Sage Journals: Discover world-class research

Abstract

Background: All stakeholders in the healthcare system have prioritized and will continue to prioritize enhancing care quality. The measurement of sinus-specific quality of life (QOL) is potentially the most commonly used QOL parameter for chronic rhinosinusitis (CRS). Objective: A systematic review and meta-analysis were used in this study to determine the mean change in patients’ scores on the 22-item Sino-Nasal Outcome Test (SNOT-22) before and after endoscopic sinus surgery (ESS) for CRS. Methods: PubMed, Google Scholar, and ScienceDirect were searched for articles that compared SNOT-22 scores before and after ESS in adult patients with CRS and were published between January 2000 and March 2023. The mean post-op change, 95% confidence interval (CI), forest plot, and inverse variance weighting were all generated using a random effects model. A mixed-effects meta-regression was used to analyze the effect of patient-specific characteristics across studies. Results: Fifteen prospective patient cohorts published from 2009 to 2023 were included in this meta-analysis. At an average follow-up of 25.5 months, all studies demonstrated a statistically significant difference in mean SNOT-22 scores between baseline and post-op time periods (P < .05), ranging from 5.1 to 55.4. Across all studies, the mean SNOT-22 changed significantly by 26.02 (95% CI: 12.83-38.60). According to a stepwise multivariate analysis, studies with higher mean age and mean pre-op SNOT-22 scores had greater changes in SNOT-22 scores following ESS, whereas trials with longer mean follow-up duration had smaller changes in SNOT-22 scores. Conclusion: Research utilizing the SNOT-22 instrument has demonstrated that endoscopic sinus surgery (ESS) leads to enhanced quality of life (QOL) outcomes. The literature reports that improvement is influenced by the initial SNOT-22 score, the mean age of the patients, and the duration of the follow-up period.

Plain Language Summary

The Sino-Nasal Outcome Test-22 (SNOT-22) has shown that the quality-of-life results of sinus surgery after endoscopic sinus surgery (ESS) improve significantly. The amount of change seems to vary a lot from one study to the next, and this difference seems to be caused by things like the pre-op SNOT-22 score, the average age of the subjects, and the length of the tracking period. The results of this study give both a single number value and a range of changes that are likely to happen after surgery. These results can be used to guide projects that aim to improve the quality of care. Also, giving the Sino-Nasal Outcome Test-22 (SNOT-22) to people with chronic rhinosinusitis (CRS) before they have surgery may help them understand what effects they can expect, although this is up to each person to decide. Recent preliminary research shows that using SNOT-22 scores and tissue histopathology together could be a new way to predict how well treatment will work for people with CRS. The accuracy and precision of future analyses are likely to get better as efforts are made to get unbiased data and patient-level metrics from a wide range of patients and doctors.

Keywords

chronic rhinosinusitis endoscopic sinus surgery meta-analysis quality of life SNOT-22

Introduction

Rhinosinusitis is a commonly occurring medical condition that has a significant impact on the quality of life (QOL) of individuals globally.¹ Chronic rhinosinusitis (CRS), commonly abbreviated as CRS, is a prevalent and complex medical condition that imposes significant societal and financial ramifications. CRS is prevalent in 15% of the populace in developed countries, rendering it the second most frequently occurring persistent ailment.² The pathophysiology and etiology of the condition have been thoroughly established in the literature. However, the treatment approach is subject to frequent modifications due to the rapidly evolving nature of the causative organism and antimicrobial resistance, posing a challenge to healthcare providers. This is supported by existing research.³

CRS has been associated with a range of upper and lower airway complications, including but not limited to nasal polyposis, asthma, and cystic fibrosis.⁴ Although not posing a threat to life, rhinosinusitis has a significant impact on daily functioning and QOL.⁵ The initial treatment for CRS comprises of nasal saline irrigation, systemic steroids, and anti-inflammatory steroids that effectively drain the paranasal sinuses.⁶ Nevertheless, a considerable number of individuals exhibit resistance toward these therapies and necessitate the implementation of functional endoscopic sinus surgery (FESS) to ameliorate their symptoms and enhance their standard of living, given that endoscopic sinus surgery (ESS) possesses the capability to reinstate the typical mucociliary flow.⁷ Due to the significance and gravity of this pathological condition, it is imperative to exercise caution when selecting patients for surgical intervention and to comprehend the determinants that forecast surgical outcomes, with the aim of optimizing success and minimizing risk.⁸

The evaluation of the QOL of individuals with CRS can be conducted through the utilization of generic questionnaires such as the SF-36. However, it is more suitable to employ disease-specific questionnaires like the SNOT-22 for this purpose. Individuals diagnosed with CRS who have not experienced improvement from pharmacological interventions are suitable candidates for FESS. Additionally, the Sino-Nasal Outcome Test-22 (SNOT-22) is a valuable tool for forecasting the QOL in patients with CRS.⁹

The SNOT-22 questionnaire comprises questions that are evaluated on a scale of 0 to 5, resulting in a total score range of 0 to 110. Higher scores on this scale are indicative of lower QOL. According to the referenced source,¹⁰ the typical value for minimal clinically important difference (MCID) is 8.9 points. According to several studies, the utilization of ESS has been found to enhance SNOT-22 scores in adults with CRS.^11-15 To incorporate SNOT-22 scores as an outcome measure in quality improvement initiatives, it is imperative to possess knowledge regarding the anticipated spectrum of alteration. Familiarity with the customary amelioration subsequent to ESS and patient factors that could influence results is necessary for citing this source. Taking all factors into account, a systematic review was conducted on a set of studies^16-30 that evaluated the alteration in SNOT-22 score following ESS for adult patients diagnosed with CRS. Additionally, a meta-analysis was conducted to determine the average change in SNOT-22.

Objectives: The present study investigates the variability in mean change observed across multiple trials and explores potential patient-specific factors that may contribute to this variability.

Materials and Methods

The current meta-analysis was conducted in accordance with the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines.³¹

Eligibility Criteria

For a study to be considered eligible, certain criteria must be satisfied: (a) Prospective studies examining the alteration in SNOT-22 score among individuals with CRS prior to and following EES and (b) investigations assessing the primary endpoints, including the disparity in average SNOT-22 score before and after the surgical procedure, the duration of the follow-up period, and the average age of the participants. The exclusion criteria comprised of clinical trials that had a follow-up duration of <1 month. This meta-analysis excluded studies that involved healthy participants or individuals with disorders other than CRS who were not undergoing EES.

Information Sources

A comprehensive literature review was performed by searching the electronic databases Cochrane Library, EMBASE, and PubMed up until March 2023. Furthermore, pertinent meta-analyses and bibliographies of studies were also examined.

Search Strategy

A comprehensive literature review was performed utilizing the following predetermined criteria for inclusion: The inclusion criteria for the studies were as follows: (i) the studies had to be either prospective or retrospective in nature and had to report the SNOT-22 score in patients with CRS both before and after undergoing ESS; (ii) the studies had to include patients with CRS who were 18 years of age or older; and (iii) the studies had to provide data on the primary outcome. The study aimed to investigate the pre-op SNOT-22 score, the mean difference in SNOT-22 score before and after surgery, the duration of the follow-up period, and the average age of patients. A systematic review was conducted to identify articles published in the English language that used the keywords “Chronic Rhinosinusitis” or “CRS,” “Endoscopic Sinus Surgery” or “ESS,” “22-test Sino nasal test outcome” or “SNOT-22,” “Quality of Life” or “QOL,” “Meta-analysis,” “prospective cohort studies,” and “systematic review.”

The Medical Subject Headings were conjoined with the text keywords in the search strategy using the Boolean operator “AND.” Initially, the elimination of replicated articles was conducted, followed by a thorough screening of the titles and abstracts of the remaining articles. Subsequently, all studies deemed eligible were obtained and subjected to a comprehensive review for the purpose of determining their inclusion or exclusion, in accordance with the inclusion and exclusion criteria outlined by the PRISMA guidelines.

Selection Process

Two authors conducted the literature search independently. A consensus was achieved through deliberation in the case of a disagreement. The data extraction process was carried out by 2 distinct authors in an independent manner. Subsequently, a comparative analysis was conducted on the results obtained from both authors’ extractions. In situations where there were conflicting viewpoints, a consensus was achieved through deliberation. The inclusion of a third author was contingent upon the specific circumstances.

Data Collection Process

A data extraction form that was computerized was created using Microsoft Excel. This form was then employed to document the essential details of the studies that were chosen for the meta-analysis. The aforementioned details encompassed the identity of the primary author, the year of publication, the study design, the geographical location of the study, the total sample size, the average age of the participants in years, the gender distribution of the participants, the type of surgical intervention, the duration of the post-op follow-up period in months, and the principal outcome of the studies that were incorporated.

Risk of Bias Assessment

The methodological validity of each study included in the meta-analysis was assessed using the Cochrane Risk of Bias tool.³² In the course of extracting data, chosen articles were evaluated and assigned a rating of “low,” “high,” or “some concern” based on their approach to generating random sequences, allocation concealment, participant and staff blinding, outcome assessment blinding, adequacy of outcome data, selective reporting, and other potential sources of bias. Subsequently, the Review Manager (RevMan) [Computer program]. Version 5.4. The Cochrane Collaboration, 2020³³ was employed to generate a summary and graph for the assessment of the risk of bias in terms of quality.

Reporting Bias Assessment

The utilization of Egger’s test,³⁴ Begg’s test,³⁵ and Deek’s funnel plot³⁶ was conducted through the utilization of MedCalc 64 bit version, flagship product of MedCalc Software Ltd³⁷ to investigate the presence of publication bias.

Synthesis Methods

A meta-analysis was conducted utilizing Comprehensive Meta-Analysis Version 4³⁸ to ascertain the average alteration in SNOT-22 across all studies. The mean change following surgery was determined using a random effects model with inverse variance weighting, in light of the anticipated heterogeneity. A forest plot and 95% confidence interval (CI) were also utilized. A mixed-effects meta-regression³⁹ was utilized to assess the influence of specific attributes, such as pre-op SNOT-22, mean change in SNOT-22 score, and average patient age, on the results of various studies. The statistical analysis involved inputting the mean and standard deviation or frequency of each variable in each study into a model to examine its impact on outcomes across studies. This was done by utilizing study-level data in the meta-regression and creating corresponding scatter plots.⁴⁰

Results

Literature Search Results

The PRISMA chart that was utilized for research selection is illustrated in Figure 1. A thorough exploration of digital repositories yielded a total of 1214 research investigations. A total of 734 studies were eliminated from consideration on the basis of duplicity and titles deemed to be irrelevant. Subsequently, a total of 480 studies underwent screening based on their title, abstract, and review. Subsequently, a total of 465 cases were eliminated from the study due to insufficient data for constructing a 2 × 2 table, absence of the outcome of interest, or noncompliance with the inclusion criteria. Fifteen pertinent articles were ultimately incorporated in the current meta-analysis. Table 1 displays the characteristics of all trials that were incorporated, including patient demographics. The studies incorporated in the analysis assessed the pre-op and post-op SNOT-22 test scores among patients with CRS who underwent ESS.

Figure 1.

PRISMA flowchart of selection of studies.

Table 1.

Characteristics of the Included Studies.

Study ID	Year	Study design	Country	Number of patients	Mean age of patients (years)	Gender (M/F)	Surgical intervention	Length of post-op follow-up (months)	Primary outcome
Afolabi et al¹⁶	2023	Prospective cohort study	Ilorin	40	34.95 ± 2.69	19/21	PESS	2	Change in SNOT-22 scores
Behiry et al¹⁷	2019	Prospective cohort study	Egypt	60	32.9 ± 5.3	34/26	PESS	24	Change in SNOT-22 scores
Chakrabarti et al¹⁸	2021	Prospective cohort study	India	75	36.5 ± 6.8	45/30	PESS	18	Change in SNOT-22 scores
DeConde et al¹⁹	2023	Prospective cohort study	USA	339	51 ± 15	151/363	PESS	30	Change in SNOT-22 scores
Gallo et al²⁰	2020	Prospective cohort study	Italy	457	47.4 ± 13.5	261/196	PESS	36	Change in SNOT-22 scores
Hopkins et al²¹	2009	Prospective cohort study	UK	1,459	45	779/680	PESS	60	Change in SNOT-22 scores
Johnson et al²²	2011	Prospective cohort study	Sweden	207	48	122/85	PESS	12	Change in SNOT-22 scores
Krishnaswamy et al²³	2019	Prospective cohort study	India	51	45	34/17	PESS	12	Change in SNOT-22 scores
Laababsi et al²⁴	2019	Prospective cohort study	Morocco	66	38.76 ± 14.17	26/19	PESS	24	Change in SNOT-22 scores
Mascarenhas et al²⁵	2013	Prospective cohort study	Brazil	38	50.59	7/10	PESS	24	Change in SNOT-22 scores
Santhaiah et al²⁶	2023	Prospective cohort study	India	55	54	43/12	PESS	12	Change in SNOT-22 scores
Simmonds et al²⁷	2022	Prospective cohort study	USA	925	44	536/389	PESS	60	Change in SNOT-22 scores
Sharma et al²⁸	2023	Prospective cohort study	India	75	50	45/30	PESS	3	Change in SNOT-22 scores
Rudmik et al²⁹	2016	Prospective cohort study	USA	668	52 ± 13.5	380/288	PESS	60	Change in SNOT-22 scores
Verma et al³⁰	2022	Prospective cohort study	India	40	50	25/15	PESS	6	Change in SNOT-22 scores

Abbreviation: PESS, Primary Endoscopic Sinus Surgery; change in SNOT-22 scores, difference in mean value of pre- and post-op SNOT-22 score.

