Lithium plus antipsychotics or anticonvulsants for bipolar disorder: Comparing clinical response and metabolic changes.

OBJECTIVE: Patients with bipolar disorder treated with lithium often require additional antipsychotics or anticonvulsants. However, the comparative effectiveness and safety of these agents as add-on to lithium has not been studied. METHODS: This secondary analysis combined two similar 24-week trials on outpatients with bipolar disorder randomized to lithium (target serum level 0.4-0.6 mEq/L). Guideline-based adjunctive antipsychotics (Li+AP) and anticonvulsants (Li+AC) could be used if clinically indicated and was assessed at every study visit. Response was measured on the Clinical Global Impression scale and we performed adjusted mixed effects linear regression analyses. Analysis of variance tests compared metabolic measures including a binary diagnosis of metabolic syndrome before and after 24 weeks of treatment. RESULTS: Among 379 outpatients (57% female, mean age 38 years, mean Clinical Global Impression 4.4), users of Li+AP (N = 50, primarily quetiapine and aripiprazole) improved to a similar degree (mean Clinical Global Impression improvement = 1.6, standard deviation = 1.5) as those using lithium-only (i.e. without adjunctive antipsychotics or anticonvulsants, N = 149, mean Clinical Global Impression improvement = 1.7, standard deviation = 1.4) (p = 0.59). Users of Li+AC (N = 107, primarily lamotrigine and valproate, mean Clinical Global Impression improvement = 1.2, standard deviation = 1.3) and users of Li+AP+AC (N = 73, mean Clinical Global Impression improvement = 1.1, standard deviation = 1.3) showed worse response compared to lithium-only users (all p < 0.01). When comparing Li+AP to Li+AC, users of Li+AP improved slightly better on general (p = 0.05) and manic symptoms (p = 0.01), but showed a worse development of glucose, triglycerides, and metabolic syndrome. CONCLUSION: Despite treatment-by-indication confounding, these findings are relevant for real-world treatment settings and emphasize the need for randomized trials on this clinically important topic.

Childhood trauma and treatment outcomes during mood-stabilising treatment with lithium or quetiapine among outpatients with bipolar disorder.

BACKGROUND: Childhood trauma affects the course of mood disorders. Researchers are now considering childhood trauma as an influential factor in the treatment of mood disorders. However, the role of childhood trauma in the treatment of bipolar disorder remains understudied. METHODS: The effect of childhood trauma on treatment outcomes was evaluated among participants randomised to treatment with lithium or quetiapine in the Clinical and Health Outcomes Initiatives in Comparative Effectiveness for Bipolar Disorder (Bipolar CHOICE) study by clinician assessment. Mixed effects linear regression models were used to analyse rates of improvement in symptom severity (assessed with the Bipolar Inventory of Symptoms Scale and the Clinical Global Impression Scale for Bipolar Disorder) and functional impairment (assessed with the Longitudinal Interval Follow-up Evaluation-Range of Impaired Functioning Tool). RESULTS: A history of any childhood trauma was reported by 52.7% of the sample (N = 476). Although participants with a history of any childhood trauma presented with greater symptom severity and functional impairment at most study visits, participants with and without a history of any childhood trauma showed similar rates of improvement in symptom severity and functional impairment over the 24 weeks of treatment. CONCLUSION: This is the first study to explore the association between childhood trauma and treatment outcomes during treatment with lithium or quetiapine in the context of a randomised trial. In Bipolar CHOICE, a history of childhood trauma did not inhibit improvement in symptom severity or functional impairment. Nevertheless, these findings need replication across different settings.

Cardiometabolic risk markers during mood-stabilizing treatment: Correlation with drug-specific effects, depressive symptoms and treatment response.

