Accurate determination of glomerular filtration rate in adults for carboplatin dosing: Moving beyond Cockcroft and Gault
Bibliographic record
Abstract
OBJECTIVE: Carboplatin is a cytotoxic chemotherapy drug developed in the 1980s which is still widely used today across various tumour types. Despite its common application, there remains a significant controversy and practice variation on its unique method of dosing by area under the curve (AUC). One potential reason for this variability stems from the reliance of using an estimated glomerular filtration rate (eGFR) as an extrapolation of the measured GFR (mGFR) which the commonly used Calvert equation was originally validated for. This review takes a novel and collaborative nephro-oncology approach to highlight the historical evolution of carboplatin dosing, methods for estimating GFR and its relative performance in the application of carboplatin dosing for adult patients. DATA SOURCES: We reviewed all pertinent publications comparing carboplatin AUC-based dosing in adult patients based on the various methods of GFR measurements or estimations in order to provide a comprehensive description of each method's advantages and risks. DATA SUMMARY AND CONCLUSIONS: The Cockcroft-Gault equation has been widely studied but newer eGFR equations, such as the CKD-Epidemiology Collaboration (CKD-EPI) or Janowitz-Williams equation have outperformed the Cockcroft-Gault in recent studies.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".