ABSTRACT
Anemia is prevalent in end-stage renal disease (ESRD). The discovery of recombinant human erythropoietin (rHuEPO) over 30 years ago has shifted the treatment of anemia for patients on dialysis from blood transfusions to rHuEPO therapy. Many anemia management protocols (AMPs) used by clinicians comprise a set of experience-based rules for weekly-to-monthly titration of rHuEPO doses based on hemoglobin (Hb) measurements. In order to facilitate the design of an AMP using model-based feedback control theory, we present a physiologically relevant erythropoiesis model and demonstrate its applicability using clinical data.
Subject(s)
Anemia , Erythropoiesis/drug effects , Kidney Failure, Chronic , Models, Biological , Algorithms , Anemia/drug therapy , Anemia/etiology , Anemia/physiopathology , Drug Monitoring , Erythropoietin/administration & dosage , Erythropoietin/pharmacokinetics , Erythropoietin/pharmacology , Erythropoietin/therapeutic use , Humans , Kidney Failure, Chronic/complications , Kidney Failure, Chronic/drug therapy , Kidney Failure, Chronic/physiopathology , Models, Statistical , Recombinant Proteins/administration & dosage , Recombinant Proteins/pharmacokinetics , Recombinant Proteins/pharmacology , Recombinant Proteins/therapeutic useABSTRACT
Calculation of the therapeutic activity of radioiodine (131)I for individualized dosimetry in the treatment of Graves' disease requires an accurate estimate of the thyroid absorbed radiation dose based on a tracer activity administration of (131)I. Common approaches (Marinelli-Quimby formula, MIRD algorithm) use, respectively, the effective half-life of radioiodine in the thyroid and the time-integrated activity. Many physicians perform one, two, or at most three tracer dose activity measurements at various times and calculate the required therapeutic activity by ad hoc methods. In this paper, we study the accuracy of estimates of four 'target variables': time-integrated activity coefficient, time of maximum activity, maximum activity, and effective half-life in the gland. Clinical data from 41 patients who underwent (131)I therapy for Graves' disease at the University Hospital in Pisa, Italy, are used for analysis. The radioiodine kinetics are described using a nonlinear mixed-effects model. The distributions of the target variables in the patient population are characterized. Using minimum root mean squared error as the criterion, optimal 1-, 2-, and 3-point sampling schedules are determined for estimation of the target variables, and probabilistic bounds are given for the errors under the optimal times. An algorithm is developed for computing the optimal 1-, 2-, and 3-point sampling schedules for the target variables. This algorithm is implemented in a freely available software tool. Taking into consideration (131)I effective half-life in the thyroid and measurement noise, the optimal 1-point time for time-integrated activity coefficient is a measurement 1 week following the tracer dose. Additional measurements give only a slight improvement in accuracy.
Subject(s)
Graves Disease/radiotherapy , Radiation Dosage , Humans , Iodine Radioisotopes/therapeutic use , Kinetics , Nonlinear Dynamics , Radiometry , Radiotherapy Dosage , Retrospective Studies , Time FactorsABSTRACT
Many end stage renal disease (ESRD) patients suffer from anemia due to insufficient endogenous production of erythropoietin (EPO). The discovery of recombinant human EPO (rHuEPO) over 30 years ago has shifted the treatment of anemia for patients on dialysis from blood transfusions to rHuEPO therapy. Many anemia management protocols (AMPs) used by clinicians comprise a set of experience-based rules for weekly-to-monthly titration of rHuEPO doses based on hemoglobin (Hgb) measurements. In order to facilitate the design of an AMP based on formal control design methods, we present a physiologically-relevant erythropoiesis model, and show that its nonlinear dynamics can be approximated using a static nonlinearity, a step that greatly simplifies AMP design. We demonstrate applicability of our results using clinical data.
Subject(s)
Anemia/drug therapy , Anemia/metabolism , Drug Therapy, Computer-Assisted/methods , Erythropoiesis/drug effects , Erythropoietin/administration & dosage , Kidney Failure, Chronic/drug therapy , Kidney Failure, Chronic/metabolism , Anemia/etiology , Computer Simulation , Erythropoietin/metabolism , Hemoglobins/analysis , Humans , Kidney Failure, Chronic/complications , Models, Biological , Treatment OutcomeABSTRACT
The thyroid, the largest gland in the endocrine system, secretes hormones that help promote bodily growth and development. This gland regulates hormonal secretion rate in spite of changes in dietary iodine which is a key ingredient in the hormone's biosynthesis. The thyroid relies on several feedback mechanisms for this regulation, and in this paper we use recent molecular-level and clinical observations to engineer a computational thyroid model. We use simulation and analysis to show that this models captures known aspects of thyroid physiology. We identify features in the model that are responsible for hormonal regulation, and use the model to identify and evaluate competing hypotheses associated with Wolff-Chaikoff escape.
