Keeping Clinical CKM Staging Distinct From Biological Enrichment

To the Editor:

We read with interest the review by Marshall et al.,¹ which reframes cardiovascular-kidney-metabolic (CKM) disease as an interconnected biological network and treats emerging biomarkers as complements rather than replacements for eGFR and albuminuria. Its pathway-based synthesis is timely as CKM care moves toward integrated risk assessment.

One point merits clarification because the review maps candidate biomarkers to American Heart Association CKM stages. Table 1 places heart failure and clinical atherosclerosis within stage 3 and lists kidney failure within the stage 4 definition. In the 2023 American Heart Association advisory, stage 3 denotes subclinical cardiovascular disease or risk equivalents, whereas stage 4 denotes clinical cardiovascular disease.² The 2026 multisociety guideline, published shortly after the review, makes this boundary explicit: pre-heart failure belongs to stage 3, clinical heart failure to stage 4, and kidney failure subdivides stage 4 rather than independently defining it.³ Clarifying Table 1 would help readers distinguish the consensus clinical staging framework from proposed biological enrichment.

That separation also matters for the suggested incorporation of metabolic dysfunction-associated steatotic liver disease (MASLD) as a stage 1 modifier. The biological rationale is persuasive, and the 2026 guideline now gives MASLD dedicated attention; however, it retains the standard CKM stages and emphasizes fibrosis-based risk assessment within MASLD.³ We suggest framing MASLD as a candidate modifier to be tested for incremental value—preferably with fibrosis-informed phenotyping—rather than as an established basis for CKM upstaging.

Figure 2 further links an elevated molecular signal to “high-risk” reclassification and earlier cardioprotective therapy. This is an attractive research pathway, but prognostic association does not establish that a biomarker predicts differential treatment benefit; this generally requires treatment-by-biomarker evidence, preferably from randomized data.⁴ Improved prediction also needs to translate into clinically useful decisions, not merely higher discrimination.⁵ This distinction does not diminish the review’s central vision. It places multiomics where the evidence is currently strongest: biological enrichment, trial stratification, and hypothesis generation, pending demonstration of net clinical benefit beyond guideline-based staging.

Disclosure

All the authors declared no competing interests.

Funding

No specific funding was received.

Data Availability Statement

No new data were generated or analyzed in this work.

Author Contributions

PY conceived the idea and drafted the manuscript. YW reviewed and revised the manuscript. Both authors approved the final version.

Declaration of AI and AI-Assisted Technologies in the Writing Process

Generative AI tools were used solely for language refinement and formatting assistance. All scientific interpretation and scholarly content were independently verified by the authors.