The risk of febrile neutropenia in breast cancer patients following adjuvant chemotherapy is predicted by the time course of interleukin-6 and C-reactive protein by modelling

C-Reactive Protein as an Early Predictor of Efficacy in Advanced Non-Small-Cell Lung Cancer Patients: A Tumor Dynamics-Biomarker Modeling Framework

In oncology, longitudinal biomarkers reflecting the patient's status and disease evolution can offer reliable predictions of the patient's response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions.

Prospective external validation of an updated algorithm to quantify risk of febrile neutropenia in cancer patients after a cycle of chemotherapy

PURPOSE

Febrile neutropenia resulting from chemotherapy is a significant cause of morbidity and mortality in cancer patients. We had previously published the associates of the risk of febrile neutropenia, and this study now extends and modifies the previous model as well as tests its external validity.

METHODS

We have recruited documented febrile neutropenia cases with solid tumors, in addition to a selected control group of cancer patients from one institution treated between 2015 and 2019. We then united our sample with our previously published original derivation group, to modify and update our previous model by logistic regression analysis. Additionally, consecutive cancer patients from 5 institutions were recruited in 2020 to test external validity of the resultant algorithm.

RESULTS

A total of 4075 cycles of chemotherapy in 1282 cases were recruited in the updated, new model derivation group, and a total of 8 variables were selected for the updated algorithm. In the new external validation group, 653 cycles of chemotherapy in 624 patients were analyzed, to indicate that after cycles without prophylactic granulocyte colony-stimulating factor (GCSF) usage, the algorithm yielded a sensitivity value of 91%, specificity of 40%, and an area under curve (AUC) figure of 0.78, when a risk cutoff threshold value of ≥ 0.20 is chosen. This algorithm is now embedded in a web application for free clinical use.

CONCLUSION

Our algorithm identifies and quantifies the risk of febrile neutropenia in cancer patients. Further studies are required to improve this model with additional predictors.

Model-based meta-analysis of the time to first acute urinary retention or benign prostatic hyperplasia-related surgery in patients with moderate or severe symptoms

AIMS

Combination therapy of 5α-reductase inhibitor and α-blocker is a guideline-endorsed therapeutic approach for patients with moderate-to-severe lower urinary tract symptoms or benign prostatic hyperplasia (LUTS/BPH) who are at risk of disease progression. We aimed to disentangle the contribution of clinical and demographic baseline characteristics affecting the risk of acute urinary retention or BPH-related surgery (AUR/S) from the effect of treatment with drugs showing symptomatic and disease-modifying properties.

METHODS

A time-to-event model was developed using pooled data from patients (n = 10 238) enrolled into six clinical studies receiving placebo, tamsulosin, dutasteride or tamsulosin-dutasteride combination therapy. A parametric hazard function was used to describe the time to first AUR/S. Covariate model building included the assessment of relevant clinical and demographic factors on baseline hazard. Predictive performance was evaluated by graphical and statistical methods.

RESULTS

An exponential hazard model best described the time to first AUR/S in this group of patients. Baseline International Prostate Symptom Score, prostate-specific antigen, prostate volume and maximum urine flow were identified as covariates with hazard ratio estimates of 1.04, 1.08, 1.01 and 0.91, respectively. Dutasteride monotherapy and tamsulosin-dutasteride combination therapy resulted in a significant reduction in the baseline hazard (56.8% and 66.4%, respectively). By contrast, the effect of tamsulosin did not differ from placebo.

CONCLUSIONS

Our analysis showed the implications of disease-modifying properties of dutasteride and tamsulosin-dutasteride combination therapy for the risk of AUR/S. It also elucidated the contribution of different baseline characteristics to the risk of these events. The use of tamsulosin monotherapy (symptomatic treatment) has no impact on individual long-term risk.

Drug Exposure to Establish Pharmacokinetic-Response Relationships in Oncology

In the oncology field, understanding the relationship between the dose administered and the exerted effect is particularly important because of the narrow therapeutic index associated with anti-cancer drugs and the high interpatient variability. Therefore, in this review, we provide a critical perspective of the different methods of characterising treatment exposure in the oncology setting. The increasing number of modelling applications in oncology reflects the applicability and the impact of pharmacometrics on all phases of the drug development process and patient management as well. Pharmacometric modelling is a worthy component within the current paradigm of model-based drug development, but pharmacometric modelling techniques are also accessible for the clinician in the optimisation of current oncology therapies. Consequently, the application of population models in a hospital setting by generating close collaborations between physicians and pharmacometricians is highly recommended, providing a systematic means of developing and assessing model-based metrics as 'drivers' for various responses to treatments, which can then be evaluated as predictors for treatment success. Characterising the key determinants of variability in exposure is of particular importance for anticancer agents, as efficacy and toxicity are associated with exposure. We present the different strategies to describe and predict drug exposure that can be applied depending on the data available, with the objective of obtaining the most useful information in the patients' favour throughout the full drug cycle. Therefore, the objective of the present article is to review the different approaches used to characterise a patient's exposure to oncology drugs, which will result in a better understanding of the time course of the response and the magnitude of interpatient variability.

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotics

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended.

Evaluation of ABC gene polymorphisms on the pharmacokinetics and pharmacodynamics of capecitabine in colorectal patients: Implications for dosing recommendations

AIMS

The aims are to develop a population pharmacokinetic model of capecitabine (CAP) and its main metabolites after the oral administration of CAP in colorectal cancer patients with different polymorphisms of the ATP-binding cassette (ABC) gene and a population pharmacokinetic/pharmacodynamic model capable of accounting for the neutropenic effects, and to optimize the dosing strategy based on the polymorphisms of the ABC gene and/or the administration regimen as a single agent or in combination.

