Estimating Risk of Antidepressant Withdrawal from a Review of Published Data

Abstract

Adaptation of the brain to the presence of a drug predicts withdrawal on cessation. The outcome of adaptation is often referred to as 'physical dependence' in pharmacology, as distinct from addiction, although these terms have unfortunately become conflated in some diagnostic guides. Physical dependence to antidepressants may occur in some patients, consistent with the fact that some patients experience withdrawal effects from these medications. It is thought that longer duration of use, higher dose and specific antidepressants affect the risk of antidepressant withdrawal effects as they might cause greater adaptation of the brain. We searched PubMed for relevant systematic reviews and other relevant analyses to summarise existing data on determinants of antidepressant withdrawal incidence, severity and duration. Overall, data were limited. From survey data, increased duration of use was associated with an increased incidence and severity of withdrawal effects, consistent with some evidence from data provided by drug manufacturers. Duration of use may be related to duration of withdrawal effects but data are heterogenous and sparse. Serotonin and noradrenaline reuptake inhibitors and paroxetine are associated with higher risks than other antidepressants, though data for some antidepressants are lacking. Higher doses of antidepressant has some weak association with an increased risk of withdrawal, with some ceiling effects, perhaps reflecting receptor occupancy relationships. Past experience of withdrawal effects is known to predict future risk. Based on these data, we outline a preliminary rubric for determining the risk of withdrawal symptoms for a particular patient, which may have relevance for determining tapering rates. Given the limited scope of the current research, future research should aim to clarify prediction of antidepressant withdrawal risk, especially by examining the risk of withdrawal in long-term users of medication, as well as the severity and duration of effects, to improve the preliminary tool for predictive purposes. Further research into the precise adaptations in long-term antidepressant use may improve the ability to predict withdrawal effects for a particular patient.

Fig. 1

Conceptual model of the neurobiology of antidepressant withdrawal. In this diagram, the homeostatic ‘set-point’ is shown in black and antidepressant (AD) drug concentrations are shown in blue dotted lines [77]. (1) The system is at baseline. At the blue arrow, an antidepressant is administered; drug plasma concentrations increase. Physiological adaptations of the system to the presence of the drug begin (which may be the period for which ‘start-up side effects’ are most pronounced). (2) At the plateau, drug plasma concentrations (and target receptor activation) have reached a steady state with a new homeostatic set-point of the system established (‘start-up side effects’ may reduce). (3) The antidepressant is abruptly ceased and plasma drug concentrations drop to zero (exponentially, according to the elimination half-life of the drug). This difference between the homeostatic set point (the ‘expectations’ of the system) and the concentration of drug in the system (dotted blue line) is experienced as withdrawal symptoms. The duration of withdrawal symptoms is largely determined by the time required for adaptations to the drug to resolve. Hence, withdrawal symptoms may worsen or peak even long after the drug has been eliminated from the system. The shaded area under the curve, representing the difference between the homeostatic set-point and the concentration of the drug, indicates the degree of risk of withdrawal symptoms: the larger the area the greater the risk. The greater the departure of drug concentration from the homeostatic set-point, the greater the risk. Adapted, with permission, from [77]

Fig. 2

Relationship between duration of treatment (before stopping) and proportion of patients who experienced withdrawal effects on stopping either paroxetine or placebo (overall trend p value <0.001) [47]. Significance for Fisher exact tests for by-month group comparisons. *p < 0.05; **p < 0.01; ***p < 0.001

Fig. 3

Relationship between duration of treatment and severity and duration of withdrawal symptoms from surveys of antidepressant users and observational studies. The relationship between duration of treatment of antidepressants and incidence of moderate or severe withdrawal symptoms. Graph is derived from data in Read et al. [57]