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Enregistrement W1543377754 · doi:10.1111/j.1532-5415.2004.52125_2.x

The Role of Positron Emission Tomography in the Diagnosis of Alzheimer's Disease

2004· letter· en· W1543377754 sur OpenAlexaboutno aff
Jeffrey L. Cummings, D.H.S. Silverman, Gary W. Small, Michael E. Phelps

Notice bibliographique

RevueJournal of the American Geriatrics Society · 2004
Typeletter
Langueen
DomaineMedicine
ThématiqueDementia and Cognitive Impairment Research
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute on Aging
Mots-clésMedicineDementiaPositron emission tomographyMedical diagnosisAppropriate Use CriteriaMEDLINECost–benefit analysisMedical physicsDiseaseIntensive care medicineNuclear medicineRadiologyPathology

Résumé

récupéré en direct d'OpenAlex

To the Editor: We would like to address several issues raised by a recent article by Gill et al.1 purporting to review the evidence-based literature regarding the potential value of positron emission tomography (PET) in the diagnosis of dementia. It concludes that there is little evidence to support the integration of PET in the clinical evaluation of patients with suspected or established dementia. Several features of this article and the data reviewed challenge this conclusion. First, the article presents itself as a cost-benefit analysis of PET in the diagnosis of Alzheimer's disease (AD), but no cost-benefit or economic analysis was performed beyond stating the cost of these scans in Ontario, Canada. Such analyses have been conducted using established cost-benefit methods based on imaging and other costs and accounting for such advantages as early introduction of therapy, deferral of nursing home placement, and reduction in use of unnecessary testing. A formally conducted cost-benefit analysis demonstrated that PET is, under the most conservative analysis, at least cost neutral and, under more-realistic conditions, cost advantageous when added to the dementia evaluation.2 Second, the authors stated that they conducted a systematic review of the peer-reviewed literature from Medline from 1975 to 2001, but they did not identify the largest single-institutional study examining the relationship between PET-based and autopsy-based diagnoses, published in 2000.3 In addition, they excluded from their main analysis the largest multicenter study to examine this relationship,4 although its publication fell within the specified time, and they note that this latter article had several advantages over the articles examined. This article demonstrated 94% sensitivity and 73% specificity for PET in the diagnosis of AD, comparable with or better than most clinical diagnostic studies. Third, the authors do not provide criteria for deciding how PET was judged to be beneficial. They conducted no critical assessment or comparisons of sensitivity, specificity, or accuracy measures for clinical diagnoses or PET-based diagnoses. Moreover, they included only papers in their main analysis that had as their primary criterion standard the clinical diagnosis of AD, excluding those papers that used the more definitive standard of autopsy-confirmed diagnosis.3,4 There was consequently no way their analysis could demonstrate any incremental value of PET over clinical diagnosis by the way they constructed and performed their evaluation. Fourth, the authors repeatedly assert that clinical diagnosis of probable AD is straightforward and accurate in up to 90% of cases, thereby seeming to obviate a priori the need for neuroimaging. They identify only one study in support of this claim,5 a paper that the American Academy of Neurology (AAN) recently identified as having Class II quality of evidence. The paper showed that, to achieve a sensitivity of 90% (as occurs with PET), clinical specificity fell to below 40%. Three papers that the AAN rated as having Class I quality of evidence demonstrated a mean accuracy rate of clinical diagnosis of less than 70%. Fifth, Table 3 of the Gill et al.1 article lists the 16 articles or publications included in their review. Of these 16, five were published before the advent of any Food and Drug Administration–approved therapy for AD, and five more were published in 1993 and 1994, when tacrine, a little-used compound, was the only available treatment. Thus, 10 of the 16 articles precede the contemporary era of pharmacotherapeutics in the management of AD. This is important because an early and accurate diagnosis becomes more urgent once therapy is widely available. Sixth, the two Class A or B articles identified by the authors and published in 1996 (the only ones in the current era of neurotherapeutics for AD) were supportive of the use of PET. One study6 found high inter- and intraobserver agreement in PET interpretation of patients with probable AD, possible AD, mild cognitive impairment, and normal controls. Another study7 found that three-dimensional stereotactic surface projections improved sensitivity and specificity. Thus, the two articles published more recently and using more-modern PET scanners support the use of PET in the diagnosis of AD. Seventh, factual errors are present in this article. On four occasions in the article, the authors state that patients diagnosed with probable AD have advanced disease when the diagnosis is easiest and therefore PET adds little to resolve diagnostic challenges. It is untrue that probable AD is necessarily advanced. Probable AD8 refers to patients who meet research criteria for AD. These criteria can be applied as soon as the patient has impairment in memory and in at least one other cognitive domain causing disability. Patients may have Clinical Dementia Rating scale scores as low as 0.5 and still meet criteria for probable AD. Diagnosis of patients at this stage of dementia is a challenge because all dementias necessarily go through mild stages of severity before reaching more-severe and more diagnostically definitive stages. A large multicenter study4 showed the accuracy of PET to be the same at mild and moderate stages of AD. Eighth, the principal challenge in the recognition, diagnosis, and treatment of AD is the lack of recognition of patients by primary care practitioners who are most likely to encounter them in early stages of the disease. Practice reviews show that 97% of patients with early dementia go undiagnosed and as many as 50% of patients with moderate to severe dementia receive no diagnosis.9 Thus, the relatively similar sensitivity and specificities reported by some academic medical centers resulting from the rigorous application of research diagnostic criteria and those of PET are irrelevant to most routine clinical practices. Primary care practitioners fail to address the important issue of cognitive decline in their patients in part because of the absence of an available diagnostic test with which to confirm their opinion. PET should not replace a thorough clinical assessment but can add important and accurate positive evidence to the diagnosis based on traditional evaluations. In summary, the absence of a cost-benefit analysis, the lack of definitions for PET utility, the truncated literature review, the emphasis on out-of-date information, the factual misstatements, and the ignoring of the potential benefit of PET to those who are most likely to benefit from its availability undermine the conclusions of this article. The available literature supports the use of PET in the assessment of dementia, and we recommend that PET be integrated into the diagnostic approach to dementia.10

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)0,014
score de la tête « metaresearch » (Gemma)0,098
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: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,076

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0140,098
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0010,003
Communication savante0,0040,005
Science ouverte0,0060,001
Intégrité de la recherche0,0150,017
Charge utile insuffisante (le modèle a refusé de juger)0,0040,002

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 Opus0,010
Tête enseignante GPT0,286
Écart entre enseignants0,276 · 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
GenreCommentaire

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

En bref

Citations7
Publié2004
Routes d'admission1
Résumé présentoui

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