囊性纤维化绿脓杆菌慢性感染急性发作期的联合抗菌药敏试验
摘要
研究背景
囊性纤维化患者急性肺部加重期的抗生素治疗，通常根据各个药物的抗菌药敏试验结果来选择。联合抗菌敏感性试验可评估两种或三种抗生素的药物组合在体外的抗菌效果，即使某些抗生素在单独使用时可能无法有效杀灭细菌，但在与其他抗生素联合使用时或许十分有效。因此，根据联合抗菌素敏感性试验选择抗生素，有可能改善囊性纤维化急性发作患者的治疗效果。本综述更新了先前发表的综述。
研究目的
本综述比较了基于常规抗菌药敏检测的抗生素治疗与基于联合抗菌药敏检测的抗生素治疗在治疗囊性纤维化和绿脓杆菌慢性感染者急性肺部加重症中的作用 。
检索策略
我们检索了Cochrane囊性纤维化和遗传疾病组专业注册库（Cochrane Cystic Fibrosis and Genetic Disorders Group Trials Register），包括检索的综合电子数据库和手工检索的相关期刊、以及会议论文集摘要册中的参考文献。最后检索日期：2020年3月19日。
我们还检索了正在进行的试验数据库。最后检索日期：2020年4月17日，
纳入排除标准
纳入标准为 基于常规抗菌药敏检测的抗生素治疗与基于联合抗菌药敏检测的抗生素治疗在囊性纤维化和绿脓杆菌慢性感染者急性肺部加重症的随机和半随机对照研究 。
资料收集与分析
两位综述作者分别独立对相关研究进行了筛选，评估试验质量以及提取资料。此外，作者联系了研究人员以获取更多信息。
主要结果
检索并纳入了一项符合纳入标准的的多中心研究。该研究前瞻性地评价了使用联合抗菌抗生素药敏检测是否能改善感染多重耐药菌的囊性纤维化急性肺加重参与者的临床结局。共有132名受试者参与了该实验并进行了随机分组。该研究调查者提供了82名仅感染绿脓杆菌的具体数据，他们的主要结局指标是下一次肺部加重的时间。对于仅感染绿脓杆菌受试对象，其后加重的风险比为0.82，优于对照组（95％置信区间（confidence interval, CI) [0.44, 1.51]) (P=0.52）。本次综述的结局指标中，没有针对感染绿脓杆菌的受试者的更多资料。我们认为纳入研究的偏倚风险低。对于仅提供绿脓杆菌感染个体数据的唯一解决指标，证据质量中等。对于其他结局，我们无法判断证据的质量，因为没有相关受试者子集的资料。
作者结论
目前的证据，仅限于一项研究，显示在治疗慢性绿脓杆菌感染的囊性纤维化患者的急性肺部加重症时，与基于联合抗菌药敏检测的抗生素相比，没有足够的证据来确定选择基于联合抗菌药敏检测的抗生素的效果更佳。未来需要进行大规模的国际和多中心研究，以进一步调查这一问题。
该综述收录的唯一一项研究发表于2005年，另外，截至2017年3月，我们没有发现任何进一步的相关研究。因此，在新的研究发表之前，我们将不更新本综述。
PICO
简语概要
联合抗生素检测治疗囊性纤维化绿脓杆菌急性感染
综述问题
我们比较了在长期（慢性）感染绿脓杆菌的人群中，传统抗生素检测（一次一个）与联合抗生素检测治疗急性呼吸道感染效果的证据 。
研究背景
囊性纤维化患者死亡的主要原因是慢性肺部感染。由于积极使用抗生素治疗肺部感染，现在囊性纤维化患者的寿命更长。按照以往经验，我们用抗生素分别对囊性纤维化患者肺部的细菌（或虫子）进行实验室检测，根据实验结果选择抗生素。某些抗生素在单独使用时可能无法有效杀灭细菌，但在与其他抗生素联合使用时或许十分有效。然而，囊性纤维化患者在选择抗生素治疗绿脓杆菌引起的肺部感染时，根据联合检测的结果来选择抗生素是否比根据单独检测的结果来选择更好，目前还不清楚。
本综述更新了先前发表的综述。
文献检索日期
证据检索更新至：2020年3月19日。
研究特征
检索发现有一项研究试图回答这个问题，并符合纳入标准。该研究招募了132名囊性纤维化患者，其中大部分人（82人）有急性肺部绿脓杆菌感染 ，并随机将他们分为两组治疗。在第一组中，经过联合抗生素试验，选择了两种抗生素；在第二组中，在测试了传统抗生素试验后选择了两种抗生素，以观察抗生素杀灭细菌的有效性。该研究在几个研究中心进行，并评价了参与者在14天疗程后的临床结局。
主要研究结果
该研究考察了不同细菌的感染情况，调查人员仅仅提供是那些感染了绿脓杆菌患者的主要结局（直到下一次急性肺部感染的时间）。与根据单抗生素检测相比，根据联合抗生素检测结果选择抗生素并不会延长下一次肺部感染前的时间。在我们的综述中，他们无法为我们提供任何感染绿脓杆菌的人的其他结局信息。
证据质量
参加治疗的人是完全随机地被分成不同的治疗组，分组情况不可预测，这一点令我们感到满意。我们还满意地看到，在研究过程中，无论是受试者还是医务人员都对分组情况毫不知情。研究中没有数据遗漏。我们所获得数据的唯一结局指标（下一次肺部感染的时间）的证据质量为中等，但我们无法判断其他结局指标的证据质量，因为没有感染绿脓杆菌的受试者单独的结果。
Authors' conclusions
Summary of findings
| Combination antimicrobial susceptibility testing compared with conventional treatment (separate testing) for pulmonary exacerbation due to Pseudomonas aeruginosa in people with cystic fibrosis | ||||||
| Patient or population: adults and children with pulmonary exacerbation due to Pseudomonas aeruginosa Settings: inpatient Intervention: combination antimicrobial susceptibility testing Comparison: conventional treatment (separate susceptibility testing) | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | Number of participants | Quality of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Assumed risk | Corresponding risk | |||||
| conventional treatment | combination susceptibility testing | |||||
| Lung function Follow up: 14 days treatment with follow up every 3 months for up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | Lung function outcomes were not reported separately for individuals with infection due to Pseudomonas aeruginosa. | |
