When a Systematic Review Might Be Preferable (or Sufficient)
Knowing When to Hold 'Em, When to Fold 'Em
While meta-analyses often hold the crown for statistical rigor, there are specific scenarios where a systematic review, without the added statistical synthesis, might be the more appropriate or even preferred method. It's not always a competition; sometimes, it's about fit. For instance, if the included studies are too heterogeneous in their design, populations, or interventions, attempting a meta-analysis could lead to a misleading "apples and oranges" comparison.
Imagine trying to combine the results of studies on the effectiveness of different types of fertilizer when some studies used tomatoes, others used peppers, and still others used flowers. The results, even if statistically combined, might not tell you much about any single crop. In such cases, a systematic review that highlights the diversity and provides a narrative synthesis of the findings is far more valuable.
Furthermore, if the primary goal is to identify gaps in the literature, explore the range of existing research, or develop hypotheses for future studies, a systematic review can be perfectly sufficient. It provides a comprehensive overview without necessarily needing to produce a single pooled estimate. Sometimes, knowing what we don't know is just as important as what we do know.
Finally, the feasibility of conducting a meta-analysis also plays a role. If there are too few studies, or if the data presented in the studies are not in a format suitable for statistical pooling, a systematic review might be the only practical option. It’s better to have a high-quality systematic review than a poorly conducted or inappropriate meta-analysis.
