Hypothesis / aims of study
Pollen has anecdotally been reported to trigger flares in patients with urologic chronic pelvic pain syndrome (UCPPS), a syndrome that frequently co-exists with allergies. To test the hypothesis that pollen triggers UCPPS flares, we linked local pollen count data with our case-crossover study of flare triggers embedded in the Multidisciplinary Approach to the Study of Chronic Pelvic Pain (MAPP) Epidemiology and Phenotyping longitudinal Study.
Study design, materials and methods
The MAPP Epidemiology and Phenotyping Study was a one-year longitudinal study of UCPPS patients designed to investigate the “usual-care” natural history of UCPPS and to identify patient sub-groups with possible differing etiology and clinical course. It included women with interstitial cystitis/bladder pain syndrome and men with interstitial cystitis/bladder pain syndrome or chronic prostatitis/chronic pelvic pain syndrome. Participants completed a lengthy battery of questionnaires at biannual study visits and a shorter set of questionnaires at biweekly online assessments.
To investigate flare triggers, participants were asked whether they were currently “experiencing a flare of their urologic or pelvic pain symptoms […] meaning symptoms that are much worse than usual” at each biweekly assessment. Participants who responded affirmatively were asked to complete an additional set of questions about their flare symptoms, flare start date, and exposures in the 3 days leading up to their flare. These questions were asked for the first 3 flares and at 3 randomly selected times when participants did not report a flare.
We limited the case-crossover analysis to participants who completed at least one flare and one non-flare assessment (n=290 of 422 participants). Flare and non-flare data were linked to daily pollen count values (obtained from IMS Health) by 3-digit residential zip code. Pollen count levels in the 3 days before (day -1, day -2, and day -3) and the day of a flare (day 0), as well as daily changes in these values, were compared to corresponding non-flare values by conditional logistic regression. Poisson regression was used to estimate flare rates in the 3 weeks following increases in pollen count in the full longitudinal study. Analyses were performed in all participants and separately in those who reported allergies. With a sample size of 290 participants, we had at least 80% power to detect odds ratios as small as 1.6-1.7, assuming 1:1 matching, a prevalence of exposure in controls of 20-30%, a correlation between observations from the same participant of 0.1-0.2, two-sided tests, and an α-level of 0.05.
Interpretation of results
In general, no consistent pattern of associations was observed between pollen count and the onset or frequency of flares.