| Time to next exacerbation Follow up: up to 4.5 years | The only data available for the time to next exacerbation due to Pseudomonas aeruginosa gave a hazard ratio of 0.82 for the conventional (control) group compared to the combination antimicrobial susceptibility testing group (95% CI 0.44 to 1.51) (P = 0.52). | N/A | 1 (82) | ⊕⊕⊕⊝ | ||
| Quality of life | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported in the included study. | |
| Length of hospital stay Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. | |
| Sputum bacterial density (CFU/mL) Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. | |
| Adverse events Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. There were 9 serious adverse events in all participants: 2/64 in the combination antimicrobial susceptibility testing group and 7/68 in the control group (P = 0.17). | |
| Mortality Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. There were 2 deaths in all participants during the study period, both in the control group. | |
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| a Downgraded once for imprecision as there is only one included study and therefore the number of participants is low. | ||||||
Background
Description of the condition
Cystic fibrosis (CF) is the most common life‐limiting genetic condition in populations of northern European descent (Farrell 2018) and respiratory failure caused by chronic pulmonary infection is the primary cause of death in people with CF (Gibson 2003). Staphylococcus aureus and Haemophilus influenzae are typically initially detected in respiratory cultures. Over time, people with CF become chronically infected with mucoid Pseudomonas aeruginosa (P aeruginosa) with associated declining pulmonary function and increasing symptoms (Burns 2001; Henry 1992; Kosorok 2001; Pamukcu 1995).
Description of the intervention
Over the past several decades, the life expectancy of people with CF has increased significantly, due partly to the aggressive use of antibiotics in the treatment of respiratory infections (Gibson 2003). The standard of care for the treatment of pulmonary exacerbations includes intravenous (IV) antibiotic use. Bacterial strains isolated from the respiratory tract of people with CF are commonly tested for in vitro antimicrobial susceptibility. Conventional in vitro antimicrobial susceptibility testing is performed on selected morphotypes, or colony types, of bacteria such as P aeruginosa. However, there may be a significant amount of variability in the antimicrobial susceptibility patterns of different morphotypes and even of individual colonies of the same morphotype of P aeruginosa (Foweraker 2005). Conventional antimicrobial susceptibility testing may thus underestimate resistance and results are often not reproducible. Although in vitro antimicrobial susceptibility testing has been shown to be of benefit in guiding antibiotic choices for pulmonary infections in people who do not have CF, the role of conventional susceptibility testing in guiding the treatment of pulmonary exacerbations in people with CF is less clear (Gaillard 1995; Smith 2003). In fact, clinicians will often ignore the results of susceptibility testing of bacterial strains obtained during a pulmonary exacerbation if the individual is already improving on IV antibiotics.
