Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients

Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxici...
Ausführliche Beschreibung

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Autor*in:	Kawakatsu, Sonoko [verfasserIn] Nikanjam, Mina Lin, Mark Le, Sonny Saunders, Ila Kuo, Dennis John Capparelli, Edmund V.

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Methotrexate Pediatric Population pharmacokinetic modeling Oncology

Anmerkung:	© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Übergeordnetes Werk:	Enthalten in: Cancer chemotherapy and pharmacology - Berlin : Springer, 1978, 84(2019), 6 vom: 04. Okt., Seite 1339-1348
Übergeordnetes Werk:	volume:84 ; year:2019 ; number:6 ; day:04 ; month:10 ; pages:1339-1348

Links:	Volltext

DOI / URN:	10.1007/s00280-019-03966-4

Katalog-ID:	SPR003622495

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245	1	0	\|a Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
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520			\|a Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity.
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700	1		\|a Kuo, Dennis John \|4 aut
700	1		\|a Capparelli, Edmund V. \|4 aut
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allfields	10.1007/s00280-019-03966-4 doi (DE-627)SPR003622495 (SPR)s00280-019-03966-4-e DE-627 ger DE-627 rakwb eng Kawakatsu, Sonoko verfasserin aut Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Nikanjam, Mina aut Lin, Mark aut Le, Sonny aut Saunders, Ila aut Kuo, Dennis John aut Capparelli, Edmund V. aut Enthalten in Cancer chemotherapy and pharmacology Berlin : Springer, 1978 84(2019), 6 vom: 04. Okt., Seite 1339-1348 (DE-627)253390435 (DE-600)1458488-8 1432-0843 nnns volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348 https://dx.doi.org/10.1007/s00280-019-03966-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 84 2019 6 04 10 1339-1348
spelling	10.1007/s00280-019-03966-4 doi (DE-627)SPR003622495 (SPR)s00280-019-03966-4-e DE-627 ger DE-627 rakwb eng Kawakatsu, Sonoko verfasserin aut Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Nikanjam, Mina aut Lin, Mark aut Le, Sonny aut Saunders, Ila aut Kuo, Dennis John aut Capparelli, Edmund V. aut Enthalten in Cancer chemotherapy and pharmacology Berlin : Springer, 1978 84(2019), 6 vom: 04. Okt., Seite 1339-1348 (DE-627)253390435 (DE-600)1458488-8 1432-0843 nnns volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348 https://dx.doi.org/10.1007/s00280-019-03966-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 84 2019 6 04 10 1339-1348
allfields_unstemmed	10.1007/s00280-019-03966-4 doi (DE-627)SPR003622495 (SPR)s00280-019-03966-4-e DE-627 ger DE-627 rakwb eng Kawakatsu, Sonoko verfasserin aut Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Nikanjam, Mina aut Lin, Mark aut Le, Sonny aut Saunders, Ila aut Kuo, Dennis John aut Capparelli, Edmund V. aut Enthalten in Cancer chemotherapy and pharmacology Berlin : Springer, 1978 84(2019), 6 vom: 04. Okt., Seite 1339-1348 (DE-627)253390435 (DE-600)1458488-8 1432-0843 nnns volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348 https://dx.doi.org/10.1007/s00280-019-03966-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 84 2019 6 04 10 1339-1348
allfieldsGer	10.1007/s00280-019-03966-4 doi (DE-627)SPR003622495 (SPR)s00280-019-03966-4-e DE-627 ger DE-627 rakwb eng Kawakatsu, Sonoko verfasserin aut Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Nikanjam, Mina aut Lin, Mark aut Le, Sonny aut Saunders, Ila aut Kuo, Dennis John aut Capparelli, Edmund V. aut Enthalten in Cancer chemotherapy and pharmacology Berlin : Springer, 1978 84(2019), 6 vom: 04. Okt., Seite 1339-1348 (DE-627)253390435 (DE-600)1458488-8 1432-0843 nnns volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348 https://dx.doi.org/10.1007/s00280-019-03966-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 84 2019 6 04 10 1339-1348
allfieldsSound	10.1007/s00280-019-03966-4 doi (DE-627)SPR003622495 (SPR)s00280-019-03966-4-e DE-627 ger DE-627 rakwb eng Kawakatsu, Sonoko verfasserin aut Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag GmbH Germany, part of Springer Nature 2019 Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213 Nikanjam, Mina aut Lin, Mark aut Le, Sonny aut Saunders, Ila aut Kuo, Dennis John aut Capparelli, Edmund V. aut Enthalten in Cancer chemotherapy and pharmacology Berlin : Springer, 1978 84(2019), 6 vom: 04. Okt., Seite 1339-1348 (DE-627)253390435 (DE-600)1458488-8 1432-0843 nnns volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348 https://dx.doi.org/10.1007/s00280-019-03966-4 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_267 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_711 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 84 2019 6 04 10 1339-1348
language	English
source	Enthalten in Cancer chemotherapy and pharmacology 84(2019), 6 vom: 04. Okt., Seite 1339-1348 volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348
sourceStr	Enthalten in Cancer chemotherapy and pharmacology 84(2019), 6 vom: 04. Okt., Seite 1339-1348 volume:84 year:2019 number:6 day:04 month:10 pages:1339-1348
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Methotrexate Pediatric Population pharmacokinetic modeling Oncology
