All-cause mortality

Overview

All-cause mortality is a clinical metric that refers to death from any cause during a specified follow-up period. Unlike cause-specific mortality, it does not require attribution of death to a particular disease, treatment complication, or external event. Because it captures total fatal risk, all-cause mortality is widely used as a primary endpoint, secondary endpoint, or composite endpoint component in clinical epidemiology, prognostic modeling, and comparative effectiveness research.

In biomedical research, all-cause mortality is valued for its objectivity and broad clinical relevance. It is commonly used to evaluate interventions and risk markers in conditions such as chronic kidney disease, type 2 diabetes, heart failure, cancer-related depression, dementia, sepsis, metabolic syndrome, and cardiovascular disease. It also serves as a robust outcome for studies of biomarkers, imaging-derived indices, DNA methylation-based aging measures, and machine learning prediction tools, including models built from NHANES data, TriNetX US collaborative network records, and other large cohorts.

Focus of Latest Publications

Recent studies have used all-cause mortality as a central endpoint across a wide range of diseases, populations, and analytic frameworks.

Several investigations focused on cardiorenal and metabolic disease. A retrospective cohort study of weight loss interventions in people with chronic kidney disease and type 2 diabetes evaluated cardiorenal outcomes and mortality. In adults with Crohn's disease and obesity, initiation of a glucagon-like peptide-1 receptor agonist was associated with lower mortality at 1 year. In diabetes-related research, all-cause mortality was examined in adults with type 2 diabetes and substance use disorders, in diabetic patients according to physical activity intensity, and in adults aged 16–50 years with and without type 2 diabetes in relation to body mass index. Other studies assessed mortality in relation to weight-adjusted waist circumference index, shrunken pore syndrome in type 1 diabetes, and stage-specific progression of cardiovascular-kidney-metabolic health. These reports collectively reflect the use of all-cause mortality as a broad outcome for cardiometabolic risk stratification, especially where obesity, abdominal obesity, glomerular filtration rate abnormalities, and CKM stages may influence long-term survival.

All-cause mortality was also prominent in renal and cardiovascular outcome studies. In end-stage kidney disease, target trial emulation of sodium glucose cotransporter 2 inhibitors used all-cause mortality as the primary outcome, and a similar design was applied to off-label apixaban dosing in heart failure with end-stage kidney disease. In peritoneal dialysis, mortality was studied in relation to the metabolic score for insulin resistance. In transcatheter aortic valve implantation and transcatheter versus surgical aortic valve replacement, all-cause mortality contributed to major adverse cardiovascular events or composite endpoints. In active cancer with acute myocardial infarction, dual antiplatelet therapy was evaluated with all-cause mortality at 1 and 5 years as the primary outcome. In transthyretin amyloid cardiomyopathy, it formed part of a composite endpoint with hospitalization. In Sjögren's disease, major adverse cardiovascular events were associated with higher all-cause mortality. In bullous pemphigoid, a nationwide Swedish cohort of 5,738 patients showed significantly higher all-cause mortality than controls. In heart failure, proteomics risk scores, anemia, performance status, and other clinical factors were studied for their association with mortality, and after heart failure onset in large B-cell lymphoma, patients had consistently higher all-cause mortality than comparators.

Mortality prediction was also a major theme in biomarker and machine learning studies. A study in older adults in Colombia addressed prediction of all-cause mortality using real-world evidence. Another study in pediatric ICU patients used comprehensive biochemical panels and machine learning-based models to predict all-cause mortality, explicitly addressing missing data and class imbalance. In COPD, systemic inflammatory indices were evaluated for mortality risk using machine learning. In liver disease, refined liver MRI-derived cT1 thresholds and a liver aging index were assessed for their ability to predict all-cause mortality, with the liver aging index showing strong discrimination. In aging research, pace of aging estimated from blood DNA methylation in the HUNT study was associated with all-cause mortality, and deep learning-based chest radiograph-derived age measures were linked to accelerated aging and increased all-cause mortality. These studies illustrate how all-cause mortality is used to validate prognostic biomarkers that capture biological aging, inflammation, organ dysfunction, and systemic risk.

