antipsychotic medication

Matti Isohanni, Professor of Psychiatry
(emeritus). Department of Psychiatry, Institute of
Clinical Medicine, University of Oulu, Finland
Midlife progression in brain
tissue loss and clinical
outcomes of schizophrenia
in the Northern Finland 1966
Birth Cohort (NFBC 1966)
Conflicts of interests
No conflicts of interest to declare
This work was supported by unrestricted
grants from
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•
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the Stanley Medical Research Institute,
the Isaac Newton Trust,
the Academy of Finland,
the Sigrid Juselius Foundation,
The Brain & Behavior Research Foundation
General aims:
We analyzed midlife progression of
schizophrenia at ages 34 to 43 years (9 year
follow-up) and its correlates to changes in brain
morphometric changes, antipsychotic
medication, cognition, and clinical outcomes:
1) What happens in outcomes (clinical,
cognitive)?
2) What happens in the brain?
3) The effects of antipsychotic medication?
4) Any clinical conclusions?
Is recovery possible in schizophrenia?
• Clinical and social recovery is possible, median
13.5% (meta-analysis by our group; Jääskeläinen et al.
Sch Bull 2013);
• In old age sz more common: 18-27%
(Jääskeläinen et al Sch Bull 2013)
• Recoveries have not increased during the last
decades, not even during the antipsychotic era –
but decreased!
Jääskeläinen et al. Meta-analysis Sz Bull 2013
Why so few recover?
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(Partly) treatment resistant disease?
Poor treatments and medications?
Poor compliance and adherence?
Demanding modern social environment
and occupational life?
• Iatrogenic hypothesis: antipsychotics
prevent benign natural course in a
subsample and cause poor recovery
(Harrow et al Psychol Med 2014)?
Methods
 Northern Finland 1966 Birth Cohort (NFBC 1966) (N=12058)
has been followed serially since mid-pregnancy at birth, at
ages 1,14, 31 and 46 years. Data linkage to national case etc
registers, hospital charts
 Psychiatric follow-up studies at age 34- and 43-years:
structural and functional MRI, cognitive, and clinical analyses
were performed at the beginning and end of this 9-year followup.
1. at age 34 years: 73 DSM schizophrenic psychoses and 104
controls (mean time since illness onset 11 years)
2. At age 43 years: 55 schizophrenic psychoses and 192 controls
(mean time since illness onset 20 years)
 41 sz cases and 75 controls participated in both surveys
Methods
* Dallas
* Augusta
* Oulu
Brisbane *
General aims:
We analyzed midlife progression of
schizophrenia at age 43 years and its
correlates to changes in brain morphometric
changes, antipsychotic medication, cognition,
and clinical outcomes:
1) What happens in outcomes (clinical,
cognitive)?
2) What happens in the brain?
3) The effects of antipsychotic medication?
4) Clinical conclusions
1) What happens in outcomes?
Cross-sectional outcome data at age 34 years in NFBC
1966 (Lauronen et al. 2007, Miettunen et al. 2006)
The outcome of schizophrenic psychoses is
heterogeneous:
•minority of individuals experience recovery
(3.4%)
•some but not many achieve at least periods
of symptomatic remission (23%) – 77% not.
•many are on disability pension (54%)
•most require re-hospitalisation (81%)
1) What happens in outcomes at age 43?
Cross-sectional outcome data from the latter follow-up at age
43 years in NFBC 1966 (Jääskeläinen et al. manuscript):
(at age 34 years similar as at age 43; Lauronen et al.
Sch Res 2008)
▪ 2.8% (one person) recovered
▪ 22% achieved remission
▪ 36% were not on disability pension
▪ 54% used no or at most 300mg/day
antipsychotic medication (as chlorpromazineequivalents)
Prodictors of poor outcomes
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Early onset age
Insidious onset
Long DUP
Suicidal ideations at the beginning
Poor scholastic performance
Deviant birth weight and length
Reduced density (volume) in frontal
and temporal areas and white
matter
Cognitive performance
• Neurocognitive performance, especially visual learning
and memory associated to poor functional or global
outcomes both in the longitudinal and cross-sectional
analyses (Juola et al in review).
