Medical assistance in dying (MAiD) in patients with cancer.
Notice bibliographique
Résumé
12028 Background: Medical assistance in dying (MAiD) was legalized in Canada in 2016. Cancer accounts for 60-70% of MAiD cases, though little is known about the demographic profile, cancer diagnoses, and treatments received in patients with cancer who pursue MAiD. We reviewed all patients with cancer who underwent MAiD through a large regional MAiD program, in order to better understand this population and identify gaps in the current system of care delivery. Methods: All patients with cancer who received MAiD through the Champlain Regional MAiD Network (CRMN) from June 1 2016 – November 30 2020 were reviewed. The CRMN provides the majority of MAiD services covering a population of 1.3 million in Eastern Ontario. Baseline demographic factors, diagnostic information, and treatment details were collected by retrospective review. The primary endpoint was the proportion of patients with an oncology consultation prior to MAiD. Results: During the study period, 255 patients with cancer underwent MAiD. Baseline characteristics included: median age at death 71 (range 31-100), 51% male, 56% married/common-law. The most prevalent solid tumors were gastrointestinal [GI] (n = 77, 30%), lung (n = 47, 18%), and genitourinary [GU] (n = 35, 14%). Most patients (n = 201, 79%) had metastatic disease at the time of MAiD. Of those without metastatic disease at time of death, common tumor sites included central nervous system (42%) and head and neck (23%). The majority of patients (n = 229, 89%) had seen an oncology specialist prior to MAiD; 226 (88%) had seen a systemic oncologist (medical, hematologic, or gynecologic oncologist), and 189 (69%) a radiation oncologist. Seventy-three percent of patients were followed by a systemic oncologist within 90 days of MAiD, and 44% within 30 days of MAiD. At least one line of systemic therapy was received by 159 (62%) patients, 138 (54%) received radiotherapy, and 61 (24%) best supportive care alone. Median time from last systemic therapy to MAiD was 85 days, and from last radiation therapy to MAiD was 137 days. Palliative care assessed at least 213 patients (84% [8% unknown]). Common reasons for pursuing MAiD included disease-related symptoms (33%), fear of future suffering or disability (19%), and ability to control the time and manner of death (17%). Among 26 patients who had not seen an oncologist, median age was 84 (range 61-100), 77% male, 42% GI primary / 19% GU / 15% lung. Most had seen a palliative care specialist (n = 23, 88%), and in the remaining 3 patients palliative care involvement was unknown. Conclusions: MAiD is a relatively new option for patients with cancer in Canada. The vast majority of patients with cancer who pursue MAiD are diagnosed with advanced/incurable disease, and most have met with an oncology specialist. As cancer treatments become more effective and more tolerable, collaboration between oncologists and MAiD providers is required to ensure patients are well informed of treatment options prior to MAiD.
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 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| 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) | 0,003 | 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 ».