Abstract P4-03-28: Patient Reported Symptom Burden Amongst Immigrant and Canadian Long-Term Resident Women Undergoing Breast Cancer Surgery
Notice bibliographique
Résumé
Abstract Background: Disparities in breast cancer outcomes are well documented, with a burgeoning body of literature shedding light on the influence of multiple factors. Much of the literature comes from the US, with the current situation in Canada less well understood. Canada’s universal health care system may mitigate some, but unlikely all differences. First generation immigrants compromise 21.9% of the Canadian population. Differences in breast cancer screening rates and stage at diagnosis have been demonstrated between immigrant and non-immigrant Canadian women. However, breast cancer outcomes in the Canadian immigrant population have not been well studied. Patient reported outcomes are one such set of outcomes and crucial in understanding the patient experience. The purpose of this study is to compare symptom burden and trajectories between immigrant and Canadian long-term resident women with breast cancer undergoing breast cancer surgery in Ontario. Methods: A population-level retrospective cohort-study using linked Ontario administrative databases was constructed. Women >18 years of age with newly diagnosed breast cancer between 2010-2016 undergoing surgery at a regional cancer center were included. Baseline variables including immigration status, age, stage, comorbidity and income quintile were collected. The proportion of patients reporting moderate/severe Edmonton Symptom Assessment System Scale (ESAS) scores for each of 9 individual symptom categories over time was collected. Multivariable logistic regression models using generalized estimating equations with exchangeable correlation structure to account for repeated measures were constructed to assess the probability of a moderate/severe score for each of the individual ESAS symptom categories. Results: The cohort included 14,056 women, of which 12,250 (87.2%) were categorized as long-term Canadian residents and 1,806 (12.8%) as immigrants. Immigrant women had a younger mean age of diagnosis (53 vs. 61 years), were more likely to reside in a lowest income quintile neighbourhood (22.2% vs 15.4%), were less likely to be on a primary care physician roster within the last 2 years (83.7% vs. 90.4%) and were less often diagnosed with Stage I/II disease (80.9% vs. 84.6%) (all p< 0.0001). The proportion of women reporting moderate/severe scores was significantly higher amongst immigrant women for 7/9 symptom categories (anxiety, depression, drowsiness, nausea, pain, shortness of breath and well-being) with the largest difference observed for depression (13.1% vs 10.8%, p< 0.0001) and pain (14.8% vs. 12.0%, p< 0.0001). Comparing symptom trajectories, differences between groups were most pronounced within the first 12 months, though for depression and pain, statistically significant differences also existed at 36 months. On multivariable regression analysis, immigration status was persistently associated with higher proportion of moderate/severe score for pain only (OR 1.12, 95% CI 1.02-1.23). Immigration status was associated with a protective effect for anxiety (OR 0.86, 95% CI 0.78-0.94), drowsiness (OR 0.81, 95% CI 0.73-0.89) and tiredness (OR 0.86, 95% CI 0.79-0.94). Conclusions: To our knowledge, this is the first study comparing symptom burden amongst immigrant and non-immigrant Canadian women with breast cancer at a population-level. Immigrant women undergoing breast cancer surgery were found to have a higher burden of symptoms across most categories, and for depression and pain this difference was found to persist even at 3-years. However, the higher burden of symptoms in many categories seemed to be explained by factors such as younger age and more advanced disease. Adjusting for other factors, immigrant women with breast cancer reported more pain, indicating a need for better symptom management in this population. Citation Format: Elena Parvez, Megan M. Chu, David Kirkwood, Aristithes Doumouras, Jessica Bogach. Patient Reported Symptom Burden Amongst Immigrant and Canadian Long-Term Resident Women Undergoing Breast Cancer Surgery. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P4-03-28.
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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 | 0,002 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 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 ».