The 22-Item Sinonasal Outcome Test as a Tool for the Assessment of Quality of Life and Symptom Control in Allergic Rhinitis

Abstract

Background

The 22-item Sinonasal Outcome Test (SNOT-22) is a validated patient-reported outcome measure for chronic rhinosinusitis and in many circumstances is used in rhinology/otolaryngology clinics to assess sinonasal symptoms in general when a formal diagnosis is not established, although with little support for such usage.

Objective

To assess the utility of the SNOT-22 as a reflection of quality of life (QOL) and symptom control for patients with allergic rhinitis (AR).

Methods

Retrospective review of 353 patients with persistent AR. Each patient completed a SNOT-22, 5-item EuroQol general health-related QOL (EQ-5D) questionnaire (from which the visual analog scale [VAS] was used), and Rhinitis Control Assessment Test (RCAT). In addition, 95 patients also completed these questionnaires 1 to 12 months later.

Results

The SNOT-22 was negatively correlated with the EuroQol 5-dimensional visual analog scale (EQ-5D VAS; r = −.45, 95% confidence interval [CI]: −0.53 to −0.36, P < .001) and RCAT (r = −.62, 95% CI: −0.68 to −0.55, P < .001), with excellent internal consistency. The SNOT-22 demonstrated responsiveness, with mean change of −5.8 (95% CI: −8.9 to −2.6, P < .001) from pre- to posttreatment. The change in SNOT-22 over the treatment period was correlated with change in EQ-5D VAS (r = −.28, 95% CI: −0.46 to −0.07, P = .008) and RCAT (r = −.56, 95% CI: −0.69 to −0.41, P < .001). The minimal clinically important difference was calculated to be between 6 and 11.

Conclusion

The SNOT-22 has utility to assess QOL and symptom control in AR, and it is both reliable and responsive in its application to patients with AR. The SNOT-22 may therefore be a convenient and versatile tool in the clinical assessment of patients with AR.

Keywords

allergic rhinitis 22-item Sinonasal Outcome Test patient-reported outcome measure control quality of life

Introduction

Allergic rhinitis (AR) affects as many as 20% to 40% of individuals and leads to a significant quality of life (QOL) loss as well as lost productivity in the workplace and at home.^1,2 AR is defined by its characteristic nasal symptoms including sneezing, pruritus, rhinorrhea, and nasal obstruction. AR is one of the most common diseases encountered in an otolaryngology practice, and the evaluation of patients with sinonasal symptoms represents a major component of otolaryngic care.^3,4

With the increasingly realized utility of patient-reported outcome measures (PROMs) in the form of questionnaires to not only assess the burden of disease but also to provide insight for prognosis, incorporation of PROMs in clinical practice is a necessity. However, convenience is critical for the successful incorporation of PROMs which require minimal disruption of clinical workflow while enabling effortless completion by the patient. One major obstacle for implementing disease-specific PROMs in clinical practice is the lack of a priori knowledge of what condition a patient may have upon presentation even after multiple clinical encounters, thus preventing the utilization of an appropriate and clinically informative PROM.

AR and chronic rhinosinusitis (CRS) have many overlapping symptoms, including diagnostic nasal symptoms and extranasal symptoms as well. A common PROM that could be given to patients presenting with symptoms suggestive of either of these diseases would be very convenient for implementation into a clinical practice and ascertainment of patient-reported outcomes from an initial encounter. The 22-item Sinonasal Outcome Test (SNOT-22) may be such a PROM.

The SNOT-22 is a validated questionnaire that was developed and validated to assess the burden of CRS symptomatology.^5,6 It includes both classic nasal symptoms as well as extranasal symptoms such as poor sleep, ear/facial discomfort, and mood disturbance, features that have also been associated with AR.^7–9 In the past, the 20-item SNOT—a predecessor of the SNOT-22—has been used to assess patients with chronic rhinitis, including patients with AR,¹⁰ and more recently, the SNOT-22 has been used to gain insights into the burden of AR symptoms and their downstream effects on patients.^7,11,12 However, to establish the clinical utility of the SNOT-22, it must be established as a reflection of outcome measures pertinent to AR. We therefore sought to establish the SNOT-22 as a reliable reflection of QOL and AR symptom control (both patient-reported outcomes utilized in the clinical management of AR) that could be followed longitudinally in order to assess the treatment response.

