Clinical correlates associated with the long-term response of bipolar disorder patients to lithium, valproate or lamotrigine: A retrospective study

Authors: Young Sup Woo aff001;  Bo-Hyun Yoon aff002;  Jye-Heon Song aff002;  Jeong Seok Seo aff003;  Beomwoo Nam aff003;  Kwanghun Lee aff004;  Jonghun Lee aff005;  Young-Eun Jung aff006;  Moon-Doo Kim aff006;  Jung Goo Lee aff007;  Sheng-Min Wang aff001;  Young-Joon Kwon aff009;  Won-Myong Bahk aff001
Authors place of work: Department of Psychiatry, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea aff001;  Department of Psychiatry, Naju National Hospital, Naju, Republic of Korea aff002;  Department of Psychiatry, School of Medicine, Konkuk University, Chungju, Republic of Korea aff003;  Department of Psychiatry, College of Medicine, Dongguk University, Gyeongju, Republic of Korea aff004;  Department of Psychiatry, School of Medicine, Catholic University of Daegu, Daegu, Republic of Korea aff005;  Department of Psychiatry, School of Medicine, Jeju National University, Jeju, Republic of Korea aff006;  Department of Psychiatry, Haeundae Paik Hospital, Paik Institute for Clinical Research, College of Medicine, Inje University, Busan, Republic of Korea aff007;  Department of Health Science and Technology, Graduate School of Inje University, Busan, Republic of Korea aff008;  Department of Psychiatry, College of Medicine, Soonchunhyang University, Cheonan, Republic of Korea aff009
Published in the journal: PLoS ONE 15(1)
Category: Research Article
doi: 10.1371/journal.pone.0227217



Although mood stabilizers such as lithium (LIT), valproate (VAL), and lamotrigine (LMT) appear to be efficacious treatments for bipolar disorder (BD) in research settings, the long-term response to these mood stabilizers in clinical practice is highly variable among individuals. Thus, the present study examined the characteristics associated with good or insufficient responses to long-term treatment with LIT, VAL, or LMT for BD.


This study retrospectively analyzed the medical records of patients who visited an outpatient clinic with a diagnosis of BD I or II. Data from patients who were treated with one of three mood stabilizing medications (LIT, VAL, or LMT) for more than 6 months were selected, and the long-term treatment responses were evaluated using the Alda scale. For the purposes of this study, two response categories were formed: insufficient response (ISR), including non-response or poor response (Alda total score ≤ 6), and good response (GR; Alda total score ≥ 7).


Of the 645 patients included in the present study, 172 were prescribed LIT, 320 were prescribed VAL, and 153 were prescribed LMT for at least 6 months. A binary logistic regression analysis revealed that a diagnosis of BD II (odds ratio [OR], 8.868; 95% confidence interval [CI], 1.123–70.046; p = 0.038), comorbid alcohol/substance use disorder (OR, 4.238; 95% CI, 1.154–15.566; p = 0.030), and a history of mixed episodes (OR, 4.363; 95% CI, 1.191–15.985; p = 0.026) were significant predictors of LIT-ISR. Additionally, a depressive-predominant polarity significantly predicted LMT-GR (OR, 8.586; 95% CI, 2.767–26.644; p < 0.001).


The present findings demonstrated that patients with a diagnosis of BD II, a comorbid alcohol/substance problem, or a history of mixed episodes were not likely to respond to LIT treatment. Additionally, LMT might be a better treatment choice for patients with a depressive-predominant polarity.


Drug therapy – Drug metabolism – Cognitive impairment – depression – Antipsychotics – Bipolar disorder – antidepressants – Lithium


Bipolar disorder (BD) is a severe and common chronic illness associated with high risks of relapse and recurrence as well as increased morbidity and mortality [1, 2]. Similar to schizophrenia, BD is considered to be a condition that tends to worsen with recurrence and prolongation of the illness [3, 4]. Accordingly, BD patients with a higher number of previous episodes tend to experience higher rates of disability, greater impairments in cognitive and interpersonal functioning, and a poorer overall quality of life [5, 6]. These findings suggest that long-term maintenance treatments are of paramount importance to prevent subsequent episodes, reduce residual symptoms, and restore functioning and quality of life [7, 8].

