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(Chest. 2006;130:1454-1461.)
© 2006 American College of Chest Physicians

The Relationship Between FEV1 and Peak Expiratory Flow in Patients With Airways Obstruction Is Poor*

Ashutosh N. Aggarwal, MD, FCCP; Dheeraj Gupta, MD, FCCP and Surinder K. Jindal, MD, FCCP

* From the Department of Pulmonary Medicine, Postgraduate Institute of Medical Education and Research, Chandigarh, India.

Correspondence to: Surinder K. Jindal, MD, FCCP, Professor and Head, Department of Pulmonary Medicine, Postgraduate Institute of Medical Education and Research, Chandigarh 160012, India; e-mail: skjindal{at}indiachest.org

Abstract

Study objectives: To evaluate the correlation between FEV1 and peak expiratory flow (PEF) values expressed as a percentage of their predicted value, and to assess factors influencing differences between the two measurements.

Design: Cross-sectional.

Setting: Pulmonary function laboratory at a tertiary-level teaching hospital in northern India.

Participants: A total of 6,167 adult patients showing obstructive pattern on spirometry over a 6-year period.

Interventions: None.

Measurements and results: There was considerable variability between percentage of predicted FEV1 (FEV1%) and percentage of predicted PEF (PEF%). Locally weighted least-square modeling revealed that PEF% overestimated FEV1% in patients with less severe obstruction and underestimated it in those with more severe obstruction. Using Bland-Altman analysis, PEF% underestimated FEV1% by a mean of only 0.7%; however, limits of agreement were wide (– 27.4 to + 28.8%), indicating that these two measurements cannot be used interchangeably. PEF% and FEV1% were > 5% apart in approximately three fourths and differed by > 10% in approximately one half of the patients. On multivariate analysis, discordance > 5% was significantly influenced by female gender (odds ratio, 1.26; 95% confidence interval [CI], 1.01 to 1.58) and increasing FEV1% (odds ratio, 1.09 for every 10% increase; 95% CI, 1.04 to 1.14) but not by height or age.

Conclusions: FEV1% and PEF% are not equivalent in many patients, especially women and those with less severe airflow limitation. Assumptions of parity between PEF% and FEV1% must be avoided.

Key Words: agreement • airflow limitation • respiratory function tests

Spirometry is the recommended investigation for diagnosis and categorization of severity of airflow limitation.1 Spirometry is a well-standardized technique, and elaborate guidelines already exist regarding procedure performance, evaluation of test quality, and interpretation of measured parameters.123 However, spirometry is not widely available, and the pitfalls of spirometry frequently limit use of this test at the primary care level.45 Peak expiratory flow (PEF) recording is proposed as an alternative to spirometry for this purpose.678 The PEF instrument is cheap, portable, and easy to operate and maintain.

Guidelines91011 on asthma management focus heavily on categorizing patients based on severity of airflow limitation measured on formal pulmonary function testing. It is suggested that either FEV1 or PEF can be expressed as a percentage of predicted values and used for this purpose. Similarly, definition and severity assessment of COPD is now based on measurement of percentage of predicted FEV1 (FEV1%) and FEV1/vital capacity (VC), although a need for evaluating the role of PEF in situations and areas where spirometry is not routinely available is recognized.1213 There is, however, no consensus on whether or not FEV1% and percentage of predicted PEF (PEF%) can be used interchangeably in patients with obstructive lung diseases. Most clinicians assume a general parity between these measurements, and some guidelines911 on asthma management also recommend the same. However, other guidelines1112 also suggest that PEF% may underestimate the degree of airways obstruction assessed by FEV1%.

Previous studies8141516171819 addressing comparisons between FEV1% and PEF% have been performed in highly selected patients and have been limited to some extent by inclusion of small number of subjects and inability to examine relationships in different subgroups of patients. We therefore studied adult patients with obstructive ventilatory defects from a large spirometry database to evaluate the correlation between FEV1% and PEF%, and to assess the factors influencing differences between the two measurements.

