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Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment
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Journal of Pediatric Urology (xxxx) xxx xxx
Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment Department of Urology, University of California, San Francisco, USA
T.W. Gaither, H.L. Copp * Summary
* Corresponding author. Mission Hall Pediatric Urology, 1825 4th Street 5th Floor, San Francisco, CA, 94143, USA.Tel/fax: 415 353 2083. [email protected] (H.L. Copp) Keywords Adherence; Bladder and bowel dysfunction; Continuous antibiotic prophylaxis; Renal scarring; Urinary tract infection; Vesicoureteral reflux Received 2 January 2019 Accepted 23 April 2019 Available online xxx
Background Continuous antimicrobial prophylaxis (prophylaxis) is associated with a reduction in recurrent urinary tract infections in children with vesicoureteral reflux. However, adherence to daily medications has been shown to be poor. Objective To determine patient/caregiver factors associated with non-adherence and to determine whether adherence alters the effect of prophylaxis on recurrent UTIs and renal scarring. Study design We conducted a secondary analysis of the Randomized Intervention for Children with Vesicoureteral Reflux trial. We stratified adherence scores into quartiles to assess trends within the data. We assessed predictors of non-adherence using ordinal logistic regression. We then examined the efficacy of prophylaxis stratified by adherence quartiles. Results Six hundred patients were included in the analysis. The quartiles of adherence were as follows: 1st quartiled0e70% adherence; 2nd quartiled71e91%
adherence; 3rd quartiled92e96% adherence; and 4th quartiled>96% adherence. Neither demographic factors nor disease severity was associated with non-adherence. In the subanalysis of patients who were toilet trained at baseline, increasing bladder and bowel dysfunction (BBD) symptom score was associated with non-adherence (adjusted odds ratio, aOR Z 1.1, 95% confidence interval [CI] 1.0e1.2). Patients least adherent were 2.5 times more likely (95%CI 1.1e5.6) to have a recurrent UTI compared with patients most adherent. After controlling for treatment arm, age, sex, degree of reflux, BBD, and number of UTIs, patients least adherent (taking the study medication less than <70% of the time) were at highest risk for renal scarring (aOR Z 24.2, 95%CI 3.0e197). In contrast, among the most adherent quartile, the probability of renal scarring was highest in those assigned prophylaxis (16.2% compared with 1.7% in those most adherent to placebo).
Conclusions Adherence is distinctly related to clinical outcomes in children with VUR. Non-adherence is common and represents a distinct clinical entity that is associated with renal scarring. Adherence should be assessed in prophylaxis management algorithms.
Summary Figure Adjusteda predicted probabilities for recurrent UTIs and renal scarring stratified by adherence quartileb. a Models adjusted for: age, sex, reflux status, BBD status, and number of prior UTIs. b Adherence quartiles: 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. BBD, bladder and bowel dysfunction. https://doi.org/10.1016/j.jpurol.2019.04.019 1477-5131/ª 2019 Published by Elsevier Ltd on behalf of Journal of Pediatric Urology Company.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Introduction Continuous antimicrobial prophylaxis (prophylaxis) has been a longstanding management strategy for children with VUR and recurrent UTIs [1]. In the Randomized Intervention for Children with Vesicoureteral Reflux (RIVUR) trial, prophylaxis was associated with a two-fold reduction in risk for recurrent UTIs in this population [2]. However, the intervention arm did not reduce the incidence of new renal scars (11.9% versus 10.2%), which is thought to represent longer term sequela of childhood UTIs [3]. Consequently, the benefits of prophylaxis beyond preventing the morbidity of recurrent UTIs have been questioned. Additionally, daily antibiotic exposure has been associated with certain risks, including harboring drug resistant organisms and weight gain [4,5]. Adherence rates for daily medications, including antibiotics, are poor [6]. This can be especially challenging for pediatric populations where other factors, such as medication taste or family stressors, can affect adherence [7,8]. Wide ranges in adherence rates specifically for prophylaxis in children with VUR have been reported varying anywhere from 40 to 90% depending on measurement method and patient population [9,10]. Adherence is an important factor in antibiotic efficacy [11]. Although evidence from randomized trials show benefit of prophylaxis in children with VUR, we hypothesize this benefit is maximized in patients adherent to the medication. We performed a secondary analysis of the RIVUR trial and had three specific aims: (1) what is the rate of non-adherence within the RIVUR trial? (2) which patient/caregiver factors predict nonadherence?, and (3) does adherence alter the effect of prophylaxis on recurrent UTIs and renal scarring?
Methods Study population We used data available from the National Institute of Diabetes and Digestive and Kidney Disease from the RIVUR trial [2]. The RIVUR trial is a double-blinded, randomized, placebo-controlled trial studying antibiotic prophylaxis to prevent recurrent UTI in patients with grade 1e4 VUR. The study included children after an index febrile or symptomatic UTI between the ages of 2e72 months. Enrolled children were followed for 2 years. Each child was randomized to trimethoprim-sulfamethoxazole (TMP-SMX) or placebo at baseline.
Main outcome and secondary outcomes Adherence was measured via patient questionnaires at each study visit (every 2 months for 2 years). Supplemental Table 1 demonstrates the adherence question with possible patient answers. Because there is no standard definition of non-adherence, we stratified adherence scores into quartiles to assess trends within the data. Quartile categorization allows for an equal number of individuals in each group, which improves statistical precision and provides more overlap of covariates. The average adherence score
T.W. Gaither, H.L. Copp was calculated by summing all adherence scores and dividing by the number of assessments. Secondary outcomes included recurrent UTIs and new renal scarring as defined by the RIVUR protocol [2]. In this analysis, adherence quartiles were used to define possible cut-offs where patients are at risk for recurrent UTIs or renal scarring.
Possible risk factors Patient and caregiver demographics including age at study enrollment (months), sex (female versus male), race/ ethnicity (White/Caucasian, Black/African American, Asian/Asian American, Hispanic/Latino, or other/unknown), prophylaxis assignment (TMP-SMX versus placebo), and education level (high school graduate or lower, some college or 2-year degree/certificate, or college graduate or higher) were collected. We also tested disease severity as measured by the number of previous UTIs (one versus two), whether the previous UTIs were symptomatic and febrile versus not symptomatic or febrile, and baseline bladder and bowel dysfunction (BBD) symptoms. These factors were chosen as these most likely represent tangible symptoms perceived by family members. Bladder and bowel dysfunction was assessed using the dysfunctional voiding questionnaire (DVQ) score [12]. The exact form used in the study can be found in the supplemental material in the original RIVUR publication [2]. Bladder and bowel dysfunction was defined as a score greater than or equal to 6 in female subjects and defined as a score greater than or equal to 9 for male subjects, as per the developers of the study [12,13]. Baseline BBD symptoms were measured by the DVQ score. The DVQ score was only assessed in toilettrained children and was thus a subanalysis of the sample (n Z 123).
