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Enregistrement W3112171960 · doi:10.1080/15622975.2020.1851052

A clinical approach to treatment resistance in depressed patients: What to do when the usual treatments don’t work well enough?

2020· article· en· W3112171960 sur OpenAlex

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Notice bibliographique

RevueThe World Journal of Biological Psychiatry · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueTreatment of Major Depression
Établissements canadiensUniversity of British ColumbiaBrain and Cognition Discovery FoundationSt. Michael's HospitalUniversity of TorontoCentre for Addiction and Mental Health
Organismes subventionnairesNational Health and Medical Research Council
Mots-clésResistance (ecology)Work (physics)PsychologyPsychotherapistMedicineEngineering

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Major depressive disorder is a common, recurrent, disabling and costly disorder that is often severe and/or chronic, and for which non-remission on guideline concordant first-line antidepressant treatment is the norm. A sizeable percentage of patients diagnosed with MDD do not achieve full remission after receiving antidepressant treatment. How to understand or approach these 'refractory', 'TRD' or 'difficult to treat' patients need to be revisited. Treatment resistant depression (TRD) has been described elsewhere as failure to respond to adequate treatment by two different antidepressants. This definition is problematic as it suggests that TRD is a subtype of major depressive disorder (MDD), inferring a boundary between TRD and depression that is not treatment resistant. However, there is scant evidence to suggest that a discrete TRD entity exists as a distinct subtype of MDD, which itself is not a discrete or homogeneous entity. Similarly, the boundary between TRD and other forms of depression is predicated at least in part on regulatory and research requirements rather than biological evidence or clinical utility. AIM: This paper aims to investigate the notion of treatment failure in order to understand (i) what is TRD in the context of a broader formulation based on the understanding of depression, (ii) what factors make an individual patient difficult to treat, and (iii) what is the appropriate and individualised treatment strategy, predicated on an individual with refractory forms of depression? METHOD: Expert contributors to this paper were sought internationally by contacting representatives of key professional societies in the treatment of MDD - World Federation of Societies for Biological Psychiatry, Australasian Society for Bipolar and Depressive Disorders, International Society for Affective Disorders, Collegium Internationale Neuro-Psychopharmacologium and the Canadian Network for Mood and Anxiety Treatments. The manuscript was prepared through iterative editing. OUTCOMES: The concept of TRD as a discrete subtype of MDD, defined by failure to respond to pharmacotherapy, is not supported by evidence. Between 15 and 30% of depressive episodes fail to respond to adequate trials of 2 antidepressants, and 68% of individuals do not achieve remission from depression after a first-line course of antidepressant treatment. Failure to respond to antidepressant treatment, somatic therapies or psychotherapies may often reflect other factors including; biological resistance, diagnostic error, limitations of current therapies, psychosocial variables, a past history of exposure to childhood maltreatment or abuse, job satisfaction, personality disorders, co-morbid mental and physical disorders, substance use or non-adherence to treatment. Only a subset of patients not responding to antidepressant treatment can be explained through pharmacokinetic or pharmacodynamics mechanisms. We propose that non remitting MDD should be personalised, and propose a strategy of 'deconstructing depression'. By this approach, the clinician considers which factors contribute to making this individual both depressed and 'resistant' to previous therapeutic approaches. Clinical formulation is required to understand the nature of the depression. Many predictors of response are not biological, and reflect a confluence of biological, psychological, and sociocultural factors, which may influence the illness in a particular individual. After deconstructing depression at a personalised level, a personalised treatment plan can be constructed. The treatment plan needs to address the factors that have contributed to the individual's hard to treat depression. In addition, an individual with a history of illness may have a lot of accumulated life issues due to consequences of their illness, and these should be addressed in a recovery plan. LIMITATIONS: A 'deconstructing depression' qualitative rubric does not easily provide clear inclusion and exclusion criteria for researchers wanting to investigate TRD. CONCLUSIONS: MDD is a polymorphic disorder and many individuals who fail to respond to standard pharmacotherapy and are considered hard to treat. These patients are best served by personalised approaches that deconstruct the factors that have contributed to the patient's depression and implementing a treatment plan that adequately addresses these factors. The existence of TRD as a discrete and distinct subtype of MDD, defined by two treatment failures, is not supported by evidence.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,072
Score d'incertitude au seuil0,604

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,057
Tête enseignante GPT0,328
Écart entre enseignants0,270 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle