Impact of Electronic Patient-Reported Outcomes on Unplanned Consultations and Hospitalizations in Patients With Cancer Undergoing Systemic Therapy: Results of a Patient-Reported Outcome Study Compared With Matched Retrospective Data
Notice bibliographique
Résumé
BACKGROUND: The evaluation of electronic patient-reported outcomes (ePROs) is increasingly being used in clinical studies of patients with cancer and enables structured and standardized data collection in patients' everyday lives. So far, few studies or analyses have focused on the medical benefit of ePROs for patients. OBJECTIVE: The current exploratory analysis aimed to obtain an initial indication of whether the use of the Consilium Care app (recently renamed medidux; mobile Health AG) for structured and regular self-assessment of side effects by ePROs had a recognizable effect on incidences of unplanned consultations and hospitalizations of patients with cancer compared to a control group in a real-world care setting without app use. To analyze this, the incidences of unplanned consultations and hospitalizations of patients with cancer using the Consilium Care app that were recorded by the treating physicians as part of the patient reported outcome (PRO) study were compared retrospectively to corresponding data from a comparable population of patients with cancer collected at 2 Swiss oncology centers during standard-of-care treatment. METHODS: Patients with cancer in the PRO study (178 included in this analysis) receiving systemic therapy in a neoadjuvant or noncurative setting performed a self-assessment of side effects via the Consilium Care app over an observational period of 90 days. In this period, unplanned (emergency) consultations and hospitalizations were documented by the participating physicians. The incidence of these events was compared with retrospective data obtained from 2 Swiss tumor centers for a matched cohort of patients with cancer. RESULTS: Both patient groups were comparable in terms of age and gender ratio, as well as the distribution of cancer entities and Joint Committee on Cancer stages. In total, 139 patients from each group were treated with chemotherapy and 39 with other therapies. Looking at all patients, no significant difference in events per patient was found between the Consilium group and the control group (odds ratio 0.742, 90% CI 0.455-1.206). However, a multivariate regression model revealed that the interaction term between the Consilium group and the factor "chemotherapy" was significant at the 5% level (P=.048). This motivated a corresponding subgroup analysis that indicated a relevant reduction of the risk for the intervention group in the subgroup of patients who underwent chemotherapy. The corresponding odds ratio of 0.53, 90% CI 0.288-0.957 is equivalent to a halving of the risk for patients in the Consilium group and suggests a clinically relevant effect that is significant at a 2-sided 10% level (P=.08, Fisher exact test). CONCLUSIONS: A comparison of unplanned consultations and hospitalizations from the PRO study with retrospective data from a comparable cohort of patients with cancer suggests a positive effect of regular app-based ePROs for patients receiving chemotherapy. These data are to be verified in the ongoing randomized PRO2 study (registered on ClinicalTrials.gov; NCT05425550). TRIAL REGISTRATION: ClinicalTrials.gov NCT03578731; https://www.clinicaltrials.gov/ct2/show/NCT03578731. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/29271.
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 | 0,005 | 0,014 |
| 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 | 0,000 |
| 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 ».