Two separable questions sit under the lipid lever, and two sources answer them. How much does lowering buy — the per-unit magnitude of event reduction (CTT 2010, the IPD meta-analysis of 26 statin RCTs). And which number to target — the metric that carries the causal signal (Marston 2022, apoB over LDL-C in ~430,000 people). This page holds the magnitude and the metric; the causal model underneath (why LDL/apoB causes disease, why the dose is cumulative) is the nucleus LDL ApoB and Cumulative Exposure. Structural sibling to Blood Pressure Lowering and Cardiovascular Events on the other big cardiometabolic lever.
The magnitude — CTT per 1.0 mmol/L LDL-C reduction
CTT scales every trial by the LDL-C reduction achieved at 1 year and reports the effect per 1.0 mmol/L (169,138 participants, 26 trials, median ~5 y):
| Outcome (per 1.0 mmol/L LDL-C reduction) | Effect |
|---|---|
| Major vascular events | RR 0.78 (95% CI 0.76-0.80) |
| All-cause mortality | RR 0.90 (0.87-0.93) |
| Coronary death | RR 0.80 |
| Non-fatal MI | RR 0.73 (-27%) |
| Coronary revascularisation | RR 0.75 (-25%) |
| Ischaemic stroke | RR 0.79 (-21%); any stroke -16% |
| Cancer incidence / non-vascular death | RR 1.00 / 0.97 (null) |
«similar proportional reductions in major vascular events per 1·0 mmol/L LDL cholesterol reduction were found in all types of patient studied (rate ratio [RR] 0·78, 95% CI 0·76-0·80; p<0·0001), including those with LDL cholesterol lower than 2 mmol/L» (Cholesterol Treatment Trialists’ Collaboration, 2010)
«all-cause mortality was reduced by 10% per 1·0 mmol/L LDL reduction (RR 0·90, 95% CI 0·87-0·93; p<0·0001)» (Cholesterol Treatment Trialists’ Collaboration, 2010)
Mortality moved, not just the marker. Unlike most of the surrogate cases the wiki holds, the LDL-C reduction transmitted all the way to all-cause death in randomised evidence — the validated-surrogate direction, and a worked instance of Surrogate Outcomes’s counter-exemplar. And with no excess cancer or non-vascular mortality even at low LDL, which retires the old low-cholesterol-harm hypothesis for the drug-lowered range.
The shape — monotone, no threshold, multiplicative
- No knee, no plateau in the studied range. «There was no evidence of any threshold within the cholesterol range studied» (Cholesterol Treatment Trialists’ Collaboration, 2010). Benefit persisted starting below 2.0 mmol/L (RR 0.71, -29%) and «even among those reaching 1·8 mmol/L (70 mg/dL) or lower» further reduction still produced definite benefit (RR 0.63, 99% CI 0.41-0.95) (Cholesterol Treatment Trialists’ Collaboration, 2010). The RR per mmol «did not depend on the baseline LDL cholesterol concentration (trend p=0·2)».
- The reduction compounds multiplicatively: «a 2 mmol/L reduction would reduce the risk by about 40% (since the combination of risk ratios of 0·78×0·78 yields a risk ratio of about 0·6)» (Cholesterol Treatment Trialists’ Collaboration, 2010). This is the per-unit face of the nucleus’s cumulative-exposure thesis: successive mmol multiply, so more and longer both pay -> LDL ApoB and Cumulative Exposure.
- A clean confirmation of the corpus’s operative dose-response default — every reduction pays; the burden is on anyone claiming a knee to locate it. The persistence of benefit at low LDL also means there is no protective lower arm (no harm from low LDL in the drug-lowered range), the interventional parallel to The U-Shaped Association Artifact.
The metric — Marston: target apoB particle number, not cholesterol content or particle type
CTT scales by LDL-C because that is what the statin trials measured. Marston asks whether LDL-C is even the right number to carry the risk. In UK Biobank (n=389,529, untreated) plus two statin RCTs (FOURIER, IMPROVE-IT; n=40,430), each lipid is entered simultaneously:
- apoB, non-HDL-C and TG each predict MI alone, but only apoB survives mutual adjustment — «when assessed together, only apoB was associated (adjusted hazard ratio [aHR] per 1 SD, 1.27; 95% CI, 1.15-1.40; P < .001). Similarly, only apoB was associated with MI in the secondary prevention cohort.» (Marston et al., 2022). Non-HDL-C fell to aHR 1.09 (NS) and TG to 1.00 (NS) once apoB was held constant.