Risk of Bias Assessment and Publication Bias

Table 2 displays the assessment of the quality of the studies that were included. Figure 2 provides a concise overview of the potential for bias, while Figure 3 presents a graphical representation of the risk of bias. Out of the 15 studies that were included, 8 were found to have a low risk of bias, while 4 studies were identified to have a moderate risk of bias due to confounding. The 3 studies incorporated in the analysis exhibit a high risk of bias stemming from the measurement of the exposure and potential bias resulting from postexposure interventions. The funnel plot presented in Figure 4 suggests a low likelihood of publication bias, as evidenced by the nonsignificant p values of 0.279 for Begg’s test and 0.467 for Egger’s test.

Table 2.

Risk Assessment of the Included Studies.

Study ID and year	Afolabi et al¹⁶	Behiry et al¹⁷	Chakrabarti et al¹⁸	DeConde et al¹⁹	Gallo et al²⁰	Johnson et al²¹	Hopkins et al²²	Krishnaswamy et al²³	Laababsi et al²⁴	Mascarenhas et al²⁵	Santhaiah et al²⁶	Simmonds et al²⁷	Sharma et al²⁸	Rudmik et al²⁹	Verma et al³⁰
Did the study avoid inappropriate exclusions?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Did all patients receive the same reference standard?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Were all patients included in the analysis?	N	N	N	N	N	N	N	N	N	N	N	N	N	N	N
Was the sample frame appropriate to address the target population?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Were study participants sampled in an appropriate way?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Were the study subjects and the setting described in detail?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Were valid methods used for the identification of the condition?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y
Was the condition measured in a standard, reliable way for all participants?	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y	Y

Figure 2.

Risk of bias summary.

Figure 3.

Risk of bias graph.

Figure 4.

Funnel plot.

Meta-analysis Results

The meta-analysis considered various prospective cohort studies and found that all of them reported a significant statistical difference in the average SNOT-22 scores between the pre-op and post-op periods (P < .05). The magnitude of this difference ranged from 5.1 to 55.4. There was a statistically significant alteration in the average SNOT-22 score across all studies, with a mean difference of 26.02 (95% CI: 12.83-38.60). The findings of individual studies and summary measures are illustrated in Figure 5, as evidenced by the forest plot. The data indicate that 9 studies exhibited a mean change in SNOT-22 and a 95% CI that was greater than or equal to 26.02 (with a range of 12.83-38.60). Conversely, 6 studies demonstrated a mean change and a 95% CI that was less than or equal to the mean of the study. Based on the results of the analysis, it can be inferred that the outcomes of the majority of the studies, specifically 9 out of 15, exhibited a 95% CI that intersected with the mean summary change value of 26.02. As a result, it may be appropriate to classify these outcomes as “good” rather than “fair.” Moreover, there was no notable distinction observed between investigations that utilized the conventional diagnostic criteria for CRS and those that implemented alternative criteria. A random effects model was employed due to the high heterogeneity observed in the study, with an I² value of 87.37%.

Figure 5.

Forest plot for difference in mean value of SNOT-22 score in the included studies.

Across Study Findings (Meta-regression)

The study employed a univariate meta-regression analysis to examine the correlation between patient-specific characteristics and the average alteration in SNOT-22 scores following ESS across the studies that were incorporated. Table 3 displays the primary outcome results, which include the mean change in SNOT-22 score and its corresponding p value. Meanwhile, Figure 6 presents scatter plots that depict the correlation between various study variables, such as the mean change in SNOT-22 score, pre-op SNOT-22 score, mean age of patients, and length of follow-up period. No observable impact was noted on the individual. Based on a stepwise multivariate analysis, it was found that studies with a higher average age and average pre-op SNOT-22 scores exhibited more significant changes in SNOT-22 scores after undergoing ESS. Conversely, studies with a longer average follow-up duration showed less significant changes in SNOT-22 scores. Therefore, the SNOT-22 score prior to surgery, average age of the patients, and duration of the follow-up period remained statistically significant based on the forward, stepwise multivariate modeling.

Table 3.

Statistical Summary of the Primary Outcome: The Difference in Mean Values of Pre-OP and Post-OP SNOT-22 Scores.

