Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
Link to record
Permanent link

Direct link
Alternative names
Publications (10 of 382) Show all publications
Arrington, L. & Karlsson, M. (2024). Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models. AAPS Journal, 26, Article ID 21.
Open this publication in new window or tab >>Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models
2024 (English)In: AAPS Journal, E-ISSN 1550-7416, Vol. 26, article id 21Article in journal (Refereed) Published
Abstract [en]

There are examples in the literature demonstrating different approaches to defining the item characteristic functions (ICF) and characterizing the latent variable time-course within a pharmacometrics item response theory (IRT) framework. One such method estimates both the ICF and latent variable time-course simultaneously, and another method establishes the ICF first then models the latent variable directly. To date, a direct comparison of the "simultaneous" and "sequential" methodologies described in this work has not yet been systematically investigated. Item parameters from a graded response IRT model developed from Parkinson's Progression Marker Initiative (PPMI) study data were used as simulation parameters. Each method was evaluated under the following conditions: (i) with and without drug effect and (ii) slow progression rate with smaller sample size and rapid progression rate with larger sample size. Overall, the methods performed similarly, with low bias and good precision for key parameters and hypothesis testing for drug effect. The ICF parameters were well determined when the model was correctly specified, with an increase in precision in the scenario with rapid progression. In terms of drug effect, both methods had large estimation bias for the slow progression rate; however, this bias can be considered small relative to overall progression rate. Both methods demonstrated type 1 error control and similar discrimination between model with and without drug effect. The simultaneous method was slightly more precise than the sequential method while the sequential method was more robust towards longitudinal model misspecification and offers practical advantages in model building.

Place, publisher, year, edition, pages
Springer, 2024
Keywords
Estimation methods, Item characteristic function, Item response theory, Pharmacometrics
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-522883 (URN)10.1208/s12248-023-00883-6 (DOI)001148749300001 ()38273096 (PubMedID)
Funder
Swedish Research Council, 2018-03317Uppsala University
Available from: 2024-02-12 Created: 2024-02-12 Last updated: 2024-02-12Bibliographically approved
Swen, J., van der Wouden, C. H., Manson, L. E. N., Abdullah-Koolmees, H., Blagec, K., Blagus, T., . . . Guchelaar, H.-J. (2023). A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study. The Lancet, 401(10374), 347-356
Open this publication in new window or tab >>A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study
Show others...
2023 (English)In: The Lancet, ISSN 0140-6736, E-ISSN 1474-547X, Vol. 401, no 10374, p. 347-356Article in journal (Refereed) Published
Abstract [en]

Background: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed.

Methods: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants.

Findings: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51.4 % female, 48.6% male; 97.7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1.6%] of the study group and 47 [1.3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11.0%] in the study group and 285 [7.9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21 center dot 0%) of 725 patients in the study group and 231 (27.7%) of 833 patients in the control group (odds ratio [OR] 0 center dot 70 [95% CI 0 center dot 54-0 center dot 91]; p=0.0075), whereas for all patients, the incidence was 628 (21.5%) of 2923 patients in the study group and 934 (28. 6%) of 3270 patients in the control group (OR 0.70 [95% CI 0.61-0.79]; p <0.0001).

Interpretation: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe.

Place, publisher, year, edition, pages
Elsevier, 2023
National Category
Pharmacology and Toxicology
Identifiers
urn:nbn:se:uu:diva-501626 (URN)10.1016/S0140-6736(22)01841-4 (DOI)000970309800001 ()36739136 (PubMedID)
Funder
EU, Horizon 2020, 668353
Available from: 2023-05-10 Created: 2023-05-10 Last updated: 2023-05-10Bibliographically approved
Liu, H., Milenković‐Grišić, A., Krishnan, S. M., Jönsson, S., Friberg, L. E., Girard, P., . . . Karlsson, M. O. (2023). A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer. CPT: Pharmacometrics and Systems Pharmacology (PSP), 12(11), 1738-1750
Open this publication in new window or tab >>A multistate modeling and simulation framework to learn dose-response of oncology drugs: Application to bintrafusp alfa in non‐small cell lung cancer
Show others...
2023 (English)In: CPT: Pharmacometrics and Systems Pharmacology (PSP), E-ISSN 2163-8306, Vol. 12, no 11, p. 1738-1750Article in journal (Refereed) Published
Abstract [en]

