期刊
NEUROPSYCHOPHARMACOLOGY
卷 46, 期 6, 页码 1122-1132出版社
SPRINGERNATURE
DOI: 10.1038/s41386-020-00866-7
关键词
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资金
- Medical Research Council-UK [MC-A656-5QD30]
- Maudsley Charity [666]
- Brain and Behaviour Research Foundation
- Wellcome Trust [094849/Z/10/Z]
- National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust
- King's College London
- National Institute for Health Research Biomedical Research Centre at South London and Maudsley National Health Service Foundation Trust
- Wellcome Trust Digital Award [215747/Z/19/Z]
- JMAS SIM Fellowship from the Royal College of Physicians, Edinburgh
- Angellini
- AstraZeneca
- Autifony
- Biogen
- Boehringer-Ingelheim
- Eli Lilly
- Heptares
- Invicro
- Jansenn
- Lundbeck
- Lyden-Delta
- Mylan
- Neurocrine
- Otsuka
- Sunovion
- Rand
- Recordati
- Roche
- Wellcome Trust [215747/Z/19/Z] Funding Source: Wellcome Trust
The study evaluated the potential of [F-18]FDOPA PET imaging to identify non-responders to antipsychotic treatment using linear and non-linear machine learning analyses and found good test-retest reproducibility and predictive power in distinguishing responders from non-responders. The economic analysis indicated potential healthcare cost savings by using [F-18]FDOPA PET to fast-track treatment-resistant patients to clozapine. Overall, the findings suggest that [F-18]FDOPA PET dopamine imaging has the potential to serve as a biomarker to guide treatment choice for patients with schizophrenia.
[F-18]FDOPA PET imaging has shown dopaminergic function indexed asK(i)(cer)differs between antipsychotic treatment responders and non-responders. However, the theragnostic potential of this biomarker to identify non-responders has yet to be evaluated. In view of this, we aimed to evaluate this as a theragnostic test using linear and non-linear machine-learning (i.e., Bernoulli, support vector, random forest and Gaussian processes) analyses and to develop and evaluate a simplified approach, standardised uptake value ratio (SUVRc). Both [F-18]FDOPA PET approaches had good test-rest reproducibility across striatal regions (K-i(cer) ICC: 0.68-0.94, SUVRc ICC: 0.76-0.91). Both our linear and non-linear classification models showed good predictive power to distinguish responders from non-responders (receiver operating curve area under the curve for region-of-interest approach:K-i(cer) = 0.80, SUVRc = 0.79; for voxel-wise approach using a linear support vector machine: 0.88) and similar sensitivity for identifying treatment non-responders with 100% specificity (K-i(cer): similar to 50%, SUVRc: 40-60%). Although the findings were replicated in two independent datasets, given the total sample size (n = 84) and single setting, they warrant testing in other samples and settings. Preliminary economic analysis of [F-18]FDOPA PET to fast-track treatment-resistant patients with schizophrenia to clozapine indicated a potential healthcare cost saving of similar to 3400 pound (equivalent to $4232 USD) per patient. These findings indicate [F-18]FDOPA PET dopamine imaging has potential as biomarker to guide treatment choice.
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