Statistical analysis All analyses were performed in Stata v.13 (College Station, TX). We used ordinal logistic regression to determine the independent effects of the risk factors on the study outcome (non-adherence by quartile). The authors repeated the model in those who were toilet-trained only (n Z 123) to assess the effect of BBD symptoms on nonadherence. For our secondary analysis, we performed multivariate logistic regression to determine risk for a recurrent UTI and renal scarring stratified by adherence quartiles. We included an interaction between prophylaxis status and adherence quartiles. We performed an adjusted analysis to improve precision based on factors associated with recurrent UTI and renal scarring risk, including age, sex, dilating VUR, BBD status, and whether or not they had two prior UTI (versus one prior UTI), which is based on previous literature [14]. We presented adjusted predicted probabilities for recurrent UTI and renal scarring based on adherence quartile and stratified by prophylaxis status. All statistical tests were two-sided and P-values less than 0.05 were considered statistically significant. The institutional review board provided exempt status for the secondary data analysis.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs
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Results
Efficacy analysis
600/607 (98.8%) patients had adherence scores available for analysis. The quartiles of adherence were as follows: 1st quartiled0e70% adherence (n Z 150); 2nd quartiled71e91% adherence (n Z 150); 3rd quartiled92e96% adherence (n Z 159); 4th quartiled>96% adherence (n Z 141). We found no significant differences in adherence quartile between those assigned to prophylaxis vs placebo. Table 1 shows the demographic and clinical characteristics of patients stratified by adherence quartile. We found no statistical differences among demographic or clinical characteristic measures. The median DVQ score was higher among patients who were nonadherent (9 vs 4, P Z 0.19), but this did not reach statistical significance in the univariable models.
The results of the logistic model by quartile of adherence scores can be found in Table 3. Dilating reflux (aOR Z 1.9, 95% CI 1.2e3.0) and number of prior UTIs (aOR Z 2.0, 95% CI 1.0e3.9) were risk factors for recurrent UTIs. In this model, prophylaxis was not associated with a reduction of recurrent UTIs (aOR Z 0.5, 95%CI 0.2e1.5). Patients least adherent were 2.5 times more likely (95%CI 1.1e5.6) to have a recurrent UTI compared with patients most adherent. There was a non-significant interaction between adherence quartiles and prophylaxis status (P Z 0.07). After controlling for treatment arm, age, sex, degree of reflux, BBD, and number of UTIs, patients least adherent (taking the study medication less than 70% of the time) were at highest risk for renal scarring (aOR Z 24.2, 95%CI 3.0e197). In addition, patients with dilating reflux at baseline (aOR Z 2.5, 95%CI 1.3e5.0) and two prior UTIs (aOR Z 2.8, 95%CI 1.1e7.0) were at risk for renal scarring. Prophylaxis was also associated with an increased risk of renal scarring (aOR Z 12.9, 95%CI 1.5e109). Fig. 1 shows the adjusted predicted probabilities of recurrent UTIs and renal scarring by adherence quartile. Among patients in both the placebo and prophylaxis groups, there was a significant interaction between adherence quartiles and renal scarring (P Z 0.001). In the placebo group, a dose-response relationship is observed among adherence quartiles and renal scarring, ranging from 1.7%
Risk factor analysis The results of the multivariable analysis can be seen in Table 2. Using all patients in the sample, the adjusted estimates were non-significant. Neither demographic factors nor disease severity was associated with non-adherence. In the subanalysis of patients who were toilet trained at baseline, DVQ score was associated with non-adherence (aOR Z 1.1; 95% confidence interval [CI] 1.0e1.2). Thus, for every 10-point increase on the DVQ score, odds of increasing non-adherence quartiles increase by 2.0 (95%CI 1.1e3.9).
Table 1
Demographic and clinical characteristics of antimicrobial prophylaxis by adherence quartilea.
Demographic and clinical variables Demographics Infant, n(%) Sex, n(%) Female Race/ethnicity, n(%) White/Caucasian Black/African American Asian/Asian American Hispanic/Latino Other/unknown Caregiver education, n(%) High school graduate or lower Some college or 2-year degree College graduate or higher Clinical characteristics Assigned to CAP, n(%) Prior UTI’s, n(%) Two One Prior UTI symptomatic and febrile, n(%) DVQ score, median (IQR) n Z 126 BBD at baseline, n(%) n Z 126
4th quartile (most adherent) n Z 141
3rd quartile n Z 159
2nd quartile n Z 150
1st quartile (least adherent) n Z 150
P-value
76 (54)
90 (57)
75 (50)
74 (49)
0.54
128 (91)
143 (90)
139 (93)
141 (94)
0.56
101 (72) 5 (4) 2 (1) 14 (10) 18 (13)
114 (72) 6 (4) 6 (4) 16 (10) 16 (10)
104 (69) 7 (5) 5 (3) 12 (8) 22 (15)
112 (75) 5 (3) 4 (3) 10 (7) 19 (13)
0.96
38 (28) 24 (17) 76 (55)
35 (22) 39 (25) 84 (53)
41 (27) 50 (33) 59 (39)
41 (27) 42 (28) 67 (45)
0.03
74 (52)
77 (48)
78 (52)
70 (47)
0.70
8 (6) 133 (94) 96 (68) 4 (2e11) 9 (43)
13 (8) 146 (92) 103 (65) 6 (3e9) 16 (53)
13 (9) 137 (91) 106 (71) 6 (3e12) 21 (62)
18 (12) 132 (88) 102 (68) 9 (5e14) 24 (60)
0.29 0.74 0.19 0.52
BBD, bladder and bowel dysfunction; DVQ, dysfunctional voiding questionnaire. a 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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T.W. Gaither, H.L. Copp Ordinal logistic regression analysis for factors associated with antimicrobial prophylaxis non-adherence quartilesa.
Demographic and clinical variables Demographics Infant, n(%) Sex, n(%) Female Race/ethnicity, n(%) White/Caucasian Black/African American Asian/Asian American Hispanic/Latino Other/unknown Caregiver education, n(%) High school graduate or lower Some college or 2-year degree College graduate or higher Clinical characteristics Assigned to CAP, n(%) Prior UTI’s, n(%) Two One Prior UTI symptomatic and febrile, n(%) DVQ score (continuous)
Non-adherent aOR (95%CI) All patients
Non-adherent aOR (95%CI) Toilet-trained only
0.9 (0.7e1.2)
e
1.3 (0.7e2.2)
1.3 (0.04e41)
1.0 0.9 1.4 0.7 1.0
1.0 0.9 2.5 1.6 1.0
(reference) (0.4e1.9) (0.6e3.3) (0.4e1.2) (0.6e1.6)
(reference) (0.1e8.6) (0.3e24) (0.5e4.7) (0.3e3.2)
1.0 (reference) 1.3 (0.8e1.9) 0.7 (0.5e1.1)-
1.0 (reference) 0.8 (0.3e2.1) 0.5 (0.2e1.2)
0.9 (0.7e1.2)
1.6 (0.8e3.1)
1.6 (0.9e2.6) 1.0 (reference) 1.0 (0.7e1.4) e
1.9 1.0 0.9 1.1
(0.8e4.2) (reference) (0.3e3.3) (1.0e1.2)b
CI, confidence interval; DVQ, dysfunctional voiding questionnaire. a 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. b For every 10 points on DVQ score, odds of increasing non-compliant quartile is 2.0 (1.1e3.9).
predicted probability of scarring in the 1st quartile (most adherent in placebo group) to 26.3% predicted probability of scarring in the 4th quartile (least adherent in placebo group). In the prophylaxis group, we observe a u-shape distribution with highest predicted probability of scarring in the 1st quartile (most adherent in prophylaxis group) at 16.8% and second highest predicted probability of scarring in the 4th quartile (least adherent in prophylaxis group) at 16.2%.
