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Number Needed to Treat (NNT) Calculator

Turn a trial's control and treatment event rates into NNT, NNH, absolute and relative risk reduction, and a 95% confidence interval — with the full working shown. Built for medical, nursing and pharmacy students appraising a randomised trial. No signup, sources cited.

By Induwara AshinsanaUpdated Jul 12, 2026
NNT & NNH calculatorAltman 95% CI
BMJ / CEBM method

Control group

The comparison / placebo arm.

Treatment group

The intervention arm.

“Events” are the bad outcome you are counting (death, MI, relapse…), not the number who improved.

Examples
Confidence
NNT = 10
95% CI: 7 to 18

On average, treat 10 patients to prevent 1 additional bad outcome.

Control rate (CER)
20%
Treatment rate (EER)
10%
Absolute risk reduction
10%
0.1 as a decimal
Relative risk (RR)
0.5
Relative risk reduction
50%
1 / ARR (unrounded)
10
Rounded up for the headline

Working shown

  1. CER = 0.2 EER = 0.1
  2. ARR = CER − EER = 0.2 − 0.1 = 0.1
  3. NNT = 1 / 0.1 = 10 → 10 (rounded up)
  4. RR = EER / CER = 0.1 / 0.2 = 0.5
  5. Cross-check via RR: 1 / (CER × (1 − RR)) = 10 → 10 ✓
  6. SE(ARR) = √[CER(1−CER)/n_c + EER(1−EER)/n_t] = 0.02
  7. 95% CI(ARR) = 0.1 ± 1.96·0.02 = (0.06, 0.14)
  8. NNT bounds = 1 / each ARR bound → 7 to 18 (both finite → significant)

Formulas: ARR/RR/RRR and NNT = 1/ARR (Cook & Sackett, BMJ 1995); confidence interval and the “spans infinity” convention (Altman, BMJ 1998); definitions cross-checked against the Oxford CEBM. Full links in the Sources section below. This tool handles a single 2×2 trial — not pooled meta-analysis or time-to-event NNT.

How it works

The calculator follows the standard evidence-based-medicine formulas published by the Oxford Centre for Evidence-Based Medicine (CEBM) and the two founding BMJ papers by Cook & Sackett (1995) and Altman (1998). Throughout, the counted “event” is the bad outcome — death, myocardial infarction, relapse and the like — not the number of patients who improved.

  1. Event rates. The control event rate is CER = control events ÷ control total; the experimental event rate is EER = treatment events ÷ treatment total. In Rates mode you enter these two percentages directly.
  2. Absolute risk reduction. ARR = CER − EER. This is the extra fraction of patients spared the bad outcome by the treatment.
  3. Number needed to treat. NNT = 1 / ARR, always rounded up to the next whole patient — you cannot treat a fraction of a person.
  4. Harm case. If EER exceeds CER the treatment increases the bad outcome. The tool then reports the number needed to harm, NNH = 1 / (EER − CER), and relabels the headline.
  5. Relative measures.Relative risk RR = EER / CER and relative risk reduction RRR = ARR / CER = 1 − RR. When CER is zero these are undefined and shown as “n/a”.
  6. Confidence interval (Altman 1998). The standard error of the ARR is SE = √[CER(1−CER)/n_c + EER(1−EER)/n_t]. The ARR interval is ARR ± z·SE, with z = 1.645, 1.96 or 2.576 for 90%, 95% or 99%. Inverting each ARR bound gives the NNT bounds.

When the ARR confidence interval crosses zero the treatment effect is not statistically significant: a true ARR of zero maps to an infinite NNT. Following Altman, the interval is then written across infinity — NNTB a to ∞ to NNTH b — because the data cannot rule out either benefit or harm. As an independent check, the tool also recomputes the NNT through the relative-risk route, 1 / (CER × (1 − RR)), and confirms it matches the 1/ARR result to the rounded patient.

Worked examples

1 — Statistically significant benefit

  1. Control 100/500 → CER = 0.20; Treatment 50/500 → EER = 0.10
  2. ARR = 0.20 − 0.10 = 0.10 → NNT = 1 / 0.10 = 10
  3. RR = 0.10 / 0.20 = 0.50; RRR = 50%
  4. SE = √(0.20·0.80/500 + 0.10·0.90/500) = 0.022361
  5. 95% CI(ARR) = 0.10 ± 1.96·0.022361 = (0.0562, 0.1438)
  6. NNT bounds = 1/0.1438 to 1/0.0562 = 6.95 to 17.80 → 7 to 18
  7. Result: NNT = 10 (95% CI 7 to 18), significant

2 — Not significant (spans infinity)

  1. Control 15/100 → CER = 0.15; Treatment 10/100 → EER = 0.10
  2. ARR = 0.05 → NNT = 20 (point estimate)
  3. SE = √(0.15·0.85/100 + 0.10·0.90/100) = 0.046637
  4. 95% CI(ARR) = 0.05 ± 1.96·0.046637 = (−0.0414, 0.1414) — crosses 0
  5. NNTB side 1/0.1414 = 7.07 → 8; NNTH side 1/0.0414 = 24.15 → 25
  6. Result: NNT = 20 (95% CI: NNTB 8 to ∞ to NNTH 25), not significant

3 — Net harm (NNH)

  1. Control 20/400 → CER = 0.05; Treatment 32/400 → EER = 0.08
  2. EER > CER → harm; ARI = 0.08 − 0.05 = 0.03
  3. NNH = 1 / 0.03 = 33.33 → 34 (rounded up)
  4. RR = 0.08 / 0.05 = 1.60; relative risk increase = 60%
  5. Result: NNH = 34 — treat 34 patients to cause 1 extra bad outcome

Frequently asked questions

Sources & references

The formulas on this page were last cross-checked against these sources on 2026-07-12. NNT is defined for binary (event / no-event) outcomes from a single randomised trial; continuous outcomes and pooled meta-analysis are out of scope.

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