Predictive factors to differentiate between allergic and nonallergic rhinitis in children

Allergic rhinitis facts from an Irish pediatric population

Objective

Assessing the main allergens in the pediatric population from the largest urban area in the country.

Methods

Clinical letters of patients referred with possible allergic rhinitis (AR) were retrospectively reviewed over the past 5 years.

Results

Five hundred and fifty-five patients were included. Males suffer twice as often with AR than females and have high titers of allergens. House dust mites (44.7%) and grass pollen (29%) were the main allergens in our area, with 48% of patients sensitized to both allergens. Half of the patients had the diagnosis of AR confirmed with positive allergen-specific tests. For the other half, the diagnosis was based on a clinical assessment performed by a pediatric otolaryngologist.

Conclusions

Half of suspected AR children have environmental allergen sensitivity confirmed by testing, and a large number had a clinical diagnosis of AR after an otolaryngology consultation. Our findings can help clinicians to initiate AR treatment considering the most problematic allergens in the area.

Developing and validating clinical models to identify candidates for allergic rhinitis pre-exposure prophylaxis

PURPOSE

Few risk-forecasting models of allergic rhinitis (AR) exist that may aid AR pre-exposure prophylaxis (PrEP) in clinical practice. Therefore, this study aimed to develop and validate an effective clinical model for identifying candidates for AR PrEP using a routine medical questionnaire.

METHODS

This study was conducted in 10 Chinese provinces with 13 medical centers (n = 877) between 2019 and 2021. Clinical characteristics and exposure history were collected via face-to-face interviews. Well-trained physicians diagnosed patients with AR based on skin prick test results and clinical performance. The least absolute shrinkage and selection operator model was used to identify potential risk factors for AR, and the logistic regression model was used to construct the risk-forecasting model. Predictive power and model reliability were assessed using area under the receiver operating characteristic curve and calibration curves, respectively.

RESULTS

This study diagnosed 625 patients with AR who had positive responses to at least one indoor or outdoor allergen and 460 to at least one outdoor pollen allergen. Two nomograms were established to identify two types of AR with various sensitization patterns. Both models had an area under curve of approximately 0.7 in the development and internal validation datasets. Additionally, our findings found good agreement for the calibration curves of both models.

CONCLUSION

Early identification of candidates for AR PrEP using routine medical information may improve the deployment of limited resources and effective health management. Our models showed good performance in predicting AR; therefore, they can serve as potential automatic screening tools to identify AR PrEP candidates.

Diagnostic performance of nasal cytology

PURPOSE

Nasal pathologies are characterized by a symptomatology that hardly allows to distinguish allergic rhinitis (AR), non-allergic rhinitis (NAR), and chronic rhinosinusitis (CRS). Nasal cytology (NC) has shown increasing importance in helping the clinician to differentiate the various phenotypes of rhinitis. NC allows us to evaluate nasal cellularity by distinguishing AR and various types of NAR. The objective of the study is to assess the diagnostic performance of the NC by evaluating its sensitivity, specificity, and predictive value.

METHODS

We recruited 387 patients with persistent rhinitis symptoms, and nasal cytology was performed. The rhinocytogram was obtained by reading for fields and the cellular count was made using quantitative and semi-quantitative grading together.

RESULTS

Two hundred and fifteen patients (55.5%; 38 had acute rhinitis, 24 acute sinusitis, 153 chronic rhinosinusitis) out of 387 referred nasal symptoms. Cytological specimen showed a mean of 94 ± 4% ciliated cells, 29 ± 0.2% mucinous cells, 16 ± 0.1% neutrophils, 11 ± 0.08% eosinophils, 4 ± 0.03 lymphocytes, 4 ± 0.03% mast cells, and 4 ± 0.01% other cells. NC was positive in 271 cases (70%). After revision of medical history, 153 patients (39%) were considered positive for NAR. Test sensibility was 100% (95% CI 97-100), specificity was 49.6% (95% CI 43-56%). Positive predictive value (PPV) was 56% (95% CI 50-62%), and negative predictive value (NPV) was 100% (95% CI 96-100%). The positive likelihood ratio was 1.98 (95% CI 1.75-2.25). Accuracy of the test was 69.5% (95% CI 64.6-74.0%).

