Lessons learned from variation in response to therapy in clinical trials

Article Outline

• Abstract
• Measuring response in a clinical trial: The components of treatment response
• Analyzing variability in treatment response
• Identifying predictors of response
  • Adults
  • Children
  • Young children
  • Smokers
• Clinical implications of variability in treatment response
• Acknowledgment
• References
• Copyright

In the past, we viewed lack of response to asthma medications as a rare event. Based on recent studies, we now expect significant variation in treatment response for all asthma medications. However, little information is available about methods to predict favorable treatment response. Research conducted in the National Heart, Lung, and Blood Institute's Asthma Clinical Research Network and Childhood Asthma Research and Education Network verified this variability in response to several long-term control medications, specifically inhaled corticosteroids and leukotriene receptor antagonists, in adults and children with mild-to-moderate persistent asthma. The networks also identified potential methods to use patients' characteristics, such as age and allergic status, and biomarkers, such as bronchodilator response, exhaled nitric oxide, and urinary leukotrienes, to help predict response to inhaled corticosteroids and leukotriene receptor antagonists and to determine which of the 2 treatments might be more effective in individual patients. This information now assists the clinician in personalizing asthma treatment at the time of initiating long-term control therapy.

Key words: Asthma, treatment response, inhaled corticosteroids, leukotriene receptor antagonists, leukotriene modifiers, β-adrenergic agonists

Abbreviations used: ACD, Asthma control day, ACRN, Asthma Clinical Research Network, BDP, Beclomethasone dipropionate, CARE, Childhood Asthma Research and Education, CLIC, Characterizing Response to Leukotriene Receptor Antagonist and Inhaled Corticosteroids, eNO, Exhaled nitric oxide, FP, Fluticasone propionate, ICS, Inhaled corticosteroid, LTRA, Leukotriene receptor antagonist, MDI, Metered-dose inhaler, MICE, Measuring Inhaled Corticosteroid Efficacy, NHLBI, National Heart, Lung, and Blood Institute, PACT, Pediatric Asthma Controller Trial, PEAK, Prevention of Asthma in Kids, PRICE, Predicting Response to Inhaled Corticosteroid Efficacy

Great care has been applied to developing asthma guidelines that provide principles of asthma management to achieve optimal control.¹, ² The general tendency in preparing guidelines is to focus on the evidence-based conclusions of studies that often portray the average response derived from specific studies. However, clinicians recognize that there is great variability in patient response to treatment, which includes significant or obvious response, minimal response that raises questions about patient adherence or inadequate effect, or even an adverse response to a medication that either prompts a reduction of the dose or discontinuation of the treatment.

Clinician guidance for treatment selection is usually derived from information reported in clinical trials and summarized in guidelines. This information is then applied in a medication trial, and the clinical response is assessed from the patient's report on symptom control. The clinician generally assumes that the patient took the medication, including using the appropriate technique, and those questions are reviewed if there is an inadequate response.

There are several weaknesses in this current process of medication selection that can result in a delay in the patient receiving the best medication to obtain the optimal treatment response. Currently, most clinical trials place emphasis on reporting the average response to the medication in relation to either placebo or another treatment. Although information is provided on the degree of variability in response, most trials do not take the next step to understand this variability in response. If information regarding the variability of response to asthma treatment were available along with methods to predict treatment response, the clinician could select the medication most likely to provide a significantly favorable response and thus reduce the time for achieving maximal symptom control.

This review will focus on the current understanding in variability of response to 2 long-term controller medications, inhaled corticosteroids (ICSs) and oral leukotriene receptor antagonists (LTRAs), which has been developed through a series of clinical trials. These specific trials were conducted in the National Heart, Lung, and Blood Institute's (NHLBI) Asthma Clinical Research Network (ACRN) and Childhood Asthma Research and Education (CARE) Network, and the results indicate how this variability in response can be associated with patients' characteristics and biomarkers that can be used to help predict treatment response in the clinical setting.

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Measuring response in a clinical trial: The components of treatment response 

In clinical studies the response to asthma therapy is traditionally assessed by measuring improvement in pulmonary function, especially in studies evaluating the efficacy of bronchodilator or quick-relief medications. However, as we turned our attention in the National Institute of Health's asthma networks to measuring response to long-term controllers, especially ICSs, it became apparent that improvement in pulmonary function response is highly variable. Therefore we need to look at the variability of other measures of clinical response, including reduction in symptoms and need for rescue therapy, increase in asthma control days (ACDs), prevention of acute exacerbations and nocturnal exacerbations, reduction in airway hyperresponsiveness, and improvement in quality of life. All of these are components of asthma that are coexistent but not necessarily codependent features.

