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Keywords:

  • antipseudomonal antibiotics;
  • carbapenem;
  • case–control study;
  • chronic obstructive pulmonary disease;
  • risk factors

Abstract

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

BACKGROUND

Pseudomonas aeruginosa is responsible for a wide range of infections. In immunocompromised patients with cancer, the emergence of multidrug resistant P. aeruginosa may have grave consequences.

METHODS

Patients with cancer who were infected with multidrug-resistant P. aeruginosa with polyclonal DNA restriction patterns were used as the case group. Two control groups were used: one group of cancer patients who were infected with multidrug-susceptible P. aeruginosa and another group of cancer patients who had the same underlying disease and the same intensive care unit exposure as patients in the case group but who were not infected or colonized by P. aeruginosa.

RESULTS

Risk factors that were associated significantly with multidrug-resistant P. aeruginosa infection were the use of carbapenem for ≥ 7 days, a history of P. aeruginosa infection during the preceding year, and a history of chronic obstructive pulmonary disease (P < 0.01).

CONCLUSIONS

Carbapenems may need to be used more judiciously as first-line empirical therapy for cancer patients with prior pseudomonal infection or chronic obstructive pulmonary disease who require hospitalization, and alternative, antipseudomonal antibiotic regimens may need to be considered, especially in this patient population. Cancer 2005. © 2005 American Cancer Society.

Pseudomonas aeruginosa is one of the leading causes of nosocomial infection in the U.S.,1 and resistance to antipseudomonal antibiotics is a growing problem.2–4 The incidence rate of infection with multidrug-resistant P. aeruginosa, which is associated with increased morbidity, mortality, and cost, is increasing.5, 6 A number of outbreak analyses have been conducted to clarify the source of nosocomial multidrug-resistant P. aeruginosa7–9; however, few studies have analyzed the risk factors associated with it.10–12

Between 1997 and 1999, the incidence rate in the U.S. of multidrug-resistant P. aerugnosa infection (defined as resistant to piperacillin, ceftazidime, imipenem, and gentamicin) was reported as 1.2%.13 Weaver et al. reported that multidrug-resistant P. aeruginosa, which they defined as resistant to ≥ 3 antimicrobial classes, including aminoglycosides, quinolones, cephalosporins, and penicillins, accounted for 23.1% of all isolates tested (n = 52,921 isolates) between 1999 and 2002.14 Furthermore, a surveillance study of P. aeruginosa isolates among intensive care unit patients in the U.S. showed that the rates of multidrug resistance (defined as resistance to ≥ 3 of the following drugs: ceftazidime, ciprofloxacin, tobramycin, or imipenem) increased from 4% in 1993 to 14% in 2002.5 This increasing rate of multidrug resistance is a major threat, especially considering that infection with multidrug-resistant P. aeruginosa is associated with increased morbidity, mortality, and cost.6

We conducted two, simultaneous case–control analyses to determine the risk factors associated with acquiring multidrug-resistant P. aeruginosa infection. We used only patients who had infections caused by genotypically diverse strains of P. aeruginosa in our case group to assess the risk factors associated with de novo selection of resistant organisms. Furthermore, we used two groups of control patients to determine whether control selection affected the study results.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

Case and Control Definition and Study Design.

Two simultaneous, retrospective 1:2 case–control analyses were performed at The University of Texas M. D. Anderson Cancer Center in Houston, Texas. After obtaining Institutional Review Board approval, the infection control surveillance records and the microbiology laboratory data base were queried to identify patients for the case group and for two control groups who were at the hospital between June 2001 and July 2002.

Patients in the case group were selected from among patients with cancer who were infected with multidrug-resistant P. aeruginosa. We used the criteria established by the Centers for Disease Control and Prevention to define infection.15 Antimicrobial susceptibility testing was done following National Nosocomial Infections Surveillance System guidelines and using the E-test (AB BIODISK, Solna, Sweden) to determine multidrug resistance. The P. aeruginosa was considered multidrug resistant if it was resistant intermediately or completely to at least three of the four following groups: 1) imipenem or meropenem; 2) cefepime or ceftazidime; 3) piperacillin, piperacillin/tazobactam, or ticarcillin/clavulanic acid; and 4) ciprofloxacin or levofloxacin.