CONCLUSION

Our data showed ability to identify the true-positive patients with NAR but a low ability to identify the true-negative patients, with a global accuracy of 69.5%.

Prevalence, comorbidities, diagnosis, and treatment of nonallergic rhinitis: real-world comparison with allergic rhinitis

Rhinitis is among the most common respiratory diseases in children. Nonallergic rhinitis, which involves nasal symptoms without evidence of systemic allergic inflammation or infection, is a heterogeneous entity with diverse manifestations and intensities. Nonallergic rhinitis accounts for 16%-89% of the chronic rhinitis cases, affecting 1%-50% (median 10%) of the total pediatric population. The clinical course of nonallergic rhinitis is generally rather mild and less likely to be associated with allergic comorbidities than allergic rhinitis. Here, we aimed to estimate the rate of coexisting comorbidities of nonallergic rhinitis. Nonallergic rhinitis is more prevalent during the first 2 years of life; however, its underestimation for children with atopic tendencies is likely due to low positive rates of specific allergic tests during early childhood. Local allergic rhinitis is a recently noted phenotype with rates similar to those in adults (median, 44%; range, 4%-67%), among patients previously diagnosed with nonallergic rhinitis. Idiopathic rhinitis, a subtype of nonallergic rhinitis, has been poorly studied in children, and its rates are known to be lower than those in adults. The prevalence of nonallergic rhinitis with eosinophilia syndrome is even lower. A correlation between nonallergic rhinitis and pollution has been suggested owing to the recent increase in nonallergic rhinitis rates in highly developing regions such as some Asian countries, but many aspects remain unknown. Conventional treatments include antihistamines, intranasal corticosteroids, and recent treatments include combination of intranasal corticosteroids with azelastin or decongestants. Here we review the prevalence, diagnosis, comorbidities, and treatment recommendations for nonallergic rhinitis versus allergic rhinitis in children.

Demographics and clinical features predictive of allergic versus non-allergic rhinitis in children aged 6-18 years: A single-center experience of 1535 patients

BACKGROUND

Chronic rhinitis (CR) is one of the most common causes accounting for lost-school days, absenteeism and resource utilization in pediatric patients. Distinction between common causes of CR, allergic (AR)and non-allergic rhinitis (NAR), based upon clinical features is critical, especially in primary care settings or facilities with lack of allergen sensitivity testing, as management strategies differ considerably. The current study elucidates clinical factors, particularly facial features associated with AR and NAR using a large cohort.

METHODS

In a retrospective cohort analysis of pediatric patients aged 6-18 years, we assessed patient demographics, clinical symptoms, and signs associated with allergic rhinitis using multivariable regression techniques.

RESULTS

Overall, 1490 patients (mean age: 10.11 ± 3.31 years; 48% female; 69% AR and 31% NAR) were included in the study. In multivariable regression analysis, major clinical features associated with AR were: sneezing (OR: 3.53; 95% CI: 2.35-5.32; p < 0.001), rhinorrhea (OR: 1.77; 95% CI: 1.18-2.66; p = 0.006), nasal itching (OR: 17.88; 95% CI: 11.92-26.83; p < 0.001), horizontal nasal crease (OR: 5.09; 95% CI: 1.29-20.01; p = 0.020) and conjunctivitis (OR: 4.66; 95% CI: 3.28-6.62; p < 0.001). On the contrary, we noted presence of Dennie-Morgan fold (OR: 1.67; 95% CI: 1.11-2.56; p = 0.014), moderate to severe persistent or intermittent symptoms to be likely associated with NAR than AR.

CONCLUSION

In pediatric patients presenting with symptoms of rhinitis, facial hallmarks serve as an adjunct to sensitivity testing in establishing a diagnosis as well as differentiating between NAR from AR, albeit individualized upon patient history and clinical features.

