Global Access to Multiple Myeloma Medications (GLAMM-2 Study): Access and Barriers to Chemoimmunotherapies and Transplant
Notice bibliographique
Résumé
Introduction Multiple myeloma (MM) is a clonal plasma cell malignancy and is the second most common type of hematologic cancer worldwide. Treatment options for MM have evolved in the last two decades with the introduction of novel therapeutic agents such as immunomodulatory drugs (IMiDs), proteasome inhibitors (PI), anti-CD-38 monoclonal antibodies (anti-CD38 MoAb), and recently BCMA-directed therapies (BDT). The variable access globally, especially for novel agents, has been a concern. We aim to study the global availability of 14 chemoimmunotherapy options in addition to autologous stem cell transplant (ASCT) which is approved in the US (excluding BDT due to limited availability), to identify regions with restricted access and analyze the main barriers to access. Methods A global cohort of oncologists outside the USA who treat MM participated in an online survey to evaluate the patterns of accessibility of MM therapies worldwide. The survey, conducted in collaboration with the US Myeloma Innovations Research Collaborative (USMIRC), was sent electronically to 176 oncologists worldwide (outside the US) from June 18th, 2023, to July 17th, 2023. It included questions on demographics, access, and perceived barriers. The respondents chose a response for each therapy as being “easily accessible”, “moderately accessible,” “not readily accessible” or “no access”. Countries were then classified as having “adequate access” if 80-100% of respondents affirmed easy/moderately easy access, while <30% were considered “limited access”, 60-79% were “high-intermediate access” and 30-59% were “low-intermediate access”. We classified countries into low- and high-income (LIC and HIC) based on the United Nations (UN) World Economic Classifications based on per capita gross national income (GNI). Means were calculated for regions of interest. An interim analysis is reported. Results Demographics: Ninety-Five (54%) oncologists from 33 countries completed the survey. Most were from Asia (56%). Others were Europe (19%), South America (12%), Africa (7%), Oceania (3%), and North America (Canada and Mexico, excluding the US) (3%). Only 17% specialized in plasma cell disorders; 50.5% were affiliated with university academic centers; 18% with private or community practices; 12% with community academic centers; and 17% were hybrid. Public-funded centers represented 61.1%, while 76% were transplant centers. Global Patterns: Most countries had adequate access to chemotherapies, IMiDs, PIs, Anti-CD38, MoAbs, and ASCT (Figure 1). Notably, ixazomib, isatuximab, and selinexor had low intermediate access, while elotuzumab had limited access. Access by Income: Most MM therapies were available in LIC and HIC. Of the therapies listed, 6 were adequately available in LIC and HIC: cyclophosphamide, lenalidomide, pomalidomide, daratumumab, bortezomib, and ASCT (Table 1). Elotuzumab and selinexor were limited in both LIC and HIC. Ixazomib and isatuximab were also limited in LIC but were low-intermediate in HIC. Access by Continent: Out of the 14 therapies, Europe had adequate or high-intermediate access to most modalities (12), followed by Oceania and Asia (10), and South America (9). North America and Africa had the lowest number of adequate or high intermediate access therapies (7) (Table 1). Barriers: The most common reason cited for limited access to MM therapies globally was the financial burden for the healthcare system, followed by limitations in local agency approval, inadequate chemotherapy suite resources, and inadequate staffing. Conclusion While most therapies were available, novel therapies such as isatuximab, ixazomib, selinexor, and elotuzumab were less readily accessible. Moreover, North America and Africa had the least access to therapies. This is likely because LIC and HIC have prioritized access to treatments with the best evidence of cost-effectiveness, while those with lower cost-effectiveness are generally limited. The financial burden on healthcare is a major limiting factor. USMIRC plans to investigate potential solutions and pursue global collaborative efforts to reduce disparities in therapies.
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 | 0,002 | 0,003 |
| 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 | 0,000 | 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 ».