Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treatment in first episode schizophrenia

SCHRES-08572; No of Pages 8 Schizophrenia Research xxx (xxxx) xxx

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Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treatment in first episode schizophrenia Robin Emsley a,⁎, Laila Asmal a, Jose M. Rubio b,c,d, Christoph U. Correll b,c,d,e, John M. Kane b,c,d a

Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, 8000 Cape Town, South Africa The Zucker Hillside Hospital, Department of Psychiatry, Northwell Health, Glen Oaks, NY, USA Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry and Molecular Medicine, Hempstead, NY, USA d The Feinstein Institute for Medical Research, Center for Psychiatric Neuroscience, Manhasset, NY, USA e Charité Universitätsmedizin Berlin, Department of Child and Adolescent Psychiatry, Berlin, Germany b c

a r t i c l e

i n f o

Article history: Received 2 September 2019 Received in revised form 11 November 2019 Accepted 13 November 2019 Available online xxxx Keywords: First episode Schizophrenia Relapse Breakthrough Antipsychotic medication Long acting injectable

a b s t r a c t Background: Some patients develop breakthrough psychotic symptoms on antipsychotic maintenance medication (BAMM), despite receiving therapeutic antipsychotic doses to which they previously responded. Methods: We examined the occurrence of BAMM in previously minimally treated first-episode patients with schizophrenia-spectrum disorders who were treated according to a standard protocol with a long-acting injectable antipsychotic and regularly assessed over 24 months. Results: Of 99 patients (age = 24.1 ± 6.5 years, male = 73.7%) who received treatment for ≥6 months (mean follow-up = 20.0 ± 6.5 months) and had responded well to treatment, 21 (21.2%) developed BAMM using operationally defined criteria, after a mean of 17.4 ± 6.1 months. Baseline risk factors for BAMM included lower baseline Positive and Negative Syndrome Scale positive symptoms, poorer quality of life in social relationships and higher blood - high-density lipoprotein-cholesterol. Regarding intra-treatment-factors, BAMM was independently predicted by an increase in low-density lipoprotein-cholesterol and current cannabis use. We did not find a relationship between BAMM and cumulative antipsychotic exposure or dose escalation. While symptoms of the BAMM episode were less severe than during the first episode, the post-BAMM treatment response was poorer than that for the first psychotic episode, suggesting a relationship between BAMM and emergent treatment refractoriness. Conclusions: About one in five patients with first-episode schizophrenia developed BAMM during the first two years of treatment, despite assured antipsychotic LAI treatment, indicating that this phenomenon is not restricted to the chronic stages of illness. The role of cannabis use and a possible link between BAMM and blood lipids should be further explored. © 2018 Elsevier B.V. All rights reserved.

1. Introduction The course of schizophrenia is characterised by chronicity, and the majority of patients experience multiple relapses (Robinson et al., 1999; Carbon and Correll, 2014). Relapse prevention is crucial in the treatment of schizophrenia, as relapse is associated with risk of jeopardising education or employment, disrupting personal relationships, further stigmatisation of the illness, increased healthcare costs and most importantly self-harm or harm to others (Kane, 2007; Correll et al., 2018). Furthermore, it has been suggested that relapse of psychotic symptoms is followed by worse response to antipsychotic treatment than during prior episodes (Lieberman et al., 1996; Wiersma et al., 1998; Emsley et al., 2013; Takeuchi et al., 2019). It is ⁎ Corresponding author. E-mail address: [email protected] (R. Emsley).

therefore important to understand the factors involved in relapse of psychotic disorders in order to improve relapse prevention and to develop novel interventions specifically for BAMM. Treatment non-adherence is by far the strongest predictor of relapse (Robinson et al., 1999; Kane et al., 2013), and after a first episode of schizophrenia estimated weighted mean relapse rates of 77% and N90% one and two years after treatment discontinuation respectively have been reported (Zipursky et al., 2014). In addition to nonadherence, other factors have been linked to relapse, including persistent substance use, careers' criticism and poorer premorbid adjustment (Alvarez-Jimenez et al., 2012), although it is not clear to what extent these factors may be mediated by poor adherence (Schoeler et al., 2017). Given the lack of pragmatic methods to estimate the extent of non-adherence with oral antipsychotic drugs, much of the research of relapse in psychosis has been limited by the confounder of treatment non-adherence (Kane et al., 2013).

https://doi.org/10.1016/j.schres.2019.11.025 0920-9964/© 2018 Elsevier B.V. All rights reserved.