BACKGROUND: Patients with bipolar disorder have higher rates of cardiometabolic comorbidities and mortality. Although guidelines emphasize the importance of cardiovascular monitoring, few studies characterized the cardiometabolic risk profile during treatment and their relation to symptomatology and treatment response. METHODS: We analyzed data from two similar 24-weeks comparative effectiveness trials, with a combined sample of 770 participants randomized to two different lithium doses, quetiapine (300 mg/day), or standard treatment without lithium. Glucose, lipids and vital signs were measured before and after 24 weeks of treatment. We calculated several cardiovascular risk scores, assessed baseline correlations and compared the four treatment arms via multiple linear regression models. RESULTS: Higher cholesterol and LDL levels were associated with greater depression severity, showing differential correlations to specific symptoms, particularly agitation, low energy and suicidality. Those randomized to quetiapine showed a significant worsening of cardiometabolic markers during the 24-week trial. Neither baseline nor change in lipid levels correlated with differential treatment response. LIMITATIONS: Study duration was short from the perspective of cardiometabolic risk markers, and all treatment arms included patients taking adjunct antipsychotics. The trials compared quetiapine to lithium, but not to other medications known to affect similar risk factors. CONCLUSIONS: Treatment with 300 mg/day quetiapine for 24 weeks, representing a short and common dose course, resulted in increased cardiometabolic risk markers, emphasizing the importance of monitoring during mood-stabilizing treatment. The symptom-specific associations are in line with previous studies in unipolar depression, suggesting a cardiometabolic-depression link that needs to be further studied in bipolar depression.

Response and remission rates during 24 weeks of mood-stabilizing treatment for bipolar depression depending on early non-response.

BACKGROUND: We aimed to study the probability of bipolar depression response at 24 weeks given initial non-response. METHODS: We combined two multi-site, 24-week trials including similar populations following the same evidence-based guidelines randomizing patients to lithium or quetiapine. Additional mood-stabilizing treatment was possible if clinically indicated. We report cumulative proportions of response (>50% improvement in MADRS) and remission (MADRS<10). RESULTS: We included 592 participants with bipolar depression (mean 39 years, 59% female, mean MADRS 25). Among 393 (66%) participants without response after 2 weeks, 46% responded by 24 weeks; for 291 (49%) without response at 4 weeks, 40% responded and 33% remitted by 24 weeks; for 222 (38%) without a response at 6 weeks, 36% responded and 29% remitted by 24 weeks; for 185 (31%) without a response at 8 weeks, 29% responded and 24% remitted by 24 weeks. Rates were similar for participants who had started an additional mood-stabilizing drug during the first 6 or 8 weeks. CONCLUSIONS: Among patients with bipolar depression and non-response after 6 weeks treatment, representing an adequate bipolar depression trial, only one-third responded by 24 weeks. These results highlight the need for better treatment alternatives for non-responders to evidence-based treatments for bipolar depression.

Adjunctive antidepressant treatment among 763 outpatients with bipolar disorder: Findings from the Bipolar CHOICE and LiTMUS trials.

BACKGROUND: Adjunctive antidepressants are frequently used for bipolar depression but their clinical efficacy has been studied in few trials and little is known about how co-occurring manic symptoms affect treatment response. METHODS: Bipolar Clinical Health Outcomes Initiative in Comparative Effectiveness (N = 482) and Lithium Treatment Moderate-Dose Use Study (N = 281) were similar comparative effectiveness trials on outpatients with bipolar disorder comparing four different randomized treatment arms with adjunctive personalized guideline-based treatment for 24 weeks. Adjunctive antidepressant treatment could be used if clinically indicated and was assessed at every study visit. Adjusted mixed effects linear regression analyses compared users of antidepressants to nonusers overall and in different subcohorts. RESULTS: Of the 763 patients, 282 (37.0%) used antidepressant drugs during the study. Antidepressant users had less improvement compared to nonusers on the Clinical Global Impression Scale for Bipolar Disorder and on measures of depression. This was particularly true among patients with co-occurring manic symptoms. Exclusion of individuals begun on antidepressants late in the study (potentially due to overall worse response) resulted in no differences between users and nonusers. We found no differences in treatment effects on mania scales. CONCLUSIONS: In this large cohort of outpatients with bipolar disorder, clinically indicated and guideline-based adjunctive antidepressant treatment was not associated with lower depressive symptoms or higher mania symptoms. The treatment-by-indication confounding due to the nonrandomized design of the trials complicates causal interpretations, but no analyses indicated better treatment effects of adjunctive antidepressants.

