RESUMO
Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.
RESUMO
Micro-phenomenology is a method for improving first-person reports of experience. Usually, micro-phenomenology is conducted using a second-person interviewer who guides someone investigating an experience. This has the advantage that the interviews can be done with untrained subjects. However, it is possible to perform micro-phenomenological self-inquiry, a form of self-interview technique, without a second-person interviewer. This has several advantages, such as being more time and cost effective. Questionable, however, is the possibility for untrained subjects to enquire into their own experience using micro-phenomenology. The present study aims to test the reliability of micro-phenomenological self-inquiry with untrained subjects using a guiding document. We replicated an experimental design that has previously been employed to test whether micro-phenomenology increases the reliability of reports. The experiment did not replicate. Reasons for this may be: (1) a methodological weakness of the previous study; (2) that the way the self-inquiry format employed as part of the present study was ineffective; or (3) that micro-phenomenological self-inquiry requires training. These specific possibilities and the idea of testing the reliability of micro-phenomenological reports in general are discussed. We conclude that the self-inquiry format is not sufficient for conducing micro-phenomenological studies and that training is required.