Even though several recent BD treatment guidelines suggest first- and second-line treatments based on evidence of established long-term relapse/recurrence prevention [8, 9], clinicians often rely on a trial-and-error approach to choose from among the therapeutic alternatives. However, this approach may result in the risk of a recurrence or breakthrough [10, 11]. Thus, the prediction of long-term mood stabilization effect to specific medications could substantially reduce the risk of a breakthrough or recurrence.

The potential predictors of the long-term prophylactic response to lithium (LIT) have been widely investigated. A positive long-term prophylactic response to lithium can be predicted in patients with euphoric mania, an episodic pattern characterized by a ‘mania-depression-interval’ of the clinical course (a biphasic course in which depressive episodes occur within weeks after manias, and are then followed by illness-free intervals), an intermediate age of onset, a family history of BD, or a family history of LIT response [12, 13]. Conversely, predictors of a poor response to lithium treatment include a high number of previous hospitalizations, continuous cycling, atypical mixed or psychotic features (especially mood-incongruent psychosis), an episodic pattern of ‘depression-mania-interval’ of the clinical course, or BD II [12, 14, 15]. However, the predictors long-term prophylactic response to other agents widely used for the treatment of BD, such as valproate (VAL) or lamotrigine (LMT), remain poorly investigated.

Only a few studies have reported a relatively good response to VAL in the presence of rapid cycling course, multiple prior episodes, or comorbid substance abuse [1620]. Likewise, few studies have observed a good response to LMT with a predominantly depressive polarity or comorbid anxiety [21, 22], or BD II [8]. However, these clinical predictors of the long-term mood stabilizing effect fail to provide conclusive evidence either in support of or in opposition to the practice [23].

Therefore, the present study used the Alda scale [13], which was designed to retrospectively assess treatment responses, to examine the demographic and clinical characteristics associated with the long-term mood stabilization effect of LIT, VAL, and LMT, three agents that are commonly recommended for the treatment of BD [24],


Subjects and assessments

The present study retrospectively investigated the medical records of patients who visited an outpatient clinic at one of seven investigation sites (six university hospitals and one mental hospital) from January 2017 to October 2018 with a diagnosis of BD I or II according to the DSM-IV-TR. Data were selected from patients who were age 20 or older. The data of patients who had been treated with one of the three mood stabilizing medications (LIT, VAL, or LMT) for more than 6 months were collected. Patients with insufficient data, who had a severe comorbid medical or neurological condition that could contribute to mood symptoms, who were treated with a combination of mood stabilizers and anticonvulsants (e.g., LIT, VAL, or LMT and carbamazepine, oxcarbazepine, or topiramate), and/or who had a diagnosis of a mood disorder due to a general medical condition were excluded from the analyses.

Long-term treatment responses were evaluated using the Alda scale [13], which was specifically developed to evaluate the long-term mood stabilization effect under naturalistic conditions. This scale measures the degree of improvement during the course of treatment (Criterion A), which is rated on a scale from 0–10, and weighs clinical factors that are considered to be relevant for determining whether or not the observed improvements are due to the treatment (Criteria B1-B5), which are rated as 0, 1, or 2 points. The total score on the Alda scale is obtained by subtracting the B score from the A score; any negative score (i.e., the B scale score exceeds the A scale score) is recorded as 0 [13]. Although it was originally developed to evaluate the LIT response, this scale was slightly modified for the present study by replacing the term “lithium” in the instructions and other items to the term “mood stabilizers” so that it could be administered to subjects treated with VAL or LMT as well. A psychiatrist at each patient’s initial investigation site and a psychiatrist from another investigational site independently reviewed the medical records and came to a consensus regarding the treatment response. For the purposes of this study, two response categories were formed: insufficient response (ISR), including a non-response or poor response (Alda total score ≤ 6 or less), and good response (GR; Alda total score ≥ 7; [15].

The following clinical variables that are known to affect the treatment response and the choice of treatment medication were also investigated: age; sex; marital status; age at onset; duration of illness prior to investigational medications (e.g., LIT, VAL, or LMT); family history of BD; type of BD (I or II); psychiatric and medical comorbidities, including metabolic abnormalities, predominant polarity, polarity of first episode, number of past episodes, past history of seasonal pattern, rapid cycling, psychotic symptoms, mixed episodes, and suicide attempts; and concomitant medications, including antipsychotics and antidepressants [15, 25, 26].

