Abstract
Background
Medical comorbidities are commonly encountered in chronic rhinosinusitis (CRS) and may impact both physical function and patient reported health-related quality-of-life (HRQOL). The functional comorbidity index (FCI) is designed to elucidate the role of comorbidities on functional prognosis. The objective of this study was to understand the impact of comorbidities known to impact physical function on baseline HRQOL using the FCI.
Methodology: Patients meeting diagnostic criteria for CRS were prospectively enrolled in a cross-sectional study. Responses from the Sinonasal Outcomes Test-22 (SNOT-22), a measure of patient HRQOL, as well as the Lund-Kennedy and Lund-Mackay scores were recorded at enrollment. FCI was calculated retrospectively using the electronic medical record. Information was collected and compared for patients without (CRSsNP) and with nasal polyps (CRSwNP) using chi-square and t-tests. Spearman’s correlations, followed by multivariate regression analysis, were used to assess the association between FCI and SNOT-22 scores.
Results
One hundred and three patients met inclusion criteria for analysis. There were no significant differences in age, gender, and SNOT-22 scores between patients with CRSsNP and those with CRSwNP. FCI was significantly and independently associated with worse SNOT-22 scores (P = .012). FCI did not correlate with endoscopy and computed tomography scores. The mean FCI for patients with CRSsNP and CRSwNP was 2.02 and 2.24, respectively, and did not differ significantly between the two cohorts (P = .565).
Conclusions
Major medical comorbidities known to affect physical function are associated with worse SNOT-22 scores in patients with CRS as measured by the FCI.
Keywords
Introduction
Individual medical comorbidities have been shown to negatively impact health-related quality-of-life (HRQOL) in chronic diseases, including asthma, gastroesophageal reflux disease (GERD), type II diabetes mellitus, and colorectal cancer.1–5 Various indices have been developed in an attempt to predict and develop prognostic models that allow health care practitioners to account for the impact of total medical comorbidities on patient outcomes. 6 A well-studied example is the Charlson Comorbidity Index, which has been used to demonstrate the influence of total medical comorbidities on disease mortality rates. 7 However, this index does not provide useful information about the impact of comorbidities on physical function in chronic diseases that do not portend mortality. 8
In order to address this deficiency, the Functional Comorbidity Index (FCI) was developed and validated in a patient population with acute respiratory distress syndrome (ARDS). Using the 36-Item Short Form Health Survey (SF-36), it was designed to incorporate major comorbidities with the greatest impact on physical function. Since its development, the FCI has been progressively validated in increasing numbers of other patient populations,9,10 including those with chronic rhinosinusitis (CRS).8,11,12 Given its focus on functional disability, it may be expected that the comorbidities included in this index have a significant negative impact onf HRQOL. However, the association with disease-specific HRQOL in this patient population has not yet been examined.
Thus, the primary objective of this study was to evaluate the impact of major functional medical comorbidities on patient reported HRQOL (i.e. Sino-Nasal Outcomes Test 22 (SNOT-22)] and objective measures of disease severity (i.e. Lund-Kennedy (LK) and Lund-Mackay (LM)] in CRS.
Materials and Methods
Institutional Review Board (IRB) approval was obtained at the University of Utah. Patients undergoing treatment of CRSsNP and CRSwNP were prospectively enrolled between 2013 and 2020. Inclusion criteria included a diagnosis of CRS as defined by the American Academy of Otolaryngology–Head and Neck Surgery (AAO-HNS). 13 Exclusion criteria included a comorbid diagnosis of primary ciliary dyskinesia, cystic fibrosis, and autoimmune related sinonasal disease.
Demographics
The following demographic information was collected for each patient: age, gender, polyp status, ethnicity, and urban vs rural living.
