In:
Journal of Cancer Research and Clinical Oncology, Springer Science and Business Media LLC, Vol. 149, No. 10 ( 2023-08), p. 6989-6998
Kurzfassung:
Hematotoxicity is a common side-effect of cytotoxic gastrointestinal (GI) cancer therapies. An unsolved problem is to predict the individual risk therefore to decide on treatment adaptions. We applied an established biomathematical prediction model and primarily evaluated its predictive value in patients undergoing chemotherapy for GI cancers in curative intent. Methods In a prospective, observational multicenter study on patients with gastro-esophageal or pancreatic cancer ( n = 28) receiving myelosuppressive adjuvant or neoadjuvant chemotherapy (FLO(T) or FOLFIRINOX), individual model parameters were learned based on patients’ observed laboratory values during the first chemotherapy cycle and further external data resources. Grades of hematotoxicity of subsequent cycles were predicted by model simulation and compared with observed data. Results The most common high-grade hematological toxicity was neutropenia [19/28 patients (68%)]. For the FLO(T) regimen, individual grades of thrombocytopenia and leukopenia could be well predicted for cycles 2–4, as well as grades of neutropenia for cycle 2. Prediction accuracy for neutropenia in the third and fourth cycle differed by one toxicity grade on average. For the FOLFIRINOX-regimen, thrombocytopenia predictions showed a maximum deviation of one toxicity grade up to the end of therapy (8 cycles). Deviations of predictions were less than one degree on average up to cycle 4 for neutropenia, and up to cycle 6 for leukopenia. Conclusion The biomathematical model showed excellent short-term and decent long-term prediction performance for all relevant hematological side effects associated with FLO(T)/FOLFIRINOX. Clinical utility of this precision-medicine approach needs to be further investigated in a larger cohort.
Materialart:
Online-Ressource
ISSN:
0171-5216
,
1432-1335
DOI:
10.1007/s00432-023-04601-9
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2023
ZDB Id:
1459285-X
