Despite the lack of guidance available for practitioners, extensive polypharmacy has become the primary method of treating patients with severe and chronic mood, anxiety, psychotic or behavioral disorders. This ground-breaking new book provides an overview of psychopharmacology knowledge and decision-making strategies, integrating findings from evidence-based trials with real-world clinical presentations. It adopts the approach and mind-set of a clinical investigator and reveals how prescribers can practice 'bespoke psychopharmacology', tailoring care to the individualized needs of patients.
Human Diversity and Considerations in Special Populations
Today you are You, that is truer than true. There is no one alive who is Youer than You.
▢ Appreciate known pharmacokinetic and pharmacodynamic differences in psychotropic drug response across sexual, racial/ethnic, age-based, and other distinct patient subgroups such as those who smoke cigarettes or significantly drink alcohol
▢ Recognize psychotropic drug safety concerns during pregnancy, lactation, and the postpartum period
▢ Recognize associations between mood disorders and menstrual dysregulation, and appropriate pharmacotherapies
▢ Understand the complexities of treating (and distinguishing iatrogenic from primary illness symptoms in) patients with somatic symptom disorder
▢ Understand the implications of major medical conditions for prescribing psychotropic medications
▢ Know the impact of diminished hepatic or renal function on drug metabolism and clearance
All patient subpopulations are inherently “special” based on their unique constellations of clinical and demographic features that moderate and mediate treatment outcomes. This chapter will focus on diversity across distinct clinical subpopulations for which moderating or mediating factors do not simply provide information about the likelihood of a favorable drug response, but more specifically identify the need to adjust medication dosages or regimens, or favor certain medications over others based on evidence for safe and effective use in a particular patient group. Chronological age and biological sex assignment rarely in themselves signal the need for dosage adjustments, although associated features (e.g., diminished hepatic or renal function; pregnancy, premenstrual mood disturbances) may bear on a select evidence base for a given subpopulation. Metabolic (e.g., CYP450) enzymes also can vary by race, gender, age, and genetic polymorphisms, as noted in Chapter 8.
For all medications with any FDA approval, manufacturers’ product information sheets routinely discuss use in “specific populations” in Section 8. More specifically, Sections 8.1 and 8.2 focus on pregnancy and lactation, respectively; Sections 8.4 and 8.5 discuss pediatric and geriatric uses, respectively; and Sections 8.6 and 8.7 typically discuss patients with hepatic and renal impairment, respectively. Note that the product labels for relatively older medications (e.g., bupropion) are sometimes less explicit than for newer medications in the language they use to specify dosage modifications in special populations (e.g., bupropion in renal impairment).
This chapter is subdivided into two main sections: populations stratified by: (a) clinically definable subgroups (including racial–ethnic–ancestral groups, sex differences, children/adolescents, geriatric/older adult patients, pregnancy/lactation, smokers, substance use disorders, and patients prone to somatization) and (b) those with clinically significant medical comorbidities or chronic medical conditions. Among the latter, rather than attempt to recapitulate the vast material contained in textbooks devoted to the topic of consultation-liaison (C-L) psychiatry, we have chosen instead to focus on a select number of commonly encountered medical conditions that bear directly on pharmacological decision-making for practitioners without formal subspecialty training in C-L psychiatry.
Ethnic and racial diversity remains a controversial topic regarding psychiatric diagnosis and treatment in general, and pharmacotherapy in particular. In part, there is much debate as to whether race constitutes a biologically valid differentiator for parsing disease susceptibility factors and treatment parameters or pharmacodynamic outcomes. Box 12.1 provides distinguishing definitions for key concepts in this area.
Ethnicity refers to cultural factors such as language, ancestry, religion, heritage, and customs. Ethnic influences might, for example, foster shunning the use of medication for depression, or pursuing spiritual rather than medical solutions to mental health problems.
Race is meant to classify groups based on shared physical attributes such as skin color, bone structure, eye color, and hair color and texture. Suspected racial predispositions to pharmacokinetic and pharmacodynamic outcomes may be confounded by ethnic, socioeconomic, geographic, or other nonbiological factors. Increasingly, race has been criticized in both the scientific and lay literature as a purely social, scientifically artificial construct that has no basis in genetics or any other biological framework.
Ancestry has become an increasingly preferred term to describe allelic variation based on someone’s geographic origins. (The term “Caucasian,” for example, emanates from an eighteenth-century racial taxonomy which proposed that Whites descended from ancestry in the Caucasus mountain region spanning Europe and Asia.) Ancestry, more than race, may more accurately describe one’s genetic composition and consequent predisposition to particular health conditions (e.g., sickle cell anemia may be more prevalent among individuals who hail from sub-Saharan Africa, rather than among those with any particular skin color).