METHODS

Forty-eight patients diagnosed with colorectal cancer were included, with 432 plasma levels of CAP, 5'-desoxi-5-fluorouridine (5'-DFUR) and 5-fluorouracil (5-FU), and 370 neutrophil observations. Capecitabine doses ranged from 1250 to 2500 mg/m² /24 h. Plasma measurements of CAP, 5'-DFUR and 5-FU were obtained at 1, 2 and 3 hours post administration. Neutrophil levels were measured between day 15 and day 24 post administration.

RESULTS

The pharmacokinetic model incorporates oxaliplatin as a covariate on absorption lag time, rs6720173 (ABCG5 gene) on clearance of 5'-DFUR (182% increase for mutated rs6720173) and rs2271862 (ABCA2 gene) on clearance of 5-FU (184% increase for mutated rs2271862). System- (Circ₀ = 3.54 × 10⁹ cells/mL, MTT = 204 hours and γ = 6.0 × 10^-2 ) and drug-related (slope [SLP] = 3.1 × 10^-2 mL/mg). Co-administration of oxaliplatin resulted in a 2.84-fold increase in SLP. The predicted exposure thresholds to G3/4 neutropenia in combination and monotherapy were 26 and 70 mg·h/L, respectively.

CONCLUSIONS

The population pharmacokinetic/pharmacodynamic model characterized the time course of capecitabine and its metabolites in plasma. Dose recommendations of capecitabine in patients with mutated and wild allele for single nucleotide polymorphisms rs2271862 of ≤3000 and ≤2400 mg/m² /24 h in monotherapy and ≤1750 and ≤600 mg/m² /24 h in combination with oxaliplatin, respectively, have been proposed.

Pharmacodynamics of immune response biomarkers of interest for evaluation of treatment effects in bacterial infections

This mini-review discusses the pharmacodynamics of immune-related biomarkers in the area of bacterial infectious diseases that could be of interest from a pharmacokinetic (PK) and pharmacokinetic/pharmacodynamic (PK/PD) perspective in the evaluation of treatment effects. The host response to an infection is often poorly defined both in preclinical assessments and in clinical practice when it comes to characterisation of PK and PK/PD relationships. Through population modelling, the time courses and variability of immune response variables can be quantified. Incorporation of such biomarker information into PK and PK/PD models may guide the evaluation of individual response to treatment (right antibiotic, more antibiotic, less antibiotic) and when to stop treatment. Furthermore, translation of results from preclinical systems to clinical scenarios may be improved with the incorporation of biomarker information. Potential biomarkers for these purposes are discussed and a few modelling examples are provided.

Neutropénie fébrile aux urgences, stratification du risque et conditions du retour à domicile

La neutropénie fébrile (NF) est une situation fréquemment rencontrée aux urgences avec un taux de mortalité non négligeable variant de 5 à 40 %. Cette variabilité importante met en avant l’importance de stratifier le risque afin de permettre un traitement ambulatoire per os de certains patients à faible risque. En plus du MASCC (The Multinational Association for Supportive Care in Cancer) score, d’autres outils permettent d’évaluer ce risque ou sont à l’étude dans ce but, tels que le dosage de la CRP, la procalcitonine ou encore le score CISNE. Après une prise en charge rapide aux urgences incluant l’administration sans délai d’un traitement adéquat, la poursuite de l’antibiothérapie per os à domicile est envisageable chez les patients à faible risque. La combinaison amoxicilline–acide clavulanique et ciprofloxacine est le plus souvent recommandée, mais la moxifloxacine ou la lévofloxacine en monothérapie peuvent également être utilisées pour les patients traités à domicile. Le retour à domicile permet de réduire fortement les coûts engendrés par l’hospitalisation, de diminuer le risque d’infection nosocomiale et d’améliorer la qualité de vie des patients avec NF à faible risque. Dans cette optique, plusieurs critères doivent être remplis, et une discussion avec le patient reste primordiale à la prise de décision. Parmi ceux-ci, nous retiendrons notamment un score MASCC supérieur à 21, une durée attendue de neutropénie inférieure à sept jours, l’accord du patient et de son entourage ainsi que la proximité entre le domicile et un service de soin adapté.

The risk of febrile neutropenia in breast cancer patients following adjuvant chemotherapy is predicted by the time course of interleukin-6 and C-reactive protein by modelling

AIMS

Early identification of patients with febrile neutropenia (FN) is desirable for initiation of preventive treatment, such as with antibiotics. In this study, the time courses of two inflammation biomarkers, interleukin (IL)-6 and C-reactive protein (CRP), following adjuvant chemotherapy of breast cancer, were characterized. The potential to predict development of FN by IL-6 and CRP, and other model-derived and clinical variables, was explored.

METHODS

The IL-6 and CRP time courses in cycles 1 and 4 of breast cancer treatment were described by turnover models where the probability for an elevated production following initiation of chemotherapy was estimated. Parametric time-to-event models were developed to describe FN occurrence to assess: (i) predictors available before chemotherapy is initiated; (ii) predictors available before FN occurs; and (iii) predictors available when FN occurs.

RESULTS

The IL-6 and CRP time courses were successfully characterized with peak IL-6 typically occurring 2 days prior to CRP peak. Of all evaluated variables the CRP time course was most closely associated with the occurrence of FN. Since the CRP peak typically occurred at the time of FN diagnosis it will, however, have limited value for identifying the need for preventive treatment. The time course of IL-6 was the predictor that could best forecast FN events. Of the variables available at baseline, age was the best, although in comparison a relatively weak, predictor.

CONCLUSIONS

The developed models add quantitative knowledge about IL-6 and CRP and their relationship to the development of FN. The study suggests that IL-6 may have potential as a clinical predictor of FN if monitored during myelosuppressive chemotherapy.