Back

Assessing the impact of limit of detection on HAI titer increase estimation in vaccine studies

Ge, Y.

2022-08-30 epidemiology
10.1101/2022.08.25.22279230 medRxiv
Show abstract

In many laboratory assays that measure immunological quantities, a portion of the measured values fall below a limit of detection (LOD). This is also the case for the hemagglutination inhibition assay (HAI), a common method used to quantify antibodies in influenza research. The conventional approach is to treat values below the LOD as either equal to the LOD or LOD/2, which can introduce potential biases. These biases can become more pronounced when calculating compound measures such as the difference between post-vaccination and pre-vaccination antibody titers (titer increase). To address this issue, we conducted simulations using LOD measurements with LOD/2 values as the standard imputation. We then developed a new method to adjust coefficient estimates that account for the censored nature of measurements below the LOD. Applying this new method to data from an influenza vaccine cohort study, we compared the impact of vaccine dose on the titer increase of HAI. Author SummaryAnalysis of measurements obtained from widely used antibody assays frequently overlooks the underlying data structure, leading to potential biases in the results. To address this issue, we have developed a method that effectively reduces these biases.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.