• Cognitive performance decreased in 9 years between 34
and 43 years, and this was also the case in controls
• High antipsychotic dose years were related to poor
cognition (adjusted with multiple clinical aspects) Husa et
al Sch Res 2014)
 “The results do not support the view that antipsychotics
in general prevent cognitive decline or promote cognitive
recovery in schizophrenia” (Husa et al Sch Res 2014)
General aims:
We analyzed midlife progression of
schizophrenia at age 43 years and its
correlates to changes in brain morphometric
changes, antipsychotic medication, cognition,
and clinical outcomes:
1) What happens in outcomes (clinical,
cognitive)?
2) What happens in the brain?
3) The effects of antipsychotic medication?
4) Clinical conclusions
Results (Veijola et al PLoS ONE 2014)
 Differences in total brain volume change between patients
and controls between ages 34 to 43:
•The mean annual total brain volume reduction was 0.69% in
schizophrenia and 0.49 % in controls. The reduction was
significant after adjusting for sex, educational level, alcohol
use and weight change.
 Does change in brain volume predict clinical outcomes in
schizophrenia?
•In linear regression, total brain volume reduction was not
associated with the mean total PANSS score, change in the
total PANSS score, mean SOFAS score or change in SOFAS
score in schizophrenia. Brain volume reduction also did not
associate with means of PANSS sub-scores or changes in
PANSS sub-scores.
General aims:
We analyzed midlife progression of
schizophrenia at age 43 years and its
correlates to changes in brain morphometric
changes, antipsychotic medication, cognition,
and clinical outcomes:
1) What happens in outcomes (clinical,
cognitive)?
2) What happens in the brain?
3) The effects of antipsychotic medication?
4) Clinical conclusions
How to measure lifetime use of
antipsychotic medication?
• Current and lifetime use of antipsychotic medication was
ascertained from interviews, registers, hospital and
outpatient case notes.
• We measured the chlorpromazine equivalents (Kroken et al
BMC Psych 2009) and used daily dose of 100 mg of
chlorpromazine for calculating dose years of lifetime
antipsychotic medication (Andreasen et al. Biol Psych
2010, Husa et al Sz Res 2014, Veijola et al PLoS ONE
2014).
• Daily 100 mg chlorpromazine eq during 9 years follow-up
is 9 dose years
• Daily 350 mg chlorpromazine (mean approx dose in NFBC
1966) during 9 years follow-up is 32 dose years
Results (cont): Is exposure to antipsychotic medication
associated with loss of total brain volume over time?
 The annual reduction in brain volume was associated with higher
number of dose years of antipsychotic medication (linear regression;
p=0.003). After adjusting for symptom severity and social functioning
(mean total PANSS score, change in total PANSS score, mean SOFAS
score, change in SOFAS score), logarithm of alcohol use and weight
gain the association still remained significant. (Veijola et al PLoS ONE
2014)
 In separate linear regression analyses, the annual reduction in brain
volume was associated with higher number of dose years of typical and
atypical antipsychotic medication (typical p=0.034; atypical p=0.005);
no interaction by type.
Linear regression between dose years (equivalent to daily 100 mg chlorpromazine) of
antipsychotics and annual change in brain volume (%) in subjects with schizophrenia
(beta=-0.47, t=-2.98, p=0.006). High exposure to antipsychotic medication associated
with loss of brain volume over time. Daily 350 mg chlorpromazine (mean approx dose in
NFBC 1966) during 9 years follow-up is 32 dose years (Veijola et al PLoS ONE 2014).
Annual brain volume reduction (%) in control subjects and in subjects with schizophrenia
in three dose year (equivalent to daily 100 mg chlorpromazine) categories of
antipsychotic medication. E.g. daily 350 mg chlorpromazine during 9 years is 32 dose
years. (Veijola et al PLoS ONE 2014)
Results (cont): Regional voxel-based analyses FSL
voxelwise SIENA (Guo et al in review)
 Progressive brain volume reduction in schizophrenia during the 9-year
follow-up was widespread and found especially in temporal lobe and
periventricular area.
 Total antipsychotic medication exposure was associated with
reductions around ventricles
 No significant differences in the effects of typical and atypical
antipsychotic medication. However, power limited
 Decline in social and occupational function was associated with right
supramarginal gyrus reduction and was independent from antipsychotic
medication exposure
Regions with greater loss of brain volume in schizophrenia during 9-year follow-up
compared to controls (adjusted for sex, handedness and interscan interval, p <
0.05 family-wise error corrected across brain edge): right frontal pole, right middle
and inferior frontal gyrus, bilateral central gyrus, bilateral supramarginal gyrus,
bilateral temporal lobe (including superior, middle and inferior divisions), right
occipital cortex inferior division, right lingual gyrus (mid-line occipital lobe), and
bilateral precuneous cortex. (Guo et al, in review)
Total antipsychotic medication exposure during 9 year
follow-up was associated with reductions around
ventricles (Guo et al in review)
Guo et al in preparation
Discussion
• The disease process itself may cause the decrease
(Lieberman 1999)
• Do iatrogenic factors such as antipsychotic medication
contribute to the excessive brain tissue loss? (Ho et al.
