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Enregistrement W759028320 · doi:10.1177/070674371506000102

Problems from the Past and Prevention for the Future

2015· editorial· en· W759028320 sur OpenAlexaffvenueabout
Scott B. Patten

Notice bibliographique

RevueThe Canadian Journal of Psychiatry · 2015
Typeeditorial
Langueen
DomaineMedicine
ThématiqueTreatment of Major Depression
Établissements canadiensHotchkiss Brain InstituteUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésConfoundingCLARITYAssertionPsychologyMatching (statistics)ScrutinyEpistemologyMedicineComputer scienceLawPolitical sciencePhilosophy

Résumé

récupéré en direct d'OpenAlex

This issue of The Canadian Journal of Psychiatry (The CJP) includes a Perspective article written by Dr H Edmund Pigott.1 Dr Pigott articulates a series of criticisms of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Some of these arguments attack the trial methodology and reporting, whereas others take issue with the broader concept of measurement-based care. There is a reason for the ascendancy of RCTs. The process of randomization helps to ensure that potential confounding variables are equally distributed between treatment groups. Unique among procedures for controlling confounding (for example, matching and statistical modelling), randomization controls for unmeasured, and even unknown, confounders. As such, it is a uniquely powerful study design. The CJP’s Perspectives format is intended to be open to expressions of opinion. Authors of Perspectives articles are encouraged to take positions on controversial topics,2,3 as Dr Pigott has done. In an accompanying Guest Editorial,4 Dr Raymond W Lam and Dr Sidney H Kennedy take issue with 3 of the arguments put forward by Dr Pigott: the assertion that a primary objective of the STAR*D trial was modified post hoc; the idea that remission is not a suitable outcome measure in depression research; and the idea that the STAR*D story provides a general indictment of the principles of measurement-based care. Questions surrounding modification of a priori hypotheses in clinical trials are not trivial. Statistical analyses are vulnerable to error if there is a lack of clarity surrounding their primary outcomes. Problems also arise when primary outcomes are not clearly distinguished from secondary and exploratory ones. In the worst-case scenario, data are analyzed and investigators then selectively report the findings that they prefer. This is the proverbial fishing expedition seen in undisciplined research. In this disastrous scenario, readers cannot correctly interpret reported P levels or confidence intervals as these no longer reflect their intended probabilities. Instead, they partially reflect decisions made by the authors. This does not mean that investigators should be denied full rein to explore their data. However, if exploratory analyses are to be conducted, they must be carefully identified as such. Results from exploratory analyses are provisional. They require additional replication to ensure that the results were not merely statistical outliers. In their Guest Editorial, Lam and Kennedy4 argue that Pigott has misunderstood some aspects of the STAR*D protocol. They feel that outcomes in question, those for the Quick Inventory of Depression Symptoms—Self-Report remission, were adequately characterized as post hoc analyses, whereas Pigott feels that these were obscured. This issue is one of transparency of reporting. Progress is being made in addressing such problems. For example, The CJP requires that clinical trials be registered in a suitable archive at or before the onset of subject enrolment. A suitable registry must be accessible to the public at no charge; be open to all prospective registrants; be managed by a not-for-profit organization; have a mechanism to ensure the validity of the registration data; and be electronically searchable. Registration protects the integrity of trials, both from methodological manipulation and from accusations of such manipulation. However, registration, in itself, is not always enough. After all, the STAR*D trial protocol was registered,5 but this did not prevent concerns and controversies from arising. Some journals (for example, The Journal of the American Medical Association) now require clinical trial protocols, including the complete statistical analysis plan, be submitted along with submissions of clinical trial reports. Increasingly, investigators are choosing to archive their complete RCT protocols, including their detailed a priori analysis plans. In contrast, Dr Pigott reports that he needed a Freedom of Information Act request to obtain the STAR*D protocol. In the systematic review literature, it is a long-standing practice to publish or archive review protocols prior to the reviews being conducted. The CJP’s recently initiated Systematic Reviews category strongly encourages authors to register their review protocols in a suitable registry (for example, PROSPERO) or to archive or publish their full protocols.3 While most major journals, this one included, require registration for trials, they usually do not require it for other types of studies. Ultimately, it would be a good idea for authors of all studies that use statistical analysis, such as epidemiologic studies or brain imaging studies, to register their protocols in a similar fashion. This would assist readers in their interpretation of the statistics reported in the ensuing papers. It would also protect them from later accusations that they have modified their analysis after the fact. While they disagree on many points, the authors of these papers1,4 agree that the STAR*D results were disappointing. Other papers in this issue of The CJP amplify this sense of urgency for greater progress against depression. Sakina J Rizvi and collaborators6 report unemployment–disability rates of 30.3% of a sample of depressed primary care patients and of 41.4% in a tertiary care sample. An updated description of the general population’s prevalence of major depressive disorder documents continuing high prevalence,7 associated dysfunction, comorbidity, and stigmatization.8 Better publication and reporting standards will help us to keep our sights on the true enemy: depression itself.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,036
score de la tête « metaresearch » (Gemma)0,076
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,036
Score d'incertitude au seuil0,191

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0360,076
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0130,028
Communication savante0,0220,035
Science ouverte0,0040,013
Intégrité de la recherche0,0280,057
Charge utile insuffisante (le modèle a refusé de juger)0,0290,010

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 Opus0,014
Tête enseignante GPT0,269
Écart entre enseignants0,256 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

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

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

En bref

Citations4
Publié2015
Routes d'admission3
Résumé présentoui

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Même revueThe Canadian Journal of PsychiatryMême sujetTreatment of Major DepressionTravaux en français237 207