Statistical analysis

The sociodemographic and clinical characteristics of the LIT, VAL, and LMT groups were compared using analysis of variance (ANOVA) and Chi-square tests. Subsequently, comparisons between subjects exhibiting a GR or an ISR were independently performed within each treatment group (LIT, VAL, or LMT). For comparisons of the demographic and clinical variables, the Chi-square test or Fisher’s exact test were used for categorical variables, and independent t-tests were used for continuous variables. Additionally, a binary logistic regression analysis with treatment response as the dependent variable and age, gender, and variables that were significant (p < 0.10) in the univariate analyses (diagnosis of BD II, comorbid alcohol/substance use disorder, recurrent episodes, and history of mixed episodes) as covariates was conducted to identify independent predictors of a GR or ISR for each treatment. All statistical analyses were performed using SPSS version 21.0, and p-values < 0.05 were considered to indicate statistical significance.

Ethical considerations

The present study was approved by the institutional review board of Yeouido St. Mary’s Hospital in Seoul, Korea (SC16QISE0038), and was conducted according to the principles of the Declaration of Helsinki. The institutional review board also approved the exemption for informed consent because this study was a retrospective chart review.


Sample characteristics

Of the 645 patients who were prescribed a mood stabilizer for at least 6 months, 172 were prescribed LIT, 320 were prescribed VAL, and 153 were prescribed LMT. Among 645 subjects, 612 (94.9%) were followed up for more than 1 year, and the median duration of follow-up was 21.6 months (range 6.0–81.6). There was no significant difference among treatment groups in duration of follow-up (p = 0.980, data not shown). The sociodemographic and clinical characteristics of the three treatment groups are summarized in Table 1. The proportions of patients with BD II, predominant manic polarity, recurrent episodes, and concomitant use of antipsychotics or antidepressants differed significantly among the groups; The order of BD II prevalence was highest in LMT group and lowest in LIT group. Patients having predominant manic polarity were highest in VAL group, followed by LIT group and LMT group. In contrast, patients having recurrent episodes or receiving concomitant antidepressants were highest for LMT group followed by LIT group and VAL group. Lastly, LIT group had the highest rate of patients receiving concomitant antipsychotics with second and third being VAL group and LMT group respectively. The distribution of treatment response scores for these three mood stabilizers is shown Fig 1 and descriptive results of treatment response scores were presented in Table 2.

Distribution of treatment response scores for lithium, valproate and lamotrigine.
Fig. 1. Distribution of treatment response scores for lithium, valproate and lamotrigine.
Tab. 1. Comparisons of sociodemographic and clinical characteristics among treatment groups.
Comparisons of sociodemographic and clinical characteristics among treatment groups.
Tab. 2. Total and individual criterion scores on the treatment response scale.
Total and individual criterion scores on the treatment response scale.

Comparison of subjects with a GR or an ISR

Univariate comparisons of GR versus ISR subjects in each of the treatment groups (Table 3) revealed that the LIT-ISR subjects had significantly higher rate of BD II, an alcohol/substance use disorder, or a history of mixed episodes compared than LIT-GR subjects. Recurrent episodes were also significantly more frequent in LIT-ISR subjects than in LIT-GR subjects. Rate of BD II, an alcohol/substance use disorder, or a history of mixed episodes did not differ between the VAL-ISR and VAL-GR subjects. Although a seasonal pattern of symptoms was numerically more prevalent in VAL-GR subjects than in VAL-ISR subjects, this difference did not reach statistical significance. In the LMT group, a diagnosis of BD II, depressive predominant polarity, or recurrent episodes was more frequently observed in LMT-GR subjects than in LMT-ISR subjects. Additionally, an alcohol/substance use disorder was significantly more prevalent in LMT-ISR subjects than in LMT-GR subjects.

Tab. 3. Comparisons of sociodemographic and clinical characteristics between ISR and GR.
Comparisons of sociodemographic and clinical characteristics between ISR and GR.

Predictors of response

A diagnosis of BD II (odds ratio [OR], 8.868; 95% confidence interval [CI], 1.123–70.046; p = 0.038), a comorbid alcohol/substance use disorder (OR, 4.238; 95% CI, 1.154–15.566; p = 0.030), and a history of mixed episodes (OR, 4.363; 95% CI, 1.191–15.985; p = 0.026) were significant predictors of LIT-ISR (Table 4). When diagnoses of BD II, comorbid alcohol/substance use disorder, predominant polarity, manic/hypomanic polarity at onset, or recurrent episodes were included as covariates in the analysis, a depressive predominant polarity significantly predicted LMT-GR (OR, 8.586; 95% CI, 2.767–26.644; p < 0.001). There were no significant predictors for the VAL treatment response when seasonal pattern was included as a covariate.