Functional Comorbidity Index
We examined the following 18 distinct comorbidities as a part of the FCI: arthritis, osteoperosis, asthma, chronic obstructive pulmonary disease (COPD)/ARDS, angina, congestive heart failure (CHF)/heart disease, heart attack, neurological disease, stroke/transient ischemic attack (TIA), diabetes mellitus I or II, peripheral vascular disease, upper gastrointestinal (GI) disease, depression, anxiety, visual impairment, hearing impairment, degenerative disc disease, obesity and/or body mass index (BMI) of > 30 kg/m2. These comorbidities have been shown to have greatest impact on physical function using the SF-36 and thus were selected for this study, as the objective of our investigation was understanding the impact of comorbidities causing functional impairment on SNOT-22 scores.8,11 Each comorbidity is assigned a score of “0” if not present or “1” if present.8,11 The maximum possible score is 18.8,11 Using comorbidities listed in the electronic medical record (EMR), score assignments were performed retrospectively and the FCI was calculated for each patient.
Measures of Disease Severity
Endoscopic examination (LK), computed tomography (CT) imaging (LM), and sinonasal HRQOL survey responses (SNOT-22) were obtained at enrollment. The SNOT-22 is a validated survey developed to evaluate symptom severity in CRS. 14 Individual item scores are measured using patient selected responses on a Likert scale, where higher scores indicate worse symptom severity and HRQOL (score range 0–110). The LM scoring system (range: 0 – 24) estimates opacification severity in the maxillary, ethmoidal, sphenoidal, ostiomeatal complex, and frontal sinus regions on computed tomography (CT) imaging. 15 The paranasal sinuses were evaluated bilaterally using rigid, 30-degree endoscopes (SCB Xenon 175; Karl Storz, Tuttlingen, Germany). Endoscopic exams were staged by the enrolling physician using the bilateral LK scoring system (score range, 0 to 20), which quantifies pathologic states within the paranasal sinuses including the severity of polyposis, discharge, edema, scarring, and crusting on a Likert scale. 16 Higher scores on both staging systems reflect worse disease severity. Given that the FCI was collected retrospectively, clinicians were blinded to FCI scores at time of clinician-based scoring of the LK and LM scales.
Statistical Analysis
Data was independently reviewed for accuracy through a standardized chart review process and tabulated; care was taken to cross-reference medical diagnoses with healthcare provider notes to ensure diagnoses were accurate and current. Chi-square tests were used to analyze categorical variables and t-tests were used to analyze continuous variables. Spearman’s correlations and Chi-Square/Fisher’s Exact Test were used to perform a univariate analysis of the relationship between clinical co-factors, individual comorbidities, and SNOT-22 scores. Multivariate analysis was performed to determine the effect of FCI on SNOT-22 scores. The following variables were included in the multivariate analysis as they were significant on univariate analysis in their relationship to the SNOT-22: age, depression, FCI, nasal polyps and DDD. Given the multiple statistical comparisons made when analyzing the relationship between individual comorbidities and various aspects of SNOT-22 scores, we have performed a Bonferroni correction method for multiple comparisons. The threshold for significance was set at P < .05.
Results
Demographics
One hundred and three patients (57 CRSsNP and 46 CRSwNP) were included in the final analysis. There was no significant difference in age, gender, and SNOT-22 scores between patients with CRSsNP and those with CRSwNP, althought patients with CRSwNP had a worse LK (P < .001), LM (P < .001), and rhinologic subdomain symptoms (P = .007) (Table 1).
Demographic Information Broken Down by Diagnosis.
*P < .05; **P < .001. [Brackets] indicate mean values.
Functional Comorbidity Index
The mean FCI was 2.12 among all CRS patients (Table 2). Mean FCI in CRSsNP and CRSwNP was 2.02 and 2.24, respectively. FCI did not differ significantly between patients with CRSsNP vs CRSwNP (P = .57) (Table 2). The most common individual comorbidities were asthma (42%), depression (26%), upper gastrointestinal (GI) disease (18%), obesity (18%), neurological disease (18%), visual impairment (16%), peripheral vascular disease (16%), and anxiety (15%). Asthma was more prevalent in patients with CRSwNP (52%) as compared to patients with CRSsNP (33%) (P = .05).
Functional Comorbidity Index.