2011, Van Haren et al. 2011). Key question in clinical
psychiatry!
Discussion (cont)
Progressive volume changes have previously been
demonstrated in schizophrenia patients selected from clinic or
ward based cohorts, in comparison to controls who have been
recruited from the community by advertisement (Hulshoff Pol
and Kahn 2008, Olabi et al 2011).
Our study is the first to report progressive loss of brain volume
in patients and controls recruited in a population-based sample
and midlife (where most patients are).
There was a dose-response relationship in schizophrenia
between cumulative exposure to antipsychotic medication and
brain volume loss over time, providing some evidence that
antipsychotic medication may cause loss of brain volume over
Discussion (cont)
We addressed potential confounding factors by controlling for
illness severity, yet the association between brain volume
change and medication dose remained statistically significant.
However, in naturalistic setting there is possibility for residual,
latent confounding – very sick patients get higher doses for
longer duration.
Do typical and atypicals differ?
• Not in this study. Both typical and atypical medications
predicted brain volume loss. However, number of cases
and statistical power was limited.
• They differ from some results, which found that typical, but
not atypical, antipsychotic medication predicted brain
cortical thinning in schizophrenia (Lieberman et al AGP
2005, Van Haren AGP 2012).
• Both typical and atypical antipsychotic agents have been
shown to produce loss of brain volume in experimental
rodents (Vernon et al Biol Psych 2011) and monkeys
(Dorph-Peterson et al Neuropsychopharm 2005).
Meta-analysis: Longitudinal studies on
antipsychotics and brain volumes.
Huhtaniska et al in submission
 Heterogeneous methods and findings!
 In total 29 publications from 16 different samples
fulfilled our inclusion criteria: scan interval over 2
years
 In meta-analysis higher antipsychotic exposure
associated statistically significantly with decrease in
parietal lobe (n=4; r=-0.14, p=0.013) and with increase
in basal ganglia volume (n=4; r=0.10, p=0.044).
 In general, most of the reported correlations between
brain volume alterations and antipsychotic dose were
statistically non-significant.
Meta-analyses brain volumes and antipsychotic exposure by tissue
type and brain area combinations. (Huhtaniska et al in submission)
studies
n
GM
- total
- cerebrum
- frontal lobe
WM
- cerebrum
CSF
- CSF and ventricles
Volume
- total brain
- cerebrum
- frontal lobe
- temporal lobe
- parietal lobe
- occipital lobe
- cerebellum
- limbic system
- basal ganglia
random effect meta-analysis
correlation (95%
z test
CI)
sign.
n
3
3
3
0.04 (-0.10-0.17)
0.08 (-0.29-0.45)
-0.04 (-0.22-0.13)
0.55
0.41
0.46
0.58
0.68
0.64
1
2
2
3
0.04 (-0.07-0.16)
0.72
0.47
1
6
0.10 (-0.09-0.28)
1.03
0.31
4
77
-0.06 (-0.23-0.10)
-0.08 (-0.19-0.02)
-0.16 (-0.34-0.02)
-0.12 (-0.27-0.03)
-0.14 (-0.26- -0.03)
-0.06 (-0.24-0.11)
0.01 (-0.09-0.11)
-0.03 (-0.13-0.08)
0.10 (0.002-0.19)
0.73
1.54
1.71
1.54
2.49
0.68
0.20
0.48
2.01
0.47
0.12
0.09
0.12
0.013
0.50
0.84
0.63
0.044
3
2
6
6
3
2
3
2
4
80
0
67
64
0
0
0
0
0
6
3
8
10
4
3
5
3
4
hete
Meta-analysis was done for categories with at least three samples.
90
81
General aims:
We analyzed midlife progression of
schizophrenia at age 43 years and its
correlates to changes in brain morphometric
changes, antipsychotic medication, cognition,
and clinical outcomes:
1) What happens in outcomes (clinical,
cognitive)?
