Author: Amy Ross

Maximizing the Impact of Research: New Reporting Guidelines Collection from PLOS

Image credit: CCAC North Library, Flickr.com

Image credit: CCAC North Library, Flickr.com

As experts in their field, many authors assume they already know the best way to report their research findings, but this is not always true. Reporting guidelines are designed help make sure that you don’t forget to include crucial bits of information that might be obvious to you as the author, but not necessarily obvious to your audience. Reporting checklists are not just exercises in ticking boxes – they are about helping you to effectively communicate what you have done so that it can be widely read, used, and influence future work in the field. It is not only frustrating to read a research paper where key pieces of information about the methods or results are missing, but more importantly, inadequate research reporting and can lead to biases in interpretation of research and wasted resources in attempts to replicate the methods.

Many researchers are unaware of the growing number of resources that can be used to guide preparation of research manuscripts and improve the quality of reporting. A new PLOS Reporting Guidelines Collection, including papers from PLOS Medicine, PLOS ONE, PLOS Biology, PLOS Computational Biology, and PLOS NTDs, aims to highlight some of these resources and has been launched to coincide with the Seventh International Congress on Peer Review and Biomedical Publication, held in Chicago from September 8 to 10, 2013.  The collection is consistent with the goals of the Peer Review Congress: “to improve the quality and credibility of scientific peer review and publication and to help advance the efficiency, effectiveness, and equitability of the dissemination of biomedical information throughout the world”.
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Spotlight from the CUGH Conference 2013: Innovative Technologies

I recently attended the Consortium of Universities for Global Health (CUGH) conference in Washington DC from March 13-16, 2013. I found the talks on Innovative Technologies most interesting, in part because technologies have a large impact on the everyday lives of people in developing countries. One technology that Dr. Sasha Kramer, an ecologist from Stanford University, presented was the design and implementation of a new type of compost toilet for use in Haiti, funded by grants and donations. Her idea aims to improve basic sanitation, reduce the risk of diseases like cholera, and create jobs for unemployed Haitians.

Kramer is the executive director and co-founder of the not-for-profit organization Sustainable Organic Integrated Livelihoods (SOIL), which has built more than 50 public composting toilet facilities in Haiti since 2006.  Eighty percent of the population in Haiti does not have access to basic sanitation and existing toilets are not well designed, with human waste flushing straight into rivers or groundwater. In this way the water supply is easily contaminated, and waterborne diseases like cholera are at epidemic levels in Haiti. From the SOIL website: “As of March 4, 2013, cholera has killed 8,057 Haitians and infected nearly 650,000 more. Despite some claims of progress, the epidemic, which was introduced by United Nations troops, has been significantly worse in 2013 than during the same period the year before.”
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Making PROGRESS in Prognostic Research

For anyone that’s sick, understanding what the likely outcome is one of the first questions they want the answer to. Yet despite the millions of dollars poured into health research every year actually predicting outcomes is a surprisingly inexact science.

This week the PROGnosis RESearch Strategy (PROGRESS) Group, comprised of investigators from multiple countries who participated in three workshops (which also included  one editor each from the BMJ and PLOS Medicine) and discussions, publish four papers in PLOS Medicine and the BMJ, (itself an unusual collaboration between journals ) that aim to better define the field of prognosis research.

Prognosis research is defined in the series as the investigation of the “relations between future outcomes (endpoints) among people with a given baseline health state (startpoints) in order to improve health”.

Prognosis research has yet to be identified as a distinct field of research and a major issue in this area is the lack of cohesion for methodology, analysis, and data reporting. Currently, there are a multitude of disparate studies claiming to have identified factors or models that predict future clinical outcomes in relation to current diagnostic and treatment practice. In a single clinical field there may be several studies that identify different factors or models for the same outcomes, but do not attempt to build on or even compare previously identified factors and models. In addition, individual studies are often underpowered or not replicated or validated in other populations.  A good example of this can be found in a study by Malats and colleagues that analyzed 168 reports and concluded that “after 10 years of research [including over 10 000 patients], evidence is not sufficient to conclude whether changes in P53 act as markers of outcome in patients with bladder cancer.” In reality, there are very few prognostic studies with sufficiently robust methods to be clinically informative; common methodological problems include the use of retrospective study designs, study biases, and selective reporting of significant findings.

In the papers published this week the researchers provide a four point framework for prognostic research to take the field further:

(1) The course of health related conditions in the context of the nature and quality of current care (fundamental prognosis research)

(2) Specific factors (such as biomarkers) that are associated with prognosis (prognostic factor research)

(3) The development, validation, and impact of statistical models that predict individual risk of a future outcome

(prognostic model research)

(4) The use of prognostic information to help tailor treatment decisions to an individual or group of individuals with similar characteristics (stratified medicine research).

 

There are  many reporting guidelines designed to help researchers improve study design and reporting of clinical research outcomes (e.g. STROBE, CONSORT, PRISMA, STARD). These four PROGRESS papers extend earlier work outlining prognosis models in clinical practice published in the BMJ in 2009Ten steps towards improving prognosis research published in the BMJ in 2010, and a related set of recommendations that were developed specifically for prognosis research related to tumor markers (REporting recommendations for tumour MARKer prognostic studies, REMARK). The PROGRESS group’s recommendations highlight the importance of  study registration, a published protocol, ideally a prospective approach, and an appropriate statistical analysis plan.  In addition, the PROGRESS papers provide a broader overview of examples of prognosis research from cancer, cardiovascular disease, musculoskeletal disorders, trauma, and beyond to provide a more cohesive approach to research practices in the field of prognosis research and will help prognosis researchers to enforcing the high standards required in other fields.

 

The PROGRESS series has been published as a collaborative effort between the PROGRESS Group, PLOS Medicine and BMJ. The first and fourth papers are published in BMJ and second and third papers are published in PLOS Medicine and can be accessed in the links below:

Prognosis research strategy (PROGRESS) 1: A framework for researching clinical outcomes

Prognosis research strategy (PROGRESS) 2: Prognostic factor research

Prognosis research strategy (PROGRESS) 3: Prognostic model impact research

Prognosis research strategy (PROGRESS) 4: Stratified medicine research

 

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