COPD, chronic obstructive pulmonary disease; ARDS, acute respiratory distress syndrome; CHF, congestive heart failure; TIA, transient ischemic attack; GI, gastrointestinal, BMI, body mass index.
The Impact of FCI on SNOT-22
Univariate analysis demonstrated a significant association between FCI and worse SNOT-22 scores among all patients (P = .01) (Table 3). FCI further significantly correlated with the psychological (P < .001) and sleep dysfunction (P = .045) sub-domain of the SNOT-22 (Table 3). Moreover, after Bonferonni correction for multiple comparisions, only depression and arthritis were significantly associated with worse SNOT-22 subdomain (psychological and extranasal, respectively) scores (Table 4). No individual comorbidity was associated with overall worse baseline SNOT-22 total scores. Multivariate regression analysis confirmed that patients with more comorbidites (i.e. greater FCI) (P = .004, 95% CI 0.657, 5.245), as well as younger patients (P = .001, 95% CI −0.627, 0.164) had worse SNOT-22 scores (Table 5).
Univariate Analysis of FCI and Clinical Co-Factors.
*P < .05; **P < .001.
Univariate Analysis of Individual Comorbidities and SNOT-22.
Spearman’s R Correlation Coefficients with 95% Confidence Interval, Bonferroni-corrected, ** P < .001. COPD, chronic obstructive pulmonary disease; ARDS, acute respiratory distress syndrome; CHF, congestive heart failure; TIA, transient ischemic attack; GI, gastrointestinal, BMI, body mass index.
Multivariate Regression Analysis: Clinical Measures of SNOT-22.
FCI, functional comorbidity index; DDD, degenerative disc disease.
Discussion
Patient reported outcome measures, along with objective measures of disease, are essential tools in the assessment of treatment success in CRS. Despite the fact that patients rarely present with a single problem in isolation from other medical conditions, sinonasal disease-specific HRQOL instruments are limited in their consideration of patient medical comorbidities. Several prior investigations have examined the association between individual comorbidities, such as anxiety and obesity, and HRQOL using the SNOT-22.17,18 These investigations suggest certain medical comorbidities play an important role in understanding patient reported outcome measures in CRS.17,18 Moreover, investigators in the orthopedic literature have demonstrated that patients with a greater number of medical comorbidities have an overall worse disease-specific QOL compared to patients with less comorbidities. 19 No study has examined the cumulative effect of the total number of comorbidities known to impact physical function on HRQOL among patients with CRS, which was the goal of our study. Nevertheless, given its focus on functional disability, it may be expected that the FCI may have a significant negative impact on HRQOL and thus the objective of our investigation was to determine whether this was true. Indeed, our data demonstrated that patients with a greater number of comorbidities associated with functional impairment, as indicated by a higher FCI score, had worse baseline HRQOL in this cohort.
Of note, although FCI did correlate with SNOT-22, a subjective measure of disease severity, it did not correlate with objective measures of sinonasal disease, such as LK and LM. This is not surprising, as FCI represents non-sinonasal comorbidities, and although there is some data to indicate that patients with asthma may have worse sinonasal disease (i.e. greater association with nasal polyposis and need for revision surgery), 20 this does not hold true of the remaining comorbidities comprising the FCI. Conversely, it is possible to understand how having multiple physically debilitating comorbidities can impact subjective interpretation of disease severity (i.e., SNOT-22).
The present study also categorized medical comorbidities causing known functional disability in patients with CRS. Several of these comorbidities have previously been reported in patients with CRS, including asthma, depression, anxiety, and upper GI disease (Table 2), while other functional impairments have never been examined in this cohort. Unsurprisingly, in the current study, asthma was the most common comorbidity detected in both cohorts (52% in CRSwNP and 33% in CRSsNP). This demonstrated congruency with the literature, which documents the prevalence of comobid asthma in up to 21% of patients with CRSsNP and up to 48% of patients with CRSwNP.21–23 Additionally, anxiety was present in 15% of patients with CRS, which is similar to previously published rates of 15–20%.18,24 Upper GI disease was seen in 18% of patients; the reported prevalence of disease in patients with CRS is 20–30%.25,26 The prevalence of depression in the examined cohort of CRS patients (i.e. 26%) also fell within the range reported in the literature (i.e. 11–40%).23,24,27,28
Only the following two of these individual comorbidities were significantly associated with worse sub-domain SNOT-22 scores after Bonferroni correction: depression and arthritis. It is possible that these particular comorbidities are more tightly linked to the SNOT-22 because the SNOT-22 is designed to highlight psychologic and pain disorders, and less likely to pick up on other functional comorbidities. This is demonstrated in the fact that the sub-domain most strongly correlated with the FCI was the psychologic dysfunction, followed by sleep dysfunction.
