Assessing the feasibility of recording smartphone-based patient-reported outcomes in patients with cancer: A pilot study.
Notice bibliographique
Résumé
e13528 Background: We conducted this study to evaluate the feasibility of completing patient-reported outcomes (PROs) using a mobile-based secure system at home, as opposed to the traditional method of completing them in crowded outpatient oncology clinics during hospital visits, which may not be ideal in resource-limited settings. Methods: The study included patients aged over 18 years who were newly diagnosed with solid-organ cancer between July 2021 and July 2022 at a tertiary cancer center in India. Patients who were able to use a smartphone were invited to complete a mobile-based Edmonton Symptom Assessment Scale (ESAS) questionnaire, which was accessed via a secure link sent to their phone as a chat. The ESAS questionnaire included physical (six domains: pain, tiredness, drowsiness, shortness of breath, nausea, loss of appetite), psychological (anxiety and depression), and overall well-being (one domain) questions, each rated on a scale of 0-10, with a higher number indicating greater symptom burden. Symptoms were classified as mild (1-3), and moderate to severe (4-10). The primary objective was to determine the completion rate of the questionnaire, while the secondary objectives were to determine the incidence of moderate to severe symptoms, both physical and psychological, at cancer diagnosis. Multivariate logistic regression analysis was used to identify factors associated with moderate to severe symptoms. Results: We reached out to 707 consecutive patients who had recently been diagnosed with solid-organ cancer and used smart phone. The median age of participants was 53 years (with an interquartile range of 43-62 years), and 52.3% were female. Breast cancer (30.6%) was the most common diagnosis, followed by lung cancer (28.8%). Approximately, one-third of all patients had metastatic disease at diagnosis, while others were similarly distributed in stage I-III. Overall, 650 patients (91.9%) patients completed the mobile-based questionnaire; 38.9% of patients had moderate to severe physical symptoms and 30.9% had moderate to severe psychological symptoms. Pain (57.7%) and tiredness (58.7%) were the most commonly reported physical symptoms in moderate to severe category, while nausea (18.1%) and drowsiness (20.3%) were reported least frequently as moderate to severe. Anxiety (35.1%) was more prevalent than depression (26.1%). The total symptom score was mild in 76.5% of patients and moderate to severe in 18.8%. On multivariate logistic regression, patients with advancing age, female sex, and metastatic disease at diagnosis were more likely to report moderate to severe symptoms. Conclusions: Using smartphone-based PROs can be an efficient way to record symptoms in cancer patients, and their high completion rates make them suitable for routine use in oncology clinics, especially considering the increasing number of smartphone subscribers globally.
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 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,001 |
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 ».