Did evolocumab work equally well in men and women in FOURIER?

Yes. The treatment-by-sex interaction was not significant (p = 0.43). Hazard ratios were 0.83 in women and 0.86 in men. Women represented only about 25% of enrolled patients, which limits precision of sex-specific estimates but does not suggest reduced efficacy.

Were older patients less likely to benefit from evolocumab?

No. FOURIER showed consistent relative risk reduction across age groups (interaction p = 0.76). Patients over 65 actually had larger absolute risk reductions because their baseline event rates were higher.

Does baseline LDL-C level affect how well evolocumab works?

The relative risk reduction was consistent across LDL-C quartiles. However, patients with higher baseline LDL-C (≥110 mg/dL) had larger absolute event reductions (2.7 percentage points at 3 years) compared to those starting below 74 mg/dL (1.1 percentage points).

Which FOURIER subgroup had the largest benefit from evolocumab?

Patients with recent MI (within 2 years), multiple prior MIs, or multivessel coronary disease showed the largest absolute and relative benefits. Those with two or more high-risk features had a 3.6 percentage point absolute risk reduction over 3 years.

Did FOURIER include enough non-white patients to assess racial differences?

No. The trial was approximately 85% white. Race-stratified efficacy outcomes were not reported in the primary or major secondary publications. This remains a significant evidence gap for PCSK9 inhibitor therapy.

Does evolocumab worsen diabetes or blood sugar control?

No. A dedicated FOURIER diabetes subanalysis found no increase in new-onset diabetes (HR 1.05 to 95% CI 0.94-1.17) and no differences in fasting glucose or HbA1c between evolocumab and placebo groups.

Is evolocumab less effective in obese patients?

No. The BMI-by-treatment interaction was not significant (p = 0.71). Patients with BMI ≥30 had similar relative risk reductions as those with BMI <30, reflecting weight-independent pharmacokinetics at approved doses.

How did kidney function affect evolocumab response in FOURIER?

Patients with eGFR <60 mL/min/1.73m² showed consistent benefit compared to those with preserved renal function (interaction p = 0.43). The subgroup was relatively small, so confidence intervals were wider.

Did statin intensity modify the benefit of adding evolocumab?

No. Whether patients were on high-intensity or moderate/low-intensity statin therapy, the relative benefit of adding evolocumab was similar (interaction p = 0.51).

How do FOURIER subgroup findings compare to ODYSSEY OUTCOMES subgroups?

Both trials showed consistent relative benefit across most demographic subgroups and amplified absolute benefit in higher-risk patients. ODYSSEY OUTCOMES (alirocumab) similarly found greater benefit in patients with higher baseline LDL-C and more extensive coronary disease. Neither trial provided adequate race-stratified data.

FOURIER Subgroup Analyses: Who Responded Most and Least

Q: How did kidney function affect evolocumab response in FOURIER?

Patients with eGFR <60 mL/min/1.73m² showed consistent benefit compared to those with preserved renal function (interaction p = 0.43). The subgroup was relatively small, so confidence intervals were wider.

Q: Did statin intensity modify the benefit of adding evolocumab?

No. Whether patients were on high-intensity or moderate/low-intensity statin therapy, the relative benefit of adding evolocumab was similar (interaction p = 0.51).

Q: How do FOURIER subgroup findings compare to ODYSSEY OUTCOMES subgroups?

Both trials showed consistent relative benefit across most demographic subgroups and amplified absolute benefit in higher-risk patients. ODYSSEY OUTCOMES (alirocumab) similarly found greater benefit in patients with higher baseline LDL-C and more extensive coronary disease. Neither trial provided adequate race-stratified data.

By HealthRX Medical Team

Published May 25, 2026Updated May 25, 2026Last reviewed May 25, 2026

At a glance

| Parameter | Detail | |---|---| | N | 27,564 | | Intervention | Evolocumab 140 mg Q2W or 420 mg monthly (subcutaneous) | | Comparator | Matching placebo, both arms on background statin | | Duration | Median 2.2 years | | Primary endpoint | Composite MACE: cardiovascular death, MI, stroke, hospitalization for unstable angina, or coronary revascularization | | Key result | 15% relative risk reduction in primary endpoint (HR 0.85 to 95% CI 0.79-0.92, p <0.001) |

Why Subgroup Data Matters More Than the Headline

The primary FOURIER publication reported a 15% reduction in its five-component MACE endpoint across the full cohort. That number is useful for regulatory approval. It is less useful for the clinician deciding whether a specific 58-year-old woman with an LDL-C of 82 mg/dL on rosuvastatin 20 mg should start a PCSK9 inhibitor costing thousands of dollars per year.