The psychopharmacological (and other psychiatric) literature broadly addressing “race” as a construct relevant to pharmacokinetics and pharmacodynamics has only recently begun to draw formal distinctions between racial, ethnic, and geographic-ancestral groupings. More specifically, psychopharmacologists are interested in how best to recognize population stratification by differentiable allelic frequencies across groups (e.g., consider the known variations in allelic frequencies for CYP450 isoenzymes described in Box 8.4 in Chapter 8). Existing literature on race or ethnicity in psychopharmacology usefully identifies racial-ethnic disparities in prescribing patterns (e.g., after the 2004 FDA boxed warning regarding suicidality and antidepressant use in youth, antidepressant prescribing in the United States declined more precipitously for Whites than for Blacks or Latinos (DePetris and Cook, 2013)). Elsewhere, the literature offers descriptive observations about “race” that may be cruder than intended, without accounting for geographic, ancestral, or cultural confounders. See Box 12.2 for examples.
As compared to White patients, African Americans with psychotic disorders tend to receive higher doses of antipsychotics, more frequent depot antipsychotics, longer overall exposure durations, and more frequent cotherapy with multiple antipsychotics (Chaudhry et al., 2008)
Asian and Latino patients appear more prone to antipsychotic extrapyramidal adverse effects than African Americans or Whites (Binder and Levy, 1981) and respond to lower antipsychotic doses as compared to Whites (Ruiz et al., 1999)
Latino women are more likely than White women to report side effects when taking tricyclic antidepressants (Sramek and Pi, 1996)
Historically, RCTs have tended to enroll more White than non-White participants, thereby generating more unknowns about the generalizability of treatment outcomes to more diverse populations. Other relevant considerations to psychopharmacology outcomes include:
Ethnic–racial groups that vary in baseline rates of underlying medical vulnerabilities (e.g., diabetes, hypertension) or lifestyle (e.g., smoking) may be more or less predisposed to certain adverse drug effects (e.g., metabolic dysregulation)
Ethnic–racial–ancestral differences in pharmacokinetics and pharmacodynamics may influence the presentation and treatment of certain psychiatric disorders: for example, relatively underactive forms of aldehyde dehydrogenase among individuals with Japanese and other Asian ancestry tend to diminish the risk for alcoholism; meanwhile, low activity variants of alcohol dehydrogenase appear to be over-represented among people with Native American ancestry, in turn raising vulnerability to heavier alcohol consumption (Peng et al., 2014) (see Box 12.3)
Higher rates of benign ethnic neutropenia (BEN) among people of African or Middle Eastern descent (as high as 25–50%; Haddy et al., 1999) differentially impacts the hematological safety profile for clozapine
People of Asian (Ng et al., 2005) or Korean descent (Matsuda et al., 1996) may require lower mean oral clozapine dosages than do Whites to achieve comparable serum clozapine levels
Ethnic rather than racial differences might account for phenomena such as the substantially higher age-adjusted suicide rates among Native Americans/Alaska natives (22.15 per 100 000) than among Asian/Pacific islanders (6.75 per 100 000)
Ethnic differences in diet and nutrition, access to health care, primary prevention, smoking status, attitudes toward psychoactive substances, and preferences for nutraceutical products
Cross-cultural differences in attitudes about mental illness, pharmacotherapy in general, and treatment adherence
Increasing racial diversity and inter-racial marriage, coupled with ever-increasing geographic mobility, tends to blur categorically defined racial or ethnic group affiliations. Expanding rates of individuals with mixed racial, geographic, and ethnic ancestries introduce further layers of population stratification that go well beyond the five standard racial categories specified by the US Office of Management and Budget (1997).
In general, there are relatively few robust differences in pharmacotherapy dosing and pharmacodynamic outcomes based strictly on sex. Pharmacokinetic sex differences can arise based on drug bioavailability (e.g., women have lower gastric acid secretion and slower gastric emptying than men) and metabolism/excretion (e.g., estrogen induces P450 enzymes). Longer drug elimination half-lives in women versus men have been observed with mirtazapine (37 hours versus 26 hours), zolpidem (45% higher Cmax and AUC, hence the manufacturer’s recommendation for 5 mg per night standard dosing in women versus 10 mg/HS in men) and olanzapine (30% reduced clearance in women than men). Women have demonstrably higher serum concentrations than men receiving comparable doses of amitriptyline, nortriptyline, doxepin, citalopram, and mirtazapine (Unterecker et al., 2013). Women also tend to have lower-activity forms of gastric and hepatic alcohol dehydrogenase as compared to men, leading to the potential for higher blood alcohol levels and reduced tolerance to the effects of alcohol in women than men.