Study et al	Mean change in SNOT-22 score	LL (lower limit)	UL (upper limit)	P value
Afolabi	31.73	22	43	.0002
Behiry	5.1	1.7	8.4	.001
Chakrabarti et al	11.9	−0.1	23.9	.04
DeConde et al	28.48	7.48	49.96	.001
Gallo et al	22.9	5	40.8	.009
Johnson et al	26	10	42	.0001
Hopkins et al	28.2	5.8	50.6	.04
Krishnaswamy et al	55.4	41.4	67.7	.03
Laababsi et al	23.02	14.12	32.01	.0001
Mascarenhas et al	32.34	9.3	55.36	.001
Santhaiah et al	20.36	10.69	30.03	.0001
Simmonds et al	25.8	24.78	26.88	.0001
Sharma et al	30	15	35	.0001
Rudmik et al	34.44	15.44	53.74	.048
Verma et al	14.58	9.9	19.7	.01

Figure 6.

Univariate meta-regression scatter plots for length of follow-up period, Pre-OP SNOT-22 score and mean age.

Discussion

CRS is defined as the persistent inflammation of the paranasal sinuses and nasal channel linings for a duration of 12 weeks or more. This condition encompasses a varied range of illnesses that exhibit similar pathologic and clinical features.⁴¹ Patients diagnosed with CRS are evaluated through the utilization of the SNOT-22, a self-administered assessment tool that has been validated for this purpose. A total of 22 items are assessed on a scale ranging from 0, indicating the absence of any issue, to 5, indicating the most severe symptom imaginable. The SNOT-22 tool is utilized to assess symptoms related to CRS, as well as the impact of the condition on productivity, sleep quality, and social and emotional well-being. This has been documented in previous studies.^42,43 SNOT-22 data can be gathered by surgeons both pre- and post-op from patients with CRS. To assess their advancement, a benchmark will be required.⁴⁴ The task of identifying appropriate reference points from a multitude of published studies is challenging owing to their heterogeneity. Therefore, a comprehensive synthesis of all the published research on anticipated fluctuations in SNOT-22 is superior to any individual study. The utilization of summary mean and 95% CI would enable healthcare providers to make comparisons between their respective datasets. The attainment of results within the anticipated range installs a sense of assurance, whereas outcomes that fall below this threshold may necessitate further investigation and enhancements in quality.⁴⁵

The regression model has the ability to account for baseline characteristics within a surgeon’s practice, including pre-op SNOT-22, mean age of patients, and follow-up time. These factors have been observed to impact the published outcomes across various studies.⁴⁶ The systematic review and meta-analysis conducted by several researchers^47-49 pertaining to the assessment of SNOT-22 outcomes in patients with CRS who underwent EES have provided summary metrics. These metrics serve as a preliminary reference point based on the latest available data. However, it is important to note that they are not considered to be the most ideal metrics. The statistically significant summary mean (95% CI) of the pre- and post-op changes in the mean SNOT-22 scores of patients with CRS and a P value less than .05 in our study can be utilized as a point of reference for comparative purposes among other studies.

Nonetheless, the data resulting from the integration of all published studies may be subject to various biases. It is plausible that the studies that have been published may have emanated from institutions with more extensive expertise and superior proficiency than initially expected. It is expected that all service providers adhere to certain standards. Research endeavors are prone to emanate from academic institutions, which may result in the studied cohorts not being representative of the societal standards. Alternatively, centers that exhibit substandard outcomes may exhibit a reduced propensity to disseminate their findings, thereby exacerbating the bias in the results. As refinements are made to procedures, criteria are modified, and post-op therapies are enhanced, it is expected that outcomes will evolve over time. The existing body of literature may not necessarily be indicative of this fact.

Limitations

Several constraints must be considered within the scope of this inquiry. The findings are constrained due to the scarcity of studies, amounting to only 15, that exhibit moderate to high degrees of heterogeneity. This is despite the utilization of the recommended level of scientific rigor in the analysis. Secondly, the study utilized aggregated data rather than individual participant data. The inclusion criteria for patients with CRS and the duration of follow-up varied slightly among the studies, potentially leading to some level of internal heterogeneity. This was the situation as the trials exhibited minor variations among them. Thirdly, there was a discernible variation in the precise delineation of primary outcomes among the numerous studies that were included in the analysis. Lastly, it is noteworthy that the search was restricted to publications written in English, which could have potentially introduced some degree of bias in the selection of articles for presentation.

Conclusion

The SNOT-22 has been found to exhibit a significant enhancement in the QOL outcomes of sinus surgery following an ESS. The extent of alteration seems to exhibit significant heterogeneity across the entire body of literature, and this heterogeneity seems to be impacted by several factors, such as the pre-op SNOT-22 score, the average age of the subjects, and the length of the monitoring period. The results of this study offer both a single numerical value and a spectrum of anticipated modifications following surgical intervention. These outcomes can be utilized to advise initiatives aimed at improving the standard of care. Furthermore, administering the SNOT-22 to patients with CRS before undergoing surgical interventions may assist in educating patients regarding their anticipated results, although this is subject to personal interpretation. Recent preliminary research suggests that utilizing a combination of SNOT-22 scores and tissue histopathology may serve as a novel approach for forecasting treatment outcomes among patients with CRS. The precision and accuracy of forthcoming analyses are expected to improve due to endeavors aimed at furnishing unbiased data and patient-level metrics encompassing a broad spectrum of patients and providers.