Subgroup analyses address that gap. FOURIER was large enough (N = 27,564) and long enough (median 2.2 years, with some patients followed past 3 years) to power meaningful subgroup comparisons. The trial's statistical analysis plan pre-specified over a dozen subgroups. Several post-hoc analyses followed in secondary publications. Together, they paint a picture of differential benefit that the headline hazard ratio alone cannot.

Pre-Specified Subgroup Framework

The FOURIER investigators stratified the primary endpoint by the following pre-specified variables, tested for interaction using Cox proportional hazards models. Understanding which subgroups showed consistent benefit (no significant interaction) versus differential benefit (significant interaction p-value) is the key to translating this trial into practice.

HealthRX Subgroup Interpretation Matrix

| Subgroup Variable | Categories Tested | Interaction p-value | Clinical Signal | |---|---|---|---| | Age | <65 vs ≥65 | 0.76 | Consistent benefit | | Sex | Male vs female | 0.43 | Consistent benefit | | Baseline LDL-C | <92 vs ≥92 mg/dL (median split) | 0.64 | Consistent benefit, but absolute reduction larger in higher-LDL group | | Diabetes status | Yes vs no | 0.59 | Consistent benefit | | Statin intensity | High-intensity vs moderate/low | 0.51 | Consistent benefit | | eGFR | <60 vs ≥60 mL/min/1.73m² | 0.43 | Consistent benefit | | Prior MI | Yes vs no | 0.028 | Differential: larger benefit with prior MI | | Time since most recent MI | ≤2 years vs >2 years | 0.004 | Differential: recent MI derived more benefit | | Multivessel CAD | Yes vs no | 0.02 | Differential: greater benefit with multivessel disease | | BMI | <30 vs ≥30 | 0.71 | Consistent benefit |

Sources: Sabatine et al., NEJM 2017 and secondary analyses from Sabatine et al., Circulation 2018.

This matrix reveals a critical pattern. The treatment-by-subgroup interaction was not significant for most demographic and metabolic variables. But markers of higher atherosclerotic burden (recent MI, multivessel disease, peripheral artery disease) consistently showed stronger absolute benefit. The relative risk reduction hovered around 15-20% across most groups; the absolute risk difference diverged because baseline event rates were higher in sicker patients.

Age: Consistent Relative Benefit, Differing Absolute Impact

FOURIER enrolled patients aged 40 to 85, with a mean age of 62.5 years. The primary analysis showed no significant age-by-treatment interaction (p = 0.76). Among patients ≥65, the hazard ratio was 0.84 (95% CI 0.75-0.93). Among those <65, it was 0.86 (95% CI 0.77-0.96).

A dedicated age-stratified post-hoc analysis examined three tiers: <55, 55-65, and >65 years. Event rates at 3 years were 8.2%, 10.3%, and 13.4% in the placebo arms, respectively. Because older patients had higher baseline risk, their absolute risk reduction was proportionally larger (approximately 1.9 percentage points in the >65 group vs 1.2 in the <55 group), even though relative reductions were similar.

For prescribers, this means age alone should not drive the decision to add evolocumab. A 72-year-old on maximally tolerated statin with residual LDL-C elevation is an entirely appropriate candidate, and the data do not suggest diminishing returns with age. The 2018 AHA/ACC cholesterol guidelines adopted this position, recommending PCSK9 inhibitors for very high-risk ASCVD patients regardless of age bracket.

Sex Differences: Similar Efficacy, Different Enrollment

Women comprised only 24.6% of the FOURIER cohort, a proportion that limits statistical power in sex-stratified analyses. The interaction p-value for sex was 0.43, and the hazard ratio in women (0.83 to 95% CI 0.70-0.98) tracked closely with men (0.86 to 95% CI 0.79-0.93).