isfreeaccess_bool	false
container_title	Cancer chemotherapy and pharmacology
authorswithroles_txt_mv	Kawakatsu, Sonoko @@aut@@ Nikanjam, Mina @@aut@@ Lin, Mark @@aut@@ Le, Sonny @@aut@@ Saunders, Ila @@aut@@ Kuo, Dennis John @@aut@@ Capparelli, Edmund V. @@aut@@
publishDateDaySort_date	2019-10-04T00:00:00Z
hierarchy_top_id	253390435
id	SPR003622495
language_de	englisch
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This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. 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author	Kawakatsu, Sonoko
spellingShingle	Kawakatsu, Sonoko misc Methotrexate misc Pediatric misc Population pharmacokinetic modeling misc Oncology Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
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topic_title	Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients Methotrexate (dpeaa)DE-He213 Pediatric (dpeaa)DE-He213 Population pharmacokinetic modeling (dpeaa)DE-He213 Oncology (dpeaa)DE-He213
topic	misc Methotrexate misc Pediatric misc Population pharmacokinetic modeling misc Oncology
topic_unstemmed	misc Methotrexate misc Pediatric misc Population pharmacokinetic modeling misc Oncology
topic_browse	misc Methotrexate misc Pediatric misc Population pharmacokinetic modeling misc Oncology
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title	Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
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title_full	Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
author_sort	Kawakatsu, Sonoko
journal	Cancer chemotherapy and pharmacology
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author_browse	Kawakatsu, Sonoko Nikanjam, Mina Lin, Mark Le, Sonny Saunders, Ila Kuo, Dennis John Capparelli, Edmund V.
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doi_str_mv	10.1007/s00280-019-03966-4
title_sort	population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
title_auth	Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
abstract	Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. © Springer-Verlag GmbH Germany, part of Springer Nature 2019
abstractGer	Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. © Springer-Verlag GmbH Germany, part of Springer Nature 2019
abstract_unstemmed	Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. The model allows for early identification of patients with slowed MTX clearance and at higher risk of toxicity. © Springer-Verlag GmbH Germany, part of Springer Nature 2019
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title_short	Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients
url	https://dx.doi.org/10.1007/s00280-019-03966-4
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author2	Nikanjam, Mina Lin, Mark Le, Sonny Saunders, Ila Kuo, Dennis John Capparelli, Edmund V.
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up_date	2024-07-03T20:43:41.107Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR003622495</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230520010723.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201001s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s00280-019-03966-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR003622495</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s00280-019-03966-4-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Kawakatsu, Sonoko</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag GmbH Germany, part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Purpose High-dose methotrexate (HD-MTX) is widely used in pediatric and adult oncology treatment regimens. This study aimed to develop a population pharmacokinetic model to characterize pediatric and adult MTX exposure across various disease types and dosing regimens, and to evaluate exposure–toxicity relationships. Methods MTX pharmacokinetic data from pediatric and adult patients were collected. A population pharmacokinetic model was developed to determine the effects of age, liver function, renal function, and demographics on MTX disposition. The final model was used in Monte Carlo simulations to generate expected exposures for different dosing regimens. The association of toxicity, determined through chart review, and MTX area under the curve (AUC) was modeled using logistic regression. Results The analysis included 5116 MTX concentrations from 320 patients (135 adult, age 19–79 years; 185 pediatric, age 0.6–19 years). Estimated glomerular filtration rate (eGFR) and treatment cycle number were independent predictors of clearance (CL). CL varied 2.1-fold over the range of study eGFR values and increased 14% for treatment cycle numbers greater than 7. Higher MTX AUC was associated with higher risk of nephrotoxicity in adults, and neurotoxicity and hepatotoxicity in pediatrics. Conclusions This study represents one of the most comprehensive evaluations of HD-MTX PK across a wide range of ages and disease types. After accounting for differences in renal function, age did not impact CL, although toxicity patterns differed by age. 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Population pharmacokinetic analysis of high-dose methotrexate in pediatric and adult oncology patients

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