Response to SSRI intervention and amygdala activity during self-referential processing in major depressive disorder.

There are conflicting reports on the impact of antidepressants on neural reactions for positive information. We thus hypothesized that there would be clinically important individual differences in neural reactivity to positive information during SSRI therapy. We further predicted that only those who responded to SSRIs would show increased amygdala reactivity to positive information following treatment to a level similar to that seen in healthy participants. Depressed individuals (n = 17) underwent fMRI during performance of a task involving rating the self-relevance of emotionally positive and negative cue words before and after receiving 12 weeks of SSRI therapy. At post-treatment, SSRI responders (n = 11) had increased amygdala activity in response to positive stimuli, and decreased activity in response to negative stimuli, compared to non-responders (n = 6). Results suggest that normalizing amygdala responses to salient information is a correlate of SSRI efficacy. Second line interventions that modulate amygdala activity, such as fMRI neurofeedback, may be beneficial in those who do not respond to SSRI medications.

Familial severe psychiatric history in bipolar disorder and correlation with disease severity and treatment response.

BACKGROUND: Bipolar disorder is a heritable disorder, and we aimed to assess the impact of family history of mental disorders in first-degree relatives on the severity and course of bipolar disorder. METHODS: The Bipolar CHOICE (lithium versus quetiapine) and LiTMUS (optimized treatment with versus without lithium) comparative effectiveness studies were similar trials among bipolar disorder outpatients studying four different randomized treatment arms for 24 weeks. Patients self-reported on six severe mental disorders among first-degree relatives. We performed ANOVA and linear regression regarding disease severity measures, sociodemographic and cardiometabolic markers and mixed effects linear regression to evaluate treatment response. RESULTS: Among 757 patients, 644 (85.1%) reported at least one first-degree relative with a severe mental disorder (mean=2.8; standard deviation=2.2; range=0-13). Depression (67.1%), alcohol abuse (51.0%) and bipolar disorder (47.0%) were the most frequently reported disorders. Familial psychiatric history correlated with several disease severity measures (hospitalizations, suicide attempts, and earlier onset) and sociodemographic markers (lower education and household income) but not with cardiometabolic markers (e.g. cholesterol or waist circumference) or cardiovascular risk scores, e.g. the Framingham risk score. Patients with familial psychiatric history tended to require more psychopharmacological treatment (p=0.054) but responded similarly (all p>0.1) to all four treatment arms. CONCLUSIONS: Our findings indicate that familial psychiatric history is common among outpatients with bipolar disorder and correlates with disease severity and sociodemographic measures. Patients with a greater familial psychiatric load required more intense treatment but achieved similar treatment responses compared to patients without familial psychiatric history.

The impact of binge eating behavior on lithium- and quetiapine-associated changes in body weight, body mass index, and waist circumference during 6 months of treatment: Findings from the bipolar CHOICE study.