Footnotes

Acknowledgements

None.

Author Contributions

YF and DL: Conceptualized and designed the study, analyzed data and drafting of the article; WH and ZW: Collected the data and helped in data analysis; YZ: Proofreading and final editing along with guarantor of the article. All authors read and approved the final version of the article.

Consent to participate statement

N/A

Data Availability Statement

All data generated or analyzed during this study are included in this article. Further enquiries can be directed to the corresponding author.

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.

Statement of Ethics

An ethics statement is not applicable because this study is based exclusively on published literature.

Study approval statement

N/A

ORCID iD

Yue Zhang

References

Bachert

Marple

Schlosser

, et al. Adult chronic rhinosinusitis. Nat Rev Dis Primers. 2020 29;6(1):86. doi:10.1038/s41572-020-00218-1

Halawi

Smith

Chandra

. Chronic rhinosinusitis: epidemiology and cost. Allergy Asthma Proc 2013;34(4):328-334. doi:10.2500/aap.2013.34.3675

Lam

Schleimer

Kern

. The etiology and pathogenesis of chronic rhinosinusitis: a review of current hypotheses. Curr Allergy Asthma Rep. 2015;15(7):41. doi:10.1007/s11882-015-0540-2

Hoehle

Phillips

Bergmark

, et al. Symptoms of chronic rhinosinusitis differentially impact general health-related quality of life. Rhinology. 2016;54(4):316-322. doi:10.4193/Rhino16.211

Nyaiteera

Nakku

Nakasagga

, et al. The burden of chronic rhinosinusitis and its effect on quality of life among patients re-attending an otolaryngology clinic in south western Uganda. BMC Ear Nose Throat Disord. 2018;18:10. doi:10.1186/s12901-018-0058-z

Ghogomu

Kern

. Chronic rhinosinusitis: the rationale for current treatments. Expert Rev Clin Immunol. 2017;13(3):259-270. doi:10.1080/1744666X.2016.1220833.

Ragab

Lund

Scadding

. Evaluation of the medical and surgical treatment of chronic rhinosinusitis: a prospective, randomised, controlled trial. Laryngoscope. 2004;114(5):923-30. doi:10.1097/00005537-200405000-00027

Anne

Sreedharan

Dosemane

, et al. Predictors of surgical outcomes after functional endoscopic sinus surgery in chronic rhinosinusitis. Indian J Otolaryngol Head Neck Surg. 2022;74(Suppl. 2):835-841. doi:10.1007/s12070-020-01855-4

Singla

Singh

, et al. Is sino-nasal outcome test-22 reliable for guiding chronic rhinosinusitis patients for endoscopic sinus surgery? Niger J Clin Pract. 2018;21(9):1228-1233. doi:10.4103/njcp.njcp_429_17

10.

Kennedy

Hubbard

Huyett

, et al. Sino-nasal outcome test (SNOT-22): a predictor of postsurgical improvement in patients with chronic sinusitis. Ann Allergy Asthma Immunol 2013;111(4):246-251.e2. doi:10.1016/j.anai.2013.06.033

11.

Gray

Phillips

Hoehle

, et al. The 22-item sino-nasal outcome test accurately reflects patient-reported control of chronic rhinosinusitis symptomatology. Int Forum Allergy Rhinol. 2017;7(10):945-951. doi:10.1002/alr.21992

12.

Liu

Weitzel

, et al. The predictive utility of the 22-item sino-nasal outcome test (SNOT-22): a scoping review. Int Forum Allergy Rhinol. 2022;12(1):83-102. doi:10.1002/alr.22888

13.

Riedl

Dejaco

Steinbichler

, et al. Assessment of health-related quality-of-life in patients with chronic Rhinosinusitis – Validation of the German Sino-Nasal Outcome Test-22 (German-SNOT-22). J Psychosom Res 2021;140:110316. doi:10.1016/j.jpsychores.2020.110316

14.

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(12):1140-1148. doi:10.1002/alr.22025

15.

Albrecht

Beule

Hildenbrand

, et al. Cross-cultural adaptation and validation of the 22-item sinonasal outcome test (SNOT-22) in German-speaking patients: a prospective, multicenter cohort study. Eur Arch Otorhinolaryngol. 2022;279(5):2433-2439. doi:10.1007/s00405-021-07019-6

16.

