. Although critical findings were taken on board by the trialists, a hierarchy of evidence nonetheless remained that limited the utility of some social science findings. This was in spite of mutual respect between clinical epidemiologists and social scientists, equal representation in management and coordination bodies, and equity in funding for the different disciplines. We discuss the positive role that social science integrated into an HIV prevention trial can play, but nonetheless highlight tensions that remain where a hierarchy of epistemologies exists alongside competing paradigms and priorities.

In order to give the best care to patients and families, paediatricians need to integrate the highest quality scientific evidence with clinical expertise and the opinions of the family.1Archimedes seeks to assist practising clinicians by providing “evidence based” answers to common questions which are not at the forefront of research but are at the core of practice. In doing this, we are adapting a format which has been successfully developed by Kevin Macaway‐Jones and the group at the Emergency Medicine Journal—“BestBets”.

A word of warning. The topic summaries are not systematic reviews, through they are as exhaustive as a practising clinician can produce. They make no attempt to statistically aggregate the data, nor search the grey, unpublished literature. What Archimedes offers are practical, best evidence based answers to practical, clinical questions.

The format of Archimedes may be familiar. A description of the clinical setting is followed by a structured clinical question. (These aid in focusing the mind, assisting searching,2 and gaining answers.3) A brief report of the search used follows—this has been performed in a hierarchical way, to search for the best quality evidence to answer the question.4 A table provides a summary of the evidence and key points of the critical appraisal. For further information on critical appraisal, and the measures of effect (such as number needed to treat, NNT) books by Sackett5 and Moyer6 may help. To pull the information together, a commentary is provided. But to make it all much more accessible, a box provides the clinical bottom lines.

Readers wishing to submit their own questions—with best evidence answers—are encouraged to review those already proposed at www.bestbets.org. If your question still hasn't been answered, feel free to submit your summary according to the Instructions for Authors at www.archdischild.com. Three topics are covered in this issue of the journal:

Does neonatal BCG vaccination protect against tuberculous meningitis?

Does dexamethasone reduce the risk of extubation failure in ventilated children?

Should metformin be prescribed to overweight adolescents in whom dietary/behavioural modifications have not helped?

REFERENCES

1. Moyer VA, Ellior EJ. Preface. In: Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health, Issue 1. London: BMJ Books, 2000.

2. Richardson WS, Wilson MC, Nishikawa J, et al. The well‐built clinical question: a key to evidence‐based decisions. ACP J Club 1995;123:A12–13.

3. Bergus GR, Randall CS, Sinift SD, et al. Does the structure of clinical questions affect the outcome of curbside consultations with specialty colleagues? Arch Fam Med 2000;9:541–7.

4. http://cebm.jr2.ox.ac.uk/docs/levels.htm (accessed July 2002).

5. Sackett DL, Starus S, Richardson WS, et al. Evidence‐based medicine. How to practice and teach EBM. San Diego: Harcourt‐Brace, 2000.

6. Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health, Issue 1. London: BMJ Books, 2000.

How to read your journals

Most people have their journals land, monthly, weekly, or quarterly, on their desk, courtesy of their professional associations. Then they sit, gathering dust and guilt, for a period of time. When the layer of either is too great for comfort (or the desk space is needed for some proper work), the wrapper is removed and the journal scanned. But does how people read reflect their information needs or their entertainment requirements?

It is not uncommon to find people straying from the editorial introduction to the value added sections (like obituaries, Lucina‐like summary pages, and end‐of‐article fillers) rather than face the impenetrable science that sits between them. I think that this is probably unhelpful, and would urge readers to do one more thing before placing the journal in the recycling. Scan the table of contents; if it mentions a systematic review or a randomised trial, then read at least the title and the abstract's conclusions. If you agree, pat yourself warmly on the back for being evidence based and up‐to‐date. If you disagree, ask if it will make any impact on your clinical (or personal) life. If it might, run through the methods and quickly appraise them. Does it supply higher quality evidence than that you already possess? If it does, it's worth reading. If it doesn't, don't bother too much.