The dose/exposure-efficacy analyses are often conducted separately for oncology end points like best overall response, progression-free survival (PFS) and overall survival (OS). Multistate models offer to bridge these dose-end point relationships by describing transitions and transition times from enrollment to response, progression, and death, and evaluating transition-specific dose effects. This study aims to apply the multistate pharmacometric modeling and simulation framework in a dose optimization setting of bintrafusp alfa, a fusion protein targeting TGF-β and PD-L1. A multistate model with six states (stable disease [SD], response, progression, unknown, dropout, and death) was developed to describe the totality of endpoints data (time to response, PFS, and OS) of 80 patients with non-small cell lung cancer receiving 500 or 1200 mg of bintrafusp alfa. Besides dose, evaluated predictor of transitions include time, demographics, premedication, disease factors, individual clearance derived from a pharmacokinetic model, and tumor dynamic metrics observed or derived from tumor size model. We found that probabilities of progression and death upon progression decreased over time since enrollment. Patients with metastasis at baseline had a higher probability to progress than patients without metastasis had. Despite dose failed to be statistically significant for any individual transition, the combined effect quantified through a model with dose-specific transition estimates was still informative. Simulations predicted a 69.2% probability of at least 1 month longer, and, 55.6% probability of at least 2-months longer median OS from the 1200 mg compared to the 500 mg dose, supporting the selection of 1200 mg for future studies.

Place, publisher, year, edition, pages
John Wiley & Sons, 2023
National Category
Cancer and Oncology Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy; Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-526750 (URN)10.1002/psp4.12976 (DOI)000986525800001 ()37165943 (PubMedID)
Funder
Swedish Cancer Society, 20 1226 PjF
Note

De två sista författarna delar sistaförfattarskapet

Available from: 2024-04-17 Created: 2024-04-17 Last updated: 2024-04-18Bibliographically approved
Ibrahim, E., Karlsson, M. & Friberg, L. (2023). Assessment of ibrutinib scheduling on leukocyte, lymph node size and blood pressure dynamics in chronic lymphocytic leukemia through pharmacokinetic-pharmacodynamic models. CPT: Pharmacometrics and Systems Pharmacology (PSP), 12(9), 1305-1318
Open this publication in new window or tab >>Assessment of ibrutinib scheduling on leukocyte, lymph node size and blood pressure dynamics in chronic lymphocytic leukemia through pharmacokinetic-pharmacodynamic models
2023 (English)In: CPT: Pharmacometrics and Systems Pharmacology (PSP), E-ISSN 2163-8306, Vol. 12, no 9, p. 1305-1318Article in journal (Refereed) Published
Abstract [en]

Ibrutinib is a Bruton tyrosine kinase (Btk) inhibitor for treating chronic lymphocytic leukemia (CLL). It has also been associated with hypertension. The optimal dosing schedule for mitigating this adverse effect is currently under discussion. A quantification of relationships between systemic ibrutinib exposure and efficacy (i.e., leukocyte count and sum of the product of perpendicular diameters [SPD] of lymph nodes) and hypertension toxicity (i.e., blood pressure), and their association with overall survival is needed. Here, we present a semi-mechanistic pharmacokinetic-pharmacodynamic modeling framework to characterize such relationships and facilitate dose optimization. Data from a phase Ib/II study were used, including ibrutinib plasma concentrations to derive daily 0-24-h area under the concentration-time curve, leukocyte count, SPD, survival, and blood pressure measurements. A nonlinear mixed effects modeling approach was applied, considering ibrutinib's pharmacological action and CLL cell dynamics. The final framework included (i) an integrated model for SPD and leukocytes consisting of four CLL cell subpopulations with ibrutinib inhibiting phosphorylated Btk production, ( ii) a turnover model in which ibrutinib stimulates an increase in blood pressure, and (iii) a competing risk model for dropout and death. Simulations predicted that the approved dosing schedule had a slightly higher efficacy (24-month, progression- free survival [PFS] 98%) than de-escalation schedules (24-month, average PFS approximate to 97%); the latter had, on average, approximate to 20% lower proportions of patients with hypertension. The developed modeling framework offers an improved understanding of the relationships among ibrutinib exposure, efficacy and toxicity biomarkers. This framework can serve as a platform to assess dosing schedules in a biologically plausible manner.

