The Effect of Dexrazoxane on Myocardial Injury in Doxorubicin-Treated Children with Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
BACKGROUND: Doxorubicin chemotherapy is very effective in children with acute lymphoblastic leukemia (ALL) but also injures myocardial cells. Dexrazoxane, a free-radical scavenger, may protect the heart from doxorubicin-associated damage. METHODS: To determine whether dexrazoxane decreases doxorubicin-associated injury of cardiomyocytes, we randomly assigned 101 children with ALL to receive doxorubicin alone (30 mg per square meter of body-surface area every three weeks for 10 doses) and 105 to receive dexrazoxane (300 mg per square meter) followed immediately by doxorubicin. Serial measurements of serum cardiac troponin T were obtained in 76 of 101 patients in the doxorubicin group and 82 of 105 patients in the group given dexrazoxane and doxorubicin. A total of 2377 serum samples (mean, 15.1 samples per patient) were obtained before, during, and after treatment with doxorubicin. Troponin T levels were evaluated in a blinded fashion to determine whether they were elevated (>0.01 ng per milliliter)--the primary end point--or extremely elevated (>0.025 ng per milliliter). RESULTS: Elevations of troponin T occurred in 35 percent of the patients (55 of 158). Patients treated with doxorubicin alone were more likely than those who received dexrazoxane and doxorubicin to have elevated troponin T levels (50 percent vs. 21 percent, P<0.001) and extremely elevated troponin T levels (32 percent vs. 10 percent, P<0.001). The median follow-up was 2.7 years. The rate of event-free survival at 2.5 years was 83 percent in both groups (P=0.87 by the log-rank test). CONCLUSIONS: Dexrazoxane prevents or reduces cardiac injury, as reflected by elevations in troponin T, that is associated with the use of doxorubicin for childhood ALL without compromising the antileukemic efficacy of doxorubicin. Longer follow-up will be necessary to determine the influence of dexrazoxane on echocardiographic findings at four years and on event-free survival.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".