Discussion Antibiotic prophylaxis has been a long-standing management strategy for patients with recurrent UTIs and concurrent VUR BBD. Although the RIVUR study, which is a well-conducted randomized trial of antibiotic prophylaxis, showed significant reduction in recurrent UTIs, the results of the current study show that the efficacy of antibiotic prophylaxis in prevention of UTI and renal scarring may be influenced by adherence in a manner not previously recognized. First, after adjusting for non-adherence, the protective effect of prophylaxis on recurrent UTIs was diminished. Second, extreme non-adherence (taking the study medication <70% of the time) is a risk factor for renal scarring. Third, in the most adherent subgroup, antibiotic prophylaxis is associated with renal scarring. The results of this study should be shared among parents and decisionmakers of children who are being considered for prophylaxis. Studies of UTIs in children should incorporate adherence, as extreme non-adherence may represent an important clinical phenotype. Additionally, the study has
implications for more frequent follow-up in patients on prophylaxis to assess for non-adherence. Approximately 25% of patients in the RIVUR trial took the study medication less than 70% of the time (quartile 1). It is estimated that 20e50% of patients do not take chronic medication as prescribed [15]. In a national study of patients with VUR specifically, Copp et al. estimated the nonadherence rate to be approximately 60% [9]. As the results in the current study are from a randomized trial, one would expect the adherence to be higher than the general population. In another study of 54 patients on prophylaxis, adherence was measured by urine chromatography, which showed a 91% adherence rate [10]. The differences observed could be because of a selected population, delayed antibiotic clearance in the urine, or that patients may be more likely to take their medication before seeing a provider. Patient adherence is difficult to measure and has been measured by self-report, pharmacy refill records, and/or the use of electronic lids [16]. As self-report tends to overestimate actual usage, the results in this study may be conservative estimates [17]. We found that neither demographic factors nor disease severity put patients at risk for non-adherence. In general, prescriptions by pediatricians are among the highest rates for filled medications (w87%) with parents of younger children more likely to get the prescription [18]. This concept has been shown in patients prescribed prophylaxis, as younger children, those more frequently hospitalized, and specialist visits were associated with prophylaxis adherence [9]. We anticipated replicating these findings; however, we found no associations between age or disease severity and non-adherence. The point estimate of infants
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs Table 3
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Multivariable logistic model of clinical outcomes by adherence quartiles.
Demographic and clinical variables Age Infant Non-infant Sex Female Male Reflux at baseline Dilating reflux Non-dilating reflux BBD during study Yes No Prior UTI’s 2 1 Treatment arm Prophylaxis Placebo Adherence levels 1st quartile (least adherent) 2nd quartile 3rd quartile 4th quartile (most adherent) Interaction (prophylaxis*adherence level)b Prophylaxis þ 1st quartile (least adherent) Prophylaxis þ 2nd quartile Prophylaxis þ 3rd quartile Prophylaxis þ 4th quartile (most adherent)
Recurrent UTI aOR (95% CI)
Renal scarring aOR (95% CI)
0.9 (0.5e1.4) 1.0 (reference)
0.4 (0.2e0.8)a 1.0 (reference)
2.1 (0.7e6.3) 1.0 (reference)
0.6 (0.2e1.9) 1.0 (reference)
1.9 (1.2e3.0)a 1.0 (reference)
2.5 (1.3e5.0)a 1.0 (reference)
1.6 (0.9e2.7) 1.0 (reference)
1.6 (0.8e3.3) 1.0 (reference)
2.0 (1.0e3.9)a 1.0 (reference)
2.8 (1.1e7.0)a 1.0 (reference)
0.5 (0.2e1.5) 1.0 (reference)
12.9 (1.5e109)a 1.0 (reference)
2.5 1.4 1.2 1.0
(1.1e5.6)a (0.6e3.2) (0.5e2.7) (reference)
24.2 (3.0e197)a 6.1 (0.7e56) 3.7 (0.4e35) 1.0 (reference)
1.3 0.4 0.8 1.0
(0.4e4.6) (0.1e1.8) (0.2e3.1) (reference)
0.04 (0.004e0.4) 0.07 (0.005e0.8) 0.1 (0.01e1.4) 1.0 (reference)
CI, confidence interval; DVQ, dysfunctional voiding questionnaire; BBD, bladder and bowel dysfunction. a P < 0.05. b Test for multiplicative interaction: recurrent UTI adherence quartile (P Z 0.07); renal scarring adherence quartile (P Z 0.001).
compared with non-infants showed a protective effect (aOR Z 0.9). We may not have been powered to detect a difference in this secondary analysis. Interestingly, patients with higher DVQ scores were at risk for non-adherence. To the authors knowledge, this represents a novel association not previously described in the literature. This association could be spurious or due to uncontrolled confounding, such as psychosocial distress in the home. For example, parenting stress has been significantly correlated with voiding dysfunction [19]. At the same time, parental stress has been linked to poorer medication adherence [8]. The relationship between prophylaxis non-adherence in patients with more severe BBD symptoms merits further study, especially since BBD is one of the strongest risk factors for recurrent UTIs [14]. Renal scarring occurs in approximately 15% of children after a first, febrile UTI [20]. Factors that predispose patients to renal scarring include high-grade VUR, recurrent UTIs, and the severity of the infection itself (high-grade fever, organisms other than E. coli, polymorphonuclear cell count of more than 60%) [14,21]. Delayed treatment has also been associated with renal scarring [22,23]. We report that non-adherence, especially those in the bottom quartile (adherent less than 70% of the time), is an independent risk factor for renal scarring. In fact, non-adherence had a larger effect size (point estimate aOR Z 24.2) than other
risk factors previously identified, such as dilating reflux (aOR Z 2.5) and prior UTIs (aOR Z 2.9). This is also apparent in the lower quartile point estimates. We also observed a doseeresponse relationship among quartiles of adherence and renal scarring in the placebo group, suggesting that this effect represents something independent of the medication itself. There is a statistically significant interaction between non-adherence and prophylaxis status, which suggests the effects of non-adherence depends on whether the child was taking prophylaxis or the placebo. Non-adherence may represent a social phenomenon, such as delayed presentation. Previous literature has shown children who were treated within 3 days of their symptoms were 1/3 as likely to scar as those whose symptoms lasted longer (OR Z 0.33, 95% CI 0.12e0.72) [24]. Providers may use non-adherence as a way to risk stratify those who may be at higher risk for renal scars. Psychosocial factors were not assessed in this study but should be taken into account in future studies. The u-shaped phenomenon among adherence quartiles and renal scarring in the prophylaxis group warrants comment. After adjustment, patients most adherent (>96% of the time taking the study medication) to prophylaxis had a predicted probability of renal scarring of 16.8%, which is compared with 1.7% of patients on placebo in the most adherent group. One explanation for this finding is that
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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T.W. Gaither, H.L. Copp
Fig. 1 Adjusteda predicted probabilities for recurrent UTIs and renal scarring stratified by adherence quartileb. a Models adjusted for: age, sex, reflux status, BBD status, and number of prior UTIs. b Adherence quartiles: 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. BBD, bladder and bowel dysfunction.
