Evaluation of Comorbidity Burden on Disease Progression and Mortality in Patients with Interstitial Pneumonia with Autoimmune Features: a Retrospective Cohort Study

doi:10.21203/rs.3.rs-3210870/v1

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Evaluation of Comorbidity Burden on Disease Progression and Mortality in Patients with Interstitial Pneumonia with Autoimmune Features: a Retrospective Cohort Study

https://doi.org/10.21203/rs.3.rs-3210870/v1

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Background

Interstitial pneumonia with autoimmune features (IPAF) is a subset of interstitial lung disease that manifests with interstitial pneumonia and features of autoimmunity while not meeting classification criteria for a defined rheumatic disease. Comorbidity burden is an important prognostic indicator in various rheumatic and interstitial lung diseases, but few studies have commented on comorbidities in this population. This study was conducted to evaluate the association of individual comorbidities, the Charlson Comorbidity Index (CCI), and the Rheumatic Disease Comorbidity Index (RDCI) with lung disease progression and transplant/mortality outcomes in patients with IPAF.

Methods

In a retrospective study, we evaluated the prevalence and severity of comorbidities in an institutional cohort of patients with IPAF. Using Cox regression, we correlated the association of individual comorbidities and comorbidity burden using CCI and RDCI with time to lung disease progression (defined as relative forced vital capacity (FVC) decline of 10% or more) and with time to lung transplant/all-cause mortality. We compared the performance of CCI and RDCI, while adjusting for the Interstitial Lung Disease Gender-Age-Physiology (ILD-GAP) index.

Results

In a sample of 201 individuals with IPAF, a history of cerebrovascular accident (CVA) or cardiovascular disease (CVD), moderate to severe chronic kidney disease, or fracture was associated with a faster onset of lung disease progression, while a history of gastroesophageal reflux was protective. History of CVA/CVD, diabetes mellitus, and lymphoma were associated with a faster onset of lung transplant/death. Both CCI and RDCI were significantly associated with shorter time to lung disease progression (hazard ratio [HR] 1.11, 95% confidence interval [CI] 1.04–1.19 and HR 1.12 with 95%CI 1.00-1.26, respectively) and lung transplant/mortality (HR 1.18 [1.07–1.30] and 1.31 [1.10–1.57], respectively).

Conclusions

CCI and RDCI may be useful tools in assessing prognosis in patients with IPAF in terms of both lung disease progression and mortality. Prospective studies are needed to further evaluate the performance of CCI and RDCI and the impact of optimizing comorbid conditions that may mitigate poor outcomes among patients with IPAF.

interstitial lung disease

comorbidity index

autoimmune disease

interstitial pneumonia

Interstitial pneumonia with autoimmune features (IPAF) is a subset of interstitial lung disease (ILD) that manifests with signs and symptoms of autoimmunity while not meeting classification criteria for a defined rheumatic disease (RD) (1). Multiple studies have examined the clinical characteristics and outcomes of IPAF patients (2–5), while few studies have commented on the presence and prevalence of comorbidities in this population (6). To our knowledge, no studies have evaluated the effect of comorbidities on lung function decline in IPAF. Comorbidity burden is an important prognostic indicator in various RDs (7–10) and ILD (11, 12) and is associated with worse disease activity, physical function, quality of life, refractory treatment, and higher mortality risk (7, 13, 14), emphasizing the need for awareness, screening, and optimization of comorbid conditions.

Composite scoring systems or indices can be used to quantify the total burden of comorbid illnesses to measure the overall burden and impact of comorbidities more accurately and to assess prognosis (15) Charlson Comorbidity Index (CCI), a summed score of 19 comorbidities weighted according to severity, was developed to predict one-year mortality in hospitalized patients. The CCI can predict various patient outcomes, including in-hospital mortality, length of hospital stays, readmission rates, functional decline, and healthcare utilization (14, 16). CCI is also a strong prognostic predictor in ILD with the frequency of 3-year ILD-related events increasing with increasing CCI; however, IPAF patients were not included in this cohort (16). In addition, CCI does not account for common comorbidities seen in RDs such as hypertension, osteoporosis, obstructive sleep apnea, or depression which can significantly impact disease activity and quality of life (7, 14).

The rheumatic disease comorbidity index (RDCI) is comprised of 11 comorbid conditions and was developed based on self-report assessments from patients with RDs (15, 17). It has performed well in predicting both physical disability and mortality in diseases such as rheumatoid arthritis and gout (15, 18). However, its usefulness in presumably autoimmune ILD, such as IPAF, has not been evaluated.

