Purpose: Urinary tract infections (UTIs) are among the most common community-acquired infections in patients with cancer. Though the prevalence of multi-drug resistant organisms (MDROs) has increased, there are limited studies on MDROs among ambulatory cancer patients with UTIs. Therefore, we aimed to evaluate the prevalence and predictors of MDROs in this patient population. Patients and Methods: A retrospective study of adult cancer patients treated for bacterial UTIs in the ambulatory setting at King Hussein Cancer Center. The medical laboratory’s system was used to identify positive urine cultures taken in the ambulatory setting, between Aug 2020 and March 2021. UTIs were defined as a positive urine culture along with the initiation of antibiotics empirically or as definitive therapy. Patient characteristics, as well as the type and sensitivity of the bacterial organisms, were recorded. MDROs were defined as intrinsic or acquired non-susceptibility to at least one agent in three or more antimicrobial categories. Logistic regression was used to identify predictors that were independently associated with MDROs. Results: A total of 376 patients had UTIs that met the inclusion criteria; mean age 60.5± 15.1 (SD) years and 330 (87.8%) had solid tumors. Gram-negative bacteria was recorded in the majority of UTIs (n = 368, 97.9%), the most common being Escherichia-coli (n = 220, 59.8%) and Klebsiella-pneumonia (n = 68, 18.5%). MDROs were recorded in 226 (60.1%) of urine cultures, with the majority being extended-spectrum-beta-lactamase producing organisms (n = 142, 62.8%). The only significant predictor was having had a UTI with MDRO within the past 6 months (OR 5.6, 95% CI 2.1– 15.2). Conclusion: More than half of the positive urine cultures of cancer patients treated for UTIs in the ambulatory setting were MDROs. A subsequent UTI due to MDROs is more likely to occur in patients who had a UTI with an MDRO within the past 6 months.

OBJECTIVES: To evaluate the effect of procalcitonin-guided management on the duration of antibiotic therapy in critically ill cancer patients with sepsis. DESIGN: Randomized, controlled, single-blinded trial. SETTING: A comprehensive multidisciplinary cancer hospital in Jordan. PATIENTS: Adults with cancer treated in the ICU who were started on antibiotics for suspected infection, met the SEPSIS-3 criteria, and were expected to stay in the ICU greater than or equal to 48 hours. INTERVENTIONS: Patients were randomized to the procalcitonin-guided or standard care (SC) arms. All patients had procalcitonin measured daily, up to 5 days or until ICU discharge or death. For the procalcitonin arm, a procalcitonin-guided algorithm was provided to guide antibiotic management, but clinicians were allowed to override the algorithm, if clinically indicated. In the SC arm, ICU clinicians were blinded to the procalcitonin levels. MEASUREMENTS AND MAIN RESULTS: Primary outcome was time to antibiotic cessation. We also evaluated the number of antibiotic-free days at 28 days, hospital discharge, or death, whichever came first, and antibiotic defined daily doses (DDDs). We enrolled 77 patients in the procalcitonin arm and 76 in the SC arm. Mean age was 58 ± 14 (sd) years, 67% were males, 74% had solid tumors, and 13% were neutropenic. Median (interquartile range [IQR]) Sequential Organ Failure Assessment scores were 7 (6–10) and 7 (5–9) and procalcitonin concentrations (ng/mL) at baseline were 3.4 (0.8–16) and 3.4 (0.5–26), in the procalcitonin and SC arms, respectively. There was no difference in the median (IQR) time to antibiotic cessation in the procalcitonin and SC arms, 8 (4–11) and 8 (5–13), respectively (p = 0.463). Median (IQR) number of antibiotic-free days were 20 (17–24) and 20 (16–23), (p = 0.484) and total DDDs were 1541.4 and 2050.4 in the procalcitonin and SC arms, respectively. CONCLUSIONS: In critically ill cancer patients with sepsis, procalcitonin-guided management did not reduce the duration of antibiotic treatment.

The updated vancomycin guideline and recent studies suggested that trough concentrations may result in underestimation of the actual area under the curve (AUC), leading to excessive dosing and nephrotoxicity. With limited data available on critically ill cancer patients, this study aimed to compare the two methods in this patient population. This was a 5‐year retrospective study on patients treated with vancomycin in the intensive care unit (ICU) of a comprehensive cancer center. The measured trough concentration was compared to Bayesian‐derived AUC/minimum‐inhibitory‐concentration (MIC), considering MIC as 1. Trough concentrations of 15–20 mg/L and AUC of 400–600 mg h/L were considered the targeted goal. Multivariate analysis was performed to identify factors associated with an AUC below the targeted goal. During the study period, 316 patients were included. The mean age was 54 years ±16 (SD); most patients had solid tumors (75%), and 11% had neutropenia. A targeted goal AUC and trough were recorded in 128 (41%) patients and in 64 (20%) patients, respectively. Of the 128 patients with targeted goal AUC, 31 (24%) had targeted goal trough concentrations and 91 (71%) had trough concentrations below 15 mg/L. Furthermore, among the patients with targeted goal trough concentration (n = 64), 33 (52%) had higher than targeted goal AUC. Augmented renal clearance (ARC), defined as a calculated creatinine‐clearance ≥130 ml/min, was associated with an AUC below the targeted goal. In a cohort of critically ill patients with cancer, over two‐thirds of the patients with a targeted goal Bayesian AUC/MIC had trough concentrations below the targeted goal. ARC was associated with AUC below the targeted goal.

Guidelines recommend monitoring vancomycin by estimating the area under the curve (AUC24) with two levels, peak and trough, preferably using Bayesian software. However, such an approach is not feasible or cost-effective in all settings. In this study, we evaluated the accuracy and precision of estimating AUC24 using a single mid-point level in critically ill cancer patients. We hypothesized that concentrations at the midpoint of the dosing interval may provide insight into the volume of distribution (Vd) and clearance (Cl), capturing pharmacokinetic parameters assessed by the peak and trough concentrations, respectively. A prospective study that included critically ill cancer patients with stable kidney function who received vancomycin during their ICU stay. Trough, peak, and midpoint concentrations were measured at steady-state. Pharmacokinetic equations from the short infusion model was used to calculate the AUC24, Cl, and Vd using a single midpoint. We also determined AUC24, Cl, and Vd using Bayesian software with peak and trough concentrations. Accuracy and precision of the pharmacokinetic estimations utilizing the mid-point level were determined, with a comparison to the Bayesian approach. We included 91 patients, with a mean age of 53 years ± 17 (SD), 54% were males, and 77% had solid tumors. The mean prescribed vancomycin dose was 15 mg/kg/dose ± 3 (SD). Median AUC24 was 426 mg.dl/hr (IQR 326–559) and 464 mg.dl/hr (IQR 345–664), using the midpoint and Bayesian approach, respectively. The mean Vd was 48 L (± 11) and 45 L (± 13) and Cl was 5 L/hr (± 3) and 5 L/hr (± 2) for both approaches, respectively. The accuracy and precision for the midpoint, against the Bayesian, were: AUC24 (11%, 22%, respectively), Cl (17%, 24%, respectively), and Vd (6%, 9%, respectively). Utilization of mid-point vancomycin levels to calculate pharmacokinetic parameters demonstrated promising findings. Further research with larger and more diverse patient populations is needed to evaluate this approach further.