There are new innovations which might aid the tedious task of consuming research effort. The on‐line Précis section of the Archives provides a highly readable version of the contents page to whet one's appetite. Finally, it's worth mentioning that evidence based summary materials (like Archimedes, or Journal Watch) are always worth reading—and if you didn't think that you wouldn't be here, would you?

To give the best care to patients and families, paediatricians need to integrate the highest‐quality scientific evidence with clinical expertise and the opinions of the family.1Archimedes seeks to assist practising clinicians by providing “evidence‐based” answers to common questions which are not at the forefront of research but are at the core of practice. In doing this, we are adapting a format that has been successfully developed by Kevin Macaway‐Jones and the group at the Emergency Medicine Journal—“BestBets”.

A word of warning. The topic summaries are not systematic reviews, although they are as exhaustive as a practising clinician can produce. They make no attempt to statistically aggregate the data, nor search the grey, unpublished literature. What Archimedes offers are practical, best evidence‐based answers to practical, clinical questions.

The format of Archimedes may be familiar. A description of the clinical setting is followed by a structured clinical question. (These aid in focusing the mind, assisting searching2 and gaining answers.3) A brief report of the search used follows—this has been carried out in a hierarchical way, to search for the best‐quality evidence to answer the question (http://www.cebm.net/levels_of_evidence.asp). A table provides a summary of the evidence and key points of the critical appraisal. For further information on critical appraisal and the measures of effect (such as number needed to treat), books by Sackett et al4 and Moyer et al5 may help. To pull the information together, a commentary is provided. But to make it all much more accessible, a box provides the clinical bottom lines.

Electronic‐only topics that have been published on the BestBets site (www.bestbets.org) and may be of interest to paediatricians include:

Are meningeal irritation signs reliable in diagnosing meningitis in children?

Is immobilisation effective in Osgood‐Schlatter's disease?

Do all children presenting to the emergency department with a needlestick injury require PEP for HIV to reduce HIV transmission?

Readers wishing to submit their own questions—with best evidence answers—are encouraged to review those already proposed at www.bestbets.org. If your question still has not been answered, feel free to submit your summary according to the Instructions for Authors at www.archdischild.com. Three topics are covered in this issue of the journal.

Is lumbar puncture necessary for evaluation of early neonatal sepsis?

Does the use of calamine or antihistamine provide symptomatic relief from pruritus in children with varicella zoster infection?

Is supplementary iron useful when preterm infants are treated with erythropoietin?

Is more research needed?

“More research is needed” is a phrase you might have read before. But is more research really needed? Two situations are offered to us in Archimedes this month where clinical questions are, as yet, unanswered. Is iron supplementation really necessary for premature infants treated with erythropoietin, and do antihistamines and calamine lotion help in children with chicken pox? How can we decide if these questions really do “need” research? It may be worth thinking of how likely benefits and harms may be, what the importance of these outcomes are and finally, how much would you consider reasonable to pay for the answer? For example, what chance is there that antihistamines work in chickenpox? What is the chance that side effects will occur? What is the relative severity of side effects versus the delight of being itch free? If we pay for research and spend hours and hours of time pressing through the increasing regulatory frameworks for clinical trials to define the answer to this question, what will be the opportunity cost? What would we fail to do by looking at this? The same questions can be asked of iron supplementation in premature infants, the salvage treatment of relapsing systemic histocytosis or the promotion of car‐seat use in low‐income families. Such value judgements are important; they will have different answers from different perspectives; they will be subject to political influences from pressure groups; being aware of them might stop us from frequently expounding “more research is needed”.

References

1Moyer VA, Ellior EJ. Preface. In: Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health, Issue 1. London: BMJ Books, 2000.

2Richardson WS, Wilson MC, Nishikawa J, et al. The well‐built clinical question: a key to evidence‐based decisions. ACP J Club 1995;123:A12–13.

3Bergus GR, Randall CS, Sinift SD, et al. Does the structure of clinical questions affect the outcome of curbside consultations with specialty colleagues? Arch Fam Med 2000;9:541–7.