The mean total FCI score for patients afflicted by these functionally critical comorbidities was low among this cohort (2.12) and did not vary by diagnosis (CRSsNP vs CRSwNP). This finding correlated with a similarly low mean FCI (2.2) reported in the only other study examining this measure in CRS. 8 These findings suggest that patients with CRS have an overall low burden of medical comorbidities that impact physical function. Nevertheless, the confidence interval for FCI demonstrated a wide range (0.657 to 5.245), indicating that providers will likely see patients on both ends of the spectrum in their practice, and thus may benefit from understanding the impact of a large number of total functionally impairing comorbidities on sinonasal HRQOL.
The fact that the association between individual comorbidities and SNOT-22 disappeared on multivariate regression analysis implies that the relationship between medical comorbidities and the SNOT-22 may be additive. For example, although having comorbidity “X” may not by itself significantly impact SNOT-22 scores, if the same patient were also to have one or two additional comorbidities, this would significantly increase the chance of having a significant effect on SNOT-22 scores. This helps explain why the total number of comorbidities (i.e. FCI) significantly correlated with SNOT-22, despite the fact that individually only a few comorbidities similarly correlated. Consequently, it is important to understand that although a patient may not exhibit the comorbidities classically considered to influence QOL, such as depression or anxiety, 18 the fact that they have 2 or 3 other comorbidities may still significantly impact their HRQOL, and should not be discounted.
Age is thought to play a significant role in FCI. It is clear that older patients have a longer period of time to develop more chronic illnesses, and this may predispose them to higher FCI scores. Despite this expectation, our data did not demonstrate a significant impact of age on FCI (P = .068). Nevertheless, our sample size was somewhat limited and it is possible that with a larger sample size, age may be shown to have a signifiacnt impact of FCI scores.
There are additional limitations to this study that should be considered. The assignment of comorbidities was by EMR chart review and thus based on prior assigned medical diagnoses by other medical professionas. However, care was taken to cross-reference medical diagnoses with healthcare provider notes to ensure diagnoses were accurate and current. If a comorbidity was not documented in the medical chart, it was not included as a part of the FCI calculation. The comorbidities comprising the FCI are not inherently life-threatening and may be overlooked by both the patient and a treating physician, which may falsely lower the FCI. 8 Several comorbidities common to CRS, such as migraine and fibromylagia, are not a part of the FCI. 8 However, it was not practical to include every single possible comorbidity in our investigation; thus, our goal was to focus on comorbidities known to have the greatest impact on physical function, which we achieved by implementing a validated measure with established reliablity for assessing functionally critical comorbidities. Finally, the present study was performed at a tertiary rhinology academic center and the findings, including severity of disease, complexity of comorbidities, and the decision to proceed with surgical intervention, may not be generalizable to non-academic settings.
Conclusion
Various indices have been developed in an attempt to inform the impact of medical comorbidities on patient outcomes. However, no such index has been correlated with sinonasal-specific HRQOL. Here, we demonstrated that the FCI, with its focus on comorbidities that specifically cause functional disability, had a significant impact on HRQOL in CRS. Specifically, the total number of medical comorbidities known to have a major impact on physical function was independently associated with worse SNOT-22 scores in patients with CRS. Having established a correlation between the FCI and SNOT-22, future studies should focus on understanding the relationship between FCI and change in sinonasal-specific HRQOL with medical and surgical treatment.
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.
