Abstract PO-041: The impact of the COVID-19 pandemic on cancer patients
Notice bibliographique
Résumé
Abstract As overwhelmed health care systems are dealing with the COVID-19 pandemic, changes to oncology care have been implemented to minimize patients’ exposure to the virus. We aim to understand the impact of COVID-19 on cancer patients through a questionnaire completed by cancer patients or their caregivers. From 3/24/2020 to 4/15/2020, a total of 112 patients/caregivers completed the questionnaire. Of the 112, 81 (72%) of those who completed the survey were the patients themselves, 14 (13%) were caregivers, and for 17 (15%) it was unknown. The majority of patients (48%) were between the ages of 50 and 69, 13% were 70-79, and for 22% of the patients, their age was unknown. 66 (59%) were females, 30 (27%) were male, and for 14% the sex was unknown. Thirteen types of cancers were reported; the most common cancer were breast, lung, and colorectal. Most of the participants were from the US (70%) with 12 countries represented, including Italy (7%), Canada (4%), Australia (3%), and the UK (3%). Of the 112 patients and caregivers who completed the survey, 78 (70%) reported that they or the patients they care for were currently receiving cancer treatment. Those not currently receiving cancer treatment reported the last time they received treatment as far back as March 2008 to March 2020. Canceled or postponed appointments due to COVID-19 were reported by 32 (29%) participants. Thirteen (12%) reported treatment delay because of COVID-19. Six patients (5%) were newly diagnosed and had to make a treatment decision about a new cancer diagnosis during the COVID-19 pandemic. Twenty-one (19%) patients had to make a decision about a treatment change. Eighty-three reported on whether COVID-19 affected any treatment decisions they had to make. Of these 83, 24 (29%) reported that COVID-19 affected their treatment decision, and 23 gave an explanation. The most common explanations of how COVID-19 affected treatment decisions were “changes to travel for treatment/change in place of treatment,” “changes in travel/living situations/other personal changes,” “changes to surveillance,” “changes, delays, or not receiving treatment to decrease risk of COVID-19 infection,” “continued on treatment that is not working,” and “did not continue to pursue a clinical trial.” Symptoms of COVID-19 (coughing, fever, shortness of breath) were reported by 16 (14%) patients and caregivers. Six (5%) patients had COVID-19 testing, with one patient still awaiting results, and all of the other five tested negative. Increased anxiety about cancer treatment due to COVID-19 was reported by 72 (64%) participants. Personalized support through follow-ups was implemented in an attempt to help patients relieve some of their anxiety about their cancer treatment. Overall, changes to appointments, treatment delays, and the impact of COVID-19 on treatment decisions were reported by patients and caregivers. A general sense of uncertainty about appointments and treatment plans was reported. Citation Format: Lola Rahib, Zach Kaufman, Erika Vial Monteverdi. The impact of the COVID-19 pandemic on cancer patients [abstract]. In: Proceedings of the AACR Virtual Meeting: COVID-19 and Cancer; 2020 Jul 20-22. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(18_Suppl):Abstract nr PO-041.
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 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 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) | 0,009 | 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 ».