Primary objective

To determine the outcome of hospitalised patients with cUTI and identify the risk factors associated with treatment failure.

Secondary objectives

1. To identify clinical characteristics and demographic factors of hospitalised patients with cUTI.

2. To identify the main causative MDR GNB, and their most frequent resistance profiles.

3. To define risk factors associated with cUTI caused by MDR GNB.

4. To describe clinical management of hospitalised patients with cUTI.

5. To determine the modifiable risk factors associated with early treatment failure in patients with cUTI.

6. To determine length of hospital stay in patients with cUTI.

7. To determine duration of antibiotic therapy (intravenous, intramuscular and oral) in patients with cUTI.

8. To determine mortality rate of hospitalised patients with cUTI.

9. To estimate the cost per case of cUTI measured by length of hospital stay, intensive care unit requirements, medications, tests and need for urological intervention and haemodialysis.

10. To estimate the total national cost of illness due to cUTI in participating countries.

11. To help identify patient types, and potential clinical trial sites for future phase 2 or 3 clinical trials in cUTI.

Study design

A multinational and multicentre retrospective, observational cohort study which will involve the collection of data on hospitalised patients from 1 January 2013 to 31 December 2014.

Study population

Data will be collected on patients who had a diagnosis of cUTI as the primary cause of hospitalisation, and patients hospitalised for another reason but who developed cUTI during their hospitalisation.

Setting

The study will be conducted in Bulgaria, Greece, Hungary, Israel, Italy, Romania, Spain and Turkey. The number of sites per country will be identified via the Clinical Trial Network (CLIN-NET), and be included in the study.

Selection of cases

Patients will be identified by searching for any of the following International Classification of Diseases (ICD)-9 Clinical Modification (CM) or ICD-10 CM Codes18 ,19 at discharge on the hospital administration system:

ICD-9 CM Codes: 590.1, 590.10, 590.11, 590.2, 590.8, 590.80, 590.9, 595.0, 595.89, 595.9, 599.0;

ICD-10 CM Codes: N10, N12, N13.6, N15.1, N15.9, N30.0, N30.8, N30.9, N39.0.

In order to avoid selection bias, all consecutive patients who have ICD-9 or ICD-10 CM codes will be reviewed at each site. All patients who meet the inclusion criteria will be selected for data collection.

Inclusion criteria

1. The following criteria, which have been adapted from Food and Drug Administration (FDA) guidance on cUTIs: Developing Drugs for Treatment. Guidance for Industry;20 European Medicines Agency (EMA) guidelines on the evaluation of medicinal products indicated for treatment of bacterial infections;21 and clinical practice guidelines for the evaluation and management of chronic kidney disease22 must be met to qualify for enrolment into this study: patients with UTI and at least one of the following:

   • Indwelling urinary catheter;

   • Urinary retention (at least 100 mL of residual urine after voiding);

   • Neurogenic bladder;

   • Obstructive uropathy (eg, nephrolithiasis, fibrosis);

   • Renal impairment caused by intrinsic renal disease: estimated glomerular filtration rate <60 mL/min;

   • Renal transplantation;

   • Urinary tract modifications, such as an ileal loop or pouch;15

   • Pyelonephritis and normal urinary tract anatomy.

2. And at least one of the following signs or symptoms:

   • Chills or rigors associated with fever or hypothermia (temperature >38°C or below 36°C);

   • Flank pain (pyelonephritis) or pelvic pain (cUTI);

   • Dysuria, urinary frequency or urinary urgency;

   • Costovertebral angle tenderness on physical examination;

   • UTI-related altered mental state.

3. And urine culture with at least 10⁵ colony-forming unit (CFU)/mL or greater of a uropathogen (no more than two species); or

4. At least one blood culture growing possible uropathogens (no more than two species) with no other evident site of infection.

If a patient has more than one episode of cUTI during the same hospitalisation, only the first episode will be included. Recurrence within 30 days will be considered as treatment failure.

Exclusion criteria

If any of the following exclusion criteria apply, the patient is not eligible for enrolment into this study:

1. Patients <18 years of age;

2. Prostatitis;

3. Polymicrobial infections that include Candida spp;

4. Polymicrobial infections that include more than two bacterial species;

5. cUTI with Candida spp. as sole uropathogen.

Definition of MDR bacteria

Bacterial multidrug resistance is defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories according to the international expert proposal published by Magiorakos et al.7

Data collection

For patients recruited into the study, data will be collected retrospectively. These data items will be obtained from different sources, including the patient notes, electronic patient records, the hospital patient administration system and the hospital laboratory systems.

For all patients, a standardised set of information will be recorded. This will include demographics, comorbidities including those required to calculate a modified Charlson score,23 functional capacity,24 place of acquisition of infection, predisposing risk factors, clinical data, clinical pathology data, microbiological data, imaging test data, infection management, antibiotic therapy, outcomes, details of discharge and readmission.

Participant timeline

The follow-up period will be for up to 2 months after discharge from the admitting hospital.

Primary end point

The primary end point will be treatment failure, applying a slightly modified definition of FDA guidance on cUTIs: Developing Drugs for Treatment. Guidance for Industry.20

This definition includes any of the following conditions:

• Signs or symptoms of cUTI present at diagnosis that have not improved by days 5–7 with appropriate antibiotic therapy;

• New cUTI-related symptoms that have developed within 30 days of the original cUTI diagnosis;

• Urine culture taken within 30 days of the original cUTI diagnosis, either during or after completion of therapy, that grows ≥10⁴ CFU/mL of the original pathogen identified in the diagnostic sample;

• Death irrespective of cause within 30 days of the original cUTI diagnosis.

Secondary end points

The following secondary end points will be evaluated:

• Time to clinical response, in days;

• Time to urological intervention for source control, in days;

• Time to death, in days;

• Duration of antibiotic therapy, in days;

• Length of hospital stay, in days;

• In-hospital mortality;

• All-cause mortality within 30 days of the original cUTI diagnosis;

• All-cause mortality for 2 months after hospital discharge;

• Cost per case of cUTI;

• Readmissions to the hospital within 60 days of hospital discharge;

• Adverse events related to antibiotic treatment including moderate or severe allergic reactions, severe renal impairment, Clostridium difficile infection.

Health economic analysis

We will evaluate the cost of cUTI in participating countries, and the factors affecting these costs. The perspective will be the hospital provider, as this is where the majority of the cost burden of cUTI is expected to fall.25 ,26 This will have three components:

1. We will estimate the cost per case of cUTI in participating countries. This will be based on collection of healthcare resource use data on length of hospital stay in different settings, medications and other treatment for infection, tests, and need of urological intervention and haemodialysis. Unit cost data for each cost component will be collected for each participating country from published and administrative sources, and multiplied by volume of resource used, and then summed across all components to calculate the costs per patient for cUTI caused by MDR GNB. Findings will be presented as means (with 95% CIs) and medians (with IQRs) of total costs, and also for each separate cost component.

2. Using data collected in this programme plus supplementary epidemiological data, the incidence of cUTI caused by MDR GNB in each country will be modelled and this will be multiplied by the mean incremental cost per patient to compute the total national cost of illness of cUTI caused by MDR GNB.

3. Multivariate regression analysis using patient-level cost data to investigate the factors associated with healthcare costs will be undertaken. The dependent variable will be mean costs per patient described under 1, given above. Independent variables will include age, gender, comorbidities, severity of infection, whether or not the patient died, signs and symptoms of UTI, and where the infection was acquired. To account for skewness of the cost data, a generalised linear model with γ family and log link27 will be used. The impact of unobserved heterogeneity due to the hierarchical structure of the data (patients within hospitals within countries) will be explored and accounted for by considering the hospital and country fixed-effects and random-effects models.

Sample size

One thousand patients should afford a power of 0.83 (α=0.05) to detect an absolute difference of 10% in the treatment failure rate between MDR bacteria and other pathogens. This should allow for the introduction of about 20 independent risk factors (or their interaction) in a logistic regression model looking at risk factors for failure.

Statistical analysis

The χ² or Fisher's exact tests will be used to compare categorical data, and the Student's t-test or Mann-Whitney U test for continuous data, as appropriate (the Kolmogorov-Smirnoff test will be used to test whether the distribution of continuous variable is normal). Logistic regression analysis will be performed to identify independent variables associated with treatment failure. Variables with p<0.10 in univariate analysis (and variables that make clinical sense) will be included in the multivariate model to control for confounding. The adequacy of the final model will be tested using the Hosmer-Lemeshow goodness-of-fit test. All tests will be two-tailed, and a p<0.05 will be considered as statistically significant.

Time to appropriate therapy, clinical response, urological intervention for source control or death will be examined using competing risks.

Monitoring plans

At each site, a screening log will be kept of the patients who were detected according to the ICD codes, and detail the excluded patients and the reasons for exclusion.

For confirmation of the data quality and to avoid fraud, study sites will be monitored and/or audited. Monitoring and audit visits will be conducted by a designated third party. Spot check monitoring and source data verification will be conducted to confirm that the data entered in the database are retrieved from actual patients and their corresponding hospital files, and has been transferred correctly. All sites' study-related documents, including patient data source documents, will have to be made available for monitoring and audit.