- Particle TYPE stops mattering once particle NUMBER is fixed — adjusting for apoB, the TG/LDL-C ratio (a proxy for TG-rich vs LDL particles) was flat (aHR 1.04, 0.99-1.09, P=.12): «for a given concentration of apoB-containing lipoproteins, the relative proportions of particle subpopulations may no longer be a predictor of risk» (Marston et al., 2022).
- Verdict: «risk of MI was best captured by the number of apoB-containing lipoproteins, independent from lipid content (cholesterol or TG) or type of lipoprotein (LDL or TG-rich)» (Marston et al., 2022). Where apoB is unavailable, «non-HDL-C in particular is the preferred surrogate for apoB, as it incorporates TG-rich lipoproteins in addition to LDL» — LDL-C is the weakest of the three because it misses the remnant particles.
The genetic version of the same answer — Richardson MVMR [2026-08-06]. Marston’s apoB-supremacy is
observational; multivariable Mendelian randomisation reaches it as a natural experiment. Instrumenting
LDL-C, TG and apoB from a UK Biobank GWAS (up to 441,016) against CARDIoGRAMplusC4D (60,801 CHD cases):
each is atherogenic alone, but entered together “only apolipoprotein B … retained a robust effect, with
the estimate for LDL cholesterol … reversing” — apoB OR 1.92 (1.31-2.81), LDL-C 0.85 (0.57-1.27, P=0.44),
TG weakened. (Richardson et al., 2020) So the metric
verdict (target apoB, not LDL-C content) is now backed by RCT-scaling (CTT), observational multivariable
(Marston), and genetic multivariable MR (Richardson) alike. Note: this does not discredit LDL-C’s
causal role — apoB is necessary and always accompanies cholesterol; a cholesterol change concordant with
apoB still moves risk (which is why CTT’s LDL-C scaling works for statins). Causal model + the
not-independent caveat: LDL ApoB and Cumulative Exposure.
CONTESTED — the particle-number-not-content leg (Helgadottir 2022). Marston’s verdict is that risk is best captured «independent from lipid content (cholesterol or TG)» (Marston et al., 2022) — i.e. count, not content. An independent MR (deCODE/Danish; no Ference/Ala-Korpela/Marston authors) that separates apoB from non-HDL-C with 82/235 discordant variants reaches the opposite: «the genetic effects on CAD risk are proportional to effects on non-HDL-C, but not to effects on apoB» (Helgadottir et al., 2022), attributing the observational apoB signal to confounding of two ~0.9-correlated traits. This leaves the apoB-over-LDL-C metric verdict intact (both agree) but contests whether the right secondary target is apoB (particle number) or non-HDL-C (cholesterol content, already on every panel) -> full joined issue: ApoB Particle Number vs Cholesterol Content. Held contested, not resolved (one MR vs Marston + the number-camp lineage).
Synthesis — the two answers reconcile; they do not clash
(inferred from Cholesterol Treatment Trialists’ Collaboration, 2010; Marston et al., 2022)
A naive reading pits them against each other: CTT scales the entire causal magnitude by LDL-C, while Marston finds LDL-C carries no independent signal beyond apoB. The parameter table shows why this is a distinction, not a tension (not-joined check (ii): different quantity, different question):
| Parameter | CTT 2010 | Marston 2022 | Same quantity? |
|---|---|---|---|
| Design | RCT IPD meta-analysis | prospective cohort (+ cited Mendelian randomization) | No |
| Estimand | causal effect of lowering LDL-C (treatment contrast) | baseline risk discrimination among correlated lipids | No |
| Lipid unit | achieved LDL-C reduction (mmol/L) | 1-SD of each lipid, mutually adjusted | No |
| What “LDL-C” does | the scaling proxy | drops to NS after apoB adjustment | — |
CTT’s LDL-C-scaled magnitude and Marston’s apoB-supremacy are compatible because LDL-C and apoB are tightly correlated in the general untreated population — ρ >= 0.95 in Marston’s untreated primary-prevention cohort (Marston et al., 2022) — and a statin lowers both. So for the concordant majority, CTT’s «per 1.0 mmol/L LDL-C» is a stand-in for the apoB-particle reduction it accompanies — the causal quantity Marston identifies and the nucleus names. The decision-relevant seam, with its proviso made explicit:
- The equivalence is strongest where the lipids concord, and that is NOT the treated/impaired case. Statin treatment and the discordant metabolic states (metabolic syndrome, diabetes, hypertriglyceridemia — small-dense-LDL) drive LDL-C and apoB apart, and Marston found apoB supreme even in its statin-treated secondary cohort. So CTT’s ρ>=0.95-backed LDL-C proxy holds for the concordant, general-population case and weakens exactly where lipid-lowering or metabolic impairment has begun — the reason to read the particle number, not the cholesterol, once treatment or discordance is in play -> LDL ApoB and Cumulative Exposure.
