The PRISMA-P reporting guideline for writing a protocol for a systematic review

The PRISMA-P reporting guideline helps authors write protocols for systematic reviews that can be understood and used by everyone. This page summarises PRISMA-P and how it can be used. Each guideline item links to more information, examples, and relevant training.

Journals endorsing PRISMA-P 1000+

PRISMA-P: The Preferred Reporting Items for Systematic review and Meta-Analysis Protocols

Version: PRISMA-P 2015 v1.1. This is the latest version ✅

How to use this reporting guideline

You can use reporting guidelines throughout your research process.

  • When writing: Consider using a writing guide to draft your manuscript or protocol.
  • After writing: Complete a checklist and include it with your journal submission.
  • To learn: Consult the guidance whenever you need it.

However you use PRISMA-P, please cite it.

Applicability criteria

Use PRISMA-P for writing a protocol or plan for a systematic review describing the rationale, the objectives, the methods you will use to locate, select and critically appraise studies, and to analyse data from the included studies.

You can also use PRISMA-P for:

  • writing a funding application or an entry for a prospective review register such as PROSPERO
  • reviewing the reporting of a systematic review protocol, but not for appraising the quality of its design.

Do not use PRISMA-P for:

Summary of guidance

Although you should describe all items below, you can decide how to order and prioritize items most relevant to your study, findings, context, and readership whilst keeping your writing concise. You can read how PRISMA-P was developed in the FAQs.

Title
1a. Identification Identify the report as a protocol of a systematic review.
1b. Update If the protocol is for an update of a previous systematic review, identify as such.
Registration
2. Registration If registered, provide the name of the registry (such as PROSPERO) and registration number.
Authors
3a. Contact Provide name, institutional affiliation, e-mail address of all protocol authors; provide physical mailing address of corresponding author.
3b. Contribution Describe contributions of protocol authors and identify the guarantor of the review.
Amendments
4. Amendments If the protocol represents an amendment of a previously completed or published protocol, identify as such and list changes; otherwise, state plan for documenting important protocol amendments.
Support
5a. Sources Indicate sources of financial or other support for the review.
5b. Sponsor Provide name for the review funder and / or sponsor.
5c. Role of sponsor or funder Describe roles of funder(s), sponsor(s), and / or institution(s), if any, in developing the protocol.
Introduction
6. Rationale Describe the rationale for the review in the context of what is already known.
7. Objectives Provide an explicit statement of the question(s) the review will address with reference to participants, interventions, comparators, and outcomes (PICO).
Methods
8. Eligibility criteria Specify the study characteristics (such as PICO, study design, setting, time frame) and report characteristics (such as years considered, language, publication status) to be used as criteria for eligibility for the review.
9. Information sources Describe all intended information sources (such as electronic databases, contact with study authors, trial registers or other grey literature sources) with planned dates of coverage.
10. Search strategy Present draft of search strategy to be used for at least one electronic database, including planned limits, such that it could be repeated.
11a. Study records - data management Describe the mechanism(s) that will be used to manage records and data throughout the review.
11b. Study records - selection process State the process that will be used for selecting studies (such as two independent reviewers) through each phase of the review (that is, screening, eligibility and inclusion in meta-analysis).
11c. Study records - data collection process Describe planned method of extracting data from reports (such as piloting forms, done independently, in duplicate), any processes for obtaining and confirming data from investigators.
12. Data items List and define all variables for which data will be sought (such as PICO items, funding sources), any pre-planned data assumptions and simplifications.
13. Outcomes and prioritization List and define all outcomes for which data will be sought, including prioritization of main and additional outcomes, with rationale.
14. Risk of bias in individual studies Describe anticipated methods for assessing risk of bias of individual studies, including whether this will be done at the outcome or study level, or both; state how this information will be used in data synthesis.
15a. Data synthesis Describe criteria under which study data will be quantitatively synthesised.
15b. Data synthesis If data are appropriate for quantitative synthesis, describe planned summary measures, methods of handling data and methods of combining data from studies, including any planned exploration of consistency (such as I2, Kendall’s τ).
15c. Data synthesis Describe any proposed additional analyses (such as sensitivity or subgroup analyses, meta-regression).
15d. Data synthesis If quantitative synthesis is not appropriate, describe the type of summary planned.
16. Meta-bias(es) Specify any planned assessment of meta-bias(es) (such as publication bias across studies, selective reporting within studies).
17. Confidence in cumulative evidence Describe how the strength of the body of evidence will be assessed (such as GRADE).