Tab. 4. Models of multivariate logistic regression.
Models of multivariate logistic regression.


The primary objective of the present study was to identify factors associated with long-term treatment responses in a large clinically representative sample of BD patients. Of the 625 BD patients who had been treated with mood stabilizers for at least 6 months, 172 were treated with LIT, 320 were treated with VAL, and 153 were treated with LMT. In contrast to previous studies [1215, 27, 28], the present study included three agents commonly used for the treatment of BD (LIT, VAL, and LMT) and examined the associations between treatment response and the clinical characteristics of the subjects. These characteristics included factors that were recently found to be associated with the treatment response to BD, such as predominant polarity [2931] and comorbid metabolic abnormalities [32, 33].

The present findings indicated that a comorbid alcohol/substance use disorder and a history of mixed episodes were associated with a poor response to LIT, as previously described [12, 15]. Additionally, the present study found that a diagnosis of BD II was associated with a poor response to LIT, which is consistent with other recent findings [15]. Recent guidelines for the management of patients with BD recommend LIT as a second-line agent for BD II depression based on studies showing that LIT is not superior to placebo for this disorder [8]. BD II patients experience more depressive symptoms than BD I patients [34] and present with significantly more depressive symptoms [35]; the relatively low effectiveness of LIT for BD depression may contribute to this result. However, controversy remains regarding the relationship between a diagnosis of BD II and the LIT response because some studies show that BD II patients have a better response to LIT [36, 37], whereas others show that diagnosis is unrelated to the LIT response [12]. It is also important to consider the serum levels of LIT when assessing the treatment response. Studies that reported a negative association between a diagnosis of BD II and a poor response to LIT did not evaluate the LIT concentrations [38] or recorded an extremely wide range (0.3–1.0 mmol/L) of serum LIT levels [39]. On the other hand, studies with appropriate LIT serum levels reported the relatively poor effectiveness of LIT for the long-term treatment of BD II [4042].

Another important finding of the present study was that a depressive predominant polarity significantly predicted a good response to LMT. This result supports the recommendations of recent treatment guidelines that suggest LMT for the maintenance phase of patients with depressive predominant polarity [8, 43, 44]. Predominant polarity is of great importance for the formulation of management goals and confers a significant amount of information regarding treatment choices for patients, as previously suggested [45]. The usefulness of LMT for patients with depressive predominant polarity was demonstrated in a recent naturalistic study [46]. These authors also identified three prescription strategies for BD patients: 1) the "anti-manic stabilization package", which includes treatments with anti-manic mechanisms of action for predominantly manic/psychotic BD I patients; 2) the "anti-depressive stabilization package", which groups predominantly depressed patients; and 3) the "anti-bipolar II package", which groups BD II patients with a depressive predominant polarity, melancholic features, and higher rates of suicide behaviors. It is noteworthy that the “anti-depressive stabilization package” includes the prescriptions of LMT and other atypical antipsychotics, such as quetiapine, which has proven efficacy for the depressive phases of BD.

Previous studies have also investigated other possible predictors of the treatment response to mood stabilizers, including age at onset, number of previous episodes, rapid cycling, psychotic features, and family history of BD [12]. None of these characteristics had a significant association with treatment response in the present study and should be analyzed in future studies with larger sample sizes. Furthermore, recent evidence suggests that BD patients with comorbid metabolic dysregulation might exhibit greater probabilities of a chronic course of illness and treatment resistance compared to BD patients without metabolic issues [32, 47]. However, in the present study, comorbid metabolic abnormalities, such as dyslipidemia, diabetes mellitus, and hypertension, were not associated with the long-term treatment response to mood stabilizers. It is important to note that the diagnoses of metabolic abnormalities in the present study were extracted from available medical records, which might have underestimated the presence of metabolic conditions.