The Gender-Age-Physiology (GAP) index was developed as a multidimensional prognostic staging system for ILD using four variables including gender (G), age (A), and two lung physiology variables (P) - forced vital capacity (FVC) and diffusing capacity for carbon monoxide (DLCO) (19). Although initially validated in patients with idiopathic pulmonary fibrosis (IPF), the GAP model has also accurately predicted the risk of death in chronic non-IPF ILD (20–22). A modified GAP index, known as the ILD-GAP index, includes a disease subtype variable that accounts for better-adjusted survival in ILD subtypes, including RD-associated ILD, chronic hypersensitivity pneumonitis, and idiopathic nonspecific interstitial pneumonia. The ILD-GAP model has predicted mortality in major chronic ILD subtypes across all stages of disease (21). However, ILD-GAP does not consider the presence or severity of comorbidities, and a recent study demonstrated that the combination of ILD-GAP and CCI performs better in predicting outcomes in ILD than ILD-GAP or CCI alone (23).

Few studies have examined comorbidities (24–26) and no studies have evaluated the association or effect of comorbidities, using indices such as the CCI or RDCI, with outcomes in IPAF. This study was conducted to determine the prevalence and type of comorbidities in an institutional cohort of patients with IPAF; to evaluate the effect of baseline comorbidities on lung disease progression and mortality; and to assess the performance of the CCI and RDCI, while adjusting for the ILD-GAP index, in predicting outcomes in IPAF patients.

Cohort Assembly:

This single-center retrospective medical records review study was performed at the University of Texas Southwestern (UTSW) Medical Center. Patients seen in the UTSW Interstitial Lung Disease Clinic between January 2005 and August 2019 who met the European Respiratory Society (ERS)/American Thoracic Society (ATS) classification criteria for IPAF were included (1). Date of entry into the cohort was considered as the first available pulmonary function test (PFT) date. The UTSW Medical Center Institutional Review Board approved the study prior to the initiation of data extraction (IRB #STU-2019-0913). Patient consent was not obtained for this retrospective medical records review study.

Inclusion/Exclusion Criteria:

All patients meeting 2015 ERS/ATS IPAF classification criteria were included for evaluation of prevalence of comorbidities and other baseline characteristics. Patients were excluded from primary outcome evaluation if they did not have at least two sets of PFT data and excluded from secondary outcome evaluation if they had less than two visits recorded in the medical record.

Baseline characteristics:

Demographic data included age at ILD diagnosis, sex, race, ethnicity, and smoking status. ILD diagnosis date was the time point at which ILD was first observed on imaging. Sex, race, and ethnicity data was recorded as documented in the electronic medical record (EMR). Smoking status was assigned as smoker if the patient ever smoked and otherwise as never smoker.

Imaging features including lung lesion pattern, presence of honeycombing, and air trapping, were assigned by a pulmonologist (TAN) based on high-resolution computed tomography scans (HRCT) of the chest. The presence of a usual interstitial pneumonia (UIP) pattern on imaging was documented, given the correlation of UIP with increased mortality and faster lung function decline in prior studies (3, 27).

Comorbidities:

Patient medical records were reviewed by an internal medicine physician (MAG) and rheumatologist (EKJ) using a standardized data extraction worksheet. Comorbidities were evaluated by searching for the key terms and reviewing pertinent documentation (including progress notes), laboratory values, and imaging at the time of entry into the cohort (defined as the date of the first PFTs recorded at the initial ILD clinic visit) (Supplementary Appendix A). Agreement between the reviewers was assessed after reviewing 50 charts to ensure accuracy.

Calculation of Comorbidity Indices and ILD Severity:

CCI and RDCI were calculated according to standardized procedures and a data extraction worksheet (Supplementary Tables 1 and 2) (15, 28).

The ILD-GAP index (Supplementary Table 3) was calculated using five predictor variables (gender, age, FVC, DLCO, and ILD category) with assigned points to obtain a total score from 0 to 8 (21). Since IPAF, by definition, is unclassified ILD due to lack of definable etiology such as RD (29), 0 points were assigned for the ILD category score for each patient in the cohort.

Pulmonary Function Tests:

PFT data included FVC, forced expiratory volume in one second (FEV1), FEV1/FVC ratio, and DLCO as percentages of predicted values. Baseline PFTs were the first available tests recorded at the first ILD clinic visit. All available additional PFT data were collected. If a patient underwent a lung transplantation, the last PFT data prior to transplant was included.

Outcomes:

The primary outcome was the time to lung disease progression, defined as relative %FVC decline of ≥ 10% after date of cohort entry. Secondary outcomes were the time to lung transplant and all-cause mortality (whichever occurred first) from the time point of entry into the cohort. All outcomes were obtained from chart review.

Statistical Analysis

Descriptive statistics were used to calculate the prevalence of baseline characteristics and comorbidities in our IPAF cohort. Continuous and categorical variables were expressed as means with standard deviation and counts with percentages, respectively. We used Cox proportional hazards to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for each outcome, first in an unadjusted model then adjusted for ILD-GAP and presence of UIP. All analyses were completed in Stata (V.17, College Station, TX).

