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Enregistrement W4255067536 · doi:10.1097/qad.0b013e3283299622

Evaluation of the WHO criteria for antiretroviral treatment failure among adults in South Africa: authors' reply

2009· article· en· W4255067536 sur OpenAlexaboutno aff
Paul Mee, Katherine Fielding, Salome Charalambous, Gavin Churchyard, Alison D. Grant

Notice bibliographique

RevueAIDS · 2009
Typearticle
Langueen
DomaineMedicine
ThématiqueHIV/AIDS Research and Interventions
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineDilemmaAntiretroviral therapySecond lineAntiretroviral treatmentHuman immunodeficiency virus (HIV)Family medicinePediatricsFirst lineViral loadInternal medicine

Résumé

récupéré en direct d'OpenAlex

We thank Schuelter-Trevisol et al. [1] for their interest in our paper [2]. Our aim was specifically to assess the performance of clinical and CD4 cell count criteria for antiretroviral treatment (ART) failure as defined in the WHO guidelines, which is important given that the criteria were developed based on expert opinion rather than evidence. Schuelter-Trevisol et al.[1] question our conclusions, based on concerns about exclusions from the analysis. Individuals excluded from this analysis fall into two main groups: first, those who were lost to follow up by 12 months and, second, those excluded because of missing laboratory data. The majority of those lost to follow up will no longer be on ART and are very likely to fulfil virological criteria for treatment failure. Our analysis was based on the scenario of a clinician assessing a patient attending 12 months after starting first-line ART and having to decide whether to continue first-line treatment or switch to second line. Individuals who are lost to follow up before 12 months are a very important group (which we are addressing in separate study), but the clinical dilemma of whether to switch to second-line therapy at the 12-month visit does not arise, which is why we think it is preferable to exclude them from this analysis. The second group excluded were, necessarily, 97 individuals with missing laboratory data at 12 months. We have compared these 97 excluded individuals with the 324 included in the study with respect to baseline factors found, in a previously published analysis, to be associated in this population with virological outcome at 12 months [3]. Comparing those excluded to those included; median age was 40.2 years in each group (P = 0.91), median weight was 65 kg in each group (P = 0.96), median CD4 cell count was 164 versus 154 cells/μl (P = 0.41) and viral load was 43 766 versus 47 503 copies/ml (P = 0.41) (P-values calculated using the Wilcoxon rank sum test in each case). Thus, those excluded from the study due to missing data were very similar to those included, and these exclusions are unlikely to have affected the reported prevalence of virological failure. The prevalence of virological failure among those retained in care in our study is similar to that quoted in other routine programmes and is rather higher than reported from many early programmes from resource-constrained settings [4]. Thus, the positive predictive value for the WHO criteria would be expected to be even lower in these settings with better outcomes, making our recommendations all the more relevant. We would expect the prevalence of virologically defined treatment failure to be higher at later time points. We plan to investigate this when we have additional data from individuals with longer duration of follow up. Our results are consistent with data from the recent studies in Canada [5], Botswana [6] and Thailand [7] cited in our paper [2] and a study in Malawi [8]. On the basis of this accumulating evidence, we stand by our recommendation that individuals fulfilling clinical or CD4 cell count criteria for treatment failure should have HIV viral load measured before switching to second-line therapy. Our recommendations are consistent with a proposal by Colebunders et al. [9] with respect to a model using clinical and simple laboratory evidence along with HIV viral load in selected cases to make decisions on switching to second-line treatment in resource-limited settings. The question of whether sex is associated with ART adherence was addressed in a literature review carried out by Ammassari et al. [10]. No association between sex and adherence was found in 10 out of 11 studies in which the question was addressed. In addition, the studies cited above [5–8] from cohorts, including a higher proportion of women, reached conclusions similar to ours.

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)0,001
score de la tête « metaresearch » (Gemma)0,001
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: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,605
Score d'incertitude au seuil0,208

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 Opus0,048
Tête enseignante GPT0,366
Écart entre enseignants0,319 · 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

Citations0
Publié2009
Routes d'admission1
Résumé présentoui

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