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Reading Risk Numbers (NNT)
"Cuts your risk by 50%" is a true sentence and a useless one. Halving a 20% risk is one of the biggest favours medicine can do you; halving a 0.2% risk is theatre, and the headline reads identically in both cases. The number that tells them apart is the number-needed-to-treat: how many people take the pill for one to actually benefit. It's free, it fits on a napkin, and once it's in your head every drug ad and screening pitch reads differently.
იცოდე მტკიცებულება ზომიერი თავი ჯანდაცვა

Any trial gives you three numbers. The relative one is the headline: a drug that takes heart-attack rate from 20 in 100 down to 15 cuts risk "by a quarter," ignoring the underlying rate. The absolute one is the real drop, 20% to 15%, five percentage points. Run that same quarter-reduction where only 2 in 100 were at risk and you get half a point. Same drug, same biology, different decision.

The number-needed-to-treat (NNT) is that absolute drop flipped over: five points means 1 in 20 treated people avoided the event, half a point means 1 in 200 1.

This isn't niche. Across 35 studies, most patients overshot the benefit of statins, mammograms, colonoscopies, and blood-pressure drugs by tenfold or more, and undershot the side effects 2. The relative number is why: a result feels bigger shown as a relative reduction than as an absolute one or an NNT, and printing both together doesn't fix it 3.

Anchors: a statin after a heart attack, 1 in 30 avoid an early death over five years 4; the same drug in low-risk people, about 1 in 95 5; an SSRI for real depression, 1 in 7 6. Same statin, NNT 30 to 95, purely from who's taking it.

Any treatment claim gets the same three questions — a drug ad, a screening letter, a prescription your doctor floats.

With a clinician it collapses to one sentence: "What's my absolute chance of this outcome over the next few years if I do nothing, and how much does this change it?" It's a question they're trained to answer and one nobody asks; handing patients the real numbers lowers regret without raising anxiety 7. thennt.com lists published NNTs and NNHs for a figure first.

The cost lands at both ends. Some swallow a daily pill for years whose real benefit they'd have declined if they'd seen it. Others hear "statins cut risk by 25%," shrug, and walk away from a one-in-thirty lifesaver for them specifically 4. The actual number tells you how much to care.

The fine print — when to skip it, and what people get wrong

"50% reduction means half of us benefit." No — it means the treated group's event rate is half the untreated group's; often 1 in 100 gains. "The headline applies to me." NNT says 1 in N benefit, not which one.

NNT is a summary, not a verdict. A huge NNT can still be a yes when the outcome is catastrophic and the fix cheap. It hides subgroups, so use stratified figures where given, and don't multiply it across untested horizons.

References
  1. 1Laupacis A, Sackett DL, Roberts RS (1988). An assessment of clinically useful measures of the consequences of treatment. New England Journal of Medicine. link
  2. 2Hoffmann TC, Del Mar C (2015). Patients' expectations of the benefits and harms of treatments, screening, and tests: a systematic review. JAMA Internal Medicine. link
  3. 3Akl EA, Oxman AD, Herrin J, et al. (2011). Using alternative statistical formats for presenting risks and risk reductions. Cochrane Database of Systematic Reviews. link
  4. 4Scandinavian Simvastatin Survival Study Group (1994). Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). The Lancet. link
  5. 5Ridker PM, Danielson E, Fonseca FA, et al. (2008). Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. New England Journal of Medicine. link
  6. 6Cipriani A, Furukawa TA, Salanti G, et al. (2018). Comparative efficacy and acceptability of 21 antidepressant drugs for the acute treatment of adults with major depressive disorder: a systematic review and network meta-analysis. The Lancet. link
  7. 7Stacey D, Légaré F, Lewis K, et al. (2017). Decision aids for people facing health treatment or screening decisions. Cochrane Database of Systematic Reviews. link
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