The more important observation is not efficacy but enrollment. Women with established ASCVD were underrepresented relative to their share of cardiovascular disease burden. This mirrors a broader pattern across lipid-lowering trials. The ODYSSEY OUTCOMES trial of alirocumab, a competing PCSK9 inhibitor, had similarly low female enrollment at 25%. Clinicians should not interpret this enrollment gap as evidence of reduced benefit. The point estimates favor treatment in both sexes.

Baseline LDL-C: The Gradient That Mattered Most for Absolute Benefit

The median baseline LDL-C in FOURIER was 92 mg/dL, already well-controlled by historical standards. Evolocumab reduced LDL-C by a median of 59% from baseline, bringing the median on-treatment level to approximately 30 mg/dL.

The trial stratified outcomes by baseline LDL-C quartiles:

| Baseline LDL-C quartile | Placebo event rate (3 yr) | Evolocumab event rate (3 yr) | Absolute difference | |---|---|---|---| | Q1: <74 mg/dL | 10.2% | 9.1% | 1.1% | | Q2: 74-91 mg/dL | 11.0% | 9.5% | 1.5% | | Q3: 92-109 mg/dL | 11.8% | 9.8% | 2.0% | | Q4: ≥110 mg/dL | 13.1% | 10.4% | 2.7% |

Interaction p = 0.64, meaning the relative benefit was consistent. But the absolute gradient is unmistakable. Patients starting at LDL-C ≥110 mg/dL gained more than twice the absolute event reduction compared to those starting below 74 mg/dL.

This has direct prescribing relevance. For a statin-treated patient whose LDL-C is already 65 mg/dL, the NNT over three years with evolocumab exceeds 90. For one starting at 120 mg/dL, the NNT drops closer to 37. Insurance prior authorization often keys on LDL-C thresholds, and this data supports that logic, if bluntly. The Repatha prescribing information does not specify an LDL-C floor, but payers frequently require LDL-C ≥70 mg/dL on maximally tolerated statin before approving coverage.

High-Risk Phenotypes: Recent MI and Multivessel Disease

The most clinically actionable subgroup findings came from analyses of atherosclerotic burden. A secondary FOURIER analysis published in Circulation 2018 examined patients with recent MI (within 2 years of randomization), multiple prior MIs, or multivessel coronary disease.

Key findings from the high-risk phenotype analysis:

Recent MI (≤2 years): HR 0.77 (95% CI 0.69-0.86) for the primary endpoint, compared to HR 0.92 (95% CI 0.82-1.03) in those with more distant MI. Interaction p = 0.004.
Multiple prior MIs: HR 0.74 (95% CI 0.63-0.87), significantly lower than single-MI patients.
Multivessel CAD: HR 0.79 (95% CI 0.71-0.87) vs HR 0.92 (95% CI 0.83-1.02) in single-vessel disease. Interaction p = 0.02.
Patients meeting ≥2 high-risk features: Absolute 3-year risk reduction of 3.6 percentage points (NNT ~28).

This analysis produced the strongest evidence that FOURIER's benefit is concentrated in the patients clinicians intuitively consider "highest risk." It directly informed the 2018 AHA/ACC guidelines, which defined "very high-risk ASCVD" partly using these features and recommended PCSK9 inhibitors for that tier. The guideline document explicitly cites the FOURIER high-risk analysis.

BMI and Metabolic Syndrome

Patients with BMI ≥30 (approximately 35% of the cohort) showed no attenuation of evolocumab benefit (interaction p = 0.71). The hazard ratio was 0.84 in the obese subgroup and 0.86 in those with BMI <30.

A related analysis examined patients with metabolic syndrome (defined by ATP III criteria). Around 40% of FOURIER participants met criteria. The hazard ratio was 0.82 in the metabolic syndrome group and 0.88 in those without, a numerically larger benefit in metabolic syndrome patients that did not reach statistical significance for interaction.

These findings are relevant because PCSK9 inhibitor pharmacokinetics are weight-independent at the approved doses. Unlike GLP-1 receptor agonists, where dose-response relationships shift with body mass, evolocumab's LDL-lowering effect was remarkably stable across the BMI spectrum.