- Use apoB (or non-HDL-C) to decide and monitor; expect roughly CTT’s magnitude per equivalent apoB reduction (exactly in the concordant; approximately when read off LDL-C, under-counting where they discord). The two sources answer which number and how much, and only together give the whole decision.
Independence note: not a type-E robustness convergence. Ference (nucleus) co-authors both Marston and
Richardson, and CTT is the RCT evidence family the nucleus’s consensus already rests on — one research
programme across all three. The value here is A/F (magnitude × metric assembled into one decision structure;
Marston refines what CTT’s LDL-C scaling is; Richardson adds the genetic-MR leg), not independent
triangulation — so none of the three is tagged [E-independent].
Decision relevance
- The relative effect is large and monotone; the absolute benefit still scales with baseline risk. A ~22% RRR per mmol is a small absolute gain in a low-risk person and a large one in a high-risk person — the same treat-on-absolute-risk logic as the BP lever (Baseline Risk and the Relative-Absolute Split, Statins for Primary Prevention and the Power of Zero CAC). CTT’s constant RR across every baseline stratum is what licenses stratifying on baseline risk without any subgroup claim (route a).
- Lower and longer both pay (no threshold, multiplicative) — but “worth it” is a net-effect call: the rhabdomyolysis excess (4 vs 1 per 10,000) was confined to 80 mg simvastatin, and the whole-strategy trade-off, not the LDL number, is the unit of decision.
- Drug route only. CTT is statin-lowering; the magnitude does not transfer to a dietary LDL-C change (the MCE/Sydney disconnects -> Surrogate Outcomes, Linoleic Acid and Cardiovascular Disease).
A dietary LDL lever, and why its magnitude does not inherit CTT [2026-08-29, Landry]
Landry’s 2024 umbrella quantifies one dietary LDL route: in 31 observational studies (Benatar), «vegan dietary patterns may be associated with significantly lower LDL-cholesterol concentrations of −0.49 mmol/l (−0.62, −0.36) (p < 0.0001) compared to omnivorous diets, though heterogeneity was high (I2=92 %)» (Landry et al., 2024). Two guards stop this being read as a ~11% event reduction off CTT’s 0.78/mmol:
- Observational and healthy-adherer confounded, GRADE low — and the randomised evidence in presumably-healthy adults found no significant effect: vegetarian+vegan combined LDL «−0.13 mmol/l (−0.37, 0.12)» (4 RCTs, NS) (Landry et al., 2024). So the −0.49 is the confounded observational estimate, not a trial effect.
- By this page’s own drug-route-only rule, a dietary LDL change does not transmit to events at CTT’s statin-derived rate (the MCE/Sydney disconnects). A modest, uncertain dietary apoB/LDL lever — cross-linked from Vegetarian Dietary Patterns and Mortality, where it is one of several small pleiotropic channels — not a statin-magnitude one. (inferred from Landry et al., 2024)
The treat-to-target number — the two guidance families converge, but the NUMBER is not the DIRECTION [2026-08-06]
CTT gives the magnitude per unit; the guidelines translate it into a level to treat to. The decision-relevant fact for 2026 is that the two major families now converge on the most aggressive target, and that convergence must be read correctly: it raises the guidance null for direction, not for the specific number.