Therefore careful studies must be done to identify a medication's predominant effect on asthma management and also to evaluate other measures of response to obtain a more comprehensive picture of the medication's potential benefits in asthma management and aide the clinician in medication selection.

Table I summarizes information that could be applied in a comprehensive clinical trial to measure the response to individual medications. Most of these measures are easily obtained in adult patients, but some, such as spirometry and markers of inflammation, are more difficult to obtain in children, especially young children.

Table I. Measures of a treatment response

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Analyzing variability in treatment response 

One of the major questions during the 1990s centered on the comparative efficacy of ICSs. Looking at traditional change in FEV₁ values as a measure of clinical response to ICS therapy, it was very difficult to assess a dose-response relationship for any individual ICS, let alone compare 2 ICSs with each other. One of the initial studies conducted by the ACRN was to carefully examine the dose-response relationship for available ICSs. Realizing the complexity of such an investigation, a trial called the Measuring Inhaled Corticosteroid Efficacy (MICE) study was designed to evaluate multiple treatment response parameters to decide which one would be most applicable to comparing responses among available ICSs and then to examine the associated systemic effect with those responses by measuring overnight plasma cortisol suppression.³

Briefly, this study was a randomized, parallel, open-label, multicenter trial conducted in adults with mild-to-moderate asthma that examined the benefit/risk ratio of 2 ICSs.³ Benefit was assessed by measuring the improvement in FEV₁ and methacholine FEV₁ PC₂₀, and risk was assessed based on overnight plasma cortisol suppression. Thirty subjects were randomized to either 168, 672, and 1,344 μg/d beclomethasone dipropionate (BDP; n = 15) or 88, 352, and 704 μg/d fluticasone propionate (FP; n = 15), both administered by means of a metered-dose inhaler (MDI) with chlorofluorocarbon propellant through a spacer in 3 consecutive 6-week intervals. This 18-week treatment course was followed by 3 weeks of FP dry powder inhaler at 2,000 μg/d.

Several key observations were made from this relatively small but important study. First, maximal FEV₁ response occurred with the low dose for FP-MDI and the medium dose for BDP-MDI and was not further increased by treatment with high-dose FP dry powder inhaler. The same pattern was seen with methacholine FEV₁ PC₂₀. Both BDP-MDI and FP-MDI caused dose-dependent cortisol suppression. Therefore high-dose ICS therapy did not significantly increase the efficacy for these 2 measures but did increase the systemic effect measure: overnight cortisol suppression.

Second, significant intersubject variability in response occurred with both FP-MDI and BDP-MDI (Fig 1).³ Good (>15%) FEV₁ response, in contrast to poor (<5%) FEV₁ response, was found to be associated with high exhaled nitric oxide (eNO) levels, high bronchodilator response, and a low FEV₁/forced vital capacity ratio before treatment. In contrast, excellent (>3 doubling dilutions) improvement in methacholine FEV₁ PC₂₀, in contrast to poor (<1 doubling dilution) improvement, was found to be associated with high sputum eosinophil levels and older age of onset of asthma.

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• Fig 1. 

  Variability in FEV₁ response (A and B) and methacholine PC₂₀ response (C and D) for BDP-MDI (Fig 1, A and C) and FP-MDI (Fig 1, B and D) for the 3 study doses and the 2-mg/d dose of FP administered through a Diskhaler. Only subjects with complete data sets are included. Reprinted with permission from Szefler et al.³

This study alerted us to the fact that treatment response was indeed highly variable, even in adults with mild-to-moderate persistent asthma, and that there was some potential to relate treatment response to patients' characteristics and biomarkers. The next set of questions was addressed in subsequent NHLBI asthma network studies, including but not limited to the following: Could the patients' characteristics and biomarkers identified in the small population included in the MICE study predict treatment response in a larger adult population of patients with mild-to-moderate asthma? Does this variability in response to ICSs noted in the MICE study also occur in children, and are the potential predictors of response similar in adults and children? Does this variability in response also occur with other long-term controllers, such as LTRAs? Can biomarkers and patients' characteristics also relate to other measures of long-term controller treatment response?

