Role of Procalcitonin in Managing Adult Patients With Respiratory Tract InfectionsProcalcitonin for Managing Respiratory Infections FREE TO VIEW

Respiratory infections remain the most common illness in humans, the most prevalent reason why patients seek acute medical care, and the most frequent and prevalent source of sepsis.^1,2 Despite advances in medical science, respiratory infections cause more disease and death than any other infection, with only little change in mortality rates over the past few decades.³ Although mortality is attributable primarily to bacterial pneumonia and severe influenza infections, most patients with respiratory infections tend to have mild viral disease.⁴ Importantly, around 75% of all antibiotic doses are prescribed for acute respiratory tract infections; of these, most are caused by viruses, not bacteria.⁵ Early differentiation of severe cases from milder infections is essential and a major challenge when managing patients with respiratory infections. This fact is of particular importance in light of studies demonstrating the benefit of early and appropriate antibiotic courses in cases of bacterial pneumonia,⁶ and, at the same time, the need to reduce unnecessary antibiotic overuse to prevent bacterial resistance^7,8 and other complications of antibiotics, such as Clostridium difficile infection. In addition, accurate prognostication of patients improves initial triage and site-of-care decisions that have important health and financial implications.⁹

Reliable clinical signs and rapid microbiologic tests to diagnose bacterial infections confidently and to identify other, nonbacterial, causes not in need of antibiotic therapy are largely lacking.¹⁰ Time-related delays inherent in culture methods, low sensitivity of blood cultures, and low specificity of sputum cultures due to quality of samples, colonization, or contamination are major limitations of these methods for everyday practice.¹¹ A novel approach to estimate the likelihood of bacterial infections and the severity of disease is the use of blood biomarkers mirroring the host response to infection, and indirectly, the severity of infection. Although an enormous number of different mediators and markers have been suggested as promising candidates, only a few of them have been tested rigorously in clinical outcome studies and have found their way into clinical practice.

One such blood marker, procalcitonin (PCT), has been evaluated in a number of clinical research studies and has been shown to be a more specific marker for bacterial infections compared with more traditional markers such as C-reactive protein and WBC.¹⁰ PCT is released in multiple tissues in response to bacterial infections via a direct stimulation of cytokines, such as IL-1β, tumor necrosis factor-α, and IL-6. The upregulation of PCT correlates with the severity^10,12‐14 and extent^11,15,16 of bacterial infections.

Conversely, interferon-γ, a cytokine released in response to viral infections, blocks the upregulation of PCT, resulting in a higher specificity of PCT toward bacterial infections.^17‐20 Quantitatively, PCT may help distinguish severe bacterial infections from milder viral illnesses.²¹

In addition, PCT shows an interesting kinetic profile over time, with a prompt increase within 6 to 12 h upon stimulation and a daily decrease of around 50% in the event that the infection is controlled by the immune system supported by effective antibiotic therapy.²² Another favorable characteristic of PCT is that it appears not to be influenced by corticosteroid treatments. Two studies found similar PCT levels in patients with and without corticosteroid treatment; one study included critically ill patients taking high doses of systemic corticosteroids (20-1,500 mg prednisone/d), whereas the other focused on biomarker levels of healthy volunteers after endotoxin injection treated with lower doses of prednisolone (30 mg/d).^23,24

Based on these characteristics, many researchers have evaluated the usefulness of PCT in improving the clinical management of patients. The aim of this review, focusing on respiratory infections, is to give physicians an overview of the potential usefulness and limitations of PCT in diagnosing bacterial infections, differentiating bacterial from viral diseases, prognosticating regarding the severity of a patient’s condition, and guiding clinical decisions about when to initiate antibiotic therapy and when it can be safely discontinued.