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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However, this limitation can be overcome by studying relapse in individuals continuously treated with long-acting injectable antipsychotics (LAIs), in whom exposure to antipsychotic drugs can be easily confirmed (Correll et al., 2016). Relapse of psychotic symptoms despite assured antipsychotic exposure is referred to as Breakthrough on Antipsychotic Maintenance Medication (BAMM) (Rubio and Kane, 2017). BAMM was initially examined in a secondary analysis of a multicentre clinical trial in which stable patients with schizophrenia were treated with risperidone-LAI over 1 year. Of 323 participants, 59 (18.3%) relapsed in this period (Alphs et al., 2016). Predictors of relapse were country of research site (Canada vs. USA) and longer duration of treatment, i.e., illness duration N10 vs. ≤5 years was associated with a 4.4fold increase in the risk of relapse. This result led the authors to suggest that patients with more chronic illness are at greater risk of BAMM (Alphs et al., 2016). The finding of the association between chronic illness and greater risk of BAMM is in line with the classic theory of dopamine supersensitivity (Chouinard et al., 1978; Silvestri et al., 2000) which postulates that chronic antipsychotic exposure may increase risk of breakthrough psychotic symptoms through dopamine D2 receptor upregulation. However, while preclinical studies support the notion of antipsychotic induced dopamine induced supersensitivity (Samaha et al., 2007) there is a paucity of information in the clinical setting (Yin et al., 2017). Additionally, a recent study from a Finnish national cohort measured the incidence and predictors of BAMM among 16,031 individuals treated with LAIs between 1996 and 2016. This study reported an incidence of 12 relapse events per 100 patient-years of continuous LAI treatment, which accounted for 31.5% of the analysed sample (Rubio et al., 2019). In this study, risk of BAMM was inversely associated with age, contradicting the findings suggested by Alphs and colleagues (Alphs et al., 2016) that BAMM may be more common in chronic illness. It should be noted that, while national registry studies may better represent routine practice, their limitations may include low internal validity, lack of quality control surrounding data collection and susceptibility to multiple sources of bias for comparing outcomes (Camm and Fox, 2018). To what degree BAMM is common among individuals early in their course of treatment and what additional risk factors might be present is not well understood. We aimed to investigate the occurrence of BAMM in the early phase of treatment in a cohort of previously minimally treated first-episode patients with schizophrenia-spectrum disorders who were treated with an LAI and regularly assessed over 24 months. The specific aims of this study were to: 1) Determine the time to BAMM and its demographic, baseline clinical and early treatment response risk factors; 2) Investigate the nature of the BAMM relapse episodes compared with the first psychotic episode in terms of symptom severity, phenomenology and response to treatment; and 3) Assess intra-treatment variables associated with BAMM. Based on the available data, we hypothesized that BAMM would occur less frequently in our first-episode sample than the 18.3% previously reported in chronic patients (Alphs et al., 2016), and that BAMM would be associated with higher cumulative antipsychotic dose and a poorer post-BAMM treatment response. 2. Methodology 2.1. Study design This is a secondary, post hoc analysis of a subset of patients from longitudinal study, in which patients were treated with the LAI flupenthixol decanoate according to a standardised protocol (see below) for 24 months. The original study was conducted at two sites, in Cape Town South Africa and Ibadan, Nigeria. This non-comparative study assessed the acceptability, feasibility, efficacy and tolerability of flexible doses of a depot antipsychotic combined with an assertive monitoring program in treating patients with first-episode schizophrenia. Details of the 12 month outcome from that study have been published previously (Chiliza et al., 2016). For the present study only patients

from the Cape Town site were included. We obtained ethics approval from the Human Research Ethics Committee of Stellenbosch University and the study was conducted according to International Conference on Harmonization good clinical practice guidelines (International Conference on Harmonization, 1996). 2.2. Participants Participants were recruited from psychiatric hospitals and community clinics in Cape Town and surroundings and treated and assessed between April 2007 and March 2016. Patients and/or their legal guardians provided written, informed consent to participate in the study. In the case of minors, assent was provided and consent was obtained from the legal guardian. Inclusion criteria were men and women, aged 16–45 years, experiencing a first psychotic episode meeting Diagnostic and Statistical Manual of Mental Diseases, Fourth Edition, Text Revisions (DSM-IV TR) (American Psychiatric Association, 1994) diagnostic criteria for schizophrenia, schizophreniform or schizoaffective disorder. Exclusion criteria were severe or unstable general medical condition, current substance abuse/dependence according to DSM-IV TR criteria (although substance use was not an exclusion criterion) and intellectual disability. For the present report, we were interested in studying the effects of treatment in patients who had been exposed to antipsychotic pharmacotherapy over an extended period and who had achieved a favourable clinical response. We therefore only included patients who had achieved clinical stability, and who had completed ≥6 months of antipsychotic treatment without symptom recurrence. Clinical stability was determined. 2.3. Treatment Patients were treated according to a fixed protocol, with LAI flupenthixol. In this study we chose flupenthixol decanoate, a firstgeneration antipsychotic, as it is widely available in South Africa, affordable in the public sector and remains a popular choice of psychiatrists for treating psychosis (Shen et al., 2012). After a 7-day lead-in with oral flupenthixol 1–3 mg/day to test for sensitivity, patients received flupenthixol decanoate intramuscular injections 2-weekly for the study duration. The initiation dose was 10 mg 2-weekly. Additional oral flupenthixol was permitted, although seldom prescribed. Flupenthixol decanoate was maintained at the lowest possible therapeutic dose, and only increased in patients with persistent insufficient response. Patients remained on flupenthixol throughout the study. In the event of symptom recurrence, short-term oral flupenthixol supplementation was allowed, together with adjustments to LAI flupenthixol as necessary. Permitted concomitant medications included lorazepam, anticholinergics, propranolol, antidepressants and medications for general medical conditions. Prohibited medications included other antipsychotics, mood stabilizers and psychostimulants. Six participants were treated in a sub-study with LAI-risperidone injection for the first 12 weeks, before being switched to flupenthixol decanoate. Using LAI removed the confounding effect of covert non-adherence and also allowed us to estimate precisely the relationship between BAMM and antipsychotic medication. We investigated the effects of antipsychotic medication in several different ways. We determined the mean modal flupenthixol decanoate dose and the treatment duration. We also estimated the total study antipsychotic dose each participant received, according to consensus-derived guidelines (Gardner et al., 2010), expressed as flupenthixol oral mg equivalents. 2.4. Assessments Patients were assessed with the Structured Clinical Interview for DSM-IV (SCID) (First et al., 1994). The following additional assessments were conducted on all patients: Positive and Negative Syndrome Scale (PANSS) (Kay et al., 1987), Clinical Global Impressions-Severity (CGI-

