Chronic Kidney Disease or Hypertension After Childhood Cancer
Notice bibliographique
Résumé
Importance: Post-cancer therapy kidney outcomes, including chronic kidney disease (CKD) and hypertension, are common in childhood cancer survivors (CCS). The incidence and timing of CKD and hypertension in CCS compared with other at-risk or general populations are unclear. Objective: To determine the association of childhood cancer treatment with post-cancer therapy CKD or hypertension. Design, Setting, and Participants: Population-based matched cohort study of children treated for cancer between April 1993 and March 2020 in Ontario, Canada, with follow-up until March 2021. The CCS (exposed) cohort included children (≤18 years) surviving cancer. Comparator cohorts were a hospitalization cohort (children who were hospitalized) and a general pediatric population (GP) cohort (all other Ontario children). Exclusion criteria were history of previous cancer, organ transplant, CKD, dialysis, or hypertension. Matching with each of the 2 comparator cohorts was performed separately and in a 1:4 ratio by age, sex, rural vs urban status, income quintile, index year, and presence of previous hospitalization. Data were analyzed from March 2021 to August 2024. Exposure: Treatment for cancer. Main Outcomes and Measures: The primary outcome was the composite of CKD or hypertension, defined by administrative health care diagnosis and procedure codes. Fine and Gray subdistribution hazard modeling, accounting for competing risks (death and new cancer diagnosis or relapse) and adjusting for cardiac disease, liver disease, and diabetes, was used to determine the association of cancer treatment with outcomes. Results: There were 10 182 CCS (median [IQR] age at diagnosis, 7 [3-13] years; 5529 male [54.3%]; median [IQR] follow-up time, 8 [2-15] years) matched to 40 728 hospitalization cohort patients (median [IQR] age at diagnosis, 7 [2-12] years; 5529 male [weighted percentage, 54.3%]; median [IQR] follow-up time, 11 [6-18] years) and 8849 CCS (median [IQR] age at diagnosis, 5 [2-11] years; 4825 male [54.5%]; median [IQR] follow-up time, 7 [2-14] years) matched to 35 307 GP cohort individuals (median [IQR] age at diagnosis, 6 [2-11] years; 4825 male [weighted percentage, 54.5%]; median [IQR] follow-up time, 10 [5-16] years). Most frequent cancer types were leukemia (2948 patients [29.0%]), central nervous system neoplasms (2123 patients [20.9%]), and lymphoma (1583 patients [15.5%]). During observation, cumulative incidence of CKD or hypertension was 20.85% (95% CI, 18.75%-23.02%) in the CCS cohort vs 16.47% (95% CI, 15.21%-17.77%) in the hospitalization cohort and 19.24% (95% CI, 15.99%-22.73%) in the CCS cohort vs 8.05% (95% CI, 6.76%-9.49%) in the GP cohort. CCS were at increased risk of CKD or hypertension compared with the hospitalization cohort (adjusted hazard ratio, 2.00; 95% CI, 1.86-2.14; P < .001) and the GP cohort (adjusted hazard ratio, 4.71; 95% CI, 4.27-5.19; P < .001). Conclusions and Relevance: In this population-based study, CCS were at increased risk for CKD and hypertension, which are associated with mortality, suggesting that early detection and treatment of these conditions in CCS may decrease late complications and mortality.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 ».