Methods

Patient Selection

This study was approved by the Massachusetts Eye and Ear Infirmary Human Studies Committee. We retrospectively identified 353 adult patients aged 18 years or older diagnosed with persistent AR based on formal skin or serological allergy testing¹³ and a history consistent with the Allergic Rhinitis and its Impact on Asthma (ARIA) guidelines.² Data were collected from each patient’s initial visit to our clinics for the management of AR between March 1, 2016 and August 1, 2018. When available (for 95 patients), data were also collected from a follow-up visit, 1 to 12 months later after medical treatment of AR with intranasal saline irrigation and intranasal corticosteroids and/or antihistamines. Exclusion criteria included comorbid diagnoses of CRS (which was excluded based on endoscopy—for example, the presence of polyps, not meeting consensus guideline CRS symptom criteria and—when needed—sinus computed tomography scan), vasculitis, cystic fibrosis, sarcoidosis, or immunodeficiency. Additional exclusion criteria included not completing the studied PROMs/assessment tools described below.

Data Collection

This is a retrospective study. Data collected at the time of each patient’s initial visit included age, gender, history of asthma (based on clinical evaluation and clinical history/prior diagnosis), and smoking history of all participants were recorded. Any participant who was a current or former tobacco smoker was considered a smoker for this study.¹⁴ All patients were evaluated using anterior rhinoscopy and nasal endoscopy. All patients completed a Rhinitis Control Assessment Test (RCAT), which assesses the control of rhinitis and its associated symptomatology, at each clinic visit.¹⁵ All patients completed a SNOT-22 questionnaire at each clinic visit.⁵ The SNOT-22 assesses 22 symptoms, which are related to nasal symptoms, sleep quality, otologic symptoms, or emotional symptoms, on an integer scale of 0—“no problem,” 1—“very mild problem,” 2—“mild to slight problem,” 3—“moderate problem,” 4—“severe problem,” or 5—“problem as bad as it can be.” General health-related QOL was measured by the validated EuroQol 5-dimensional visual analog scale (EQ-5D VAS) given with the 5-level EQ-5D questionnaire at each clinic visit.^16,17 EQ-5D VAS measures the current state of health—with 0 as the minimum, representing the “worst health you can imagine” and 100 as the maximum, representing the “best health you can imagine.” At the follow-up visits, patients also answered a question related to change in their general health, which asked patients to compare their general health at the follow-up visit compared to the prior clinic visit, on a 5-item scale: “Much worse,” “A little worse,” “About the same,” “A little better,” and “Much better.”⁵

Statistical Analysis

All analyses were performed with the statistical software package R.¹⁸ Standard descriptive statistics were performed. All correlations were calculated with Pearson’s correlation. Where it was used, receiver operator characteristic (ROC) curve analysis¹⁹ was performed by calculating the area under the ROC curve (AUC) with the trapezoid rule and the 95% confidence interval [CI] of the AUC was calculated by performing 2000 bootstraps of the data.

Internal consistency was assessed using Cronbach’s alpha, mean item–item correlation, and mean correlation between each item and the sum of the rest of the items. The SNOT-22 as reflection of QOL and AR symptom control was assessed by checking for the correlation (at the first visit) between SNOT-22 and RCAT and correlation between SNOT-22 and EQ-5D VAS scores. Responsiveness was assessed by comparing SNOT-22 score at the initial visit to the SNOT-22 score at follow-up after medical treatment of AR. Responsiveness was also assessed by checking for the correlation between change in SNOT-22 and change in RCAT as well as the correlation between change in SNOT-22 and change in EQ-5D VAS, after medical treatment of AR.

The minimal clinically important difference (MCID) of the SNOT-22 was calculated in 3 ways. The first method was a distribution-based method that was calculated as half of the standard deviation of patients’ SNOT-22 scores at the first visit.²⁰ The second method was an anchor-based method whereby the MCID was calculated as the difference in mean SNOT-22 score change between patients responding with “About the same” compared to those responding with “A little better” on the general health anchor question.^5,6,20 The third method for calculating MCID used ROC analysis.¹⁹ The ROC method identified the change in SNOT-22 score which maximized the sum of sensitivity and specificity of identifying participants who reported an improvement (“A little better” or “Much better”) in their general health.