4Sackett DL, Starus S, Richardson WS, et al. Evidence‐based medicine. How to practice and teach EBM. San Diego: Harcourt‐Brace, 2000.

5Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health, Issue 1. London: BMJ Books, 2000.

To give the best care to patients and families, paediatricians need to integrate the highest quality scientific evidence with clinical expertise and the opinions of the family.1Archimedes seeks to assist practising clinicians by providing “evidence‐based” answers to common questions that are not at the forefront of research but are at the core of practice. In doing this, we are adapting a format that has been successfully developed by Kevin Mackway‐Jones and the group at the Emergency Medicine Journal—“BestBets”.

A word of warning. The topic summaries are not systematic reviews, although they are as exhaustive as a practising clinician can produce. They make no attempt to statistically aggregate the data, nor to search the grey, unpublished literature. What Archimedes offers is practical, best evidence‐based answers to practical, clinical questions.

The format of Archimedes may be familiar. A description of the clinical setting is followed by a structured clinical question. (These aid in focusing the mind, assisting searching2 and obtaining answers.3) A brief report of the search used follows—this has been performed in a hierarchical way, to search for the best quality evidence to answer the question (http://www.cebm.net). A table provides a summary of the evidence and key points of the critical appraisal. For further information on critical appraisal, and the measures of effect (such as the number needed to treat), books by Sackett4 and Moyer5 may help. To pull the information together, a commentary is provided, but to make it all much more accessible, a box provides the clinical bottom lines.

Electronics‐only topics that have been published on the BestBets site (www.bestbets.org) and may be of interest to paediatricians include the following.

Can steroids be used to reduce post tonsillectomy pain?

Readers wishing to submit their own questions—with best evidence answers—are encouraged to review those already proposed at www.bestbets.org. If your question still hasn't been answered, feel free to submit your summary according to the instructions for authors at www.archdischild.com. Three topics are covered in this issue of the journal:

Is teething the cause of minor ailments?

Should steroid creams be used in cases of labial fusion?

Does erythromycin cause pyloric stenosis?

References

1 Moyer VA, Ellior EJ. Preface. In: Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health. Issue 1. London: BMJ Books, 2000.

2 Richardson WS, Wilson MC, Nishikawa J, et al. The well‐built clinical question: a key to evidence‐based decisions. ACP J Club 1995;123:A12–13.

3 Bergus GR, Randall CS, Sinift SD, et al. Does the structure of clinical questions affect the outcome of curbside consultations with specialty colleagues? Arch Fam Med 2000;9:541–7.

4 Sackett DL, Starus S, Richardson WS, et al. Evidence‐based medicine. How to practice and teach EBM. San Diego: Harcourt‐Brace, 2000.

5 Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health. Issue 1. London: BMJ Books, 2000.

Can: doing, using and replicating evidence‐based child health

The practice of evidence‐based child health is said to be the five‐step way of asking questions, acquiring information, appraising the evidence, applying the results and assessing our performance.

If the truth be known, for the vast majority of the time, most of us perform our clinical practice replicating what we have done previously. Most of the time this is based on the combination of excellent education, skilled interpretation of clinical findings, and good discussions with children and families. We hope that the education we rely on was (and remains) based on the best available scientific evidence. If it is, we are practising a form of “micro‐evidence‐based healthcare (EBHC)” (doing just step 4).

Sometimes, we question our knowledge (or more uncomfortably, someone does this for us), and will head off to top up our understanding of an area. This “using” mode, if we use well‐appraised resources to supply our thirst for information, will also promote the practice of evidence‐based care. This midi‐EBHC asks us to go through steps 1, 2 and 4.

Occasionally, we also actually need to go through the entire process of getting “down and dirty” with the primary research and appraising it to influence our practice. Maxi‐EBHC is considerably more demanding in time, but largely more satisfying intellectually.