Materials and Methods

Our laboratory provides facilities for spirometry and other detailed investigations (such as estimation of static lung volumes, diffusion testing, and study of pulmonary and airway mechanics). Patients are referred for lung function testing not only from our department but also from other medical and surgical specialties of our hospital. Since our institute is a tertiary academic center in northern India, patients are referred for diagnosis and management from several northern Indian states. Records of all consecutive adult patients (aged > 15 years) undergoing spirometry during a 6-year period were retrieved. Sources of referral, reasons for performing spirometry, as well as other clinical details were, however, not analyzed further. All subjects performed spirometry on a dry rolling seal spirometer (Spiroflow; P K Morgan Ltd; Kent, UK), followed by PEF estimation using a Wright peak flowmeter. VC, FEV1, and PEF were measured using American Thoracic Society guidelines, and the highest measurements from among three technically acceptable and reproducible maneuvers were expressed at body temperature and pressure saturated with water vapor.3 All technicians performing spirometry were experienced in pulmonary function testing and strictly followed standard procedures while analyzing the kymograph output. The spirometer was frequently calibrated to ensure optimum performance. Since the study was a retrospective analysis of already available laboratory records, and patient confidentiality was not breached in any fashion, prior approval from our Hospital Ethics Committee was not required.

Age, gender, height, and spirometric data were recorded for all patients using software previously developed by us.20 The predicted values for VC, FEV1, FEV1/VC ratio, and PEF were generated using previously defined prediction equations for North Indian adults.2021 The regression equations for spirometric indexes were generated from studies performed on 962 healthy nonsmoking North Indian adults, aged 15 to 74 years, using a water seal spirometer. The regression equations for PEF were derived from measurements performed on 3,166 healthy nonsmoking North Indian adults, aged > 20 years, using a Wright peak flowmeter. Both these sets of regression equations predict lung function parameters using formulae containing gender, height, and age as variables (Table 1 ).


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  		Table 1. Prediction Equations for Lung Function in Healthy North Indian Adults*

 
A spirometry record with FEV1/VC ratio less than its predicted lower limit of normal was categorized as having an obstructive defect. The lower limit of normal for FEV1/VC ratio was computed by subtracting 1.645 times the SE of estimate of the corresponding equation from the predicted value. To minimize analysis bias related to multiple records showing obstructive defects in the same individual because of repeated pulmonary function testing, only the first record was retained for further analysis in such situations. Wherever available, postbronchodilator values were chosen for interpretation of spirometry.

Observed values for both FEV1 and PEF were expressed as percentages of predicted values. A simple scatterplot was constructed to assess how closely PEF% approximated FEV1%. Iterative locally weighted smoothing techniques were applied to this distribution to obtain a regression curve fitting this data; such a method avoids the undue influence of outlying values on curve estimation by assigning a relatively lesser weight to these values.22 In order to evaluate if PEF and FEV1 could be used interchangeably across different categories of age, height, gender, and severity of airway obstruction, we calculated the limits of agreement between the two estimates using Bland-Altman analysis.23 Multiple logistic regression analysis was also performed to study factors responsible for FEV1% and PEF% values being > 5% apart from each other.

Results

During the study period, 25,914 spirometry procedures were performed. After excluding 775 individuals < 15 years old and 302 incomplete records, 24,837 records were retained. Of these, 7,395 records (29.8%) were interpreted as having obstructive defect. After excluding 1,228 repeat procedures, 6,167 records formed the database for further analysis. There were 3,213 men (52.1%) aged 16 to 95 years (median, 53 years; interquartile range, 41 to 64 years) and 136 to 189 cm in height (median height, 165 cm; interquartile range, 161 to 170 cm); and 2,954 women (47.9%) aged 16 to 94 years (median, 47 years; interquartile range, 36 to 60 years) and 136 to 189 cm in height (median height, 153 cm; interquartile range, 149 to 157 cm).

PEF was reduced in 4,935 patients (80.0%). In general, there was a moderate correlation between FEV1% and PEF%, with overall Pearson correlation coefficients of 0.768 (p < 0.001) and 0.725 (p < 0.001) among men and women, respectively. However, the scatter was wide, more so in patients with mild obstruction (Fig 1 ). The regression curve generated using iterative locally weighted smoothing techniques showed two zones. In patients with FEV1% > 40%, PEF% tended to underestimate FEV1%; in patients with more severe obstruction, PEF% tended to overestimate FEV1% (Fig 1). Agreement between FEV1% and PEF% was only fair, with weighted {kappa} estimate of 0.514 using 10% categories for both FEV1% and PEF%. Using arbitrary severity categories based on 20% FEV1% intervals, PEF% and FEV1% severity categories were concordant in only 3,013 instances (48.9%), with better concordance as severity of obstruction (based on FEV1%) became more severe (Table 2 ).


Figure 1
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  		Figure 1. Scatterplot showing relationship between FEV1 and PEF readings referenced to their respective predicted values. The regression curve is fitted using iterative locally weighted smoothing techniques.

