Limits of Detection in Acute-Phase Protein Biomarkers Affect Inflammation Correction of Serum Ferritin for Quantifying Iron Status among School-Age and Preschool-Age Children and Reproductive-Age Women

Abstract

Background: Standardized practices are needed in the analysis of inflammation biomarker values outside limits of detection (LODs) when used for inflammation correction of nutritional biomarkers.

Objective: We assessed the direction and extent to which serum C-reactive protein (CRP) and α-1-acid-glycoprotein (AGP) values outside LODs (<0.05 mg/L and >4.0 g/L, respectively) affect inflammation regression correction of serum ferritin and compared approaches to addressing such values when estimating inflammation-adjusted ferritin and iron deficiency (ID).

Methods: We examined 29 cross-sectional datasets from 7 countries with reproductive-age women (age 15-49 y) (n = 12,944), preschool-age children (age 6-59 mo) (n = 18,208), and school-age children (age 6-14 y) (n = 4625). For each dataset, we compared 6 analytic approaches for addressing CRP <LOD: listwise deletion, single imputation (lower, middle, or upper bound; LOD/√2; random number), with multiple imputation (MI). For each approach, inflammation-adjusted ferritin and ID using BRINDA (Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia) regression correction were estimated. We calculated deviance of each estimate from that given by MI within each dataset and performed fixed-effects multivariate meta-regression with an analytic approach as a moderator to compare the reliability of each approach to MI.

Results: Across datasets, observations outside LOD ranged from 0.0 to 35.0% of CRP values and 0.0 to 2.5% of AGP values. Pooled deviance estimates for mean ferritin (μg/L) and ID (percentage points) were: listwise deletion -0.46 (95% CI: -0.76, -0.16) and 0.14 (-0.43, 0.72), lower bound 0.45 (0.14, 0.76) and -0.36 (-0.91, 0.20), middle bound -0.21 (-0.51, 0.09) and 0.22 (-0.34, 0.79), LOD/√2 -0.26 (-0.57, 0.04) and 0.25 (-0.31, 0.81), upper bound -0.31 (-0.61, -0.01) and 0.30 (-0.27, 0.86), and random number -0.08 (-0.38, 0.22) and 0.11 (-0.46, 0.67). There was moderation by approach in the ferritin model (P < 0.001).

Conclusions: These findings demonstrate the need for standardized analyses of inflammation biomarker values outside LODs and suggest that random number single imputation may be a reliable and feasible alternative to MI for CRP <LOD.

Keywords: acute phase proteins; imputation; inflammation; iron deficiency; left censored; limit of detection; regression correction.

Figure 1:. Deviance and Reliability of Inflammation-Adjusted Mean Serum Ferritin Concentration under Differing Analytic Approaches for C-reactive Protein (CRP) Less Than the Limit of Detection (LOD) Within 29 Surveys Across 7 Countries (n=33,053)

LOD for CRP=0.05 mg/L. The dotted reference line at 0 indicates the estimated mean serum ferritin adjusted for inflammation using multiple imputation within each survey and population group. Points and error bars represent the deviance of each approach from the multiple imputation estimate within each survey and population group with 95% confidence intervals. The polygon represents the mean deviance of all surveys using the labelled approach. Test for differences by analytic approach (subgroup differences): Q_M=20.19, df=5, p<.001.

Figure 2:. Deviance and Reliability of Inflammation-Adjusted Prevalence of Iron Deficiency under Differing Imputation Analytic Approaches for C-reactive Protein (CRP) Less Than the Limit of Detection (LOD) Within 29 Surveys Across 7 Countries (n=33,053)

LOD for CRP=0.05 mg/L. The dotted reference line at 0 indicates the estimated prevalence of inflammation-adjusted iron deficiency using multiple imputation within each survey and population group. Points and error bars represent the deviance of each approach from the multiple imputation estimate within each survey and population group with 95% confidence intervals. The polygon represents the mean deviance of all surveys using the labelled approach. Test for differences by analytic approach (subgroup differences): Q_M=3.59, df=5, p=0.61.