BACKGROUND: Lithium and quetiapine can cause weight gain, but their comparative longer term anthropometric effects are unknown, as are the potential moderating effects of baseline binge-eating (BE) behavior. METHODS: We assessed 6 month changes in body weight, body mass index (BMI) and waist circumference in 482 adults with DSM-IV bipolar disorders who participated in a comparative effectiveness study of lithium and quetiapine with evidence-based adjunctive treatment (Bipolar CHOICE). Anthropometric measurements were obtained at baseline, and at 2, 4, 6, 8, 12, 16, 20, and 24 weeks. BE behavior was defined as affirmative responses to MINI items M1 and M3 at baseline. Data were analyzed using a mixed model repeated measures approach, adjusted for baseline values of dependent measures. RESULTS: On average, body weight and BMI increased over 6 months with lithium and quetiapine. However, those treated with quetiapine experienced greater increases from baseline in body weight (peak change, + 3.6 lbs. vs. + 1.4 lbs.) and BMI (peak change, + 0.6 kg/m2 vs. + 0.3 kg/m2), starting at 2 weeks (group x time, F8,3052 = 2.9, p = 0.003 for body weight, F8,3052 = 3.0, p = 0.002 for BMI). Significant increases in waist circumference were observed only with quetiapine. The relationship between drug treatment and changes in body weight (group x time x binge eating status, F1,2770 = 2.0, p = 0.002), BMI (F1,2767 = 2.0, p = 0.002), and waist circumference (women only, F25,1621 = 2.9, p < 0.0001) were moderated by BE behavior. The largest increases over 24 weeks in body weight and BMI, and waist circumference in women, occurred for quetiapine-treated patients with baseline binge-eating, relative to quetiapine-treated patients without binge eating and lithium-treated patients with or without baseline binge-eating. LIMITATIONS: Bipolar CHOICE was not designed to study anthropometric outcomes. CONCLUSIONS: Greater changes in body weight, BMI, and waist circumference occurred with quetiapine- versus lithium-based treatment over 6 months of treatment. The effects of study drugs on these anthropometric measures were moderated by BE behavior at baseline.

Correlation between white blood cell count and mood-stabilising treatment response in two bipolar disorder trials.

BACKGROUND: Immune system markers may predict affective disorder treatment response, but whether an overall immune system marker predicts bipolar disorder treatment effect is unclear. METHODS: Bipolar CHOICE (N = 482) and LiTMUS (N = 283) were similar comparative effectiveness trials treating patients with bipolar disorder for 24 weeks with four different treatment arms (standard-dose lithium, quetiapine, moderate-dose lithium plus optimised personalised treatment (OPT) and OPT without lithium). We performed secondary mixed effects linear regression analyses adjusted for age, gender, smoking and body mass index to investigate relationships between pre-treatment white blood cell (WBC) levels and clinical global impression scale (CGI) response. RESULTS: Compared to participants with WBC counts of 4.5-10 × 109/l, participants with WBC < 4.5 or WBC ≥ 10 showed similar improvement within each specific treatment arm and in gender-stratified analyses. CONCLUSIONS: An overall immune system marker did not predict differential treatment response to four different treatment approaches for bipolar disorder all lasting 24 weeks.

Patterns of changes in bipolar depressive symptoms revealed by trajectory analysis among 482 patients with bipolar disorder.

INTRODUCTION: Depressive episodes are often prevalent among patients with bipolar disorder, but little is known regarding the differential patterns of development over time. We aimed to determine and characterize trajectories of depressive symptoms among adults with bipolar disorder during 6 months of systematic treatment. METHODS: The pragmatic clinical trial, Bipolar Clinical Health Outcomes Initiative in Comparative Effectiveness (CHOICE), randomized 482 outpatients with bipolar disorder to lithium or quetiapine. Depressive symptoms were rated at up to 9 visits using the Montgomery-Asberg Depression Rating Scale (MADRS). Growth mixture modeling was utilized to identify trajectories and multinomial regression analysis estimated associations with potential predictors. RESULTS: Four distinct trajectories of depressive symptoms were identified. The responding class (60.3%) with a rapid reduction and subsequent low level; the partial-responding class (18.4%) with an initial reduction followed by an increase during the remaining weeks; the fluctuating class (11.6%) with a fluctuation in depressive symptoms; and the non-responding class (9.7%) with sustained moderate-severe depressive symptoms. Bipolar type I predicted membership of the non-responding class and randomization to quetiapine predicted membership of either the responding or the non-responding class. CONCLUSION: Approximately 30% experienced a partial or fluctuating course, and almost 10% had a chronic course with moderate-severe depression during 6 months. Patients diagnosed with bipolar type 1 had higher risk of being categorized into a class with a worse outcome. While no differences in average overall outcomes occurred between the lithium and quetiapine groups, trajectory analysis revealed that the lithium group had more variable courses.

