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PEGASUS aims to test acceptability and feasibility of studying phenoconversion (the change in metabolism phenotype) using probe medications in a paediatric oncology patient population. The study will be conducted in patients (6-25 years of age) with Hodgkin lymphoma or non-Hodgkin lymphoma as exemplar cohort, but with the understanding that cancer-directed and supportive care medicines of the CYP3A4, CYP2C19, and CYP2D6 metabolic pathways are commonly utilised for the treatment of many paediatric, adolescent, young adult, and adult cancers.
The study involves administration of the probe medication at timepoints which align with pre-determined hospital visits for the treatment of lymphoma and subsequent blood draws to measure the metabolism of the probe medications.
The acceptability and feasibility of this study will inform future studies in phenoconversion within the paediatric cancer population to direct more personalised precision medicine.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Omeprazole | Drug | Sub-therapeutic probe drug administration to measure phenoconversion. | ||
| Dextromethorphan | Drug | Sub-therapeutic probe drug administration to measure phenoconversion. |
| Measure | Description | Time Frame |
|---|---|---|
| Proportion of patients who consent to study and complete baseline and at least two longitudinal timepoints with successful measurement of probe drug MR (Metabolic ratio) | This measure is to help inform whether future studies of this nature are feasible and identify if any procedures need to be adjusted to ensure study participant completion. | 12 months, 24 Months |
| Measure | Description | Time Frame |
|---|---|---|
| Percentage of participants completing all required longitudinal blood sampling | This measure is to help inform whether future studies of this nature are feasible and identify if any procedures need to be adjusted to ensure study participant completion. | Baseline through to 24 Months |
| Proportion of participants with successful detection of probe drug overall and at each sampling timepoint |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Rachel Conyers, MBBS (Hons) | Contact | +61393455522 | rachel.conyers@mcri.edu.au |
| Name | Affiliation | Role |
|---|---|---|
| Rachel Conyers, MBBS (Hons) | Murdoch Childrens Research Institute | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Peter MacCallum Cancer Centre | Recruiting | Melbourne | Victoria | 3000 | Australia |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34114066 | Background | Helsby N, Yong M, Burns K, Findlay M, Porter D. Cyclophosphamide bioactivation pharmacogenetics in breast cancer patients. Cancer Chemother Pharmacol. 2021 Sep;88(3):533-542. doi: 10.1007/s00280-021-04307-0. Epub 2021 Jun 10. | |
| 24519754 | Background | Burns KE, Goldthorpe MA, Porteus F, Browett P, Helsby NA. CYP2C19 genotype-phenotype discordance in patients with multiple myeloma leads to an acquired loss of drug-metabolising activity. Cancer Chemother Pharmacol. 2014 Mar;73(3):651-5. doi: 10.1007/s00280-014-2409-9. Epub 2014 Feb 12. |
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This measure is to help inform whether future studies of this nature are feasible and identify if the method for probe drug detection requires improvement. |
| Baseline through to 24 Months |
| Proportion of participants where phenotype can be classified according to MR overall at each sampling timepoint | This measure is to help inform whether future studies of this nature are feasible and identify if the phenotype can be clearly classified at each timepoint; (i) Prior to commencing first lymphoma chemotherapy cycle (ii) 2 months (week 8) (iii) 4 months (week 16) (iv) Completion of therapy (> week 16) (v) Up to a maximum of 2 febrile neutropenic episodes and for how many patients. | Baseline through to 24 Months |
| The level of acceptability of participation in pharmacogenomic & phenoconversion testing using the PEGASUS specific survey tool (based on the Theoretical Framework of Acceptability [TFA]) | This measure is to help inform whether future studies of this nature are feasible and acceptable. Participants will complete the survey which asks 26 questions, with a numerical scale of 1-7 or a wording scale of 7 choices depending on the question. | Baseline through to 24 Months |
| Percentage of participants experiencing an adverse event (AE) during probe drug administration | This measure is to help inform whether future studies of this nature are feasible and identify if/how many adverse events are experienced during probe drug administration. | Baseline through to 24 Months |
| Incidence of genotype and phenotype mismatch, overall and across longitudinal timepoints | This measure is to help inform whether future studies of this nature are feasible and identify if genotype and phenotype mismatch occurs throughout each timepoint and the overall study. | Baseline through to 24 Months |
| Proportion of participants with disease staging and biomarkers of extent of disease | This measure is to help inform whether future studies of this nature are feasible, to identify any variables that stand out and inform future research questions. | Baseline through to 24 Months |
| Proportion of participants with a systemic inflammatory state | This measure is to help inform whether future studies of this nature are feasible, to identify any variables that stand out and inform future research questions. | Baseline through to 24 Months |
| Proportion of participants taking medications involving the CYP P450 pathway | This measure is to help inform whether future studies of this nature are feasible, to identify any variables that stand out and inform future research questions. | Baseline through to 24 Months |
