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Hallucinations occur in many psychiatric disorders1. They are highly intrusive for patients, result in low quality of life, high caregiver burden and excess mortality2. Psychoeducation, improving coping skills and cognitive behavioural therapy are the first lines of treatment, but often additional biological treatment is needed 3-5. Biological treatments may be effective, but can also cause major side-effects. Currently, it is not possible to predict who will benefit and who will be harmed by these treatments and clinicians basically have to practice trial-and-error.

STAR-H introduces a new concept that matches treatment to individual neurobiological deviation. To accomplish this, we will identify biomarkers with novel combinations of neuroimaging techniques. For the first time, personalized treatment for hallucinations will become feasible by coupling these biomarkers to specific treatments.

With the use of transcranial magnetic stimulation (TMS), Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI), we will assess biomarkers in 120 patients who have disstressing and frequent hallucinations with four diagnoses (schizophrenia, borderline personality disorder, bipolar disorder, post-traumatic stress disorder) and compare them to matched controls. Patients receive targeted treatment based on individual Z scores (computed with the use of age-specific normal distributions).

Efficacy of treatment based on these biomarkers (personalized treatment arm)will be compared to treatment with the same interventions without information on biomarkers (control arm).

In the personalized treatment arm:

1. decreased cholinergic innervation is compensated with rivastigmine;

2. increased dopamine signaling is treated with amisulpride;

3. neuronal network instability (de-afferentation) is reversed with repetitive TMS.

In both arms, the choice for treatment will be made in a shared decision process between the patient, his/her partner/relatives and the treating physician, with the important difference that in the personalized treatment arm the treating physician will be provided with information about the patient's biomarker profile.

A panel of four people with lived-experience will assist the patients throughout the study and support them in the shared decision process.

To facilitate large-scale clinical implementation, we will also assess “psychomarkers” using deep phenotyping with a systematic questionnaire we recently developed together with the International Consortium for Hallucinations Research (ICHR): the Questionnaire for Psychotic Experiences (QPE). If accuracy of psychomarkers is satisfactory, they can replace biomarkers. If these psychomarkers are a valid alternative for neuro-imaging-derived biomarkers, personalized treatment of hallucinations can be provided in all treatment setting without the need for technical facilities or academic know-how.

Finally, a data-driven approach is applied to all bio- and psychomarkers to unveil new homogeneous clusters for optimal outcome prediction. This approach may provide new classification concepts for better treatment prediction.

In the STAR-H, different scientific elements are put into a chain to translate neuroscientific insight into personalized treatment for hallucinations in day-to-day practice. This is enabled by a unique consortium where all key elements (clinical trials in patient cohorts; deep phenotyping, TMS, MRI; PET; machine learning) can be performed. Our group has done most elements of this project before (assessing F-Dopa uptake18 performing transient-network analyses19 and treating hallucinations with rTMS6), which provides a firm basis for this project.

Novelty of STAR-H lies in its potential to radically change treatment of psychiatric symptoms from diagnosis-based to biomarker or psychomarker-based therapy. This approach is the missing link between academic knowledge and clinical practice and can improve outcome for many patients with hallucinations. Most importantly, it will prevent unnecessary and at times severe side-effect of somatic treatment.

 

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