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Identifying predictors of response 

Adults 

Based on the provocative results of the MICE study, the ACRN developed a larger follow-up study, the Predicting Response to Inhaled Corticosteroid Efficacy (PRICE) trial, to evaluate potential biomarkers associated with short-term (6-week) response to ICSs, with subsequent evaluation of responders and nonresponders to asthma control over a longer interval (16 additional weeks).⁴

For the PRICE study, 83 subjects with asthma who were off steroid therapy were enrolled in this multicenter ACRN study. Biomarkers and asthma characteristics were evaluated as associated features of ICS response over a 6-week trial for changes in FEV₁ and methacholine FEV₁ PC₂₀. After this 6-week ICS treatment period, an additional 4-month trial evaluated asthma control.

The key findings in this study included the following observations. First, although multiple baseline features had significant correlations with improvements for short-term ICS success, the only strong correlations (r ≥± 0.6) were albuterol reversibility (r ≥±0.83, P < .001), FEV₁/forced vital capacity ratio (r ≥± −0.75, P < .001), and FEV₁ percent predicted (r ≥± −0.71, P < .001). Second, for the nonresponders (<5% FEV₁ improvement), asthma control remained unchanged whether ICSs were continued or were substituted with a placebo (Fig 2).⁴ Third, the good short-term responders (>5% improvement in FEV₁) maintained asthma control longer-term only if maintained on ICSs. In this larger validation study, eNO was not identified as an associated biomarker of ICS pulmonary response in adults with mild-to-moderate persistent asthma, as noted in the MICE study.

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• Fig 2. 

  Asthma control as measured by the Asthma Control Questionnaire (ACQ) over the 16-week ICS or placebo (PBO) continuation trial. The groups are categorized on the basis of the FEV₁ results of the previous 6-week ICS trial: nonresponders, 5% or less improvement on ICSs; responders, greater than 5% improvement on ICSs. The only significant within-group difference occurred between the placebo and ICS responder groups (P = .007). Reprinted with permission from Martin et al.⁴ Note that a clinically significant change in the Asthma Control Questionnaire score is considered to be 0.5 units.

Therefore we concluded from the PRICE study that short-term response to ICSs with regard to FEV₁ improvement predicts long-term control. The clinical implications for these findings were that (1) the decision to use long-term ICSs could be based on a short-term trial and (2) different therapeutic strategies would need to be established for nonresponders.

Children 

As the NHLBI's CARE Network was established, one of the first studies conducted sought to examine the variability in treatment response to ICSs and LTRAs in children in the Characterizing Response to Leukotriene Receptor Antagonist and Inhaled Corticosteroids (CLIC) study.⁵ A main driving force to conduct the CLIC study was the experience derived from the NHLBI's MICE study³ in identifying variable response to ICSs in adults with asthma, as well as other reports showing variable response to LTRAs in adults with asthma.⁶ It was decided to conduct a cross-over study with these 2 treatments to determine whether response to ICSs and LTRAs were concordant for individuals or whether asthmatic patients who do not respond to one medication have a response to the other medication.

For the CLIC study, children 6 to 17 years of age with mild-to-moderate persistent asthma were enrolled. These children were required to have asthma symptoms or rescue bronchodilator use on an average of 3 or more days per week during the previous 4 weeks and improvement in FEV₁ of 12% or greater after maximal bronchodilation or methacholine PC₂₀ of 12.5 mg/mL. The children were randomized to one of 2 crossover sequences, including 8 weeks of an ICS (FP, 100 μg twice daily) and 8 weeks of an LTRA (montelukast, 5–10 mg nightly depending on age) in a multicenter, double-masked, 18-week trial. In the primary analysis response was assessed on the basis of improvement in FEV₁ (≥7.5%) and assessed for relationships to baseline asthma phenotype-associated biomarkers.

Once again, several key observations were reported in this study. First, 17% of the 126 participants responded to both medications, 23% responded to fluticasone alone, 5% responded to montelukast alone, and 55% responded to neither medication (Fig 3, A).⁵ Second, compared with those who responded to neither medication, favorable response to FP alone was associated with higher levels of eNO, total eosinophil counts, levels of serum IgE, and levels of serum eosinophilic cationic protein and lower levels of methacholine FEV₁ PC₂₀ and pulmonary function; a favorable response to montelukast alone was associated with younger age, higher urinary leukotriene levels, and shorter duration of disease. Third, greater differential response to FP over montelukast (Fig 3, B) was associated with higher bronchodilator use, bronchodilator response, eNO levels, and eosinophilic cationic protein levels and lower methacholine FEV₁ PC₂₀.

