Differential diagnosis of reactive arthritis in a patient with intravesical BCG immunotherapy

Aguridă, Aida Roxana; Sîrbu, Cristina Maria; Neguț, Alina Cristina; Moțoi, Maria Magdalena; Bradu, Luminița Mariana; Popescu, R.; Nițulescu, Andrei; Streinu‐Cercel, Anca; Streinu‐Cercel, Adrian

doi:10.1186/1471-2334-14-s7-p25

Cited by 2 publications

(1 citation statement)

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“…In particular, BCG efficacy is limited by its potential adverse reaction profile showing a cause of side-effects for approximately 90% of patients affected with bladder cancer [12], [29]. Recently, Roxana Aguridǎ et al [3] reported many kind of BCG side-effects including arthritis for a 50 years-old female patient affected with bladder cancer, operated in January 2014. On the other hand, research on urology reported in several papers that the optimal dose of BCG, its maintenance schedule and duration of its treatment, are yet unknown [1].…”

Section: Overview On Bacillus Calmette-guérin (Bcg)mentioning

confidence: 99%

A Stochastic Optimal Control Model for BCG Immunotherapy in Superficial Bladder Cancer

Aboulaïch

Darouichi

Elmouki

et al. 2017

Math. Model. Nat. Phenom.

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Urologic studies have reported in several papers that the optimal dose of Bacillus Calmette-Guérin (BCG) immunotherapy in superficial bladder cancer, is still a subject of research. Our main goal from this paper, is to find treatment regimens that minimize the total number of tumors in the presence of a diffusion process. For this, we devise a stochastic model in the form of a nonlinear system of four stochastic differential equations (SDEs) that describe tumor-immune dynamics after BCG instillations. Therefore, we study the existence and the stability results. Then, we introduce a control function in the mathematical model, to represent the dose of BCG intravesical therapy, and we seek its optimal values through the application of a stochastic version of Pontryagin's maximum principle. Finally, we present some numerical simulations using iterative stochastic Runge-Kutta progressive-regressive schemes which we propose for solving the optimality system of the obtained stochastic two-point boundary value problem.

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