increased antibiotic exposure places these adherent patients most at risk for drug resistant organisms during a breakthrough UTI. Drug resistance is a known side-effect of prophylaxis [4]. For every 21 patients with VUR treated with prophylaxis, 1 patient is estimated to develop a multidrugresistant organism [25]. Longer duration of antibiotics and multiple courses are associated with higher rates of resistance [26]. For plausibility of this theory, we performed a post-hoc analysis of resistant organisms in this subgroup (most adherent quartile). In the most adherent group, 5/7 (71%) of patients had a resistant organism to TMP/SMZ in the prophylaxis group and 3/12 (25%) of patients had a resistant organism to TMP/SMZ in the placebo group. The benefits of UTI prevention must be weighed against the risks for renal scarring, especially in patients who have a strong history of adherence. This suggests that the best strategy for this patient group could be prompt treatment of recurrent UTIs alone without prophylaxis. However, this theory requires further exploration and testing before any clinical implementation. The results of this study have clinical implications for providers managing patients on prophylaxis. Adherence should be assessed during prophylaxis treatment. The exact method for adherence assessment can be practice specific. We suggest a simple question, such as ‘In an average week how often are you taking the antimicrobial prophylaxis?’ The optimal timing and frequency for monitoring adherence is unclear, but we suggest assessing adherence within
1e2 months of initiating prophylaxis. For one, episodes of non-adherence occur as early as within the first 2 months of initiating treatment. Second, the risk of recurrent UTIs is greatest within 6 months of the initial UTI [27]. Evaluation of adherence may be performed at regular patient followup visits and/or with interim phone calls. Patient education on non-adherence (defined as taking the medication 4 days per week or less) should be provided, and discontinuing prophylaxis should be considered if nonadherence is determined. Return precautions should always be given in such cases. The results of this study have limitations. This is a secondary analysis of data not intended directly for this purpose. The adherence questionnaire was not validated in this population. There is no exact definition for nonadherence identified in the literature and likely depends on the medication being assessed. From this data, taking the study medication about 70% of the time or less appears to be a clinically significant value. This cut-off however should be validated in another cohort of children. The RIVUR trial was not powered to detect differences in renal scar formation, and thus the study results warrant further investigation. We stress that these results are meant to be hypothesis generating and are not conclusive. Self-reported adherence may underestimate the true prevalence in the population. It is theoretically possible that those who developed scars early in the study reported greater adherence. Caregiver factors
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs beyond education, such as income, previous experience with chronic medications, family stress, etc, were not collected in the RIVUR trial.
Conclusions No baseline demographics or disease severity characteristics are associated with non-adherence; however, patients with more severe BBD symptoms may be more likely to be non-adherent. Adherence to prophylaxis affects both recurrent UTI and renal scarring risk. Severe non-adherence (taking the medication less than 70% of the time) is strongly associated with renal scarring, whereas among very adherent patients, antibiotic prophylaxis is associated with renal scarring. Adherence should be assessed in prophylaxis management algorithms. The relationships between nonadherence and renal scarring and non-adherence and BBD merit future study.
Author statements Ethical approval None sought.
Funding No external or internal funding for this manuscript. The authors have no financial relationships relevant to this article to disclose.
Competing interest The authors have no conflicts of interest relevant to this article to disclose.
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1.e7 [8] Gerson AC, Furth SL, Neu AM, Fivush BA. Assessing associations between medication adherence and potentially modifiable psychosocial variables in pediatric kidney transplant recipients and their families. Pediatr Transplant 2004;8(6): 543e50. [9] Copp HL, Nelson CP, Shortliffe LD, Lai J, Saigal CS, Kennedy WA, et al. Compliance with antibiotic prophylaxis in children with vesicoureteral reflux: results from a national pharmacy claims database. J Urol 2010;183(5): 1994e2000. [10] Yiee JH, Baskin LS, Patel N, Yang J, Disandro M. Prospective blinded laboratory assessment of prophylactic antibiotic compliance in a pediatric outpatient setting. J Urol 2012; 187(6):2176e81. [11] Kardas P. Noncompliance in current antibiotic practice. Infect Dis Clin Pract 2006;14(4):S11e4. [12] Farhat W, Ba ¨gli DJ, Capolicchio G, O’reilly S, Merguerian PA, Khoury A, et al. The dysfunctional voiding scoring system: quantitative standardization of dysfunctional voiding symptoms in children. J Urol 2000;164(3):1011e5. [13] Shaikh N, Hoberman A, Keren R, Gotman N, Docimo SG, Mathews R, et al. Recurrent urinary tract infections in children with bladder and bowel dysfunction. Pediatrics 2015: 2015e982. [14] Keren R, Shaikh N, Pohl H, Gravens-Mueller L, Ivanova A, Zaoutis L, et al. Risk factors for recurrent urinary tract infection and renal scarring. Pediatrics 2015;136(1):e13e21. [15] Kripalani S, Yao X, Haynes R. Interventions to enhance medication adherence in chronic medical conditions: a systematic review. Arch Intern Med 2007;167(6):540e9. [16] Bosworth HB. Medication adherence. In: Bosworth H, editor. Improving patient treatment adherence: a clinician’s guide. New York, NY: Springer New York; 2010. p. 68e94. [17] Daniels T, Goodacre L, Sutton C, Pollard K, Conway S, Peckham D. Accurate assessment of adherence. Chest 2011; 140(2):425e32. [18] Fischer MA, Stedman MR, Lii J, Vogeli C, Shrank WH, Brookhart MA, et al. Primary medication non-adherence: analysis of 195,930 electronic prescriptions. J Gen Intern Med 2010;25(4):284e90. [19] Wolfe-Christensen C, Manolis A, Guy WC, Kovacevic N, Zoubi N, El-Baba M, et al. Bladder and bowel dysfunction: evidence for multidisciplinary care. J Urol 2013;190(5): 1864e8. [20] Shaikh N, Ewing AL, Bhatnagar S, Hoberman A. Risk of renal scarring in children with a first urinary tract infection: a systematic review. Pediatrics 2010;126(6):1084e91. [21] Shaikh N, Craig JC, Rovers MM, Da Dalt L, Gardikis S, Hoberman A, et al. Identification of children and adolescents at risk for renal scarring after a first urinary tract infection: a meta-analysis with individual patient data. JAMA Pediatrics 2014;168(10):893e900. [22] Shaikh N, Mattoo TK, Keren R, Ivanova A, Cui G, MoxeyMims M, et al. Early antibiotic treatment for pediatric febrile urinary tract infection and renal scarring. JAMA Pediatrics 2016;170(9):848e54. [23] KK A, Alexandra S, Maria KA, Charalampos T, HF A, SC J. Delayed treatment of the first febrile urinary tract infection in early childhood increased the risk of renal scarring. Acta Paediatr 2017;106(1):149e54. [24] Coulthard MG, Lambert HJ, Vernon SJ, Hunter EW, Keir MJ, Matthews JN. Does prompt treatment of urinary tract infection in preschool children prevent renal scarring: mixed retrospective and prospective audits. Arch Dis Child 2014; 99(4):342e7. [25] Selekman RE, Shapiro DJ, Boscardin J, Williams G, Craig JC, Brandstro ¨m P, et al. Uropathogen resistance and antibiotic prophylaxis: a meta-analysis. Pediatrics 2018;142(1).
