Children's Oncology Group Trial AALL1231: A Phase III Clinical Trial Testing Bortezomib in Newly Diagnosed T-Cell Acute Lymphoblastic Leukemia and Lymphoma.

2022

JCO2102678

2022 Mar 10

1527-7755

<p><strong>PURPOSE: </strong>To improve the outcomes of patients with T-cell acute lymphoblastic leukemia (T-ALL) and lymphoblastic lymphoma (T-LL), the proteasome inhibitor bortezomib was examined in the Children's Oncology Group phase III clinical trial AALL1231, which also attempted to reduce the use of prophylactic cranial radiation (CRT) in newly diagnosed T-ALL.</p>

<p><strong>PATIENTS AND METHODS: </strong>Children and young adults with T-ALL/T-LL were randomly assigned to a modified augmented Berlin-Frankfurt-Münster chemotherapy regimen with/without bortezomib during induction and delayed intensification. Multiple modifications were made to the augmented Berlin-Frankfurt-Münster backbone used in the predecessor trial, AALL0434, including using dexamethasone instead of prednisone and adding two extra doses of pegaspargase in an attempt to eliminate CRT in most patients.</p>

<p><strong>RESULTS: </strong>AALL1231 accrued 824 eligible and evaluable patients from 2014 to 2017. The 4-year event-free survival (EFS) and overall survival (OS) for arm A (no bortezomib) versus arm B (bortezomib) were 80.1% ± 2.3% versus 83.8% ± 2.1% (EFS, = .131) and 85.7% ± 2.0% versus 88.3% ± 1.8% (OS, = .085). Patients with T-LL had improved EFS and OS with bortezomib: 4-year EFS (76.5% ± 5.1% 86.4% ± 4.0%; = .041); and 4-year OS (78.3% ± 4.9% 89.5% ± 3.6%; = .009). No excess toxicity was seen with bortezomib. In AALL0434, 90.8% of patients with T-ALL received CRT. In AALL1231, 9.5% of patients were scheduled to receive CRT. Evaluation of comparable AALL0434 patients who received CRT and AALL1231 patients who did not receive CRT demonstrated no statistical differences in EFS ( = .412) and OS ( = .600).</p>

<p><strong>CONCLUSION: </strong>Patients with T-LL had significantly improved EFS and OS with bortezomib on the AALL1231 backbone. Systemic therapy intensification allowed elimination of CRT in more than 90% of patients with T-ALL without excess relapse.</p>

10.1200/JCO.21.02678

J Clin Oncol

35271306

Multisite external validation of a risk prediction model for the diagnosis of blood stream infections in febrile pediatric oncology patients without severe neutropenia.

2017

2017 May 23

1097-0142

<p><strong>BACKGROUND: </strong>Pediatric oncology patients are at an increased risk of invasive bacterial infection due to immunosuppression. The risk of such infection in the absence of severe neutropenia (absolute neutrophil count ≥ 500/μL) is not well established and a validated prediction model for blood stream infection (BSI) risk offers clinical usefulness.</p>

<p><strong>METHODS: </strong>A 6-site retrospective external validation was conducted using a previously published risk prediction model for BSI in febrile pediatric oncology patients without severe neutropenia: the Esbenshade/Vanderbilt (EsVan) model. A reduced model (EsVan2) excluding 2 less clinically reliable variables also was created using the initial EsVan model derivative cohort, and was validated using all 5 external validation cohorts. One data set was used only in sensitivity analyses due to missing some variables.</p>

<p><strong>RESULTS: </strong>From the 5 primary data sets, there were a total of 1197 febrile episodes and 76 episodes of bacteremia. The overall C statistic for predicting bacteremia was 0.695, with a calibration slope of 0.50 for the original model and a calibration slope of 1.0 when recalibration was applied to the model. The model performed better in predicting high-risk bacteremia (gram-negative or Staphylococcus aureus infection) versus BSI alone, with a C statistic of 0.801 and a calibration slope of 0.65. The EsVan2 model outperformed the EsVan model across data sets with a C statistic of 0.733 for predicting BSI and a C statistic of 0.841 for high-risk BSI.</p>

<p><strong>CONCLUSIONS: </strong>The results of this external validation demonstrated that the EsVan and EsVan2 models are able to predict BSI across multiple performance sites and, once validated and implemented prospectively, could assist in decision making in clinical practice. Cancer 2017. © 2017 American Cancer Society.</p>

10.1002/cncr.30792

Cancer

28542918