Results

Patient Characteristics

A total of 353 of patients (35.7% male, 64.3% female) with persistent AR were identified with mean age of 43.5 (standard deviation [SD]: 15.8). Among all of the patients, 22.9% had a history of smoking tobacco and 19.0% were asthmatics. In these patients, the mean SNOT-22 score was 38.3 (SD: 21.4), the mean RCAT score was 19.2 (SD: 4.4), and the mean EQ-5D VAS was 72.5 (SD: 18.8). Of these patients, 69.1% had RCAT score less than 22, indicating poor AR control. There was a statistically significant difference in SNOT-22 score (P = .006) in asthmatics (mean = 44.1, SD: 19.8) compared to nonasthmatics (mean = 36.9, SD: 21.6). For 95 patients, data (including SNOT-22, RCAT, and EQ-5D scores) were available at the next clinical follow-up visit between 1 and 12 months later (mean follow-up time was 176 days). In these 95 patients at baseline, the mean SNOT-22 score was 36.4 (SD: 19.7), the mean RCAT score was 19.6 (SD: 4.2), and the mean EQ-5D VAS was 72.8 (SD: 15.9). At follow-up, the mean SNOT-22 score was 30.6 (SD: 19.7), the mean RCAT score was 20.9 (SD: 3.9), and the mean EQ-5D VAS was 74.5 (SD: 15.8).

All SNOT-22 Items Are Relevant to AR Patients

The SNOT-22 questionnaire consists of not only the classic nasal symptoms (sneezing, mucus production, and nasal obstruction) that AR patients experience but also extranasal symptoms related to poor sleep, ear/facial discomfort, and mood disturbance. Although these symptoms have all been associated with AR, it is important to determine whether all of the items on the SNOT-22 are pertinent to the assessment of patients with AR. The internal consistency of the SNOT-22 for these patients with AR can help to determine whether any of the items is not relevant, that is, not consistent with the others.

The internal consistency of the SNOT-22 was assessed in several ways and the results are summarized in Table 1. Cronbach’s alpha for the entire SNOT-22 was measured at 0.93 (95% CI: 0.92–0.94). This value of Cronbach’s alpha did not change by dropping any of the SNOT-22 items, which suggested that none of the items were superfluous. The mean item–item correlation ranged from 0.28 to 0.49. The mean correlation between each item and the sum of the rest ranged from 0.46 to 0.81.

Table 1.

Internal Consistency of the SNOT-22.

SNOT-22 Item	Cronbach Alpha If Item Dropped	Mean Item–Item Pearson Correlation Coefficient	Mean Item–Total Pearson Correlation Coefficient^a
1—Need to blow nose	.93	0.32	0.54
2—Sneezing	.93	0.28	0.46
3—Runny nose	.93	0.28	0.46
4—Cough	.93	0.28	0.46
5—Post nasal discharge	.93	0.34	0.55
6—Thick nasal discharge	.93	0.38	0.62
7—Ear fullness	.93	0.34	0.56
8—Dizziness	.93	0.36	0.58
9—Ear pain/pressure	.93	0.34	0.57
10—Facial pain/pressure	.93	0.36	0.59
11—Difficulty falling asleep	.93	0.42	0.69
12—Waking up at night	.93	0.41	0.68
13—Lack of a good night’s sleep	.93	0.44	0.74
14—Waking up tired	.93	0.48	0.79
15—Fatigue during the day	.93	0.49	0.81
16—Reduced productivity	.93	0.48	0.80
17—Reduced concentration	.93	0.48	0.79
18—Frustrated/restless/irritable	.93	0.47	0.77
19—Sad	.93	0.40	0.65
20—Embarrassed	.93	0.35	0.57
21—Sense of taste/smell	.93	0.31	0.50
22—Blockage/congestion of nose	.93	0.37	0.60

Abbreviation: SNOT-22, 22-Item Sinonasal Outcome Test.

Corrected item–total correlation coefficient where the item itself was not included in the total score.