Identifying a true “gold standard” for the diagnosis of respiratory infections is often problematic. The use of blood and sputum cultures have significant limitations^25,26 because of the duration of time required to obtain positive cultures and issues of colonization and contamination. Additionally, the inability to grow certain bacteria in standard cultures, as evidenced by the fact that causative microorganisms can be detected in only 10% to 20% of patients with respiratory infections, further confounds the diagnostic process.^9,11 Research on the diagnosis of respiratory infections is hampered by this lack of a gold standard and, therefore, may be difficult to interpret. Because of these limitations, previous studies and meta-analyses evaluating diagnostic markers that rely on observational studies have produced contradictory conclusions.^27,28

In the clinical setting, one potential option for improving the diagnosis of bacterial infections is biomarkers that rise selectively in response to bacterial infection. To investigate this function of PCT, researchers have investigated a number of different clinical conditions to identify whether PCT has helped differentiate bacterial from other infections.

In one study, Müller et al¹¹ evaluated PCT in 925 patients with community-acquired pneumonia (CAP). In this cohort, 7.9% of subjects had bacteremic CAP with typical pathogens, mostly Streptococcus pneumoniae. PCT was increased significantly in bacteremic patients compared with patients without an identified bacterial pathogen with an area under the receiver operating curve (AUC) of 0.82. Less than 1% of patients had a positive blood culture when their initial PCT level was < 0.25 μg/L, which increased to > 20% in patients with PCT > 2.5 μg/L. Similar results concerning bacteremia have been reported in other CAP cohorts (AUC, 0.85),¹⁰ for patients with pyelonephritis¹⁶ and patients in the ED with fever.²⁹

Another study focused on the potential of PCT to differentiate patients with a viral respiratory infection with or without bacterial superinfection. This was investigated in 103 patients with confirmed 2009 influenza A(H1N1) pneumonia in a critical care setting in France.²¹ PCT had an AUC of 0.90 for differentiating the 48 patients with bacterial superinfection from patients with viral pneumonia only. At a PCT cutoff of 0.8 μg/L, the negative predictive value was 91% to exclude bacterial superinfection. Similar results were reported from other studies in Korea³⁰ and Spain.³¹

Other researchers have investigated whether PCT can predict the specific pathogens causing respiratory infections. Whereas patients with severe infections caused by Legionella species have shown high PCT levels,³² other atypical pathogens such as mycoplasma do not appear to induce a strong PCT response in patients.³³ A large German CAP cohort found that PCT was highest in patients with typical bacterial causation, but did not allow prediction of specific cause in individual patients.³³

For other respiratory infections, such as ventilator-associated pneumonia (VAP)³⁴ or TB,³⁵ clinical studies have produced mixed results and the clinical usefulness of PCT as a diagnostic test has not been established conclusively. For VAP, recent studies suggested that serial measurements may be the preferred approach, but at additional cost.^36,37

These data show that PCT should not be used as a traditional diagnostic test because it does not clearly identify specific pathogens. Yet its impact may be more pronounced in identifying the higher likelihood of a relevant bacterial infection that increases with increasing PCT concentrations and, conversely, falls if the PCT level is low. Optimal “diagnostic cutoffs” are different according to the severity of presentation and clinical setting (eg, primary care or ICU), and may also depend on pathogen characteristics and antibiotic pretreatment (Fig 1).³⁸

Accurate assessment of disease severity and predictions regarding a patient’s clinical course assist patients, families, and caregivers with setting appropriate expectations regarding the illness. These assessments and predictions are also prerequisites for the adequate allocation of health-care resources and therapeutic options in the management of respiratory infections.⁹ This includes decisions regarding the need for regular hospital or ICU admission, diagnostic evaluation, and assessment for appropriate early discharge.

The role of prognostication is acknowledged by respiratory infection guidelines, which recommend stratifying patients with CAP based on predicted risk of mortality using validated risk scores (ie, the pneumonia severity index or the CURB-65 [confusion, urea, respiratory rate, BP] score).^39,40 Clinical risk scores are somewhat limited by practicality and risk of miscalibration due to different patient populations and, therefore, have only moderate operational characteristics.⁴¹ Thus, there is interest in additional prognosticating mechanisms, using newly available biomarkers that are objectively and rapidly measurable and responsive to clinical recovery and that add relevant, reliable, and real-time information.

