Abstract
The primary aim was to examine and compare the increased risk of incident diabetes associated with second-generation antipsychotics (SGAs) and first-generation antipsychotics (FGAs), with and without adjusting for potential confounding factors. The secondary aim was to recalculate the relative risks of diabetes onset using a semi-symmetric bidirectional case-crossover (SSBC) design to adjust for time-trend bias.
Prescription records (2005-2015) of antipsychotics were sourced from New Zealand Pharmaceutical Collections. The first-time diabetes diagnosis was extracted from the National Minimal Dataset. Relative risks (RRs) of diabetes onset were calculated using conditional logistic regression. Time-trend bias was corrected by recalculating the RR using a SSBC design.
Among 645 individuals, the risk of diabetes onset is higher in SGA users (ARR = 8.72, 95% CI = [5.57, 13.67]) compared to FGA users (ARR = 5.68, 95% CI = [3.43, 9.39]). The increased risk of diabetes onset associated with quetiapine is higher (ARR = 7.47, 95% CI = [4.10, 13.62]), compared to haloperidol (ARR = 5.05, 95% CI = [2.91, 8.75]). However, the increased risk of diabetes onset associated with olanzapine (ARR = 2.27, 95% CI = [0.86, 5.98]) is insignificant after adjusting for concomitant use of effect modifiers and other antipsychotic drugs.
The results support that the magnitude of the risk of diabetes is higher with SGA use compared with FGA use, and the risk is higher when co-prescribed. Confounding by indication and time-varying confounders such as body mass index could bias the risk of onset of diabetes. Marginal structural models could provide more precise estimates of the risk of onset of diabetes following exposure to antipsychotics.