Impact of Cooperating Myeloid Gene Mutations on Disease Progression and Survival in Japanese MPN Patients: A Multicenter Study
Notice bibliographique
Résumé
In addition to driver mutations such as JAK2, CALR, and MPL, some patients with Polycythemia vera (PV), Essential thrombocythemia (ET), and Primary myelofibrosis (PMF) also have mutations common to other myeloid tumors. We conducted this study from 2018 to clarify the impact of such cooperating myeloid gene mutations on survival in real-world clinical settings. We included 622 MPN patients (PV 180, ET 360, PMF 82) from 8 hospitals who were examined for driver mutations for diagnosis and diagnosis confirmation at the University of Miyazaki from March 2007 to March 2023. 69.1% of all DNA samples were collected within 1 year from diagnosis. We investigated gain-of-function hotspot mutations in six genes (IDH1, IDH2, ASXL1, U2AF1, SF3B1, U2AF1) using Sanger sequencing. Loss-of-function mutations without hotspots (e.g., EZH2, TP53, ZRSR2, RUNX1) were not investigated. We retrospectively investigated overall survival and disease progression (progression to myelofibrosis or leukemia in PV and ET, and progression to leukemia in PMF). The median observation period was 5.1, 5.9, and 3.1 years for PV, ET, and PMF, respectively. One or more cooperating mutations were found in 9.4%, 11.7%, and 43.9% of PV, ET, and PMF cases, respectively, with ASXL1 being the most common mutation found in 5.4%, 7.3%, and 26.8% of cases. The incidence of disease progression in PV and ET patients was 0.066 and 0.098 at 10 years, respectively. Patients with cooperating mutations had a higher rate of progression than patients without these mutations (PV: 0.348 vs 0.029, p=0.0088; ET: 0.388 vs 0.060, p<0.0001). The incidence of leukemic transformation in PMF patients was 0.14 at 5 years. Patients with cooperating mutations had a higher rate of transformation compared to patients without these mutations (0.270 vs 0.051, p=0.053).The 10-year overall survival (OS)rates for patients with PV and ET were 87.6% and 85.6%, respectively. The 5-year OS rate for patients with PMF was 62.6%. Patients with cooperative mutations in PV and ET had lower 10-year OS rate than those without (PV: 58.2% vs 91.2%, p=0.02; ET: 74.7% vs 88.1%, p=0.00029).In PMF, patients with these mutations had a lower 5-year OS rates than those without (41.5% vs 80.0%, p=0.00093). We analyzed survival from the time of DNA sampling for 183 patients with PV or ET (55 PV, 128 ET) who were examined for mutations using DNA sampled more than 1 year after diagnosis. The median time from diagnosis to DNA sampling (interquartile range, IQR) was 5.3 years (IQR, 2.2-10.0 years), and the median follow-up period after DNA sampling was 5.4 years. In this patient population, patients with cooperative mutations also had a lower 5-year OS rate compared to patients without mutations (55.4% vs 93.1%, p<0.0001). In this study, genetic mutation analysis did not use NGS, resulting in lower sensitivity in mutation detection and a limited number of genes investigated. Despite these limitations, it was evident that some cooperating myeloid gene mutations had a clear negative impact on both disease progression and survival in real-world clinical settings. Our results also indicate that screening for these mutations may be of prognostic value even during the course of PV or ET. In conclusion, screening for such mutations is crucial for managing all MPN patients.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».