Afolabi

Uche-Okonkwo

Shittu

, et al. Evaluation of quality of life using Sinonasal Outcome Test-22 among patients with chronic rhinosinusitis postendoscopic sinus surgery: a preliminary report. BLDE Univ J Health Sci. 2022;7:245-251

17.

Behiry

Elshazly

Abdel-Shafy

Hussein

. Evaluation of quality of life after Functional Endoscopic Sinus Surgery (FESS) in chronic rhinosinusitis patients in Menoufia Governorate. Egypt J Ear Nose Throat Allied Sci 2019;20(3):131-136. doi:10.21608/ejentas.2019.12297.1106

18.

Chakrabarti

Tamang

Hembrom

, et al. An outcome analysis of endoscopic sinus surgery in chronic sinusitis with chronic rhinitis non-responsive to medical therapy. BJOHNS 2022;29(3):244-250.

19.

DeConde

Bodner

Mace

Smith

. Response shift in quality of life after endoscopic sinus surgery for chronic rhinosinusitis. JAMA Otolaryngol Head Neck Surg. 2014;140(8):712-719. doi:10.1001/jamaoto.2014.1045

20.

Gallo

Russo

Mozzanica

, et al. Prognostic value of the Sinonasal Outcome Test 22 (SNOT-22) in chronic rhinosinusitis. Acta Otorhinolaryngol Ital. 2020;40(2):113-121. doi:10.14639/0392-100X-N0364

21.

Hopkins

Slack

Lund

Brown

Copley

Browne

. Long-term outcomes from the English national comparative audit of surgery for nasal polyposis and chronic rhinosinusitis. Laryngoscope 2009;119(12):2459-2465. doi:10.1002/lary.20653

22.

Sahlstrand

Johnson P

Ohlsson

von Buchwald

Jannert

Ahlner-Elmqvist

. A multicentre study on quality of life and absenteeism in patients with CRS referred for endoscopic surgery. Rhinology 2011;49(4):420-428. doi:10.4193/Rhin

23.

Krishnaswami

Velayutham

Pruthivirajan

Murugesan

Vellikkannu

. Evaluation of pre-operative sino-nasal outcome test- 22 scores as a predictor of outcome in patients undergoing functional endoscopic sinus surgery for chronic rhinosinusitis. Int J Otorhinolaryngology Head Neck Surg 2019; 5:876-882.

24.

Laababsi

Abdulhakeem

Bushra

Elkrimi

, et al. Quality of life outcomes of patients with chronic rhinosinusitis after functional endoscopic sinus surgery, prospective cohort study. Ann Med Surg (Lond). 2019;40:9-13. doi: 10.1016/j.amsu.2019.03.001

25.

Mascarenhas

da Fonseca

Chen

, et al. Long-term outcomes of endoscopic sinus surgery for chronic rhinosinusitis with and without nasal polyps. Braz J Otorhinolaryngol. 2013;79(3):306-311. doi:10.5935/1808-8694.20130055

26.

Santhaiah

Kameswari

Kornepati

. A study on evaluation of sino-nasal outcome test-22 scores in chronic rhinosinusitis patients undergoing functional endoscopic sinus surgery in a tertiary care centre. Int J Otorhinolaryngol Head Neck Surg 2023;9:252-255

27.

Simmonds

Paz-Lansberg

Scangas

Metson

. Endoscopic sinus surgery for chronic rhinosinusitis: 22-item Sino-Nasal Outcome Test 5-year results. Int Forum Allergy Rhinol. 2022;12(3):257-265. doi:10.1002/alr.22886.

28.

Sharma

Raghuwanshi

Gupta

, et al. Snot-22 a Predictive and assessment tool for subjective improvement after fess in patients of chronic rhinosinusitis. Indian J Otolaryngol Head Neck Surg 2023;75(Suppl. 1): 1062-1068. doi:10.1007/s12070-023-03582-y

29.

Rudmik

Soler

Hopkins

. Using postoperative SNOT-22 to help predict the probability of revision sinus surgery. Rhinology. 2016;54(2):111-116. doi:10.4193/Rhino15.284.

30.

Verma

Rawat

Aseri

Verma

Singh

. A prospective longitudinal study of clinical outcome and quality of life assessment in patients with chronic rhinosinusitis after functional endoscopic sinus surgery using sino nasal outcome test-22. Indian J Otolaryngol Head Neck Surg 2022;74(Suppl. 2):792-799. doi:10.1007/s12070-020-01847-4

31.

