Localised Model-Based Active Controlling of Blood Flow During Chemotherapy to Prevent Nail Toxicity and Onycholysis

Preventing taxane-related peripheral neuropathy, pain and nail toxicity: a prospective self-controlled trial comparing hilotherapy with frozen gloves in early breast cancer

PURPOSE

The prevention of taxane-related toxicities at the extremities is highly important for patients' treatment and quality-of-life. Several studies endorse hand/foot-cooling using frozen gloves as a prophylactic intervention. Unlike frozen gloves, hilotherapy produces cooling at a constant temperature. Comparative data with frozen gloves are unavailable.

METHODS

This prospective self-controlled study explores the efficacy of hilotherapy at the right hand and foot compared to frozen gloves at the left in patients with early breast cancer treated with weekly paclitaxel 80 mg/m² or three-weekly docetaxel 75 mg/m². Patient-reported outcomes were collected at baseline, 6, 12, 18 and 24 weeks after the start of treatment. Primary and secondary endpoints were the incidence of any-grade and ≥ grade 2 side-effects (peripheral neuropathy, pain and nail toxicities), and perceived comfort of both interventions.

RESULTS

Sixty-two patients participated. The incidence of any-grade side-effects was similar on both sides, 85.5% with hilotherapy and 90.3% with frozen gloves (p = 1.000). The incidence of ≥ grade 2 side-effects at the extremities was significantly lower with hilotherapy: 43.6% compared to 61.3% with frozen gloves (p = 0.013). Perceived comfort was significantly better for hilotherapy than for frozen gloves (p < 0.0001).

CONCLUSIONS

Compared to frozen gloves, continuous cooling of hands and feet using hilotherapy produces better prevention of ≥ grade 2 patient-reported side-effects at the extremities (peripheral neuropathy, pain and nail toxicities). Perceived comfort was significantly better for hilotherapy. From a clinical and patient perspective, hilotherapy is a better alternative for preventing clinically significant taxane-related side-effects.

Optimal control methods for drug delivery in cancerous tumour by anti-angiogenic therapy and chemotherapy

There are numerous mathematical models simulating the behaviour of cancer by considering variety of states in different treatment strategies, such as chemotherapy. Among the models, one is developed which is able to consider the blood vessel‐production (angiogenesis) in the vicinity of the tumour and the effect of anti‐angiogenic therapy. In the mentioned‐model, normal cells, cancer cells, endothelial cells, chemotherapy and anti‐angiogenic agents are taking into account as state variables, and the rate of injection of the last two are considered as control inputs. Since controlling the cancerous tumour growth is a challenging matter for patient's life, the time schedule design of drug injection is very significant. Two optimal control strategies, an open‐loop (calculus of variations) and a closed‐loop (state‐dependent Riccati equation), are applied on the system in order to find an optimal time scheduling for each drug injection. By defining a proper cost function, an optimal control signal is designed for each one. Both obtained control inputs have reasonable answers, and the system is controlled eventually, but by comparing them, it is concluded that both methods have their own benefits which will be discussed in details in the conclusion section.

Model-Based Monitoring of Occupant’s Thermal State for Adaptive HVAC Predictive Controlling

Conventional indoor climate design and control approaches are based on static thermal comfort/sensation models that view the building occupants as passive recipients of their thermal environment. Recent advances in wearable sensing technologies and their generated streaming data are providing a unique opportunity to understand the user’s behaviour and to predict future needs. Estimation of thermal comfort is a challenging task given the subjectivity of human perception; this subjectivity is reflected in the statistical nature of comfort models, as well as the plethora of comfort models available. Additionally, such models are using not-easily or invasively measured variables (e.g., core temperatures and metabolic rate), which are often not practical and undesirable measurements. The main goal of this paper was to develop dynamic model-based monitoring system of the occupant’s thermal state and their thermoregulation responses under two different activity levels. In total, 25 participants were subjected to three different environmental temperatures at two different activity levels. The results have shown that a reduced-ordered (second-order) multi-inputs-single-output discrete-time transfer function (MISO-DTF), including three input variables (wearables), namely, aural temperature, heart rate, and average skin heat-flux, is best to estimate the individual’s metabolic rate (non-wearable) with a mean absolute percentage error of 8.7%. A general classification model based on a least squares support vector machine (LS-SVM) technique is developed to predict the individual’s thermal sensation. For a seven-class classification problem, the results have shown that the overall model accuracy of the developed classifier is 76% with an F1-score value of 84%. The developed LS-SVM classification model for prediction of occupant’s thermal sensation can be integrated in the heating, ventilation and air conditioning (HVAC) system to provide an occupant thermal state-based climate controller. In this paper, we introduced an adaptive occupant-based HVAC predictive controller using the developed LS-SVM predictive classification model.