Commentary on “HDL-C/LDL-C Ratio and All-Cause Mortality in Populations at High CVD Risk: A Prospective Observational Cohort Study”

Abstract

Lin and colleagues leveraged the 32,609-participant Fu-CARE cohort to report a U-shaped association between the high-density-lipoprotein-cholesterol/low-density-lipoprotein-cholesterol (HDL-C/LDL-C) ratio and all-cause mortality, with the lowest risk at 0.30–0.50 [1]. Their large sample and sex-specific restricted-cubic-spline modeling deserve praise, but several methodological issues temper causal inference and translational value.

Short follow-up and event scarcity: Median follow-up was 3.4 years (approx. 1100 deaths, 3.4% of the cohort). Cardiovascular epidemiology standards recommend ≥10 years to capture sufficient outcome variability and reduce reverse-causation from subclinical disease or frailty-related lipid changes [2]. Extending surveillance or performing landmark analyses that exclude deaths within the first 2 years could test the robustness of the U-shaped curve.

Single baseline lipid measurement: HDL-C and LDL-C vary with diet, medication, and intercurrent illness. Repeated measures or time-updated covariates would mitigate regression-dilution bias and clarify whether extreme ratio categories represent chronic dyslipidemia or transient fluctuations [3].

Residual confounding: Models adjusted for traditional factors but omitted socioeconomic status, alcohol quantity, dietary pattern, kidney function, inflammatory markers (high-sensitivity C-reactive protein, neutrophil-to-lymphocyte ratio), and medication classes (statins, SGLT-2 inhibitors, corticosteroids). Each independently influences both lipids and mortality [4-6]. Multiple-imputation and inverse-probability-weighted models incorporating these variables could diminish bias.

Data-driven categorization and lack of external validation: Cut points (0.30 and 0.50) were derived from the same spline used to test association, risking overfitting. Internal bootstrap optimism-corrected C-statistics, or, ideally, application to an external cohort such as CHARLS or UK Biobank, would gauge generalizability [7].

Limited clinical utility metrics: The authors reported hazard ratios but did not evaluate whether the ratio adds discrimination or net reclassification beyond LDL-C, HDL-C, and established risk scores (e.g., China-PAR). Decision-curve analysis could determine whether measuring HDL-C/LDL-C meaningfully improves risk stratification versus guideline-directed lipid panels [8].

Diabetes-specific findings require caution: The null association in participants with type 2 diabetes mellitus (T2DM) may reflect inadequate power (T2DM subgroup deaths, n = 250) or differential statin intensity. Stratified analyses by baseline lipid-lowering therapy and glycemic control (hemoglobin A1c) would clarify effect modification [9].

In summary, the Fu-CARE data hint that maintaining an HDL-C/LDL-C ratio between 0.30 and 0.50 may optimize survival in high-risk Chinese adults without T2DM. Still, short follow-up, single-time-point exposure assessment, and residual confounding preclude immediate clinical adoption. Future studies should incorporate repeated lipid measurements, richer socioeconomic and biochemical covariates, and external validation with decision-analytic metrics before recommending ratio-based targets in lipid management guidelines.

The authors declare no conflicts of interest.

Data sharing is not applicable to this article as no new data were created or analyzed in this study.