How the intervention might work
If conventional antimicrobial susceptibility testing identifies a multi‐drug resistant bacterial strain from the respiratory tract of an individual with CF, combination antimicrobial susceptibility testing may be undertaken on the strain. This type of testing often shows that combinations of two or three antibiotics have in vitro activity against a bacterial isolate when individual antibiotics have little or none (Aaron 2000; Saiman 1996). Although combination antibiotic therapy may be better than antibiotic monotherapy to treat CF exacerbations caused by P aeruginosa (Smith 1999), choosing antibiotics based on multiple combination bactericidal antibiotic testing (MCBT), a type of combination antimicrobial susceptibility testing, may not affect clinical outcomes (Aaron 2005).
Both conventional and combination antimicrobial testing are usually performed on bacteria growing planktonically or "free‐floating". There is growing evidence that bacterium such as P aeruginosa actually grows as a biofilm or a "slime layer" in the airways of people with CF with chronic pulmonary infections (Drenkard 2002; Singh 2000). Biofilms are communities of bacteria embedded in an exopolysaccharide matrix and are highly resistant to killing by antibiotics (Prince 2002). Work has been done to develop antimicrobial susceptibility testing based on biofilm growth of bacteria rather than planktonic growth in an effort to mimic the pathophysiology of the CF lung (Ceri 1999; Moskowitz 2004; Moskowitz 2005). Although biofilm antimicrobial susceptibility testing of P aeruginosa strains has demonstrated different, more resistant susceptibility profiles, the effect of these results on treatment outcomes has yet to be determined.
Why it is important to do this review
In light of the uncertainties we have described, we aimed to compare antibiotic therapy based on conventional antimicrobial susceptibility testing to antibiotic therapy based on combination antimicrobial susceptibility testing in the treatment of acute pulmonary exacerbations in CF.
This is an updated version of a previously published review (Waters 2008; Waters 2015; Waters 2017).
Objectives
The objective was to compare antibiotic therapy based on conventional antimicrobial susceptibility testing to antibiotic therapy based on combination antimicrobial susceptibility testing in the treatment of acute pulmonary exacerbations in people with CF and chronic infection with P aeruginosa.
Methods
Criteria for considering studies for this review
Types of studies
Randomised (RCTs) and quasi‐randomised controlled trials.
Types of participants
Adults and children (with all levels of disease severity) diagnosed with CF, confirmed with sweat test or genetic testing or both with an acute pulmonary exacerbation due to P aeruginosa.
Types of interventions
We compared antibiotic therapy based on conventional antimicrobial susceptibility testing to antibiotic therapy based on combination antimicrobial susceptibility testing for treating acute pulmonary exacerbations in CF due to chronic infection with P aeruginosa.
An acute pulmonary exacerbation was defined according to symptoms, chest examination findings and change in forced expiratory volume in one second (Rosenfeld 2001). We defined chronic infection as follows: when measured monthly over a 12‐month period, more than 50% of months when samples had been taken, were P aeruginosa culture positive (Lee 2003).
Types of outcome measures
We planned to measure outcomes at less than a week, one to two weeks, more than two weeks to three weeks, more than three weeks to four weeks; the outcome 'Time to next pulmonary exacerbation' would be measured in monthly intervals after these time points. We would have also considered outcomes measured at other time points.
Primary outcomes
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Lung function
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forced expiratory volume in one second (FEV1) (L/min or % predicted)
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forced vital capacity (FVC) (L/min or % predicted)
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Time to next pulmonary exacerbation
Secondary outcomes
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Quality of life
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Length of hospital stay
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Sputum bacterial density measured in colony forming units/mL (CFU/mL)
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Adverse events
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Mortality
Search methods for identification of studies
There are no restrictions regarding language or publication status.
Electronic searches
We identified relevant trials from the Group's Cystic Fibrosis Trials Register using the term 'susceptibility testing' OR 'sensitivity testing'.
The Cystic Fibrosis Trials Register is compiled from electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL) (updated each new issue of the Cochrane Library), weekly searches of MEDLINE, a search of Embase to 1995 and the prospective handsearching of two journals ‐ Pediatric Pulmonology and the Journal of Cystic Fibrosis. Unpublished work is identified by searching the abstract books of three major cystic fibrosis conferences: the International Cystic Fibrosis Conference; the European Cystic Fibrosis Conference and the North American Cystic Fibrosis Conference. For full details of all searching activities for the register, please see the relevant sections of the Cystic Fibrosis and Genetic Disorders Group website.