All infection-causing isolates of multidrug-resistant P. aeruginosa were collected and tested by pulsed-field gel electrophoresis. Only patients who had infections caused by isolates of polyclonal DNA restriction patterns were defined as cases.

Two control groups were selected for this study. The ratio of cases to controls was 1:2 for each of the control groups. The first control group consisted of cancer patients infected with antibiotic-susceptible P. aeruginosa who were seen at the clinic or the inpatient ward of The University of Texas M. D. Anderson Cancer Center during the same period as patients in the case group (Control Group 1). The other control group consisted of patients with cancer who had the same underlying disease and who were admitted to the same hospital service, including intensive care units, and during the same period as patients in the case group but who were not infected or colonized with P. aeruginosa (Control Group 2).

Data Collected and Risk Factors Investigated.

Data were collected from patient charts as well as computerized administrative, pharmacy, and laboratory data bases at The University of Texas M. D. Anderson Cancer Center. The data collected included age, gender, cancer diagnosis, and comorbid conditions, such as chronic obstructive lung disease, surgery, radiation, and antineoplastic chemotherapy. The following were considered comorbid conditions if they occurred among patients in the case group and in Control Group 1 within the 30 days before isolation of P. aeruginosa and, in Control Group 2, within the 30 days before and during hospital admission: a stay at the intensive care unit, mechanical ventilation and its duration, hemodialysis, neutropenia and its duration, and a history of steroid therapy and total administered dose. A history of P. aeruginosa infection or colonization was considered a comorbid condition if it occurred within 1 year before isolation of P. aeruginosa for patients in the case group and in Control Group 1 and if it occurred within 1 year before the date of hospital admission for patients in Control Group 2. The total dosage of antibiotics administered was a comorbid condition within 90 days before the isolation of P. aeruginosa for patients in the case group and in Control Group 1 and within 90 days before hospital admission for patients in Control Group 2. The total dosage of the antibiotics was expressed as the total number of adult defined daily doses, as defined by World Health Organization for 2003.16

Statistical Analysis

All statistical analyses were performed using SPSS 11.0 software (SPSS Inc., Chicago, IL). Univariate analyses were conducted separately for each of the variables. Categorical variables were compared by chi-square test or Fisher exact test, as appropriate. Continuous variables with normal distribution were compared with the Student t test, and variables that were not distributed normally were compared with the Mann–Whitney U test. Clinically relevant variables that were significant at P ≤ 0.05 in univariate analysis were included in multiple logistic regression analysis using a step-wise, forward method to identify the independent risk factors associated with acquiring the infection. All tests were 2-tailed, and statistical significance was set at P ≤ 0.05.

RESULTS

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

We identified a total of 90 infections with multidrug-resistant P. aeruginosa during the study period. Among these, 18 infections represented distinguishable DNA restriction patterns by pulsed-field gel electrophoresis, and the patients with those infections were included in the study as the case group. Each of the two control groups included 36 patients.

The results of the univariate analyses of the risk factors associated with acquiring multidrug-resistant P. aeruginosa infection using Control Group 1 are outlined in Table 1, and the results for Control Group 2 are outlined in Table 2. Eleven of 18 patients in the case group had prior history of P. aeruginosa infection or colonization during the preceding year. Ten of those prior infections or colonizations were due to susceptible P. aeruginosa strains.

Table 1. Univariate Analysis of Risk Factors Associated with Multidrug-Resistant Pseudomonas aeruginosa Infection using Control Group 1
VariableNo. of patients (%)P value
Cases (n = 18)Control Group 1 (n = 36)
  1. SD: standard deviation; COPD: chronic obstructive pulmonary disease; ICU: intensive care unit; DDDs: adult defined daily doses; P. aeruginosa: Pseudomonas aeruginosa.

