Abstract B60: Exposure assessment among an adult population on radiation therapy, chemotherapy, and other cancer therapies in childhood
Notice bibliographique
Résumé
Abstract Childhood cancer therapies are known risk factors for the development of second primary cancers. They are also suggested risk factors for late adverse health effects. Until now, there is no established questionnaire to retrospectively assess exposure to cancer therapies in childhood among adults. Therefore, we aim to validate a new self-administered questionnaire. The study population consists of 438 former childhood cancer patients of the KiKme study. Participants are asked whether they had received cancer therapies and how often and with which dose they were treated. Used medications and affected body regions are inquired. Questionnaire data are used to compute cytotoxic drugs dose of chemotherapy, taking patients’ weight and height into account, and to reconstruct individual organ doses. For validation, self-reports are compared to data of cancer therapies of 178 patients from hospitals and clinical studies. Quality assessment for binary variables are performed by measuring sensitivity and specificity. AUC and ROC curve are used for graphical comparison. The validity is analyzed by the positive (PPV) and negative predictive value (NPV). Cohen’s Kappa (κ) is used to measure the concordance between the two assessments. Continuous variables are tested for validity by the intraclass correlation coefficient. A Bland-Altman plot is used to consider the patterns of disagreement between the measurements. Influencing factors (e.g., number of neoplasms, sex, sociodemographic factors, comorbidities, time since cancer treatment) on the dichotomous outcome variable “degree of agreement” are analyzed using logistic regression. If the questionnaire is reliable, logistic regression and mixed models will be used to estimate possible risk associations with cancer therapies. A perfect agreement between questionnaire and therapy data was found on whether a chemotherapy was received (κ = 1.00). The agreement for exposure to radiotherapy was lower, but in the upper substantial area (κ = 0.77). For radiotherapy, sensitivity (94%) and PPV (96%) of the questionnaire were at a very high level. Specificity (85%) and NPV (80%) were less precise. The agreement for exposure to radiotherapy was higher in participants with one cancer (κ = 0.82) compared to participants with more than one diagnosis (κ = 0.62). The odds ratios for agreement were 0.5 (0.1; 1.8) for participants with two vs. one diagnosis, 1.3 (0.3; 4.9) for men vs. women, 10.9 (1.7; 71.9) for age over 36.4 years (median) vs. younger participants, 2.2 (0.6; 9.0) for high vs. low education, 0.3 (0.1; 1.4) for over 26.5 years of follow-up (median) vs. less, 2.4 (0.6; 9.5) for existing vs. nonexisting comorbidities. In conclusion, the new developed questionnaire seems to be reliable for the retrospective assessment of binary exposure to cancer therapies in childhood, especially for chemotherapy. However, for radiotherapy older participants showed a significant higher agreement. All other tested variables showed no significant influence. Citation Format: Lara Kim Brackmann, Caine Lucas Grandt, Heike Schwarz, Irene Schmidtmann, Thomas Hankeln, Danuta Galetzka, Sebastian Zahnreich, Peter Scholz-Kreisel, Maria Blettner, Heinz Schmidberger, Manuela Marron. Exposure assessment among an adult population on radiation therapy, chemotherapy, and other cancer therapies in childhood [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B60.
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 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».