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What are the absolute risk reductions and number-needed-to-treat for mortality reported in the 2019 statin meta-analysis?

Checked on November 19, 2025
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Executive summary

The 2019 large individual-participant meta-analysis (CTT Collaboration) reported relative benefits of statins on vascular outcomes and implied reductions in mortality, but the provided search results do not include that paper’s explicit absolute risk reductions (ARR) or number-needed-to-treat (NNT) figures. The Lancet 2019 summary of 28 trials describes proportional effects (e.g., consistent proportional reduction in vascular mortality per mmol/L LDL lowering) and warns the absolute risks in the trial populations "are not likely to be representative of any contemporary population" [1].

1. What the 2019 CTT meta-analysis actually reported — proportional effects, not ready-made NNTs

The 2019 meta-analysis published in The Lancet (the CTT Collaboration pooling individual participant data from 28 randomized trials) focused on proportional (relative) reductions in major vascular events and vascular mortality per 1.0 mmol/L LDL-cholesterol reduction rather than publishing single, universal absolute risk reductions or NNTs that apply to all patients; the paper emphasizes relative effects and heterogeneity of baseline absolute risk across populations [1].

2. Why absolute risk reduction (ARR) and NNT depend on baseline risk

ARR = baseline event rate × relative risk reduction. Because the CTT authors pooled diverse trials with different baseline risks and follow‑up durations, they explicitly caution that "the absolute risk of major vascular events and mortality in our overall study population is not likely to be representative of any contemporary population" — a direct warning that converting relative reductions into a single ARR/NNT for "all patients" would be misleading [1].

3. What related meta-analyses did report that can help estimate ARR/NNT

Other meta-analyses in the search set report relative reductions and some alternative metrics: older trial meta-analyses found all‑cause mortality reduced by about 15% (relative) in pooled RCTs (10 trials, 79,494 subjects) [2], and a BMJ Open follow‑up meta‑analysis found post‑trial all‑cause death hazard ratio of ~0.90 in primary prevention trials [3]. A different 2019 analysis used "postponement of death" and estimated an average gain of ~12.6 days of life in trials’ durations (meta of 16 trials) instead of NNT [4]. These are relative or alternative outcome measures, not direct ARR/NNT values [2] [3] [4].

4. How you can compute ARR and NNT from CTT-like results (method and caveats)

To derive an ARR or NNT from the CTT relative effect you need: (A) the baseline absolute risk (event or mortality rate) over the same follow‑up period in your target population; (B) the relative risk reduction reported by the meta‑analysis. Then ARR = baseline risk × (1 − RR). NNT = 1 / ARR. The Lancet paper’s warning that trial baseline risks differ from contemporary populations means any computed NNT will be conditional on the chosen baseline risk and follow‑up time [1].

5. Example using numbers from related pooled RCTs — illustrative, not from CTT text

If you take the earlier pooled RCT meta‑analysis that reported ~15% relative reduction in all‑cause mortality [2] as a working RR and assume a hypothetical baseline 5‑year mortality of 5%, ARR = 5% × 0.15 = 0.75 percentage points, so NNT ≈ 133 over that period. This is an illustrative calculation: it uses a relative reduction reported in a different pooled analysis and an assumed baseline risk — neither figure is the single ARR/NNT published in the 2019 CTT paper [2] [1].

6. Alternative metrics reported instead of NNT: postponement of death and legacy effects

The 2019 Journal of General Internal Medicine meta‑analysis modeled "postponement of death" and pooled trials to estimate an average postponement of ~12.6 days of all‑cause mortality within trials’ durations — a patient‑centric measure offered as an alternative to NNT [4]. BMJ Open’s "legacy effects" meta‑analysis also reported hazard ratios for post‑trial mortality (e.g., HR ~0.90 for all‑cause death in primary prevention) rather than simple NNTs [3].

7. Bottom line and recommendation for a precise NNT

Available sources do not provide a single, definitive ARR or NNT for mortality "reported in the 2019 statin meta‑analysis" — The Lancet CTT paper reports proportional effects and explicitly cautions about applicability of absolute risks across populations [1]. If you want a concrete NNT for a specific patient group, pick the target baseline event/mortality risk and follow‑up period, then apply the CTT or another pooled RR to compute ARR and NNT, remembering the CTT authors’ warning that absolute rates vary by population [1] [2].

If you’d like, tell me a target population (age, primary vs secondary prevention, expected baseline 5‑year mortality) and I will compute an illustrative ARR and NNT using the reported relative reductions from these pooled analyses and note the assumptions and limitations [1] [2].

Want to dive deeper?
What were the relative risk reductions for mortality in the 2019 statin meta-analysis and how do they compare to absolute risk reductions?
Which patient subgroups (primary vs secondary prevention) showed the largest absolute mortality benefit in the 2019 statin meta-analysis?
How were absolute risk reductions and NNT for mortality calculated in the 2019 statin meta-analysis (follow-up time, baseline risk assumptions)?
How do the 2019 statin meta-analysis NNTs for mortality compare to earlier meta-analyses or large RCTs like HPS and JUPITER?
What are the implications of the 2019 statin meta-analysis absolute benefits for shared decision-making and guideline recommendations?