Comorbid anxiety in bipolar CHOICE: Insights from the bipolar inventory of symptoms scale.

BACKGROUND: Approximately 86-89% of patients with BD have a comorbid anxiety disorder associated with poor quality of life and reduced likelihood of recovery from an acute mood episode. The purpose of this study is to assess the prevalence and impact of comorbid anxiety using the Bipolar Inventory of Symptoms Scale (BISS) in patients with BD who participated in a 6-month pragmatic trial. METHODS: Participants (N = 482) in the Bipolar Clinical Health Outcomes Initiative in Comparative Effectiveness (CHOICE) study were adults with BD I or II. Anxiety diagnoses were assessed with the MINI. Global illness severity was assessed using the Clinical Global Impression-Bipolar Version. Mood symptoms and anxiety severity were assessed using the BISS. RESULTS: 61% of the study sample met criteria for a current anxiety disorder. Patients with a higher BISS anxiety score at baseline had a higher overall BD illness severity, depressive severity, and manic episode severity (p < 0.001). A single cutoff value of BISS anxiety had great sensitivity, yet poor specificity for determining a comorbid anxiety diagnosis. There were no significant differences in outcomes for individuals treated for anxiety disorders with anxiolytics compared with those who were not treated with anxiolytics. LIMITATIONS: Sample size limitations prevented an analysis of whether the BISS cutoff score of 10 performed differently across varied anxiety disorders. CONCLUSIONS: Given its ability to identify patients with co-occurring anxiety, the BISS anxiety subscale shows clinical utility as a screening measure though its application as a clinical assessment measure may not be advisable.

Sleep disturbance may impact treatment outcome in bipolar disorder: A preliminary investigation in the context of a large comparative effectiveness trial.

BACKGROUND: Bipolar patients experience sleep disturbances during and between mood episodes. Yet the impact of sleep on treatment with different medications has not been fully explored. The purpose of this paper is to explore the potential impact of poor sleep at baseline on outcomes in a randomized effectiveness trial of quetiapine and lithium. METHODS: The Bipolar CHOICE study was a 6-month, parallel group, multisite randomized controlled trial. Participants with bipolar disorder (N = 482; 59% female and age 18-70 years) received quetiapine or lithium. Patients were allowed to also receive adjunctive personalized treatments, which were guideline-informed, empirically-based medications added to treatment as needed. Medication changes were recorded as necessary clinical adjustments (NCA). Fisher's exact tests, mixed-regression models, and Mann-Whitney U tests were used to assess demographic and clinical characteristics as well as whether sleep disturbance would predict outcomes. RESULTS: 63% of patients had baseline sleep disturbance. Individuals with sleep disturbance had worse bipolar illness severity, greater severity of depression, mania, anxiety, irritability, and psychosis, were less likely to have sustained response (17% vs. 29%; adjusted RR: 0.55, 95% CI: 0.38-0.78, p = 0.0006) and had more NCAs (median 0.71 vs. 0.59, p = 0.03). LIMITATIONS: Our findings were limited by how we defined sleep disturbance, and by how severity of sleep disturbance was assessed with one item with a non-sleep specific measure. CONCLUSIONS: Baseline sleep disturbance was associated with more severe bipolar symptoms and worse 6-month outcomes. Further research is warranted on improving sleep in bipolar disorder, especially the role of psychosocial interventions.

Trajectories of suicidal ideation over 6 months among 482 outpatients with bipolar disorder.

