Trajectory of symptoms reported in remote symptom monitoring over the course of oncology treatment for gynecologic cancers.
Notice bibliographique
Résumé
270 Background: Patients now have the ability to utilize electronic patient reported outcomes (ePROs) for remote symptom monitoring (RSM). This analysis seeks to better understand trajectory of reported symptoms during treatment for patients with gynecologic cancer participating in RSM. Methods: We approached patients with gynecological cancer initiating treatment at the Mitchell Cancer Institute (MCI) between 7/1/21-4/30/2022. Patients were eligible if they were starting chemotherapy, targeted therapy, or immunotherapy for a new cancer. Patients seeking a second opinion were excluded. Enrolled patients received symptom survey (PRO-CTCAE questions) via text or email once per week. Initially, only severe alerts were forwarded to the clinical care team; moderate alerts were forwarded to clinical teams once they were comfortable with alert management. Patients completed symptom assessments for 24 weeks or until withdrawal. Patient age at enrollment, race, sex, cancer type, cancer stage, and PROs were abstracted from electronic health records and the PRO platform (Carevive). Descriptive statistics were calculated using frequencies and percentages for categorical variables and median and interquartile ranges (IQR) for continuous variables. Results: A total of 60 female patients with gynecological cancer were enrolled; 33% were Black or African American and 67% were White; median age was 61 years (IQR 53-68). Seventy-eight percent (47/60) of patients reported 379 symptoms with at least one moderate or severe alert during this time period; 32% considered moderate and 68% considered severe. Overall, the most frequently reported symptom was pain (29%). At baseline (week 0), 14% and 41% of 56 patients reported moderate symptoms and severe symptoms, respectively. Symptom burden decreased over time with 4% and 7% of 27 patients who completed a survey at 12 weeks reporting moderate and severe symptoms. Specific symptom trajectories followed similar patterns. Conclusions: In our sample, patients reported the majority of symptoms during the first three months of treatment. Symptom trajectory decreased with time, suggesting symptoms are being effectively monitored and addressed by the clinical teams engaging in RSM. Future research is needed to understand if symptom improvement translates to increased quality of life, decreased hospitalizations, and increased survival for patients, as well as lessen the burden of call volume on the clinical team.
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 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| 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 ».