The Cotinine Field Guide
A source-backed calculator for nicotine exposure, urine cotinine cutoffs, and the uncertainty around smoking-status tests.
Urinary cotinine after quitting
① The curve is a model, not a lab result. It uses a daily-use steady-state anchor, then estimates first-order cotinine decay after quitting.
Detection thresholds, and what they are trying to separate
A cotinine "positive" is not a universal state. The cutoff is chosen for a purpose: sensitive exposure screening, active-use classification, insurance-style smoking verification, or clinical follow-up.
Cotinine is the metabolite most nicotine tests lean on because nicotine itself disappears quickly1. Lower urine cutoffs can catch light or passive exposure; higher cutoffs are less sensitive but better aligned with active smoking classification34.
What the curve is actually telling you
Cotinine is a metabolite, not nicotine.
Nicotine clears fast. Cotinine lasts longer, so urine testing often uses cotinine as the practical marker of nicotine exposure1.
That is why the chart starts at the quit time. It estimates the cotinine already present at that point from a daily-use steady-state anchor, then lets it decay by half-life.
Days matter more than hours.
A 16 h half-life means the curve moves slowly. Many daily users fall below a 200 ng/mL active-use cutoff in a few days, while lower cutoffs can stay relevant longer depending on starting concentration and metabolism25.
Secondhand exposure is a low-cutoff problem.
Very sensitive cutoffs can detect low-level environmental exposure. That does not mean every low positive proves active smoking; it means the cutoff was chosen to be sensitive3.
Why this is not a test result
Real specimens vary by urine concentration, timing, product type, nicotine yield, inhalation, pregnancy, CYP2A6 metabolism, and lab method. This model teaches the shape of cotinine clearance; it does not predict a legal, medical, insurance, workplace, or forensic outcome.
How the model works
The calculator is intentionally small: a cited set of assumptions feeds one pharmacokinetic model, and the chart renders that result. These are the assumptions currently active in the curve above.