If we reframe the practice of EBHC as using the family and child values, the best evidence, and our clinical expertise, then we can do it by micro‐methods, midi‐methods or maxi‐methods, and choose the most appropriate approach for the situation we confront.

Acknowledgement

I thank Dr Sharon Straus, Director of the Center for Evidence‐based Medicine, University of Toronto, Toronto, Ontario, Canada.

In order to give the best care to patients and families, paediatricians need to integrate the highest quality scientific evidence with clinical expertise and the opinions of the family.1Archimedes seeks to assist practising clinicians by providing “evidence‐based” answers to common questions which are not at the forefront of research but are at the core of practice. In doing this, we are adapting a format which has been successfully developed by Kevin Macaway‐Jones and the group at the Emergency Medicine Journal—“BestBets”.

A word of warning. The topic summaries are not systematic reviews, though they are as exhaustive as a practising clinician can produce. They make no attempt to statistically aggregate the data, nor search the grey, unpublished literature. What Archimedes offers are practical, best evidence‐based answers to practical, clinical questions.

The format of Archimedes may be familiar. A description of the clinical setting is followed by a structured clinical question. (These aid in focusing the mind, assisting searching2 and gaining answers.3) A brief report of the search used follows—this has been performed in a hierarchical way, to search for the best‐quality evidence to answer the question. (http://www.cebm.net). A table provides a summary of the evidence and key points of the critical appraisal. For further information on critical appraisal, and the measures of effect (such as number needed to treat), books by Sackett et al4 and Moyer et al5 may help. To pull the information together, a commentary is provided. But to make it all much more accessible, a box provides the clinical bottom lines.

Electronic‐only topics that have been published on the BestBets site (www.bestbets.org) and may be of interest to paediatricians include:

When is a second course of indomethacin effective for PDA in neonates?

Does delayed cord clamping prevent sepsis?

Readers wishing to submit their own questions—with best evidence answers—are encouraged to review those already proposed at www.bestbets.org. If your question still hasn't been answered, feel free to submit your summary according to the Instructions for Authors at www.archdischild.com. Three topics are covered in this issue of the journal:

In children aged <3 years does procalcitonin help exclude serious bacterial infection in fever without focus?

Does avoidance of breast feeding reduce mother‐to‐infant transmission of hepatitis C virus infection?

Should children under treatment for juvenile idiopathic arthritis receive flu vaccination?

CAN gambling with other people's children

When we use tests to “rule out” a condition, we generally accept that we are left with a small risk of being wrong. (I think we have all discharged a child with an “upper respiratory tract infection” on a Friday to be greeted with them on antibiotics for pneumonia the following Monday.) How much faith we place in a test result is a product of two things: our initial assumption about the likelihood of the diagnosis (pretest probability) and our opinion as to how effective the test is (accuracy), but our actions do not just reflect these factors.

For instance, a well, afebrile child with a scattering of petechiae over its wrist 8 hours before, is unlikely to have meningococcal disease. If you perform a couple of tests, you can find that it has a low C‐reactive protein and a normal full blood count. What we do with this varies widely; some people would treat this with 48 h of antibiotics, others would discharge the patient home.

It is interesting to reflect on two things: first, what chance of meningococcal disease would you put on this clinical picture (before the test), and what about with the test results? What about your colleagues? You may be surprised by how widely this varies. Second, even those who have the same estimates of risk of disease may have different preferred actions (depending on their attitude to risk).

In looking at the diagnostic test for the ruling out of a disease, we can make our arguments more useful by having some data on the assumptions we make, and then transparently discussing our attitudes to risk. It is only after doing this that we can really decide if a test is good enough for us, regardless of how accurate it might be.

References

1Moyer VA, Ellior EJ. Preface. In: Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health, Issue 1. London: BMJ Books, 2000.

2Richardson WS, Wilson MC, Nishikawa J, et al. The well‐built clinical question: a key to evidence‐based decisions. ACP J Club 1995;123:A12–13.

3Bergus GR, Randall CS, Sinift SD, et al. Does the structure of clinical questions affect the outcome of curbside consultations with specialty colleagues? Arch Fam Med 2000;9:541–7.

