Abstract Pediatric-inspired regimens have improved outcomes in adolescents and young adults (AYA) with acute lymphoblastic leukemia (ALL). Their intensity and duration increase toxicity, often leading to phase delays and interruptions that compound the recognized challenges of non-adherence and abandonment in AYA (Ganesan P et al. BJH 2021). Given the evidence in children that delays in treatment impact outcomes; such interruptions and delay are a cause of concern.Using the prospectively maintained Indian Acute Leukemia research database INwARD registry established in 2018 by the Hematology Cancer Consortium (HCC), we explored the treatment timelines and phase completion durations among AYA-ALL treated using the pediatric-inspired (BFM) protocol in our population. The primary objective was to determine the effect of treatment delays on event-free survival in 15–40-year-old ALL patients treated on a BFM protocol, with a secondary aim to describe real-world treatment timelines for the different phases of treatment. Registry data (1st January 2018 through 29th February 2024) for AYA ALL collected from 24 member institutions in the INwARD registry was analyzed for presenting characteristics, treatment and survival outcomes. The optimal cutoff values for treatment phase delays based on survival analysis were determined using X-tile 3.6.1 software (Yale University,USA) (Camp R L et al, CCR 2004). X-tile identified the optimal division (in days) of the entire cohort into 2 groups across four phases- Phase A: Diagnosis to start of treatment (4 d), Phase B: Start of Induction to end of induction (45 d), Phase C: End of Induction to start of Maintenance (187 d), and phase D: start of Maintenance through completion (754 d). Survival and follow-up data were analyzed as on 31st May 2025, calculated using the Kaplan-Meier method assessed by log rank tests. A total of 2002 patients, were registered Males: 1449(72.4%), Median age: 22 years (15-40), B -ALL: 1326(66.4%), T-ALL: 547 (27.4%); Ph + :274 (20.6%); MRD positive (end of induction) :493 (24.6%). The median (Q1, Q3) durations of the treatment phases were Phase A n=2002 - 3 days (0, 7), Phase B n=1508 - 40 days (36, 45), Phase C n=941 - 167 days (150, 189), and Phase D n=451 - 731 days (698, 752). During a median follow up of 28.8 months,398 (19.8%) patients had relapsed, 72(3.5%) had refractory disease, and 478(23.8%) died (69 deaths in CR). The 5-year EFS and OS probabilities were 50.47% and 65.23% respectively. The X-tile derived divisions for Phase A (≤4 days vs. 4 days; events: 445 vs 275, p-0.028) and Phase B (≤45 days vs. 45 days; events: 370 vs 127, p-0.0331) showed statistically significant differences in event free survival. Baseline characteristics (age, immunophenotype, gender, WBC counts, conventional karyotype, FISH, ploidy, BCR-ABL status, and MRD (end of induction) were largely comparable: though patients with Delay A 4 days were slightly older (24.6 vs 23.7 years; p=0.016) with a different CNS distribution (p=0.028), and we noted a higher frequency of abnormal conventional karyotype in the Delay B 45-day group (53.6% vs 39.6%; p=0.006). In contrast, comparison of EFS across division in Phase C at ≤187 days vs. 187 days, events: 152 vs 57, p-0.967), and Phase D at ≤754days vs. 754, events: 27 vs 9, p-0.767), were not significant. On univariable Cox analysis, inferior EFS was associated with older age, CNS-3 status, hypodiploidy, and treatment delays (Delay A 4 days; Delay B 45 days). In the multivariable model, Delay B 45 days remained independently associated with worse EFS (aHR 1.36; 95% CI, 1.04–1.78). In conclusion, treatment delays influence outcomes in AYA ALL. In our cohort, most relapses and deaths occurred early; the infrequency of late events likely reflects the overall short median follow-up, limiting our ability to detect differences in later phases. Additional caveats include heterogeneity in centre level practices, supportive care, and protocol adherence among the inherent limitations of registry analyses. Even so, we report one of the largest real-world analyses describing treatment timelines , quantifying phase-specific delays in BFM-treated AYA ALL and their association with survival. Our data identify potential benchmarks: initiating treatment within 4 days of diagnosis and completing induction within 45 days. These early time targets may help optimize improvement in survival, particularly in resource-limited settings.
Shetty et al. (Mon,) studied this question.