CP-091 Dose adjustment in cancer patients with renal or hepatic impairment
Bibliographic record
Abstract
Background Treatment outcomes and tolerability are not easily predicted in cancer patients receiving chemotherapy, especially in those patients with renal or hepatic dysfunction, where dose modifications become necessary. Purpose To evaluate drug dose modifications made in cancer patients with renal and hepatic impairment receiving antineoplastic treatment. Material and methods A review of several dose modification protocols was previously made (Cancer Care Ontario, UpToDate and the EMA product information). A prospective, observational study was done (March 2014–June 2014). All adult cancer patients being treated with antineoplastic treatment (chemotherapy, hormonal or biological therapy) were included. Gender, age, tumour type, protocol, drugs given, dose, body surface area and liver (bilirubin and transaminases) and renal (creatinine clearance) function tests were recorded for each course of treatment. Prescribed dose and recommended dose modification according to protocols were also analysed. Results 370 patients were evaluated (51.6% male; mean age 65.2 years). 1.764 blood tests were reviewed. Liver and renal impairment was observed in 37.7% of blood tests (19% liver impairment only, 13% renal impairment only and 6% both). According to protocols, only 10.2% of these altered blood tests would make dose modifications necessary. But of these patients, the dose was modified in only 53.7% of the administrations and protocols dosage recommendations were followed in just 38.8% of these dose modifications. Conclusion The rate of protocol-guided dose modifications of antineoplastic treatment in patients with renal and hepatic impairment was low. A dose modifications protocol, based on published guidelines and agreed with the departments involved, should be implemented in all units administering treatment to cancer patients. Other considerations apart from laboratory tests, such as tolerability and tumour response, should be taken into account. References and/or Acknowledgements No conflict of interest.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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".