The SNOT-22 Score Is Reflective of QOL and Symptom Control in AR

We checked for the validity of the SNOT-22 as reflections of QOL and AR symptom control by checking for the correlation between the SNOT-22 and the EQ-5D VAS (a measure of general health-related QOL) and the RCAT (a measure of AR control). The SNOT-22 was correlated with both the RCAT (r = −.67, 95% CI: −0.75 to −0.56, P < .001) and the EQ-5D VAS (r = −.50, 95% CI: −0.61 to −0.37, P < .001). The relationships are depicted in Figure 1. We additionally found that a SNOT-22 score of greater than 36 accurately detected patients with poor AR control (AUC = 0.759, 95% CI: 0.705–0.813, P < .001). A SNOT-22 score of greater than 36 detected patients with poor AR control with 59.8% sensitivity and 78.9% specificity.

Figure 1.

Scatterplot of SNOT-22 versus (A) RCAT score and (B) EQ-5D VAS. EQ-5D VAS, EuroQol 5-dimensional visual analog scale; RCAT, Rhinitis Control Assessment Test; SNOT-22, 22-Item Sinonasal Outcome Test.

The SNOT-22 Score Appropriately Changes After Treatment, and in Conjunction With Change in QOL or Symptom Control

Appropriate change in SNOT-22, or responsiveness, after treatment for AR was assessed by comparing the change in SNOT-22 score from pre- to posttreatment of AR. After treatment for AR, patients experienced a statistically significant decrease (improvement) in the SNOT-22 score, with a mean change of −5.8 (95% CI: −8.9 to −2.6, P < .001). We also checked for the correlation between change in the SNOT-22 and change in the RCAT and EQ-5D VAS, respectively (Figure 2). We found that the change in SNOT-22 score was correlated with the change in RCAT (r = −.56, 95% CI: −0.69 to −0.41, P < .001) and with the change in EQ-5D VAS (r = −.28, 95% CI: −0.46 to −0.07, P = .008).

Figure 2.

Scatterplot of change in SNOT-22 versus change in (A) RCAT score and (B) EQ-5D VAS. EQ-5D VAS, EuroQol 5-dimensional visual analog scale; RCAT, Rhinitis Control Assessment Test; SNOT-22, 22-Item Sinonasal Outcome Test.

MCID of the SNOT-22 for AR

The MCID of the SNOT-22 after treatment of AR was calculated in several ways. Using a distribution-based method, by calculating 0.5 times the standard deviation of the SNOT-22 of all patients at the first time point, the MCID would be 10.7. An MCID of 10.7 would provide 48.5% sensitivity and 69.4% specificity for detecting patients who report their symptoms to be at least “a little better” after treatment. We also used anchor-based methods to calculate MCID (with data summarized in Table 2 and Figure 3). Using the global anchors for general health, we found that the difference in SNOT-22 score change between patients who report their health to be “about the same” compared to “a little better” after treatment of AR was 8.1 (P = .016). An MCID of 8.1 provided 57.6% sensitivity and 64.5% specificity for detecting patients who reported that their health was at least “a little better” after treatment for AR. Using ROC analysis, we found that an MCID of 6 (AUC = 0.645, 95% CI: 0.532–0.769, P = .020) maximized the sum of sensitivity (72.7%) and specificity (56.5%) for detecting patients who reported their health to be at least “a little better” from pre- to posttreatment.

Table 2.

Anchor-Based Changes in SNOT-22 Score.

Change in General Health	Much Worse	A Little Worse	About the Same	A Little Better	Much Better
Change in SNOT-22 score, mean (SD)	1 (—)	1.6 (18.6)	−4.3 (16.2)	−12.4 (13.8)	−7.7 (10.0)

Abbreviations: SD, standard deviation; SNOT-22, 22-Item Sinonasal Outcome Test.

Figure 3.

Boxplot of change in SNOT-22 versus patient response on general health anchor question. SNOT-22, 22-Item Sinonasal Outcome Test.