Date of the most recent search of the Group's Cystic Fibrosis Trials Register: 19 March 2020.
We also checked the National Institutes of Health (NIH) sponsored website (www.clinicaltrials.gov) and the WHO ICTRP website (apps.who.int/trialsearch/)* for any ongoing studies with potential interim results. For search terms please see the appendices (Appendix 1).
Date of last search: 08 April 2020.
*For update 2020, this database is not currently available due to Covid‐19.
Searching other resources
We checked the reference lists of all studies identified for any further relevant studies.
Data collection and analysis
Selection of studies
For the original review and updates to 2017, two authors (VW, FR) independently applied the inclusion criteria to all potential studies; thereafter SS and TR undertook this task. The authors were not blinded to the studies. The authors planned to resolve any disagreements by discussion with a third person (Nikki Jahnke (NJ)).
Data extraction and management
Using a data collection form, or the original review and updates to 2017, two authors (VW, FR) independently obtained data from published reports or from study investigators. From the 2020 update, SS and TR would have undertaken this task had any new studies been identified. They would have resolved any disagreement by discussion with a third person (Nikki Jahnke (NJ)). In addition to information about study references and authors and verification of study eligibility, the data collection form included information about the methods of the study (e.g. study duration, type of trial, blinding, number of dropouts and potential confounders). The authors also reported characteristics of the study participants including age, sex and setting of the study on the form. The authors described the intervention, specifically antibiotic therapy, with regards to type of antibiotic, route of delivery, doses and length of treatment. The authors collected data for all randomised participants. When possible, the authors planned to record the mean change (before and after antibiotic therapy) in FEV1 and FVC, the mean quality of life score after antibiotic therapy, the mean hospital length of stay, the mean change in sputum bacterial density (before and after antibiotic therapy) and the number of adverse events and mortalities. For each mean value, they also planned to obtain the standard deviation. For time to next exacerbation, they planned to collect log‐rank estimates and Cox model estimates.
Assessment of risk of bias in included studies
For the original review and updates to 2017, two authors (VW, FR) independently assessed the risk of bias of the included study, originally using the following criteria (Jüni 2001), which they later adapted and expanded using the criteria in the Cochrane risk of bias tool. From the 2020 update, SS and TR checked the existing judgements and would have undertaken this task for any new studies identified.
Assessment of generation of allocation sequences
The authors assessed each study as to the generation of allocation sequences:
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adequate: if allocation sequence is suitable to prevent selection bias (i.e. random numbers table, drawing envelopes, tossing a coin, throwing dice etc);
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inadequate: if allocation sequence could be related to prognosis and thus introduce selection bias (i.e. assigning participants based on case record number, date of birth, date of admission etc);
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unclear: if the study is described as randomised but the method used to generate the allocation sequence is not stated.
Assessment of concealment of allocation sequences
The authors also assessed the method used to conceal the allocation sequences in each study:
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adequate: if participants and investigators cannot predict which group the participant will be assigned to (i.e. coded drug containers, central randomisation, numbered, sealed, opaque envelopes etc);
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inadequate: if participants and investigators can predict which group the participant will be assigned to and thus introduce selection bias (i.e. open allocation schedule, non‐opaque envelopes etc);
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unclear: if the method of concealing the allocation sequence is not described.
Assessment of blinding
In order to determine the potential for performance and detection bias, the authors assessed each study with respect to the degree of blinding:
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the participant is blinded to participant assignment;
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the care provider is blinded to participant assignment;
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the investigator measuring study outcomes is blinded to participant assignment.
Assessment of follow up
To assess for the possibility of attrition bias, the authors examined each study with respect to:
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whether or not it was stated how many participants were lost to follow up and why they were lost to follow up;
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whether or not an intention‐to‐treat analysis was used (i.e. inclusion in the final analysis of all randomised participants into a trial in the groups to which they were randomised irrespective of what happened subsequently).
Incorporating assessments of study validity in reviews
The authors planned to weigh studies according to the inverse of the variance of the estimated measure of effect. If they considered there was a high risk of bias, we would have investigated the effects of this with a sensitivity analysis (see below).