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• Fig 3. 

  A, Variability of response and differential response to FP and montelukast, as measured by change in FEV₁. Four regions show categories of response, defining a favorable response as 7.5% or greater. Mt, Montelukast. The line of identity is designated, with patients favoring montelukast falling above the line, and those favoring fluticasone falling below the line. The concordance correlation with 95% CIs is displayed. B, Difference in FEV₁ response between FP and montelukast for individual participants. Each line designates a single participant. Reprinted with permission from Szefler et al.⁵

Therefore we concluded form the CLIC study that response to FP and montelukast vary considerably in children with mild-to-moderate asthma. Also, children with low pulmonary function or high levels of markers associated with allergic inflammation should receive ICS therapy.

A subsequent expanded analysis of the CLIC study focused on the assessment of intraindividual and interindividual response profiles and predictors of response to evaluate clinical, pulmonary, and inflammatory responses to ICSs and LTRAs. Zeiger et al⁷ from the CARE Network derived several new clinical findings from the CLIC study. First, improvements in most clinical asthma control measures occurred with both controllers. Second, clinical outcomes, pulmonary responses, and inflammatory biomarkers, specifically eNO levels, improved significantly more with FP than with montelukast treatment. Third, the eNO level was both a predictor of ACDs and a response indicator in discriminating the difference in ACD response between FP and montelukast. In other words, the higher the participant's eNO level, the greater the response to FP compared with montelukast in that participant.

The clinical implication of this subsequent analysis was that more favorable clinical, pulmonary, and inflammatory responses to an ICS than to an LTRA provide pediatric-based group evidence to support ICSs as the preferred first-line therapy for mild-to-moderate persistent asthma in children. Also, eNO level, as an associated feature of favorable response to ICSs, might help to identify individual children not receiving controller therapy who achieve a greater improvement in ACDs with an ICS compared with an LTRA.

The findings of the CLIC study prompted an evaluation of a subsequent study conducted in the CARE Network, entitled the Pediatric Asthma Controller Trial (PACT), to identify phenotypic characteristics having potential value for identifying the difference in treatment responses between twice-daily FP and once-daily montelukast.⁸, ⁹ The PACT compared the effectiveness of 3 regimens in achieving asthma control in a total of 285 children (age, 6-14 years) with mild-to-moderate persistent asthma on the basis of symptoms and with an FEV₁ of 80% or greater of predicted value and a methacholine FEV₁ PC₂₀ of 12.5 mg/mL or less.⁸ The children were randomized to one of 3 double-blind 48-week treatments: 100 μg of fluticasone twice daily (fluticasone monotherapy; Flovent Diskus; GlaxoSmithKline, Research Triangle Park, NC); 100 μg of fluticasone and 50 μg of salmeterol (Advair Diskus, GlaxoSmithKline) in the morning and 50 μg of salmeterol (Serevent Diskus; Glaxo Smith Kline) in the evening (PACT combination); and 5 mg of montelukast (Singulair; Merck, Whitehouse Station, NJ) in the evening. Outcomes included ACDs (primary outcome), exacerbations, quality-of-life measurements, and pulmonary function.

The general conclusions derived from the PACT included the following observations.⁸ Both fluticasone monotherapy and the PACT combination achieved greater improvement in ACDs than montelukast. However, fluticasone monotherapy was superior to the PACT combination in achieving greater improvement in other dimensions of asthma control. A subsequent analysis of the PACT conducted by Knuffman et al⁹ in the CARE Network sought to identify phenotypic characteristics associated with response to FP monotherapy and montelukast.

Data from the PACT were assessed with multivariate analysis. Outcomes included the change in ACDs, FEV₁, peak expiratory flow, and time to first asthma exacerbation measured over the 2-year treatment period. Key findings in this secondary analysis included the following observations. First, a history of parental asthma best predicted the expected treatment benefit with FP compared with montelukast in terms of gain in ACDs and time to first exacerbation. Second, increased baseline eNO levels were associated with the differential treatment response for FP regarding the gain in ACDs. Third, prior ICS use and low methacholine FEV₁ PC₂₀ values were associated with the benefit of FP over montelukast regarding the time to first exacerbation. Fourth, no phenotypic characteristic was associated with treatment benefits for montelukast over fluticasone for either outcome.

