Where do I get the list of included studies from each review?

From the reviews themselves, usually from the characteristics-of-included-studies table or the reference list. It is tedious rather than difficult. Reviews that do not list their included studies in an extractable form are themselves a reporting failure worth noting.

Is an overview the same as an umbrella review?

The terms are used interchangeably in much of the literature. Both synthesise existing systematic reviews rather than primary studies. What matters more than the label is that you state the unit of analysis, handle overlap explicitly, and avoid double-counting the same primary study across multiple included reviews when reporting effects.

How do I handle the same primary study appearing in several included reviews?

Report the overlap, and choose a prespecified rule for which review's data to use when reporting an effect: the most recent, the largest, the most methodologically sound by AMSTAR 2, or the one whose eligibility criteria match your question most closely. State the rule in the protocol and apply it consistently.

Check the Overlap Before You Start Another Review

6 September 20264 min

Before designing a review of a question that has already been reviewed, work out how much the existing reviews share. It takes an afternoon and it changes the design more often than people expect.

A preprint from August 2026 illustrates why. [Weibel and colleagues]( https://doi.org/10.64898/2026.08.20.26360343) examined 42 systematic reviews of corticosteroids in sepsis published between 2015 and 2025, covering 121 unique randomised trials. More than half of the pairwise comparisons between reviews shared no trials at all. Only three pairs showed high overlap.

Forty-two reviews of one clinical question, and most pairs of them were working from entirely different evidence.

Overlap tells you what kind of gap you have

Three situations, and each calls for a different design.

High overlap and consistent conclusions. The ground is covered. A new review adds little unless enough time has passed for substantial new trials to have reported, or unless you are answering a genuinely different question.

High overlap and inconsistent conclusions. The reviews share trials but disagree, so the disagreement is methodological: different effect measures, different models, different handling of missing data. An overview or a re-analysis explains more than a new review would.

Low overlap. The reviews have been asking different questions under similar titles. This is the case in the sepsis example, and the useful contribution is usually an overview that maps how eligibility decisions produced the divergence, not a forty-third review that adds to it.

How to measure it

The corrected covered area is the standard measure (Pieper et al., 2014). Build a citation matrix with reviews as columns and primary studies as rows, mark which studies appear in which reviews, and calculate the proportion of repeated occurrences adjusted for the size of the matrix.

Pieper and colleagues proposed interpretive bands: roughly 0–5% slight overlap, 6–10% moderate, 11–15% high, and above 15% very high. Report the value and the matrix. Overview readers need to know that a finding appearing in five reviews may rest on the same two trials each time.

Specification, not statistics

The most instructive result in the sepsis preprint is not the overlap figure. Of the 38 reviews reporting a meta-analysis of short-term mortality, 39% found a benefit and 61% found no effect. That discordance occurred exclusively among reviews of broadly specified corticosteroid strategies. Reviews of narrowly specified regimens agreed with each other.

The obvious explanations for reviews disagreeing are statistical, and statistical explanations predict disagreement scattered across the whole set. They do not predict disagreement falling entirely on one side of a line drawn by how tightly the intervention was defined.

An eligibility explanation fits. "Corticosteroids in sepsis" is a family of questions covering different drugs, doses, timings relative to shock onset, durations and severity thresholds. Each team drew the boundary somewhere; different boundaries produced different trial sets; different trial sets produced different answers. The reviews are not in conflict so much as talking past each other.

For anyone designing a review, the lesson is that if dose and timing plausibly modify the effect, they belong in the eligibility criteria rather than in a subgroup analysis added afterwards.

If you proceed anyway, publish the overlap

Sometimes a further review is justified: the existing ones have aged, a large trial has reported since, or they genuinely answer a different question. In that case the overlap analysis you did at the planning stage is worth publishing rather than filing.

A short paragraph in the introduction stating how many prior reviews exist, how much they share, and where your eligibility boundary sits relative to theirs does three jobs. It answers the reviewer question about why another review was needed. It tells readers which earlier reviews yours supersedes and which it sits alongside. And if your conclusion differs from a well-known predecessor, it lets the reader see whether you were working from the same trials.

Most reviews of crowded questions assert novelty in a sentence. Showing the arithmetic takes a paragraph and is considerably more convincing.

References

Pieper, D., Antoine, S.-L., Mathes, T., Neugebauer, E. A. M., & Eikermann, M. (2014). Systematic review finds overlapping reviews were not mentioned in every other overview. Journal of Clinical Epidemiology, 67(4), 368–375. https://doi.org/10.1016/j.jclinepi.2013.11.007

Weibel, S., et al. (2026). Why systematic reviews of the same question disagree: A case study of corticosteroids in sepsis [Preprint]. https://doi.org/10.64898/2026.08.20.26360343

Common questions

Where do I get the list of included studies from each review?: From the reviews themselves, usually from the characteristics-of-included-studies table or the reference list. It is tedious rather than difficult. Reviews that do not list their included studies in an extractable form are themselves a reporting failure worth noting.
Is an overview the same as an umbrella review?: The terms are used interchangeably in much of the literature. Both synthesise existing systematic reviews rather than primary studies. What matters more than the label is that you state the unit of analysis, handle overlap explicitly, and avoid double-counting the same primary study across multiple included reviews when reporting effects.
How do I handle the same primary study appearing in several included reviews?: Report the overlap, and choose a prespecified rule for which review's data to use when reporting an effect: the most recent, the largest, the most methodologically sound by AMSTAR 2, or the one whose eligibility criteria match your question most closely. State the rule in the protocol and apply it consistently.