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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S) and Improvement (CGI-I) (Guy, 2000), Social and Occupational Functioning Assessment Scale (SOFAS) (American Psychiatric Association, 1994), Extrapyramidal Symptom Rating Scale (ESRS) (Chouinard and Margolese, 2005); Neurological Evaluation Scale (NES) (Buchanan and Heinrichs, 1989), Birchwood Insight Scale (BIS) (Birchwood et al., 1994), Premorbid Adjustment Scale (PAS) (Cannon-Spoor et al., 1982), and the World Health Organization Quality of Life-Bref (WHOQOL-Bref) questionnaire (Karow et al., 2014). Scheduled visits for clinical assessments by investigators were at baseline, 7 weeks, and 3-monthly intervals thereafter. Patients were seen by the study nurses at 2-weekly intervals for LAI administration throughout the study. In the event of non-attendance, patients or their families were immediately contacted and reminded. A register was kept of each visit and the medication received, enabling precise calculation of adherence and total antipsychotic exposure. In the event of symptom recurrence unscheduled visits were arranged and adjustments to medication were made as necessary. Blood pressure, heart rate, body mass index (BMI), fasting glucose and lipids and serum prolactin were assessed at baseline and at 6-monthly intervals, as was urine toxicology screening. We classified participants as “current cannabis users” if they tested positive at any of these visits. 2.5. Definition of BAMM To meet BAMM criteria, we deemed it important to define firstly that patients had shown a favourable treatment response, and secondly subsequently met clear-cut criteria for symptom recurrence. We therefore applied operationally defined criteria for remission (Andreasen et al., 2005) that patients had to meet on two successive 3-monthly visits prior to relapse, and relapse criteria adapted from those of Csernansky et al. (2002) comprising any of: (i) ≥25% increase in PANSS total score from the previous visit; (ii) increase of ≥10 points if the PANSS total score was b40; or (iii) a score of 6 (‘much worse’) or 7 (‘very much worse’) on the CGI-I scale. 2.6. Statistical methods Normality of data distribution was assessed by histograms and scatterplots. Descriptive statistics were used to calculate the mean and standard deviation (SD) or the median and range for continuous variables, and counts and percentages for categorical variables. We used two sample t-tests for continuous variables and chi-square test for categorical variables. All tests were two-sided and statistical significance was set as p b 0.05. The analyses were carried out using STATA, version 14 and Statistica (Dell) version13. 2.6.1. Time to BAMM and predictors of BAMM Survival analysis was conducted for time to BAMM after remission. Survival curves were constructed using unadjusted Kaplan–Meier estimates. Patients were censored if they discontinued from the study for any reason, e.g., lost to follow-up or patient decision. Cox regression analyses were used to identify factors associated with BAMM via univariate and multivariate analyses. Univariate analyses were conducted, and factors that were statistically significant (p b 0.05) were subsequently entered into a multivariable Cox proportional hazards regression model. 2.6.2. Phenomenology and treatment response for BAMM vs. the first psychotic episode Symptom expression of the BAMM episode was compared with that of the first episode for PANSS factor-analysis derived positive, negative, disorganised, anxiety/depression and excitement/hostility domains (Emsley et al., 2003). Since symptom severity differed between the first and BAMM episodes, the domain scores were expressed as a percentage of the sum score of all of the domains, in order to compare proportional representation of the domains. We then compared the

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treatment response by PANSS total score after the BAMM episode with that of their first episode in the 21 patients who experienced BAMM, by linear mixed model for repeated measures (MMRM) analysis. We included one 3-monthly post-episode visit and adjusted for baseline scores.

2.6.3. Evidence of dose escalation associated with BAMM We compared BAMM patients with the rest of the sample for antipsychotic dose at three timepoints, i.e., v1 = 6 months, v2 = For the BAMM patients the visit at the onset of BAMM, and for the nonBAMM participants 18 months (i.e. mean time to BAMM), and V3 = 24 months. We used MMRM analyses and adjusted for current cannabis use, which differed significantly between the groups, and has been associated with poorer treatment outcomes (Zammit et al., 2008).

2.6.4. Changes in physical and laboratory measures during the 24 month study period as predictors of BAMM To assess whether treatment related changes in physical and laboratory variables were associated with BAMM, we compared change scores (calculated from baseline to endpoint) for NES total and subscale scores, ESRS total scores, parkinsonism and dyskinesia subscale scores, BMI, systolic and diastolic blood pressure, heart rate, serum prolactin, fasting blood glucose and lipid profiles (total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, triglycerides). Since there were no significant group differences at the p b 0.05 level, we selected those with a p-value of b0.1 and fitted them as independent predictors into a forward stepwise logistic regression model, with BAMM/no BAMM as the binary dependent variable and adjusting for effects of treatment duration and current cannabis use.