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1.e8 [26] Costelloe C, Metcalfe C, Lovering A, Mant D, Hay AD. Effect of antibiotic prescribing in primary care on antimicrobial resistance in individual patients: systematic review and metaanalysis. BMJ 2010;340.
T.W. Gaither, H.L. Copp [27] Nuutinen M, Uhari M. Recurrence and follow-up after urinary tract infection under the age of 1 year. Pediatr Nephrol 2001; 16(1):69e72.
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jpurol.2019.04.019.
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Journal of Pediatric Urology (xxxx) xxx xxx
Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment Department of Urology, University of California, San Francisco, USA
T.W. Gaither, H.L. Copp * Summary
* Corresponding author. Mission Hall Pediatric Urology, 1825 4th Street 5th Floor, San Francisco, CA, 94143, USA.Tel/fax: 415 353 2083. [email protected] (H.L. Copp) Keywords Adherence; Bladder and bowel dysfunction; Continuous antibiotic prophylaxis; Renal scarring; Urinary tract infection; Vesicoureteral reflux Received 2 January 2019 Accepted 23 April 2019 Available online xxx
Background Continuous antimicrobial prophylaxis (prophylaxis) is associated with a reduction in recurrent urinary tract infections in children with vesicoureteral reflux. However, adherence to daily medications has been shown to be poor. Objective To determine patient/caregiver factors associated with non-adherence and to determine whether adherence alters the effect of prophylaxis on recurrent UTIs and renal scarring. Study design We conducted a secondary analysis of the Randomized Intervention for Children with Vesicoureteral Reflux trial. We stratified adherence scores into quartiles to assess trends within the data. We assessed predictors of non-adherence using ordinal logistic regression. We then examined the efficacy of prophylaxis stratified by adherence quartiles. Results Six hundred patients were included in the analysis. The quartiles of adherence were as follows: 1st quartiled0e70% adherence; 2nd quartiled71e91%
adherence; 3rd quartiled92e96% adherence; and 4th quartiled>96% adherence. Neither demographic factors nor disease severity was associated with non-adherence. In the subanalysis of patients who were toilet trained at baseline, increasing bladder and bowel dysfunction (BBD) symptom score was associated with non-adherence (adjusted odds ratio, aOR Z 1.1, 95% confidence interval [CI] 1.0e1.2). Patients least adherent were 2.5 times more likely (95%CI 1.1e5.6) to have a recurrent UTI compared with patients most adherent. After controlling for treatment arm, age, sex, degree of reflux, BBD, and number of UTIs, patients least adherent (taking the study medication less than <70% of the time) were at highest risk for renal scarring (aOR Z 24.2, 95%CI 3.0e197). In contrast, among the most adherent quartile, the probability of renal scarring was highest in those assigned prophylaxis (16.2% compared with 1.7% in those most adherent to placebo).
Conclusions Adherence is distinctly related to clinical outcomes in children with VUR. Non-adherence is common and represents a distinct clinical entity that is associated with renal scarring. Adherence should be assessed in prophylaxis management algorithms.
Summary Figure Adjusteda predicted probabilities for recurrent UTIs and renal scarring stratified by adherence quartileb. a Models adjusted for: age, sex, reflux status, BBD status, and number of prior UTIs. b Adherence quartiles: 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. BBD, bladder and bowel dysfunction. https://doi.org/10.1016/j.jpurol.2019.04.019 1477-5131/ª 2019 Published by Elsevier Ltd on behalf of Journal of Pediatric Urology Company.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Introduction Continuous antimicrobial prophylaxis (prophylaxis) has been a longstanding management strategy for children with VUR and recurrent UTIs [1]. In the Randomized Intervention for Children with Vesicoureteral Reflux (RIVUR) trial, prophylaxis was associated with a two-fold reduction in risk for recurrent UTIs in this population [2]. However, the intervention arm did not reduce the incidence of new renal scars (11.9% versus 10.2%), which is thought to represent longer term sequela of childhood UTIs [3]. Consequently, the benefits of prophylaxis beyond preventing the morbidity of recurrent UTIs have been questioned. Additionally, daily antibiotic exposure has been associated with certain risks, including harboring drug resistant organisms and weight gain [4,5]. Adherence rates for daily medications, including antibiotics, are poor [6]. This can be especially challenging for pediatric populations where other factors, such as medication taste or family stressors, can affect adherence [7,8]. Wide ranges in adherence rates specifically for prophylaxis in children with VUR have been reported varying anywhere from 40 to 90% depending on measurement method and patient population [9,10]. Adherence is an important factor in antibiotic efficacy [11]. Although evidence from randomized trials show benefit of prophylaxis in children with VUR, we hypothesize this benefit is maximized in patients adherent to the medication. We performed a secondary analysis of the RIVUR trial and had three specific aims: (1) what is the rate of non-adherence within the RIVUR trial? (2) which patient/caregiver factors predict nonadherence?, and (3) does adherence alter the effect of prophylaxis on recurrent UTIs and renal scarring?
Methods Study population We used data available from the National Institute of Diabetes and Digestive and Kidney Disease from the RIVUR trial [2]. The RIVUR trial is a double-blinded, randomized, placebo-controlled trial studying antibiotic prophylaxis to prevent recurrent UTI in patients with grade 1e4 VUR. The study included children after an index febrile or symptomatic UTI between the ages of 2e72 months. Enrolled children were followed for 2 years. Each child was randomized to trimethoprim-sulfamethoxazole (TMP-SMX) or placebo at baseline.