We like publishing transparent research because we think it’s more likely to be used and cited. That’s why we ask authors to use reporting guidelines.

Robin Lavery

Editor, International Journal of World Medicine

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Protocol

A protocol is the plan or set of steps to be followed in a study. A protocol for a systematic review should describe the rationale for the review; the objectives; and the methods that will be used to locate, select and critically appraise studies, and to collect and analyse data from the included studies. Protocols can, and probably should, be amended. A plan may change because the nature of a review changes. The key thing is that the amendments to the protocol need to be noted, together with the reasons. Protocols are good things because they make you think about what you are going to do, and why.

Source

Reporting Guidelines are recommendations to help describe your work clearly

Your research will be used by people from different disciplines and backgrounds for decades to come. Reporting guidelines list the information you should describe so that everyone can understand, replicate, and synthesise your work.

Reporting guidelines do not prescribe how research should be designed or conducted. Rather, they help authors transparently describe what they did, why they did it, and what they found.

Reporting guidelines make writing research easier, and transparent research leads to better patient outcomes.

Easier writing

Following guidance makes writing easier and quicker.

Learn more »

Smoother publishing

Many journals require completed reporting checklists at submission.

Learn more »

Maximum impact

From nobel prizes to null results, articles have more impact when everyone can use them.

Learn more »

Who reads research?

You work will be read by different people, for different reasons, around the world, and for decades to come. Reporting guidelines help you consider all of your potential audiences. For example, your research may be read by researchers from different fields, by clinicians, patients, evidence synthesisers, peer reviewers, or editors. Your readers will need information to understand, to replicate, apply, appraise, synthesise, and use your work.

Cohort studies

A cohort study is an observational study in which a group of people with a particular exposure (e.g. a putative risk factor or protective factor) and a group of people without this exposure are followed over time. The outcomes of the people in the exposed group are compared to the outcomes of the people in the unexposed group to see if the exposure is associated with particular outcomes (e.g. getting cancer or length of life).

Source.

Case-control studies

A case-control study is a research method used in healthcare to investigate potential risk factors for a specific disease. It involves comparing individuals who have been diagnosed with the disease (cases) to those who have not (controls). By analysing the differences between the two groups, researchers can identify factors that may contribute to the development of the disease.

An example would be when researchers conducted a case-control study examining whether exposure to diesel exhaust particles increases the risk of respiratory disease in underground miners. Cases included miners diagnosed with respiratory disease, while controls were miners without respiratory disease. Participants' past occupational exposures to diesel exhaust particles were evaluated to compare exposure rates between cases and controls.

Source.

Cross-sectional studies

A cross-sectional study (also sometimes called a "cross-sectional survey") serves as an observational tool, where researchers capture data from a cohort of participants at a singular point. This approach provides a 'snapshot'— a brief glimpse into the characteristics or outcomes prevalent within a designated population at that precise point in time. The primary aim here is not to track changes or developments over an extended period but to assess and quantify the current situation regarding specific variables or conditions. Such a methodology is instrumental in identifying patterns or correlations among various factors within the population, providing a basis for further, more detailed investigation.

Source

Systematic reviews

A systematic review is a comprehensive approach designed to identify, evaluate, and synthesise all available evidence relevant to a specific research question. In essence, it collects all possible studies related to a given topic and design, and reviews and analyses their results.

The process involves a highly sensitive search strategy to ensure that as much pertinent information as possible is gathered. Once collected, this evidence is often critically appraised to assess its quality and relevance, ensuring that conclusions drawn are based on robust data. Systematic reviews often involve defining inclusion and exclusion criteria, which help to focus the analysis on the most relevant studies, ultimately synthesising the findings into a coherent narrative or statistical synthesis. Some systematic reviews will include a meta-analysis.

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Systematic review protocols

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Meta analyses of Observational Studies

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Randomised Trials

A randomised controlled trial (RCT) is a trial in which participants are randomly assigned to one of two or more groups: the experimental group or groups receive the intervention or interventions being tested; the comparison group (control group) receive usual care or no treatment or a placebo. The groups are then followed up to see if there are any differences between the results. This helps in assessing the effectiveness of the intervention.

