Pediatric inspired (BFM) protocol in adolescent and young adults (AYA) with acute lymphoblastic leukemia (ALL) in India: Real‑world treatment timelines and impact of delays on survival
Abstract
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.
Article Details
Authors (34)
Chepsy Philip
1Believers Church Medical College Hospital, Thiruvalla, India
Hasmukh Jain
11Hematolymphoid Unit, Department of Medical Oncology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, India
Prasanth Ganesan
Department of Medicine (R.A.A., S.B., K.A.B., X.L., P.G., A.C.P., E.A.A., P.J.W., M.V.P., S.M.N., A.J.R.), Stanford University, CA.
Alok Shetty
32Tata Memorial Centre, Mumbai, India
Alka Khadwal
2PGIMER, Chandigarh, India
Parathan Karunakaran
5Cancer Institute (WIA) Adyar, Chennai, India
Smitha Saldanha
6Kidwai Memorial Institute of Oncology, Bengaluru, India
Sushil Selvarajan
7Christian Medical College, Vellore, India
Jina Bhattacharyya
Prasanna Samuel
Thejeswar N
10Nizam's Institute of Medical Sciences, Telengana, India
Abhilash Menon
11Malabar Cancer Centre, Thalassery, India
Sharat Damodar
2Mazumdar Shaw Medical Centre, Narayana Health City, Bengaluru, India
Sanjeevan Sharma
1Army Hospital (Research & Referral), Delhi, India
Chirag Trivedi
14Christian Medical College, Ludhiana, India
Priyanka Samal
Sreeraj Vasudevan
8Amala Institute of Medical Sciences, Department of Clinical Hematology, Thrissur, India
Rasmi Palassery
17Ramaiah Medical College, Bengaluru, India
Reshma Roshan
18Sher-e-Kashmir Institute of Medical Sciences, Srinagar, India
Sandeep Nemani
19Shri Siddhivinayak Ganapati Cancer Hospital, Miraj, India
Punit Jain
20Apollo Hospital, Mumbai, India
Omprakash Karunamurthy
3Christian Medical College, Department of Haematology, Vellore, India
Jansi Rani
9Christian Medical College - Clinical Data Management Centre, Vellore, India
Gayathri S
21Amrita Institute of Medical Sciences, Ernakulam, India
Minu Luckose
1Believers Church Medical College Hospital, Thiruvalla, India
Asif Iqbal
22Dr. Bhubaneswar Borooah Cancer Institute, Guwahati, India
Esha Kaul
23Max Super Specialty Hospital, Delhi, India
Rohan Halder
1Rajiv Gandhi Cancer Institute and Research Centre, Delhi, India
Prashant Parameswaran
6MVR Cancer Centre and Research Institute (MVRCCRI), Calicut, India
Smita Kayal
3Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherrry, India
Lingaraj Nayak
2Tata Memorial Centre, Department of Medical Oncology, Mumbai, India
Bhausaheb Bagal
2Tata Memorial Centre, Department of Medical Oncology, Mumbai, India
Vikram Mathews
Manju Sengar
32Tata Memorial Centre, Mumbai, India