In the case of depression, women tend to manifest more atypical depressive features (i.e., hypersomnia, hyperphagia, anergia) than do men, as well as more extensive anxiety comorbidity, suicide attempts, and seasonal mood variation patterns. Whether or not antidepressant treatment outcomes differ in women versus men remains an open question. One oft-cited study in chronic depression (Kornstein et al., 2000), involving a post hoc analysis of sex differences on treatment outcomes with sertraline versus imipramine, found that women responded better to sertraline while men responded better to imipramine, and postmenopausal women had comparable response rates to both antidepressant classes. That study also prompted interest in the hypothesis that SSRIs may work better in the presence of estrogen, a hypothesis further supported by a short-term (four-week) study showing better antidepressant efficacy in perimenopausal women taking estradiol (17 β-estradiol (100 micro g/day)) than placebo (Cohen et al., 2003). However, numerous subsequent prospective studies and meta-analyses have failed to replicate the finding of a sex difference in antidepressant responses with other SSRIs or SNRIs (Sramek et al., 2016).
Antidepressant adherence has been shown to be better in men than women during youth (ages 20–40), but in women more than men during middle and older age (ages 50–70) (i.e., adherence is better in older women than older men (Krivoy et al., 2015)).
When prescribing FGAs or SGAs to women, clinicians should remember that agents with high risk for causing hyperprolactinemia are relatively contraindicated in patients with a history of estrogen receptor (ER)-positive breast cancer, due to the potential trophic effects of prolactin on ER-positive malignant tissue. Prolactin-sparing SGAs such as aripiprazole remain a preferred agent in such instances. Hyperprolactinemia caused by SGAs in general tends to be somewhat higher in women than men, and for women in particular may more often lead to osteoporosis (as well as more common galactorrhea than in men).
Little has been written about possible unique psychopharmacotherapy issues in transgender individuals. Among individuals diagnosed with gender dysphoria, incident rates of depression, suicidal thinking, and self-harm/nonsuicidal self-injury are disproportionately elevated as compared to the general population, often within the context of interpersonal problems, issues involving low self-esteem, and poor perceived social support (Claes et al., 2015; Witcomb et al., 2018).
Nearly 70% of male-to-female (MtF) or female-to-male (FtM) adults with gender dysphoria have an identifiable current or lifetime psychiatric disorder, most often affective and anxiety disorders, while rates of personality disorders appear comparable to those seen in the general population (Heylens et al., 2014). Social anxiety disorder, in particular, was noted in nearly one-third of a cohort of 210 subjects prior to biological sex reassignment interventions, who were studied as part of a specialized transgender unit within a university hospital in Spain (Bergero-Miguel et al., 2016).
With respect to further diagnostic issues, some authors have noted that primary psychotic disorders such as schizophrenia can involve “pseudotranssexualism” (Borras et al., 2007) or delusions related to the idea of sex reassignment that may attenuate with appropriate antipsychotic treatment – noting that transgender concerns are difficult to evaluate as bona fide phenomena when they may be secondary to untreated psychosis in patients who manifest signs of schizophrenia or other psychotic disorders.
We are aware of no formal trials of any pharmacotherapies specifically among transgender individuals. At least on theoretical grounds, clinicians should be mindful of the potential impact of gonadal steroid treatment on mood and thinking, in addition to pharmacokinetics. In FtM persons, high-dose testosterone has been shown to increase serotonin transporter binding in limbic structures and the dorsal striatum – although potential links with these observations and depression symptoms or serotonergic antidepressant response remain purely speculative (Kranz et al., 2015).