Non-allergic rhinitis in children: Epidemiological aspects, pathological features, diagnostic methodology and clinical management

Chronic rhinitis is a very common disease, as the prevalence in the general population resulted to be 40%. Allergic rhinitis has been considered to be the most frequent form of chronic rhinitis, as non-allergic rhinitis has been estimated to account for 25%. However, several evidences suggested that non-allergic rhinitis have been underrated, especially in children. In pediatrics, the diagnostic definition of non-allergic rhinitis has been often limited to the exclusion of an allergic sensitization. Actually, local allergic rhinitis has been often misdiagnosed as well as mixed rhinitis has not been recognized in most cases. Nasal cytology is a diagnostic procedure being suitable for routine clinical practice with children and could be a very useful tool to characterize and diagnose non-allergic rhinitis, providing important clues for epidemiological analysis and clinical management.

Neural Abnormalities in Nonallergic Rhinitis

Sensory nerve endings within the airway epithelial cells and the solitary chemoreceptor cells, synapsing with sensory nerves, respond to airborne irritants. Transient receptor potential (TRP) channels (A1 and V1 subtypes, specifically) on these nerve endings initiate local antidromic reflexes resulting in the release of neuropeptides such as substance P and calcitonin G-related peptides. These neuropeptides dilate epithelial submucosal blood vessels and may therefore increase transudation across these vessels resulting in submucosal edema, congestion, and rhinitis. Altered expression or activity of these TRP channels can therefore influence responsiveness to irritants. Besides these pathogenic mechanisms, additional mechanisms such as dysautonomia resulting in diminished sympathetic activity and comparative parasympathetic overactivity have also been suggested as a probable mechanism. Therapeutic effectiveness for this condition has been demonstrated through desensitization of TRPV1 channels with typical agonists such as capsaicin. Other agents effective in treating nonallergic rhinitis (NAR) such as azelastine have been demonstrated to exhibit TRPV1 channel activity through the modulation of Ca(2+) signaling on sensory neurons and in nasal epithelial cells. Roles of antimuscarinic agents such as tiotropium in NAR have been suggested by associations of muscarinic cholinergic receptors with TRPV1. The associations between these channels have also been suggested as mechanisms of airway hyperreactivity in asthma. The concept of the united airway disease hypothesis suggests a significant association between rhinitis and asthma. This concept is supported by the development of late-onset asthma in about 10-40 % of NAR patients who also exhibit a greater severity in their asthma. The factors and mechanisms associating NAR with nonallergic asthma are currently unknown. Nonetheless, free immunoglobulin light chains and microRNA alteration as mediators of these inflammatory conditions may play key roles in this association.

Characterization of Rhinitis According to the Asthma Status in Adults Using an Unsupervised Approach in the EGEA Study

Background

The classification of rhinitis in adults is missing in epidemiological studies.

Objective

To identify phenotypes of adult rhinitis using an unsupervised approach (data-driven) compared with a classical hypothesis-driven approach.

Methods

983 adults of the French Epidemiological Study on the Genetics and Environment of Asthma (EGEA) were studied. Self-reported symptoms related to rhinitis such as nasal symptoms, hay fever, sinusitis, conjunctivitis, and sensitivities to different triggers (dust, animals, hay/flowers, cold air…) were used. Allergic sensitization was defined by at least one positive skin prick test to 12 aeroallergens. Mixture model was used to cluster participants, independently in those without (Asthma-, n = 582) and with asthma (Asthma+, n = 401).

Results

Three clusters were identified in both groups: 1) Cluster A (55% in Asthma-, and 22% in Asthma+) mainly characterized by the absence of nasal symptoms, 2) Cluster B (23% in Asthma-, 36% in Asthma+) mainly characterized by nasal symptoms all over the year, sinusitis and a low prevalence of positive skin prick tests, and 3) Cluster C (22% in Asthma-, 42% in Asthma+) mainly characterized by a peak of nasal symptoms during spring, a high prevalence of positive skin prick tests and a high report of hay fever, allergic rhinitis and conjunctivitis. The highest rate of polysensitization (80%) was found in participants with comorbid asthma and allergic rhinitis.

Conclusion

This cluster analysis highlighted three clusters of rhinitis with similar characteristics than those known by clinicians but differing according to allergic sensitization, and this whatever the asthma status. These clusters could be easily rebuilt using a small number of variables.