Different studies have evaluated the prognostic potential of PCT in patients with respiratory infections, mainly in patients with CAP (Table 1). Most studies have found that PCT levels were increased in patients not surviving their disease compared with survivors with moderate prognostic accuracy. In a large CAP cohort in the United States,⁴³ the greatest benefit of PCT was found in patients classified as high risk by the pneumonia severity index score. Having a PCT < 0.1 μg/L virtually excluded mortality in these high-risk patients. A Swiss study found that initial PCT levels did not improve clinical risk scores for mortality prediction⁴⁴; subsequent repeated measurements of PCT in this population demonstrated improved clinical outcomes with falling PCT levels. In addition, the study found that PCT was more helpful in predicting serious adverse events other than mortality, such as ICU admission or CAP-related complications. For these outcomes, PCT significantly improved clinical risk scores. Another large CAP study from Germany, which included mostly low-risk patients, found that PCT was an accurate predictor of mortality and significantly improved clinical risk scores.⁴²

Based on these studies, the prognostic usefulness of PCT in patients with respiratory infections who have had their clinical risk assessed (eg, using clinical risk scores) may be summarized as follows: (1) in low-risk patients with respiratory infections, PCT levels < 0.25 μg/L identify patients at lower risk of a bacterial cause and CAP and thus low mortality; (2) in low-risk patients with respiratory infections, PCT levels > 0.25 μg/L identify patients at higher risk of a bacterial cause and CAP and, perhaps, higher mortality; (3) in a high-risk population, PCT levels < 0.1 μg/L effectively decrease the likelihood of mortality from a bacterial cause, and other nonbacterial pathologies should be aggressively sought; (4) more helpful than initial values is the assessment of PCT kinetics over time in moderate and high-risk patients. Levels failing to decline during initial follow-up identify patients not responding to therapy. This last conclusion is also in accordance with ICU studies focusing on patients with sepsis^49,50 and patients with VAP⁴⁶ that demonstrated that a decreasing PCT level over time is a more sensitive outcome predictor than is the initial PCT level.

Importantly, prognostic outcome studies are largely lacking, and it remains unclear whether an improved initial prognostic assessment and later monitoring of patients with PCT translate into better triage decisions and/or outcomes in patients. Of note, a recent large sepsis trial with > 50% of patients having respiratory infections found that PCT-guided escalation of diagnostic procedures and antimicrobial therapy in the ICU did not improve survival. Instead, the algorithm used led to increased risk of renal failure and prolonged ICU stays.⁵¹ From the study it remains unclear, however, if it was primarily a failure of the PCT protocol to identify high-risk patients or if the therapeutic and diagnostic strategies were insufficient, similar to other interventions that have failed to improve outcomes in patients with severe sepsis.⁵² Importantly, the study provided further convincing evidence that increased antibiotic exposure has potentially harmful effects in patients and should be avoided where possible. Similar outcome studies need to be done for patients with respiratory infections in and outside the ICU to investigate whether PCT adds useful prognostic information and thereby improves the daily clinical management and outcomes of patients.

Although timely use of antibiotics is the most effective measure of preventing mortality and morbidity from bacterial respiratory infections, overuse of antibiotics causes considerable harm by exposing individual patients to adverse events including Clostridium difficile infection, by increasing the development of bacterial resistance, and by generating high costs.^7,8 Because of the limitations of traditional signs and symptoms in differentiating viral from bacterial disease, overuse of antibiotics in respiratory infections is a major challenge. Overuse may result from both overprescribing in low-acuity patients⁵³ and unnecessarily prolonged duration of antibiotic therapy in higher-acuity patients in the hospital and ICU setting.⁷ To limit antibiotic overuse, rapid and accurate differentiation of clinically relevant bacterial infection from other causes is essential, as is closely monitoring patients’ clinical recovery to discontinue antibiotics at the earliest safe point in their recovery. Because PCT becomes upregulated during bacterial infections and decreases upon recovery of patients, it may help determine the necessity and optimal duration of antibiotic therapy.^22,54

