Prospective Validation of Risk Prediction Indexes for Acute and Delayed Chemotherapy-Induced Nausea and Vomiting
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Notice bibliographique
Résumé
BACKGROUND: Despite the use of standardized anti-emetic guidelines, up to 20% of cancer patients suffer from moderate-to-severe chemotherapy-induced nausea and vomiting (cinv)-that is, grade 2 or greater according to the U.S. National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0. We previously developed cycle-based prediction models and associated scoring systems for acute and delayed cinv. As part of the validation process, we prospectively evaluated the ability of the scoring systems to accurately identify patients deemed to be high risk for grade 2 or greater cinv. METHODS: Patients who were receiving any chemotherapy for solid tumours and who consented to participate were provided with symptom diaries. Compliance to the diaries was enhanced by 24-hour and 5-day telephone callbacks after chemotherapy in every cycle. All patients received anti-emetic prophylaxis as prescribed by the treating physician. Before each cycle of chemotherapy, the acute and delayed cinv scoring systems were used to stratify patients into low- and high-risk groups. Logistic regression modelling was then applied to compare the risk for grade 2 or greater cinv between patients considered to be at high and at low risk. The external validity of each system was also assessed using an area under the receiver operating characteristic curve (auroc) analysis. RESULTS: We collected cinv outcomes data from 95 patients during 181 cycles of chemotherapy. The incidence of grade 2 or greater acute and delayed cinv was 17.7% and 18.2% respectively. As previously identified, major predictors for grade 2 or greater cinv included younger patient age, platinum- or anthracycline-based chemotherapy, low alcohol consumption, earlier cycles of chemotherapy, previous history of morning sickness, and prior emetic episodes after chemotherapy. The acute and delayed scoring systems both had good predictive accuracy when applied to the external validation sample (acute-auroc: 0.69; 95% confidence interval: 0.59 to 0.79; delayed-auroc: 0.70; 95% confidence interval: 0.60 to 0.80). Patients identified by the scoring systems to be at high risk were 2.8 (p = 0.025) and 3.1 (p = 0.001) times more likely to develop grade 2 or greater acute and delayed cinv. CONCLUSIONS: The present study demonstrates that our scoring systems are able to accurately identify patients at high risk for acute and delayed cinv. Application and planned continued refinement of the scoring systems will be an important means of patient-specific risk assessment that will allow for optimization of anti-emetic therapy.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 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) | 0,000 | 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 découle