2) What happens in the brain?
3) The effects of antipsychotic medication?
4) Clinical conclusions
What is the significance of loss of brain
volume in schizophrenia?
• At present, the clinical significance of antipsychotic
induced brain volume reduction is uncertain (harmful
loss? harmless loss? delayed pruning?)
• Do we scare - without scientific arguments –
numerous patients and clinicians that antipsychotics
shrink the brain?
• Loss of brain volume occurs throughout adult life in
the healthy population.
• Optimising and minimising antipsychotic medication
might, however, be one targeted intervention.
• Main reason are neurological, metabolic and
cognitive side effects, not speculative brain effects
Clinical conclusions (cont)
• Antipsychotic medications are used increasingly on-label or
off-label (Rissanen et al Human Psychopharm 2013),
including dementia, bipolar disorder, unipolar depression,
and in a variety of childhood psychiatric conditions
• Resposes to antipsychotics are heterogeneous and
individualized. Group-level effect size is about 0.4 but
individual responses vary from 0 to 0.8.
• Antipsychotics may have potentially serious side-effects (in
addition to neurological and metabolic) and should be used
with considerable caution, especially in conditions where
their efficacy has not been established
• It is possible that some schizophrenia cases with small
relapse risk are overmedicated
Clinical conclusions (cont)
• “Nothing is known about the effects of antipsychotic drugs
compared to placebo after three years” (Leucht et al Cochr
Database 2012)
• A subsample of sz patients may show good outcomes
without prolonged antipsychotic treatment (Bleuler 1978,
Fenton and McGlashan 1987, Harding et al 1987,
Wunderink et al 2013, Harrow et al 2014)
• Reduced use or dose is one alternative (Isohanni 1983,
Ciompi and Hoffman 2004, Bola et al 2009)
• In a subsample antipsychotics may cease to have positive
effects and long-term efficacy: excess or supersensitive
dopamine receptors may cause this
 This is very common phenomenon in somatic medicine
(cancers, asthma, PD)
Wunderink
2013;
reduction
Wunderink
2013;
maintenanc
e
14
(160mg/day:
Isohanni
1983 cases)
13,5
(150mg/day)
33
(370mg/day:
Isohanni 1983
controls)
81
(900mg/day)
Linear regression between dose years (equivalent to daily 100 mg chlorpromazine) of
antipsychotics and annual change in brain volume (%) in subjects with schizophrenia
(beta=-0.47, t=-2.98, p=0.006). High exposure to antipsychotic medication associated
with loss of brain volume over time. Daily 350 mg chlorpromazine (mean approx dose in
NFBC 1966) during 9 years follow-up is 32 dose years (Veijola et al in revision).
Is it possible to reduce dose
or discontinue medication?
• The first long-term (7-year) follow-up of a randomized early dose
reduction/discontinuation clinical trial was published recently by
Wunderink et al (2013).
• The study demonstrates superior long-term functional outcome in
the dose reduction/discontinuation group, even though the initial
relapse rate was about two-fold higher.
• In dose reduction group, the mean daily dose (as haloperidol
equivalents) was quite low (2.79 mg) compared to the maintenance
group (4.08 mg).
• In most treatment algorithms, the recommend range in maintenance
treatment varies between 150-900 mg/day as chlorpromazine
equivalents or 3-18 mg as haloperidol equivalents, to be continued
at least 1 year after the first episode and 5 years after multiple
episodes (Gaebel et al 2005).
Difficulties to predict patients advancing tapering
•
There seems to be a subgroup of patients (15-20%?) with schizophrenia
who manage well especially at the stabilized phase, especially with regards
to functional remission, with small doses of antipsychotics, and even without
permanent antipsychotic medication. Other (poorly known and partly
overlapping) subgroups may be: treatment-resistants, ex-responders, noncompliance patients, etc.
•
Presently, there are no replicated predictors of patients who respond well to
a dose reduction/discontinuation strategy.
•
Maximal use of psychosocial interventions reduced the dose of
antipsychotics (as chlorpromazine equivalents) in an acute psychosis ward
from 370 mg/day to 160 mg/day (Isohanni 1983), which is the level identical
to Wunderink’s et al (6) dose reduction/discontinuation group.