| Participant demographic information | This measure is to help inform whether future studies of this nature are feasible, to identify any variables that stand out and inform future research questions. | Baseline |
| Proportion of participants with other environmental factors | This measure is to help inform whether future studies of this nature are feasible, to identify any variables that stand out and inform future research questions. | Baseline through to 24 Months |
| Longitudinal inflammatory profile of participants with Hodgkin or non-Hodgkin Lymphoma as measured by a panel including serum levels of procalcitonin, c-reactive protein and cytokine analysis. | This measure is to identify if there are fluctuations within the inflammatory profile of the patients which helps to inform whether future studies of this nature are feasible. The panel detects a comprehensive set of studied and biologically relevant inflammatory markers including those shown to be predictive of severe infection in children with cancer and febrile neutropenia when out of normal ranges. | Baseline through to 24 Months |
| 22451032 | Background | Kim S, Ostor AJ, Nisar MK. Interleukin-6 and cytochrome-P450, reason for concern? Rheumatol Int. 2012 Sep;32(9):2601-4. doi: 10.1007/s00296-012-2423-3. Epub 2012 Mar 27. |
| 36937881 | Background | Rodieux F, Daali Y, Rollason V, Samer CF, Ing Lorenzini K. Practice of CYP450 genotyping and phenotyping in children in a real-life setting. Front Pharmacol. 2023 Feb 27;14:1130100. doi: 10.3389/fphar.2023.1130100. eCollection 2023. |
| 24722393 | Background | Bosilkovska M, Samer CF, Deglon J, Rebsamen M, Staub C, Dayer P, Walder B, Desmeules JA, Daali Y. Geneva cocktail for cytochrome p450 and P-glycoprotein activity assessment using dried blood spots. Clin Pharmacol Ther. 2014 Sep;96(3):349-59. doi: 10.1038/clpt.2014.83. Epub 2014 Apr 10. |
| 27378571 | Background | Lloret-Linares C, Rollason V, Lorenzini KI, Samer C, Daali Y, Gex-Fabry M, Aubry JM, Desmeules J, Besson M. Screening for genotypic and phenotypic variations in CYP450 activity in patients with therapeutic problems in a psychiatric setting, a retrospective study. Pharmacol Res. 2017 Apr;118:104-110. doi: 10.1016/j.phrs.2016.07.002. Epub 2016 Jul 1. |
| 33121061 | Background | Rollason V, Lloret-Linares C, Lorenzini KI, Daali Y, Gex-Fabry M, Piguet V, Besson M, Samer C, Desmeules J. Evaluation of Phenotypic and Genotypic Variations of Drug Metabolising Enzymes and Transporters in Chronic Pain Patients Facing Adverse Drug Reactions or Non-Response to Analgesics: A Retrospective Study. J Pers Med. 2020 Oct 27;10(4):198. doi: 10.3390/jpm10040198. |
| 34512355 | Background | Ing Lorenzini K, Desmeules J, Rollason V, Bertin S, Besson M, Daali Y, Samer CF. CYP450 Genotype-Phenotype Concordance Using the Geneva Micrococktail in a Clinical Setting. Front Pharmacol. 2021 Aug 26;12:730637. doi: 10.3389/fphar.2021.730637. eCollection 2021. |
| 34791831 | Background | Lenoir C, Niederer A, Rollason V, Desmeules JA, Daali Y, Samer CF. Prediction of cytochromes P450 3A and 2C19 modulation by both inflammation and drug interactions using physiologically based pharmacokinetics. CPT Pharmacometrics Syst Pharmacol. 2022 Jan;11(1):30-43. doi: 10.1002/psp4.12730. Epub 2021 Nov 17. |
| 32110941 | Background | Mandrioli R, Mercolini L, Protti M. Blood and Plasma Volumetric Absorptive Microsampling (VAMS) Coupled to LC-MS/MS for the Forensic Assessment of Cocaine Consumption. Molecules. 2020 Feb 26;25(5):1046. doi: 10.3390/molecules25051046. |
| 34093531 | Background | Doerflinger M, Haeusler GM, Li-Wai-Suen CSN, Clark JE, Slavin M, Babl FE, Allaway Z, Mechinaud F, Smyth GK, De Abreu Lourenco R, Phillips B, Pellegrini M, Thursky KA. Procalcitonin and Interleukin-10 May Assist in Early Prediction of Bacteraemia in Children With Cancer and Febrile Neutropenia. Front Immunol. 2021 May 20;12:641879. doi: 10.3389/fimmu.2021.641879. eCollection 2021. |
| 40259519 | Derived | Conyers R, Stenta T, Somogyi AA, Kirkpatrick C, Halman A, Wang S, Moore C, Khatri D, Williams E, Dyas R, Spelman T, Elliott DA, Gwee A, Alexander M. Phenoconversion of CYP3A4, CYP2C19 and CYP2D6 in Pediatrics, Adolescents and Young Adults With Lymphoma: Rationale and Design of the PEGASUS Study. Clin Transl Sci. 2025 Apr;18(4):e70209. doi: 10.1111/cts.70209. |
| ID | Term |
|---|---|
| D006689 | Hodgkin Disease |
| D008228 | Lymphoma, Non-Hodgkin |
| ID | Term |
|---|---|
| D008223 | Lymphoma |
| D009370 | Neoplasms by Histologic Type |
| D009369 | Neoplasms |
| D008232 | Lymphoproliferative Disorders |
| D008206 | Lymphatic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
| D007160 | Immunoproliferative Disorders |
| D007154 | Immune System Diseases |
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| ID | Term |
|---|---|
| D009853 | Omeprazole |
| D003915 | Dextromethorphan |
| ID | Term |
|---|---|
| D053799 | 2-Pyridinylmethylsulfinylbenzimidazoles |
| D013454 | Sulfoxides |
| D013457 | Sulfur Compounds |
| D009930 | Organic Chemicals |
| D011725 | Pyridines |
| D006573 | Heterocyclic Compounds, 1-Ring |
| D006571 | Heterocyclic Compounds |
| D001562 | Benzimidazoles |
| D006574 | Heterocyclic Compounds, 2-Ring |
| D000072471 | Heterocyclic Compounds, Fused-Ring |
| D009019 | Morphinans |
| D053610 | Opiate Alkaloids |
| D000470 | Alkaloids |
| D006572 | Heterocyclic Compounds, Bridged-Ring |
| D006576 | Heterocyclic Compounds, 4 or More Rings |
| D010616 | Phenanthrenes |
| D011084 | Polycyclic Aromatic Hydrocarbons |
| D011083 | Polycyclic Compounds |
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