The very-high-risk secondary-prevention target is the same in both families.
| Parameter | ESC-EAS (2019, reaffirmed 2025) | ACC-AHA 2026 | Same quantity? |
|---|---|---|---|
| Very-high-risk LDL-C goal | <1.4 mmol/L (55 mg/dL) + ≥50% reduction | «a goal of LDL-C <55 mg/dL (1.4 mmol/L)» + ≥50% reduction | Yes |
| High-risk / primary-high goal | <1.8 mmol/L (70 mg/dL) | «goal of LDL-C <70 mg/dL (1.8 mmol/L)» | Yes |
| non-HDL-C secondary goal | — (not set in the 2025 text) | <85 mg/dL (2.2 mmol/L) | ACC-only |
(Blumenthal et al., 2026) — ESC-EAS 2025 states «the LDL-C treatment goals … for persons in each risk category have not changed from the 2019 ESC/EAS Guidelines» (Mach et al., 2025); the ESC numeric figure itself lives in that update’s Fig. 1 (not in the OCR’d text — do not source the numbers to the 2025 document; they are the reaffirmed 2019 targets).
The delta that makes this a finding: ACC-AHA restored numeric goals. The 2018 US guideline had abandoned treat-to-target; 2026 puts it back — «LDL-C and non-HDL-C treatment goals are back to guide LLT» (Blumenthal et al., 2026) — and lands on the ESC numbers. So the US and European families, which diverged on whether to name a target for a decade, now agree on the target itself.
But this is shared-source agreement, and the two families are not two separate witnesses. Both rest on
the same trial base — CTT for the per-mmol magnitude (ESC states it as its «average 20 % proportional
… reduction … per each mmol/L» (Mach et al., 2025); the
ACC document rests on CTT 2010 throughout) plus FOURIER/ODYSSEY/IMPROVE-IT/CLEAR. Two guideline committees
reading the same trials to the same number is convergence of shared warrant, not a second route — so this
carries no [E-independent] weight.
The load-bearing honesty — the DIRECTION is evidenced, the specific NUMBER is a reasoned extrapolation. A target is legitimate only if its transmission to a patient-important outcome is itself evidenced. Here:
- Direction (lower LDL/apoB → fewer events, monotone, no threshold) is high-certainty — CTT’s «no evidence of any threshold», benefit persisting «even among those reaching 1·8 mmol/L (70 mg/dL) or lower», and the concordant genetic MR (Richardson). The guidelines’ own claim that the per-unit benefit is mechanism-agnostic is the same view: «similar reductions in the risk of CVD as statins … per unit decrease in LDL-C» (Mach et al., 2025).
- The specific cut (why <55 and not <50 or <70) has no head-to-head trial. No RCT randomized patients to target <55 vs <70 mmol/L; the numbers are derived from achieved-LDL strata in the outcome trials and the monotone curve, extrapolated to a round threshold. Under a monotone no-threshold curve a target is a pragmatic stopping point, not an evidenced optimum — reducing past it merely keeps paying (or stops being worth the added agent/cost/adherence burden), which is a net-effect judgment, not a measured knee. So the convergence licenses «lower, for the high-risk» with confidence; it does not certify 1.4 mmol/L as the right number.
(inferred from Blumenthal et al., 2026; Cholesterol Treatment Trialists’ Collaboration, 2010; Mach et al., 2025)
Limits
- CTT magnitude is a ~5-year per-mmol effect from drug trials; the lifetime cumulative effect is larger by the nucleus’s own logic but is modelled, not measured here.
- Marston is observational (with cited MR) and shares lineage with the nucleus’s consensus — large and consistent, but not independent of it; measured on conventional panels, not NMR; not enriched for severe hypertriglyceridemia.
- The guidelines are WHAT-TO-DO documents; their effect claims are borrowed. ACC-AHA and ESC-EAS are named here for the recommendation (the target, the escalation), never as evidence of the magnitude — the magnitude is CTT’s/Marston’s, which the guidelines themselves rest on (ACC-AHA even reproduces Marston’s aHR 1.27). A guideline’s restatement of CTT is not a second confirming study.
- The open loop stands: no operation here grades either against a realized patient outcome.