Management of chronic myeloid leukaemia (CML) during pregnancy: A systematic review of maternal and foetal outcomes
Bibliographic record
Abstract
Abstract Introduction The introduction of tyrosine kinase inhibitors (TKIs) has transformed the treatment of Chronic Myeloid leukaemia (CML), markedly improving prognosis and long-term outcomes. However, their use during pregnancy presents a complex clinical challenge due to concerns regarding teratogenicity and the absence of standardised treatment protocols. Despite advances in novel therapeutics, pregnancy is generally excluded from clinical trials, resulting in a substantial gap in high-quality, prospective data to guide clinical decision-making. The existing literature predominantly consists of retrospective case series and small observational cohorts, with limited information on novel agents, inconsistent reporting and variable follow-up. This heterogeneity limits the ability to draw robust, generalizable conclusions. Consequently, patients and clinicians often face difficult choices without an evidence-based consensus, balancing the risk of maternal disease progression against fetal harm. Given these uncertainties, a comprehensive, evidence-based synthesis of maternal and fetal outcomes across treatment strategies is urgently needed. This systematic review aims to address this gap by critically appraising and synthesising available evidence on the management of CML during pregnancy, to evaluate the effectiveness and safety of different therapeutic approaches on both maternal disease control and fetal development. Methods Following PRISMA guidelines, 96 studies from 24 countries were included from 2001 (introduction of TKIs) to 2025. These studies comprised observational cohorts and case series reporting maternal and fetal outcomes in CML pregnancies. Study quality was rated with the Newcastle-Ottawa and JBI scales. Therapies applied included TKIs, interferon-alpha (IFN-α), hydroxyurea (HU), leukapheresis, and watchful waiting. Treatment strategies evaluated independently were IFN-α (n=34), HU (n=10), and leukapheresis (n=9). In women taking TKIs, the strategies evaluated were first-trimester TKI exposure (n=267), watchful waiting after TKI cessation at conception (n=117), and TKI restarted in the second or third trimester (n=37). Primary outcomes were live births, congenital abnormalities, maternal hematologic (CHR), cytogenetic (CCyR), and molecular (MMR/CMR) responses. Results A total of 535 pregnancies were analysed. Of these, 267 pregnancies involved TKI exposure during the first trimester, predominantly imatinib (n=251), followed by dasatinib (n=9), nilotinib (n=4), bosutinib (n=2) and one with unspecified TKI exposure (n=1). Among first-trimester exposures with known outcomes (n=232), 195 live births (84.1%) occurred, with 26 preterm births and 37 miscarriages (14 elective, 23 spontaneous). Congenital abnormalities were reported in 20 cases (8.6%), most commonly cardiac, renal, skeletal and CNS anomalies, which is above the general population rate of 3-6%. In the watchful waiting group (n=117), where TKIs were stopped pre-conception or upon pregnancy confirmation, 116 live births were recorded (99.1%), with only 1 miscarriage and no congenital anomalies. However, molecular relapse occurred in 46% of cases, with MMR regaining postpartum within 3 months in most, and 13 patients achieving sustained treatment-free remission. INF-a therapy (n=34) resulted in 34 live births and a 79% CHR rate at delivery. HU therapy (n=10) resulted in 9 live births, one miscarriage and no reported abnormalities. Leukapheresis alone was utilised in 9 pregnancies with no adverse fetal outcomes. TKIs restarted in the 2nd or 3rd trimester (n=36), led to 36 live births. Significant molecular recovery was observed, with 23 achieving MMR and 7 achieving CMR postpartum. Conclusion Optimal outcomes in CML-affected pregnancies are closely linked to preconception planning, achievement of deep molecular remission and early TKI discontinuation. First-trimester TKI exposure poses quantifiable teratogenic risk. IFN-α has emerged as a safe and effective bridging therapy throughout pregnancy. However, data remains limited regarding the safety of newer generation TKIs, emerging therapies, and the impact of TKI re-initiation in later trimesters. These gaps highlight the urgent need for further research. Collectively, these findings reinforce the importance of a risk-adapted, individualised management strategy and emphasise the critical role of proactive pre-pregnancy counselling in women with CML.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".