Rather than embark on any diluted attempt to address the vast topic of evidence-based pharmacotherapies in children and adolescents, we wish instead here to draw attention to known differences in pharmacotherapy safety and efficacy in youth versus adulthood across major domains of psychopathology. Main findings across broadly defined drug classes are presented in Tables 12.1–12.7.
|Broad drug classification||Key findings|
Abbreviations: PTSD = post-traumatic stress disorder; RCT = randomized controlled trial; SNRI = serotonin-norepinephrine reuptake inhibitor; SSRI = selective serotonin reuptake inhibitor
|Drug class||Key findings|
Abbreviations: RCT = randomized controlled trial; SGA = second-generation antipsychotic; TD = tardive dyskinesia
|Drug class||Key findings|
Abbreviations: ADHD = attention deficit hyperactivity disorder; RCT = randomized controlled trial; SMD = standard mean difference
|Gabapentin||Pediatric safety data limited to epilepsy and neuropathic pain; no RCTs assessing possible anxiolytic or other psychotropic effects|
|Oxcarbazepine||In children and adolescents with epilepsy, most common adverse events were headache (33%), somnolence (32%), nausea or vomiting (1–28%), dizziness (23%), rash (3%), and fatigue (1.6%) (Bourgeois and D’Souza, 2005). In the sole published RCT of oxcarbazepine in pediatric mania, no differences in efficacy versus placebo were observed over six weeks; nausea was the most common adverse event; weight gain was significantly greater with oxcarbazepine (+0.83 kg) than placebo (–0.13 kg); no observed hyponatremia (Wagner et al., 2006)|
|Pregabalin||No data on safety or efficacy for psychotropic use in children and adolescents|
|Topiramate||RCTs for psychiatric uses in children and adolescents are limited to Tourette’s syndrome, suggesting only modest benefit for tic control; common adverse effects include drowsiness (up to 16%), appetite loss (up to 17%), cognitive dysfunction (up to 13%), and weight loss (up to 11%) (Yang et al., 2013)|
Abbreviations: RCT = randomized controlled trial
|Benzodiazepines, buspirone, hydroxyzine, or sedative hypnotics||
Abbreviations: GAD = generalized anxiety disorder; RCT = randomized controlled trial
|Psychostimulants and other treatments for ADD/ADHD||
Table 12.7 presents a summary of relative efficacies (ORs for treatment response, with 95% CIs) pairwise between ADHD pharmacotherapies and placebo or as comparisons between pairs of active drugs based on random-effects Bayesian network meta-analyses involving 171 RCTs with 22 961 patients (Catalá-López et al., 2017). Main findings from these network meta-analyses included the following:
Abbreviations: ADD = attention deficit disorder; ADHD = attention deficit hyperactivity disorder; CI = confidence interval; OR = odds ratio; RCT = randomized controlled trial
|Placebo||0.59 (0.46–0.75)||0.78 (0.52–1.18)||0.85 (0.68–1.07)||0.40 (0.20–0.78)||0.79 (0.54–1.14)||0.67 (0.37–1.24)||1.54 (0.39–6.76)|
|5.26 (4.09–6.82)||Methylphenidate||1.33 (0.85–2.08)||1.45 (1.09–1.91)||0.68 (0.33–1.35)||1.34 (0.86–2.07)||1.14 (0.61–2.19)||2.60 (0.66–11.64)|
|7.45 (5.10–11.09)||1.42 (0.92–2.20)||Amphetamine||1.09 (0.71–1.66)||0.51 (0.23–1.11)||1.01 (0.58–1.72)||0.86 (0.42–1.79)||1.96 0(0.47–9.21)|
|3.63 (2.81–4.73)||0.69 (0.52–0.92)||0.49 (0.32–0.74)||Atomoxetine||0.47 (0.22–0.94)||0.92 (0.61–1.41)||0.79 (0.42–1.52)||1.80 (0.45–8.03)|
|3.96 (1.89–8.41)||0.75 (0.36–1.58)||0.53 (0.23–1.22)||1.09 (0.50–2.39)||Clonidine||1.99 (0.91–4.33)||1.69 (0.70–4.33)||3.88 (0.82–20.02)|
|3.29 (2.27–4.82)||0.62 (0.40–0.98)||0.44 (0.26–0.75)||0.91 (0.58–1.41)||0.83 (0.36–1.92)||Guanfacine||0.86 (0.42–1.76)||1.95 (0.47–8.84)|
|5.51 (3.04–10.32)||1.05 (0.56–2.00)||0.74 (0.36–1.54)||1.52 (0.79–2.94)||1.41 (0.53–3.66)||1.68 (0.82–3.45)||Modafinil||2.28 (0.52–11.33)|
|2.41 (0.48–11.63)||0.46 (0.09–2.21)||0.32 (0.06–1.65)||0.67 (0.13–3.29)||0.61 (0.10–3.36)||0.74 (0.14–3.72)||0.44 (0.08–2.36)||Bupropion|
Data below the diagonal (clear cells) represent efficacy (odds ratios for treatment response); data above the diagonal (shaded cells) represent acceptability (odds ratios for all-cause discontinuation). Note that ORs <1.00 reflect a lower probability of an event while ORs >1.00 indicate increased probability of an event. Statistically significant ORs (with 95% CIs) are bolded.
