Jens Egeland Sykehuset i Vestfold, Psykologisk

Institutt, UiO

The psychometrics of Matrics

A specialized instrument for measuring changes in cognitive function

Could additional functional and predicitive value be added by new measures?

Matrics Consensus Cognitive Battery (MCCB)

• “the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) project resulted in the MCCB test battery in 2008

• Support from NIMH and FDA

• The overarching goal of MATRICS was to construct a pathway for drug approval in schizophrenia

• Sensitive to change more important than reliable cognitive profile

Current «Nasjonal faglig retningslinje for utredning, behandling

og oppfølging av personer med psykoselidelser» (2013)

• Recommends NP assessment of first episode psychosis. – «En kognitiv screening vil kunne vise om det er

aktuelt med en mer omfattende funksjonsvurdering. En omfattende kognitiv undersøkelse vil kunne gi utfyllende informasjon om funksjonsnivået, inkludert sterke og svake sider, samt behovet for tilrettelegging.«

the Matrics battery somewhere in between the recommended screening

battery and the comprehensive NP-battery

• Norwegian norms: 300 typically functioning persons aged 12-69. 50 persons pr age cohort.

• «Våre resultater avviker noe fra funnene i den amerikanske

normative studien av MCCB, men skårene befinner seg stort sett innenfor et standardavvik av de amerikanske normene. Derfor konkluderer vi med at de amerikanske normene for MCCB er egnet til bruk i utreding av nevrokognitiv funksjon i Norge.» (Mohn, Sundet, Rund , 2013)

Matrics:

1. Trail Making Test- A 2. BACS Coding 3. HVLT-R (- delayed memory+ recogn) 4. WMS-II Spatial Span 5. Letter Number Span 6. NAB Mazes 7. Brief Visual Memory Test-R 8. Category fluency 9. (MSCEIT) 10.CPT-Identical Pairs

Factor structure:

• Constructed to measure 7 factors: speed of

processing, attention/vigilance, working memory, verbal learning, visual learning, reasoning and problem solving, and social cognition. Shown to be unstable?

• Burton (2013): 3 factor model (-MSCEIT): Processing speed, attention/WM, memory.

Coding, SS & BVMT accounts alone for 83 % of variance in global score.

In the Clinic:

• Advantage with short tests (more patients will be testable).

• Testing should be able to give new information (not only confirm a deficit that everyone know already…): – A global score not sufficient, but must give

information about: • Modality discrepancies

• Give a valid and reliable profile (should measure speed and WM across input and output modalities)

– Prediction

Do we need a full NP or could we get more out of MATRICS:

• Methodological position: the quantitative process approach: Deconstrue performance by computing additional measures.

• Preliminary data from the Ephaps (Effect of Physical Training in Psychosis) project.

• So far: Deconstructing Category Fluency and Verbal Memory

• Overall question in cognitive testing in schizophrenia: What mediates different types of cognitive impairment: Specifically the relationship between symptoms and cognition

Included as of spring 2016: Mean S.D. Range

N 64 M 39, F 25

Age 36.7 yrs. 14.3 20-67

Educ. 11.8 yrs. X 9-17

PANNS tot 66.1 15.5 38-111

PANNS-P 9.9 4.1 4-21

PANNS N 14.9 6.3 6-29

WAIS GAI 87.8 16.6 54-132

MCCB

cognitive

total

34.5 8.3 15-55

Fluency

• Category & Fonemic: – Category (animal naming) measures speed and

semantic memory integrity (Egeland et al., 2006)

– Fonemic: (FAS) measures speed and executive function

• Reverberi (2014): computed 8 additional measures to total responses: differentiated between different types of dementia

• Troyer (2000): Clustering and switching – Clustering=automatic – Switching =effortful, frontal functioning

Overall category fluency performance:

The dyssemantic hypothesis

• Expecting a specific association between Similarities and Fluency and not to Mazes (EF)

• Results: – Similarities and Fluency: r= .45 (p<.001) Controlling for

Mazes: r= .42 (p=.001)

– Mazes and Fluency: r=.18 (n.s.) Controlling for Similarities: r=.02

• Giving support for the Dyssemantic hypothesis (two variants: overactivation (Brebion, 2013) and disorganization (Condray,2010).