Measures of treatment effect
For dichotomous data (adverse events, mortality), the authors planned to gather information on participants randomised to each treatment group, based on an intention‐to‐treat analysis. They planned to include interim results from individual randomised participants from ongoing studies in the analysis. They defined time points for each study outcome according to when it was measured (less than a week, one to two weeks, more than two weeks to three weeks, more than three weeks to four weeks); they planned to analyse study outcomes separately according to these time points. As the authors identified only one study for inclusion in the review, they did not combine results from different studies. However, for future updates, when they are able to include more studies, they plan to pool the treatment effect across studies to determine an odds ratio with 95% confidence intervals for each study outcome.
For continuous data (FEV1, FVC, quality of life, length of hospital stay, sputum bacterial density), the authors planned to calculate the difference between the mean values (mean difference (MD)) of treatment effect for each group. As a summary statistic across studies, they will use the MD if the same scale is used or the standardised mean difference (SMD) if different scales are used (e.g. quality of life measurements). For time‐to‐event data (time to next exacerbation), most studies use Kaplan‐Meier survival analysis. The authors thus planned to collect log‐rank estimates and Cox model estimates to subsequently summarise the time‐to‐event data as a hazard ratio with 95% CIs (Higgins 2011; Parmar 1998).
Unit of analysis issues
If the authors identify cluster‐randomised studies in the future, they will include the data if the relevant information is available. The authors will calculate the intracluster correlation coefficient (ICC) according to Donner (Donner 2001).
Dealing with missing data
Although a true intention‐to‐treat analysis must include all participants who were randomised, regardless of whether their outcomes were actually collected, in reality, data are often missing for participants who are lost to follow up. This was not the case in the only study included in the review. However, for future updates, the authors will perform an available‐case analysis (analysing data for every participant for whom the outcome is obtained) in these situations. The authors will collect the percentages of participants from whom no outcome data were available and will report these on the data collection form. The authors will include data on only those whose results are known, using as a denominator the total number of people who completed the study for the particular outcome in question. The authors will consider the variation in the degree of missing data across studies as a potential source of heterogeneity.
Assessment of heterogeneity
In performing a meta‐analysis, the authors planned to measure the variability of results between trials (heterogeneity) using the I² statistic described by Higgins (Higgins 2003). The I² statistic describes the percentage of total variation across studies that is due to heterogeneity rather than by chance. It is calculated using Cochran's heterogeneity statistic and the degrees of freedom. The I² statistic can range from 0% to 100%, where a value of 0% indicates no observed heterogeneity and larger values show increasing heterogeneity. A value greater than 50% may be considered substantial heterogeneity.
Assessment of reporting biases
As the searches identified only one study which was eligible for inclusion, the authors were not able to assess publication bias. If sufficient studies are included in the future, they will assess publication bias in a future update by constructing a funnel plot. In the absence of bias, the plot should resemble a symmetrical inverted funnel (Higgins 2011). If there is asymmetry, the authors will consider publication bias and other reasons (such as location biases, true heterogeneity, poor methodological quality of smaller studies etc.) as a potential cause.
Data synthesis
The authors identified only one study for inclusion the review. For future updates, if the authors include more studies, they plan to combine multiple studies as follows. If the studies are too clinically diverse (e.g. different lengths of antibiotic treatment), the authors will not perform a meta‐analysis. If the studies are considered clinically similar enough to combine and where there is no significant heterogeneity, they will calculate the pooled effect estimates using a fixed‐effect model. If there is statistical heterogeneity, the authors will investigate as outlined below and will perform a random‐effects meta‐analysis to incorporate heterogeneity among studies.
Subgroup analysis and investigation of heterogeneity
If the authors find significant heterogeneity (assessment as detailed above and P < 0.10 by the Q test) (Higgins 2011), they will explore the potential causes of this (i.e. different types of antimicrobial susceptibility testing, different participant populations etc) and if possible, conduct subgroup analyses of the studies. For example, study results may vary if different types of combination antimicrobial susceptibility testing are used (e.g. MCBT compared to checkerboard dilution assays). In addition, results may vary if one study has more adult participants who can produce sputum (a more accurate sample with potentially more reliable susceptibility results) and another study has more pediatric participants who can only do throat swabs (a less reliable respiratory tract sample).
Sensitivity analysis
When the authors are able to include more studies in the review, they will perform a sensitivity analysis to determine the robustness of the results. They will investigate whether changing which studies are included, based on our assessment of the methodological quality (including or excluding CCTs, including or excluding trials reporting degrees of blinding etc.) or changing our chosen statistical model (i.e. random effects model compared to a fixed‐effect model) changes the results of our review. If the sensitivity analysis does not significantly change the results, it strengthens the confidence that can be placed in these results.
