MétaCan
Menu
Retour à la cohorte
Enregistrement W4417015865 · doi:10.1182/blood-2025-5548

Beyond survival in chronic myeloid leukemia: A systematic review of secondary malignancies in the era of tyrosine kinase inhibitors

2025· article· en· W4417015865 sur OpenAlexaboutno aff
Ghasoub Rola, Maria Benkhadra, Laila Shafei, Sara Aldali, Anas Hamad, Sa’ad Laws, Mohammed A. Yassin

Notice bibliographique

RevueBlood · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Myeloid Leukemia Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMyeloid leukemiaIncidence (geometry)Systematic reviewMEDLINETyrosine kinaseMedical recordConcomitantTyrosine-kinase inhibitorNilotinib

Résumé

récupéré en direct d'OpenAlex

Abstract Background: The introduction of tyrosine kinase inhibitors (TKIs) has markedly extended survival in chronic myeloid leukemia (CML), shifting clinical priorities toward long-term safety and late treatment effects, including the emergence of secondary malignancies (SMs). Reports on this risk are mixed, with varying conclusions regarding the frequency and spectrum of SMs in TKI-treated CML patients. This systematic review aimed to synthesize the existing evidence on the incidence, types, and timing of SMs in patients with chronic-phase CML treated with TKIs. Methods: We conducted a systematic review following PRISMA guidelines (PROSPERO ID: CRD420251067085). A comprehensive literature search was performed through May 2025 across PubMed, Embase, Medline, and Web of Science, using Medical Subject Headings (MeSH) terms. Eligible studies were those reporting the incidence of SMs in adults with chronic-phase CML treated with TKIs, including imatinib, dasatinib, nilotinib, bosutinib, ponatinib, and asciminib. Studies were excluded if they involved patients with advanced CML phases or received concomitant chemotherapy. Case reports, grey literature, or non-English studies were also excluded. Two independent reviewers performed the screening, data extraction, and quality assessment using the Newcastle-Ottawa Scale, National Institutes of Health (NIH), and Cochrane tools, as appropriate. Data synthesis was descriptive of the SM types and ranges of incidence due to clinical and methodological heterogeneity. Results: A total of 408 records were identified [EMBASE: 199; PubMed: 81; Medline: 77; Web of Science: 51]. After title and abstract screening, 154 duplicates and 84 irrelevant records were excluded. Following full-text screening, 156 studies were excluded for ineligible populations (n=48), absence of outcomes of interest (n=45), lack of SM data reporting (n=24), inappropriate design [case reports/series (n=19), grey literature (n=16)], and non-English language (n=4). Fourteen studies were included in the final analysis (13 retrospective cohorts, 1 prospective RCT), representing 42,781 chronic-phase CML patients treated with TKI. The studies were geographically diverse, with overlapping use of multiple TKIs (n=7). Imatinib was the most commonly reported (n=12), followed by dasatinib (n=8) and nilotinib (n=7). Data on bosutinib (n=2) and ponatinib (n=1) were limited, while asciminib was not reported in any study. Due to heterogeneity in reporting, pooling of incidence rates was precluded by inconsistencies in exposure duration and sequencing of therapies. Reported SM incidence ranged from 3.1% to 7.5% in single-institution cohorts, while large population-based studies reported proportions between 4.2% and 5.6%. Standardized incidence ratios (SIRs) ranged from 0.6 to 2.45 with a median time to SM onset of 2.4–6.0 years post-TKI initiation. The most commonly reported SMs affected the gastrointestinal (GI), genitourinary (GU), and respiratory (RSP) systems. In the largest study (Sasaki et al., n=13,276; 597 SMs), GI, GU, and RSP cancers accounted for 21.6%, 31.2%, and 15.4% of SMs, respectively. Across studies, the most frequent tumor types were prostate (13.3%–21.6%), colorectal (6.1%–10.4%), and lung (9.0%–15.1%) cancers. Hematologic SMs, particularly non-Hodgkin lymphoma (NHL), were reported in 4%–16.5% of SM cases; Miranda et al. observed an elevated NHL risk (SIR 3.33 in men, 4.29 in women). Endocrine, skin, and breast cancers were also frequent, comprising 9%–47.5%of reported SMs. SM-related mortality ranged from 14% to 56%. The development of an SM was associated with a poor prognosis. No consistent association was found between TKI generation, treatment duration, or line of therapy and SM risk. Most studies did not report additional malignancy risk factors and were of moderate to high quality based on NOS, NIH, or Cochrane risk assessment tools. Conclusion: This review identified a notable incidence of SMs, particularly involving prostate, colorectal, lung, and lymphoid cancers. While some variability in cancer types was observed across studies, no consistent association could be established between TKI generation or treatment duration and SMs risk. SM development was associated with poor prognosis and increased mortality, highlighting the need for proactive surveillance. Large-scale prospective studies are needed to clarify causality, define long-term safety, and inform survivorship strategies.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,014
score de la tête « metaresearch » (Gemma)0,053
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,015
Score d'incertitude au seuil0,073

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0140,053
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0110,010
Bibliométrie0,0150,015
Études des sciences et des technologies0,0010,001
Communication savante0,0030,003
Science ouverte0,0020,002
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,251
Écart entre enseignants0,243 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueBloodMême sujetChronic Myeloid Leukemia TreatmentsTravaux en français237 207