Symptom patterns and the course of depression
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1 Symptom patterns and the course of depression Claudia van Borkulo University Medical Center Groningen - University of Amsterdam Promotors: R.A. Schoevers, D. Borsboom
2 Resilient system Insomnia Concentration Mood Vulnerable system Insomnia Concentration Mood From Denny Borsboom
3 Outline Design of study Initial results Tackle some issues More results Discussion
4 Outline Design of study Initial results Tackle some issues More results Discussion
5 Outline Design of study Initial results Tackle some issues More results Discussion
6 Outline Design of study Initial results Tackle some issues More results Discussion
7 Outline Design of study Initial results Tackle some issues More results Discussion
8 Design of study 515 patients with MDD at baseline: those with persistent MDD (n = 253) and those with remitted MDD (n = 262) Networks estimated on 11 DSM criteria: from IDS at baseline Comparison of networks: Network Comparison Test Van Borkulo, Boschloo, Borsboom, Penninx, Waldorp, Schoevers. Association of symptom network structure with the course of depression. JAMA Psychiatry. 2015;72(12):
9 Design of study Depressed Persister Not depressed Remitter
10 Design of study Baseline
11 Design of study Baseline 2-year follow-up
12 Design of study Baseline 2-year follow-up
13 Design of study Baseline
14 Baseline
15 Baseline Persisters (253) Remitters (262) baseline
16 Design of study Network estimation Advanced method: L1-regularized partial correlations Epskamp et al., 2012 Regularization: to find optimal balance between parsimony and goodness of fit of the network Low false positive rate Van Borkulo et al., 2014
17 Design of study 1" 2" 3" 4" 5"!!6!!!7!!!8!!!9! 10! Permuted(data(and(networks Group(A Group(B Network comparison With newly developed Network Comparison Test (NCT) Permutation test!!9!!!7!!!2! 10!!!5!!10!!!!9!!!!5!!!!7!!!!4!!!3!!!6!!!4!!!1!!!8!!!!6!!!!3!!!!8!!!!1!!!!2! 1" 2" 3" 4" 5"!!9!!!7!!!2! 10!!!5!!10!!!!9!!!!5!!!!7!!!!4! Observed(data(and(networks Group(A!!6!!!7!!!8!!!9! 10! Permuted(data(and(networks Group(A!!3!!!6!!!4!!!1!!!8!!!!6!!!!3!!!!8!!!!1!!!!2! Group(B Group(B observed difference Area Between Curves observed difference NCT performs well in a range of circumstances Type I error rate is close to the nominal significance level Power is sufficiently high if sample size and/or difference between networks are large enough Van Borkulo, Boschloo, Kossakowski, Tio, Schoevers, Borsboom, Waldorp. Comparing network structures: A permutation test. (in prep).
18 25% edges cut from one equally sized group 25% edges cut from smallest group 25% edges cut from largest group % edges cut from one equally sized group 50% edges cut from smallest group 50% edges cut from largest group Design of study 1" 2" 3" 4" 5"!!6!!!7!!!8!!!9! 10! Permuted(data(and(networks Group(A Group(B Network comparison With newly developed Network Comparison Test (NCT) Permutation test!!9!!!7!!!2! 10!!!5!!10!!!!9!!!!5!!!!7!!!!4!!!3!!!6!!!4!!!1!!!8!!!!6!!!!3!!!!8!!!!1!!!!2! 1" 2" 3" 4" 5"!!9!!!7!!!2! 10!!!5!!10!!!!9!!!!5!!!!7!!!!4! Observed(data(and(networks Group(A!!6!!!7!!!8!!!9! 10! Permuted(data(and(networks Group(A!!3!!!6!!!4!!!1!!!8!!!!6!!!!3!!!!8!!!!1!!!!2! Group(B Group(B observed difference Area Between Curves observed difference NCT performs well in a range of circumstances Proportion p<= Proportion p<= Proportion p<= Type I error rate is close to the nominal significance level Power is sufficiently high if sample size and/or difference between networks are large enough Proportion p<=.05 Proportion p<= Sample size equal sample sizes unequal sample sizes Proportion p<= Sample size Sample size Sample size Proportion p<= Proportion p<=.05 Proportion p<= Sample size Sample size Sample size Sample size Sample size Van Borkulo, Boschloo, Kossakowski, Tio, Schoevers, Borsboom, Waldorp. Comparing network structures: A permutation test. (in prep).
19 Initial results dep dep sui int sui int con wap con wap gui ins gui ins ene hyp ene hyp ret agi ret agi Persisters Remitters
20 Initial results dep dep sui int sui int con wap con wap gui ins gui ins ene hyp ene hyp ret agi ret agi Persisters P =.01 Remitters
21 But
22 Tackle some issues Are results confounded by baseline severity? Two strategies to tackle this issue: 1. Match number of patients with same IDS sum score 2. Matching by partialing out severity
23 Tackle some issues Are results confounded by baseline severity? Two strategies to tackle this issue: 1. Match number of patients with same IDS sum score 2. Matching by partialing out severity
24 Tackle some issues Are results confounded by baseline severity? Two strategies to tackle this issue: 1. Match number of patients with same IDS sum score 2. Matching by partialing out severity
25 Tackle some issues sui dep int sui dep int sui dep int con wap con wap con wap Persisters gui ins gui ins gui ins ene hyp ene hyp ene hyp ret agi ret agi ret agi sui dep int sui dep int sui dep int con wap con wap con wap Remitters gui ins gui ins gui ins ene hyp ene hyp ene hyp ret agi ret agi ret agi original a data (P =.01) matched b on IDS (P =.04) matched on c WHODAS (P =.02)
26 More results 4 centrality measures strength closeness betweenness eigenvector centrality Focus on largest difference with bootstrapping of centrality measures effect size is based on the difference in means From Van Bork, Van Borkulo, Waldorp, Cramer & Borsboom. Network models for clinical psychology. (submitted)
27 sui dep int sui dep int con wap con wap More results gui ene hyp ins gui ene hyp ins ret agi ret agi 0.8 persisters remitters strength closeness agi con dep ene gui hyp ins int ret sui wap a symptoms agi con dep ene gui hyp ins int ret sui wap b symptoms betweenness eigenvector agi con dep ene gui hyp ins int ret sui wap c symptoms agi con dep ene gui hyp ins int ret sui wap d symptoms
28 Discussion Conclusion Patterns in symptom associations seem predictive for the course of MDD More pronounced associations between symptoms may be an important determinant of persistence in MDD Controlling for difference in baseline severity confirmed main results Limitations It is currently unclear what this means at the level of an individual patient Analysis at individual level can (theoretically) result in radically different network (Simpson s paradox) Future Investigate relationship between networks at group and individual level
29 Thanks to Denny Borsboom Lynn Boschloo Brenda Penninx Robert Schoevers Lourens Waldorp Van Borkulo, Boschloo, Borsboom, Penninx, Waldorp, Schoevers. Association of symptom network structure with the course of depression. JAMA Psychiatry. 2015;72(12):
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