Patient-reported experience of diagnosis, management, and burden of renal cell carcinomas: Results from the 2020 Global Patient Survey from 41 countries.
Notice bibliographique
Résumé
4579 Background: The sustained increased global prevalence of kidney cancer (renal cell carcinoma, RCC) has increased the burden to health systems, and most of all, to individual patients and their families. Although individual national surveys have been held, no conclusions could be drawn about country-level variation in patient experience or best practice. Here, we report on the second biennial Global Patient Survey on the diagnosis, management, and burden of RCC. Conducted by the International Kidney Cancer Coalition (IKCC) and involving its Affiliate Organizations worldwide, the survey aims to improve collective understanding and to contribute toward the reduction of the burden of kidney cancer around the world. Methods: A 35-question survey on the diagnosis, management, and burden of RCC was designed by a multi-country steering committee of patient leaders to identify geographic variations in 6 key dimensions: patient education, experience and awareness, access to care and clinical trials, best practices, quality of life, and unmet psychosocial needs. The survey was distributed in 13 languages to patients with kidney cancer and their caregivers, through IKCC’s 46 Affiliate Organisations and social media. It was completed online or in paper form between 29 Oct 2020 and 5 Jan 2021. Results: 2,012 (1,586 patients, 417 carers, 9 undisclosed) responses were recorded from 41 countries in 13 languages. Survey results were analyzed using cross-tabulations by an independent third-party organization. The full global report will be publicly available, as well as 7 individual country reports where at least 100 responses were received. 52% lacked understanding of subtype at diagnosis. 42% reported that the likelihood of surviving their cancer beyond 5 years was not explained. 51% reported that they were involved as much as they wanted to be in developing their treatment plan. 41% indicated that “No one” discussed cancer clinical trials with them. 31% were invited to take part in a clinical trial. 56% experienced barriers to their treatment. 45% self-reported that they were insufficiently physically active; 15% were completely sedentary. 50% indicated that they ‘very often’ or ‘always’ experienced disease-related anxiety. 55% indicated that they ‘very often’ or ‘always’ experienced a fear of recurrence. 52% reported having talked to their doctor/healthcare professional about their concerns. Conclusions: The IKCC and its global affiliates will use these results to ensure that patient and caregiver voices are heard and acted upon, with ultimate incorporation of these findings by much broader communities into care pathways, clinical practice, or health technology assessments. Furthermore, individual countries can use their reports to advance understanding of patient experiences and to drive improvements in providing care locally.
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 | 0,003 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 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 | 0,001 | 0,001 |
| 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 ».