Discussion

The use of PROMs can offer tremendous insights into patient care but efficiency, convenience, and proper distribution of PROMs to the appropriate patients can be obstacles to implementation. The proper distribution of PROMs—that is, knowing which patients should receive which PROMs—can be a challenge since diagnoses are not always made on the first or even second encounter. As a result, often disease-specific PROMs cannot be reliably used in the clinical setting until after treatments have been given and important points in the clinical decision-making process have passed without the added benefit of an informative PROM. AR and CRS are both conditions for which treatment decisions are tailored toward maximizing patient-reported symptom burden. CRS and AR (in particular persistent AR) may have substantially overlapping symptomatology and those affected by each of these diseases sometimes meet subjective diagnostic criteria for both conditions. This poses a logistical dilemma for the utilization of disease-specific PROMs until objective diagnostic testing (eg, sinus computed tomography scan and skin or serological allergy testing) can be performed. Ideally, one common PROM could be used to assess clinical outcomes of patients with either AR or CRS. We hypothesized that the SNOT-22, which assesses nasal and extranasal symptoms associated with both AR and CRS, could serve as such a tool in the clinical setting. As a reflection of the burden of CRS symptomatology, the SNOT-22 has been used as a measure of symptom control as well as disease-specific QOL.^21–24 However, its use for AR has not been established. In this study, we showed that the SNOT-22 may have utility for assessing QOL and symptom control for AR and for monitoring these outcomes longitudinally.

Multiple PROMs have already been developed, validated, and well established for the assessment of patients with AR. These PROMs include the RCAT, Rhinoconjunctivitis Total Symptom Score (RTSS), and the Rhinoconjunctivitis Quality of Life Questionnaire (RQLQ). The RCAT was developed and validated to assess the control of AR disease manifestations such as nasal congestion, sneezing, watery eyes, poor sleep problems, and activity avoidance.²⁵ The RTSS was developed and validated to assess the severity of nasal symptoms.²⁶ In comparison, the 28-item RQLQ, like the SNOT-22, was developed and validated to assess disease-specific (ie, AR-specific) QOL.²⁷ The RQLQ assesses the burden of a broad range of AR disease manifestations, such as disruption of daily activities, decreased general well-being, and AR-related symptomatology.

In this study, we focused on the SNOT-22 which assesses nasal and extranasal symptoms that are all associated with both AR and CRS.^9,28–32 In administration of the SNOT-22 to patients with AR, we found that the SNOT-22 was internally consistent with all SNOT-22 items pertinent (ie, all items consistent) and reliably reflective of QOL and AR symptom control. We also found that a SNOT-22 score greater than 36 accurately identified patients with poor AR symptom control, a finding that was remarkably consistent with our prior study showing that a SNOT-22 score of 35 accurately identified patients with CRS who felt their symptoms were uncontrolled.²¹ Moreover, we find that the MCID of SNOT-22 for patients with AR to be in the range of 6 to 11, which is similar to previously reported MCIDs of the SNOT-22 for CRS.^5,6

Although PROMs have been specifically developed and validated for the assessment of AR, we propose that the SNOT-22 may be a viable tool for the assessment of patients with AR in the clinical setting for practical reasons. PROMs are increasingly used outside of research in the clinical setting and are being recognized as important mechanisms through which providers can quantitatively assess patients in a manner that can be both immediately informative and directly translated to long-term prognosis.³³ The use of the SNOT-22 to assess sinonasal symptom burden in a patient who may have either AR or CRS but for whom the diagnosis has not yet been formally established is better than not using any PROM.

Our results should be interpreted in the context of their limitations. First, the SNOT-22 was not developed as a tool for the assessment of AR and we do not contend that the SNOT-22 is the optimal tool for assessing AR symptom burden. In fact, PROMs developed specifically for AR such as the RQLQ more comprehensively assess the symptomatology of AR, such as the assessment of allergic conjunctivitis that is assessed by the RQLQ but not the SNOT-22. However, given the realities of clinical practice and the uncertainties in diagnoses, we would propose that administering a PROM that is reliably reflective of QOL and symptom control in both CRS and AR is better than not at all. The argument could also be made that an AR-specific tool, such as the RQLQ, could be applied to CRS. However, the SNOT-22 is over 20% shorter in length than the RQLQ, which increases the convenience and time expenditure for patients and the SNOT-22 also assesses symptoms associated with both diseases while the RQLQ assesses symptoms (eg, ocular symptoms) that are not associated with CRS, and therefore may exhibit lower internal consistency. Our study was also retrospective in nature and limited by the inherent biases in these analyses. With respect to the sample size, the MCID was calculated with a subset of patients from whom we had data from multiple time points. Although our calculated MCIDs are similar to previous estimates of SNOT-22 MCID for CRS, we did not find our MCID estimates to be particularly accurate with respect to the sensitivity and specificity in identifying patients experiencing significant clinical improvement—a problem that is common with MCID in general^6,17,34–37—although this finding could very well have been also related to the smaller number of patients used in our analysis. Future work should seek to either confirm or revise the MCID estimates provided here.

