Merging of Children's Oncology Group and Pediatric Health Information Systems Data to Determine Resource Utilization and Treatment Costs on AAML0531: A Report From the Children's Oncology Group
Notice bibliographique
Résumé
Abstract Abstract 2617 Background: National Cancer Institute (NCI)-funded cooperative oncology group trials have improved overall survival for children with cancer from 10% to 85%, and have set standards of care for adults with malignancies. However, the lack of data on resource utilization and treatment costs of patients on cooperative group trials is a critical limitation particularly in the present economic climate. To address this important knowledge gap, we merged data from the Children's Oncology Group (COG) AAML0531 Phase III trial for de novo acute myeloid leukemia (AML) and the Pediatric Health Information Systems (PHIS) data base to determine resource utilization and inpatient treatment costs for the overall trial and by treatment arm. Methods: 1022 eligible patients without trisomy-21 enrolled on AAML0531 were randomized to standard chemotherapy plus gemtuzumab (GMTZ) or standard chemotherapy (no GMTZ). Patients enrolled at 43 free standing pediatric hospitals in PHIS had COG and PHIS data merged by a probabilistic algorithm using center, ICD9 code for AML (205.xx), and date of birth. Once merged, resource utilization and cost data were analyzed for the first Induction chemotherapy course based on PHIS data. Cost data were estimated using standardized costs determined from a validated master costing index. Results: Of 416 patients enrolled on the Phase III COG trial at PHIS centers, 392 (94%) were successfully matched. Of the 392 matched patients, 378 (96%) had inpatient PHIS data available beginning at date of study enrollment and 259 (66%) had cost data available. Patients with and without available data did not differ in demographic characteristics. Daily blood product usage is illustrated in Figure 1. Patients receiving GMTZ required a significantly greater number of platelet transfusions per 100 hospital days (26.4 vs 22.1, p = 0.02), but fewer red cell transfusions (15.8 vs 19.2, p = 0.04). Hemostatic factor transfusions did not differ significantly between treatment arms. Table 1 presents mean number of antibiotic, antifungal and antiviral exposures per 100 hospital days. On average, patients received a total of 2.3 antibiotic and antifungal medication exposures for each hospital day during the first hospitalization. Antibiotic and antifungal use did not differ significantly by treatment arm. Median cost of Induction I did not differ by treatment arm: $98,324 (GMTZ) vs $93,846 (no GMTZ), p = 0.45. However, treatment costs increased significantly by age categories of 0–1, 1–9, 10–19, and greater than 19 years: $71,859, $87,171, $107,071, and $197,614, p = 0.0003. No cost differences by gender or race/ethnicity were observed. Conclusions: To our knowledge, these are the first data demonstrating that patients enrolled on a NCI-funded cooperative group oncology trial can be identified in an administrative data set, and that the supportive care resources utilization and treatment cost data can be analyzed by treatment arm and other patient characteristics. For AAML0531, these data demonstrate a significant difference in platelet and red cell transfusions between study arms and a significantly increasing treatment costs by age category. Additional work is ongoing to include all treatment courses in the resource utilization and cost analyses, to determine the drivers of total hospital costs, and to correlate resource utilization with reported adverse events. Such data will provide investigators, clinicians, and others with accurate estimates of the changes in resources and costs needed to treat pediatric patients with GMTZ. Furthermore, this approach should be broadly applicable to other pediatric and adult cooperative group oncology trials. Disclosures: Hall: CHCA: Employment. Bertoch:CHCA: Employment.
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 | 0,021 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,006 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».