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Association of Liver Function Tests with Mortality in an Insurance Applicant Population
Steven J Rigatti1, Robert Stout1
1Rigatti - Founder, Rigatti Risk Analytics, LLC, Consultant Medical Director, Clinical Reference Laboratories, Lenexa KS. Stout - Chief Scientific Officer / Laboratory Director, Clinical Reference Laboratories, Lenexa KS.
Liver function tests (LFTs) strongly predict mortality risk in life insurance applicants. Elevated GGT and alkaline phosphatase showed linear risk, while albumin and AST had inverse or J-shaped associations, persisting over a decade.
Area of Science:
- Biostatistics
- Epidemiology
- Clinical Chemistry
Background:
- Liver function tests (LFTs) are routinely measured in clinical practice.
- Previous studies have suggested associations between LFTs and mortality, but often with limited follow-up or specific populations.
Purpose of the Study:
- To determine the relationship between various liver function test (LFT) results and all-cause mortality.
- To assess the durability of this relationship over time in a large cohort of life insurance applicants.
Main Methods:
- Analysis of mortality data from the Social Security Master Death File for 15,272,955 life insurance applicants.
- Stratification of results by sex and age (<60/>=60), with LFT values grouped by percentiles.
- Cox proportional hazards models were used, treating LFTs as continuous variables alongside age and smoking status.
Main Results:
- Gamma-glutamyl transferase (GGT) and alkaline phosphatase demonstrated a linear, steep increase in mortality risk with higher values.
- Aspartate aminotransferase (AST) showed a J-shaped association with mortality.
- Alanine aminotransferase (ALT) exhibited a low-magnitude inverse correlation, while albumin showed a stronger inverse correlation, particularly at lower levels.
Conclusions:
- LFTs are robust and durable predictors of all-cause mortality in life insurance applicants.
- The long-term predictive power of LFTs suggests their value in mortality risk assessment, even when using historical data.
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