Signals by drug and event

Note: first load takes a few seconds while the app computes label matches and class stats for the displayed rows. Subsequent interactions are fast. AERS data ends 2012Q3; FAERS continues at faers.mobi .

All (drug, event) pairs flagged by ≥2 of 4 disproportionality methods (GPS/EBGM, PRR, ROR, IC) over the AERS 2004–2012 era. The splash shows the top 2000 by Adj EB05 (peak EB05 after Weber-effect shrinkage for drugs <5 years on market at the time); use search to find any other pair. Default filter: Novel pairs with ≥3 quarters of signal. Click any row to see the time-course plot and the label cross-check.

Novel column: “novel” means the event is absent from the drug’s current FDA label — boxed warning, contraindications, warnings, adverse reactions, indications — after MedDRA-synonym expansion (UMLS CUI) and British↔American + clinical-term normalization. Note this compares historical AERS-era signals to current labels: a drug whose label was updated 2013–2025 in response to a real signal will show as “known” here. Medication- error, product-quality, and administration PTs are hidden. Class co-flags = number of other drugs in the same ATC4 class that also flag this event across the full pair universe (1 = drug-specific; ≥3 suggests class effect). The default view hides pairs with ≥3 class co-flags as likely class effects; clear the Class co-flags column filter to see them. Treat remaining rows as historical hypotheses, not confirmed novel associations.


Disclaimer: disproportionate reporting is a statistical pattern, not evidence of causation. Signals are hypotheses requiring further investigation. 'Known' means the event appears in the drug's current FDA label; 'Novel' means it does not (label coverage is limited to drugs we have cached openFDA label data for).

Bayesian Gamma-Poisson Signal Detection

Upload your own AE report CSV (columns: product, event) to run disproportionality analysis in the browser. For precomputed historical AERS signals, see the Signals over time tab.


Expected columns: product, event

Each row = one adverse event report.


Signal Detection Results

About aers.mobi

Signal detection over the legacy AERS database (2004-2012), the predecessor to FAERS. Captures the classic case studies of the era: Vioxx / myocardial infarction (withdrawn 2004), Avandia, Baycol, and many others.

Companion to faers.mobi which covers the current FAERS era (2018 onward).

Data source

AERS quarterly ASCII dumps from FDA, processed through the same R/targets pipeline as faers.mobi with era-aware schema handling (ISR/CASE -> primaryid/caseid).

Statistical methods

  • GPS — EB05 is the 5th-percentile credible bound of the two-component Gamma mixture posterior (DuMouchel 1999 framework, linear RR scale). This is a direct posterior quantile, not the EBGM geometric mean.
  • PRR + Yates chi-squared (Evans 2001)
  • ROR with log-normal CI (van Puijenbroek 2002)
  • BCPNN/IC with 95% credibility bound (Bate 1998)

Disclaimer

Disproportionate reporting is a statistical pattern, not evidence of causation. Signals are hypotheses requiring further investigation.