 

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  		Table 2. Concordance Between Categorization of Severity of Airway Obstruction Based on FEV1% and PEF%*

 
The differences between FEV1% and PEF% followed a normal distribution (Fig 2 ); for the entire study population, PEF% underestimated FEV1% by a mean of only 0.7%. However, limits of agreement were wide and exceeded ± 25% (Fig 3 ). Overall, differences were more marked in women and in patients at extremes of height distribution (Table 3 ).


Figure 2
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  		Figure 2. Histogram showing the near-normal distribution of differences between FEV1 and PEF values. Both are described as a percentage of their respective predicted values, and the latter is subtracted from the former to compute the difference. A discrepancy of ≥ 10% between FEV1% and PEF% occurred in more than one half of instances.

 

Figure 3
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  		Figure 3. Bland-Altman plot highlighting magnitude of difference between FEV1 and PEF values expressed as a percentage of their respective predicted values. Horizontal dashed lines represent the mean bias and its 95% confidence limits.

 

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  		Table 3. Mean Bias and Limits of Agreement Between PEF% and FEV1% in the Study Population

 
PEF% and FEV1% were > 5% apart in 4,574 patients (74.2%) and > 10% apart in 3,161 patients (51.3%). Although there is no consensus on the issue, a discordance > 5% could be considered a clinically important error for estimation of severity of airway obstruction. On univariate analysis, the proportion of such discordant results was significantly more in women, and increased significantly with worsening FEV1%, and decreasing height (Table 4 ). On multivariate analysis, gender and FEV1% independently influenced discordance (Table 4).


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  		Table 4. Results of Logistic Regression Analysis To Study Factors Responsible for Patients Having FEV1% and PEF% Values > 5% Apart From Each Other

 
Discussion

In patients with obstructive lung diseases, both FEV1% and PEF% are widely used to estimate the degree of pulmonary impairment. In general, FEV1 measurements are preferred as these are much more reproducible. However, spirometry is not widely available in developing countries such as India, and there is a need to assess if similar information could be acquired using PEF measurements, which are cheaper and much more widely available. Since clinical decisions are often based on the results of these measurements, we attempted to compare their utility in defining severity of airflow obstruction.

A few investigators1415161719 have looked at correlation between PEF and FEV1 in cross-sectional studies. The correlation between absolute values of PEF and FEV1 values was rather low in one study.14 In general, the correlation between PEF% and FEV1% has been moderate, with correlation coefficients ranging from 0.5 to > 0.8.161719 In our own database, there was a moderate correlation between FEV1% and PEF%. In one follow-up study,15 individual correlation coefficients were found to range from 0.68 to 0.98.

However, a numerical summary of information does not imply that PEF can be used as a surrogate for FEV1. Scatterplots from various reports show considerable difference in FEV1% and PEF% values in individual patients, although most coordinates lie close to the line of identity. To avoid undue influence from outlying values, we used iterative locally weighted smoothing to obtain a regression curve fitting our data; and we found that in patients with severe airway obstruction (FEV1 < 40% of predicted), PEF% overestimated FEV1%, whereas exactly the opposite happened in patients with less severe airway obstruction. Previous investigators14 have also noted similar trends. In one study,18 PEF% values were higher than corresponding FEV1% values, particularly in patients with moderate-to-severe asthma. In another study,16 most patients could generate higher PEF% values than FEV1% values, although very few patients had severe airway obstruction.

Overall, PEF% and FEV1% were > 5% apart in 74.2% and > 10% apart in 51.3% of patients in our data set. Thus, only a minority of patients had PEF% and FEV1% values close to each other (Fig 2). Data from previous studies817182425 also show that limits of agreement are wide and point toward absence of parity between FEV1% and PEF% values. In our own data set, limits of agreement were – 27.4 to + 28.8. This means that for a given value of PEF%, corresponding FEV1% could be 28.8% lower or 27.4% higher. These values render substitution of PEF% for FEV1% useless in routine clinical practice.

Our results are at slight variance with observations in other reports. The mean difference between FEV1% and PEF% in this study was only 0.7%. Previous studies81718 have shown a much wider mean difference, with FEV1% being lower than PEF% by 9.1 to 17.2%. This possibly is related to the selection and size of study populations enrolled in these studies. Most of these studies81718 included small number of patients (25 to 101 patients). Some studies81518 recorded multiple paired observations on each subject and analyzed each pair as a separate unit. Both factors preclude generalization of results. Some studies8151618 also included patients who, although suffering from an obstructive lung disease, did not have airflow limitation at time of evaluation. As discussed earlier, PEF% in these subjects is likely to be much greater than FEV1% in comparison to patients having more severe airway obstruction at time of evaluation, and it is difficult to generalize these results while categorizing severity of airway obstruction.