INTRODUCTION: Suicidal ideation occurs frequently among individuals with bipolar disorder; however, its course and persistence over time remains unclear. We aimed to investigate 6-months trajectories of suicidal ideation among adults with bipolar disorder. METHODS: The Bipolar CHOICE study randomized 482 outpatients with bipolar disorder to 6 months of lithium- or quetiapine-based treatment including other psychotropic medications as clinically indicated. Participants were asked at 9 visits about suicidal ideation using the Concise Health Risk Tracking scale. We performed latent Growth Mixture Modelling analysis to empirically identify trajectories of suicidal ideation. Multinomial logistic regression analyses were applied to estimate associations between trajectories and potential predictors. RESULTS: We identified four distinct trajectories. The Moderate-Stable group represented 11.1% and was characterized by constant suicidal ideation. The Moderate-Unstable group included 2.9% with persistent thoughts about suicide with a more fluctuating course. The third (Persistent-low, 20.8%) and fourth group (Persistent-very-low, 65.1%) were characterized by low levels of suicidal ideation. Higher depression scores and previous suicide attempts (non-significant trend) predicted membership of the Moderate-Stable group, whereas randomized treatment did not. LIMITATIONS: No specific treatments against suicidal ideation were included and suicidal thoughts may persist for several years. CONCLUSION: More than one in ten adult outpatients with bipolar disorder had moderately increased suicidal ideation throughout 6 months of pharmacotherapy. The identified predictors may help clinicians to identify those with additional need for treatment against suicidal thoughts and future studies need to investigate whether targeted treatment (pharmacological and non-pharmacological) may improve the course of persistent suicidal ideation.

Clinical correlates of acute bipolar depressive episode with psychosis.

BACKGROUND: Psychotic bipolar depressive episodes remain remarkably understudied despite being common and having a significant impact on bipolar disorder. The aim of this study is to identify the characteristics of depressed bipolar patients with current psychosis compared to those without psychosis. METHODS: We used baseline data of a comparative effectiveness study of lithium and quetiapine for bipolar disorder (the Bipolar CHOICE study) to compare demographic, clinical, and functioning variables between those with and without psychotic symptoms. Of the 482 participants, 303 (62.9%) were eligible for the present study by meeting DSM-IV criteria for an acute bipolar depressive episode. Univariate analyses were conducted first, and then included in a model controlling for symptom severity. RESULTS: The sample was composed mostly of women (60.7%) and the mean age was 39.5±12.1 years. Psychosis was present in 10.6% (n=32) of the depressed patients. Psychotic patients had less education, lower income, and were more frequently single and unemployed. Psychosis was also associated with a more severe depressive episode, higher suicidality, more comorbid conditions and worse functioning. Most group differences disappeared when controlling for depression severity. LIMITATIONS: Only outpatients were included and the presence of psychosis in previous episodes was not assessed. CONCLUSION: Psychosis during bipolar depressive episodes is present even in an outpatient sample. Psychotic, depressed patients have worse illness outcomes, but future research is necessary to confirm if these outcomes are only associated with the severity of the disorder or if some of them are independent of it.

Bipolar mixed features - Results from the comparative effectiveness for bipolar disorder (Bipolar CHOICE) study.

BACKGROUND: DSM-5 changed the criteria from DSM-IV for mixed features in mood disorder episodes to include non-overlapping symptoms of depression and hypomania/mania. It is unknown if, by changing these criteria, the same group would qualify for mixed features. We assessed how those meeting DSM-5 criteria for mixed features compare to those meeting DSM-IV criteria. METHODS: We analyzed data from 482 adult bipolar patients in Bipolar CHOICE, a randomized comparative effectiveness trial. Bipolar diagnoses were confirmed through the MINI International Neuropsychiatric Interview (MINI). Presence and severity of mood symptoms were collected with the Bipolar Inventory of Symptoms Scale (BISS) and linked to DSM-5 and DSM-IV mixed features criteria. Baseline demographics and clinical variables were compared between mood episode groups using ANOVA for continuous variables and chi-square tests for categorical variables. RESULTS: At baseline, the frequency of DSM-IV mixed episodes diagnoses obtained with the MINI was 17% and with the BISS was 20%. Using DSM-5 criteria, 9% of participants met criteria for hypomania/mania with mixed features and 12% met criteria for a depressive episode with mixed features. Symptom severity was also associated with increased mixed features with a high rate of mixed features in patients with mania/hypomania (63.8%) relative to those with depression (8.0%). LIMITATIONS: Data on mixed features were collected at baseline only and thus do not reflect potential patterns in mixed features within this sample across the study duration. CONCLUSIONS: The DSM-5 narrower, non-overlapping definition of mixed episodes resulted in fewer patients who met mixed criteria compared to DSM-IV.

