IMPORTANCE OF A GOOD QUESTION
A good meta-analysis is based on a well-formulated, clinically relevant, practically feasible, and answerable question. This question is the lifeline of the meta-analysis. A good question guides the meta-analysis at every step, from inclusion/exclusion criteria for studies, to the choice of statistical methods, to the presentation of the results, to writing a manuscript, to choice of the journal where you would like it to be published. On the other hand, a poor question will result in an incoherent effort and confused manuscript.
ORIGIN OF GOOD QUESTION
We find plenty of questions in our routine clinical practice. These questions may be asked by our patients (for example, will this cholesterol lowering drug increase my risk of developing cancer? or, can I lower my cholesterol by eating garlic?) or may appear in clinician’s mind in complex clinical cases. We may try to answer these questions with some guess-work, or with pseudo-confidence, or we may admit our lack of knowledge, or level of uncertainty in relation to that particular question. Once we admit uncertainty about the answer to a particular clinical problem, we should try to find its answer. Sometimes, answers are straightforward, while on other occasions, there is no clear answer providing a researcher an opportunity.
CHOOSING A CLINICALLY RELEVANT QUESTION
The number of questions with unclear answers is limitless, however, not all questions can be answered with a meta-analysis and the resources and time available to a researcher are quite limited. Thus, we have to choose the clinically most important question. The definition of the clinically most important may be quite variable depending on whether we choose clinician’s perspective, or patient’s perspective. Generally, a good question should have a major effect on patients as well as should improve clinical practice.
FORMULATING A QUESTION
The earliest stage of developing a research question involves defining, very broadly, three things; exposure variable(s), outcome variable(s), and the study-population. Basically, we want to see the effect of exposure variable on the outcome variable in a particular study population.
If the definitions of these three terms are not clear, then try to phrase the research question in the following manner:
Effect of A on B in C
Here A is exposure variable, B is outcome variable, and C is study population. The relationship between these three terms is our research question or hypothesis.
Exposure variable can be any factor to which a study-population has been, is, or will be subjected to such as a risk factor, treatment, or a diagnostic test.
An outcome variable is a measure of the response to the exposure variable, such as a disease condition cured or improved, death, or increased mobility.
A study population is the group of patients (or subjects) on which the results of the meta-analysis will be applicable. Both the control group and the treatment group should have been sampled from this population.
SHORT-CUT
Updating a previous meta-analysis circumvents the problem of finding and formulating a question. One can update a previous meta-analysis if sufficient new data is available from studies completed after the publication of that met-analysis that can change its conclusions.