3. Results Of 126 participants entered into the initial study from the Cape Town site, 99 (79%) completed at least 6 months of treatment and were included in the analysis. Reasons for non-inclusion were: Withdrawal of consent (n = 8), loss to follow-up (n = 7), poor treatment response (n = 5), relocated (n = 2), substance abuse (n = 1) and other (n = 4). At baseline, 54 (54.5%) were antipsychotic naïve and 45 (45.5%) had received antipsychotic medication as necessary for a mean of 11.0 ± 6.9 days. Twenty-one (21.2%) of the 99 prospectively followed patients met our criteria for BAMM during the 24-month treatment period (mean follow-up = 20.0 ± 6.5 months), corresponding with an incidence of 1.37 (95%CI.90 to 2.11) per 10 person-years. Mean time to BAMM was 17.4 ± 5.5 months. Five (23.8%) of the 21 patients discontinued the study subsequent to developing BAMM, due to poor treatment response (n = 1), medication side effects (n = 1), loss to follow-up (n = 1), and incarceration (n = 2). Of the 99 patients included in the analysis, 63 (64%) completed 24 months of treatment.

3.1. Risk and correlates of BAMM The Kaplan-Meier survival curve for time to BAMM is provided in Fig. 1. Demographic, baseline clinical and early treatment response details and univariate Cox regression analysis results for patients who experienced BAMM vs. those who did not are provided in Table 1. In the multivariable Cox regression model, BAMM was significantly predicted by fewer PANSS positive symptoms at baseline (i.e. prior to initiation of study treatment) (HR = 1.17, 95% confidence interval (CI) = 1.02–1.33, p = 0.02); poorer quality of life social relationships subscale (HR = 1.13, 95%CI = 1.02–1.26, p = 0.02) and higher HDL-cholesterol levels (HR = 1.73, 95%CI = 0.99–3.0, p = 0.05), and at a trend-level by lower prolactin levels (HR = 1.15, 95%CI = 1–1.33=, p = 0.06).

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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0.00

0.25

0.50

0.75

1.00

Relapse probability in FES with >=6m treatment

0

5

10 15 analysis time

20

25

99

99

80

58

0

Number at risk 70

Fig. 1. Kaplan-Meier survival curve for time to BAMM.

3.2. Phenomenology of the first psychotic episode vs. BAMM episode Symptoms were significantly more severe in the first episode than the BAMM episode for the positive (16.2 ± 3.2 vs 7.1 ± 3.2,

t1:1 t1:2

t1:40 t1:41 t1:42 t1:43 t1:44 t1:45 t1:46

3.3. Treatment response following the BAMM episode vs. following the first psychotic episode Fig. 3 provides the MMRM results for the comparison of symptom reduction in PANSS total scores over 3 months following antipsychotic treatment in the first psychotic episode vs in the BAMM episode. After adjusting for baseline scores there was a significant group × time interaction, reflecting a lesser treatment response for the BAMM episode vs. the first episode. Post-hoc Fisher's Least Significant Difference tests indicate significantly higher PANSS total scores at 3 months after the BAMM episode (66.6 [95%CI 60.0–70.3]) vs the first psychotic episode (43.1 [95%CI 37.6–48.6]) (p b 0.0001).

Table 1 Univariate Cox regression analyses of demographic and baseline clinical risk factors for patients who experienced BAMM vs those who did not.

t1:3 t1:4 t1:5 t1:6 t1:7 t1:8 t1:9 t1:10 t1:11 t1:12 t1:13 t1:14 t1:15 t1:16 t1:17 t1:18 t1:19 t1:20 t1:21 t1:22 t1:23 t1:24 t1:25 t1:26 t1:27 t1:28 t1:29 t1:30 t1:31 t1:32 t1:33 t1:34 t1:35 t1:36 t1:37 t1:38 t1:39

p b 0.0001), negative (21.7 ± 5.5 vs 12.0 ± 3.9, p b 0.0001) and disorganised (12.9 ± 2.3 vs 7.2 ± 2.6, p b 0.0001) domains, but not for the depression/anxiety (9.7 ± 4.4 vs 7.3 ± 3.7, p = 0.06) and excitement/hostility (8.1 ± 4.5 vs 6.0 ± 3.0, p = 0.09) domains. Fig. 2 depicts the proportional representation of the PANSS factor domains, expressed as the percentage of the sum of the domain scores, for the BAMM episode vs. the first psychotic episode. The domains were similarly expressed, except that the positive domain represented a smaller proportion of the total score in the BAMM episode vs. the first episode (F = 7.4, p = 0.01).

