Impact of weight and creatinine measurements in carboplatin dosing.
Bibliographic record
Abstract
e13027 Background: Controversy surrounding weight in Carboplatin dosing is still current. Also, new methods of measuring serum creatinine have raised more questions regarding the precision of Carboplatin dose calculations. The two objectives of this study were to evaluate the impact of alternative weight indicators (actual and adjusted body weight) in the Cockcroft–Gault equation and the use of different creatinine measurements (standard and IDMS) in order to accurately predict Carboplatin dose. Methods: We performed a retrospective chart review on all patients who received at least one dose of Carboplatin between March 7 th and May 8 th 2010. The patients were divided into two groups according to their body mass index (BMI): 20 < BMI < 27 and BMI ≥ 27. The differential creatinine clearance and Carboplatin dose were assessed in each group using the actual body weight and the adjusted body weight with IDMS creatinine. Moreover, for patients who had their creatinine measurement at the CHUM hospital, we calculate the difference in Carboplatin dose by using the standard creatinine (SC) measurement and IDMS creatinine with the same weight. Results: A total of 95 patients, representing 119 Carboplatin doses, were included in the analysis. 82% were women and median age was 63. The average BMI was 26,6. The Carboplatin expected AUC was 5 for 89% of patients and Carboplatin was associated to Paclitaxel in 78% of patients. In patients with a 20<BMI< 27 (44%), the average difference between the calculated dose using their actual body weight and adjusted body weight was +6.03% (95% CI, 5.2 to 6.9%). For patients with a BMI ≥ 27 (43%), the mean dose difference was +20.6% (95% CI, 18.8 to 22.5%). The use of SC or IDMS creatinine led to a discrepancy in doses of 5.2% (95% CI, 4.7 to 5.7%) for patients with BMI <27 (35 patients) and 5.5% (95% CI, 4.9 to 6.2%) for those with BMI ≥ 27 (23 patients). Conclusions: Based on these findings, we decide in our clinic, to use the actual body weight for patients with a BMI between 20 and 27, and the adjusted body weight for those with a BMI ≥ 27. We also chose not to modify our doses based on the type of the serum creatinine measurement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".