Findings are based on data reported by Catalá-López et al., 2017.
Safety concerns with psychotropic drugs in the elderly are summarized in a consensus panel statement by the American Geriatrics Society known as the Beers Criteria® for potentially inappropriate medication (PIM) use (2019 American Geriatrics Society Beers Criteria® Update Expert Panel), a document that undergoes updates approximately every three years. Among the key recommendations regarding psychotropic use in older adults within the 2019 guidelines are the following:
Avoid coprescribing opiates with benzodiazepines or gabapentinoids (i.e., gabapentin, gabapentin enacarbol, or pregabalin) (see Box 12.4)
Prior recommendations to avoid H2 blockers in older adults based on concerns that they can cause dementia were removed, because evidence to support such a correlation is weak – although H2 blockers are considered a risk for causing or worsening delirium and should be avoided in that setting
Dextromethorphan/quinidine can increase the risk for falls and drug–drug interactions and lacks value in dementia unless pseudobulbar affect is clearly present (See Box 12.5)
In the setting of Parkinson’s disease, avoid all anti-dopaminergic antipsychotics other than quetiapine or clozapine (presumably based on relatively low risk for adverse motor effects or nigrostriatal DA blockade, due to less potent D2 receptor binding; see also Chapter 10, Box 10.5)
A large (n = 191 973) Swedish registry study found a hazard ratio of 1.26 for suicidal behavior, 1.24 for unintentional overdoses, 1.22 for head/body injuries, and 1.13 for motor vehicle accidents among gabapentin or (especially) pregabalin recipients (Molero et al., 2019). While that study controlled for age, sex and several other potential confounders, its nonrandomized design precludes assessing for possible confounding by indication in possible higher-risk subgroups within the population. Other observational reports identify increased misuse/abuse (Chiappini and Schifano, 2016) as well as a sharp rise in the use of gabapentinoids in age-associated intentional drug overdoses since 2007 (Daly et al., 2018a).
PBA is a neurological phenomenon that involves uncontrollable fits of crying or laughing, most often resulting from traumatic brain injury, stroke, dementia, multiple sclerosis, amyotrophic lateral sclerosis, or Parkinson’s disease. It is sometimes treated with dextromethorphan/quinidine.
Other psychotropic medications considered “inappropriate” for older adults according to the Beers Criteria®, identified as “strong” recommendations, are shown in Box 12.6.
Anticholinergics: diphenhydramine, hydroxyzine
Antiparkinsonian: benztropine, trihexyphenidyl
Cardiovascular: prazosin, terazosin
Antidepressants: amitriptyline, amoxapine, clomipramine, desipramine, doxepin >6 mg/day, imipramine, nortriptyline, paroxetine, protriptyline, trimipramine
Antipsychotics: “avoid, except in schizophrenia or bipolar disorder” 1
Barbiturates: all, due to “high rate of physical dependence, tolerance to sleep benefits, greater risk of overdose at low doses”
Benzodiazepines: all, due to “increased risk for cognitive impairment, delirium, falls, fractures, motor vehicle crashes”
Nonbenzodiazepine benzodiazepine receptor agonist hypnotics (“Z-drugs”): eszopiclone, zaleplon, zolpidem (similar concerns as with benzodiazepines)
* As per the Beers Criteria®
Given the concerns with benzodiazepines and “Z-drugs” noted in the Beers Criteria® recommendations, alternative preferred sleep aids would include ramelteon and suvorexant. Are they evidence-based, or just lesser evils? In a study of 829 elderly patients with chronic insomnia, 4 or 8 mg/HS of ramelteon improved sleep latency and total sleep time, with mild-to-moderate nausea and headache being the most common associated adverse effects (Roth et al., 2006). Similar findings showing improved sleep latency with good tolerability were found over five weeks among 157 older adults (mean age 72.3 years) taking ramelteon 8 mg/HS (Mini et al., 2007). Suvorexant and lemborexant have a novel mechanism of action involving orexin receptor blockade that spares antihistaminergic or anticholinergic pathways. A pooled analysis of three-month data with suvorexant involving 319 adults over the age of 65 with chronic insomnia showed efficacy and good tolerability as compared to placebo in improving sleep latency and continuity; daytime somnolence occurred in 5–9% of subjects, with no evidence of adverse cardiovascular effects (Herring et al., 2017). FDA registration trials for suvorexant also included 159 patients aged 75 or over, again with observed good tolerability.