Summary of findings and assessment of the certainty of the evidence
In a post hoc change to the protocol we have included a summary of findings table for the comparison of combination antibiotic susceptibility testing with conventional single antibiotic susceptibility testing (summary of findings Table 1).
We included the following outcomes: change in lung function (FEV1 and FVC % predicted and L/min), time to next exacerbation, quality of life, length of hospital stay, sputum bacterial density (measured in CFU/mL), adverse events and mortality.
To determine the quality of the evidence we used the GRADE approach in which the quality of the evidence is downgraded where there was high risk of bias in included trials, indirectness of the evidence to our population of interest, imprecision of the results or a high risk of publication bias. The quality of evidence may be downgraded once if the reason is serious and twice if the reason is deemed to be very serious.
Results
Description of studies
Results of the search
The searches identified four studies and only one study was eligible for inclusion in the review (Aaron 2005).
Included studies
The only included study was a multicentre, randomised, double‐blind controlled clinical study that prospectively assessed whether the use of combination antibiotic susceptibility testing improved clinical outcomes in participants with acute pulmonary exacerbations of CF who were infected with multiresistant bacteria. Participants who developed an exacerbation of pulmonary disease were randomised to receive a 14‐day course of any two IV antibiotics (labelled "antibiotic #1" and "antibiotic #2") chosen on the basis of either results from conventional sputum culture and sensitivity testing or the result of MCBT. Individuals were eligible for enrolment into the study if they had a confirmed diagnosis of CF, were at least 12 years old, could spontaneously produce sputum for culturing and were chronically infected with multiresistant P aeruginosa, Burkholderia cepacia complex, Stenotrophomonas maltophilia or Achromobacter xylosoxidans. Although the study included participants who were infected with different types of multiresistant organisms, the majority were infected with P aeruginosa (67.2% in the MCBT group and 57.4% in the control group). The authors have provided us with the data specific to the participants who were only infected with P aeruginosa for the study's primary outcome; however the information about the study participants given below pertains to the whole study cohort. The primary outcome of the study was time from randomisation until the participant's next pulmonary exacerbation and corresponded to the length of participant follow up. Outcome measurements were taken and reported for day 0 and day 14 of antibiotic treatment.
A total of 132 participants were randomised in the study; 64 to the MCBT‐treated group and 68 to the conventionally‐treated (control) group. All 132 participants received the intended treatment and all 132 participants were included in the final analysis. The mean age (SD) in the MCBT group was 29.5 years (8.2) and in the control group was 25.8 years (6.5). In the MCBT group, 29 participants were male and 35 were female and in the control group, 31 were male and 37 were female. The baseline FEV1 (SD) in the MCBT group was 1.67 L (0.66) and was 1.63 L (0.67) in the control group. The number of participants with diabetes was 15 (23.4%) in the MCBT group and 13 (19.1%) in the control group. The number of participants with pancreatic insufficiency was 63 (98.4%) in the MCBT group and 65 (95.6%) in the control group. The number of participants with liver disease was 6 (9.4%) in the MCBT group and 8 (11.8%) in the control group.
Excluded studies
Two studies were excluded as they did not examine combination antimicrobial testing (Oermann 2013; Wainwright 2011). The remaining two studies were excluded as they examined biofilm antimicrobial susceptibility testing (Moskowitz 2011; Yau 2015).
Risk of bias in included studies
The overall risk of bias was minimal in the included study (Figure 1).
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
Allocation
Allocation of participants was done through a computer‐generated random listing of the two treatment assignments blocked in groups of four and stratified by site; this was therefore graded as adequate (low risk of bias). Randomisation was undertaken centrally through the research pharmacy. The research staff, participants and caregivers were unaware of the allocation. Thus the concealment of allocation was graded as adequate (low risk of bias).
Blinding
The person responsible for participant care, the participant and the outcome assessor were all blinded leading to a judgement of a low risk of bias.
Incomplete outcome data
All 132 participants receiving an intervention were included in the final analysis (intention‐to‐treat analysis) presented in the study report. There were no withdrawals from the study (low risk of bias).
Selective reporting
Although the study itself reported all the data for all participants enrolled (low risk of bias), we were only able to retrieve data for one study outcome (time to subsequent exacerbation) for participants infected with P aeruginosa. However, this was the study's primary outcome and is a clinically relevant outcome listed in this review.
