Global data and haemophilia care trends: commentary
Notice bibliographique
Résumé
The lack of global data and evidence to confirm the prevalence and treatment outcomes of people with haemophilia A has been an impediment to improving and optimizing care for people with bleeding disorders. Two comprehensive papers in this issue of Haemophilia, titled ‘A study of variations in the reported haemophilia A prevalence around the world’ and ‘A study of reported factor VIII use around the world’, use data from the World Federation of Hemophilia (WFH) and other sources to help address this lack of evidence [1, 2]. Together, these papers are of particular significance to the global bleeding disorders community as they enhance understanding and provide an important new perspective of the relative level of care development for patients with haemophilia between and within countries. Both papers use historical data to analyse the number of people identified with haemophilia and the use of clotting factor concentrates (CFCs). As would be expected, some of the differences in both the number of patients identified and amount of CFCs used track very closely with economic measurements. However, Stonebraker et al note important differences within and between economic groups, which merit further investigation. Why, for instance, have some countries identified more people with haemophilia than in neighbouring countries? Why do countries with similar economies use very different amounts of factor VIII per capita? Moreover, these papers will spark additional interest in the need to answer important clinical questions such as, what is the appropriate amount of CFCs that governments should allocate and purchase for each patient? How can the use of CFCs be optimized to maximize clinical outcomes and patient quality of life? At a time when concepts such as Comparative Effectiveness Research and Health Technology Assessment are being applied to evaluate the life-saving, but costly, care for people with bleeding disorders, the availability of quality global data that help answer such questions is more important than ever. These two papers use data from the National Member Organisations (NMOs) that comprise the WFH. These data have been analysed along with other measurements and the results raise important questions about national differences in bleeding disorder prevalence and CFC use. Significantly, the factor VIII use paper [2] brings to light two important global trends: 1) across the economic groupings there has been a steady increase in the availability of CFCs and 2) the gap in CFC availability between developed and developing countries has narrowed. This paper also highlights some remarkable national achievements in this regard, such as in Russia, as well as the individual challenges still faced. It is encouraging to see that as more patients are identified, the global supply of factor VIII concentrates also continues to grow. Although steady progress has been made in improving treatment and care for people with bleeding disorders, today about 70% of the estimated patients with haemophilia in the world are still not diagnosed and 75% receive inadequate treatment. Additionally, within individual countries the standard of diagnosis and level of care varies. It is important to define both per capita and per patient measurements when analysing factor VIII usage. As haemophilia care starts to develop within a country, and where initially very few patients have been identified, small amounts of factor VIII can make a significant difference for those patients being treated. A low per capita level of factor VIII may not mean that individual patients diagnosed to date are receiving inadequate care. However, as more patients are identified, what was once a sufficient amount of treatment product will no longer meet patient needs. The comparative measurements, per capita and per patient usage, provide a more complete picture of the level of care within a country, relative to other countries. Understanding and promoting the value of such analyses can assist national health care planning as well as strategically direct global development initiatives of the WFH and its partners. A word of caution relates to the use of historical data, as alluded to in the factor VIII use paper [2]. Although useful for developing a global picture and making general conclusions about levels of care and prevalence in countries with different economic groupings, it would be unwise to overly interpret single data points or individual country data without more locally informed investigation. As Stonebraker et al note, even among highly advanced countries there is a lack of standardized data forms, definitions, and data collection procedures [1], and treatment strategies for prophylaxis, surgery, and inhibitors vary from country to country [2]. Similar ambiguities can arise in measurement of factor supply; for example, a large tender and purchase in one year, followed by two years of minimal or no supply could create a false perception, dependent on when data were collected. Despite its limitations, the WFH global database is the most robust and comprehensive which exists for the small global patient population. Each year its quality improves as more countries implement national registries and the cumulative database allows for trend and comparative analysis. It is recognized as an increasingly useful tool for national healthcare agencies and ministries of health, patient and health care provider associations, manufacturers of treatment products, and researchers. Additionally, the database helps to support program planning, allows measurement of progress, and enables the bleeding disorders community to work strategically towards the WFH’s goal of Treatment for All. The WFH is grateful to its NMOs for their extensive time and effort in annually responding to the global survey. Together with the authors of these papers, the WFH aspires to continually improve data collection and encourage associations, academics, and other researchers to collaborate in making the most of this unique resource. The authors stated that they had no interests which might be perceived as posing a conflict or bias.
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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 | 0,020 | 0,199 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,007 | 0,013 |
| Études des sciences et des technologies | 0,003 | 0,004 |
| Communication savante | 0,006 | 0,010 |
| Science ouverte | 0,009 | 0,004 |
| Intégrité de la recherche | 0,031 | 0,024 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,043 | 0,007 |
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 ».