Model uses clinical variables, biomarkers to accurately predict nasal polyp recurrence
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A combined set of clinical and biological variables predicted polyp recurrence and severity among patients who have had endoscopic sinus surgery, according to a study published in The Journal of Allergy and Clinical Immunology.
These models may help clinicians determine which patients with chronic rhinosinusitis with nasal polyps may derive the greatest benefits from adjunctive therapies to prevent polyp recurrence, the researchers wrote.
“Endoscopic sinus surgery is a commonly recommended treatment for patients with CRSwNP. However, it is known that some patients will experience polyp regrowth after surgery,” Bruce K. Tan, MD, MS, associate professor in the department of otolaryngology - head and neck surgery and in the division of allergy and immunology of the department of medicine at Northwestern Medicine Feinberg School of Medicine, told Healio.
“Prior to this study, it was unclear what the implications of polyp regrowth were on patient symptoms and on overall disease burden. It was also unclear what clinical features or biomarkers were useful in predicting polyp recurrence,” Tan said.
The study involved 94 patients (median age, 49.5 years; 58.5% men) with CRSwNP who had endoscopic sinus surgery (ESS) with nasal polyp collection at Northwestern Memorial Hospital between 2012 and 2017.
At an average of 34.9 (± 11.3) months after ESS, these patients underwent CT scan and endoscopy and provided patient-reported outcome measures.
After ESS, patients’ modified Lund-Mackay (MLM) scores of radiographic severity improved 73.2%, from a median of 28 to 7.5, and Sinonasal Outcomes Test scores improved 58.1%, from a median of 43 to 18 (P < .0001 for both).
Endoscopies revealed polyp recurrence in 39.4% of these patients, which the researchers associated with worse SNOT-22 and Chronic Rhinosinusitis Patient-Reported Outcomes scores. These patients had a median total polyp score of 2 as well.
The researchers selected 11 clinical variables as candidates for their predictive model, including six comorbidities — aspirin-exacerbated respiratory disease, asthma, allergic rhinitis, prior ESS, steroid use and smoking at the time of ESS — two interoperative findings, pre-ESS MLM score, age and sex.
A least absolute shrinkage and selection operator regression analysis of these variables selected pre-ESS MLM and asthma as predictive factors for polyp recurrence, with an area under the curve (AUC) of 0.79 and Akaike information criterion (AIC) of 108.7.
Also, the researchers assessed 17 biomarkers including type 1 and 2 cytokines and proinflammatory chemokines and found that log-transformed eosinophil cationic protein (P < .01), anti-dsDNA IgG (P < .05) and IL-5 (P < .05) significantly predicted polyp recurrence, with an AUC of 0.78 and AIC of 113.6.
A combined model including log eosinophil cationic protein, log anti-dsDNA IgG, IL-5, pre-ESS MLM and asthma was more accurate than the clinical and biomarker models individually, with an AUC of 0.89 and an AIC of 94.1.
“We were interested in a phenomenon of autoantibody production in nasal polyps that we had published a number of years ago. In this study, we found that the level of an autoantibody helped supplement a set of other biomarkers and clinical predictors for improving the accuracy of predicting surgical outcomes,” Tan said.
It had been known that type 2 inflammation had implications on surgical outcomes, Tan continued, but it remained unclear which aspects of type 2 inflammation were most salient.
“Together, we found three biomarkers and two clinical features that were observable at the time of their surgery were optimal for creating a prediction model of which patients subsequently experienced recurrence,” Tan said.
Overall, the researchers concluded that tissue inflammation should be considered together with individual patient characteristics for optimal accuracy so clinicians can predict which patients will experience polyp recurrence and provide treatment accordingly.
“The results of this study help point doctors to the clinical predictors that are most pertinent for predicting their outcomes from sinus surgery,” Tan said.
“However, it also points out that their clinical predictors are only moderately good at predicting long-term outcomes, and this study identifies candidate biomarkers that could improve the accuracy of outcome prediction. The field needs to develop and validate these measures further to improve predictions of outcomes from ESS,” he said.
The ongoing study is continuing to recruit patients.
“The ability of this study to accrue patients was impacted by the onset of the COVID-19 pandemic, so we studied our outcomes up to the beginning of the pandemic. We continue to collect outcomes of subsequent patients that we hope could form a validation set for the findings of the published study,” Tan said.
The researchers said they also would like to expand their studies to evaluate other unstudied biomarkers that may help predict outcomes.
“We would like to collect more outcomes from sinus surgery to independently validate the findings of this study,” Tan said. “We want to better understand this phenomenon of local autoantibody production that seems to negatively impact outcomes of endoscopic sinus surgery.”
For more information:
Bruce K. Tan, MD, MS, can be reached at btan@nm.org.