Place, publisher, year, edition, pages
WILEY, 2023
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-517953 (URN)10.1002/psp4.13010 (DOI)001037648300001 ()37452622 (PubMedID)
Funder
Swedish Cancer Society, 20: 1226 PjFSwedish Cancer Society, CAN 2017/626
Available from: 2023-12-15 Created: 2023-12-15 Last updated: 2023-12-15Bibliographically approved
Bukkems, L. H., Versloot, O., Cnossen, M. H., Jönsson, S., Karlsson, M. O., Mathot, R. A. A. & Fischer, K. (2023). Association between Sports Participation, Factor VIII Levels and Bleeding in Hemophilia A. Thrombosis and Haemostasis, 123(03), 317-325
Open this publication in new window or tab >>Association between Sports Participation, Factor VIII Levels and Bleeding in Hemophilia A
Show others...
2023 (English)In: Thrombosis and Haemostasis, ISSN 0340-6245, E-ISSN 2567-689X, Vol. 123, no 03, p. 317-325Article in journal (Refereed) Published
Abstract [en]

Background

Little is known on how sports participation affects bleeding risk in hemophilia. This study aimed to examine associations between sports participation, factor VIII (FVIII) levels and bleeding in persons with hemophilia A.

Methods

In this observational, prospective, single-center study, persons with hemophilia A who regularly participated in sports were followed for 12 months. The associations of patient characteristics, FVIII levels, and type/frequency of sports participation with bleeding were analyzed by repeated time-to-event modelling.

Results

One hundred and twelve persons (median age: 24 years [interquartile range:16-34], 49% severe, 49% on prophylaxis) were included. During follow-up, 70 bleeds of which 20 sports-induced were observed. FVIII levels were inversely correlated with the bleeding hazard; a 50% reduction of the baseline bleeding hazard was observed at FVIII levels of 3.1 and a 90% reduction at 28.0 IU/dL. The bleeding hazard did not correlate with sports participation. In addition, severe hemophilia, prestudy annual bleeding rate, and presence of arthropathy showed a positive association with the bleeding hazard.

Conclusions

This analysis showed that FVIII levels were an important determinant of the bleeding hazard, but sports participation was not. This observation most likely reflects the presence of adequate FVIII levels during sports participation in our study. Persons with severe hemophilia A exhibited a higher bleeding hazard at a similar FVIII levels than nonsevere, suggesting that the time spent at lower FVIII levels impacts overall bleeding hazard. These data may be used to counsel persons with hemophilia regarding sports participation and the necessity of adequate prophylaxis.

Place, publisher, year, edition, pages
Georg Thieme Verlag KG, 2023
Keywords
bleeding, hemophilia A, prophylaxis, repeated time-to-event, sports
National Category
Hematology Cardiac and Cardiovascular Systems
Identifiers
urn:nbn:se:uu:diva-501898 (URN)10.1055/a-1983-0594 (DOI)000906393500003 ()36402130 (PubMedID)
Available from: 2023-05-16 Created: 2023-05-16 Last updated: 2023-08-28Bibliographically approved
Chasseloup, E. & Karlsson, M. (2023). Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect. Pharmaceutics, 15(2), Article ID 460.
Open this publication in new window or tab >>Comparison of Seven Non-Linear Mixed Effect Model-Based Approaches to Test for Treatment Effect
2023 (English)In: Pharmaceutics, ISSN 1999-4923, E-ISSN 1999-4923, Vol. 15, no 2, article id 460Article in journal (Refereed) Published
Place, publisher, year, edition, pages
MDPI, 2023
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-486295 (URN)10.3390/pharmaceutics15020460 (DOI)000942115000001 ()36839782 (PubMedID)
Funder
Swedish Research Council, 2018-03317
Note

