Health-Related Quality of Life in European Childhood Cancer Survivors: Protocol for a Study Within PanCareLIFE
Notice bibliographique
Résumé
BACKGROUND: Survival after childhood cancer has improved to more than 80% during the last few years, leading to an increased number of childhood cancer survivors. Cancer itself, or its treatment, may cause chronic health conditions, including somatic and mental sequelae, which may affect survivors' health-related quality of life (HRQoL). OBJECTIVE: The project PanCareLIFE aims to establish a large database with comprehensive data on childhood cancer survivors from different European countries, including data on HRQoL. Within PanCareLIFE, this study aims to describe HRQoL in survivors, investigate predictors of HRQoL, and describe the association of HRQoL with hearing and female fertility impairment. This paper describes the design of the HRQoL study, the origin of data, strategies for data collection, and sampling characteristics of survivors from each contributing country. METHODS: A total of 6 institutions from 5 European countries (the Czech Republic, France, Germany, the Netherlands, and Switzerland) provided data on HRQoL assessed with the Short Form 36 and on relevant predictors. The central PanCareLIFE data center aggregated the data and harmonized the variables between the institutions. Survivors were eligible if they received a diagnosis of cancer according to the 12 main groups of the International Classification of Childhood Cancer, 3rd edition, or Langerhans cell histiocytosis; were aged ≤18 years at the time of diagnosis; were residents of the respective country at the time of diagnosis; had survived ≥5 years after cancer diagnosis; were aged ≥18 years at the time of the questionnaire survey; and did not refuse to registration in the national or local childhood cancer cohort. RESULTS: We identified 24,993 eligible survivors. Of those, 19,268 survivors received a questionnaire and 9871 survivors participated, resulting in response rates of 9871/24,993 (39.50%) of eligible survivors and of 9871/19,268 (51.23%) invited survivors. Most participants were diagnosed with cancer between the ages of 10 and 14 years (3448/9871, 34.93%) or <5 years (3201/9871, 32.43%). The median age was 8 years. Of the 9871 participants, 3157 (31.97%) were survivors of leukemia, 2075 (21.02%) lymphoma, and 1356 (13.7%) central nervous system (CNS) tumors. Most participants (9225/9871, 93.46%) had no history of a subsequent tumor; 77.45% (7645/9871) received chemotherapy with or without other treatments. More than half (5460/9871, 55.31%) were aged 25 to 34 years at the time of the HRQoL study. Participating survivors differed from nonparticipants; participants were more often women, survivors of leukemia or lymphoma, and less frequently, survivors of CNS tumors than nonparticipants. CONCLUSIONS: PanCareLIFE successfully assessed HRQoL and its predictors in 9871 European survivors of childhood cancer. This large population will permit detailed investigations of HRQoL after childhood cancer, particularly the impact of hearing and female fertility impairment on HRQoL. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/21851.
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 | 0,025 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,005 |
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 ».