Abstract P4-18-01: Waiting for Treatment: Addressing Inequities in access to essential medications for metastatic breast cancer
Notice bibliographique
Résumé
Abstract Introduction: Of the women in Canada diagnosed with breast cancer each year, 5% will have an initial diagnosis of metastatic breast cancer and many more will recurr with metastatic disease. Despite global advancements in metastatic breast cancer, access to new drugs in Canada remains inequitable. Objective: To examine the present situation in Canada for drug approval and decision-making by provinces and territories around new metastatic drugs and to assess processes in the system causing the greatest lags, the range in wait times for new treatments by province and the jurisdictions most affected by wait time delays. Methodology: - A bilingual survey in spring 2015, focusing on access to metastatic treatments across Canada. 98 women responded to the survey from all Canadian jurisdictions except Yukon. -A case study of 4 metastatic therapies undergoing multi-step drug review. Results: Systemic Delays: Patients endure 1-2 years for drugs to be approved for sale in Canada and further delays in access through the pCODR, pCPA and provincial drug assessment processes. The longest delays occur at the provincial review stage. Inequitable Access to Treatments across Provinces: Lack of firm deadlines for the provinces to list a drug on their formulary once a drug has been approved pricing negotiated. Often a 2-year time lag or longer between provinces in making reimbursement decisions, resulting in inequitable access across the country. Line Sequencing Access Delays: Further limitations on access created by the restrictions that provinces place on when drugs can be used in the course of treatment. Formularies often cover older drugs that are less costly, and as such it is a challenge to secure coverage of newer therapies. Conclusion: Wait time delays create a significant barrier to patients receiving optimal treatment and care. Metastatic patients are forced to endure wait time delays of 2-4 years before accessing new treatments. These delays occur at nearly every stage of the approval process, with the greatest waits occurring at the provincial level. Lags in treatment access across the country also have an impact on standards of care. Patients in provinces with timely approvals, have access to more treatment options than those in provinces where patients must wait for new treatments to be added to the formulary. Lengthy wait times for new treatments complicate a patient's prognosis. Slowing the progression of their disease and maintaining a better quality of life is of critical concern and metastatic patients with urgent treatment needs cannot wait for new treatments to become publicly accessible. For these patients, expedited access to a diversity of treatment options can make all the difference in ensuring optimal health outcomes and improved quality of life. Citation Format: Faucette C. Waiting for Treatment: Addressing Inequities in access to essential medications for metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-18-01.
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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 | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 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 ».