Title in the list of papers of Estelle Chasseloup thesis: Comparison of seven non-linear mixed effect model-based approaches to test for drug effect

Available from: 2022-10-06 Created: 2022-10-06 Last updated: 2023-05-12Bibliographically approved
Chasseloup, E., Hooker, A. & Karlsson, M. (2023). Generation and application of avatars in pharmacometric modelling. Journal of Pharmacokinetics and Pharmacodynamics, 50, 411-423
Open this publication in new window or tab >>Generation and application of avatars in pharmacometric modelling
2023 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 50, p. 411-423Article in journal (Refereed) Published
National Category
Pharmaceutical Sciences
Identifiers
urn:nbn:se:uu:diva-486296 (URN)10.1007/s10928-023-09873-9 (DOI)
Available from: 2022-10-06 Created: 2022-10-06 Last updated: 2024-04-09Bibliographically approved
Verbeeck, J., Geroldinger, M., Thiel, K., Hooker, A. C., Ueckert, S., Karlsson, M., . . . Zimmermann, G. (2023). How to Analyze Continuous and Discrete Repeated Measures in Small-Sample Cross-Over Trials?. Biometrics, 79(4), 3998-4011
Open this publication in new window or tab >>How to Analyze Continuous and Discrete Repeated Measures in Small-Sample Cross-Over Trials?
Show others...
2023 (English)In: Biometrics, ISSN 0006-341X, E-ISSN 1541-0420, Vol. 79, no 4, p. 3998-4011Article in journal (Refereed) Published
Abstract [en]

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.

Place, publisher, year, edition, pages
Oxford University Press, 2023
Keywords
Barnard test, cross-over, epidermolysis bullosa simplex, GEE, generalized pairwise comparison, model averaging, non-parametric marginal model, rare diseases, repeated measures
National Category
Pharmaceutical Sciences Probability Theory and Statistics
Research subject
Pharmaceutical Science; Statistics
Identifiers
urn:nbn:se:uu:diva-526358 (URN)10.1111/biom.13920 (DOI)001049312800001 ()37587671 (PubMedID)
Funder
EU, Horizon 2020, 825575
Available from: 2024-04-09 Created: 2024-04-09 Last updated: 2024-04-17Bibliographically approved
Llanos-Paez, C., Ambery, C., Yang, S., Beerahee, M., Plan, E. L. & Karlsson, M. O. (2023). Joint longitudinal model-based meta-analysis of FEV1 and exacerbation rate in randomized COPD trials. Journal of Pharmacokinetics and Pharmacodynamics, 50(4), 297-314
Open this publication in new window or tab >>Joint longitudinal model-based meta-analysis of FEV1 and exacerbation rate in randomized COPD trials
Show others...
2023 (English)In: Journal of Pharmacokinetics and Pharmacodynamics, ISSN 1567-567X, E-ISSN 1573-8744, Vol. 50, no 4, p. 297-314Article in journal (Refereed) Published
Abstract [en]

Model-based meta-analysis (MBMA) is an approach that integrates relevant summary level data from heterogeneously designed randomized controlled trials (RCTs). This study not only evaluated the predictability of a published MBMA for forced expiratory volume in one second (FEV1) and its link to annual exacerbation rate in patients with chronic obstructive pulmonary disease (COPD) but also included data from new RCTs. A comparative effectiveness analysis across all drugs was also performed. Aggregated level data were collected from RCTs published between July 2013 and November 2020 (n = 132 references comprising 156 studies) and combined with data used in the legacy MBMA (published RCTs up to July 2013 - n = 142). The augmented data (n = 298) were used to evaluate the predictive performance of the published MBMA using goodness-of-fit plots for assessment. Furthermore, the model was extended including drugs that were not available before July 2013, estimating a new set of parameters. The legacy MBMA model predicted the post-2013 FEV1 data well, and new estimated parameters were similar to those of drugs in the same class. However, the exacerbation model overpredicted the post-2013 mean annual exacerbation rate data. Inclusion of year when the study started on the pre-treatment placebo rate improved the model predictive performance perhaps explaining potential improvements in the disease management over time. The addition of new data to the legacy COPD MBMA enabled a more robust model with increased predictability performance for both endpoints FEV1 and mean annual exacerbation rate.

