Is prevention of systemic lupus erythematosus a goal?
Notice bibliographique
Résumé
Prevention of systemic lupus erythematosus (SLE) presents many challenges. By contrast, prevention of acquired immunodeficiency syndrome (AIDS) is relatively straightforward: an infective agent has been identified, risk behaviors are well-delineated, antiviral therapeutics are highly effective and neonates have been apparently cured. Lupus is a more complex disease, with a significant but incompletely defined genetic component, widely heterogeneous manifestations and major gaps in knowledge about pathogenesis. The characteristic features of SLE can be exploited in the quest for preventive strategies. One of these is the presence of a latent phase during which expressed autoantibodies are increasing in number and complexity prior to the onset of clinical symptoms. This offers a path to the development of screening blood tests that would be cost-effective and generally acceptable to subjects. ANA alone is clearly not sufficient to establish risk, as it is highly prevalent in the healthy population. Alternatively, a panel of autoantibodies, possibly combined with cytokines and gene expression levels, might be useful. The skewed demographics of SLE can also be exploited, including the higher prevalence in females, first-degree relatives and individuals < 40 years old, permitting focus on those who are most likely to be at risk. A composite index, with demographics and multiplex blood autoantibody profiles, has been proposed. This index showed statistically significant correlation with progression of disease in a small prospective cohort ( P = 1 × 10 ). As the science improves, the risk definition could be augmented with targeted genetic information, as is now available for several inherited cancers; even the simple inclusion of family history as a proxy for genetic input might be of value. All such screening efforts would be for naught in the absence of an available intervention. Fortunately, several candidate treatments are available for the incomplete lupus phenotypes, and precedent for using therapeutics in individuals who are not yet ill has been established in other conditions, notably type I diabetes mellitus. It is timely to propose a prevention trial in individuals at high risk for development of SLE. A placebo arm would probably be required in such a study to show that the enrollment criteria successfully identified high-risk individuals. Challenges to trial design include acceptance of "no treatment" by persons profiled as high risk and the relatively long timeline likely to be required to achieve observable clinical change. However, despite these issues, available tools and therapeutics make prevention trials in SLE a feasible, near-term prospect.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,010 | 0,023 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,005 |
| Communication savante | 0,005 | 0,007 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,009 | 0,017 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,007 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».