Conclusion

The SNOT-22 has utility to assess QOL and symptom control in AR. Although the SNOT-22 was not developed for AR, our findings facilitate the use of a single PROM for both CRS and AR patients. This single tool may be particularly helpful during early clinical patient encounters when common symptomatology between these diseases may make them indistinguishable before further objective testing can be performed.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Seidman

Gurgel

Lin

, et al. Clinical practice guideline: allergic rhinitis. Otolaryngol Head Neck Surg. 2015; 152:S1–S43.

Bousquet

Khaltaev

Cruz

, et al. Allergic Rhinitis and its Impact on Asthma (ARIA) 2008 update (in collaboration with the World Health Organization, GA(2)LEN and AllerGen). Allergy. 2008; 63 Suppl 86:8–160.

Cheang

Khalil

Do rhinology care pathways in primary care influence the quality of referrals to secondary care?

J Laryngol Otol. 2013; 127:364–367.

Rosenfeld

Piccirillo

Chandrasekhar

, et al. Clinical practice guideline (update): adult sinusitis. Otolaryngol Head Neck Surg. 2015; 152:S1–S39.

Hopkins

Gillett

Slack

Lund

Browne

JP.

Psychometric validity of the 22-item Sinonasal Outcome Test.

Clin Otolaryngol. 2009; 34:447–454.

Phillips

Hoehle

Caradonna

Gray

Sedaghat

AR.

Minimal clinically important difference for the 22-item Sinonasal Outcome Test in medically managed patients with chronic rhinosinusitis.

Clin Otolaryngol. 2018; 43:1328–1334.

Hoehle

Speth

Phillips

, et al. Association between symptoms of allergic rhinitis with decreased general health-related quality of life. Am J Rhinol Allergy. 2017; 31:235–239.

Zhou

Hur

Shen

Wrobel

Impact of sinonasal disease on depression, sleep duration, and productivity among adults in the United States.

Laryngoscope Investig Otolaryngol. 2017; 2:288–294.

Feng

Wesely

Hoehle

, et al. A validated model for the 22-item Sino-Nasal Outcome Test subdomain structure in chronic rhinosinusitis. Int Forum Allergy Rhinol. 2017; 7:1140–1148.

10.

Pynnonen

Kim

Terrell

JE.

Validation of the Sino-Nasal Outcome Test 20 (SNOT-20) domains in nonsurgical patients.

Am J Rhinol Allergy. 2009; 23:40–45.

11.

Campbell

Hoehle

Phillips

Caradonna

Gray

Sedaghat

AR.

Depressed mood is associated with loss of productivity in allergic rhinitis.

Allergy. 2018; 73:1141–1144.

12.

Speth

Hoehle

Phillips

Caradonna

Gray

Sedaghat

AR.

Treatment history and association between allergic rhinitis symptoms and quality of life.

Ir J Med Sci. 2019; 188:703–710.

13.

Dykewicz

Fineman

Skoner

, et al. Diagnosis and management of rhinitis: complete guidelines of the Joint Task Force on Practice Parameters in Allergy, Asthma and Immunology. American Academy of Allergy, Asthma, and Immunology. Ann Allergy Asthma Immunol. 1998; 81:478–518.

14.

Hoehle

Phillips

Caradonna

Gray

Sedaghat

AR.

A contemporary analysis of clinical and demographic factors of chronic rhinosinusitis patients and their association with disease severity.

Ir J Med Sci. 2018; 187:215–221.

15.

Schatz

Meltzer

Nathan

, et al.

Psychometric validation of the Rhinitis Control Assessment Test: a brief patient-completed instrument for evaluating rhinitis symptom control.

Ann Allergy Asthma Immunol. 2010; 104:118–124.

16.

EuroQol

EuroQol—a new facility for the measurement of health-related quality of life. Health Policy (Amsterdam, Netherlands). 1990; 16:199–208.

17.

Hoehle

Phillips

Speth

Caradonna

Gray

Sedaghat

AR.