Baseline Characteristics:

The cohort, comprised of 201 patients meeting the 2015 ERS/ATS IPAF criteria, was predominantly female (76.1%), with a mean age at the time of initial PFTs of 61.8 ± 12.4 years, and an average time of follow-up of 5.6 ± 3.7 years (Table 1). White patients represented 69.6% of the cohort and 84.6% of patients were non-Hispanic and 34.5% were former or current smokers. The baseline mean %FVC was 64.7% ± 19.1% of predicted. The mean %DLCO was 45.8% ± 20.3% of predicted. The mean baseline ILD-GAP index in our cohort was 3.2 ± 1.7 points. Forty-eight (23.9%) patients had a UIP pattern on imaging with 46.8% having unexplained air trapping and 21.4% having honeycombing on HRCT.

Table 1

Baseline Features of the IPAF Cohort
Baseline characteristic	N = 201
Age at initial PFTs, years; Mean [SD]	61.8 [12.4]
Male sex, n (%)	48 (23.9)
Race, n (%) White Black Asian Other	140 (69.6) 34 (16.9) 10 (5) 17 (8.5)
Ethnicity, n (%) Non-Hispanic Hispanic	170 (84.6) 31 (15.4)
Never smoke, n (%)	114 (65.5)
Baseline FVC, %; Mean [SD]	64.7 [19.1]
Baseline DLCO (n = 200), %; Mean [SD]	45.8 [20.3]
HRCT pattern, n (%) Unable to determine LIP NSIP NSIP/OP OP UIP	21 (10.5) 5 (2.5) 117 (58.2) 9 (4.5) 1 (0.5) 48 (23.9)
Unexplained air trapping on HRCT, n (%)	94 (46.8)
Honeycombing on HRCT, n (%)	43 (21.4)
Follow-up time, years; Mean [SD]	5.6 [3.7]
Mortality outcome, n (%) Loss to follow-up after one visit Alive at the end of follow-up Death due to all causes Lung transplant	1 (0.5) 137 (68.2) 48 (23.9) 15 (7.5)
Time to FVC decline of 10% or more (n = 104), years; Mean [SD]	2.2 [2.0]
Time to death or lung transplant (n = 63), years; Mean [SD]	4.2 [2.8]
CCI; Mean [SD]	3.2 [2.4]
RDCI; Mean [SD]	3.7 [1.3]
ILD-GAP; Mean [SD]	3.2 [1.7]
IPAF – interstitial pneumonia with autoimmune features; SD – standard deviation; PFTs – pulmonary function tests; FVC – forced vital capacity; DLCO – diffusing capacity of lung for carbon monoxide; HRCT – high resolution computed tomography; LIP – lymphocytic interstitial pneumonia; NSIP – non-specific interstitial pneumonia OP – organizing pneumonia; UIP – usual interstitial pneumonia.

Table 1included on the bottom of the file

Prevalence of Comorbidities:

The prevalence of individual comorbidities is shown in Table 2. The most prevalent comorbidities in our cohort included hypertension (67.7%) and gastroesophageal reflux disease (GERD) (64.7%). More than 20% of the cohort had chronic obstructive pulmonary disease (COPD), depression, and diabetes mellitus (DM). The average baseline CCI and RDCI were 3.2 (± 2.4) and 3.7 (± 1.3), respectively (Table 1).

Table 2

Baseline Comorbidities of the IPAF Cohort
Baseline comorbidity	N = 201 n (%)
Myocardial infarction	21 (10.4)
Congestive heart failure	32 (15.9)
Peripheral vascular disease	12 (6)
Cerebrovascular accident*	13 (6.5)
Cardiovascular disease or cerebrovascular accident	41 (20.4)
Chronic obstructive pulmonary disease	58 (28.9)
Peptic ulcer disease	15 (7.5)
Liver disease	7 (3.5)
Diabetes mellitus Diet-controlled Uncomplicated requiring medications With end-organ damage	44 (21.9) 10 (5) 25 (12.4) 9 (4.5)
Chronic kidney disease Any Mild Moderate-severe	38 (18.9) 34 (16.9) 4 (2)
Malignancy** Solid tumor Localized Metastatic Leukemia Lymphoma	31 (15.4) 29 (14.4) 25 (12.4) 4 (2) 0 (0) 2 (1.0)
Acquired immunodeficiency syndrome	0 (0)
Hemiplegia	0 (0)
Fracture (hip/leg/spine)	18 (9)
Osteoporosis	25 (12.4)
Depression	45 (22.4)
Dementia	9 (4.5)
Hypothyroidism	26 (12.9)
Hypertension	136 (67.7)
Obstructive sleep apnea	24 (11.9)
Gastroesophageal reflux disease	130 (64.7)
IPAF – interstitial pneumonia with autoimmune features
*Including transient ischemic attack
**Including skin cancer and hematologic malignancy

