Background
Recent studies show that using a combination of blinatumomab and a BCR::ABL1 tyrosine kinase inhibitor is very effective for treating patients with Philadelphia chromosome-positive acute lymphoblastic leukemia (Ph + ALL) without chemotherapy. However, we still do not fully understand the factors that may lead to a relapse in these patients.
Methods
We conducted a phase II clinical trial with 76 newly diagnosed Ph + ALL patients. Each patient received 12-15 doses of intrathecal chemotherapy to prevent central nervous system (CNS) involvement. We studied how and when relapses occurred and identified clinical and molecular factors that may predict these relapses.
Results
After following the patients for an average of 29 months:
- The estimated 3-year event-free survival rate was 78%.
- The estimated 3-year overall survival rate was 88%.
- 13% of patients relapsed, typically around 18 months after starting treatment.
- Most relapses (6 out of 10) happened in extramedullary sites such as the CNS, peritoneum, and lymph nodes.
- All patients who relapsed still showed high levels of CD19 expression.
Factors linked to a higher chance of relapse included:
- White blood cell (WBC) count of 70 or more at diagnosis (higher risk).
- CNS involvement at diagnosis.
- VPREB1 deletion.
A high WBC count was particularly concerning, as 22% of patients had this level and experienced a 53% chance of relapse, compared to only 6% for those with lower counts. On deeper analysis, only high WBC count at diagnosis was significantly linked to relapse risk.
Conclusions
A WBC count of 70 or above at diagnosis is a major risk factor for relapse in patients treated with blinatumomab and ponatinib. This finding suggests that we may need to explore different treatment options for these high-risk patients to improve their long-term outcomes.
Opportunities for Improvement
Based on the trial data, here are some practical steps clinics and patients can take:
- Define Measurable Outcomes: Set clear goals for monitoring the molecular characteristics and predictors of relapse in Ph + ALL patients.
- Select Appropriate AI Tools: Choose AI solutions that fit specific clinical needs, aiming to improve patient outcomes.
- Implement Step-by-Step Strategies: Start with pilot projects and track results over time to see the real-world impact of these solutions.
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