4Sackett DL, Starus S, Richardson WS, et al. Evidence‐based medicine. How to practice and teach EBM. San Diego: Harcourt‐Brace, 2000.

5Moyer VA, Elliott EJ, Davis RL, et al, eds. Evidence based pediatrics and child health. Issue 1. London: BMJ Books, 2000.

Background

The number of subjects that can be recruited in immunological studies and the number of immunological parameters that can be measured has increased rapidly over the past decade and is likely to continue to expand. Large and complex immunological datasets can now be used to investigate complex scientific questions, but to make the most of the potential in such data and to get the right answers sophisticated statistical approaches are necessary. Such approaches are used in many other scientific disciplines, but immunological studies on the whole still use simple statistical techniques for data analysis.

Results

The paper provides an overview of the range of statistical methods that can be used to answer different immunological study questions. We discuss specific aspects of immunological studies and give examples of typical scientific questions related to immunological data. We review classical bivariate and multivariate statistical techniques (factor analysis, cluster analysis, discriminant analysis) and more advanced methods aimed to explore causal relationships (path analysis/structural equation modelling) and illustrate their application to immunological data. We show the main features of each method, the type of study question they can answer, the type of data they can be applied to, the assumptions required for each method and the software that can be used.

Conclusion

This paper will help the immunologist to choose the correct statistical approach for a particular research question.

Context:

Scientific research output measured by the number and quality of publications reflects the research productivity of a certain community.

Aims:

To examine the quantity and quality of research produced by Syrian institutions with particular emphasis on the clinical and biomedical research.

Settings and Design:

Retrospective observational analysis of research originating from Syrian institutions indexed by Medline and Science Citation Index (SciVerse) Scopus bibliographic databases.

Materials and Methods:

Comprehensive review of the literature indexed by Medline and SciVerse was conducted including data from Jan 01, 1980 till February 2011 searching for authors affiliated with Syrian institutions. Clinical and biomedical research data were further analyzed quantitatively and qualitatively.

Results:

The total of manuscripts indexed by SciVerse originating from Syrian institutions during the last 3 decades is 3540. A total of 458 publications cover clinical and biomedical subject areas. The quality of these 458 publications was evaluated by the citation frequency and impact factor of publishing journals with h-index of 24.

Conclusions:

Although the spectrum of research originating from Syrian institutions is broad, the overall number of publications particularly in clinical and biomedical subjects is minuscule and of limited quality. The presented data indicate the need to promote research capabilities and to bridge the gap in research productivity by Syrian institutions.

Motivation: Animal models play a pivotal role in translation biomedical research. The scientific value of an animal model depends on how accurately it mimics the human disease. In principle, microarrays collect the necessary data to evaluate the transcriptomic fidelity of an animal model in terms of the similarity of expression with the human disease. However, statistical methods for this purpose are lacking.

Results: We develop the agreement of differential expression (AGDEX) procedure to measure and determine the statistical significance of the similarity of the results of two experiments that measure differential expression across two groups. AGDEX defines a metric of agreement and determines statistical significance by permutation of each experiment's group labels. Additionally, AGDEX performs a comprehensive permutation-based analysis of differential expression for each experiment, including gene-set analyses and meta-analytic integration of results across studies. As an example, we show how AGDEX was recently used to evaluate the similarity of the transcriptome of a novel model of the brain tumor ependymoma in mice to that of a subtype of the human disease. This result, combined with other observations, helped us to infer the cell of origin of this devastating human cancer.

Availability: An R package is currently available from www.stjuderesearch.org/site/depts/biostats/agdex and will shortly be available from www.bioconductor.org.

Contact: stanley.pounds@stjude.org

Supplementary information: Supplementary data are available at Bioinformatics online.

