Serum samples that have been stored long-term (>10 years) can be used as a suitable data source for developing...

Area of Science:

• Biochemistry
• Rheumatology
• Cardiovascular Medicine

Background:

• Rheumatoid arthritis (RA) patients have an unmet need for specific cardiovascular risk (CV) algorithms.
• Lipoprotein data, crucial for CV risk assessment, are often unavailable in RA cohorts.
• Frozen serum samples offer a potential source for obtaining historical lipoprotein data.

Purpose of the Study:

• To evaluate the impact of long-term storage (>10 years) at -20°C on lipoprotein levels in serum samples from RA patients.
• To develop a lipid decay correction factor for stored samples.
• To assess the clinical significance of storage effects on CV risk reclassification.

Main Methods:

• Longitudinal regression analyses were used to assess the storage effect on lipoproteins in 152 RA patients with samples stored for 1-26 years.
• A lipid decay correction factor was calculated for total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-c).
• The impact on CV risk reclassification was determined using the SCORE risk calculator.

Main Results:

• Storage time significantly affected TC (P<0.001) and HDL-c (P<0.001) levels, but not LDL-c (P=0.83).
• A decay correction factor of 0.03 mmol/L/year for TC and 0.024 mmol/L/year for HDL-c was established.
• After correction, only 5% of patients were reclassified to a different CV risk category.

Conclusions:

• A minor storage decay effect on lipoproteins was observed, unlikely to substantially alter CV risk stratification in RA.
• Long-term stored serum samples (>10 years) are suitable for deriving valid lipid levels for developing CV risk prediction models in RA.
• A decay correction factor may not be necessary for CV risk assessment in RA cohorts using long-term stored samples.