The combination of ramelteon plus suvorexant has been shown to safely and effectively improve sleep quality as well as reduce the risk for poststroke delirium as compared to GABAergic drugs (Kawada et al., 2019). Notable as well are randomized data showing a significantly reduced risk for developing intensive care unit (ICU) delirium with suvorexant (15–20 mg/HS) than seen with conventional sedative-hypnotics (Azuma et al., 2018).
Risk for hyponatremia and SIADH with antidepressant use is higher in older adults. Some primary care physicians therefore advise checking serum Na+ levels about a month after starting a serotonergic antidepressant (Frank, 2014); the Beers Criteria® advise “close monitoring” of serum Na+ levels in older adults taking SSRIs, SNRIs, mirtazapine, tricyclics, carbamazepine, or oxcarbazepine.
Because of increased falls risk in the elderly, α1-blocking agents (with a resultant risk for orthostatic hypotension), alongside anticholinergic drugs (and their potential for adverse cognitive effects) are generally discouraged.
Coadministration of lithium with ACE inhibitors or loop diuretics is also discouraged (by Beers Criteria®) due to a risk for lithium toxicity (or, otherwise, in our view very close monitoring of serum lithium levels is advisable if benefits are thought to outweigh risks).
For patients taking lithium who also require treatment with a nonsteroidal anti-inflammatory, lower the dose of lithium by at least 20% for the duration of cotherapy and for five days after NSAID discontinuation, while following lithium levels to assure absence of toxicity.
Antidepressant response rates in older adults are notoriously lower than in younger populations. In a meta-analysis of 10 acute (6–12 week) placebo-controlled antidepressant trials in late-life depression, Nelson and colleagues (2008) found a pooled response rate with antidepressants (44.4%) that was only modestly better than placebo (34.7%), with a somewhat higher probability of response during longer trials (10–12 weeks; OR = 1.73) than shorter trials (6–8 weeks; OR = 1.22). A moderator analysis involving 7 of these 10 trials found that duration of illness (especially >10 years) and higher baseline depression symptom severity were the two most robust predictors of antidepressant response; in other words, antidepressants had little to no difference versus placebo when late-life depression was of short duration and only mild-to-moderate severity (Nelson et al., 2013).
It is hard to know how much outcomes in late-life depression may be moderated by episode number. In STAR*D first-episode MDE patients, remission rates and time to remission were comparable for subjects with first episodes below the age of 55 versus those aged 55–75 (Kozel et al., 2008).
A later meta-analysis involving 15 RCTs examined older as well as newer-generation antidepressants for MDD patients aged 55 and older (Tedeschini et al., 2011). Overall antidepressant response among MDD patients aged over 65 was found to be no better than with placebo (p = 0.265; NNT for this group was 21), while placebo response rates in themselves were similar in older and younger adult MDD groups. Observed risk ratios for response across RCTs in that meta-analysis are presented in Table 12.8.
|Antidepressant||N||Dosing range||RR for response|
a Based on findings reported in meta-analysis by Tedeschini et al., 2011
b The two RCTs of escitalopram for acute late-life depression noted here did not show a difference from placebo; however, elsewhere, escitalopram was superior to placebo for depression relapse prevention after acute open-label remission (Gorwood et al., 2007)
Finally, another network analysis of 15 RCTs examined partial response relative to all-cause dropout (i.e., effectiveness) and found the strongest evidence for effectiveness (i.e., efficacy balanced against all-cause dropout) with sertraline (RR for partial response = 1.28), paroxetine (RR for partial response = 1.48) or duloxetine (RR for partial response = 1.62) relative to placebo, with less robust effectiveness seen with citalopram, escitalopram, venlafaxine, or fluoxetine (Thorlund et al., 2015). Among adverse effects, dizziness was least common with sertraline (RR = 1.14) or duloxetine (RR = 1.31) and most severe with duloxetine (RR = 3.18) or venlafaxine (RR = 2.94).
In addition to the above findings are the following:
Vortioxetine dosed at 5 mg/day was superior to placebo, and well tolerated, in a dedicated placebo-controlled trial for late-life depression (Katona et al., 2012).
Two RCTs of duloxetine in late-life depression subsequent to the Tedeschini et al. (2011) meta-analysis yielded conflicting results: in the above-noted placebo-controlled trial of vortioxetine (Katona et al., 2012), duloxetine as an active comparator showed efficacy versus placebo, but another 24-week trial found no difference from placebo in depression outcomes (although pain scores improved more with duloxetine); about a quarter of depression nonremitters to a 60 mg/day dose by week 12 went on to subsequent remission after dosing was increased up to 120 mg/day (Robinson et al., 2014).
