In medical literature reviews, 25–60 included studies is common; there’s no fixed minimum, and a meta-analysis needs two or more studies.
A medical literature review pulls together all eligible evidence on a focused question, screens it against clear criteria, and synthesizes what the studies show. Readers often ask for a number. The honest answer: there isn’t a magic count. Field maturity, outcome variety, and study eligibility shape the final tally. That said, patterns do appear across review types, and you can plan your screening workload and sample size targets with those patterns in mind.
Quick Ranges By Review Type
The table below shows broad ranges that teams commonly see once screening and eligibility checks are complete. These are not rules; they’re planning anchors drawn from editorial guidance and reporting standards used in medicine (for instance, the PRISMA 2020 checklist and the Cochrane Handbook stress transparent reporting, not a fixed quota of studies). You’ll also notice a column for meta-analysis feasibility, since pooling needs at least two comparable studies, per the Cochrane statistical chapter.
| Review Type | Typical Included Studies | Meta-Analysis Feasible? |
|---|---|---|
| Systematic Review (Interventions) | 10–60 (many end near 20–40) | Yes, when ≥2 studies share design, outcomes, and measures |
| Systematic Review (Diagnostics/Prognosis) | 8–40 (varies with test/outcome definitions) | Often, if measures are comparable across studies |
| Scoping Review | 30–200+ sources is common for mapping breadth | Usually not the goal; mapping > pooling |
| Narrative Review (Invited/Topical) | 20–80 curated studies; range is wide | Not typical; emphasis is synthesis and context |
| Qualitative Evidence Synthesis | 10–40 studies; depth over volume | Pooling uses thematic/meta-synthesis, not numeric pooling |
Two points anchor these ranges. First, reporting standards like the PRISMA 2020 checklist ask you to show how many records you found, screened, excluded, and included; they don’t prescribe a minimum count. Second, Cochrane’s statistics chapter defines meta-analysis as a combination of results from “two or more” studies, which sets a practical floor for pooling but not for the review itself; a review can be valid even when no study meets strict criteria (sometimes called an “empty review”). You’ll still report the question, methods, search, and reasons no study qualified, and you’ll point to gaps for research — all standard practice in evidence-based medicine as outlined by the Cochrane community and in evaluations of empty reviews.
How Many Papers Should A Medical Literature Review Include?
Plan for a number that fits your question and eligibility rules rather than a fixed target. On clinical treatment questions with clear outcomes and common comparators, ending near 20–40 included trials is common. Broader questions (multi-condition, multiple comparators, mixed designs) often land higher. Diagnostic and prognosis topics can shrink or expand with how strict your definitions are. And if only a few small trials exist, the review might include fewer than ten — still valuable if the methods are complete and transparent, with pooling only when studies match.
What The Field Typically Sees
Large review programs offer helpful context. Cochrane samples have shown many meta-analyses built from a small set of eligible trials; a classic analysis of reviews found meta-analyses commonly based on a handful of studies, while the number of participants per review spanned a wide range. Editors in major journals ask authors to report the full count screened, the number excluded, and the final number included, along with reasons for each exclusion.
When “Zero Included” Happens
Strict criteria sometimes leave you with no eligible primary studies. That’s not a failure; it’s a clear signal about the state of the evidence. Cochrane groups describe such outputs as empty reviews and provide instructions for reporting them responsibly. The message to readers is simple: the question matters, the methods are sound, and research is needed.
Set A Smart Target Using Your PICO
PICO (Population, Intervention, Comparator, Outcome) shapes both feasibility and yield. Narrow PICO usually improves internal consistency but can shrink the study pool. Broader PICO expands coverage but increases heterogeneity. Match your target to the question you must answer, not the biggest number you can assemble.
Population And Setting
Specialty populations (rare diseases, pediatrics, specific surgical subtypes) often limit the pool. Multicenter adult topics expand it. Screening plans should reflect the expected volume.
Interventions And Comparators
Head-to-head trials with standard comparators are common in pharmacotherapy, which tends to boost counts. Device and procedural topics often have fewer randomized trials; eligibility may lean on non-randomized designs (as allowed by your protocol and the risk-of-bias approach in the Handbook).
Outcomes And Timing
Hard clinical endpoints (mortality, hospitalization) appear less often than intermediate markers. If your primary outcome is rare or long-term, expect fewer eligible studies and plan to narrate rather than pool where measures don’t align.
Screening Math You Can Use
Planning starts with search volume, not just the final count. The mini-calculator below helps teams forecast workload from search to inclusion. Adjust the percentages to fit your field and past experience.
From Records To Included Studies
- Initial records: database hits + trial registries + citations.
- After de-duplication: remove 15–25% duplicates.