Poor quality of life and functioning in bipolar disorder.

BACKGROUND: This study explores the association of demographic and clinical features with quality of life and functioning in individuals with bipolar disorder. METHODS: Adult participants (N = 482) with bipolar I or II disorder were enrolled in a comparative effectiveness study across eleven study sites and completed baseline measures of medical and psychiatric history, current mood, quality of life, and functioning. Participants with at least mildly depressive or manic/hypomanic symptomatic severity were randomized to receive lithium or quetiapine in addition to adjunctive personalized treatment for 6 months. RESULTS: Participants with more severe depressive and irritability symptoms had lower quality of life and higher functional impairment. All psychiatric comorbid conditions except substance use disorder were associated with worse quality of life. On average, females had lower quality of life than males. Patients who were married, living as married, divorced, or separated had worse functional impairment compared with patients who were single or never married. A composite score of social disadvantage was associated with worse functioning and marginally associated with worse quality of life. Symptom severity did not moderate the effect of social disadvantage on quality of life or functioning. CONCLUSIONS: Our findings highlight that depression, irritability, and psychiatric comorbid conditions negatively impact quality of life and functioning in bipolar disorder. The study suggests that individuals with social disadvantage are at risk for functional impairment. Trial Registration This study is registered with ClinicalTrials.gov. Identification number: NCT01331304.

Nonsteroidal anti-inflammatory drugs (NSAIDs) and paracetamol do not affect 6-month mood-stabilizing treatment outcome among 482 patients with bipolar disorder.

BACKGROUND: Many mood disorder patients need analgesics due to increased pain sensitivity. Recent studies have suggested that nonsteroidal anti-inflammatory drugs (NSAIDs) may inhibit antidepressant treatment, which requires replication before clinical recommendations. METHODS: The Clinical and Health Outcomes Initiatives in Comparative Effectiveness for Bipolar Disorder Study randomized participants to 6 months lithium or quetiapine treatment. Use of NSAIDs and paracetamol was assessed throughout the study period and psychopathology measured with the Clinical Global Impression Scale for Bipolar Disorder (CGI-BP) and Bipolar Inventory of Symptoms Scale (BISS). The effects of NSAIDs and paracetamol on treatment outcome were examined using mixed effects linear regression adjusted for age, gender, body mass index, smoking status, exercise, and somatic diseases. RESULTS: Among 482 participants, 177 (36.7%) used NSAIDs and/or paracetamol during the study. NSAID and paracetamol users did not differ from nonusers with respect to treatment outcome with lithium or quetiapine at any time point during 6 months treatment on the overall CGI-BP (ß = 0.001 (95% CI = -0.01 to -0.01), P = .87), the BISS (ß = 0.01 (95% CI = -0.17 to 0.15), P = .91), nor the CGI-BP subscales for depression or mania. Users of NSAIDs only (n = 76), paracetamol only (n = 62), and users of both NSAIDs and paracetamol (n = 39) showed no statistical difference compared to nonusers (all P > .3). CONCLUSIONS: This is the first trial to show that use of NSAIDs and paracetamol, alone or in combination, does not affect lithium- or quetiapine-based bipolar disorder mood-stabilizing treatment outcomes. Prior studies have suggested that NSAIDs may inhibit antidepressant treatment, whereas our results support findings indicating no detrimental effects of NSAIDs or paracetamol on affective disorder treatment.

White blood cell count correlates with mood symptom severity and specific mood symptoms in bipolar disorder.