Today, a total of 14 randomized controlled trials have evaluated the efficacy and safety of using PCT for antibiotic decisions (see an overview of the different trials in Table 2).⁶⁷ All studies used somewhat similar protocols, which recommended initiation or discontinuation of antibiotic therapy based on PCT levels.⁶⁷ Several PCT cutoff ranges were used, mirroring the increase in likelihood of bacterial disease with higher PCT levels. The protocols further adapted cutoffs to the clinical setting or the acuity of patients. In lower-acuity settings (primary care) or lower-acuity conditions (eg, bronchitis), PCT was used mainly to assist in the decision to prescribe or withhold antibiotic therapy. Conversely, in more severe respiratory infections (ie, pneumonia requiring hospitalization) or in the highest-acuity care settings (ie, sepsis or septic shock in the ICU), PCT was used not to determine whether antibiotics should be initiated, but rather when to discontinue them. All patients were reassessed in case antibiotics were withheld initially or if the clinical condition did not improve spontaneously over a day or two.

Within all trials, these strategies proved to be highly effective in terms of reductions of antibiotic exposure. In low-acuity patients, PCT guidance resulted in lower prescription rates by 40% to 75% in primary care patients with upper and lower respiratory infections,^57,64 by 60% to 75% in patients with acute bronchitis,^55,60 and by 30% to 45% in patients with exacerbation of COPD.^56,60 In higher-acuity patients, PCT guidance resulted in reduced duration of therapy by approximately 35% to 55% in CAP^13,60 and by around 35% in VAP.⁶¹ Importantly, there was no increase in either mortality or any other adverse outcome tracked in any of the individual trials. Similarly, neither mortality nor other adverse events surfaced when pooling the data in different aggregate-data meta-analyses.^67,68‐70 Still, particularly for ICU trials, lower adherence rates to the PCT protocol and the remaining uncertainty about safety relating to relatively large CIs calls for future trials in the ICU to validate these findings.

An individual patient data meta-analysis focusing on different patient-relevant outcomes and using standardized outcome definitions across trials, and predefined sensitivity and subgroup analyses is currently under way and should shed more light on these issues.^71,72 In addition to the randomized trials mentioned here, different studies evaluating PCT in “real life” and outside of study conditions found reductions in antibiotic usage without an apparent increase in adverse outcomes.^73,74

Although further study of PCT in respiratory infections is warranted, it seems reasonable to begin using it clinically, based on the more robust areas of data summarized here. As previously reported, a number of protocols using PCT measurements can now be recommended that consider both clinical severity (based on patient characteristics or level of acuity of care site) and clinical entity (ie, which type of respiratory infection is being considered) to help physicians consider questions of initiation and duration of antibiotic therapy (Fig 1).⁶⁷

Importantly, these recommendations may be true only when highly sensitive PCT assays are used and may not be applied unconditionally to specific patient populations that have not been adequately studied, such as immune-compromised patients, neonates, and pregnant women.

An important consideration when using a new diagnostic test is the cost associated with the test with respect to the potential for producing a cost saving (the current cost of a PCT test in the United States varies from about $25 to $30). A recent meta-analysis concluded that PCT in the critical care setting may be cost effective because of the high antibiotic costs in critically ill patients.⁷⁰ Although the same may not necessarily be true for general hospital inpatients with less expensive antibiotics, secondary costs due to side effects and the emergence of antibiotic resistance should also be considered. In addition, some studies have suggested that PCT measurement may help improve the use of other costly diagnostic tests, such as blood cultures, by focusing these tests on patients with higher PCT levels and, hence, a higher likelihood of positive results. A previous study calculated that if blood culture collection were limited to patients with CAP and an initial PCT level of > 0.25 μg/L, blood cultures could be reduced by almost 40%. The number needed to screen to have one positive culture would decrease from 13 to eight, whereas total patient costs (including PCT measurement costs) would decrease by almost 20%, with only 4% of positive cultures being missed.¹¹

It is clear that the use of PCT is not a stand-alone test and will not replace clinical intuition or thorough clinical evaluations of patients.⁷⁷ PCT needs to be interpreted within the context of the clinical setting and the patient’s situation because the correct understanding of PCT levels is predicated on the physician’s pretest probability. In this way, it is similar to other markers such as the cardiac troponin or D-dimer. If PCT is embedded in clinical protocols adapted to the type of infection and clinical context, it clearly has the potential to improve clinical decision making in patients with respiratory infections.