A post hoc analysis of nine pooled desvenlafaxine MDD RCTs revealed no significant moderating effect of age from 18–40 versus 41–54 versus 55–64; too few subjects precluded assessment of those aged 65 or over; a higher incidence of orthostatic hypotension than seen in younger adult populations was noted (Mosca et al., 2017). No RCTs of desvenlafaxine for MDD in adults aged over 65 are available.
FDA registration trials of vilazodone enrolled 2.2% (n = 65) of subjects aged over 65, although no separate analyses examined treatment outcomes in that subpopulation. No specific dosing adjustments are advised in the elderly.
In FDA registration trials of levomilnacipran for MDD, 2.8% of enrolled subjects were aged over 65, but no separate analyses of efficacy and tolerability have thus far been reported.
In older adult patients beware the risk of acute urinary retention with SNRIs.
From a safety standpoint, although anticholinergic antidepressants are shunned by the Beers Criteria®, it is noteworthy that placebo-controlled trials support the safety/tolerability and efficacy of low-dose paroxetine CR for MDD in adults over 60, as noted in Table 12.3; as well as secondary amine tricyclics such as nortriptyline (especially for older adult depression with melancholic features, where it outperformed fluoxetine; Roose et al., 1994). In a large Medicare database of new SSRI users in a nursing-home setting (n = 19 952), incident rates of newly diagnosed dementia over a two-year period were no higher among those who took paroxetine than other SSRIs (Bali et al., 2015).
In the 2001 Expert Consensus Guideline Series on the pharmacotherapy of depression in older adult depression (Alexopoulos et al., 2001), lower dosages and slower titration periods were a maxim described in most instances; the expert panel advocated making no changes to a low-dose drug regimen for two to four weeks if little or no response is evident, and waiting three to five weeks in the case of a partial response. In patients able to tolerate higher doses, three to six weeks is considered an adequate trial if no response is evident, while four to seven weeks is recommended if a partial response is detected. After response or remission to a first episode, the experts collectively advise continuation pharmacotherapy for one year; for a second lifetime episode, most experts advised continuation therapy for two years (39%) or three or more years (37%), with a minority advising shorter durations. Nearly all (98%) advocated continued therapy for longer than three years in patients with more than three lifetime episodes.
In depressed venlafaxine (up to 300 mg/day) nonresponders over the age of 60 (n = 181), adjunctive aripiprazole (2–15 mg/day) for 12 weeks yielded a higher remission rate than did adjunctive placebo (44% versus 29%, respectively; OR for remission = 2.0, NNT = 6.6); parkinsonism was a notable adverse event arising in 17% of those taking active drug (Lenze et al., 2015). A post hoc analysis of that study found that response was moderated by unimpaired baseline set-shifting (measured by Trail-Making task condition 4 versus 5) on neurocognitive testing (Kaneriya et al., 2016). Brexpiprazole2 (1–3 mg/day) has been studied in open-label fashion over 26 weeks as an adjunct to monoaminergic antidepressants, with outcomes complicated most often by fatigue and restlessness (18% withdrew due to adverse events) (Lepola et al., 2018). In a dedicated late-life MDD trial, quetiapine XR monotherapy dosed from 50–300 mg/day (mean dose = 158 mg/day) over nine weeks in 166 MDD patients aged 66 or over yielded a greater reduction in depressive symptoms than seen with placebo (n = 172); the most commonly seen adverse events were dizziness, somnolence, and headache (Katila et al., 2013). A post hoc analysis from that study found efficacy for quetiapine XR over placebo regardless of the presence or absence of baseline anxiety, high or low sleep disturbances, and pain scores (Montgomery et al., 2014).
Psychostimulants have long been of interest in the treatment of anergic depression both in younger-and older-adult MDD. An RCT of methylphenidate dosed from 5–40 mg/day (mean dose = 16 mg/day) or placebo added to citalopram (dosed from 20–60 mg/day, mean dose = 32 mg/day) showed faster and more extensive improvement with combination therapy; cognitive outcomes and adverse effects were similar for both treatment groups (Lavretsky et al., 2015). That study affirmed and extended findings from a previous small (n = 16) 10-week pilot RCT of adjunctive methylphenidate (Lavretsky et al., 2006). Clinical trials are lacking in late-life MDD with amphetamine formulations, modafinil/armodafinil, or solriamfetol, although each of these compounds has a rationale particularly in anergic, nonagitated, or hypersomnic presentations of MDD.
