MOOSE

What it is

MOOSE (Meta-analysis Of Observational Studies in Epidemiology) is a reporting guideline for meta-analyses and systematic reviews of observational studies — cohort, case-control, and cross-sectional evidence rather than randomized trials. It originated as a consensus proposal from a 27-member expert workshop convened by the editors of JAMA and published by Stroup and colleagues in 2000, and a structured reporting-checklist version was reaffirmed and re-issued by Brooke and colleagues in 2021. MOOSE is catalogued and maintained by the EQUATOR Network as the observational-evidence counterpart to PRISMA. Its 35 recommended items are organized into six reporting domains: reporting of background, reporting of search strategy, reporting of methods, reporting of results, reporting of discussion, and reporting of conclusions. MOOSE is a reporting instrument: it standardizes what a manuscript must disclose so a reader can judge how the synthesis was conducted — it does not score study quality and does not adjudicate risk of bias.

When to use

Apply MOOSE whenever the deliverable is a synthesis of observational studies intended for a peer-reviewed journal, an HTA/payer evidence dossier, or a regulatory (FDA/EMA) submission that leans on pooled real-world or epidemiologic evidence. Typical triggers: a pooled estimate of a drug-outcome association across pharmacoepidemiologic cohorts; a meta-analysis of incidence, prevalence, or natural-history estimates from registries and claims; a comparative-effectiveness synthesis where no head-to-head trial exists. Decision rule for which guideline applies: if the included studies are observational, MOOSE is the design-specific reporting standard, used alongside PRISMA 2020 (the general systematic-review scaffold for flow diagrams, abstract, and search reporting) — they are complementary, not substitutes. If the synthesis pools randomized trials, use PRISMA 2020 with a trials focus, not MOOSE. If you are reporting a single primary observational study (one cohort, one case-control analysis, one claims database study), MOOSE does not apply — use STROBE, or RECORD/RECORD-PE for routinely collected health data. For the protocol of an observational review, register and report with PRISMA-P; MOOSE governs the completed synthesis.

What it requires

MOOSE's six domains force explicit disclosure of the substantive choices that make an observational synthesis interpretable. Background: the problem definition, hypothesis, study outcome(s), exposure/intervention, study designs eligible, and the target population. Search strategy: qualifications of searchers, databases and registries used, search terms and date limits, use of hand-searching and contact with authors, inclusion of non-English and unpublished/grey literature, and the handling of publication bias — the reporting analogue of data-fitness-for-use, since the "data" of a meta-analysis are the retrievable primary studies. Methods: the rules for judging study conformance to the question, rationale for selection, documentation of how studies were assessed (and how heterogeneity in exposure/outcome definitions and phenotypes across primary studies was handled), the pooling method, statistical model (fixed vs random effects), tests for heterogeneity, sensitivity and subgroup analyses, and assessment of confounding within and across the included studies. Results: a study-flow diagram (accounting for attrition from records screened to studies pooled), tabulation of descriptive and effect estimates with appropriate measures of variability, and graphical summaries. Discussion and conclusions: quantitative assessment of bias (including publication bias), justification of exclusions, the validity and generalizability of the pooled estimate, and guidance for future research. For real-world-data syntheses, MOOSE compliance specifically means documenting how disparate exposure windows, outcome algorithms, time-zero conventions, and confounding-control strategies across the source studies were reconciled before pooling.

When NOT to use — limitations and common misapplications

MOOSE is a reporting checklist, not a risk-of-bias instrument and not a quality score: completing all 35 items certifies that a manuscript disclosed its methods, not that those methods were sound. Pair it with a genuine risk-of-bias tool — ROBINS-I for the included studies, or the Newcastle-Ottawa Scale — and do not report a MOOSE "score" as if it graded validity. Specific failure modes: (a) using MOOSE to report a single primary observational study when STROBE or RECORD-PE is the correct standard; (b) treating MOOSE completion as evidence that the pooled estimate is causal — observational synthesis inherits the confounding of its inputs, and a transparently reported meta-analysis of biased studies is still biased ("garbage in, garbage out"); (c) checklist-as-theater — filing a completed checklist in an appendix while the manuscript body omits the heterogeneity, publication-bias, and sensitivity analyses the items demand; (d) applying MOOSE to a meta-analysis of RCTs, where PRISMA 2020 governs; (e) skipping MOOSE because the team already has PRISMA 2020 — PRISMA is the general scaffold and MOOSE adds the observational-specific reporting expectations, so both are completed.

How it maps to this catalog

MOOSE's reporting domains map onto concrete methods concepts in this repository that implement what each item demands. Search-strategy and study-eligibility reporting are operationalized by the synthesis concepts meta-analysis-obs, systematic-review, and network-meta-analysis (for indirect/mixed comparisons). The MOOSE requirement to reconcile outcome and exposure definitions across primary studies is implemented by diagnosis-phenotype-algorithm-1ip-2op-time-window-rwe (phenotype/algorithm transparency and validation) and, for the underlying data, claims-analysis and fit-for-purpose-data-assessment-rwe. MOOSE's confounding-assessment items are implemented by active-comparator-new-user and high-dimensional-propensity-score-hdps-rwe (how the included studies controlled confounding, which a synthesis must summarize and contrast). The estimand and intercurrent-event reporting that a defensible pooled effect requires is implemented by estimands-ate-att-intercurrent-events-rwe, and where the synthesis emulates a trial protocol, target-trial-emulation. MOOSE's study-flow and attrition reporting is implemented by attrition-and-loss-to-follow-up-rwe, and the PICOTS framing that anchors background and eligibility items is implemented by picots-framework-rwe. Applied note for claims/EHR/registry RWE: when meta-analyzing pharmacoepidemiologic studies built on routinely collected data, the highest-yield MOOSE work is documenting cross-study heterogeneity in code lists, lookback/washout windows, time-zero conventions, and PS strategies — differences that frequently explain between-study heterogeneity more than clinical effect modification, and that a transparent MOOSE-compliant report must surface before any pooled estimate is trusted.