Hyerang Roh(1)(2), Hankil Son(2), Donghwan Lee(2), Young Deuk Choi(3), Kyungsoo Park(2)
(1) Yonsei University College of Medicine, Seoul, Korea Supported by Brain Korea 21 Plus Project for Medical Science, Yonsei University, (2) Department of Pharmacology, College of Medicine, Yonsei University, Seoul, Korea, (3) Department of Urology, College of Medicine, Yonsei University, Seoul, Korea
Objectives: Nocturia occurs in about 70% of the elderly, lowering the quality of life seriously. However, due to the lack of understanding of the disease and objective tool, drug effects have been evaluated based on empirical bases. [1-4] This study aimed to quantitatively characterize the diurnal pattern of nocturia’s main symptoms and to develop a model for quantitative assessments of drug effects given routine clinical data.
Methods: Data were collected from Frequency Volume Chart of 20 male outpatients with severe nocturia (≥ 3 urinations/night) evaluated over 3 periods, before treatment (Period 1), after 1 month of mono-therapy of tamsulosin (Period 2), and after 3 months of combination therapy of tamsulosin and solifenacin (Period 3). The urination frequency (FREQ) and the average urine volume per void (FBC, functional bladder capacity) for every 2 hour interval within the 24 hour period were analyzed as ordered categorical variables with differential odds models after being categorized. The model was chosen by maximizing the joint likelihood of the two categorical variables using NONMEM 7.2. The joint ordered categorical model thus built was used to describe the data, where no-urination category was analyzed in the frequency model only, as it was redundant in the volume model [5, 6].
Results: Each variable was divided into 3 categories, 0, 1, 2 urinations for FREQ, and <100, 100-200, ≥200 mL for FBC. For period 1, the baseline logit was best described by a constant (category ≥ 1) decreased by a circadian function with 24-hr period (category ≥ 2) for FREQ, and a circadian one with 12-hr period decreased by a constant for FBC. Drug effects for FREQ were best described by an exponential decay (period 2) plus an additional constant (period 3) added to the baseline logit, allowing for a change in the baseline mesor for period 3 for FBC, yielding 0.17/hr and -0.34 for exponential decay rate and additional constant decrease for FREQ and 40% increase in the mesor for FBC. When drug effects were assessed by symptom improvements in nocturia, the probability of no-urination category at nighttime increased from 16% up to 44% and 52% in period 2 and 3, respectively, while that of large FBC category increased from 26% up to 41% in period 3.
Conclusions: These results demonstrate the feasibility of applying the proposed method to quantitative understanding of nocturia characteristics and objective assessment of drug effects with less cost and greater accessibility.
References:
[1] Haylen BT, de Ridder D, Freeman RM, et al. An International Urogynecological Association(IUGA)/International Continence Society (ICS) joint report on the terminology for female pelvic floor dysfunction. Neurourol Urodyn. 2010;29(1):4–20
[2] Bosch JL, Weiss JP. The prevalence and causes of nocturia. J Urol. 2010;184(2):440–6
[3] Tikkinen KA, Johnson 2nd TM, Tammela TL, et al. Nocturia frequency, bother, and quality of life: how often is too often? A population-based study in Finland. Eur Urol. 2010;57(3):488–96.
[4] Zhang X, Zhang J, Chen J, et al. Prevalence and risk factors of nocturia and nocturia-related quality of life in the Chinese population. Urol Int. 2011;86(2):173–8.
[5] Kjellsson MC, Zingmark PH, Jonsson EN, Karlsson MO., Comparison of proportional and differential odds models for mixed-effects analysis of categorical data., J Pharmacokinet Pharmacodyn. 2008 Oct;35(5):483-501
[6] Pharmacometrics(2007), Ene I. Ette, 24. Pharmacometrics PK/PD Analysis of Binary (Logistic) Outcome Data & 25. Population Pharmacokinetic/ Pharmacodynamic Modeling of Ordered Categorical Longitudinal Data
Reference: PAGE 23 () Abstr 3195 [www.page-meeting.org/?abstract=3195]
Poster: Drug/Disease modeling - Other topics