Abstract
BackgroundCancer is one of the leading death causes globally with about 8.2 million deaths per year and an increase in numbers in recent years. About 90% of cancer deaths do not occur due to primary tumors but due to metastases, of which most are not clinically identifiable because of their relatively small size at primary diagnosis and limited technical possibilities. However, therapeutic decisions are formed depending on the existence of metastases and their properties. Therefore non-identified metastases might have huge influence in the treatment outcome. The quantification of clinically visible and invisible metastases is important for the choice of an optimal treatment of the individual patient as it could clarify the burden of non-identifiable tumors as well as the future behavior of the cancerous disease.ResultsThe mathematical model presented in this study gives insights in how this could be achieved, taking into account different treatment possibilities and therefore being able to compare therapy schedules for individual patients with different clinical parameters. The framework was tested on three patients with non-small cell lung cancer, one of the deadliest types of cancer worldwide, and clinical history including platinum-based chemotherapy and PD-L1-targeted immunotherapy. Results yield promising insights into the framework to establish methods to quantify effects of different therapy methods and prognostic features for individual patients already at stage of primary diagnosis.
Highlights
Cancer is one of the leading death causes globally with about 8.2 million deaths per year and an increase in numbers in recent years
This allows for an explanation of refractory effects termed as ‘kinetic resistance’ that are widely observed in clinical chemotherapy applications on tumors reaching a small size [24]. This kinetic resistance is an important driver of therapy outcome. To account for these refractory effects in a simpler way we introduce the dynamics of chemotherapy as follows
Clinical data The patient data examined in the following contain patients with non-small cell lung cancer (NSCLC) and were collected from volumetric measurements of primary tumors and metastases of patients with adenocarcinoma and adenosquamous carcinoma with different histologies
Summary
Cancer is one of the leading death causes globally with about 8.2 million deaths per year and an increase in numbers in recent years. The quantification of clinically visible and invisible metastases is important for the choice of an optimal treatment of the individual patient as it could clarify the burden of non-identifiable tumors as well as the future behavior of the cancerous disease. The vast majority of primary malignant lung tumors are carcinomas, which contain two major subgroups: nonsmall cell lung cancer (NSCLC) and small cell lung cancer (SCLC). The former group accounts for about 85% of all lung cancers and is itself divided into the main. TTF1 has been shown to be expressed in about 80% of primary lung ADC [3]. The identification for markers of successful treatment is current scientific work [10]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