The present study has several possible limitations that should be considered when interpreting the findings. First, the retrospective assessment of the long-term response to treatment may have introduced a recall bias and/or reviewer bias. Additionally, diagnoses of BD I, BD II, and other psychiatric comorbidities were made clinically. Second, the associations observed in the present study might have been influenced by uncontrolled confounders, such as selection, dosage, and serum levels of index medications, because much of the clinical information was obtained during natural clinical practice. Moreover, the rate of patients receiving antipsychotics did not differ between insufficient response group and good response group. However, it is not still possible to rule out the possibility that atypical antipsychotics provided mood stabilizing effect. Third, the relatively small sample sizes of BD patients in each group resulting from low long-term treatment success or high retention rates could have caused type-II errors. A large proportion of BD patients failed to maintain index medication for more than 6 months, and thus, were ineligible for this study. Additionally, the prevalence of comorbid anxiety disorder in the LIT-ISR group (15.6%) was nearly double that of the LIT-GR group (8.0%); this difference did not reach statistical significance. Finally, the present study included Korean patients only. Moreover, demographic and clinical characteristics of patients who were excluded from the study were not investigated, which could have caused potential bias. Thus, the findings should be interpreted cautiously.


Despite these limitations, the present study identified several associations between clinical factors and the long-term responses to mood stabilizers commonly used for the treatment of BD. Although previous studies already investigated factors predicting good treatment response or mood stabilizing effect of mood stabilizers, these studies investigated predictors of individual mood stabilizers only. In contrast, our results provided additional information by including three mood stabilizers (LMT, LIT, and VAL) and investigating their long-term mood stabilizing effects. The results from this naturalistic study has enable us to directly compare characteristics of the three mood stabilizers. By doing so, the study improved the current understanding of how clinical characteristics of BD disorder patients might predict treatment response to a specific drug, and it may provide a more valid response phenotype for future genetic and other studies.

Supporting information

S1 Dataset [xlsx]


1. Hayes JF, Miles J, Walters K, King M, Osborn DP. A systematic review and meta-analysis of premature mortality in bipolar affective disorder. Acta Psychiatr Scand. 2015;131(6):417–25. doi: 10.1111/acps.12408 25735195; PubMed Central PMCID: PMC4939858.

2. Grunze H, Vieta E, Goodwin GM, Bowden C, Licht RW, Moller HJ, et al. The World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for the biological treatment of bipolar disorders: update 2012 on the long-term treatment of bipolar disorder. World J Biol Psychiatry. 2013;14(3):154–219. doi: 10.3109/15622975.2013.770551 23480132.

3. Berk M, Berk L, Dodd S, Cotton S, Macneil C, Daglas R, et al. Stage managing bipolar disorder. Bipolar Disord. 2014;16(5):471–7. doi: 10.1111/bdi.12099 23782499.

4. Rosa AR, Gonzalez-Ortega I, Gonzalez-Pinto A, Echeburua E, Comes M, Martinez-Aran A, et al. One-year psychosocial functioning in patients in the early vs. late stage of bipolar disorder. Acta Psychiatr Scand. 2012;125(4):335–41. doi: 10.1111/j.1600-0447.2011.01830.x 22283440.

5. Magalhaes PV, Dodd S, Nierenberg AA, Berk M. Cumulative morbidity and prognostic staging of illness in the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Aust N Z J Psychiatry. 2012;46(11):1058–67. doi: 10.1177/0004867412460593 23015748.

6. Lewandowski KE, Cohen BM, Ongur D. Evolution of neuropsychological dysfunction during the course of schizophrenia and bipolar disorder. Psychol Med. 2011;41(2):225–41. doi: 10.1017/S0033291710001042 20836900.

7. Cipriani A, Hawton K, Stockton S, Geddes JR. Lithium in the prevention of suicide in mood disorders: updated systematic review and meta-analysis. BMJ. 2013;346:f3646. doi: 10.1136/bmj.f3646 23814104.

8. Yatham LN, Kennedy SH, Parikh SV, Schaffer A, Bond DJ, Frey BN, et al. Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder. Bipolar Disord. 2018;20(2):97–170. Epub 2018/03/15. doi: 10.1111/bdi.12609 29536616; PubMed Central PMCID: PMC5947163.

9. Fountoulakis KN, Grunze H, Vieta E, Young A, Yatham L, Blier P, et al. The International College of Neuro-Psychopharmacology (CINP) Treatment Guidelines for Bipolar Disorder in Adults (CINP-BD-2017), Part 3: The Clinical Guidelines. Int J Neuropsychopharmacol. 2017;20(2):180–95. Epub 2016/12/13. doi: 10.1093/ijnp/pyw109 27941079; PubMed Central PMCID: PMC5408976.

