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Circulating tumor cell counts is a better predictor of overall survival than dynamic tumor size changes – a quantitative modeling framework
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. Uppsala University. (Pharmacometrics)ORCID iD: 0000-0003-4677-4741
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences. (Pharmacometrics)
Department of Medical Cell BioPhysics, Faculty of Science and Technology, University of Twente, Enschede, The Netherlands.
Department of Medical Oncology, University Medical Centre Utrecht, Utrecht University, Utrecht, the Netherlands.
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(English)In: Clinical Cancer Research, ISSN 1078-0432, E-ISSN 1557-3265Article in journal (Other academic) Submitted
Abstract [en]

Purpose: Quantitative relationships between treatment-induced changes in tumor size and circulating tumor cell (CTC) counts, and their links to overall survival (OS), are lacking. We here present a population modeling framework identifying and quantifying such relationships, based on longitudinal data collected in patients with metastatic colorectal cancer (mCRC) to evaluate the value of tumor size and CTC counts as predictors of OS.

Experimental design: A pharmacometric approach (i.e., population pharmacodynamic modeling) was used to characterize the changes in tumor size and CTC count and evaluate them as predictors of OS in 451 patients with mCRC treated with chemotherapy and targeted therapy in a prospectively randomized phase 3 study (CAIRO2).

Results: A tumor size model of tumor quiescence and drug-resistance, was used to characterize the tumor size time-course, and was, in addition to the total normalized dose (i.e., of all administered drugs) in a given cycle, related to the CTC counts through a negative binomial model (CTC model). A CTC count≥3/7.5 mL (hazard ratio=3.51, 95% confidence interval: 2.85-4.32), as described by the CTC model, was a better predictor of OS than tumor size changes. The modeling framework was applied to explore if dose-modifications (increased and reduced) would result in a CTC count below 3/7.5 mL after 1-2 weeks of treatment.

Conclusions: Time-varying CTC counts can be useful for early predicting OS in patients with mCRC, and may therefore have potential for model-based treatment individualization. Although tumor size had a strong connection to CTC, its link to OS was weaker. 

National Category
Pharmaceutical Sciences
Research subject
Pharmacokinetics and Drug Therapy
Identifiers
URN: urn:nbn:se:uu:diva-390191OAI: oai:DiVA.org:uu-390191DiVA, id: diva2:1341480
Funder
Swedish Cancer Society, CAN 2017/626Available from: 2019-08-08 Created: 2019-08-08 Last updated: 2019-08-09
In thesis
1. Pharmacometric Evaluation of Biomarkers to Improve Treatment in Oncology
Open this publication in new window or tab >>Pharmacometric Evaluation of Biomarkers to Improve Treatment in Oncology
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cancer is a family of many different diseases with substantial heterogeneity also within the same cancer type. In the era of personalized medicine, it is desirable to identify an early response to treatment (i.e., a biomarker) that can predict the long-term outcome with respect to both safety and efficacy. It is however not uncommon to categorize continuous data, e.g., using tumor size data to classify patients as responders or non-responders, resulting in loss of valuable information. Pharmacometric modeling offers a way of analyzing longitudinal time-courses of different variables (e.g., biomarker and tumor size), and therefore minimizing information loss.

Neutropenia is the most common dose-limiting toxicity for chemotherapeutic drugs and manifests by a low absolute neutrophil count (ANC). This thesis explored the potential of using model-based predictions together with frequent monitoring of the ANC to identify patients at risk of severe neutropenia and potential dose delay. Neutropenia may develop into febrile neutropenia (FN), a potentially life-threatening condition. Interleukin 6, an immune-related biomarker, was identified as an on-treatment predictor of FN in breast cancer patients treated with adjuvant chemotherapy. C-reactive protein, another immune-related biomarker, rather demonstrated confirmatory value to support FN diagnosis.

Cancer immunotherapy is the most recent advance in anticancer treatment, with immune checkpoint inhibitors, e.g., atezolizumab, leading the breakthrough. In a pharmacometric modeling framework, the area under the curve of atezolizumab was related to tumor size changes in non-small cell lung cancer patients treated with atezolizumab. The relative change from baseline of Interleukin 18 at 21 days after start of treatment added predictive value on top of the drug effect. The tumor size time-course predicted overall survival (OS) in the same population.

Circulating tumor cells (CTCs) are tumor cells that have shed from a tumor and circulate in the blood. CTCs may cause distant metastases, which is related to a poor prognosis. A novel modeling framework was developed in which the relationship between tumor size and CTC count was quantified in patients with metastatic colorectal cancer treated with chemotherapy and targeted therapy. It was also demonstrated that the CTC count was a superior predictor of OS in comparison to tumor size changes.

In summary, IL-6 predicted FN, IL-18 predicted tumor size changes and tumor size changes and CTC counts predicted OS. The results in this thesis were obtained by using pharmacometrics to evaluate biomarkers to improve treatment in oncology.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 85
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Pharmacy, ISSN 1651-6192 ; 275
Keywords
Pharmacometrics, Biomarkers, Oncology, Population PKPD Modeling, NONMEM
National Category
Pharmaceutical Sciences
Research subject
Pharmaceutical Science
Identifiers
urn:nbn:se:uu:diva-390192 (URN)978-91-513-0709-1 (ISBN)
Public defence
2019-09-27, Room B21, Biomedicinskt centrum (BMC), Husargatan 3, Uppsala, 09:15 (English)
Opponent
Supervisors
Available from: 2019-09-05 Created: 2019-08-09 Last updated: 2019-09-17

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