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Re-Induction Outcome for Pediatric Patients with Relapsed or Refractory B-Cell Precursor Acute Lymphoblastic Leukemia: A Retrospective Cohort Study of the Therapeutic Advances in Childhood Leukemia Consortium

2015· article· en· W2577204667 on OpenAlexaff
Weili Sun, Jemily Malvar, Richard Sposto, Anupam Verma, Jennifer J. Wilkes, Robyn M. Dennis, Kenneth Heym, Elena Eckroth, Jeannette Vandergiesse, Paul S. Gaynon, Alan S. Wayne, James A. Whitlock

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineInternal medicineRetrospective cohort studyCohortClinical endpointHematopoietic stem cell transplantationTransplantationClinical trialOncologyPediatrics

Abstract

fetched live from OpenAlex

Abstract Introduction Remission induction rates after a second or greater relapse is a critical endpoint in phase II trials of childhood acute lymphoblastic leukemia (ALL). A robust benchmark is crucial for identification of novel multi-agent regimens worthy of further study. The Therapeutic Advances in Childhood Leukemia and Lymphoma (TACL) consortium previously reported the response rates of children with multiply relapsed and refractory (R/R) ALL treated between 1995 and 2004, which provided a benchmark for clinical trials. To define more recent treatment patterns and test the robustness of this benchmark, we performed a retrospective cohort review of children with R/R ALL who experienced second or greater treatment failure at TACL consortium sites between 2005 and 2013. Patients and Methods Eligible patients were identified at participating TACL institutions. This cohort was comprised of patients with medullary R/R B-cell precursor ALL who experienced at least 2 treatment failures or relapsed after hematopoietic stem cell transplant. Patient demographic data and details of the initial and R/R disease characteristics were abstracted from medical records and entered into a central database. This study was approved by the IRB of each participating institution. Treatment failure was defined by the presence or re-emergence of circulating blasts, M2/M3 BM, or extramedullary (EM) disease despite therapy. Complete remission (CR) was defined as M1 marrow, no EM disease and evidence of peripheral count recovery. For the purpose of statistical analysis, patients who met these criteria without platelet recovery (CRp) or normal blood count recovery (CRi) were included as CR. Univariate and multivariate logistic regression were utilized to evaluate the risk of re-induction failure. Predictors included in this preliminary analysis were NCI risk criteria at diagnosis, duration of the prior remission, the treatment attempt number, and the EM and BM status at the start of each therapy attempt. Results This report includes 214 patients. Fifty-six percent were male. At initial diagnosis, 32% were at least 10 years old, 26% had initial white blood cell (WBC) counts over 50,000/µL, and 39% were classified as high risk by the NCI risk criteria (Table 1). Therapy involved various combinations of agents and ranged between 2 and 10 attempts. The CR rate was 42% for third treatment attempt and 24% for fourth and subsequent treatment attempts (Table 2). Treatment failures were significantly associated with increased number of treatment attempts (p < 0.001), shorter duration of previous CR (p < 0.001) and NCI risk category at diagnosis (p = 0.018). Conclusion This preliminary analysis found similar CR rates in patients with third treatment failure compared to the 1st TACL retrospective study of the prior decade (42% vs. 44%, Ko et al, 2010) and an Austrian report with a small cohort of patients (Reismüller et al, 2013). Further analysis will be performed in comparison to the initial TACL retrospective study cohort once enrollment to this study has been completed (approximately 400 patients). A robust, contemporary historical control may serve as an alternative to a randomized control when outcome with past therapies in unacceptably poor. Table 1. Patient Characteristics at Initial Diagnosis of Patients with ALL who received at least two treatment attempt (n = 214 patients) Characteristic No of patients % Age, years < 1 (infants) 18 8 1-9 126 59 10 and over 70 33 WBC count/uL < 50K 128 60 50K and over 56 26 Unknown 30 14 NCI risk criteria at diagnosis Non-infants, standard risk 82 38 Non-infants, high risk 84 39 Non-infants, unknown 30 14 Infants 18 8 Sex Female 94 44 Male 120 56 CNS disease Yes 42 20 No 148 69 Unknown 24 11 Karyotype1 Normal 68 30 11q23 (MLL gene) rearranged 19 8 Hypodiploidy 7 3 Hyperdiploidy 26 12 iAMP21 2 1 t(12;21) 6 3 t(1;19) 7 3 t(9;22) 15 7 Other 46 21 Unknown 28 12 1 Karyotype is available for 214 unique patients; 2 entries were reported for 7 patients, and 4 entries were reported for 1 patient. Table 2. Achievement of CR/CRp/CRi After Treatment of R/R ALL by Preceding Remission Duration and Treatment Attempt Third treatment attempt Fourth through tenth treatment attempt Duration of preceding CR Response Total % Response Total % Not achieved (refractory) 24 63 38 20 86 23 < 18 months duration 28 78 36 11 49 22 18 to 36 months duration 9 15 60 3 5 60 ≥ 36 months duration 8 8 100 0 1 0 All patients combined 69 164 42 34 141 24 Disclosures Sun: Gateway for Cancer Researchy: Research Funding; Amgen: Research Funding. Wilkes:Healthcare Research and Quality: Research Funding; Alex's Lemonade Stand Foundation: Research Funding. Gaynon:Bristol Meyers Squibb: Membership on an entity's Board of Directors or advisory committees; Sigma Tau: Speakers Bureau; JAZZ: Speakers Bureau. Wayne:Medimmune: Honoraria, Other: travel support, Research Funding; NIH: Patents & Royalties; Kite Pharma: Honoraria, Other: travel support; Pfizer: Honoraria; Spectrum Pharmaceuticals: Honoraria, Other: travel support, Research Funding. Whitlock:Amgen: Honoraria.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.276
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations3
Published2015
Admission routes1
Has abstractyes

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