Age in years, mean (SD) Sex, n males (%) Highest school grade, mean (SD) Ethnicity, n (%) Black Mixed ancestry White DSM diagnosis, n (%) Schizophreniform Schizophrenia Schizoaffective % PANSS total change at week 7,a mean (SD) Mean (SD) 2-wkly modal flupenthixol dose (mg) Age of onset of illness, mean (SD) Current cannabis useb n (%) DUP weeks, median (IQR) PANSS domain scores, mean (SD) Total Positive Negative Depressed Excitement/hostility Disorganised SOFAS, mean (SD) WHO QoL domains, mean (SD) Physical health Psychological Social relationships Environment BMI (kg/m2), mean (SD) Prolactin (ng/ml), mean (SD) Fasting glucose (mmol/L), mean (SD) HDL (mmol/L), mean (SD) LDL (mmol/L), mean (SD) TG (mmol/L), mean (SD) Cholesterol (mmol/L), mean (SD)

BAMM (n = 21)

Non-BAMM (n = 78)

HR

95% CI

22.95(4.99) 17 (81%) 9.71(1.90)

24.45(6.79) 56 (78%) 9.76(2.30)

0.95 0.68 1.02 1.97

0.87 0.23 0.84 0.90

0(0%) 18(86%) 3(14%)

13(17%) 58(74%) 7(9%)

4(19) 17(81) 0 (0) 0.744(0.21) 11.67(2.89) 22.19(4.71) 13 (61.9%) 24.15(4.86–76.29)

28(36) 49(63) 1(1) 0.578(1.83) 12.85(3.82) 22.89(6.77) 32 (41.6%) 20.14(7.58–39.15)

0.74 1.00 0.95 2.40 1.00

0.40 0.89 0.88 0.99 0.99

1.34 1.12 1.02 5.80 1.01

−0.305 −0.002 −0.055 0.874 −0.001

0.32 0.97 0.173 0.053 0.823

97.24(14.69) 16.19(3.22) 21.71(5.47) 9.71(4.38) 8.09(4.54) 12.90(2.26) 43.11(8.80)

94.03(16.47) 17.64(3.33) 19.74(5.37) 8.47(4.35) 8.29(3.73) 11.83(2.92) 44.42(13.10)

1.01 0.87 1.06 1.04 1.00 1.13 0.99

0.98 0.77 0.99 0.95 0.89 0.96 0.96

1.03 0.98 1.14 1.14 1.11 1.33 1.03

0.009 −0.140 0.060 0.037 −0.003 0.123 −0.006

0.478 0.078 0.111 0.433 0.95 0.131 0.765

11.37(2.75) 12.41(2.90) 9.32(3.95) 10.74(3.26) 20.72(4,04) 7.31(2.41) 4.67(0.30) 1.45(0.72) 2.57(0.70) 0.91(0.34) 4.11(1.15)

12.11(2.19) 13.04(2.45) 12.61(3.76) 11.88(2.99) 21.99(3.87) 13.35(18.89) 4.82(0.79) 1.09(0.49) 2.75(0.99) 0.89(0.57) 4.26(1.11)

0.87 0.91 0.83 0.89 0.90 0.86 0.72 1.63 0.91 0.74 0.99

0.72 0.78 0.74 0.77 0.78 0.76 0.34 1.04 0.58 0.28 0.69

1.04 1.06 0.93 1.02 1.04 0.97 1.52 2.56 1.44 1.95 1.42

−0.139 −0.098 −0.184 −0.121 −0.106 −0.155 −0.327 0.487 −0.090 −0.300 −0.015

0.136 0.221 0.001 0.085 0.142 0.014 0.391 0.035 0.696 0.543 0.936

1.03 2.02 1.23 4.33

r

p

−0.055 −0.387 0.018 0.678

0.189 0.487 0.854 0.092

0.281

BAMM: breakthrough psychotic symptoms on antipsychotic maintenance medication; BIS: Birchwood Insight Scale; BMI: body mass index; CGI-S: Clinical Global Impressions-Severity; DSM: Diagnostic and Statistical Manual of Mental Diseases; DUP: duration of untreated psychosis; ESRS: Extrapyramidal Symptom Rating Scale; NES: Neurological Evaluation Scale; PANSS: Positive and Negative Syndrome Scale; SOFAS: Social and Occupational Functioning Assessment Scale; WHOQOL-Bref: World Health Organization Quality of Life-Bref questionnaire. a % PANSS total change at week 7 was the change in PANSS total scores from baseline to the visit at week 7 (after one week of oral and 6 weeks of LAI flupenthixol), representing “early treatment response”. b Current cannabis use = positive urine test at any of the baseline or 6 monthly visits.

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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Fig. 2. Mean and 95%CI PANSS domain percentage scores for the first episode and the BAMM episode.

3.4. No evidence for dose escalation in BAMM patients We found no significant differences in the mean modal flupenthixol decanoate dose (11.67 ± 2.89 mg/2wkly vs. 12.05 ± 3.83 mg/2wkly, t = 3.82, p = 0.67) as well as the total antipsychotic dose received (2041.69 ± 462.15 mg equivalents vs. 1774.42 ± 869.08fmg equivalents, t = 1.36, p = 0.18) for the BAMM patients vs the rest of the sample. Also, the MMRM analysis for flupenthixol dose at 6 months, BAMM episode and at 24 months did not reveal a significant group × time interaction (F(2, 167) = ,44965, p = 0.6).

