Should I retain a PopPK covariate that passes forward/backward SCM but has a bootstrap 95% CI crossing zero?
I developed a population pharmacokinetic model in nlmixr2 (SAEM) using data from 103 patients. Three covariates were retained on clearance after forward inclusion (ΔOFV > 3.84) and backward elimination (ΔOFV > 6.63). A 200-replicate non-parametric bootstrap was then performed using bootstrapFit() (fixed final model; no repeated stepwise selection). Two covariates showed bootstrap 95% CIs excluding zero with sign consistency of 98.5% and 100%. For the third covariate, the estimate was 0.067 (RSE ≈40%), with significant forward (ΔOFV = −7.7, p = 0.0054) and backward (ΔOFV = +17.7) support. The bootstrap median was 0.056, the 95% CI was −0.019 to 0.159 (crossing zero), and 88.5% of bootstrap estimates retained the original positive sign (11.5% were small negative estimates; none were exactly zero). The covariate is mechanistically plausible but shows borderline bootstrap support. Should it be retained and reported transparently with its bootstrap CI and sign consistency, or would it be preferable to remove it and re-estimate the reduced model? Is there pharmacometric precedent for retaining OFV-significant but bootstrap-borderline covariates? Can anyone please guide me. I would be highly grateful.