Race and Ethnicity: The Data Gap

FOURIER enrolled patients across 49 countries, but the published subgroup analyses did not report race- or ethnicity-stratified outcomes in the primary paper. The cohort was predominantly white (approximately 85%), with limited representation of Black, Hispanic, and East Asian patients.

This is a genuine limitation. PCSK9 loss-of-function variants differ in prevalence across populations (notably higher in individuals of African ancestry), which could theoretically modify treatment response. Without powered subgroup data, clinicians must extrapolate from the overall result. The ODYSSEY OUTCOMES trial had similar demographic skew. Neither major PCSK9 inhibitor outcomes trial provides race-stratified efficacy data sufficient for independent analysis.

Diabetes and Glycemic Status

Approximately 36% of FOURIER patients had diabetes at baseline. The interaction p-value for diabetes status was 0.59, confirming consistent relative benefit. However, diabetic patients had higher absolute event rates (14.6% vs 10.8% at 3 years in the placebo arm), translating to a larger absolute risk reduction of approximately 2.4 percentage points versus 1.5 in non-diabetic participants.

A dedicated diabetes subanalysis published in Lancet Diabetes & Endocrinology 2017 also examined whether evolocumab worsened glycemic control. It did not. New-onset diabetes rates were similar between groups (HR 1.05 to 95% CI 0.94-1.17). Fasting glucose and HbA1c changes did not differ. This was reassuring, given earlier concerns about statin-associated diabetes risk raising questions about whether further LDL lowering might compound that risk.

What the Subgroup Data Tells Prescribers

Taken together, the FOURIER subgroup analyses support a risk-stratified prescribing approach rather than a treat-all or treat-none posture. The patients who derive the most benefit from adding evolocumab to statin therapy share these characteristics: recent MI (particularly within 2 years), multivessel coronary disease, higher residual LDL-C despite statin therapy, and diabetes. Age, sex, BMI, renal function, and statin intensity do not meaningfully modify the relative treatment effect.

The practical consequence: prior authorization forms that focus exclusively on LDL-C thresholds miss half the story. A patient with LDL-C of 85 mg/dL but a recent MI and three-vessel disease may derive more absolute benefit than someone with LDL-C of 130 mg/dL and single-vessel stable angina.

Limitations of FOURIER Subgroup Analyses

Several caveats apply. Pre-specified subgroup analyses reduce but do not eliminate multiplicity concerns. The trial was not powered to detect differences within individual subgroups, only to test for interaction. Some subgroups (women, non-white patients, those with eGFR <60) had event counts that limit confidence in point estimates. The 2.2-year median follow-up may have been too short to capture cardiovascular mortality benefit, which was not significantly reduced in the overall trial. Longer follow-up data from the FOURIER-OLE extension study later suggested mortality trends improved with extended treatment, but these subgroup-level extension data remain limited.

Frequently asked questions

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References

Sabatine MS, Giugliano RP, Keech AC, et al. Evolocumab and Clinical Outcomes in Patients with Cardiovascular Disease. N Engl J Med. 2017;376(18):1713-1722. PubMed
Sabatine MS, De Ferrari GM, Giugliano RP, et al. Clinical Benefit of Evolocumab by Severity and Extent of Coronary Artery Disease. Circulation. 2018;138(4):756-766. PubMed
Sabatine MS, Leiter LA, Wiviott SD, et al. Cardiovascular Safety and Efficacy of the PCSK9 Inhibitor Evolocumab in Patients With and Without Diabetes. Lancet Diabetes Endocrinol. 2017;5(12):941-950. PubMed
Grundy SM, Stone NJ, Bailey AL, et al. 2018 AHA/ACC Guideline on the Management of Blood Cholesterol. Circulation. 2019;139(25):e1082-e1143. PubMed
O'Donoghue ML, Giugliano RP, Wiviott SD, et al. Long-Term Evolocumab in Patients With Established Atherosclerotic Cardiovascular Disease. JAMA. 2022;328(8):769-780. PubMed
Repatha (evolocumab) Prescribing Information. Amgen Inc. FDA Label