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Randomised Trial Protocols

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Qualitative research

Research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation. This type of research typically involves in-depth interviews, focus groups, or field observations in order to collect data that is rich in detail and context. Qualitative research is often used to explore complex phenomena or to gain insight into people's experiences and perspectives on a particular topic. It is particularly useful when researchers want to understand the meaning that people attach to their experiences or when they want to uncover the underlying reasons for people's behavior. Qualitative methods include ethnography, grounded theory, discourse analysis, and interpretative phenomenological analysis.

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Case Reports

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Diagnostic Test Accuracy Studies

Diagnostic accuracy studies focus on estimating the ability of the test(s) to correctly identify subjects with a predefined target condition, or the condition of interest (sensitivity) as well as to clearly identify those without the condition (specificity).

Prediction Models

Prediction model research is used to test the accurarcy of a model or test in estimating an outcome value or risk. Most models estimate the probability of the presence of a particular health condition (diagnostic) or whether a particular outcome will occur in the future (prognostic). Prediction models are used to support clinical decision making, such as whether to refer patients for further testing, monitor disease deterioration or treatment effects, or initiate treatment or lifestyle changes. Examples of well known prediction models include EuroSCORE II for cardiac surgery, the Gail model for breast cancer, the Framingham risk score for cardiovascular disease, IMPACT for traumatic brain injury, and FRAX for osteoporotic and hip fractures.

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Animal Research

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Quality Improvement in Healthcare

Quality improvement research is about finding out how to improve and make changes in the most effective way. It is about systematically and rigourously exploring "what works" to improve quality in healthcare and the best ways to measure and disseminate this to ensure positive change. Most quality improvement effectiveness research is conducted in hospital settings, is focused on multiple quality improvement interventions, and uses process measures as outcomes. There is a great deal of variation in the research designs used to examine quality improvement effectiveness.

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Economic Evaluations in Healthcare

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Meta Analyses

A meta-analysis is a statistical technique that amalgamates data from multiple studies to yield a single estimate of the effect size. This approach enhances precision and offers a more comprehensive understanding by integrating quantitative findings. Central to a meta-analysis is the evaluation of heterogeneity, which examines variations in study outcomes to ensure that differences in populations, interventions, or methodologies do not skew results. Techniques such as meta-regression or subgroup analysis are frequently employed to explore how various factors might influence the outcomes. This method is particularly effective when aiming to quantify the effect size, odds ratio, or risk ratio, providing a clearer numerical estimate that can significantly inform clinical or policy decisions.

How Meta-analyses and Systematic Reviews Work Together

Systematic reviews and meta-analyses function together, each complementing the other to provide a more robust understanding of research evidence. A systematic review meticulously gathers and evaluates all pertinent studies, establishing a solid foundation of qualitative and quantitative data. Within this framework, if the collected data exhibit sufficient homogeneity, a meta-analysis can be performed. This statistical synthesis allows for the integration of quantitative results from individual studies, producing a unified estimate of effect size. Techniques such as meta-regression or subgroup analysis may further refine these findings, elucidating how different variables impact the overall outcome. By combining these methodologies, researchers can achieve both a comprehensive narrative synthesis and a precise quantitative measure, enhancing the reliability and applicability of their conclusions. This integrated approach ensures that the findings are not only well-rounded but also statistically robust, providing greater confidence in the evidence base.

Why Don't All Systematic Reviews Use a Meta-Analysis?

Systematic reviews do not always have meta-analyses, due to variations in the data. For a meta-analysis to be viable, the data from different studies must be sufficiently similar, or homogeneous, in terms of design, population, and interventions. When the data shows significant heterogeneity, meaning there are considerable differences among the studies, combining them could lead to skewed or misleading conclusions. Furthermore, the quality of the included studies is critical; if the studies are of low methodological quality, merging their results could obscure true effects rather than explain them.

Protocol

A plan or set of steps that defines how something will be done. Before carrying out a research study, for example, the research protocol sets out what question is to be answered and how information will be collected and analysed.

Source

Protocol

A protocol is the plan or set of steps to be followed in a study. A protocol for a systematic review should describe the rationale for the review; the objectives; and the methods that will be used to locate, select and critically appraise studies, and to collect and analyse data from the included studies. Protocols can, and probably should, be amended. A plan may change because the nature of a review changes. The key thing is that the amendments to the protocol need to be noted, together with the reasons. Protocols are good things because they make you think about what you are going to do, and why. [Source](https://casp-uk.net/glossary/protocol/)