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. 2016 Nov;196(5):1450-1455.
doi: 10.1016/j.juro.2016.04.070. Epub 2016 Apr 27.

Symptom Variability and Early Symptom Regression in the MAPP Study: A Prospective Study of Urological Chronic Pelvic Pain Syndrome

Alisa J Stephens-Shields  1 , J Quentin Clemens  2 , Thomas Jemielita  3 , John Farrar  3 , Siobhan Sutcliffe  4 , Xiaoling Hou  5 , J Richard Landis  3 ; MAPP Research Network
Collaborators, Affiliations

Symptom Variability and Early Symptom Regression in the MAPP Study: A Prospective Study of Urological Chronic Pelvic Pain Syndrome

Alisa J Stephens-Shields et al. J Urol. 2016 Nov.

Abstract

Purpose: We examined symptom variability in men and women with urological chronic pelvic pain syndrome. We describe symptom fluctuations as related to early symptom regression and its effect on estimated 1-year symptom change. We also describe a method to quantify patient specific symptom variability.

Materials and methods: Symptoms were assessed biweekly in 424 subjects with urological chronic pelvic pain syndrome during 1 year. To evaluate the impact of early symptom regression subjects were classified as improved, no change or worse according to the rate of change using 1) all data, 2) excluding week 0 and 3) excluding weeks 0 and 2. Patient specific, time varying variability was calculated at each interval using a sliding window approach. Patients were classified as high, medium or low variability at each time and ultimately as high or low variability overall based on the variability for the majority of contacts.

Results: Prior to excluding early weeks to adjust for early symptom regression 25% to 38% and 5% to 6% of patients were classified as improved and worse, respectively. After adjustment the percent of patients who were improved or worse ranged from 15% to 25% and 6% to 9%, respectively. High and low variability phenotypes were each identified in 25% to 30% of participants.

Conclusions: Patients with urological chronic pelvic pain syndrome show symptom variability. At study enrollment patients had worse symptoms on average, resulting in a regression effect that influenced the estimated proportion of those who were improved or worse. Prospective studies should include a run-in period to account for regression to the mean and other causes of early symptom regression. Further, symptom variability may be quantified and used to characterize longitudinal symptom profiles of urological chronic pelvic pain syndrome.

Keywords: cystitis; epidemiologic research design; interstitial; pain; prostate; symptom assessment.

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Figures

Figure 1
Figure 1. Defining Time-varying Symptom Variability
For an example patient the pain severity symptom level is plotted for 48 weeks. Example intervals for the calculation of 3 within subject standard deviation measurements in time are shown: σ6, the standard deviation over the first 6 weeks, calculated using data from weeks 0 through 6; σ10 the standard deviation estimate at week 10 calculated from data weeks 4 through 10, and σ48, the standard deviation at week 48, calculated from data weeks 42 through 48.
Figure 2
Figure 2
Mean Symptom Severity at Weeks 0, 2, and 4
Figure 2
Figure 2
Mean Symptom Severity at Weeks 0, 2, and 4
Figure 3
Figure 3. Distribution of 6-Week Standard Deviation of Pain and Urinary Symptoms at Weeks 6, 24 and 48
Boxplots show the distribution of the standard deviation of pain severity (blue) and urinary severity (gold) at weeks 6, 24, and 48.
See this image and copyright information in PMC

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