The Myeloproliferative Neoplasm Landscape: A Patient’s Eye View
Notice bibliographique
Résumé
Patients with myeloproliferative neoplasms (MPNs), a group of rare haematological conditions including polycythaemia vera, essential thrombocythaemia, and myelofibrosis, often experience a range of symptoms which can significantly impact their quality of life (QoL). Although symptom burden is highest in myelofibrosis and high-risk patients, lower-risk patients also report symptoms impacting their daily life and ability to work. In addition to physical symptoms, MPNs affect emotional well-being, with anxiety and depression frequently reported by patients. Despite significant advances in treatment options, such as the introduction of JAK1/JAK2 inhibitors, therapy for MPNs is often palliative; therefore, reduction of symptoms and improvement of QoL should be considered as major treatment goals. One of the main issues impacting MPN treatment is the discord between patient and physician perceptions of symptom burden, treatment goals, and expectations. New technologies, such as app-based reporting, can aid this communication, but are still not widely implemented. Additionally, regional variation further affects the psychosocial burden of MPNs on patients and their associates, as treatments and access to clinical trials are options for patients living in some areas, but not others. Overcoming some of the challenges in patient–physician communication and treatment access are key to improving disease management and QoL, as well as giving the patient greater input in treatment decisions. Myeloproliferative neoplasms (MPNs) are a group of blood diseases where the body makes too many blood cells. Patients with MPNs can have symptoms which interfere with their daily lives, such as tiredness, pain, sweating at night, dizziness, itching, and difficulty sleeping. They also often suffer from anxiety and/or depression. In nearly all cases, physicians cannot cure the disease, but drugs can prevent blood clots and reduce the speed at which the disease gets worse. Usually, the main aim of treatment is improving patients’ quality of life (QoL). Targeted drugs, such as ruxolitinib, treat MPNs and reduce symptoms, but do not cure the disease. Patients frequently want to play a bigger part in decisions about their treatment. However, physicians and patients often have different views on how well treatments are working and what to expect from the treatment. This can mean that patients feel they are not getting the best treatment for their symptoms. Also, patients may not be able to get some treatments or take part in a trial of a new drug, depending on where they live. This creates feelings of unfairness which can affect their mental health. Addressing all these problems may help improve the QoL for patients with these blood diseases.
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 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,007 | 0,012 |
| Science ouverte | 0,001 | 0,007 |
| Intégrité de la recherche | 0,009 | 0,014 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,006 |
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 ».