Place, publisher, year, edition, pages
Springer Nature, 2023
Keywords
Chronic obstructive pulmonary disease, Model-based meta-analysis, Forced expiratory volume in one second, Exacerbation rate
National Category
Pharmaceutical Sciences Respiratory Medicine and Allergy
Identifiers
urn:nbn:se:uu:diva-510944 (URN)10.1007/s10928-023-09853-z (DOI)000954657300001 ()36947282 (PubMedID)
Funder
Swedish Research Council, 2022-06725
Available from: 2023-09-13 Created: 2023-09-13 Last updated: 2023-09-13Bibliographically approved
Madathil Krishnan, S., Friberg, L., Mercier, F., Zhang, R., Wu, B., Jin, J. Y., . . . Karlsson, M. (2023). Multistate Pharmacometric Model to Define the Impact of Second-Line Immunotherapies on the Survival Outcome of the IMpower131 Study. Clinical Pharmacology and Therapeutics, 113(4), 851-858
Open this publication in new window or tab >>Multistate Pharmacometric Model to Define the Impact of Second-Line Immunotherapies on the Survival Outcome of the IMpower131 Study
Show others...
2023 (English)In: Clinical Pharmacology and Therapeutics, ISSN 0009-9236, E-ISSN 1532-6535, Vol. 113, no 4, p. 851-858Article in journal (Refereed) Published
Abstract [en]

Overall survival is defined as the time since randomization into the clinical trial to event of death or censor (end of trial or follow-up), and is considered to be the most reliable cancer end point. However, the introduction of second-line treatment after disease progression could influence survival and be considered a confounding factor. The aim of the current study was to set up a multistate model framework, using data from the IMpower131 study, to investigate the influence of second-line immunotherapies on overall survival analysis. The model adequately described the transitions between different states in patients with advanced squamous non-small cell lung cancer treated with or without atezolizumab plus nab-paclitaxel and carboplatin, and characterized the survival data. High PD-L1 expression at baseline was associated with a decreased hazard of progression, while the presence of liver metastasis at baseline was indicative of a high risk of disease progression after initial response. The hazard of death after progression was lower for participants who had longer treatment response, i.e., longer time to progression. The simulations based on the final multistate model showed that the addition of atezolizumab to the nab-paclitaxel and carboplatin regimen had significant improvement in the patients' survival (hazard ratio = 0.75, 95% prediction interval: 0.61-0.90 favoring the atezolizumab + nab-paclitaxel and carboplatin arm). The developed modeling approach can be applied to other cancer types and therapies to provide a better understanding of efficacy of drug and characterizing different states, and investigate the benefit of primary therapy in survival while accounting for the switch to alternative treatment in the case of disease progression.

Place, publisher, year, edition, pages
Wiley-Blackwell, 2023
National Category
Cancer and Oncology
Identifiers
urn:nbn:se:uu:diva-501766 (URN)10.1002/cpt.2838 (DOI)000923391300001 ()36606486 (PubMedID)
Funder
Swedish Cancer Society, 20 1226 PjF
Note

De två sista författarna delar sistaförfattarskapet.

Available from: 2023-05-12 Created: 2023-05-12 Last updated: 2023-05-12Bibliographically approved
Projects
Model-based development of anti-tuberculosis drug combinations [2011-03442_VR]; Uppsala UniversityComposite score models for efficient use of patient data in decision making for development and usage of drugs [2018-03317_VR]; Uppsala University
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1258-8297

Search in DiVA

Show all publications