Other potential sources of bias
We judged there to be an unclear risk from other sources of bias for a number of reasons. In this study antibiotics were prescribed for participants randomised to the MCBT arm by one investigator, whereas antibiotics were prescribed for participants randomised to the control arm by the participants' own doctors. This approach was necessary, since the local physicians had to remain blinded to the MCBT results, but it could have affected the study outcomes. A second limitation is that this study was powered to show a 79% increase in the time to next exacerbation, but did not have the statistical power to exclude a smaller effect of MCBT‐directed therapy. FInally, conventional clinical microbiological testing and MCBT testing both involve the culture of planktonically growing bacteria (i.e., free floating bacteria growing in broth). Bacteria growing in biofilms, e.g. P aeruginosa, have been shown to be significantly more resistant to antimicrobials than those growing planktonically.
Effects of interventions
Primary outcomes
1. Lung function
a. FEV1 (L/min or % predicted)
Data specific for the participants with only P aeruginosa infection were not available for this outcome.
b. FVC (L/min or % predicted)
Data specific for the participants with only P aeruginosa infection were not available for this outcome.
2. Time to next pulmonary exacerbation
Seven participants (three in the MCBT group and four in the control group) did not have a subsequent pulmonary exacerbation during the study follow‐up period (up to 4.5 years). Based on information sent to us directly from the study investigator, for the participants specifically infected with only P aeruginosa, the hazard ratio for subsequent exacerbation was 0.82 for the conventional (control) group compared to the MCBT group (95% CI 0.44 to 1.51) (P = 0.52) (Aaron 2005).
Secondary outcomes
1. Quality of life
Although the included study measured dyspnoea using the transitional dyspnoea index score, the study did not have a validated measurement of quality of life (Aaron 2005).
2. Length of hospital stay
Data specific for the participants with only P aeruginosa infection were not available for this outcome.
3. Sputum bacterial density (CFU/mL)
Data specific for the participants with only P aeruginosa infection were not available for this outcome.
4. Adverse events
Data specific for the participants with only P aeruginosa infection were not available for this outcome. However, the study did report serious adverse events for all participants. There were two serious adverse events (one case of allergic rash and one case of reversible hepatitis) in the MCBT group and seven serious adverse events in the control group (five cases of allergic rash and two deaths due to respiratory failure; P = 0.17).
5. Mortality
Data specific for the participants with only P aeruginosa infection were not available for this outcome. However, the study did report two deaths in the whole study cohort.
Discussion
Summary of main results
The only included study showed that the use of MCBT to guide antibiotic treatment of people with CF with acute pulmonary exacerbations due to P aeruginosa did not result in longer times to subsequent pulmonary exacerbations (Aaron 2005).
Overall completeness and applicability of evidence
It is important to note that the results of this study are based on one method of MCBT and they may not be generalizable to other methodologies such as checkerboard dilution assays. The primary outcome chosen by the investigators, time until the next pulmonary exacerbation, is highly clinically relevant to people with CF. However, the Aaron study was powered to detect a difference in this outcome for people with CF infected with several different types of multiresistant gram negative bacteria and not for people with CF infected with only P aeruginosa (subject of this review).
Any individual with CF who was chronically infected with multiresistant gram negative bacteria was eligible for enrolment into the study. However, in practice, MCBT tends to be reserved for those who fail empirically chosen antibiotic treatment or who have respiratory bacterial strains that are resistant to all antibiotics tested by conventional methods. It is possible that the use of MCBT may improve outcomes in this subset of people with CF.
In addition, testing antibiotics against bacteria grown planktonically, or "free‐floating", in the laboratory may not accurately reflect the environment in the CF lung. For example, P aeruginosa is known to grow as a biofilm, or a slime layer, in the sputum of people with CF (Drenkard 2002; Singh 2000). Antimicrobial susceptibility testing based on biofilm growth of P aeruginosa may therefore be a more rational way of choosing antibiotics to treat pulmonary exacerbations and may lead to improved clinical outcomes in people with CF.
Quality of the evidence
The main strengths of the study were the quality of the methods (randomisation, allocation concealment and blinding) and the choice of a clinically relevant primary outcome.
If the antibiotics chosen based on the MCBT test were more effective than those chosen based on the conventional test, we would expect the pulmonary bacterial load to decrease more in the MCBT group than in the control group, leading to a longer time before a subsequent exacerbation (Regelmann 1990; Smith 1999). The Aaron study was powered to detect a difference in the time until the next pulmonary exacerbation in people with CF infected with several different types of multiresistant gram negative bacteria.