3.5. Changes in physical and laboratory measures as potential predictors of BAMM Variables with change score differences at p b 0.1 significance that were selected for the regression model were HDL-cholesterol

(−0.35 ± 0.72 mmol/L vs. -0.12 ± 0.48 mmol/L, t = −1.8, p = 0.08); LDL-cholesterol (0.35 ± 0.79 mmol/L vs. 0.04 ± 0.60 mmol/L, t = 1.97, p = 0.05); total cholesterol (0.45 ± 1.06 vs. 0.06 ± 0.77, t = 1.88, p = 0.06). We also entered treatment duration (94.67 ± 23.72 vs. 82.57 ± 30.94, t = 1.66, p = 0.10) and current cannabis use status (13/21[62%] vs. 32/78[41%], Chi square = 2.75, p = 0.09) compares the change scores over the 24 months of treatment for the physical and laboratory measures for the patients who experienced BAMM vs. the rest of the sample. According to the logistic regression model, BAMM was independently predicted by an increase in LDL-cholesterol (OR = 2.94 95%CI = 1.17–7.14, p = 0.02) as well as current cannabis use (OR = 4.5, 95%CI = 1.4–14.6, p = 0.01), but not by a decrease in HDL-cholesterol (OR = 2.0, 95% CI = 0.89–4.5, p = 0.09) or longer duration of treatment (OR = 1.02, 95%CI = 1–1.04, p = 0.09). The Hosmer-Lemeshow goodness-of-fit test (6.04, p = 0.2) confirmed the acceptability of the binary logistic regression model which accounted for 22% of the variability (Nagelkerke R2). 4. Discussion

Fig. 3. Mixed models repeated measures analysis of treatment response for the BAMM vs the first psychotic episode.

Our results indicate that a substantial portion of patients with firstepisode schizophrenia-spectrum disorders developed breakthrough psychotic symptoms during the first 24 months of treatment, while receiving assured LAI antipsychotic medication in doses to which they had initially responded. The rate of 21% that we found is somewhat higher than that of a previous study in a chronic sample, in which 18.3% developed breakthrough psychosis symptoms while receiving depot antipsychotic (Alphs et al., 2016), although that study was conducted over only one year, while ours was over 24 months. Our rate is similar to the 21.5% relapse reported for LAIs in a meta-analysis of trials lasting at least 12 months (Leucht et al., 2011). Also, our incidence rate of 1.37 per 10 person years was similar to the 1.20 10 person years rate for LAI treatment in the Finnish cohort study (Rubio et al., 2019), suggesting that BAMM occurs at a relevant frequency during both the early and the later stages of treatment. The BAMM rate is lower than the 35% of first episode patients experiencing a hospitalization over 24 months in a large first episode study involving physician's choice antipsychotic medication, (Kane et al., 2016) which is likely related to the fact that b20% were receiving LAIs (Robinson et al., 2015).

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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Studies investigating factors associated with relapse in schizophrenia have, with the exception of medication discontinuation and persistent substance use disorder (Alvarez-Jimenez et al., 2012; Robinson et al., 2019), not identified consistent demographic or baseline clinical predictors, although some found poor premorbid adjustment (Robinson et al., 1999), more severe overall symptoms (Schennach et al., 2012; Robinson et al., 2019), more prior hospitalizations and longer duration of untreated psychosis (Robinson et al., 2019), more treatment side effects (Schennach et al., 2012), older age, previous suicide or self-harm attempts and better social functioning (Almond et al., 2004) to be significant predictors. A systematic review identified 95 studies investigating factors associated with relapse, with antipsychotic discontinuation, stress/depression and substance abuse as the most frequently cited factors associated with relapse (Olivares et al., 2013). To date, few studies investigated relapses during assured antipsychotic medication intake. Of all the potential predictors we examined, only lower baseline positive symptoms, poorer QoL regarding social relations and lower HDL-cholesterol levels predicted the time to emergence of BAMM. This finding would suggest that a different set of variables predict BAMM as opposed to predicting relapse in clinical settings where covert nonadherence may at least in part mediate the effects of risk factors such as substance use and stress. The relationship that we found between poorer baseline QoL and BAMM is of interest. While one previous study found no significant differences in QoL between patients who relapsed and those who did not (Almond et al., 2004), another study using data from a multicentre cohort study of patients with schizophrenia found that a higher level of QoL as assessed by the Short Form 36 scale predicted lower rates of relapse at 24 months for both the Physical and Mental Composite Scores (Boyer et al., 2013). They noted that poorer quality of life has been reported as an independent predictor of clinical outcome and illness recurrence in various chronic diseases, including malignancies, suggesting that good perceived quality of life may be associated with generally increased resilience to illness recurrence. We could not establish a relationship between BAMM and antipsychotic treatment dose. The mean modal dose was similar between those who developed BAMM and those who did not, as was the estimated total antipsychotic exposure. One possible explanation is the relatively small variation in the dose range in this study. In addition, we did not find evidence of dose escalation after BAMM, counting against the development of tolerance in these patients. Furthermore, that lower levels of baseline positive symptoms predicted increased risk for BAMM seems counterintuitive, and suggests against a link between BAMM and treatment refractoriness. While some have found an association between more severe baseline symptoms (Schennach et al., 2012; Robinson et al., 2019), others have found that baseline symptoms did not significantly predict relapse (Robinson et al., 1999; AlvarezJimenez et al., 2012) or that specifically higher negative scores predicted relapse (Wunderink and Sytema, 2017). However, there was only a 1.4 point lower positive symptom score in patients who later developed BAMM, which calls the clinical relevance of this finding into question. Nevertheless, the association of lower baseline positive symptoms with BAMM in our sample should be examined further in future studies. The high rate of cannabis use in our patients is consistent with that reported in other samples of first-episode psychosis (Wisdom et al., 2011). The finding that current cannabis use (as assessed by repeated urine tests throughout the study) was associated with BAMM has important implications. While persistent cannabis use is a recognised risk factor for relapse and poor overall outcome (van der Meer and Velthorst, 2015; Schoeler et al., 2016a) it is not known whether this association represents a direct effect, or whether it is mediated by other factors. Indeed, studies suggest that the relationship is mediated, at least in part, by poor medication adherence (Schoeler et al., 2016b; Zammit et al., 2008; Colizzi et al., 2016). Our results suggest that the association between cannabis use and psychosis relapse stands after removing the confounder of non-adherence with antipsychotic