There could be several reasons for lack of equivalence between FEV1% and PEF%.26 For one, measured PEF values depend heavily on lung volumes. Any disease process leading to reduced lung volumes will effect a corresponding reduction in measured PEF. This implies that in addition to patients with airway obstruction, those with restrictive lung defects are also likely to have a reduced PEF. Secondly, normal population variability of PEF is quite large. Hence calculation of lower limits of predicted normal based on regression equations leads to values that are much lower than corresponding values for other spirometric indexes like FEV1. Thirdly, while PEF is measured on the first effort-dependent portion of the forced expiratory maneuver and predominantly reflects large airway function, FEV1 is determined both by the effort-dependent and effort-independent portions of this maneuver and reflects both large and peripheral airway function.27 Thus differential changes in FEV1 and PEF may be observed, depending on the amount and predominant site of airways narrowing. These factors are likely to lead to a greater discrepancy in patients with COPD and airway collapsibility secondary to the loss of elastic tissue. In these patients, the initial rapid rise in expiratory flow is similar but, as intrathoracic pressure increases, that pressure is transmitted to the segmental and other large airways, which "collapse" and obstruct passage of air through those airways. This results in the rapid reduction in flow after a relatively normal peak has been attained, leading to significantly lower values of FEV1 compared to PEF.

These issues could lead to a significant discordance if FEV1% values are replaced by PEF% values for purpose of severity classification. As it is, there is no clearly defined objective strategy to categorize severity of airflow limitation based on FEV1% values. Various guidelines on management of asthma and COPD use arbitrary standards for this purpose, adding to the confusion. The FEV1% cutoffs used to categorize mild, moderate, and severe obstruction are variable for Global Initiative for Chronic Obstructive Lung Disease (80% and 30%), British Thoracic Society (60% and 40%), American Thoracic Society (50% and 35%), European Respiratory Society (70% and 50%) and new American Thoracic Society/European Respiratory Society (80% and 50%) guidelines on COPD.1213282930 Both Global Initiative for Asthma and National Institutes of Health guidelines on asthma use FEV1% cutoffs of 80% and 60%.911 In the absence of any standard severity classification, we used arbitrary severity groups based on FEV1% values and have shown that less than one half the subjects were correctly classified if PEF% replaces FEV1% values (Table 2).

In addition, there are other technical issues related to equipment. Several PEF meters do not show linear responses, with different proportional error at different flow levels.31 Significant decrease in accuracy and precision has also been reported after regular peak flowmeter use.32 Submaximal effort during PEF maneuver, supramaximal flow transients occurring early during a forced expiration, and PEF maneuver-induced bronchospasm are phenomena that may account for some of the discrepancies between PEF and FEV1 values.

It is clear from these results that if international guidelines are followed and PEF% is used as a surrogate for FEV1%, then severity of obstruction may be wrongly categorized in a large proportion of patients. The impact of use of PEF on categorization of severity of stable asthma was reported in an earlier study,18 in which the categorization using PEF% and FEV1% was concordant in only one half of the patients. Misclassification was particularly evident in patients with severe asthma. Significant differences were also reported in a study24 of patients with exacerbation of asthma. These differences are likely to be more pronounced in women and in patients with less severe airways obstruction (defined by FEV1%), as is evident from the results of logistic regression analysis conducted in this study. This has far-reaching implications for developing and resource-poor countries where facilities for conducting spirometry are not freely available, and physicians rely mainly on clinical features and/or PEF estimation to assess severity of airflow limitation. While our data set comprising of a large number of spirometry records does provide results that can perhaps be interpreted with greater confidence than previous studies, we are aware of certain inadequacies. The major limitation of our work is its retrospective nature, because of which we are unable to provide results separately for patients with asthma and COPD, or provide exact data regarding acceptability/repeatability goals of individual spirometry maneuvers. Moreover, our results remain strictly applicable to only the kind of patient population investigated at our pulmonary function laboratory and may not be generalized to other sets of patients. We therefore suggest that until such time that more data are available, assumptions of parity between PEF% and FEV1% must be avoided in assessment of patients with obstructive airway disease. In case spirometry is not available, PEF measurements can be performed for broad assessment, but patients should not be categorized as having mild, moderate, or severe obstruction based on these results.

Footnotes

Abbreviations: CI = confidence interval; FEV1% = percentage of predicted FEV1; PEF = peak expiratory flow; PEF% = percentage of predicted peak expiratory flow; VC = vital capacity

The authors have no conflicts of interest to disclose.

Received for publication November 16, 2005. Accepted for publication April 13, 2006.

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