Nadja Haas1, Elli Husso1, Eduard Schmulenson1, Mathias Hoiczyk2, Yon-Dschun Ko3, Lothar Müller4, Henning Schulze-Bergkamen2, Ulrike Schwinger5, Ulrich Jaehde1
1Department of Clinical Pharmacy, Institute of Pharmacy, University of Bonn, 2Medical Clinic II, Marien-Hospital Wesel gGmbH, 3Department of Internal Medicine, Hematology and Oncology, Johanniter Krankenhaus Bonn, 4Study Centrum Unter Ems, Practice for Oncology and Hematology, 5Practice for Oncology, Medical care center at the Rober-Bosch-Krankenhaus
Introduction: Adverse drug events (ADE) represent a great burden for patients in the treatment with antitumor drugs and can in the worst case be therapy-limiting. Regarding the evaluation of ADE, the patient’s perspective is becoming increasingly important, e.g. through the Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) developed by the National Cancer Institute [1]. Predictions of patient-reported symptom burden may contribute to an individual and targeted optimization of therapeutic and supportive measures in anticancer treatment. MCTMMs, in combination with pharmacokinetic models, are well suited to describe the relationship between drug exposure and toxicity [2, 3]. Objective: Development of different mCTMMs to identify covariate influences on the occurrence of selected patient-reported ADEs in patients treated with fluorouracil (5-FU). Methods: The 5-FU PRO observational study was conducted to investigate the incidence and severity of selected patient-reported symptoms during 5-FU therapy. During the 12-week observation period, patients with colorectal cancer completed an electronic questionnaire with selected PRO-CTCAE symptoms every seven days. The study centers documented additional information on treatment with 5-FU, comedication and comorbidity. MCTMMs were developed for all 16 PRO-CTCAE symptoms. Covariate influences were then investigated using the symptom diarrhea. The pre-selected potential covariates included basic data such as age and sex, comedication commonly used in in combination with 5-FU, and the presence of supportive therapy for diarrhea. The influence of these covariates was first tested on the intercept a1 (model 1). The same covariates were then tested separately on the mean equilibration time (MET) (model 2). Model 1 and model 2 had a classic mCTMM structure in which one MET was estimated. The mCTMM structure was then modified by estimating two different METs for the transitions between two adjacent severity levels. Covariate tests were again performed on this new model structure for a1 (model 3) and the METs (model 4). These models were then compared to determine which of the model structures provided the best fit, using model 1 as a reference. Covariates were included in the model structure if they resulted in a significant reduction in the objective function value (dOFV) of 6.67 (p-value = 0.01). Results: Between November 2020 and December 2022, 40 patients were included in the 5-FU-PRO study and 355 PRO-CTCAE questionnaires were collected. Severity grades 2 and 3 were combined for the development of mCTMM, as grade 3 was very rarely reported. A base mCTMM was developed for diarrhea and the covariate test was performed. In model 1, three covariates showed a significant influence: age, body surface area (BSA) and bolus administration of 5-FU. All three covariates reduced the probability of severe diarrhea. Inclusion of the covariates resulted in a dOFV of -29.36 compared with the base model. Two covariates were included in model 2: sex and supportive medication for diarrhea resulting in a dOFV of +1.41 compared to model 1. In model 3 the same covariates were significant as in model 1 with a dOFV of -2.41. In model 4, only sex showed an influence with a dOFV of +14.62. Overall, models 2 – 4 showed no significant improvement in OFV compared to model 1. Conclusion: The development of mCTMMs in combination with PRO-CTCAE symptom scores was shown to be feasible. The diarrhea model was improved by the inclusion of covariates. Covariates influencing MET were identified and OFV was slightly reduced by including a second MET. However, the two models with two METs were less stable than the model with one MET, presumably because the data was too sparse for the number of estimated parameters. For a better evaluation of the modifications, further analyses with larger data sets should be performed.
[1] Minasian L et al. Patient Relat Outcome Mes, 13:249–258, 2022. [2] Schindler E and Karlsson M. O. AAPS Journal, 19:1424–1435, 2017. [3] Schmulenson E et al. Cancer Chemother Pharmacol, 86:435–444, 2020.
Reference: PAGE 33 (2025) Abstr 11461 [www.page-meeting.org/?abstract=11461]
Poster: Drug/Disease Modelling - Safety