Socio-demographic and clinical predictors of outcome to long-term treatment with lithium in bipolar disorders: a systematic review of the contemporary literature and recommendations from the ISBD/IGSLI Task Force on treatment with lithium
Abstract:Objective
To identify possible socio-demographic and clinical factors associated with Good Outcome (GO) as compared with Poor Outcome (PO) in adult patients diagnosed with Bipolar Disorder (BD) who received long-term treatment with lithium.
Methods
A comprehensive search of major electronic databases was performed to identify relevant studies that included adults patients (18 years or older) with a diagnosis of BD and reported sociodemographic and/… Show more
“…Furthermore, in clinical practice, Li response can be viewed as a dimensional rather than a categorical construct (Scott, Etain, Nierenberg & Bellivier, 2020). In this study, we chose to classify individuals into GR or NR groups as this was the most reported measure of Li response in a recent systematic review (Grillaut-Laroche, Etain, Severus, Scott, & Bellivier, 2020). However, other prospective assessments of Li response and those that measure continuous or categorical outcomes should be considered instead of or as well the Alda scale.…”
Background
Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).
Methods
Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).
Results
Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).
Conclusions
To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.
“…Furthermore, in clinical practice, Li response can be viewed as a dimensional rather than a categorical construct (Scott, Etain, Nierenberg & Bellivier, 2020). In this study, we chose to classify individuals into GR or NR groups as this was the most reported measure of Li response in a recent systematic review (Grillaut-Laroche, Etain, Severus, Scott, & Bellivier, 2020). However, other prospective assessments of Li response and those that measure continuous or categorical outcomes should be considered instead of or as well the Alda scale.…”
Background
Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).
Methods
Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).
Results
Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).
Conclusions
To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.
“…In 3 prospective studies (n = 101; n = 336; n = 442) rapid cycling course is predictive of poor response to lithium [ 59 - 61 ], but not to valproate in one of these [ 59 ]. History of rapid cycling is associated with poor outcome to lithium in 2 meta-analyses and in a review of respectively 20 (n = 2,054), 71 (n = 17,396), 34 (n = 12,602) studies [ 62 - 64 ]. Body of evidence is considered too inconsistent in a systematic review of 43 (n = 4,280) studies [ 65 ].…”
Section: Resultsmentioning
confidence: 99%
“…In a post hoc RCT (n = 165) analysis of the relationship between treatment response and the number of previous affective episodes find that > 3 depressive and > 11 maniac episodes are associated with poor lithium response but not to valproate response [ 68 ]. History of previous hospitalizations is considered predictive to poor outcome to lithium in a meta-analysis and in 2 systematic reviews [ 63 - 65 ], in prospective (n = 402) and RCT (n = 372) studies [ 61 , 69 ], related to an inferior outcome than valproate in one of these studies [ 69 ].…”
Since decades, lithium and valproate remain the pharmacological cornerstone to treat bipolar disorder. Different response patterns occur according to the phases of illness. At same time, individual pretreatment variables may concur to determine a specific drug-response. Our narrative review focuses on these two key clinical aspects to summarize the state of art. Information from i) clinical trials and ii) the most relevant international guidelines is collected to assess the clinical and preclinical factors that may guide the use of lithium rather than valproate. Lithium may be effective in treating acute mania, and lithium efficacy is maximized when used to prevent both manic and depressive episodes. Lithium may be a better treatment choice in patients with: positive family history for bipolar disorder, mania-depression-interval pattern, few previous affective episodes/hospitalizations, high risk for suicide, no comorbidities. Valproate may be more effective as antimanic rather than prophylactic agent. Valproate might be a better choice in patients with many previous affective episodes/hospitalizations and psychiatric comorbidities. Finally, neither lithium nor valproate are suggested for the treatment of acute mixed states or bipolar depression. To consider clinical and preclinical factors may thus be useful to select the best treatment strategy.
“…Pharmacogenetic studies are attempting to identify response or tolerability biomarkers, but the process of cherry-picking candidate genes has been proven not to be ideal considering the size of the human genome [ 2 ]. Favorable response is more likely for patients with a BD-I diagnosis, few comorbidities, manic/hypomanic-depression-euthymic interval cycle pattern, early age of symptom onset and treatment onset, family history of BD, and adequate drug adherence [ 8 , 9 , 10 ]. Familial clusters may be a prognosticator for recurrent mood episodes due to patients with good lithium response tending to cluster in families, but alone this datum holds little weight [ 11 ].…”
Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.
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