Determining the Associations Between Glucocorticoid Use During Hematologic Chemotherapy Treatment and New-onset Diabetes and Hyperglycemia and Mortality: A Population-based Cohort Study
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine the associations between glucocorticoid administration during chemotherapy for hematologic malignancy and hyperglycemia, new-onset diabetes, and mortality in Ontario, Canada. Hospitalization and emergency room utilization during the chemotherapy treatment period were also described. METHODS: We conducted a retrospective cohort study using health administrative data from ICES, Ontario, to assess risk of new-onset diabetes, new-onset hyperglycemia, and hyperglycemia for individuals with leukemia, non-Hodgkin lymphoma (NHL), and Hodgkin lymphoma (HL) receiving glucocorticoids during chemotherapy between 2006 and 2016. Using multivariable regression models, we determined the associations between glucocorticoid exposure and our outcomes of interest, controlling for age, sex, marginalization, and comorbidities. RESULTS: Our cohort included 19,530 individuals; 71.1% (n=13,893) received a glucocorticoid. The highest proportion of hyperglycemia occurred with leukemia (25.4%, n=1,301). Of the 15,580 individuals with no history of diabetes, those with leukemia had the highest rate of new-onset diabetes (7.1%, n=279) and new-onset hyperglycemia (18.1%, n=641), and glucocorticoid exposure increased the risk of new-onset diabetes (hazard ratio [HR] 1.29, 95% confidence interval [CI] 1.01 to 1.64, p=0.04) and new-onset hyperglycemia (HR 1.28, 95% CI 1.09 to 1.5, p=0.003). Hyperglycemia during chemotherapy increased the risk of all-cause mortality for the combined (HR 1.18, 95% CI 1.09 to 1.27, p<0.0001) and NHL (HR 1.16, 95% CI 1.04 to 1.28, p=0.007) cohorts. CONCLUSIONS: Hyperglycemia is common during hematologic chemotherapy treatment and is associated with a modest increased risk of all-cause mortality. Routine screening, monitoring, and management of hyperglycemia should be an integral part of treatment plans for leukemia, NHL, or HL, with or without glucocorticoid administration.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".