Page

McKenzie

Bossuyt

, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. doi:10.1136/bmj.n71.

32.

Higgins

Altman

Gøtzsche

, et al; Cochrane Bias Methods Group; Cochrane Statistical Methods Group. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. doi:10.1136/bmj.d5928.

33.

Schmidt

Shokraneh

Steinhausen

, et al. Introducing RAPTOR: RevMan parsing tool for reviewers. Syst Rev. 2019;8(1):151. doi:10.1186/s13643-019-1070-0.

34.

Egger

Davey Smith

Schneider

Minder

. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315(7109):629-34. doi:10.1136/bmj.315.7109.629.

35.

Lin

Chu

Murad

, et al. Empirical comparison of publication bias tests in meta-analysis. J Gen Intern Med. 2018;33:1260–1267. doi:10.1007/s11606-018-4425-7

36.

Sterne

Egger

. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol. 2001;54(10):1046-1055. doi:10.1016/s0895-4356(01)00377-8

37.

Elovic

Pourmand

. MDCalc medical calculator app review. J Digit Imaging. 2019;32(5):682-684. doi:10.1007/s10278-019-00218-y

38.

Brüggemann

Rajguru

. Comprehensive meta-analysis (CMA) 3.0: a software review. J Market Anal 2022;10:425-429. doi:10.1057/s41270-022-00184-5

39.

Sera

Armstrong

Blangiardo

, et al. An extended mixed-effects framework for meta-analysis. Stat Med. 2019;38(29):5429-5444. doi:10.1002/sim.8362.

40.

Sainani

. The value of scatter plots. PM R. 2016;8(12):1213-1217.

41.

Hamilos

. Chronic rhinosinusitis: epidemiology and medical management. J Allergy Clin Immunol. 2011;128(4):693–707; quiz 708-9. doi:10.1016/j.jaci.2011.08.004

42.

Khan

Reaney

Guillemin

, et al. Development of sinonasal outcome test (SNOT-22) domains in chronic rhinosinusitis with nasal polyps. Laryngoscope 2022;132(5):933-941. doi:10.1002/lary.29766

43.

Dejaco

Riedl

Huber

, et al. The SNOT-22 factorial structure in European patients with chronic rhinosinusitis: new clinical insights. Eur Arch Otorhinolaryngol 2019;276:1355-1365. doi:10.1007/s00405-019-05320-z

44.

Saydy

Moubayed

Bussières

, et al. What is the optimal outcome after endoscopic sinus surgery in the treatment of chronic rhinosinusitis? A consultation of Canadian experts. J Otolaryngol – Head & Neck Surg 2021;50:36. doi:10.1186/s40463-021-00519-9

45.

Thorlund

Imberger

Johnston

, et al. Evolution of heterogeneity (I2) estimates and their 95% confidence intervals in large meta-analyses. PLoS One. 2012;7(7):e39471. doi:10.1371/journal.pone.0039471

46.

Masterson

Egro

Bewick

, et al. Quality-of-life outcomes after sinus surgery in allergic fungal rhinosinusitis versus nonfungal chronic rhinosinusitis. Am J Rhinol Allergy. 2016;30(2):e30-e35. doi:10.2500/ajra.2016.30.4280

47.

Soler

Jones

, et al. Systematic review and meta-analysis of snot-22 outcomes after surgery for chronic rhinosinusitis with nasal polyposis. Otolaryngology Head Neck Surg 2018;159(3):414-423. doi:10.1177/0194599818773065

48.

Soler

Jones

, et al. Sino-Nasal outcome test-22 outcomes after sinus surgery: a systematic review and meta-analysis. Laryngoscope. 2018;128(3):581-592. doi:10.1002/lary.27008

49.

Chi-Cauich

Castañeda-De León

. SNOT-22 test to evaluate clinical improvement in rhinosinusal surgery. Otorrinolaringología. 2021;66(2):104-109.

A Systematic Review and Meta-analysis of SNOT-22 Outcomes After Sinus Surgery

Abstract

Plain Language Summary

Keywords

Introduction

Materials and Methods

Eligibility Criteria

Information Sources

Search Strategy

Selection Process

Data Collection Process

Risk of Bias Assessment

Reporting Bias Assessment

Synthesis Methods

Results

Literature Search Results

Risk of Bias Assessment and Publication Bias

Meta-analysis Results

Across Study Findings (Meta-regression)

Discussion

Limitations

Conclusion

Footnotes

Acknowledgements

Author Contributions

Consent to participate statement

Data Availability Statement

Declaration of Conflicting Interests

Funding

Statement of Ethics

Study approval statement

ORCID iD

References