10. Alda M, Manchia M. Personalized management of bipolar disorder. Neurosci Lett. 2018;669:3–9. Epub 2017/12/07. doi: 10.1016/j.neulet.2017.12.005 29208408.

11. Goodwin GM, Haddad PM, Ferrier IN, Aronson JK, Barnes T, Cipriani A, et al. Evidence-based guidelines for treating bipolar disorder: Revised third edition recommendations from the British Association for Psychopharmacology. J Psychopharmacol. 2016;30(6):495–553. Epub 2016/03/17. doi: 10.1177/0269881116636545 26979387; PubMed Central PMCID: PMC4922419.

12. Kleindienst N, Engel R, Greil W. Which clinical factors predict response to prophylactic lithium? A systematic review for bipolar disorders. Bipolar Disord. 2005;7(5):404–17. Epub 2005/09/24. doi: 10.1111/j.1399-5618.2005.00244.x 16176433.

13. Grof P, Duffy A, Cavazzoni P, Grof E, Garnham J, MacDougall M, et al. Is response to prophylactic lithium a familial trait? J Clin Psychiatry. 2002;63(10):942–7. Epub 2002/11/06. doi: 10.4088/jcp.v63n1013 12416605.

14. Backlund L, Ehnvall A, Hetta J, Isacsson G, Agren H. Identifying predictors for good lithium response—a retrospective analysis of 100 patients with bipolar disorder using a life-charting method. Eur Psychiatry. 2009;24(3):171–7. Epub 2009/03/17. doi: 10.1016/j.eurpsy.2008.12.009 19286354.

15. Sportiche S, Geoffroy PA, Brichant-Petitjean C, Gard S, Khan JP, Azorin JM, et al. Clinical factors associated with lithium response in bipolar disorders. Aust N Z J Psychiatry. 2017;51(5):524–30. doi: 10.1177/0004867416664794 27557821.

16. Gyulai L, Bowden CL, McElroy SL, Calabrese JR, Petty F, Swann AC, et al. Maintenance efficacy of divalproex in the prevention of bipolar depression. Neuropsychopharmacology. 2003;28(7):1374–82. Epub 2003/06/05. doi: 10.1038/sj.npp.1300190 12784116.

17. Suppes T, Brown E, Schuh LM, Baker RW, Tohen M. Rapid versus non-rapid cycling as a predictor of response to olanzapine and divalproex sodium for bipolar mania and maintenance of remission: post hoc analyses of 47-week data. J Affect Disord. 2005;89(1–3):69–77. Epub 2005/10/29. doi: 10.1016/j.jad.2005.07.011 16253344.

18. Calabrese JR, Delucchi GA. Spectrum of efficacy of valproate in 55 patients with rapid-cycling bipolar disorder. Am J Psychiatry. 1990;147(4):431–4. Epub 1990/04/01. doi: 10.1176/ajp.147.4.431 2107762.

19. Salloum IM, Cornelius JR, Daley DC, Kirisci L, Himmelhoch JM, Thase ME. Efficacy of valproate maintenance in patients with bipolar disorder and alcoholism: a double-blind placebo-controlled study. Arch Gen Psychiatry. 2005;62(1):37–45. Epub 2005/01/05. doi: 10.1001/archpsyc.62.1.37 15630071.

20. Brady KT, Myrick H, Henderson S, Coffey SF. The use of divalproex in alcohol relapse prevention: a pilot study. Drug Alcohol Depend. 2002;67(3):323–30. Epub 2002/07/20. doi: 10.1016/s0376-8716(02)00105-9 12127203.

21. Ketter TA, Calabrese JR. Stabilization of mood from below versus above baseline in bipolar disorder: a new nomenclature. J Clin Psychiatry. 2002;63(2):146–51. Epub 2002/03/05. doi: 10.4088/jcp.v63n0210 11874216.

22. Popovic D, Reinares M, Goikolea JM, Bonnin CM, Gonzalez-Pinto A, Vieta E. Polarity index of pharmacological agents used for maintenance treatment of bipolar disorder. Eur Neuropsychopharmacol. 2012;22(5):339–46. Epub 2011/10/18. doi: 10.1016/j.euroneuro.2011.09.008 22000157.