All-cause mortality also served as an endpoint in infectious disease, critical care, and neurologic studies. In pediatric trauma patients admitted to intensive care, in-hospital mortality was the primary outcome. In sepsis, 28-day all-cause mortality was studied in ICU patients using plasma colloid osmotic pressure. In hospitalized patients with dementia, 90-day all-cause mortality was the primary endpoint in a study of Serum vitamin B12. In aspiration pneumonia among older adults with dementia, mortality was assessed alongside hospitalization and length of stay. In Parkinson's disease claims-based research, all-cause mortality was evaluated during follow-up. In influenza-related hospitalization, mortality was examined in a nationwide Brazilian cohort. In cancer-related depression, esketamine use was studied with all-cause mortality as the primary outcome. These studies show the metric’s utility in acute care, geriatric medicine, and neuropsychiatry.

The metric was also used in population health and comparative safety studies. In a multinational cohort of skin immune-mediated inflammatory diseases, JAK inhibitors were associated with lower all-cause mortality than conventional immunomodulatory therapy. In patients with bullous pemphigoid, mortality was elevated relative to controls. In older adults in East Asia, progression across CKM stages was correlated with subsequent all-cause mortality. In general population cohorts such as NHANES, mortality associations were examined for albumin-to-neutrophil-lymphocyte ratio, weight-adjusted waist circumference index, and physical activity. In BioBank Japan, China Kadoorie Biobank, and other large cohorts, all-cause mortality was used as a stable endpoint for long-term risk estimation and model validation.

Key Publications

• Jun Cardiorenal outcomes of weight loss interventions in people with CKD and type 2 diabetes. (Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 2026, PMID 41344888): "This retrospective cohort study evaluates these interventions on cardiorenal outcomes and mortality..."
• Jun Lactate/albumin ratio as an independent predictor of mortality in pediatric trauma patients admitted to a pediatric intensive care unit. (European journal of pediatrics, 2026, PMID 42366245): "The primary outcome was in-hospital mortality."
• Jun Prediction of all-cause mortality in older adults in Colombia: real-world evidence from a middle-income country. (Scientific reports, 2026, PMID 42350702): "Accurate mortality prediction in older adults is a critical component of precision public health and risk stratification in healthcare systems worldwide."
• Jun Cross-Cultural Perspectives on Metabolic Syndrome Management and Attitudes Toward Using Digital Health Tools in Two Distinct Populations: Protocol for a Qualitative Descriptive Study. (JMIR research protocols, 2026, PMID 42342245): "Individuals with MetS face significantly increased risks of cardiovascular disease, type 2 diabetes, and all-cause mortality."
• Jun Proteomics risk scores and mortality in heart failure: Generalizability across populations. (PloS one, 2026, PMID 42335150): "Proteomics risk scores have shown promise in predicting mortality beyond guideline-recommended clinical tools."
• Jun Association between COVID-19 booster vaccination and influenza mortality: a nationwide retrospective cohort study using the SIVEP-Gripe database in Brazil. (Immunologic research, 2026, PMID 42324378): "A total of 15,995 hospitalized influenza cases were included, with an overall case fatality rate of 12.1%."
• Jun Association of Esketamine use with mortality and clinical outcomes in patients with cancer-related depression: A target trial emulation. (Progress in neuro-psychopharmacology & biological psychiatry, 2026, PMID 42235877): "The primary outcome was all-cause mortality; secondary outcomes encompassed emergency room (ER) visits, intensive care unit (ICU) visits, hospitalizations, suicide-related events, palliative care, several physical complications, and psychiatric outcomes."
• Jun GLP-1 receptor agonists and clinical outcomes in adults with Crohn's disease and obesity: a propensity score-matched real-world cohort study. (Scientific reports, 2026, PMID 42321339): "At 1 year, GLP-1RA initiation was associated with lower mortality (0.7% vs. 4.2%; RR 0.17, 95% CI 0.13-0.22),"
• Jun CD1D knockout swine are permissive to African swine fever virus genotype II infection. (Emerging microbes & infections, 2026, PMID 42101028): "No significant differences in disease severity or mortality between ASFV-infected WT and KO pigs were observed."
• Jun Refined liver MRI-derived cT1 thresholds capturing hepatic fat fraction enhance mortality risk prediction. (JHEP reports : innovation in hepatology, 2026, PMID 42309239): "We aimed to evaluate whether cT1 values below 800ms are associated with mortality..."