Abstract 989: Do physician-reported toxicities accurately reflect patient-reported symptom burden? An analysis of ESAS and CTCAE for patients with lung cancer
Notice bibliographique
Résumé
Abstract Purpose/Objectives: Symptom adverse events can be quantitatively monitored by oncologists with the U.S. National Cancer Institute’s Common Terminology Criteria for Adverse Events (CTCAE). Symptoms can also be reported by patients through the Edmonton Symptom Assessment Scale (ESAS). There is increasing recognition of the importance of assessing patient-reported symptoms as part of clinical care. The aim of this study is to examine correlation between patient-reported and physician-graded symptoms in patients with lung cancer who underwent external beam thoracic radiotherapy, in an attempt to identify gaps between these parameters. Materials/Methods: Between August 2015 and July 2016, 265 patients with diagnosis of lung cancer had completed ESAS and CTCAE data obtained during weekly clinic visit while undergoing thoracic radiotherapy.The following stratification for symptom severity was used: ESAS (none, 0; mild 1-3, moderate 4-6, severe 7-10) and CTCAE scores (none, 0; mild, 1; moderate, 2; and severe, 3-4). Five associated symptoms were compared: tiredness, nausea, shortness of breath, and other (cough and dysphagia) from ESAS and fatigue, nausea, dyspnea, cough and esophagitis from CTCAE. Frequency tables and boxplots combined with the scatter plots were used to assess the distribution, correlation and to identify possible outliers. Spearman correlation coefficients were analyzed to evaluate rank-associated correlations between associated ESAS domains and CTCAE toxicities. Results: Statistical analysis showed that the associated ESAS symptoms and CTCAE toxicity pairs (tiredness/fatigue, nausea, shortness of breath/dyspnea, dysphagia/esophagitis, cough) were highly correlated (p<0.05), However, analysis showed that ESAS reported by patients screens for more severe symptoms than the toxicities graded by physicians using the CTCAE; this includes fatigue (16.1% as opposed to 0.5%), nausea (5.0% as opposed to 0.0%), dyspnea (11.8% as opposed to 2.4%), cough (2.1% as opposed to 0.2%), and esophagitis (1.5% as opposed to 0.5%). ESAS collected additional symptom domains including overall wellbeing symptoms, depression, anxiety, and spiritual wellbeing, which are not included on CTCAE. ESAS detected 6.2% of patients reporting severe depression, 8.3% with severe anxiety, 9.7% marking severe for poor overall wellbeing, and 8.3% marking severe for poor spiritual wellbeing. Conclusion: This studied demonstrated that while ESAS and CTCAE reports are correlated, patients reported more severe symptoms through ESAS compared to physician-graded toxicities from CTCAE in this group of lung cancer patients who underwent thoracic radiotherapy. Systematic acquisition of patient-reported symptoms is important to optimize clinical care and symptom management. Citation Format: Bansi Savla, Thomas Dilling, Syeda Mahrukh Naqvi, Jae K. Lee, Hsiang-Hsuan M. Yu. Do physician-reported toxicities accurately reflect patient-reported symptom burden? An analysis of ESAS and CTCAE for patients with lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 989. doi:10.1158/1538-7445.AM2017-989
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 | 0,004 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».