There were some limitations to the study. The study was only powered to show a minimum of 79% increase in the time to next exacerbation and did not have the power to detect a smaller increase in the time to next exacerbation. Given the multifactorial nature of pulmonary exacerbations in CF, it is unlikely that antibiotic choices alone could almost double the time to next exacerbation. Therefore, we cannot exclude a smaller effect of MCBT‐guided therapy. Furthrmore, in the included study, one person prescribed antibiotics for the MCBT group while multiple individual physicians prescribed antibiotics for the control group. Although this was meant to simulate "real life" conditions, it introduces a significant degree of variability that the authors could not control for as there is no standardized method for choosing antibiotics. Choosing antibiotics based on their ability to kill bacteria in vitro may also not be as important as their potential anti‐inflammatory effects. The study investigators correctly point out that the use of antibiotics such as azithromycin, which has no bactericidal effect against P aeruginosa, but may have an anti‐inflammatory effect, has been associated with clinical improvement in people with CF (Equi 2002; Saiman 2003).
Overall, we found the quality of the body of evidence to be moderate for the only outcome (time to next exacerbation) for which data were available for those people with infection due to P aeruginosa; for other outcomes we were unable to judge the quality of the evidence as no data were available for the relevant subset of participants (summary of findings Table 1).
Potential biases in the review process
Overall, there was little risk of bias in the review process. We performed a comprehensive search of the literature not limited by language; we used broad search terms when searching the Cochrane CF clinical trials register, the clinicaltrials.gov website and the WHO trials website. The two authors independently assessed the studies, extracted the data, analysed the data and assessed the studies for bias.
Agreements and disagreements with other studies or reviews
There are no other studies or trials examining this particular question in CF. However, other studies that have examined the relationship between in vitro antimicrobial susceptibility testing and clinical outcomes in individuals with CF have similarly been unable to find a correlation. No study to date has identified a superior antibiotic regimen in the treatment of pulmonary exacerbations in people with CF, highlighting the multifactorial, complex nature of the infection and response to therapy.
Risk of bias summary: review authors' judgements about each risk of bias item for each included study.
| Combination antimicrobial susceptibility testing compared with conventional treatment (separate testing) for pulmonary exacerbation due to Pseudomonas aeruginosa in people with cystic fibrosis | ||||||
| Patient or population: adults and children with pulmonary exacerbation due to Pseudomonas aeruginosa Settings: inpatient Intervention: combination antimicrobial susceptibility testing Comparison: conventional treatment (separate susceptibility testing) | ||||||
| Outcomes | Illustrative comparative risks* (95% CI) | Relative effect | Number of participants | Quality of the evidence | Comments | |
|---|---|---|---|---|---|---|
| Assumed risk | Corresponding risk | |||||
| conventional treatment | combination susceptibility testing | |||||
| Lung function Follow up: 14 days treatment with follow up every 3 months for up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | Lung function outcomes were not reported separately for individuals with infection due to Pseudomonas aeruginosa. | |
| Time to next exacerbation Follow up: up to 4.5 years | The only data available for the time to next exacerbation due to Pseudomonas aeruginosa gave a hazard ratio of 0.82 for the conventional (control) group compared to the combination antimicrobial susceptibility testing group (95% CI 0.44 to 1.51) (P = 0.52). | N/A | 1 (82) | ⊕⊕⊕⊝ | ||
| Quality of life | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported in the included study. | |
| Length of hospital stay Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. | |
| Sputum bacterial density (CFU/mL) Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. | |
| Adverse events Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. There were 9 serious adverse events in all participants: 2/64 in the combination antimicrobial susceptibility testing group and 7/68 in the control group (P = 0.17). | |
| Mortality Follow up: up to 4.5 years | Outcome not reported ‐ see comment. | N/A | N/A | N/A | This outcome was not reported separately for people with infection due to Pseudomonas aeruginosa. There were 2 deaths in all participants during the study period, both in the control group. | |
| *The basis for the assumed risk (e.g. the median control group risk across studies) is provided in footnotes. The corresponding risk (and its 95% confidence interval) is based on the assumed risk in the comparison group and the relative effect of the intervention (and its 95% CI). | ||||||
| GRADE Working Group grades of evidence | ||||||
| a Downgraded once for imprecision as there is only one included study and therefore the number of participants is low. | ||||||