Male9 (50.0)21 (58.3)0.56
Mean ± SD age (yrs)51.8 ± 15.860.3 ± 17.10.05
Diagnosis   
 Leukemia6 (33.3)3 (8.3)0.05
 Lymphoma or myeloma2 (11.1)5 (13.9)0.57
 Solid tumor10 (55.6)28 (77.8)0.09
Underlying condition   
 Chemotherapy7 (38.9)15 (41.7)0.85
 Surgery5 (27.8)12 (33.3)0.68
 Radiation3 (16.7)3 (8.3)0.39
 COPD4 (22.2)1 (2.8)0.04
ICU stay during prior month2 (11.1)3 (8.3)1.00
Mechanical ventilation within prior month9 (50.0)9 (25.0)0.07
Mean ± SD duration of mechanical ventilation (days)21.2 ± 15.61.5 ± 0.80.005
Hemodialysis within prior month2 (11.1)0 (0.0)0.11
Neutropenia (<500/μL) within prior month4 (22.2)2 (5.6)0.09
Mean ± SD duration of neutropenia (days)15.0 ± 8.52.5 ± 2.10.12
Pseudomonas infection or colonization during prior yr11 (61.1)3 (8.3)<0.001
Steroid use10 (55.6)7 (19.4)0.007
Mean ± SD steroid equivalent to methylprednisone (mg)1006.5 ± 1400.7534.1 ± 468.30.41
Antibiotic use ≥7 DDDs within 90 days prior to first positive culture   
 Carbapenem14 (77.8)3 (8.3)<0.001
 Cephalosporin8 (44.4)0 (0.0)<0.001
 Fluoroquinolone12 (66.7)6 (16.7)<0.001
 Aminoglycocide5 (27.8)0 (0.0)0.003
 Penicillins5 (27.8)0 (0.0)0.003
 Vancomycin12 (66.7)2 (5.6)<0.001
Antibiotic use (mean ± SD of total no. of DDDs)   
 Carbapenem17.6 ± 9.77.6 ± 10.30.02
 Cephalosporin17.9 ± 10.71.0 ± —0.001
 Fluoroquinolone22.7 ± 19.715.1 ± 12.30.31
 Aminoglycocide9.2 ± 4.62.6 ± 2.30.06
 Penicillins12.7 ± 8.72.3 ± 2.20.02
 Vancomycin14.3 ± 9.39.4 ± 5.90.028
Response9 (50.0)30 (83.3)0.01
Table 2. Univariate Analysis of Risk Factors Associated with Multidrug-Resistant Pseudomonas aeruginosa using Control Group 2
VariableNo. of patients (%)P value
Cases (n = 18)Control Group 2 (n = 36)
  1. SD: standard deviation; COPD: chronic obstructive pulmonary disease; ICU: intensive care unit; DDDs: adult defined daily doses; P. aeruginosa: Pseudomonas aeruginosa.