Anxiolytic pharmacotherapy in older adults involves similar concerns as for depression regarding pharmacotherapy safety and tolerability, although the hazards of sedative-hypnotics pose particular limitations. A meta-analysis of 32 RCTs assessing psychosocial interventions as well as pharmacother-apies (benzodiazepines, SSRIs, SNRIs, SGAs, TCAs, and other drugs, including buspirone, nefazodone, and carbamazepine) found overall greater improvement resulting from pharmacotherapy than psychosocial interventions alone, with no single preferred agent identified (Pinquart and Duberstein, 2007).
Limited RCT data address the safety and efficacy of SGAs in patients over 65, across varied indications, either relative to placebo or in head-to-head comparisons between active agents. Generally, manufacturers’ product labeling does not advise dosing adjustments in older adults unless factors that directly impede metabolism or drug clearance (i.e., renal or hepatic impairment) are known to be present. In schizophrenia, one meta-analysis of 18 RCTs involving 1225 participants found mainly that olanzapine was superior to haloperidol in treating overall and negative symptoms, incurred less use of antiparkinsonian drugs, and had fewer dropouts than did risperidone (Krause et al., 2018b). Insufficient data precluded a network meta-analysis. SGAs whose FDA registration trials enrolled sufficient numbers of adults over the age of 65 to determine that age alone did not impair tolerability include quetiapine (n = 232), olanzapine (n = 263), and paliperidone (n = 125 schizophrenia patients aged 65 or over (n = 22 aged 75 or over), as well as an additional 114 in a dedicated six-week trial in schizophrenia patients aged 65 or over). Each of these databases suggest no inherent differences in tolerability or efficacy among older versus younger patients based on age alone.
Tobacco smoke induces CYP450 1A1, 1A2 and 2E1. Accordingly, with respect to monoaminergic antidepressants, cigarette smokers would be expected to have decreased serum concentrations of duloxetine (metabolized by CYP 1A2 and 2D6; bioavailability (AUC) is reduced by about one-third), fluvoxamine (metabolized by CYP 1A2 and 2D6), and mirtazapine (metabolized by CYP 1A2, 2D6, and 3A4). Serum trazodone levels also were found to be lower among smokers than nonsmokers, even though its metabolism is only via CYP 3A4 (reviewed by Oliveira et al., 2017). Metabolic clearance of olanzapine (primarily a CYP 1A2 substrate) is ~40% higher in smokers than nonsmokers. Although asenapine is predominantly a CYP 1A2 substrate, smokers have not been shown to differ from nonsmokers in clearance. Smoking has not been shown to affect serum levels of fluoxetine but may raise levels of its metabolite norfluoxetine.
All psychotropic drugs carry manufacturers’ warnings against concomitant use of any alcohol. Why? There are several reasons. First, from the standpoint of absorption and bioavailability, gastric emptying is accelerated by consuming low-content alcohol beverages (<15%; e.g., beer and wine) and delayed via high-alcohol-content beverages. Acute alcohol use also delays gastric emptying and small bowel transit time, while chronic use more likely accelerates gastric emptying and transit time in the small intestines. These factors could result in relatively higher or lower absorption and bioavailability of contemporaneously ingested psychotropic compounds. Second, pharmacokinetically, alcohol induces CYP450 enzymes, in turn accelerating the metabolism of hepatically cleared medications. First-pass metabolism is also thought to be lower in people who regularly drink significant amounts of alcohol, especially in women or people who take H2 blockers, due to decreased activity of alcohol dehydrogenase (Oneta et al., 1998). Alcohol in combination with opiates or benzodiazepines at sufficient quantities poses a significant risk for respiratory suppression and cardiovascular collapse. Finally, the CNS depressant effects of alcohol (and its eventual withdrawal) are at pharmacodynamic cross purposes with the intended effects of most psychotropic medications, very likely negating their intended benefits.
1 Manufacturers’ product inserts for all antipsychotics carry a boxed warning of an increased risk for all-cause mortality when used for dementia-related psychosis. The Beers Criteria® support this perspective “unless nonpharmacological options (e.g., behavioral interventions) have failed or are not possible and the older adult is threatening substantial harm to self or others.”
2 On the other hand, studies elsewhere have shown that baseline neurocognitive performance did not influence response versus nonresponse to short-term open-label trials of an SSRI or SNRI with subsequent SGA augmentation in late-life depression (Koenig et al., 2014).