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Enregistrement W4360600505 · doi:10.1111/bdi.13323

Contradictions, methodological flaws, and potential for misinterpretations in ranking treatments of depression

2023· article· en· W4360600505 sur OpenAlexaff
Nikolas Heim, Allan Abbass, Patrick Luyten, Sven Rabung, Christiane Steinert, Falk Leichsenring

Notice bibliographique

RevueBipolar Disorders · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth Policy Implementation Science
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésNiceExcellenceDepression (economics)PsychologyAmbiguityGuidelinePsychiatryEvidence-based medicineMedicineClinical psychologyPsychotherapistAlternative medicinePolitical scienceComputer science

Résumé

récupéré en direct d'OpenAlex

In this journal, Malhi et al. recently argue1 that the UK National Institute for Health and Care Excellence (NICE) guidelines for depression2 rank short-term psychodynamic therapy (STPP) as last of 11 therapies recommended for less severe depression and 7 out of 10 treatments recommended for more severe depression. They stress that STPP was ranked by NICE below counseling and that individual cognitive-behavior therapy (CBT) has the highest ranking.1 However, we argue that the NICE guidelines for depression are ambiguous in that they recommend multiple treatments as equal first-line treatments for depression on the one hand, but then go on to rank order them in terms of effectiveness and cost-effectiveness based on the NICE guideline's committee interpretation of the available evidence. We are concerned that this ambiguity leads to possible misinterpretations of the evidence as evidenced by Malhi and colleagues. Furthermore, we briefly summarize several methodological flaws in the NICE guidelines proposed ranking of treatments, which further questions the prioritization of one treatment over another in the treatment of depression. Indeed, in their main document, the NICE guidelines recommend several treatments as first-line treatments for less severe depression, emphasizing that patient preferences and other factors such as experiences with previous treatments are important in deciding the type of treatment that is offered to a given patient2, p. 13, 45: “…. take into account that all treatments in table 1 can be used as first-line treatments” (NICE, 2022, p. 28). Similarly, for more severe depression NICE clearly states that “all treatments in table 2 can be used as first-line treatments” (p. 45). As we will discuss below this is in line with the head-to-head comparisons conducted by NICE themselves as well as independent meta-analytic evidence. Yet, contradicting these recommendations, NICE2, p. 13, 45 also rank orders for these treatments based “on the committee's interpretation of their clinical and cost effectiveness and consideration of implementation factors”. This contradiction creates considerable ambiguity and allows for (mis-)interpretation of the NICE guidelines as prioritizing some treatments over others, as appears to be the case by Malhi et al.1 For example, for less severe depression, Malhi et al. state1, p. 468: “Notably, antidepressants are ranked below CBT, BA, and IPT but are recommended ahead of STPP.” For more severe depression, Malhi et al. concluded from the NICE treatment ranking1, p. 468: “This suggests that individuals with severe acute depression should be offered CBT, BA, antidepressant, individual problem-solving, and counseling prior to considering STPP…”. According to the NICE recommendations, however, treatment ranking is secondary to patient preferences and other factors when it comes to deciding which first-line treatment to provide.2, p. 13, 45 For example, NICE emphasizes2, p. 44–45: “Discuss treatment options with people who have a new episode of more severe depression, and match their choice of treatment to their clinical needs and preferences… use table 2 and the visual summary to guide and inform the conversation [and] take into account that all treatments in table 2 can be used as first-line treatments”. This is consistent with the fact that few statistically or clinically significant differences were found in head-to-head comparisons of the treatments listed by NICE as first-line as discussed below. In their reading of the NICE guidelines, Malhi and colleagues do not mention the emphasis in the NICE guidelines on patient preference and other factors and that NICE stresses that all the listed treatments can be offered as a first-line treatment. In summary, neither the indirect nor direct comparisons carried out by the NICE committee nor the cost-effectiveness analyses or independent research5 support Malhi et al.'s claim of superiority of counseling over STPP, prioritizing CBT over other treatments, and ranking STPP among the least effective treatments.1 In conclusion, we argue that the NICE guidelines for depression are ambiguous and even contradictory. This ambiguity may easily lead to misinterpretations as done by Malhi and colleagues resulting in a misrepresentation of the evidence for psychodynamic psychotherapy and other types of psychotherapy. Furthermore, we highlighted several methodological flaws in the NICE treatment ranking. Presently it is not clear which patients benefit from which empirically-supported treatment. Thus, we continue to discourage the devaluing of efficacious treatments so that as many patients as possible may benefit from them. The following authors have been trained in PDT: FL, AA, PL, and CS. SR has been trained in CBT but has mainly done research on psychodynamic therapy. NH is presently in training of PDT. PL received royalties from Guilford Press, Wiley, Routledge, and Cambridge University Press. AA received royalties from Seven Leaves Press. FL received royalties from Hogrefe Publisher. Data are available.

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.

Comment cette classification a été obtenuedéplier

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)0,002
score de la tête « metaresearch » (Gemma)0,002
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 enseignants0,266
Score d'incertitude au seuil0,343

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,485
Tête enseignante GPT0,641
Écart entre enseignants0,156 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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