Male9 (50.0)24 (66.7)0.24
Mean ± SD age (yrs)51.8 ± 15.852.8 ± 14.50.82
Diagnosis   
 Leukemia6 (33.3)11 (30.6)0.85
 Lymphoma or myeloma2 (11.1)5 (13.9)0.99
 Solid tumor10 (55.6)20 (55.6)0.99
Underlying condition   
 Chemotherapy7 (38.9)13 (36.1)0.84
 Surgery5 (27.8)10 (27.8)1.00
 Radiation3 (16.7)6 (16.7)0.64
 COPD4 (22.2)0 (0.0)0.01
ICU during prior month2 (11.1)7 (19.4)0.36
Mechanical ventilation within prior month9 (50.0)10 (27.8)0.11
Mean ± SD duration of mechanical ventilation (days)21.2 ± 15.613.1 ± 13.20.25
Hemodialysis within prior month2 (11.1)2 (5.6)0.41
Neutropenia (< 500/μL) within prior month4 (22.2)6 (16.7)0.44
Mean ± SD duration of neutropenia (days)15.0 ± 8.510.3 ± 10.30.52
P. aeruginosa infection or colonization during prior yr11 (61.1)<0.001
Steroid use10 (55.6)21 (58.3)0.85
Mean ± SD steroid equivalent to methylprednisone (mg)1006.5 ± 1400.7937.9 ± 1235.20.89
Antibiotic use ≥7 DDDs within 90 days prior to first positive culture   
 Carbapenems14 (77.8)16 (44.4)0.02
 Cephalosporins8 (44.4)9 (25.0)0.15
 Fluoroquinolones12 (66.7)22 (61.1)0.69
 Aminoglycocides5 (27.8)3 (8.3)0.10
 Penicillins5 (27.8)3 (8.3)0.10
 Vancomycin12 (66.7)11 (30.6)0.01
Antibiotic use (mean ± SD of total no. of DDDs)   
 Carbapenem17.6 ± 9.715.9 ± 8.80.6
 Cephalosporin17.9 ± 10.712.4 ± 9.50.22
 Fluoroquinolone22.7 ± 19.728.8 ± 24.10.41
 Aminoglycocide9.2 ± 4.66.8 ± 7.10.5
 Penicillins12.7 ± 8.78.7 ± 9.20.35
 Vancomycin14.3 ± 9.314.2 ± 16.70.97

In a univariate analysis using Control Group 1, the following factors were associated significantly with acquiring multidrug-resistant P. aeruginosa infection: age (P = 0.05), leukemia (P = 0.05), a history of chronic obstructive lung disease (P = 0.04), steroid use during the 30 days before the infection (P = 0.007), a history of P. aeruginosa infection or colonization during the preceding year (P < 0.001), the duration of mechanical ventilation (P = 0.005), and the use of the following antibiotics for ≥ 7 days: carbapenems, cephalosporins, fluoroquinolones, aminoglycosides, penicillins, and vancomycin (P ≤ 0.003). The carbapenems used consisted of imipenem and meropenem only. More patients received meropenem than imipenem (11 of 18 patients [61%] vs. 7 of 18 patients [39%)], respectively).

In a univariate analysis using Control Group 2, the following risk factors were associated significantly with acquiring multidrug-resistant P. aeruginosa infection: a history of chronic obstructive lung disease (P = 0.01), a history of P. aeruginosa infection during the preceding year (P < 0.001), the use of carbapenems for ≥ 7 days (P = 0.02), and the use of vancomycin for ≥ 7 days (P = 0.01). In univariate analyses using both Control Groups 1 and 2, the same risk factors that were associated with acquiring multidrug-resistant P. aeruginosa infection were a history of chronic obstructive lung disease, a history of P. aeruginosa infection or colonization during preceding year, the use of carbapenems for ≥ 7 days, and the use of vancomycin for ≥ 7 days. The results of the logistic regression analyses of the risk factors are outlined in Table 3.

Table 3. Results of Multiple Logistic Regression Analysis using Control Group 1
VariableUnivariate P valueMultivariate
P valueOR95% CI
  1. OR: odds ratio; 95% CI: 95% confidence interval; P. aeruginosa; Pseudomonas aeruginosa.

Carbapenem use ≥7 defined daily dose<0.0010.00123.83.5–166.67
History of previous P. aeruginosa infection<0.0010.1213.71.79–111.1
Steroid use during prior 30 days0.007   
Chronic obstructive pulmonary disease0.040.03325.01.30–480.90
Leukemia0.05   

In a multiple logistic regression analysis using Control Group 1, the following variables were associated independently with multidrug-resistant P. aeruginosa infection: a history of chronic obstructive lung disease during the preceding year (odds ratio [OR], 24.99; 95% confidence interval [95% CI], 1.30–480.90), the use of carbapenem for ≥ 7 days during the preceding 90 days (OR, 23.90; 95% CI, 3.49–163.92), and a history of P. aeruginosa infection or colonization during the preceding year (OR, 13.77; 95% CI, 1.79–106.04). In a multiple logistic regression analysis using Control Group 2, no variables were associated independently with multidrug-resistant P. aeruginosa infection.

