Evidence map›Paper›PMID 38992166›Full record

ArticleCancer chemotherapy and pharmacology2024

A joint model of longitudinal pharmacokinetic and time-to-event data to study exposure-response relationships: a proof-of-concept study with alectinib.

Lishi Lin, Vincent van der Noort, Neeltje Steeghs, Gerrina Ruiter, Jos H Beijnen, Alwin D R Huitema

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Article in Cancer chemotherapy and pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Lishi LinDepartment of Pharmacy & Pharmacology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
Vincent van der NoortDepartment of Biometrics, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
Neeltje SteeghsDepartment of Medical Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
Gerrina RuiterDepartment of Thoracic Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands.
Jos H BeijnenDepartment of Pharmacy & Pharmacology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
Alwin D R HuitemaDepartment of Pharmacy & Pharmacology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. a.huitema@nki.nl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeIn exposure-response analyses of oral targeted anticancer agents, longitudinal plasma trough concentrations are often aggregated into a single value even though plasma trough concentrations can vary over time due to dose adaptations, for example. The aim of this study was to compare joint models to conventional exposure-response analyses methods with the application of alectinib as proof-of-concept.

methodsJoint models combine longitudinal pharmacokinetic data and progression-free survival data to infer the dependency and association between the two datatypes. The results from the best joint model and the standard and time-dependent cox proportional hazards models were compared. To normalize the data, alectinib trough concentrations were normalized using a sigmoidal transformation to transformed trough concentrations (TTC) before entering the models.

resultsNo statistically significant exposure-response relationship was observed in the different Cox models. In contrast, the joint model with the current value of TTC in combination with the average TTC over time did show an exposure-response relationship for alectinib. A one unit increase in the average TTC corresponded to an 11% reduction in progression (HR, 0.891; 95% confidence interval, 0.805-0.988).

conclusionJoint models are able to give insights in the association structure between plasma trough concentrations and survival outcomes that would otherwise not be possible using Cox models. Therefore, joint models should be used more often in exposure-response analyses of oral targeted anticancer agents.

Indexed as

CarbazolesPiperidinesAdministration, OralDose-Response Relationship, DrugFemaleHumansLongitudinal StudiesLung NeoplasmsMaleMiddle AgedModels, BiologicalProgression-Free SurvivalProof of Concept StudyProportional Hazards ModelsalectinibCarbazolesPiperidinesAlectinibExposure responseMixed effects modelsSurvival analysis

Identifiers

PMID38992166
PMCPMC11420381

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.