Good study design and forward planning

在本帖中，理文编辑 学术总监Dr. Daniel McGowan将向大家展示“如何做好研究设计和预先规划工作”。

Rejection following peer review can mean a considerable amount of additional work for many authors to get their studies published. In the worst cases, their studies may be simply un-publishable. Much heartbreak and hard work can be avoided by simply planning and designing your study properly in advance. In the long run, this will save you time, allowing you to get on with the research for your next big paper.

No-one wants to have to repeat experiments because the controls were inappropriate or the case/sample numbers were insufficient to provide enough statistical power. Frequently though, researchers rush into experiments without making all the proper considerations, and this can result in delays when their manuscripts reach the peer review stage. Remembering a few basic principles of study design can help to reduce the risk of outright rejection and repeated experimentation.

1. Have a hypothesis or research question
Having a hypothesis or appropriate research question enables you to ‘frame’ your research within an appropriate context, which in turn will help you apply the appropriate controls. It will also help you describe the rationale for your study when it is time to write it up. Having a hypothesis also means that the objectives of the study are clearly defined, thus reducing the chance that your study will be open-ended and possibly criticised for being incomplete. You can then logically work through these objectives and, importantly, present your results in a logical manner rather than haphazardly.

2. Ensure that the appropriate methods are used
Once you have a clear idea of the aims of your study, and the specific research question you are setting out to answer, you will need able to determine what methods would be appropriate to achieve these. Important considerations include deciding whether subjective, qualitative data will be sufficient to address your question, or whether there is a need for more quantitative methods. For basic science studies, such considerations might include the following questions. Will the combination of RT-PCR and in situ data be enough, or is there a need for qPCR? Is Western blotting alone sufficiently sensitive or do you need to also perform immunohistochemistry and cell counting experiments to show a difference between groups? For clinical studies, important considerations include the choice of controls, sample sizes, statistical tests and approach, all of which are described in more detail in the points below.

3. Ensure that the appropriate controls are used
Controls are included in experiments to rule out alternative hypotheses. There’s an old saying that “nothing can be proven, only disproved”, and this is precisely why appropriate controls are necessary: to disprove any feasible alternative interpretations of the data you obtain and/or to eliminate or minimize the effects of extraneous variables. Consider what alternative hypotheses exist, and systematically rule them out by performing experiments that disprove them. There are generally two types of controls: positive and negative. Positive controls show that a negative result is not due to a failure of the experimental system. Negative controls provide an indication of the ‘background noise’ or baseline value with which to compare values from your experimental sample. In quantitative studies, a “relative control” or “housekeeping control” is required to show that changes in the apparent levels of a target gene or protein are not caused by differences in the amounts of protein or DNA in the sample. These levels can be used as a baseline to measure changes in relative levels of a target gene or protein. Common housekeeping molecules include β-actin and GAPDH. In clinical trials, subjects in a placebo group in intervention trials, and normal control subjects in observational trials, need to be matched as closely as possible to those in the treatment or disease group in terms of age, sex and numerous other potential confounding factors. In randomized controlled trials, accepted procedures for assignment to groups also need to be followed (see, for example, the ICH good clinical practice guidelines at: http://www.ich.org/LOB/media/MEDIA482.pdf).

4. Use sample sizes large enough to provide a definitive result
Many studies fail to achieve the desired impact or to fully support a given hypothesis because the effect is too small or the variability too large to show statistical significance. Often this can be simply overcome by increasing the sample size. However, once a study has been performed and the data analyzed, it can be impossible to go back and increase the numbers without starting all over again. For this reason, pilot studies are often performed in advance of larger scale studies. Talk to a statistician. Determine the size of the effect of your treatment and/or the variability in your population before starting large-scale studies, and use this information to determine the sample size required to give you statistical power. Doing this can save you time, money and potential disappointment later.

5. Use appropriate statistical tests to analyze your data
Statistical analysis of your data is essential to show that an effect is genuine and significant. Tests of significance demonstrate the robustness of your findings, essentially showing how unlikely it is that your findings were obtained ‘by chance’. Are your data continuous or discrete? Are they normally distributed or non-normally distributed? The nature of your data will determine how they should be analyzed and what tests are appropriate. If in doubt, consult a statistician who will be able to advise you on the most appropriate tests to use and what these tests indicate. Determining the right tests to use in advance will save you having to repeat your analyses if you got it wrong first time round, with the distinct possibility that no significant effect will be observed when the appropriate tests are used. For clinical trials, the following guidelines may be useful: http://www.ich.org/LOB/media/MEDIA485.pdf.