Main outcome and secondary outcomes Adherence was measured via patient questionnaires at each study visit (every 2 months for 2 years). Supplemental Table 1 demonstrates the adherence question with possible patient answers. Because there is no standard definition of non-adherence, we stratified adherence scores into quartiles to assess trends within the data. Quartile categorization allows for an equal number of individuals in each group, which improves statistical precision and provides more overlap of covariates. The average adherence score
T.W. Gaither, H.L. Copp was calculated by summing all adherence scores and dividing by the number of assessments. Secondary outcomes included recurrent UTIs and new renal scarring as defined by the RIVUR protocol [2]. In this analysis, adherence quartiles were used to define possible cut-offs where patients are at risk for recurrent UTIs or renal scarring.
Possible risk factors Patient and caregiver demographics including age at study enrollment (months), sex (female versus male), race/ ethnicity (White/Caucasian, Black/African American, Asian/Asian American, Hispanic/Latino, or other/unknown), prophylaxis assignment (TMP-SMX versus placebo), and education level (high school graduate or lower, some college or 2-year degree/certificate, or college graduate or higher) were collected. We also tested disease severity as measured by the number of previous UTIs (one versus two), whether the previous UTIs were symptomatic and febrile versus not symptomatic or febrile, and baseline bladder and bowel dysfunction (BBD) symptoms. These factors were chosen as these most likely represent tangible symptoms perceived by family members. Bladder and bowel dysfunction was assessed using the dysfunctional voiding questionnaire (DVQ) score [12]. The exact form used in the study can be found in the supplemental material in the original RIVUR publication [2]. Bladder and bowel dysfunction was defined as a score greater than or equal to 6 in female subjects and defined as a score greater than or equal to 9 for male subjects, as per the developers of the study [12,13]. Baseline BBD symptoms were measured by the DVQ score. The DVQ score was only assessed in toilettrained children and was thus a subanalysis of the sample (n Z 123).
Statistical analysis All analyses were performed in Stata v.13 (College Station, TX). We used ordinal logistic regression to determine the independent effects of the risk factors on the study outcome (non-adherence by quartile). The authors repeated the model in those who were toilet-trained only (n Z 123) to assess the effect of BBD symptoms on nonadherence. For our secondary analysis, we performed multivariate logistic regression to determine risk for a recurrent UTI and renal scarring stratified by adherence quartiles. We included an interaction between prophylaxis status and adherence quartiles. We performed an adjusted analysis to improve precision based on factors associated with recurrent UTI and renal scarring risk, including age, sex, dilating VUR, BBD status, and whether or not they had two prior UTI (versus one prior UTI), which is based on previous literature [14]. We presented adjusted predicted probabilities for recurrent UTI and renal scarring based on adherence quartile and stratified by prophylaxis status. All statistical tests were two-sided and P-values less than 0.05 were considered statistically significant. The institutional review board provided exempt status for the secondary data analysis.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs
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Results
Efficacy analysis
600/607 (98.8%) patients had adherence scores available for analysis. The quartiles of adherence were as follows: 1st quartiled0e70% adherence (n Z 150); 2nd quartiled71e91% adherence (n Z 150); 3rd quartiled92e96% adherence (n Z 159); 4th quartiled>96% adherence (n Z 141). We found no significant differences in adherence quartile between those assigned to prophylaxis vs placebo. Table 1 shows the demographic and clinical characteristics of patients stratified by adherence quartile. We found no statistical differences among demographic or clinical characteristic measures. The median DVQ score was higher among patients who were nonadherent (9 vs 4, P Z 0.19), but this did not reach statistical significance in the univariable models.
The results of the logistic model by quartile of adherence scores can be found in Table 3. Dilating reflux (aOR Z 1.9, 95% CI 1.2e3.0) and number of prior UTIs (aOR Z 2.0, 95% CI 1.0e3.9) were risk factors for recurrent UTIs. In this model, prophylaxis was not associated with a reduction of recurrent UTIs (aOR Z 0.5, 95%CI 0.2e1.5). Patients least adherent were 2.5 times more likely (95%CI 1.1e5.6) to have a recurrent UTI compared with patients most adherent. There was a non-significant interaction between adherence quartiles and prophylaxis status (P Z 0.07). After controlling for treatment arm, age, sex, degree of reflux, BBD, and number of UTIs, patients least adherent (taking the study medication less than 70% of the time) were at highest risk for renal scarring (aOR Z 24.2, 95%CI 3.0e197). In addition, patients with dilating reflux at baseline (aOR Z 2.5, 95%CI 1.3e5.0) and two prior UTIs (aOR Z 2.8, 95%CI 1.1e7.0) were at risk for renal scarring. Prophylaxis was also associated with an increased risk of renal scarring (aOR Z 12.9, 95%CI 1.5e109). Fig. 1 shows the adjusted predicted probabilities of recurrent UTIs and renal scarring by adherence quartile. Among patients in both the placebo and prophylaxis groups, there was a significant interaction between adherence quartiles and renal scarring (P Z 0.001). In the placebo group, a dose-response relationship is observed among adherence quartiles and renal scarring, ranging from 1.7%
Risk factor analysis The results of the multivariable analysis can be seen in Table 2. Using all patients in the sample, the adjusted estimates were non-significant. Neither demographic factors nor disease severity was associated with non-adherence. In the subanalysis of patients who were toilet trained at baseline, DVQ score was associated with non-adherence (aOR Z 1.1; 95% confidence interval [CI] 1.0e1.2). Thus, for every 10-point increase on the DVQ score, odds of increasing non-adherence quartiles increase by 2.0 (95%CI 1.1e3.9).
Table 1
Demographic and clinical characteristics of antimicrobial prophylaxis by adherence quartilea.
Demographic and clinical variables Demographics Infant, n(%) Sex, n(%) Female Race/ethnicity, n(%) White/Caucasian Black/African American Asian/Asian American Hispanic/Latino Other/unknown Caregiver education, n(%) High school graduate or lower Some college or 2-year degree College graduate or higher Clinical characteristics Assigned to CAP, n(%) Prior UTI’s, n(%) Two One Prior UTI symptomatic and febrile, n(%) DVQ score, median (IQR) n Z 126 BBD at baseline, n(%) n Z 126
4th quartile (most adherent) n Z 141
3rd quartile n Z 159
2nd quartile n Z 150
1st quartile (least adherent) n Z 150
P-value
76 (54)
90 (57)
75 (50)
74 (49)
0.54
128 (91)
143 (90)
139 (93)
141 (94)
0.56
101 (72) 5 (4) 2 (1) 14 (10) 18 (13)
114 (72) 6 (4) 6 (4) 16 (10) 16 (10)
104 (69) 7 (5) 5 (3) 12 (8) 22 (15)
112 (75) 5 (3) 4 (3) 10 (7) 19 (13)
0.96
38 (28) 24 (17) 76 (55)
35 (22) 39 (25) 84 (53)
41 (27) 50 (33) 59 (39)
41 (27) 42 (28) 67 (45)
0.03
74 (52)
77 (48)
78 (52)
70 (47)
0.70
8 (6) 133 (94) 96 (68) 4 (2e11) 9 (43)
13 (8) 146 (92) 103 (65) 6 (3e9) 16 (53)
13 (9) 137 (91) 106 (71) 6 (3e12) 21 (62)
18 (12) 132 (88) 102 (68) 9 (5e14) 24 (60)
0.29 0.74 0.19 0.52
BBD, bladder and bowel dysfunction; DVQ, dysfunctional voiding questionnaire. a 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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T.W. Gaither, H.L. Copp Ordinal logistic regression analysis for factors associated with antimicrobial prophylaxis non-adherence quartilesa.