Therefore the clinical implications of the PACT secondary analysis are that in children with mild-to-moderate persistent asthma, a parenteral history of asthma, airway hyperresponsiveness, or increased measures of inflammation might have a superior response to an ICS over an LTRA. These findings helped to corroborate and extend the initial observations obtained in the CLIC study, and the 2 studies combined suggested that eNO level could be a better predictor of ICS treatment response in children compared with the experience in our adult study.⁴

Young children 

It is also desirable to determine whether patients' characteristics could be associated with response to long-term controller medications in young children. A secondary analysis was performed on the Prevention of Asthma in Kids (PEAK) trial conducted in the CARE Network to evaluate this question.¹⁰ The PEAK study was a randomized trial conducted in 285 participants 2 to 3 years of age with a positive asthma predictive index who were assigned to treatment with either FP at a dose of 88 μg twice daily or masked placebo for 2 years, followed by a 1-year period without study medication. The primary outcome for this study was the proportion of episode-free days during the 1-year observation period. The primary conclusion of this study was that in preschool children at high risk for asthma, 2 years of ICS therapy did not change the development of asthma symptoms or lung function during the third treatment-free year. However, during the treatment period, compared with placebo, use of ICSs was associated with a greater proportion of episode-free days and a lower rate of exacerbations and of supplementary use of controller medication.

After the primary outcome report, a secondary analysis was conducted by Bacharier et al¹¹ in the CARE Network to determine whether demographic and atopic features were associated with a favorable response to ICSs in the PEAK trial. This analysis revealed 2 important findings. First, significantly greater improvement with FP than placebo in terms of episode-free days occurred among boys, white subjects, participants with an emergency department visit or hospitalization within the past year, and those who experienced more symptomatic days at baseline. Second, children with aeroallergen sensitization experienced greater benefits in terms of oral corticosteroid use, urgent care and emergency department visits, and use of supplemental controller medications. The clinical implication of this analysis was that preschool children at high risk for asthma experience favorable responses to ICS therapy, particularly when indicators of greater disease severity and aeroallergen sensitization are present.

Smokers 

Another important predictor of long-term controller response in adults was identified in the ACRN's Smoking Modulates Outcomes of Glucocorticoid Therapy Trial.¹² The purpose of this study was to determine whether the response to an ICS or an LTRA is attenuated in subjects with asthma who smoke. This was a multicenter, placebo-controlled, double-blind, crossover trial with 44 nonsmokers and 39 light smokers with mild asthma who were assigned randomly to treatment twice daily with inhaled BDP and once daily with oral montelukast. The primary outcome was change in prebronchodilator FEV₁ in smokers versus nonsmokers.

This study provided the following insights into treatment response. First, in subjects with mild asthma who smoke, the response to ICSs is attenuated, suggesting that adjustments to standard therapy might be required to attain asthma control. Second, greater improvement in some outcomes in smokers treated with montelukast, specifically an increase in morning peak flow (12.6 L/min, P = .002), but not in nonsmokers, suggested that LTRAs might be useful in this group of patients.

The Smoking Modulates Outcomes of Glucocorticoid Therapy Trial confirmed the presence of corticosteroid insensitivity in patients with asthma who smoke and suggested that leukotriene modifiers might be beneficial for these patients. However, large prospective studies are required to determine whether leukotriene modifiers can be recommended for managing asthma in patients who smoke.

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Clinical implications of variability in treatment response 

The results of the studies conducted in the ACRN and CARE Networks provide new insights into individualizing asthma therapy at the step 2 level of the asthma guidelines. The step 2 treatment step recognizes ICSs as the preferred medication, with other long-term controllers, including leukotriene modifiers, identified as alternative treatments.¹, ² Despite evidence from multiple studies showing that ICSs are indeed the preferred long-term controller for adults and children with asthma, patients, parents, and clinicians are still concerned regarding the long-term safety of ICSs and require additional information to support the use of ICSs as the preferred treatment for the specific subject being treated. They might also be concerned about reported adverse effects associated with the LTRAs. This is indeed the heart of individualized or personalized medicine. Is there specific information that the clinician can use for either reinforcing the need for the preferred medication, in this case ICSs, or that an alternative medication, such as an LTRA, might provide an equivalent or perhaps even better response to the preferred treatment?