OBJECTIVE: Immune alterations may play a role in bipolar disorder etiology; however, the relationship between overall immune system functioning and mood symptom severity is unknown. METHODS: The two comparative effectiveness trials, the Clinical and Health Outcomes Initiatives in Comparative Effectiveness for Bipolar Disorder Study (Bipolar CHOICE) and the Lithium Treatment Moderate-Dose Use Study (LiTMUS), were similar trials among patients with bipolar disorder. At study entry, white blood cell count and bipolar mood symptom severity (via Montgomery-Aasberg Depression Rating Scale and Bipolar Inventory of Symptoms Scale) were assessed. We performed analysis of variance and linear regression analyses to investigate relationships between deviations from median white blood cell and multinomial regression analysis between higher and lower white blood cell levels. All analyses were adjusted for age, gender, body mass index, smoking, diabetes, hypertension and hyperlipidemia. RESULTS: Among 482 Bipolar CHOICE participants, for each 1.0 × 109/L white blood cell deviation, the overall Bipolar Inventory of Symptoms Scale severity increased significantly among men (coefficient = 2.13; 95% confidence interval = [0.46, -3.79]; p = 0.013), but not among women (coefficient = 0.87; 95% confidence interval = [-0.87, -2.61]; p = 0.33). Interaction analyses showed a trend toward greater Bipolar Inventory of Symptoms Scale symptom severity among men (coefficient = 1.51; 95% confidence interval = [-0.81, -3.82]; p = 0.2). Among 283 LiTMUS participants, higher deviation from the median white blood cell showed a trend toward higher Montgomery-Aasberg Depression Rating Scale scores among men (coefficient = 1.33; 95% confidence interval = [-0.22, -2.89]; p = 0.09), but not among women (coefficient = 0.34; 95% confidence interval = [-0.64, -1.32]; p = 0.50). When combining LiTMUS and Bipolar CHOICE, Montgomery-Aasberg Depression Rating Scale scores increased significantly among men (coefficient = 1.09; 95% confidence interval = [0.31, -1.87]; p = 0.006) for each 1.0 × 109/L white blood cell deviation, whereas we found a weak association among women (coefficient = 0.55; 95% confidence interval = [-0.20, -1.29]; p = 0.14). Lower and higher white blood cell levels correlated with greater symptom severity and specific symptoms, varying according to gender. CONCLUSION: Deviations in an overall immune system marker, even within the normal white blood cell range, correlated with mood symptom severity in bipolar disorder, mostly among males. Studies are warranted investigating whether white blood cell count may predict response to mood-stabilizing treatment.

Tracking medication changes to assess outcomes in comparative effectiveness research: A bipolar CHOICE study.

BACKGROUND: Comparative effectiveness research uses multiple tools, but lacks outcome measures to assess large electronic medical records and claims data. Aggregate changes in medications in response to clinical need may serve as a surrogate outcome measure. We developed the Medication Recommendation Tracking Form (MRTF) to record the frequency, types, and reasons for medication adjustments in order to calculate Necessary Clinical Adjustments (NCAs), medication adjustments to reduce symptoms, maximize treatment response, or address problematic side effects. METHODS: The MRTF was completed at every visit for 482 adult patients in Bipolar CHOICE, a 6-month randomized comparative effectiveness trial. RESULTS: Responders had significantly fewer NCAs compared to non-responders. NCAs predicted subsequent response status such that every additional NCA during the previous visit decreased a patient's odds of response by approximately 30%. Patients with more severe symptoms had a greater number of NCAs at the subsequent visit. Patients with a comorbid anxiety disorder demonstrated a significantly higher rate of NCAs per month than those without a comorbid anxiety disorder. Patients with greater frequency, intensity, and interference of side effects had higher rates of NCAs. Participants with fewer NCAs reported a higher quality of life and decreased functional impairment. LIMITATIONS: The MRTF has not been examined in community clinic settings and did not predict response more efficiently than the Clinical Global Impression-Bipolar Version (CGI-BP). CONCLUSIONS: The MRTF is a feasible proxy of clinical outcome, with implications for clinical training and decision-making. Analyses of big data could use changes in medications as a surrogate outcome measure.