The ultimate goal of research is to produce dependable knowledge or to provide the evidence that may guide practical decisions. Statistical conclusion validity (SCV) holds when the conclusions of a research study are founded on an adequate analysis of the data, generally meaning that adequate statistical methods are used whose small-sample behavior is accurate, besides being logically capable of providing an answer to the research question. Compared to the three other traditional aspects of research validity (external validity, internal validity, and construct validity), interest in SCV has recently grown on evidence that inadequate data analyses are sometimes carried out which yield conclusions that a proper analysis of the data would not have supported. This paper discusses evidence of three common threats to SCV that arise from widespread recommendations or practices in data analysis, namely, the use of repeated testing and optional stopping without control of Type-I error rates, the recommendation to check the assumptions of statistical tests, and the use of regression whenever a bivariate relation or the equivalence between two variables is studied. For each of these threats, examples are presented and alternative practices that safeguard SCV are discussed. Educational and editorial changes that may improve the SCV of published research are also discussed.

Background

Due to differences in current socio-economical situation and historically shaped values, different societies have their own concepts of high-quality life. This diversity of concepts interferes with quality of life (Qol) research in health sciences. Before deciding to apply a Qol assessment tool designed in and for another society, a researcher should answer the question: how will this instrument work under the specific circumstances of my research. Our study represents an example of the utilization of qualitative research methods to investigate the appropriateness of the Rheumatoid Arthritis Quality of Life Scale (RAQol) for the assessment of Qol in Estonian patients.

Methods

Semi-structured interviews were conducted with the rheumatoid arthritis (RA) patients of Tartu University Hospital and these were analyzed using the principles of the grounded theory.

Results

We described the significance of the questionnaire's items for our patients and also identified topics that were important for the Qol of Estonian RA patients, but that were not assessed by the RAQol. We concluded that the RAQol can be successfully adapted for Estonia; the aspects of Qol not captured by the questionnaire but revealed during our study should be taken into account in future research.

Conclusions

Our results show that qualitative research can successfully be used for pre-adaptation assessment of a Qol instrument's appropriateness.

Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.

In industry, hospital, clinic, laboratory or office, professionals are continually faced with “all size” of problems which can be successfully answered by using investigative scientific methods.

The recognition and formulation of an existing problem followed by the desire to seek an answer are the first major steps. Collecting and analyzing data, followed by valid scientific conclusion completes the picture.

Professional success means knowing most about something, not something about most. Investigation-research is a particular pattern in weaving, made of organized curiosity, skillful analysis, inventive thinking and professional objectivity.

The purpose of the article remains to identify fundamental questions which emerge from clinical observations and practice, to identify and project needed research and to guide the finding of scientific answers.

The distinction between clinical practice and surgical research may seem trivial, but this distinction can become a complex issue when innovative surgeries are substituted for standard care without patient knowledge. Neither the novelty nor the risk of a new surgical procedure adequately defines surgical research. Some institutions tacitly allow the use of new surgical procedures in series of patients without informing individuals that they are participating in a scientific study, as long as no written protocol or hypothesis exists. Institutions can justify this practice by viewing human research in narrow terms as an activity outlined in a formal protocol. Application of limited definitions, however, erodes patients' rights and risks losing public confidence in how biomedical research is conducted. I propose an operational definition of human research also be recognised. Enforcing more rigid and less ambiguous guidelines of human research may curtail enrolment into some studies, but it will also protect patients from being used as subjects without their knowledge.

Key Words: Experimental surgery • innovative surgery • medical ethics • surgical research

Background

Providers of health care usually have much better information about health and health care interventions than do consumers. The internet is an important and rapidly evolving source of global health-related information and could provide a means of correcting for asymmetric information. However, little is known about who accesses this information and how it is used in New Zealand.

The aims of this research were to: determine the nature of the health information sought, how respondents use the information, how helpful they perceive the information to be, and the self-assessed value of such information.

Methods

The researchers conducted an anonymous five minute telephone and mall intercept survey of randomly selected Wellington residents who had searched for health-related information on the internet. Investigators entered the data into an Excel spreadsheet and transferred it to SPSS for data cleaning, data exploration and statistical analysis. Search time costs were based on the opportunity cost of income foregone and respondents were asked to provide a money value for the information found.