23. Fornaro M, De Berardis D, Anastasia A, Novello S, Fusco A, Cattaneo CI, et al. The identification of biomarkers predicting acute and maintenance lithium treatment response in bipolar disorder: A plea for further research attention. Psychiatry Res. 2018;269:658–72. Epub 2018/09/15. doi: 10.1016/j.psychres.2018.08.034 30216918.

24. Jeong JH, Bahk WM, Woo YS, Lee JG, Kim MD, Sohn I, et al. Korean Medication Algorithm for Bipolar Disorder 2018: Comparisons with Other Treatment Guidelines. Clin Psychopharmacol Neurosci. 2019;17(2):155–69. Epub 2019/03/25. doi: 10.9758/cpn.2019.17.2.155 30905116; PubMed Central PMCID: PMC6478090.

25. Dell'Osso B, Buoli M, Riundi R, D'Urso N, Pozzoli S, Bassetti R, et al. Clinical characteristics and long-term response to mood stabilizers in patients with bipolar disorder and different age at onset. Neuropsychiatr Dis Treat. 2009;5:399–404. Epub 2009/08/04. doi: 10.2147/ndt.s5970 19649214; PubMed Central PMCID: PMC2714289.

26. Geoffroy PA, Bellivier F, Leboyer M, Etain B. Can the response to mood stabilizers be predicted in bipolar disorder? Front Biosci (Elite Ed). 2014;6:120–38. Epub 2014/01/07. doi: 10.2741/e696 24389147.

27. Tighe SK, Mahon PB, Potash JB. Predictors of lithium response in bipolar disorder. Ther Adv Chronic Dis. 2011;2(3):209–26. Epub 2011/05/01. doi: 10.1177/2040622311399173 23251751; PubMed Central PMCID: PMC3513882.

28. Swann AC, Bowden CL, Calabrese JR, Dilsaver SC, Morris DD. Pattern of response to divalproex, lithium, or placebo in four naturalistic subtypes of mania. Neuropsychopharmacology. 2002;26(4):530–6. Epub 2002/04/03. doi: 10.1016/S0893-133X(01)00390-6 11927177.

29. Belizario GO, Silva M, Lafer B. Impact of predominant polarity on long-term outcome in bipolar disorder: A 7-year longitudinal cohort study. J Affect Disord. 2018;241:37–40. Epub 2018/08/11. doi: 10.1016/j.jad.2018.07.086 30096590.

30. Carvalho AF, Quevedo J, McIntyre RS, Soeiro-de-Souza MG, Fountoulakis KN, Berk M, et al. Treatment implications of predominant polarity and the polarity index: a comprehensive review. Int J Neuropsychopharmacol. 2014;18(2). Epub 2014/12/19. doi: 10.1093/ijnp/pyu079 25522415; PubMed Central PMCID: PMC4368897.

31. Sentissi O, Popovic D, Moeglin C, Stukalin YB, Mosheva M, Vieta E, et al. Predominant polarity in bipolar disorder patients: The COPE bipolar sample. J Affect Disord. 2019;250:43–50. Epub 2019/03/04. doi: 10.1016/j.jad.2019.02.053 30826493.

32. Steardo L Jr., Fabrazzo M, Sampogna G, Monteleone AM, D'Agostino G, Monteleone P, et al. Impaired glucose metabolism in bipolar patients and response to mood stabilizer treatments. J Affect Disord. 2019;245:174–9. Epub 2018/11/06. doi: 10.1016/j.jad.2018.10.360 30391773.

33. Bai YM, Li CT, Tsai SJ, Tu PC, Chen MH, Su TP. Metabolic syndrome and adverse clinical outcomes in patients with bipolar disorder. BMC Psychiatry. 2016;16(1):448. Epub 2016/12/17. doi: 10.1186/s12888-016-1143-8 27978821; PubMed Central PMCID: PMC5159954.

34. Judd LL, Schettler PJ, Akiskal HS, Maser J, Coryell W, Solomon D, et al. Long-term symptomatic status of bipolar I vs. bipolar II disorders. Int J Neuropsychopharmacol. 2003;6(2):127–37. Epub 2003/08/02. doi: 10.1017/S1461145703003341 12890306.