Traditional culture methods, such as blood cultures, focus on identification and characterization of pathogens. Yet they have low sensitivity and thus, if negative, hardly influence clinical decision making in patients with respiratory infections. A blood marker, such as PCT, mirrors the patient’s response to infection and thus, indirectly, the extent and severity of infection. The marker may not be able to identify the specific cause of infection, but the likelihood of a relevant bacterial pathogen increases with increasing marker levels. The marker may then help rule out infection and provide information about patient recovery. With new microbiologic methods becoming available that rapidly identify microorganisms with higher sensitivity, PCT may help increase specificity by providing information about the severity and “relevance” of culture results in individual patients.

Although the moderate prognostic value of initial PCT levels and further enhancement by considering its kinetics over time have been found in multiple observational studies, results from longer-term intervention studies evaluating the usefulness of clinical decision making concerning triage decisions based on PCT levels are largely lacking. The only intervention study available today, to our knowledge, that has evaluated the prognostic potential of PCT in patients with sepsis in the ICU has been disappointing.⁷⁸ Similar types of studies should be conducted to see whether PCT measurement has the ability to improve triage decisions in patients, thereby safely reducing the costs of inpatient treatment.

Emerging bacterial resistance to antimicrobial agents and the huge increase in Clostridium difficile infections call for more effective efforts to reduce the unnecessary and prolonged use of antibiotics in self-limiting, nonbacterial, and resolving bacterial infections.⁷⁹ Randomized controlled studies have shown the efficacy of using PCT protocols to guide antibiotic decisions in patients with upper and lower respiratory infections. Even though previous meta-analyses consistently found no evidence for safety concerns with PCT-based algorithms for antibiotic therapy decisions, the remaining uncertainty associated with the relatively large CIs for mortality, particularly in patients in the ICU,⁷⁰ calls for further research in this high-risk patient population. In addition, most intervention studies today have been conducted in Europe and China; validation of PCT protocols and cutoffs in other countries is, therefore, warranted.

PCT-guided decision making is an innovative approach to managing patients with respiratory infections. It adds useful information about the patient’s response to the infection and clinical recovery, thereby complementing a thorough clinical assessment and clinical intuition. Recent lower respiratory tract infection guidelines emphasize this concept and mention that “biomarkers can guide treatment duration by the application of predefined stopping rules for antibiotics. It has been shown that such rules work even in most severe cases, including pneumonia with septic shock….”⁸⁰ Instead of further observational studies reporting the accuracy of PCT in different clinical settings and situations, future intervention studies should propose PCT protocols with specific cutoffs and evaluate their impact on patient-relevant outcomes to tackle the existing vicious cycle of diagnostic uncertainty, overuse of antibiotics, and expanding use of hospital resources. The evidence suggests that using PCT for patients with respiratory infections can lead to more parsimonious antibiotic use and de-escalation, without safety concerns. Further studies are needed to illuminate whether PCT has a role in microbiologic diagnostic strategies and clinical prognostication.

Financial/nonfinancial disclosures: The authors have reported to CHEST the following conflicts of interest: Dr Schuetz was supported by a research grant from the Swiss Foundation for Grants in Biology and Medicine (Schweizerische Stiftung für medizinisch-biologisc Stipendien, PASMP3-127684/1) and received support from BRAHMS Inc and bioMerieux to attend meetings and fulfill speaking engagements. Dr Amin has received support from bioMerieux for speaking engagements. Dr Greenwald has reported that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.