DISCUSSION

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES

In the univariate analysis using Control Groups 1 and 2 and in the multivariate analysis using Control Group 1, we found that the use of carbapenems for ≥ 7 days, a history of P. aeruginosa infection or colonization during the preceding year, and a history of chronic obstructive lung disease were associated independently with multidrug-resistant P. aeruginosa infection. This study was unique in two aspects: First, we selected patients for the case group who had infections caused by isolates with polyclonal DNA restriction patterns, as determined by pulsed-field gel electrophoresis. This case definition was used based on the premise that using a case group of patients with genotypically diverse strains would enable us to assess the risk factors associated with de novo selection of resistant organisms, and not horizontal transfer due to breach in infection-control measures.17 In virtually all previous case–control studies, patients who acquired infection with resistant microorganisms by de novo selection due to antibiotic pressure and those who acquired it through horizontal transfer of a single clone were included together for analysis. To our knowledge, ours is the first case–control analysis in which pulsed-field gel electrophoresis was used to identify case patients with infections caused by antibiotic-resistant organisms that had genetic diversity.

The second unique aspect of our study is that we used two control groups: patients with susceptible P. aeruginosa infection and patients at high clinical risk but without any isolation of P. aeruginosa from any clinical specimens. We used this approach to avoid overestimating the odds ratio for antibiotic use as a risk factor. There had been some concerns that the conventional method for selecting control patients in case–control analyses was not sufficient. In their systematic review, Harris et al. pointed out that case–control studies that analyze the risk factors for infection with antibiotic-resistant organisms may result in biased estimates if patients with antibiotic-susceptible microorganisms are used as controls.18 Harris and his group demonstrated that selecting control patients infected with antibiotic-susceptible organisms could result in falsely identifying certain antibiotics and overestimating the odds ratio of the resistance-defining antibiotic.19

The use of carbapenems for ≥ 7 days was identified as a risk factor for infections with multidrug-resistant P. aeruginosa using control patients infected with susceptible P. aeruginosa. In previous studies, the use of imipenem was identified as a risk factor for the subsequent emergence of imipenem-resistant P. aeruginosa.4, 20–23 However, in those previous studies, imipenem was assessed as a potential risk factor specifically for imipenem-resistant P. aeruginosa, and not for multidrug-resistant P. aeruginosa. In other previous studies, several antibiotics were tested as potential risk factors for infections with multidrug-resistant P. aeruginosa. Murray and Snydman described in their outbreak analysis that the use of aminoglycosides and other antibiotics was a risk factor for the emergence of multidrug-resistant P. aeruginosa infection.24 However, the majority of their case patients appeared to have been infected by a single clonal strain, and only 40% of those patients received aminoglycosides. In their review, Sanders and Sanders stated that receiving newer generations of cephalosporins was a risk factor for acquiring multiple β-lactam resistance due to inducible chromosomal β-lactamase occurring among gram-negative bacilli.25, 26 Those authors did not determine risk factors associated with resistance to other classes of antibiotics, such as fluoroquinolones and aminoglycosides. Muder et al. showed that the total number of days of antimicrobial exposure was associated with multidrug-resistant P. aeruginosa, but the use of any single antibiotic was not identified as a risk factor.12 Recently, Paramythiotou et al. studied the role of antibiotics with antipseudomonal activity in the development of multidrug-resistant P. aeruginosa in critically ill patients. In their multivariate analysis, the duration of ciprofloxacin therapy was a significant risk factor, with a trend observed for the duration of imipenem therapy.27

