Sex-based disparities in MPN treatment patterns: A study of 1167 patients from the Quebec MPN registry
Notice bibliographique
Résumé
Abstract Background: Sex and gender have emerged as fundamental modifiers of disease biology, phenotype, and prognosis in myeloproliferative neoplasms (MPN) (Blood Adv, 2020). Furthermore, substantially higher symptom burden has been documented in women vs men with MPN, including recent data from our group (publication pending, 2025), prompting inquiry into how these distinctions inform therapeutic strategy. Contemporary data on sex-driven differences in treatment courses and outcomes remain scarce and the impact of such patterns is often underappreciated. The objective of this study was to determine sex-specific treatment patterns in patients with MPN with the goal of better directing and personalizing management. Methods: Consecutive patients with WHO/ICC-defined polycythemia vera (PV), essential thrombocythemia (ET), and myelofibrosis (MF) from the Quebec MPN Research Group Registry (13 academic/community centers) were included. Clinical data were abstracted from medical records spanning 3/2015 (registry deployment) to 1/2024. Conventional disease-specific risk stratification models were used. Clinical endpoints were defined per convention. Standard statistics were used (SAS version 9.4; Cary, NC, USA); all tests were two-sided with p<0.05 considered significant. Results: Women accounted for 55% of the 1167 patients studied. Median age at diagnosis was comparable across sexes (60/61 years in women/men (range 17-95); p=0.54). Median follow-up was 88 months (0.56-506), irrespective of sex. Disease-specific sex distribution showed a preponderance of women with ET (63%), a minority with MF (32%) (p<0.0001), and equal ratios for PV. Baseline demographics and comorbidities were balanced. Disease-specific models revealed similar risk profiles between women and men in all 3 MPN subtypes (p=0.1-0.49). Regarding therapy, an equivalent proportion of women were approached frontline with cytoreduction (vs observation) compared men (p=1.0). However, significantly fewer female PV and MF patients required phlebotomy or transfusions, respectively, over disease course compared to their male counterparts (p=0.0017 each). Considering MPN subtypes collectively, first-line cytoreductive regimens revealed significantly higher interferon exposure in women (2.6%) vs men (0.4%) (p<0.0001), and, conversely, skewing towards ruxolitinib use in men (9.2%) vs women (3.1%), concordant with the enrichment of male MF patients in the registry. Next, stratified by MPN subtype, cytoreductive agent patterns were found to be largely homogeneous across sexes: hydroxyurea predominated as first-line in both women and men in PV (women/men; 70.3%/75.2%; p=0.66) and ET (68.4%/70.5%; p=0.19), while ruxolitinib was the leading agent in MF (50%/52%; p=0.47). Of all patients on cytoreduction, 62.1% of women and 54.4% of men remained on frontline therapy at the time of data collection (p<0.0001). Remarkably, treatment discontinuation patterns revealed the reason for stopping/switching from first-line agent varied significantly according to sex. Of those who discontinued therapy, intolerance was the leading cause in women (18.9% vs 15.5% in men) (p<0.0001), while resistance and death were more common in men (respectively vs women 3.6% vs 1.7%; and 10.9% vs 4.3%) (p<0.0001). When overall length of drug exposure was scrutinized, this was found to be balanced between sexes for all agents except interferon, for which duration of treatment was significantly longer in men vs women (94.3 months vs 34.3; p=0.02). Conclusions: This is, to our knowledge, one of only available accounts of treatment patterns appraised under a sex-informed lens in the cadre of MPN. These large-scale, mature, real-world data confirm that in this schema – sex matters. Overall, key disparities in therapeutic strategies between women and men are disclosed, reflecting sex-biased enrichment of specific MPN subtypes. However, when subtype-stratified, remarkably uniform, sex-agnostic patterns were observed, despite well-documented higher symptom burden in women. This challenges the extent to which symptomatology, distinct in females, is justly informing treatment decisions. Finally, more women than men discontinued therapy due to intolerance, underscoring the need for better-tolerated agents as well as complementary treatment strategies.
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 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 ».