Material and Methods
This
is a retrospective and nonconcurrent cohort study. The study was
approved by the local Ethics Committee ([2017]164).
According
to the European Position Paper on Rhinosinusitis and Nasal Polyps 2012
(EPOS2012) guidelines, patients who satisfied the diagnostic criteria of
chronic rhinosinusitis with nasal polyps were included in the study
fromA, B, C hospital. All patients received FESS between January 2018
and December 2020 and were periodically reassessed during their routine
outpatient visits following the surgery. These patients were initially
treated with AMT i.e., nasal steroids (drops/sprays/rinses), saline
rinses, educated regarding technique, oral corticosteroid short-course
(OCS), and two-course antibiotics before surgery.
Patients
were instructed to use topical corticosteroids-budesonide nasal spray
(256ug/day for 6 months), and intranasal budesonide suspension (1mg/day
for 4 weeks) after surgery. They were reassessed periodically at their
routine outpatient visits at 1 to 3 months after surgery then once in 3
months until 1 year follows up. During the assessment in the follow-up
visits, if their symptoms or endoscopic signs persisted, they received
new AMT i.e., nasal steroids (drops/spray/rinses), saline rinses,
education regarding technique, OCS, and optional two-course antibiotics.
The symptoms, endoscopic scores, and modified treatment (if any) were
recorded by clinicians after 1 year.
Items
recorded from the enrolled patients were as following:
- Nasal symptoms
- Lund and Kennedy score recorded by nasal endoscopy findings
- Comorbidities: smoking habit, asthma (based on the spirometry and
clinical parameters)
- Respiratory allergens
- Peripheral blood eosinophil count before the initiation of oral
corticosteroids. More than 0.3X109/L was considered
as high blood eosinophilia in CRS
Data collection
Patients
were divided into 2 groups of controlled (included partly controlled)
and uncontrolled CRS, based on the disease control criteria of EPOS2020.
Patients were followed up for 1 year after surgery, until the end of the
study period (30th December 2020). Time-to-event was defined as the time
starting from surgery till the 12th month post-operatively. According to
the EPOS2020, the control criteria of the CRS can be divided into
symptoms, nasal endoscopy, the need for recuse treatment. Symptom
substituted by ‘VAS (Visual Analogue Scale)< 5’, and
‘present/impaired’ by ‘VAS ≥ 5. Furthermore, the detailed symptoms
related to CRS are included in supplement table S1. The evaluation
endpoint was 12th month post-operatively.
Nomogram development
The nomogram model was formulated by the results of multivariate
analysis.
Univariate
analysis with a significant difference at P-value(<0.05) between all variables was included in the multivariate
analysis. The P-value <0.05 in multivariate analysis
was also included as the prognostic factor in the nomogram.
AR
and PBEC were statistically significant in univariate analysis for 1
year disease control but not significant difference in multivariate
analysis for 1 year diease control.
However,
AR and PBEC have long been recognized to determine the prognosis of CRS.
AR
and PBEC were also included in the nomogram for the current study, since
excluding these covariates would have over-inflated the effects of the
remaining factors and decrease the predictive power of our model. The
Cox proportional hazard model was used to produce nomograms for
predicting the risk of the uncontrolled incident after the
surgery.
A score based on regression coefficients was assigned to these factors.
Model evaluation
The nomogram’s forecast performance was evaluated by the receiver
operating characteristic (ROC), the area under curve (AUC) for both
training and validation cohort. In a logistic regression model, the
value of AUC is the same as that yielded by the concordance index
(c-index), with values ranging from 0.5 (no predictive value) to 1.0
(complete discrimination).
A
larger AUC value represents a more accurate prediction of the
uncontrolled disease possibility.
The
agreement between the predicted uncontrolled incident and the observed
uncontrolled incident after bias correction was quantified by the
calibration curves of the nomogram for determining the uncontrolled
incident rate. Decision curve analysis (DCA) was also carried out to
compare the potential net benefit of the predictive models.
Statistical analysis
We compared the patient pathologic characteristics and demographic
profile between training and validation cohort by using Fisher’s exact
tests and chi-squared tests.
Multivariate
logistic regression analysis was used to distinguish the independent
risk factors associated with uncontrolled disease. Nomogram development
was carried out by using the library “rms” in R for MACOS. All
statistical analyses were conducted by the R software version 4.0.2 (R
Foundation for Statistical Computing, Vienna, Austria;
www.R-project.org). The p values<0.05 were considered
statistically significant.