- Title/abstract keep rate: 5–20% usually pass to full-text.
- Full-text inclusion rate: 10–40% of those screened at full-text.
With 2,000 records, a common path might be 1,600 after de-duplication, 160 full-texts, and 25–40 included studies. This mirrors the flow mandated by PRISMA diagrams and journal formats.
When Pooling Is Sensible
Pooling needs at least two comparable studies. That line comes straight from Cochrane’s statistics chapter. If outcomes, time-points, or effect measures are inconsistent, narrate findings and justify why a pooled estimate would mislead. Link your decision to heterogeneity checks and risk-of-bias considerations, as outlined in the Handbook. For readers who want a one-click reference, see the Cochrane meta-analysis chapter.
Quality Over Quantity Always Wins
Editors reward clarity on eligibility criteria, risk-of-bias methods, and certainty grading. The count alone never guarantees usability. Follow reporting guides, show the PRISMA flow, and make clear why each study qualifies. That transparency is what makes a review decision-ready. A quick source for the checklist and flow diagram is the PRISMA site.
Practical Targets By Scenario
Use the guide below to set a realistic aim for your project plan. Treat these as starting points, then refine after pilot screening.
| Scenario | Planning Target (Included Studies) | Notes |
|---|---|---|
| Common Drug Vs Standard Care | 20–40 | Likely many RCTs; pooling often feasible if outcomes align |
| Rare Disease Treatment | 5–15 | Expect small trials/observational designs; pooling may be limited |
| Screening Test Accuracy | 12–30 | Check reference standards and thresholds to judge comparability |
| Rehabilitation Or Lifestyle Intervention | 10–30 | Outcomes and time-points vary; plan subgroup logic early |
| Scoping Map Of Emerging Topic | 50–150+ | Goal is coverage across concepts, not pooling |
Workflow That Gets You To The Right Number
Write A Tight Protocol
Define PICO, databases, dates, languages, study designs, comparators, and primary outcomes. Pre-register when possible to lock decisions before seeing the data. Eligibility clarity is what turns a vague target into a defendable final count.
Pilot Your Screen
Have two reviewers pilot 100–200 titles/abstracts, compare conflicts, and adjust rules. Piloting quickly shows whether your target is realistic or if you should refine criteria.
Track Reasons For Exclusion
Use a simple taxonomy (wrong population, wrong comparator, wrong outcome, wrong design, duplicate, incomplete data). Journal guidelines ask you to report counts per step and reasons for exclusion at full-text.
Plan For “Few Studies” Outcomes
Even when the overall review includes many studies, some outcomes will have only a handful at pooling time. Report them fully, but resist inflated claims. When studies are too heterogeneous, keep the synthesis narrative and point to gaps.
What Review Leaders And Editors Expect To See
- Transparent Methods: search strategy, dates, databases, and registries.
- Clear Eligibility: inclusion/exclusion rules, with examples.
- Risk-Of-Bias Methods: tool selection and domain decisions.
- Flow Diagram: records identified, screened, excluded, included.
- Appropriate Synthesis: pooling only where comparable, with heterogeneity checks.
- Certainty Judgments: summary tables that tie evidence to decisions.
These points are echoed throughout the Cochrane Handbook and PRISMA materials used across clinical journals.
Frequently Missed Nuances About “How Many”
More Isn’t Always Better
A review with 70 weak studies can be less helpful than one with 15 solid trials. Quality, consistency, and directness carry the day.
Pooling Isn’t Mandatory
When measures don’t match, narrate findings and explain why a pooled estimate would mislead. Cochrane guidance is clear on when to avoid pooling and how to present results instead.
Empty Can Be Informative
When eligibility rules are tight and the field is thin, a review with no included studies still helps clinicians and funders by mapping the gap. Cochrane calls these “empty reviews” and offers reporting pointers.
Action Plan For Your Project
- Draft PICO And Protocol: pre-specify designs and outcomes you’ll accept.
- Choose Reporting Guides: line up the PRISMA 2020 checklist and journal rules so your flow and counts match expectations.
- Pilot And Calibrate: run a small screen to check volume.
- Forecast Workload: estimate de-duplication, title/abstract pass rates, and full-text inclusion to plan staff time.
- Decide Pooling Rules: commit to when you’ll pool and when you’ll narrate, aligning with the Cochrane meta-analysis chapter.
Bottom Line For Planning
There’s no set count that all medical reviews must hit. Most land in the 25–60 range for included studies when the topic is common and eligibility is clear. Pool when at least two studies genuinely match; narrate when they don’t. Report each step with PRISMA, and your review will read as trustworthy regardless of whether it includes five studies or fifty.