Several mechanisms for the emergence of resistance to carbapenems have been described. Mutational impermeability due to loss of OprD, which is a porin that forms transmembrane channels for carbapenems, is induced by the use of carbapenem and leads to resistance.28 If this were accompanied by the up-regulation of an efflux system, e.g., MexAB-OprM,29 then broad resistance to β-lactam and fluoroquinolone antibiotics would emerge. The second major factor is that metallo-β-lactamases hydrolize β-lactams, including carbapenems, but not aztreonam.30 Currently, P. aeruginosa that carries this β-lactamase is found in Asia31 and Europe32–34; although it is still rare, scattered cases have been reported from North America.35 An even more problematic point is that the genes for metallo-β-lactamases often are carried as cassettes within integrins, which are natural recombination systems that assemble series of acquired genes behind a single promoter.36 This raises the possibility that the emergence of metallo-β-lactamases may be accompanied by acquired resistance to other antibiotic classes, e.g., aminoglycoside.

Given these findings, it is reasonable to suggest that carbepenem use is a risk factor for multidrug-resistant P. aeruginosa, because carbapenem resistance, which can be induced or introduced under the pressure of carbapenem use, also is associated with broad resistance to other classes of antibiotics. The data from our study support the findings of Paramythiotou et al., who found that the duration of imipenem therapy was of borderline significance (multivariate analysis; P = 0.07) for the acquisition of multidrug-resistant P. aeruginosa.27

A history of P. aeruginosa infection during the preceding year also was associated independently with multidrug-resistant P. aeruginosa infection. A case series study by Harris et al.11 showed that multidrug-resistant P. aeruginosa emerges in a stepwise manner after exposure to antipseudomonal antibiotics and results in adverse outcomes. In the case–control study by Muder et al., the isolation of multidrug-resistant P. aeruginosa was associated with the total number of days of antimicrobial exposure (OR, 1.07; 95%CI, 1.01–1.12; P = 0.011).12

The current results suggest that patients with a history of prior infection by P. aeruginosa had had notable exposure to various antipseudomonal antibiotics. Consequently, the preexisting, antibiotic-susceptible P. aeruginosa eventually may have become multidrug resistant.

Finally, a history of chronic obstructive lung disease was associated independently with multidrug-resistant P. aeruginosa infection (OR, 24.99; 95% CI; 1.30–480.90). Previous studies showed that patients with chronic obstructive pulmonary disease are colonized with P. aeruginosa at a high rate.37–39 They not only frequently are colonized by P. aeruginosa, but they also are at high risk of infection. Furthermore, previous studies showed that chronic obstructive pulmonary disease is a risk factor for ventilator-associated pneumonia with P. aeruginosa.40, 41 These findings suggest that patients with this chronic lung condition would have more exposure to antipseudomonal antibiotics because of the frequent episodes of infection with P. aeruginosa.

The small number of patients in our case group is a limitation of this study that should be taken into consideration when interpreting the results. In addition, the inclusion of control patients was done retrospectively rather than screening patients prospectively, which may have led to an underestimation of the true prevalence of infection and colonization by antibiotic-susceptible P. aeruginosa among the patients in Control Group 1. Furthermore, because most of the patients in the study were not neutropenic and had solid tumors, it is likely that the outcome would be even less favorable among patients with leukemia and transplantation recipients. Therefore, it is important to validate further the findings of this study through future studies that include larger numbers of patients at higher risk.

In conclusion, this study to our knowledge is the first to determine risk factors associated with the acquisition of multidrug-resistant P. aeruginosa in patients with cancer. These risk factors were the use of carbapenems, a history of prior infection by P. aeruginosa, and chronic obstructive pulmonary disease. Thus, carbapenems should be considered carefully as a first-line, empirical therapy for the treatment of patients with cancer who have a prior pseudomonal infection or chronic obstructive pulmonary disease. Alternative antibiotic regimens that include antipseudomonal β lactams with or without aminoglycoside or fluoroquinolone, may need to be considered, particularly in the presence of the risk factors described above.

REFERENCES

  1. Top of page
  2. Abstract
  3. MATERIALS AND METHODS
  4. RESULTS
  5. DISCUSSION
  6. REFERENCES
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