Demographic and clinical variables Demographics Infant, n(%) Sex, n(%) Female Race/ethnicity, n(%) White/Caucasian Black/African American Asian/Asian American Hispanic/Latino Other/unknown Caregiver education, n(%) High school graduate or lower Some college or 2-year degree College graduate or higher Clinical characteristics Assigned to CAP, n(%) Prior UTI’s, n(%) Two One Prior UTI symptomatic and febrile, n(%) DVQ score (continuous)
Non-adherent aOR (95%CI) All patients
Non-adherent aOR (95%CI) Toilet-trained only
0.9 (0.7e1.2)
e
1.3 (0.7e2.2)
1.3 (0.04e41)
1.0 0.9 1.4 0.7 1.0
1.0 0.9 2.5 1.6 1.0
(reference) (0.4e1.9) (0.6e3.3) (0.4e1.2) (0.6e1.6)
(reference) (0.1e8.6) (0.3e24) (0.5e4.7) (0.3e3.2)
1.0 (reference) 1.3 (0.8e1.9) 0.7 (0.5e1.1)-
1.0 (reference) 0.8 (0.3e2.1) 0.5 (0.2e1.2)
0.9 (0.7e1.2)
1.6 (0.8e3.1)
1.6 (0.9e2.6) 1.0 (reference) 1.0 (0.7e1.4) e
1.9 1.0 0.9 1.1
(0.8e4.2) (reference) (0.3e3.3) (1.0e1.2)b
CI, confidence interval; DVQ, dysfunctional voiding questionnaire. a 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. b For every 10 points on DVQ score, odds of increasing non-compliant quartile is 2.0 (1.1e3.9).
predicted probability of scarring in the 1st quartile (most adherent in placebo group) to 26.3% predicted probability of scarring in the 4th quartile (least adherent in placebo group). In the prophylaxis group, we observe a u-shape distribution with highest predicted probability of scarring in the 1st quartile (most adherent in prophylaxis group) at 16.8% and second highest predicted probability of scarring in the 4th quartile (least adherent in prophylaxis group) at 16.2%.
Discussion Antibiotic prophylaxis has been a long-standing management strategy for patients with recurrent UTIs and concurrent VUR BBD. Although the RIVUR study, which is a well-conducted randomized trial of antibiotic prophylaxis, showed significant reduction in recurrent UTIs, the results of the current study show that the efficacy of antibiotic prophylaxis in prevention of UTI and renal scarring may be influenced by adherence in a manner not previously recognized. First, after adjusting for non-adherence, the protective effect of prophylaxis on recurrent UTIs was diminished. Second, extreme non-adherence (taking the study medication <70% of the time) is a risk factor for renal scarring. Third, in the most adherent subgroup, antibiotic prophylaxis is associated with renal scarring. The results of this study should be shared among parents and decisionmakers of children who are being considered for prophylaxis. Studies of UTIs in children should incorporate adherence, as extreme non-adherence may represent an important clinical phenotype. Additionally, the study has
implications for more frequent follow-up in patients on prophylaxis to assess for non-adherence. Approximately 25% of patients in the RIVUR trial took the study medication less than 70% of the time (quartile 1). It is estimated that 20e50% of patients do not take chronic medication as prescribed [15]. In a national study of patients with VUR specifically, Copp et al. estimated the nonadherence rate to be approximately 60% [9]. As the results in the current study are from a randomized trial, one would expect the adherence to be higher than the general population. In another study of 54 patients on prophylaxis, adherence was measured by urine chromatography, which showed a 91% adherence rate [10]. The differences observed could be because of a selected population, delayed antibiotic clearance in the urine, or that patients may be more likely to take their medication before seeing a provider. Patient adherence is difficult to measure and has been measured by self-report, pharmacy refill records, and/or the use of electronic lids [16]. As self-report tends to overestimate actual usage, the results in this study may be conservative estimates [17]. We found that neither demographic factors nor disease severity put patients at risk for non-adherence. In general, prescriptions by pediatricians are among the highest rates for filled medications (w87%) with parents of younger children more likely to get the prescription [18]. This concept has been shown in patients prescribed prophylaxis, as younger children, those more frequently hospitalized, and specialist visits were associated with prophylaxis adherence [9]. We anticipated replicating these findings; however, we found no associations between age or disease severity and non-adherence. The point estimate of infants
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs Table 3
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Multivariable logistic model of clinical outcomes by adherence quartiles.
Demographic and clinical variables Age Infant Non-infant Sex Female Male Reflux at baseline Dilating reflux Non-dilating reflux BBD during study Yes No Prior UTI’s 2 1 Treatment arm Prophylaxis Placebo Adherence levels 1st quartile (least adherent) 2nd quartile 3rd quartile 4th quartile (most adherent) Interaction (prophylaxis*adherence level)b Prophylaxis þ 1st quartile (least adherent) Prophylaxis þ 2nd quartile Prophylaxis þ 3rd quartile Prophylaxis þ 4th quartile (most adherent)
Recurrent UTI aOR (95% CI)
Renal scarring aOR (95% CI)
0.9 (0.5e1.4) 1.0 (reference)
0.4 (0.2e0.8)a 1.0 (reference)
2.1 (0.7e6.3) 1.0 (reference)
0.6 (0.2e1.9) 1.0 (reference)
1.9 (1.2e3.0)a 1.0 (reference)
2.5 (1.3e5.0)a 1.0 (reference)
1.6 (0.9e2.7) 1.0 (reference)
1.6 (0.8e3.3) 1.0 (reference)
2.0 (1.0e3.9)a 1.0 (reference)
2.8 (1.1e7.0)a 1.0 (reference)
0.5 (0.2e1.5) 1.0 (reference)
12.9 (1.5e109)a 1.0 (reference)
2.5 1.4 1.2 1.0
(1.1e5.6)a (0.6e3.2) (0.5e2.7) (reference)
24.2 (3.0e197)a 6.1 (0.7e56) 3.7 (0.4e35) 1.0 (reference)
1.3 0.4 0.8 1.0
(0.4e4.6) (0.1e1.8) (0.2e3.1) (reference)
0.04 (0.004e0.4) 0.07 (0.005e0.8) 0.1 (0.01e1.4) 1.0 (reference)
CI, confidence interval; DVQ, dysfunctional voiding questionnaire; BBD, bladder and bowel dysfunction. a P < 0.05. b Test for multiplicative interaction: recurrent UTI adherence quartile (P Z 0.07); renal scarring adherence quartile (P Z 0.001).