Results

Eighty-three percent of respondents accessed the internet from home, and 87% conducted the search for themselves. Forty-five percent of people were looking for general health and nutrition information, 42% for data about a specific illness and 40% for a medicine.

After finding the information, 58% discussed it with a family member/ friend/ workmate, 36% consulted a general practitioner, 33% changed their eating or drinking habits, and 13% did nothing. Respondents found the information very quick to find and useful. It took them on average 0.47 hours and cost $12 (opportunity cost of time) to find the information. The average value of the data found was $60 and the net benefit to the consumer was $48 ($60 – $12).

Conclusion

The results of this research could assist providers of health information via the internet to tailor their websites to better suit users' needs. Given the high perceived value of internet health information (greater than the average general practitioner fee) and the fact that some of the information found may be unreliable or even unsafe a valuable public health policy initiative would be to provide an improved New Zealand health information website containing information on how to evaluate data sourced from the world-wide-web and links to a range of useful and trustworthy health information sites.

Objective

Biomedical literature is increasingly enriched with literature reviews and meta-analyses. We sought to assess the understanding of statistical terms routinely used in such studies, among researchers.

Methods

An online survey posing 4 clinically-oriented multiple-choice questions was conducted in an international sample of randomly selected corresponding authors of articles indexed by PubMed.

Results

A total of 315 unique complete forms were analyzed (participation rate 39.4%), mostly from Europe (48%), North America (31%), and Asia/Pacific (17%). Only 10.5% of the participants answered correctly all 4 “interpretation” questions while 9.2% answered all questions incorrectly. Regarding each question, 51.1%, 71.4%, and 40.6% of the participants correctly interpreted statistical significance of a given odds ratio, risk ratio, and weighted mean difference with 95% confidence intervals respectively, while 43.5% correctly replied that no statistical model can adjust for clinical heterogeneity. Clinicians had more correct answers than non-clinicians (mean score ± standard deviation: 2.27±1.06 versus 1.83±1.14, p<0.001); among clinicians, there was a trend towards a higher score in medical specialists (2.37±1.07 versus 2.04±1.04, p = 0.06) and a lower score in clinical laboratory specialists (1.7±0.95 versus 2.3±1.06, p = 0.08). No association was observed between the respondents' region or questionnaire completion time and participants' score.

Conclusion

A considerable proportion of researchers, randomly selected from a diverse international sample of biomedical scientists, misinterpreted statistical terms commonly reported in meta-analyses. Authors could be prompted to explicitly interpret their findings to prevent misunderstandings and readers are encouraged to keep up with basic biostatistics.

An analysis of the articles published in 1992 in the Journal of the National Medical Association (JNMA) was performed to assess the content, statistical analysis, and the profile of its contributors. Seventy-six articles were reviewed. The majority of the articles focused on biomedical aspects of health; however, a significant proportion of the remaining articles contained information on the psychosocial aspects of health as it relates to people of African descent in the United States, Africa, and the Caribbean. Most of the literature was derived from physicians in university settings, with the contributions from traditionally black medical schools constituting nearly 30% of the articles. Analysis of data from contingency tables was the most common research method used. This study suggests that the JNMA is contributing to the mission of the National Medical Association. Reasons why authors who perform research with more rigorous scientific method do not publish in JNMA should be explored.

Deciding which piece of information to acquire or attend to is fundamental to perception, categorization, medical diagnosis, and scientific inference. Four statistical theories of the value of information—information gain, Kullback-Liebler distance, probability gain (error minimization), and impact—are equally consistent with extant data on human information acquisition. Three experiments, designed via computer optimization to be maximally informative, tested which of these theories best describes human information search. Experiment 1, which used natural sampling and experience-based learning to convey environmental probabilities, found that probability gain explained subjects’ information search better than the other statistical theories or the probability-of-certainty heuristic. Experiments 1 and 2 found that subjects behaved differently when the standard method of verbally presented summary statistics (rather than experience-based learning) was used to convey environmental probabilities. Experiment 3 found that subjects’ preference for probability gain is robust, suggesting that the other models contribute little to subjects’ search behavior.

