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| pretty_name | FAERS disproportionality signals, 2004-2026 | ||||||
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Drug–event reporting associations computed over every adverse event report FDA has published since 2004 — 20.3 million distinct cases after deduplication, spanning both the legacy LAERS and current FAERS eras.
Produced by a fully reproducible DVC pipeline: https://github.com/neksa/openfda-faers
These are reporting associations, not evidence of harm. A drug–event pair scoring highly here is reported together more often than the rest of the database predicts. That is a hypothesis to investigate. It is not causation, and it is not a rate — the number of people who took the drug without incident is unknown, so incidence cannot be computed from these data. See Limitations.
| File | Rows | Description |
|---|---|---|
scored.parquet |
~2.3M | One row per drug–event pair, with contingency counts and five disproportionality measures |
descriptive/ |
small | Corpus description: growth, demographics, reporters, top terms, report structure |
*.json |
small | Stage metrics: deduplication, normalization, signal counts, drift, duplicates |
| Column | Type | Meaning |
|---|---|---|
ingredient |
string | Active ingredient, uppercase. Resolved from the reported drug name; see Drug resolution |
ingredient_rxcui |
string | RxNorm identifier for the ingredient, where known. Join key to RxNorm/OMOP |
ingredient_curated |
bool | false means the name is an unmapped product string, not a resolved substance. Filter on this |
pt |
string | MedDRA Preferred Term for the reaction, as published by FDA in FAERS |
All counts are of reports, not of table rows: a report naming the same ingredient three times contributes once.
| Column | Type | Meaning |
|---|---|---|
a |
int | Reports with this ingredient and this reaction |
b |
int | Reports with this ingredient, without this reaction |
c |
int | Reports with this reaction, without this ingredient |
d |
int | Reports with neither |
n_ij, n_i, n_j |
int | Co-reports, ingredient total, reaction total (a, a+b, a+c) |
expected |
float | n_i × n_j / N — expected co-reports under independence |
Every measure is reported with its interval. Screen on the lower bound, never the point estimate: a ratio of 8 computed from two co-reports is noise.
| Column | Meaning |
|---|---|
ror, ror025, ror975 |
Reporting odds ratio, 95% CI (Haldane–Anscombe corrected) |
prr, prr025, prr975 |
Proportional reporting ratio, 95% CI |
chi2_yates |
Yates-corrected χ², the companion to PRR in the MHRA rule |
p_fisher, q_bh |
One-sided Fisher exact p-value; Benjamini–Hochberg q-value |
ic, ic025, ic975 |
Information component (BCPNN), Norén 2006 shrinkage |
ebgm, eb05, eb95 |
Empirical Bayes geometric mean (MGPS/DuMouchel), posterior 5th/95th percentiles |
| Column | Rule | Convention |
|---|---|---|
signal_ror |
ror025 > 1 |
common |
signal_prr_mhra |
prr ≥ 2 and χ² ≥ 4 and a ≥ 3 |
MHRA |
signal_ic |
ic025 > 0 |
WHO-UMC |
signal_eb05 |
eb05 ≥ 2 |
FDA / MGPS — the most conservative |
signal_fdr |
q_bh < 0.05 |
multiplicity-controlled |
No flag is authoritative. They are published side by side because their disagreement is
informative; signal_eb05 is very nearly a subset of the others.
Source: FDA's quarterly FAERS/LAERS ASCII extracts (public domain), 90 archives, each pinned by
SHA-256 in source_manifest.json.
- Harmonize both eras into one schema. They differ substantially — LAERS is
ISR-keyed with no active-ingredient field; FAERS isprimaryid/caseid/caseversion-keyed. - Deduplicate. 16.7% of raw records are redundant: 4.0M superseded case versions and 67,838 FDA-retracted cases. 82,134 cases span the 2012 era boundary.
- Resolve drug names to ingredients (98.6% of rows) via FDA's
prod_ai, a dictionary bootstrapped from the corpus, FDA's NDC directory, and NLM RxNav. - Score every pair with ≥3 co-reports, restricted to primary/secondary suspect drugs.
Read these before using the data.
- No causality, no rates. Reporting associations only. The unexposed denominator is unknown.
- Highly-ranked pairs are frequently indication bias, not harm. The top-scoring pairs in this corpus include a radioisotope tracer with "radioisotope scan abnormal" and an antipsychotic with a feature of the psychosis it treats. They rank highly because the association is real and near-deterministic — which is precisely why disproportionality cannot distinguish harm from reason-for-prescribing.
- ~24% of distinct drug labels in the signal table are product names, not substances. These
have
ingredient_curated = false. Their marginals are split, which both understates the parent substance and inflates the fragment. Filter them for anything quantitative. - MedDRA version drift is flagged, not corrected. Terms are revised twice yearly; see
drift_summary.jsonand thedrift_suspectflag. Correcting it requires the licensed MedDRA release. Temporal claims should exclude flagged terms. - Independent duplicates are estimated, not removed. The same incident reported separately
under different case ids is detected by blocked record linkage and reported in
duplicates_summary.json, but not removed from these tables. Blocking makes the estimate a lower bound. - q-values are approximate. Benjamini–Hochberg assumes independence or positive dependence; drug–event tests share reports and are dependent.
- Partial dates are completed to the start of the period, biasing them toward month-starts.
nSIDES is the closest prior work and this is a complement, not a replacement. OFFSIDES covers FAERS through 2014 and reports PRR with a propensity-score-matched design. This covers 2004Q1–2026Q2 across both eras, deduplicated, and reports five measures with intervals plus FDR. OFFSIDES' propensity-score adjustment is methodologically stronger on confounding than the Mantel–Haenszel stratification used here; this dataset is broader in coverage and in measures. Use both.
This is a non-commercial academic project.
The derived tables are released CC BY 4.0. That covers what is actually this project's work: the contingency counts, the computed measures, the resolution provenance and the code that produced them.
It does not, and cannot, relicense the underlying vocabularies. A licence granted here applies only to this project's contribution.
| Component | Origin | Terms |
|---|---|---|
| Contingency counts, measures, flags | this project | CC BY 4.0 |
| Underlying reports | FDA FAERS | public domain (US federal work) |
ingredient, ingredient_rxcui |
RxNorm (NLM) | public domain |
pt |
MedDRA, as published by FDA in the public FAERS release | see below |
MedDRA is a licensed terminology owned by IFPMA and maintained by the MSSO. The preferred terms in
pt reach this dataset through FDA's public-domain FAERS release, not from the MedDRA
distribution — FDA publishes them openly, to everyone, with no licence check. No MedDRA product is
redistributed here and no MedDRA dictionary was used to build this: the pipeline treats these
strings as opaque labels and performs no terminology lookup anywhere.
If you intend to use the pt column in your own work, confirm your own position. MedDRA
subscriptions are free of charge for non-profit, non-commercial and academic organisations and for
regulatory authorities; commercial users pay a revenue-scaled fee. Nothing else here carries that
consideration — the drug side is RxNorm, the statistics are CC BY 4.0 — so a consumer who would
rather not engage with it can drop that single column and use the entire rest of the dataset.
@misc{goncearenco_faers_2026,
author = {Goncearenco, Alexander},
title = {FAERS disproportionality signals, 2004--2026},
year = {2026},
url = {https://github.com/neksa/openfda-faers}
}van Puijenbroek et al. (2002) Pharmacoepidemiol Drug Saf 11:3–10 · DuMouchel (1999) Am Stat 53:177–190 · Norén et al. (2006) Stat Med 25:3740–3757 · Robins, Breslow & Greenland (1986) Biometrics 42:311–323