compared with non-infants showed a protective effect (aOR Z 0.9). We may not have been powered to detect a difference in this secondary analysis. Interestingly, patients with higher DVQ scores were at risk for non-adherence. To the authors knowledge, this represents a novel association not previously described in the literature. This association could be spurious or due to uncontrolled confounding, such as psychosocial distress in the home. For example, parenting stress has been significantly correlated with voiding dysfunction [19]. At the same time, parental stress has been linked to poorer medication adherence [8]. The relationship between prophylaxis non-adherence in patients with more severe BBD symptoms merits further study, especially since BBD is one of the strongest risk factors for recurrent UTIs [14]. Renal scarring occurs in approximately 15% of children after a first, febrile UTI [20]. Factors that predispose patients to renal scarring include high-grade VUR, recurrent UTIs, and the severity of the infection itself (high-grade fever, organisms other than E. coli, polymorphonuclear cell count of more than 60%) [14,21]. Delayed treatment has also been associated with renal scarring [22,23]. We report that non-adherence, especially those in the bottom quartile (adherent less than 70% of the time), is an independent risk factor for renal scarring. In fact, non-adherence had a larger effect size (point estimate aOR Z 24.2) than other
risk factors previously identified, such as dilating reflux (aOR Z 2.5) and prior UTIs (aOR Z 2.9). This is also apparent in the lower quartile point estimates. We also observed a doseeresponse relationship among quartiles of adherence and renal scarring in the placebo group, suggesting that this effect represents something independent of the medication itself. There is a statistically significant interaction between non-adherence and prophylaxis status, which suggests the effects of non-adherence depends on whether the child was taking prophylaxis or the placebo. Non-adherence may represent a social phenomenon, such as delayed presentation. Previous literature has shown children who were treated within 3 days of their symptoms were 1/3 as likely to scar as those whose symptoms lasted longer (OR Z 0.33, 95% CI 0.12e0.72) [24]. Providers may use non-adherence as a way to risk stratify those who may be at higher risk for renal scars. Psychosocial factors were not assessed in this study but should be taken into account in future studies. The u-shaped phenomenon among adherence quartiles and renal scarring in the prophylaxis group warrants comment. After adjustment, patients most adherent (>96% of the time taking the study medication) to prophylaxis had a predicted probability of renal scarring of 16.8%, which is compared with 1.7% of patients on placebo in the most adherent group. One explanation for this finding is that
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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T.W. Gaither, H.L. Copp
Fig. 1 Adjusteda predicted probabilities for recurrent UTIs and renal scarring stratified by adherence quartileb. a Models adjusted for: age, sex, reflux status, BBD status, and number of prior UTIs. b Adherence quartiles: 1st quartiled0e70% adherence; 2nd quartiled71e91% adherence; 3rd quartiled92e96% adherence; 4th quartiled>96% adherence. BBD, bladder and bowel dysfunction.
increased antibiotic exposure places these adherent patients most at risk for drug resistant organisms during a breakthrough UTI. Drug resistance is a known side-effect of prophylaxis [4]. For every 21 patients with VUR treated with prophylaxis, 1 patient is estimated to develop a multidrugresistant organism [25]. Longer duration of antibiotics and multiple courses are associated with higher rates of resistance [26]. For plausibility of this theory, we performed a post-hoc analysis of resistant organisms in this subgroup (most adherent quartile). In the most adherent group, 5/7 (71%) of patients had a resistant organism to TMP/SMZ in the prophylaxis group and 3/12 (25%) of patients had a resistant organism to TMP/SMZ in the placebo group. The benefits of UTI prevention must be weighed against the risks for renal scarring, especially in patients who have a strong history of adherence. This suggests that the best strategy for this patient group could be prompt treatment of recurrent UTIs alone without prophylaxis. However, this theory requires further exploration and testing before any clinical implementation. The results of this study have clinical implications for providers managing patients on prophylaxis. Adherence should be assessed during prophylaxis treatment. The exact method for adherence assessment can be practice specific. We suggest a simple question, such as ‘In an average week how often are you taking the antimicrobial prophylaxis?’ The optimal timing and frequency for monitoring adherence is unclear, but we suggest assessing adherence within
1e2 months of initiating prophylaxis. For one, episodes of non-adherence occur as early as within the first 2 months of initiating treatment. Second, the risk of recurrent UTIs is greatest within 6 months of the initial UTI [27]. Evaluation of adherence may be performed at regular patient followup visits and/or with interim phone calls. Patient education on non-adherence (defined as taking the medication 4 days per week or less) should be provided, and discontinuing prophylaxis should be considered if nonadherence is determined. Return precautions should always be given in such cases. The results of this study have limitations. This is a secondary analysis of data not intended directly for this purpose. The adherence questionnaire was not validated in this population. There is no exact definition for nonadherence identified in the literature and likely depends on the medication being assessed. From this data, taking the study medication about 70% of the time or less appears to be a clinically significant value. This cut-off however should be validated in another cohort of children. The RIVUR trial was not powered to detect differences in renal scar formation, and thus the study results warrant further investigation. We stress that these results are meant to be hypothesis generating and are not conclusive. Self-reported adherence may underestimate the true prevalence in the population. It is theoretically possible that those who developed scars early in the study reported greater adherence. Caregiver factors
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019
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Adherence of antimicrobial prophylaxis for UTIs beyond education, such as income, previous experience with chronic medications, family stress, etc, were not collected in the RIVUR trial.
Conclusions No baseline demographics or disease severity characteristics are associated with non-adherence; however, patients with more severe BBD symptoms may be more likely to be non-adherent. Adherence to prophylaxis affects both recurrent UTI and renal scarring risk. Severe non-adherence (taking the medication less than 70% of the time) is strongly associated with renal scarring, whereas among very adherent patients, antibiotic prophylaxis is associated with renal scarring. Adherence should be assessed in prophylaxis management algorithms. The relationships between nonadherence and renal scarring and non-adherence and BBD merit future study.
Author statements Ethical approval None sought.
Funding No external or internal funding for this manuscript. The authors have no financial relationships relevant to this article to disclose.
Competing interest The authors have no conflicts of interest relevant to this article to disclose.
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Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jpurol.2019.04.019.
Please cite this article as: Gaither TW, Copp HL, Antimicrobial prophylaxis for urinary tract infections: implications for adherence assessment, Journal of Pediatric Urology, https://doi.org/10.1016/j.jpurol.2019.04.019