Overall fluency performance:

Relation to negative and positive symptoms

• Generally: findings of relationships between cognitive function and pos/neg. symptoms are inconsistent.

• Hypothesis that – negative symptoms related to frontal dysfunction

(attention/EF impairments) – positive symptoms related to temporal lobe

dysfunction (amnesia and semantic disorders).

• Original PANSS negative scale contaminated by 3 cognitive items. (Wallwork: a separate cognitive scale).

Analysis:

• Sample divided in above/below median level of positive and negative symptoms.

• Both groups had equal PANSS total score

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< median > median

Positive

Negative

Total Fluency performance for subjects above/below median negative symptoms

Positive symptoms-groups: p :0.43 Negative symptoms-groups: 0:.007

Few symptoms: good performance

Many symptoms: impaired performance

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14

16

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< median > median

Positive

Negative

Fluency performance for subjects above/below median negative and positive symptoms

Positive symptoms-groups: p :0.43 Negative symptoms-groups: 0:.007

Many symptoms: better performance

Negative symptoms and fluency

Low negative symptoms (21)

High negative symptoms (28)

Negative symptoms 10.0 (4.9) 19.9 (3.8) +

Positive symptoms 9.4 (3.3.) 9.6 (2.9)

Fluency effectiveness 20.5 (5.3) + 16.4 (4.6)

Switches 8.9 (2.7) + 6.2 (3.1)

Clusters 4.9 (1.4) n.s. 4.2 (1.7)

Single words 4.7 (2.9) + 3 (2.7)

High negative symptoms: Impaired overall fluency, Fewer Switches (executive measure) and fewer Single words (inhibition of response?) Clusters: (automatic) not related

Positive symptoms and fluency Below median positive symptoms (n=26)

Above median positive symptoms (n=23)

Positive symptoms (Wallwork)

6.5 (1.8) 13.3 (3.3) +

Negative symptoms 15.6 (5.6) 15.3 (6.8) n.s.

Fluency effectiveness 17.5 (4.7) 20.3 (6.8) +

repetitions .15 (.37) .56 (87) +

Switching 6.7 (3.5) 8.2 (2.6) n.s.

Clusters 4.1 (3.5) 4.9 (1.4) n.s.

Single words 3.3 (2.9) 4.1 (2.9) n.s.

High positive symptoms: better overall performance, more repetions + tendency to more Switches (EF) and more single words, no difference in Clusters. Overactivation?

Primacy effect in HVLT-r:

• Primacy effect in list learning: measure of complex Working Memory

• Lack of primacy effect → negative prognosis in dementia

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primacy<25% primacy>25%

PosSymp

NegSympt

Subjects with no primacy effect vs normal primacy: «No primacy» associated with higher negative symptoms.

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primacy<25% primacy>25%

PosSymp

NegSympt

The association between lack of primacy and negative symptoms are specific and do not indicate generally more psychopathology. Those with no primacy effect had somewhat less positive symptoms.

Double dissociation significant. Interaction: F=6.1 P=.016

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65

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Low primacy normal prim

WAIS_GAI

Matrics

«No primacy» group had relatively higher GAI and lower Matrics score than those with normal primacy: Predictive of more severe state impairment? A prognostic marker as in dementia?

Significant double dissociation: Interaction: F=6,96 P=.011

Summing up

• MATRICS has the advantage of being short, but the limitation of not giving thorough information as to deficient processes neccessary for interventions (?).

• Might be possible to add value by adding analyses/measures, but more will follow as the Ephaps data base grows.…