In population pharmacokinetic analyses, missing categorical data are often encountered. We evaluated several methods of performing covariate analyses with partially missing categorical covariate data. Missing data methods consisted of discarding data (DROP), additional effect parameter for the group with missing data (EXTRA), and mixture methods in which the mixing probability was fixed to the observed fraction of categories (MIX(obs)), based on the likelihood of the concentration data (MIX(conc)), or combined likelihood of observed covariate data and concentration data (MIX(joint)). Simulations were implemented to study bias and imprecision of the methods in datasets with equal-sized and unbalanced category ratios for a binary covariate as well as datasets with non-random missingness (MNAR). Additionally, the performance and feasibility of implementation was assessed in two real datasets. At either low (10%) or high (50%) levels of missingness, all methods performed similarly well. Performance was similar for situations with unbalanced datasets (3:1 covariate distribution) and balanced datasets. In the MNAR scenario, the MIX methods showed a higher bias in the estimation of CL and covariate effect than EXTRA. All methods could be applied to real datasets, except DROP. All methods perform similarly at the studied levels of missingness, but the DROP and EXTRA methods provided less bias than the mixture methods in the case of MNAR. However, EXTRA was associated with inflated type I error rates of covariate selection, while DROP handled data inefficiently.

The addition of rabbit anti-human thymocyte globulin (ATG) to the conditioning regimen prior to allogeneic hematopoietic cell transplantation has significantly reduced the risk of graft-versus-host disease (GvHD) and graft failure. However, ATG has a small therapeutic window. Overexposure of ATG post-HCT hampers T cell immune reconstitution and has been associated with increased relapse rates and viral reactivations, whereas underexposure has been associated with an increased incidence of GvHD, both of which lead to increased mortality. Therapeutic drug monitoring of T cell binding ATG plasma levels provides a means to optimize dosing for patients at high risk for graft failure to ensure timely T cell immune reconstitution and subsequently increase survival chances. This manuscript describes the first liquid chromatography tandem-mass spectrometry (LC-MS/MS) method to quantify the pharmacologically active fraction of polyclonal ATG in plasma. This was achieved through immunoaffinity purification of active ATG from plasma with Jurkat T cells. After the binding and washing, samples were eluted, denatured, and trypsin-digested. Signature peptides originating from the IgG constant chain were measured with LC-MS/MS. Critical method parameters were optimized, and the method was successfully validated following European Medicines Agency (EMA) guidelines. The method covered the therapeutic range of ATG and was validated at a lower limit of quantification (LLOQ) of 1 AU/mL with an overall CV and bias of 11.8% and - 2.5%, respectively. In conclusion, we developed a LC-MS/MS-based method to quantify active polyclonal rabbit ATG in human plasma. We suggest that this novel assay can be used to monitor and optimize dosing of ATG in clinical practice.