The observations from the National Institute of Health's asthma network studies help to address this question for step 2 therapy and therefore set the stage for incorporating personalized medicine into the asthma guidelines. Studies are currently being conducted in the ACRN and the CARE Network to understand individual treatment response at the step 3 level and could be the subject of a future review as this information becomes available.

The following conclusions can be derived from the studies summarized in this review. First, the clinician should expect variability in treatment response to clinical, physiologic, and inflammatory indicators of response for ICSs and LTRAs in all patients including children and adults. Second, low pulmonary function, bronchodilator response, and airway hyperresponsiveness are associated with a favorable response to ICS therapy in all patients, and indicators of allergic inflammation, specifically eNO level, are associated with a favorable response to ICSs in children but not adults. Third, younger age, higher urinary leukotriene levels, and shorter duration of disease are linked to a favorable response to LTRAs in children. Fourth, particularly in children, a greater pulmonary response to ICSs over LTRAs is observed with higher eNO levels, as well as higher bronchodilator use, and lower methacholine PC₂₀ and pulmonary function. Fifth, adult patients with asthma who smoke might have a favorable response to LTRAs over ICSs.

Based on the observations summarized in this review, it is now possible to use a combination of patients' characteristics and biomarkers to help direct long-term controller therapy in children and adults. This is primarily based on outcome measures of clinical symptoms, pulmonary function, and inflammation markers. Fig 4 summarizes the key steps necessary to link variability in treatment response to indicators associated with favorable response derived from clinical trials and then to use this information to predict and ultimately monitor outcomes in the clinical setting. All preliminary observations based on retrospective data analysis should be tested with large, prospective follow-up studies. They should also be evaluated for their cost-effectiveness in clinical management.

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• Fig 4. 

  Application of clinical trial information to clinical care. Based on the studies presented, the clinician should anticipate that variability to response will occur with each treatment, this variability in response can be associated with patients' characteristics, biomarkers, and genetics, and response to treatment should be monitored for the various outcomes measures, especially symptom control and pulmonary function, to ensure rapid and sustained achievement of asthma control.

In regard to biomarkers, the most easily measured and readily available biomarker for clinical application is eNO. Many lessons can be derived from experience with eNO as a biomarker. For example, measurements of eNO levels before treatment might be useful in predicting response to ICS therapy in children but not in adults. In addition, there is not a clear set of rules for applying a biomarker to clinical practice in the setting of predicting treatment response. Information to date is gathered from a body of evidence and not a rigorous set of protocols defined by a regulatory agency, such as the US Food and Drug Administration.

In the future, we could benefit from such a standardized set of rules to evaluate biomarkers as a tool for clinical practice. In addition, we could benefit from the discovery of patients' characteristics, biomarkers, or genetics that are linked to a higher risk of disease progression or severe asthma. Biomarkers to measure key pathways associated with asthma progression would be useful to monitor disease activity and also serve as an indicator of treatment resistance and perhaps as a therapeutic target for medication selection.

Another weakness in our current body of knowledge is the ability to predict who is susceptible to an asthma exacerbation and measures of an impending asthma exacerbation that could be used to signal early intervention to prevent an asthma exacerbation. For example, in a National Institute of Allergy and Infectious Diseases' Inner City Asthma Consortium study entitled the Asthma Control Evaluation study, the investigators demonstrated that regular measures of eNO levels added to an asthma guideline-based approach did not add significant benefit over the guidelines-based approach alone in proving asthma control.¹³ Therefore a single biomarker might address some questions related to asthma management, such as predicting treatment response, but additional tools will be necessary to address other important questions, such as the ability to select medications most likely to prevent an asthma exacerbation or prevent asthma progression.

Despite the ongoing needs for future management, much has been gained in the past 20 years to assist the clinician in individualizing or personalizing asthma therapy. We should now look to further refine that knowledge around the application of these techniques, including cost-effectiveness studies, to continue to improve overall asthma care, perhaps even developing methods to anticipate and prevent asthma exacerbations and to induce full remission of persistent and even emerging asthma.

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We thank our colleagues in the NHLBI's ACRN and CARE Networks, including the research staff and investigators, for their ongoing collaboration in the design, implementation, and publication of the network studies. In addition, we would like to thank the NHLBI for their foresight in setting up the asthma networks to address key gaps in information related to asthma management and allow the investigators to design and interpret the data generated from these studies. We also thank the pharmaceutical firms that provided medication and placebo to conduct these high-quality studies. Most of all, we thank the study participants, including children and parents, for their dedication to improving asthma care.

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