35. Vinberg M, Mikkelsen RL, Kirkegaard T, Christensen EM, Kessing LV. Differences in clinical presentation between bipolar I and II disorders in the early stages of bipolar disorder: A naturalistic study. J Affect Disord. 2017;208:521–7. Epub 2016/11/07. doi: 10.1016/j.jad.2016.10.031 27816324.

36. Rybakowski JK. Response to lithium in bipolar disorder: clinical and genetic findings. ACS Chem Neurosci. 2014;5(6):413–21. Epub 2014/03/15. doi: 10.1021/cn5000277 24625017; PubMed Central PMCID: PMC4063501.

37. Post RM, Leverich GS, Kupka R, Keck PE Jr., McElroy SL, Altshuler LL, et al. Clinical correlates of sustained response to individual drugs used in naturalistic treatment of patients with bipolar disorder. Compr Psychiatry. 2016;66:146–56. Epub 2016/03/21. doi: 10.1016/j.comppsych.2016.01.009 26995248.

38. Okuma T. Effects of carbamazepine and lithium on affective disorders. Neuropsychobiology. 1993;27(3):138–45. Epub 1993/01/01. doi: 10.1159/000118969 8232828.

39. Kato T, Inubushi T, Kato N. Prediction of lithium response by 31P-MRS in bipolar disorder. Int J Neuropsychopharmacol. 2000;3(1):83–5. Epub 2001/05/10. doi: 10.1017/S1461145799001674 11343583.

40. Yazici O, Kora K, Ucok A, Tunali D, Turan N. Predictors of lithium prophylaxis in bipolar patients. J Affect Disord. 1999;55(2–3):133–42. Epub 2000/01/11. doi: 10.1016/s0165-0327(98)00216-x 10628882.

41. Tondo L, Baldessarini RJ, Floris G. Long-term clinical effectiveness of lithium maintenance treatment in types I and II bipolar disorders. Br J Psychiatry Suppl. 2001;41:s184–90. Epub 2001/07/14. 11450181.

42. Hartong EG, Moleman P, Hoogduin CA, Broekman TG, Nolen WA, LitCar G. Prophylactic efficacy of lithium versus carbamazepine in treatment-naive bipolar patients. J Clin Psychiatry. 2003;64(2):144–51. Epub 2003/03/14. doi: 10.4088/jcp.v64n0206 12633122.

43. Fountoulakis KN, Yatham L, Grunze H, Vieta E, Young A, Blier P, et al. The International College of Neuro-Psychopharmacology (CINP) Treatment Guidelines for Bipolar Disorder in Adults (CINP-BD-2017), Part 2: Review, Grading of the Evidence, and a Precise Algorithm. Int J Neuropsychopharmacol. 2017;20(2):121–79. Epub 2016/11/07. doi: 10.1093/ijnp/pyw100 27816941; PubMed Central PMCID: PMC5409012.

44. Woo YS, Bahk WM, Lee JG, Jeong JH, Kim MD, Sohn I, et al. Korean Medication Algorithm Project for Bipolar Disorder 2018 (KMAP-BP 2018): Fourth Revision. Clin Psychopharmacol Neurosci. 2018;16(4):434–48. Epub 2018/11/24. doi: 10.9758/cpn.2018.16.4.434 30466216; PubMed Central PMCID: PMC6245301.

45. Colom F, Vieta E, Daban C, Pacchiarotti I, Sanchez-Moreno J. Clinical and therapeutic implications of predominant polarity in bipolar disorder. J Affect Disord. 2006;93(1–3):13–7. Epub 2006/05/03. doi: 10.1016/j.jad.2006.01.032 16650901.

46. Nivoli AM, Colom F, Pacchiarotti I, Murru A, Scott J, Valenti M, et al. Treatment strategies according to clinical features in a naturalistic cohort study of bipolar patients: a principal component analysis of lifetime pharmacological and biophysic treatment options. Eur Neuropsychopharmacol. 2013;23(4):263–75. Epub 2012/09/04. doi: 10.1016/j.euroneuro.2012.07.015 22939529.

47. Calkin CV, Ruzickova M, Uher R, Hajek T, Slaney CM, Garnham JS, et al. Insulin resistance and outcome in bipolar disorder. Br J Psychiatry. 2015;206(1):52–7. Epub 2014/10/18. doi: 10.1192/bjp.bp.114.152850 25323142.

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