6. Remove investigator and patient bias
Many experiments involve subjective measurements or assessments performed by the investigators, as opposed to objective results provided by the experimental system. If the investigator has prior knowledge of the groups to which individuals/samples belong, then investigator bias is a distinct possibility, and this can invalidate any of the findings obtained. In such cases, where the investigator is a factor inherent in the experimental system, it is essential that the investigator is ‘blinded’ to the groups to which individuals or samples belong. Doing so ensures the objectivity of the findings and improves their reliability. Such blinding can refer to treatment in an intervention trial, or to assessment or interpretation of clinical findings in an observational trial. Similarly, the outcome of a treatment could be influenced if a patient knows if they are receiving a placebo or drug; such patient bias should be avoided, by blinding the patient to the nature of the treatment. Being aware of the potential for bias before commencing experimentation can again save the need for time- and resource-consuming repeats.

7. Comply with ethical requirements
There are strict regulations regarding the use of human and animal subjects, and in many countries, regarding the use of stem cells, cell lines and genetically modified materials. Failure to comply with these regulations will prevent publication of your findings and could lead to legal issues; at best, it will limit the range of journals to which you can submit your findings. Make yourself aware of these regulations before you commence your study and ensure that all requirements are complied with so you don’t encounter problems later on. As well as ethical requirements regarding experimentation, there are also strict guidelines provided by most journals regarding the requirements for authorship, and these also need to be complied with. Clinical trials should comply with the Declaration of Helsinki (http://www.wma.net/e/policy/b3.htm) in addition to any local requirements. Informed consent is essential for most trials involving human subjects. Animal studies should comply with local and national regulations, although many journals are now aligning themselves with standards such as the NIH “Guidelines for the Care and Use of Animals” (http://oacu.od.nih.gov/regs/guide/guide.pdf). Finally, many journals require a statement describing who gave ethical approval for the study.

8. Clinical study registration
Many top-tier journals now request that prospective clinical trials involving human participants should be registered online in an accessible database. Many journals will instantly reject studies of this type that have not been registered. More information on this can be found at http://www.icmje.org/faq.pdf. International clinical trial registries include the Chinese Clinical Trials Register (http://www.chictr.org/), the Japanese Primary Registries Network (http://rctportal.niph.go.jp/), The International Standard Randomised Control Trial Number database (http://isrctn.org/) and Clinical Trials.gov (http://www.clinicaltrials.gov/). Registration should be done before the first participant is enrolled, but many of the databases do allow retrospective registration. However, by registering the trial once you receive ethical consent you will save time and overcome a major obstacle to publication.

All studies are different and therefore have different requirements regarding appropriate study design. The points above are just a few of the important considerations that should be made prior to the commencement of experimentation, and the general principles apply to a variety of different study types. It is true that sometimes even peer review fails to detect flaws in study design, as shown, for example, in the following report on randomized controlled clinical trials published in Chinese journals: http://www.trialsjournal.com/content/10/1/46. However, if you want your study to stand the test of time, be published in a top-tier journal and to be widely accepted by the international research community, then planning ahead and designing your study to make it robust and reliable will only serve to save you time, money and heartbreak later on.

在这里还需提请各位注意，Dr. McGowan 的母语是英语，无法阅读中文，因此请大家尽量使用英文回帖，如有任何需要与他沟通的学术和语言问题也请使用英语，Dr. McGowan 会及时回复大家的。

Dr. Daniel McGowan 曾任 Nature Reviews Neuroscience 副编辑，负责约稿，管理和撰写期刊内容。于2006年加入理文编辑（Edanz Group） 并从2008年起担任学术总监。Dr. Daniel McGowan 有超过十年的博士后和研究生阶段实验室研究经验，主要致力于神经退化疾病、分子及细胞生物学、蛋白质生物化学、蛋白质组学和基因组学。