•
This result suggests that in a well-organized treatment entity and
individualized treatment program with a lot of non-pharmacological care
(McGorry et al 2013, McGurk et al 2013, Mueser et al 2013), patient and
family guidance, and accurate diagnostics, dose reduction may be a more
relevant strategy, contrasted to a situation where antipsychotics are the only
active treatment.
Future research is needed
• Most studies supporting maintenance treatment on antipsychotic
medication are performed with relatively short follow-ups and initial
phase.
• However, most patients with schizophrenia are in midlife and the
duration of illness is 10-20 years.
• Randomized controlled trials have methodological problems:
selection and attrition biases, poor compliance, short follow-up
periods, slow study processes.
• Case-control studies do not detect the heterogeneity of effects and
different individual/subgroup effect sizes
• In an observational, naturalistic setting (e.g registers and cohorts in
Nordic Countries), there are many methodological challenges. The
patients are not treated randomly. This may cause residual, latent
confounding: very sick patients often get higher doses and a longer
duration of antipsychotic medications. This problem can often be
controlled
Will clinical decision-making change?
•
Ethical principles provide guidance, especially Hippocrates´ principle
of rejecting mischief. He teaches us: primum non nocere (first, do not
harm).
•
This is one reason to consider the minimizing antipsychotic doses and
maximizing psychosocial treatments.
•
However, even a very experienced clinician may be prone to
“pessimism or clinical bias”: he often meets selectively difficult,
treatment-resistant and complex patients, but cases with good
response and recovery are lost to follow-up.
•
All this may reduce his courage to taper or discontinue antipsychotic
medication and leave these decisions solely to the patients.
•
Current care guidelines are undifferentiated and vague in regards to
dose tapering and discontinuation, and to recommended psychosocial
interventions.
•
Current guidelines make low doses and discontinuation possible, but
do not specifically encourage this strategy or suggest how to go about
tapering antipsychotic doses (i.e., at what point in the clinical course
of illness, over what time period, etc.).
Take home message
• We do not know the real effectiveness and benefits/risks of
antipsychotic drugs from longitudinal (midlife schizophrenia) and
lifespan view.
• Stochastic factors and chance (e.g. non-compliance) influence (too)
much to antipsychotic practices in longitudinal perspective
• Scientific understanding of many major somatic disorders (e.g.
cancers, cardiovascular diseases) has increased dramatically. Such a
breakthrough has not been achieved in schizophrenia.
• To minimise risks we may overmedicate many patients which harms
some
• Most patients do not have optimal non-pharmacological or
pharmacological care (In NFBC 1966 one third of overtly psychotic
patients had no contact to any treatment systems; Nykänen et al in
preparation)
• New data does not change current care guidelines but may expand
clinical decision making into lower doses, stopping medication, and
biopsychosocial care.
Acknowledgements:
This work was supported by grants from
• the Stanley Medical Research Institute,
• the Isaac Newton Trust,
• the Academy of Finland,
• the Sigrid Juselius Foundation,
• NARSAD
Software development for image analysis was supported by a
• Human Brain Project grant from the National Institute of
Biomedical Imaging & Bioengineering and
• The National Institute of Mental Health.
Thanks!
For giving data and slides: Erika Jääskeläinen, Jouko Miettunen, Graham
Murray, Joyce Guo, Juha Veijola, Sanna Huhtaniska, Salla Nykänen
UOulu: Matti Isohanni, Juha Veijola, Jouko Miettunen, Erika Jääskeläinen (nee
Lauronen), Sanna Huhtaniska, Päivikki Tanskanen, Hannu Koponen, Antti Alaräisänen,
Marianne Haapea, Salla Nykänen, Pirjo Mäki, Matti Penttilä, David Cowling, Irina
Rannikko, Irene Isohanni, Kristiina Moilanen, Johanna Koskinen, Marjo-Riitta Järvelin,
Anja Husa, Vesa Kiviniemi, Osmo Tervonen.
UEastern Finland/Helsinki: Hannu Koponen, Heli Koivumaa-Honkanen, Jari Tiihonen
UCambridge: Graham Murray, Joyce Guo, Peter Jones, Khanum Ridler, Edward
Bullmore, Anna Barnes, J. Suckling
Medical College of Georgia: Brian Miller, Brian Kirkpatrick
UTSW, Dallas: Carol Tamminga, Subroto Ghose, Elena Ivleva
UQueensland: John McGrath, Joy Welham
LMU, Munich: Hans-Jurgen Möller
Finland: about 11000 Cohort members and their relatives, about 100 scientific
partners