Model‐informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records
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Wiley
2025
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| author | Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink |
| author_facet | Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink |
| collection | Wiley Open Access |
| contents | Model‐informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink British Journal of Clinical Pharmacology Abstract Aims This study aimed to develop and validate a population pharmacokinetic‐pharmacodynamic (pop‐PK‐PD) model to describe carboplatin‐induced myelosuppression in cancer patients and support dose individualization. Methods Data from 580 cancer patients treated with carboplatin at Amsterdam UMC between 2019 and 2022 were used for model development, focusing on lung, gynaecological and gastric/oesophageal cancers. Platelet (PLT) and neutrophil (NT) counts, along with patient‐specific covariates (e.g., age, serum albumin, eGFR), were extracted from Electronic Health Records and used in the analysis. Given the absence of pharmacokinetic (PK) samples, PK parameters were derived from a literature carboplatin pop‐PK model. Model applicability to inform personalized carboplatin dosing was evaluated on a separate cohort of 210 patients treated between 2022 and 2024 in the same centre. Results Two joint Friberg models effectively described carboplatin‐induced myelosuppression. Serum albumin, eGFR and paclitaxel and pemetrexed co‐medications were included in the final model. On the test cohort, >85% of NT and >87% of PLT observations fell within the 90% confidence interval of Bayesian model predictions, confirming that the model can support dose adjustments for subsequent treatment cycles. An example of model‐based dose adjustments is also presented with a simulation study. Conclusions The pop‐PK‐PD model demonstrated strong performance in describing and predicting carboplatin‐induced myelosuppression, thus providing a valuable strategy for dose personalization. Further refinements and validation steps are needed before integrating such an approach into clinical workflows. 10.1002/bcp.70413 http://creativecommons.org/licenses/by-nc/4.0/ |
| doi_str_mv | 10.1002/bcp.70413 |
| format | Artículo Open Access |
| id | wiley_oa_10_1002_bcp_70413 |
| institution | Wiley Open Access |
| license_str_mv | http://creativecommons.org/licenses/by-nc/4.0/ |
| publishDate | 2025 |
| publisher | Wiley |
| record_format | wiley_oa |
| spellingShingle | Model‐informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink British Journal of Clinical Pharmacology Model‐informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records Alessandro De Carlo Elena Maria Tosca Mirjam Crul Tim Schutte Lia van Zuijlen Idris Bahce Medhat M. Said Jan Buter Harmen Huls Paolo Magni Imke Bartelink British Journal of Clinical Pharmacology Abstract Aims This study aimed to develop and validate a population pharmacokinetic‐pharmacodynamic (pop‐PK‐PD) model to describe carboplatin‐induced myelosuppression in cancer patients and support dose individualization. Methods Data from 580 cancer patients treated with carboplatin at Amsterdam UMC between 2019 and 2022 were used for model development, focusing on lung, gynaecological and gastric/oesophageal cancers. Platelet (PLT) and neutrophil (NT) counts, along with patient‐specific covariates (e.g., age, serum albumin, eGFR), were extracted from Electronic Health Records and used in the analysis. Given the absence of pharmacokinetic (PK) samples, PK parameters were derived from a literature carboplatin pop‐PK model. Model applicability to inform personalized carboplatin dosing was evaluated on a separate cohort of 210 patients treated between 2022 and 2024 in the same centre. Results Two joint Friberg models effectively described carboplatin‐induced myelosuppression. Serum albumin, eGFR and paclitaxel and pemetrexed co‐medications were included in the final model. On the test cohort, >85% of NT and >87% of PLT observations fell within the 90% confidence interval of Bayesian model predictions, confirming that the model can support dose adjustments for subsequent treatment cycles. An example of model‐based dose adjustments is also presented with a simulation study. Conclusions The pop‐PK‐PD model demonstrated strong performance in describing and predicting carboplatin‐induced myelosuppression, thus providing a valuable strategy for dose personalization. Further refinements and validation steps are needed before integrating such an approach into clinical workflows. 10.1002/bcp.70413 http://creativecommons.org/licenses/by-nc/4.0/ |
| title | Model‐informed precision dosing of carboplatin in cancer patients by leveraging myelosuppression data from electronic health records |
| topic | British Journal of Clinical Pharmacology |
| url | https://bpspubs.onlinelibrary.wiley.com/doi/10.1002/bcp.70413 |