2. Disclosure belangen NHG spreker
(Potentiële) belangenverstrengeling
Geen
Voor bijeenkomst mogelijk relevante relaties met bedrijven
Sponsoring of onderzoeksgeld
SBOH
Stichting Stoffels Hornstra

3. Predicting the 2-year course of persistent MUPS
Nikki Claassen – van Dessel, MD PhD
Dept of General Practice and Elderly Care Medicine
VU University Medical Centre
Amsterdam

4. MUPS? MUPS are very common
MUPS are physical symptoms which persist for at least several weeks and for which no adequate explanation can be found after proper medical examination by a MD
MUPS are very common
25-50% of symptoms presented to GP remain unexplained

5. Course of MUPS 50%↑, 10-30%↓ Persistent MUPS are associated with:
Unnecessary diagnostic interventions and medication
Great risk of functional impairment and psychological distress
Doubling of medical care utilization
Long term absence of work

6. Predicting MUPS Known predictors of the course of MUPS:
Higher number of symptoms at baseline
Longer duration of symptoms at baseline
Female sex
Medical characteristics?
Psychological aspects?
Cognitive aspects?
Behavioural aspects?

7. Study objective
To develop a prediction model for the course of MUPS in terms of symptom severity and physical/mental functioning

8. Methods Longitudinal prospective cohort study
Multiple settings (primary care / specialized MUPS care)
325 MUPS patients, age: years
2 year follow-up (4 follow-up moments)

9. Measures Outcomes: Potential predictors:
Number and severity of symptoms (PHQ-15)
Nunctional impairment (SF-36)
Potential predictors:
Patient characteritics
Symptom characteristics
Biological factors
Psychological factors
Behavioural factors
Social factors
Personality

10. Statistics Linear Mixed Models for all outcomes
Backwards stepwise selection
No imputation
Explained variances
Sensitivity analyses (for health care setting)
Bootstrapping procedures
We performed linear mixed model analyses using a backwards-stepwise procedure to predict symptom severity (PHQ-15 score), physical functioning (RAND 36 PCS score) and mental functioning (RAND 36 MCS score) over time. Within mixed model analysis an adjustment is made for the correlation between repeated observations within the subject, by modeling the variability among the subjects [50,51]. Predictors with a p≤0.05 in the multivariate analyses remained in the final models [48,52].
The quality of the final models was derived from the explained variance (R²). We decided not to use imputation techniques to handle missing data in outcomes or predictors, as altogether percentages of missing data were low.

11. Results – baseline data
Text
Total group
(N=325)
Mean (SD)
N (%)
Age (range 19-70)
46.53 (12.3)
Female gender
244 (75.1%)
Nationality
Dutch
279 (85.8%)
Other
46 (14.2%)
Number of somatic comorbidities
1.71 (1.60)
Depressive symptoms (QIDS-SR, scale 0-27)
9.31 (4.9)
Anxiety (BAI, scale 0-63)
12.45 (9.6)
Symptom severity (PHQ-15, scale 0-30)
12.28 (5.3)
Physical functioning (RAND 36 PCS, scale 0-100)
47.84 (19.8)
Mental functioning (RAND 36 MCS, scale 0-100)
46.25 (17.8)
Belangrijkste klacht
47% Bewegingsapparaat
17% Vermoeidheid
15% Neurologisch
12% Maag-darmstelsel

12. Results - identified predictors
Unfavourable predictors
Favourable predictors
Physical comorbidities
Limited alcohol use
Severe symptoms at baseline
Higher education
Anxiety
Better physical/mental function at baseline
Catastrophising
Extraversion
Embarrassment
Symptom focusing*
Avoidance cognitions
Damage cognitions*
Avoidance behaviours
Neuroticism

13. Quality of the models
Explained interpersonal variance for all three models varied between 70.5 and 76.0%
Performance of the models was comparable in primary and secondary/tertiary care

14. Conclusion
The prediction models identified several relevant demographic, medical, psychological and behavioural predictors
They can potentially be used in future classification systems
External validation is needed prior to clinical implementation

15. Research team Nikki Claassen – van Dessel n.vandessel@vumc.nl
Hans van der Wouden, PhD
Jos Twisk, professor
Joost Dekker, professor
Henriette van der Horst, professor