CE-22 Cancer in systemic lupus erythematosus: results from the slicc inception cohort
Notice bibliographique
Résumé
Background To describe cancer incidence in the largest inception SLE cohort in the world. Materials and methods Patients meeting ACR criteria for new-onset SLE were enrolled across 32 centres. At enrolment and annual assessments, new cancer diagnoses (in the intervening year) were recorded by the examining physician. Confirmation of cancers was done by reviewing medical files including pathology reports. Of 1848 patients enrolled (across 1999–2011), 1676 had at least one follow-up. Patients were followed until death, last visit, or end of study interval for this analysis (August 2015). Results Of 1676 patients followed, the majority (88.7%) were female and 828 (49.4%) were Caucasian (16.5% black, 15.2% Asian, 15.2% Hispanic, 3.7% other). Average age at SLE diagnosis was 34.6 (standard deviation, SD 13.3) years. At baseline, 1085 (64.7%) patients were never-smokers; the remainder were current (n = 248) or ex-smokers (n = 342). Average follow-up from cohort entry was 6.9 (SD 3.6) years. Two patients had cancer (one squamous cell skin and one breast cancer) prior to their SLE diagnosis; these cancers were not included in our analyses. We observed 46 cancers in 46 subjects (with three other subjects reported to have cervical intraepithelial neoplasia, a premalignant condition). At cancer diagnosis, the average age was 51.7 (SD 15.3) years and the average SLE duration was 4.8 (SD 3.1) years. The most common cancer type was breast (n = 9), followed by non-melanoma skin cancer (n = 8, six of which were basal cell), lung (n = 6), prostate (n = 5), four head and neck (tonsillar, tongue, and two oral), cervical (n = 2), thyroid (n = 2), melanoma (n = 2) and one each of Non-Hodgkin lymphoma, leukaemia, multiple myeloma, meduloblastoma brain cancer, renal carcinoma, gastric carcinoid, thymoma, and cutaneous dermatofibrosarcoma. Most of the cancer cases were female (34 cases, 73.9%) and Caucasian (34 cases, 73.9%). Four cancer cases were Hispanic, 4 were black, and 4 were Asian. Twenty of the 46 patients (43.5%) who developed cancers were current (n = 4) or ex-smokers (n = 16); five of the six lung cancers were current (n = 1) or ex-smokers (n = 4). Conclusions Just under 3% of the incident SLE cohort developed a cancer over an average follow-up of 6.9 years. The most common cancers were breast, non-melanoma skin, and lung cancers. The vast majority of lung cancers were smokers, supporting the belief that lung cancer risk in SLE (as in the general population) is largely driven by smoking. Further analyses will determine the standardised incidence rates for these cancers in SLE, versus the general population. Acknowledgements We thank all SLICC investigators and their patients for their invaluable data and dedication to SLE research
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».