Responsiveness and minimal clinically important difference for the EQ-5D in chronic rhinosinusitis.

Rhinology. 2019; 57:110–116.

18.

TeamRDC. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2011.

19.

Gerlinger

Schmelter

Determining the non-inferiority margin for patient reported outcomes.

Pharm Stat. 2011; 10:410–413.

20.

Cook

CE.

Clinimetrics corner: the Minimal Clinically Important Change Score (MCID): a necessary pretense.

J Man Manip Ther. 2008; 16:E82–E83.

21.

Gray

Phillips

Hoehle

Caradonna

Sedaghat

AR.

The 22-item Sino-Nasal Outcome Test accurately reflects patient-reported control of chronic rhinosinusitis symptomatology.

Int Forum Allergy Rhinol. 2017; 7:945–951.

22.

Hoehle

Phillips

Bergmark

Caradonna

Gray

Sedaghat

AR.

Symptoms of chronic rhinosinusitis differentially impact general health-related quality of life.

Rhinology. 2016; 54:316–322.

23.

Speth

Hoehle

Phillips

Caradonna

Gray

Sedaghat

AR.

Changes in chronic rhinosinusitis symptoms differentially associate with improvement in general health-related quality of life. Ann Allergy Asthma Immunol. 2018; 121:195–199.

24.

Sedaghat

Hoehle

Gray

ST.

Chronic rhinosinusitis control from the patient and physician perspectives.

Laryngoscope Investig Otolaryngol. 2018; 3:419–433.

25.

Meltzer

Schatz

Nathan

Garris

Stanford

Kosinski

Reliability, validity, and responsiveness of the Rhinitis Control Assessment Test in patients with rhinitis.

J Allergy Clin Immunol. 2013; 131:379–386.

26.

United States Food and Drug Adminstration. Allergic Rhinitis: Developing Drug Products for Treatment—Guidance for Industry. https://www.fda.gov/downloads/drugs/guidances/ucm071293.pdf. Accessed December 14, 2018.

27.

Juniper

Guyatt

GH.

Development and testing of a new measure of health status for clinical trials in rhinoconjunctivitis.

Clin Exp Allergy. 1991; 21:77–83.

28.

Bousquet

Demoly

Devillier

Mesbah

Bousquet

Impact of allergic rhinitis symptoms on quality of life in primary care.

Int Arch Allergy Immunol. 2013; 160:393–400.

29.

Hiraki

Suzuki

Udaka

Shiomori

Snoring, daytime sleepiness, and nasal obstruction with or without allergic rhinitis.

Arch Otolaryngol Head Neck Surg. 2008; 134:1254–1257.

30.

Pelikan

The role of nasal allergy in chronic secretory otitis media.

Ann Allergy Asthma Immunol. 2007; 99:401–407.

31.

Chen

, et al.

Allergic disorders and risk of depression: a systematic review and meta-analysis of 51 large-scale studies.

Ann Allergy Asthma Immunol. 2018; 120:310–317.e312.

32.

Sedaghat

Gray

Caradonna

DS.

Clustering of chronic rhinosinusitis symptomatology reveals novel associations with objective clinical and demographic characteristics.

Am J Rhinol Allergy. 2015; 29:100–105.

33.

Hopkins

Rudmik

Lund

VJ.

The predictive value of the preoperative Sinonasal Outcome Test-22 score in patients undergoing endoscopic sinus surgery for chronic rhinosinusitis.

Laryngoscope. 2015; 125:1779–1784.

34.

Schram

Spuls

Leeflang

Lindeboom

Bos

Schmitt

EASI, (objective) SCORAD and POEM for atopic eczema: responsiveness and minimal clinically important difference.

Allergy. 2012; 67:99–106.

35.

Katzberg

Barnett

Merkies

Bril

Minimal clinically important difference in myasthenia gravis: outcomes from a randomized trial.

Muscle Nerve. 2014; 49:661–665.

36.

Young

Jeong

Rothenberger

, et al. Minimal clinically important difference of voice handicap index-10 in vocal fold paralysis. Laryngoscope. 2018; 128:1419–1424.

37.

Sedaghat

AR.

Understanding the minimal clinically important difference (MCID) of patient-reported outcome measures. Otolaryngol Head Neck Surg. 2019; 161:551–560.