treatment. Further studies should clarify the potentially causal nature of this association and identify subgroups of patients in whom cannabis use alters antipsychotic treatment response. The relationship that we found between blood lipids and BAMM warrants further consideration, given the in vitro effects of antipsychotic drugs on cellular cholesterol biosynthesis and transport (Skrede et al., 2013). As far as we are aware, this is the first report of an association between blood lipids and symptom recurrence in schizophrenia, although it is well recognised that elevated lipid levels accompanying antipsychotic treatment are associated with a more favourable treatment response. Systematic reviews have reported an association between treatment-emergent weight gain and metabolic changes and clinical response (Kim et al., 2019), and it has been proposed that a shared mechanistic pathway exists between the metabolic changes induced by antipsychotics and their clinical efficacy (Venkatasubramanian et al., 2013). Lally et al. (2013) reported that hypertriglyceridemia predicted clinical response in patients treated with clozapine and suggested that clozapine's therapeutic efficacy is linked to serum lipid changes. Solberg et al. (2015) found significant positive correlations between serum triglyceride levels and PANSSpositive scores and HDL levels and global assessment of functioning (GAF) scores, and significant negative correlations between serum triglyceride levels and GAF scores. However, while our finding that higher pre-treatment HDL levels were associated with BAMM is consistent with this proposal, the association between greater treatmentemergent increases in LDL and BAMM is not, thereby suggesting a more complex relationship between lipids and treatment efficacy. Moreover, one important consideration with these associations is the confound of better treatment adherence being associated with both increased lipid levels and better treatment response (De Hert et al., 2011). Nevertheless, our finding is of potential significance, and further exploration of the relationship between lipid levels/changes and BAMM seems warranted. The mechanisms underlying the re-emergence of psychotic symptoms with ongoing antipsychotic treatment in individuals who previously responded to treatment are also poorly understood. Whether this event represents illness recurrence, or whether it is a breakthrough or rebound phenomenon, is not known. One possibility is that BAMM may be related to effects of antipsychotic treatment per se, and dopamine receptor supersensitivity has been suggested as a mechanism. Originally conceptualised by Chouinard et al. (Chouinard et al., 1978; Chouinard and Jones, 1980; Chouinard, 1991), antipsychotic-induced supersensitivity psychosis is proposed to be caused by alteration of mesolimbic or mesocortical dopamine receptors as a result of prolonged antipsychotic blockade, similar to the postulated mechanism of tardive dyskinesia involving changes in the neostriatum (Davis and Rosenberg, 1979). In animal models, chronic administration of antipsychotics upregulates D2 receptors and produces receptor supersensitivity, manifested by behavioural supersensitivity to dopamine (Burt et al., 1977), providing a model for movement disorders and supersensitivity psychosis in humans (Chouinard et al., 2017). While supersensitivity psychosis was originally described in the context of antipsychotic withdrawal or dose reduction, it has been proposed to also occur in the context of ongoing antipsychotic treatment. Dopamine supersensitivity develops early during antipsychotic exposure and has been linked to loss of antipsychotic efficacy and treatment failure as a breakthrough phenomenon (Samaha et al., 2007). Supersensitivity psychosis has been suggested to be responsible for 39% of relapses occurring in patients compliant with antipsychotic medication, as diagnosed by cooccurrence of tardive dyskinesia and relapse (Fallon et al., 2012). However, arguments against dopamine supersensitivity being the main driver of relapses include a rather linear development of relapses after antipsychotic treatment discontinuation, similar relapse rates in a placebo-controlled relapse prevention meta-analysis independent of whether the antipsychotic was withdrawn abruptly or slowly, and lack of significant advantages of partial dopamine D2 agonists for

Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025

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relapse prevention, although they cause less/no postsynaptic upregulation of dopamine receptors (Correll et al., 2018). Nevertheless, proposed features of supersensitivity psychosis include testable elements, such as tolerance to previously observed therapeutic effects of antipsychotics, need for dose escalation, emergence of treatment refractoriness, and the presence of tardive dyskinesia and other drug-induced movement disorders (Chouinard et al., 1978). Additional features include high levels of prolactin, exacerbation of symptoms by stress and more severe negative symptoms. Furthermore, if symptom recurrence is not related to illness recurrence, the two should have their own distinct symptom profiles. In particular, symptoms should be more severe and psychological symptoms associated with rebound or discontinuation syndromes, such as anxiety, dysphoria, aggression and excitement, and physiological symptoms, such as tachycardia and hypertension could be expected. In contrast, in the event of illness recurrence, similar symptoms to the previous episode would be anticipated (Emsley et al., 2018). We did not find signs of supersensitivity psychosis in the patients who developed BAMM, insofar as they did not experience antipsychotic dose escalation, increased rates of dyskinesia or parkinsonism, elevated prolactin levels or more severe negative symptoms. Also, we did not find other physiological or psychological signs that could be associated with a breakthrough phenomenon. The patients who developed BAMM did not display elevated blood pressure, tachycardia or more symptoms of anxiety, dysphoria or excitement. This finding is consistent with the recent study of BAMM in the Finnish cohort, which also did not support the dopamine supersensitivity hypothesis as a mechanism involved in BAMM (Rubio et al., 2019). We did, however, find that the post-BAMM treatment response was significantly attenuated compared to that of the first psychotic episode. This finding is consistent with others who found evidence of less adequate response after relapse associated with medication discontinuation (Lieberman et al., 1996; Wiersma et al., 1998; Emsley et al., 2012; Emsley et al., 2013; Takeuchi et al., 2019), suggesting that relapse events may be a critical factor in the evolution of treatment-emergent refractoriness. Several study limitations need to be considered. First, this was a post-hoc analysis of a study whose primary aims were not related to BAMM. Second, the relatively small sample restricted our power to detect differences between BAMM subjects and the rest of the sample. Third, a longer period of treatment may have resulted in more cases of BAMM emerging. Fourth, our findings are not necessarily generalizable to populations treated with other antipsychotics with different receptor binding profiles. Fifth, it could be argued that for 6 participants who were treated with LAI risperidone for 12 weeks initially, the switching to flupenthixol may have predisposed them to relapse. We consider this unlikely however, as we used consensus-derived to calculate dose equivalence for switching (Gardner et al., 2010), and while two of these participants experienced BAMM episodes they occurred much later, at 15 and 21 months. Finally, despite the use of LAIs it is possible that non-adherence could have played a role in relapses. However, the patients were carefully followed and our outreach approach ensured high levels of adherence in both groups (97.7 ± 3.5% vs 98.4 ± 4.0%, t = −0.74, p = 0.46). Strengths of the study include the following: by including minimally treated, first-episode patients, we were able to reduce the effects of illness chronicity and previous treatment; the use of standardised treatment with a single antipsychotic eliminated the risk of confounding effects of different antipsychotics; the LAI formulation provided assured delivery of antipsychotic medication, removing the confound of covert non-adherence; and the comprehensive characterisation of our sample allowed us to investigate multiple potential predictors and correlates of BAMM. In summary, about one in five patients with first-episode schizophrenia developed BAMM during the first two years of treatment. While few significant predictors of BAMM were identified, our findings suggest that persistent cannabis use and poorer quality of life in social relationships increase the risk of BAMM, independent of non-

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adherence. Also, a possible association between BAMM and blood lipids should be explored in future studies. Finally, we did not find evidence for dopamine supersensitivity being a main driver of BAMM, but the poorer post-BAMM treatment response compared to that of the firstepisode in the same patients suggests a relationship between BAMM and emergent refractoriness. Clearly, in view of the frequency of BAMM, its relevance and the lack of studies of this phenomenon, more research is needed. Contributors RE drafted the manuscript and with LA undertook the statistical analysis. All authors contributed to the design of the study and provided revisions to the manuscript. All authors have approved the final manuscript. Role of funding sources The funding sources had no role in the design of the study, nor during its execution, analyses, interpretation of results and drafting of the manuscript. Declaration of competing interest RE has participated in speakers/advisory boards and received honoraria from Janssen, Lundbeck, Servier and Otsuka, and has received research funding from Janssen and Lundbeck. LA has no interests to declare. JMR has participated as speaker and in advisory board for Lundbeck. CUC has been a consultant and/or advisor to or has received honoraria from: Alkermes, Allergan, Angelini, Boehringer-Ingelheim, Gedeon Richter, Gerson Lehrman Group, Indivior, IntraCellular Therapies, Janssen/J&J, LB Pharma, Lundbeck, MedAvanteProPhase, Medscape, Merck, Neurocrine, Noven, Otsuka, Pfizer, Recordati, Rovi, Servier, Sumitomo Dainippon, Sunovion, Supernus, Takeda, and Teva. He has provided expert testimony for Bristol-Myers Squibb, Janssen, and Otsuka. He served on a Data Safety Monitoring Board for Boehringer-Ingelheim, Lundbeck, Rovi, Supernus, and Teva. He received royalties from UpToDate and grant support from Janssen and Takeda. He is also a shareholder of LB Pharma. JMK has been a consultant and/or advisor to or has received honoraria from: Alkermes, Allergan, IntraCellular Therapies, Janssen/J&J, LB Pharma, Lundbeck, Medscape, Merck, Neurocrine, Otsuka, Pierre Fabre, Sumitomo Dainippon, Roche, Sunovion, Takeda, and Teva. He has provided expert testimony for Bristol-Myers Squibb, Janssen, and Otsuka. He served on a Data Safety Monitoring Board for Boehringer-Ingelheim, Lundbeck, Rovi, Supernus, and Teva. He received royalties from UpToDate and grant support from Janssen and Takeda. He is a shareholder of LB Pharma and The Vanguard Research Group. Acknowledgements This study was funded by a New Partnership for Africa's Development (NEPAD) grant, through the Department of Science and Technology of South Africa, the South African Medical Research Council ‘SHARED ROOTS’ Flagship Project Grant no. MRC-RFA-IFSP-012013 and an unrestricted grant from Lundbeck International.

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Please cite this article as: R. Emsley, L. Asmal, J.M. Rubio, et al., Predictors of psychosis breakthrough during 24 months of long-acting antipsychotic maintenance treat..., Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.11.025