In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular due to its flexibility and efficiency. Based on adaptations applied, adaptive designs can be classified into three categories: prospective, concurrent (ad hoc), and retrospective adaptive designs. An adaptive design allows modifications made to trial and/or statistical procedures of ongoing clinical trials. However, it is a concern that the actual patient population after the adaptations could deviate from the originally target patient population and consequently the overall type I error (to erroneously claim efficacy for an infective drug) rate may not be controlled. In addition, major adaptations of trial and/or statistical procedures of on-going trials may result in a totally different trial that is unable to address the scientific/medical questions the trial intends to answer. In this article, several commonly considered adaptive designs in clinical trials are reviewed. Impacts of ad hoc adaptations (protocol amendments), challenges in by design (prospective) adaptations, and obstacles of retrospective adaptations are described. Strategies for the use of adaptive design in clinical development of rare diseases are discussed. Some examples concerning the development of Velcade intended for multiple myeloma and non-Hodgkin's lymphoma are given. Practical issues that are commonly encountered when implementing adaptive design methods in clinical trials are also discussed.

Objective: The research sought to determine if primary care physicians' attitudes toward risk taking or uncertainty affected how they sought information and used electronic information resources when answering simulated clinical questions.

Methods: Using physician-supplied data collected from existing risk and uncertainty scales, twenty-five physicians were classified as risk seekers (e.g., enjoying adventure), risk neutral, or risk avoiders (e.g., cautious) and stressed or unstressed by uncertainty. The physicians then answered twenty-three multiple-choice, clinically focused questions and selected two to pursue further using their own information resources. Think-aloud protocols were used to collect searching process and outcome data (e.g., searching time, correctness of answers, searching techniques).

Results: No differences in searching outcomes were observed between the groups. Physicians who were risk avoiding and those who reported stress when faced with uncertainty each showed differences in searching processes (e.g., actively analyzing retrieval, using searching heuristics or rules). Physicians who were risk avoiding tended to use resources that provided answers and summaries, such as Cochrane or UpToDate, less than risk-seekers did. Physicians who reported stress when faced with uncertainty showed a trend toward less frequent use of MEDLINE, when compared with physicians who were not stressed by uncertainty.

Conclusions: Physicians' attitudes towards risk taking and uncertainty were associated with different searching processes but not outcomes. Awareness of differences in physician attitudes may be key in successful design and implementation of clinical information resources.

To date, we are unaware of a review that has investigated common cosmeceutical ingredients in order to answer the three specific questions proposed by the father of cosmeceuticals, Dr. Albert Kligman. It is the goal of this review to gather all the published scientific data on five common cosmeceutical ingredients, answer the three major questions about the scientific rationale for their use, and ascertain how much we really know about consumers' favorite cosmeceutical ingredients.

Most of the research concerning cosmeceutical retinoid ingredients is based upon the effects of retinoic acid on the skin. Clinical trials concerning retinol and retinaldehyde are scant and lacking in statistical evaluation for significance. There is research substantiating the effects of kinetin in plants and also in-vitro antioxidant effects. However, proof of anti-aging activity remains elusive, and the clinical efficacy of kinetin is based on limited data. Niacinamide is the ingredient investigated that most closely upholds the “Kligman standards” of cosmeceutical-ingredient analysis. With the available scientific evidence on topical niacinamide, clinicians are able to adequately answer questions about permeability, mechanism, and clinical effect. Both green tea and soy have been popularized commercially based on their antioxidant effects, yet there is a paucity of clinical studies concerning their efficacy as topical anti-aging agents. It may be that soy and green tea are better at preventing the signs and symptoms of skin aging than actually reversing them. Since cosmeceutical products are claiming to therapeutically affect the structure and function of the skin, it is rational and necessary to hold them to specified scientific standards that substantiate efficacy claims.