Early Detection of Complications During Immunotherapy for Haematological Malignancy

Overview

Aims * To identify patients that should remain admitted in hospital for more intense surveillance because of high risk for development of clinical complications * Expand the understanding of the interactions between physiology and immunology for the design of future projects and general knowledge Hypothesis Development of a risk model based on a combination of physiological and immunological parameters can contribute to early detection of patients at risk for clinical complications after anti-cancer treatment.

Patients going through medical or surgical cancer treatment have a joined risk for clinical complications after treatment. Complications are often discovered too late because patients are checked on periodically during hospitalization, but it is estimated that at least 40% of these complications can be prevented if they are discovered in time. Yet this requires the development of new methods for patient monitoring. Immunologic and physiologic monitoring show promising results, because activation of the immune system is either a consequence to a clinical complication (e.g. infection), or on its own pathological (e.g. systemic inflammatory response syndrome (SIRS), and cytokine release syndrome (CRS)). Therefor the purpose of this study is to combine three research projects to further the understanding physiological and immunological pathways, and attempt to improve patient monitoring, in hopes of raising patient care levels and enhance clinical outcomes. The research projects are as follows: * WARD (''Wireless Assessment of Respiratory and circulatory Distress''). A continuous wireless surveillance of patient vital signs in real time. Time stamped data facilitate comparing of patterns of more than one vital sign. WARD clinical support system is developed and tested on \> 3.000 patients with more than 250.000 hours of recordings since 2016. * Phase one unit. An acknowledged clinical research unit where advanced cancer immune therapy is administered safely and under close observation. Thus, patients can safely be admitted for days to weeks and supervised for development of any clinical complications which make intervention possible in time. The unit has a high patient volume which guarantees a high inclusion rate and is a unique opportunity to conduct advanced project in a controlled environment, which is essential for the project machine-learning methodology * TruCulture and Duraclone. High dimensional immune phenotyping as well as standardised testing system study the immune function in blood after ex vivo stimulation from selected host response pathways, and measuring of plasma levels for pro- and anti-inflammatory markers for systemic inflammation (TNF-alpha, interleukins, CRP etc.) The project group has until now focused on the surgical trauma as a standardized stimulation of the immune system, where development of clinical complications can be related to measurements before and after the trauma. This stands in opposition to most other illnesses, where patients are first seen by a healthcare worker when the illness has occurred. In this joined project the three projects previously mentioned will be combined to make a unique description of the development of clinical complications or the absence hereof in relation to treatment of haematological malignancies with antigen receptor stimulation. The project will be based on the previous decades' development of anti-cancer treatments, where focus has shifted from chemotherapy to biological targeted treatments. An example hereof is small molecules that affects intracellular pathways (Kinase inhibitor) and antibody treatments targeting cancer specific surface molecules \[7\]. In the past five years has the development taken a rapid leap with some kinds of immune therapy, especially chimeric antigen receptor T-cell treatment (CART) and T-cell engaging bispecific antibodies (BsAbs). With these new treatment options comes other side effects and these T-cell antigen treatments are no exception. The most common side effect to CART and BsAbs is cytokine release syndrome (CRS). It is seen in \> 50% of the treated patients within the first month of treatment. CRS is a hyperinflammatory syndrome, that occurs when a series of cytokine sand chemokines are released by T-cell activation and -recruitment. The syndrome ranges from monosymptomatic fever (grade 1) but is often accompanied by hypoxia and/or hypotension (grade 2). CRS grade three to four include affection of vital organs, which can possibly develop into an irreversible condition. The treatment entails antipyretics, adrenocorticotropic hormone in the early phases, and more advanced monoclonal antibodies in cases of CRS grade two to four. The definition and grading of CRS is based on the presence of fever and the grade of hypoxia and hypotension, thus based on thresholds for vital signs and without the use of immunologic markers. The early detection of signs for CRS will enable early onset of treatment which subsequently can halt the development of the condition. Risk factors for the development of severe CRS are described but the predictive value is low. The level of inflammatory cytokines is correlated to the severity of CRS but these cytokines (CRP, IL-6 etc.) significantly increase hours to days after the development of the clinical syndrome, which make not suitable for evaluating the need for hospitalization and/or treatment for CRS. Early onset markers for the development of CRS are therefor clinical signs of systemic inflammation, e.g. rise in temperature, decrease in blood pressure, desaturation, and likely tachycardia. Thus, the combination of CART and BsAbs treatment, the WARD project and immune profiling is a unique opportunity to improve this field and potentially have great impact on patients' outcome. Statistical analysis plan: * Descriptive univariate analysis between potentially predictive variables and CRS * Descriptive analysis of vital signs development during immunotherapy * Developing a risk model with a 90% certainty, measured as 0.9 area under the curve (AUC), using regression analysis that identifies patients at risk of severe clinical complications within 30 days after anti-cancer treatment * Developing a risk model with a 90% certainty, measured as 0.9 area under the curve (AUC), using regression analysis that identifies patients without risk of severe clinical complications within 30 days after anti-cancer treatment * Patient and nurse experiences from continuous vital sign monitoring during immunotherapy