Table 2included on the bottom of the file

Primary Outcome:

One hundred and ninety-one (95.0%) patients had ≥ 2 PFTs and were included in lung function decline analysis. Of the 191 patients, 104 (54.5%) patients progressed over an average of 2.2 ± 2.0 years. In univariable analysis, older age, being of race other than Asian, history of cerebrovascular accident (CVA) and/or cardiovascular disease (CVD), moderate to severe chronic kidney disease (CKD), and fracture were significantly associated with faster onset of lung disease progression. The presence of honeycombing and GERD were associated with delayed onset of lung disease progression. These associations remained significant when adjusted for ILD-GAP and UIP (Table 3).

Table 3

Association of Baseline Characteristics with Time to Lung Function Decline
Baseline Characteristic	Univariable Analysis			Bivariable Analysis Model Adjusted for ILD-GAP			Bivariable Analysis Model Adjusted for UIP			Multivariable Analysis Model Adjusted for ILD-GAP and UIP
N = 191	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P
Age at initial PFTs (years)	1.01	1.00-1.03	0.04	1.01	0.999–1.03	0.069	1.01	0.998–1.03	0.099	1.01	0.996–1.02	0.15
Male sex	1.20	0.85–1.69	0.30	1.15	0.80–1.64	0.46	1.13	0.79–1.61	0.51	1.08	0.74–1.56	0.70
Race White (referent) Black Asian Other	1 0.71 0.36 0.66	0.48–1.04 0.18–0.75 0.39–1.10	0.08 0.01 0.11	1 0.71 0.37 0.66	0.49–1.05 0.18–0.78 0.39–1.10	0.08 0.01 0.11	1 0.71 0.36 0.68	0.49–1.05 0.17–0.75 0.41–1.14	0.08 0.01 0.14	1 0.72 0.37 0.68	0.49–1.05 0.18–0.77 0.41–1.14	0.09 0.01 0.14
Hispanic ethnicity	1.02	0.68–1.52	0.93	1.00	0.67–1.49	> 0.99	1.02	0.68–1.51	0.93	1.00	0.67–1.49	> 0.99
Smoking history	1.10	0.82–1.49	0.52	1.08	0.80–1.46	0.63	1.06	0.78–1.44	0.73	1.03	0.76–1.41	0.84
Baseline FVC (%)	1.01	0.998–1.01	0.15	1.01	1.00-1.02	0.01	1.00	0.997–1.01	0.26	1.01	1.00-1.02	0.03
Baseline DLCO (%)	1.00	0.99–1.01	0.92	1.01	0.996–1.02	0.24	0.999	0.99–1.01	0.88	1.00	0.99–1.02	0.41
UIP pattern on HRCT	1.28	0.92–1.79	0.14	1.27	0.91–1.78	0.16	-	-	-	-	-	-
Unexplained air trapping on HRCT	1.00	0.75–1.33	0.99	1.02	0.77–1.37	0.88	1.06	0.79–1.43	0.69	1.08	0.80–1.46	0.60
Honeycombing on HRCT	0.64	0.45–0.92	0.02	0.65	0.45–0.93	0.02	0.66	0.46–0.95	0.03	0.67	0.46–0.97	0.03
Hypertension	1.12	0.83–1.51	0.47	1.11	0.82–1.51	0.49	1.12	0.82–1.51	0.48	1.11	0.82–1.50	0.51
Myocardial infarction	1.56	0.99–2.47	0.06	1.57	0.99–2.48	0.05	1.45	0.90–2.35	0.13	1.47	0.91–2.37	0.12
Congestive heart failure	1.15	0.77–1.71	0.49	1.12	0.75–1.68	0.56	1.15	0.77–1.72	0.48	1.13	0.76–1.68	0.56
Peripheral vascular disease	1.52	0.84–2.74	0.17	1.43	0.78–2.62	0.25	1.42	0.78–2.59	0.25	1.35	0.73–2.48	0.34
Cerebrovascular accident*	1.46	0.83–2.57	0.19	1.38	0.77–2.47	0.28	1.40	0.79–2.48	0.25	1.33	0.74–2.38	0.34
Cardiovascular disease or cerebrovascular accident	1.64	1.15–2.35	0.01	1.61	1.12–2.31	0.01	1.60	1.11–2.29	0.01	1.56	1.09–2.25	0.02
Chronic obstructive pulmonary disease	1.20	0.87–1.65	0.36	1.29	0.93–1.79	0.13	1.21	0.88–1.67	0.23	1.30	0.93–1.80	0.12
Obstructive sleep apnea	1.23	0.78–1.91	0.37	1.24	0.79–1.93	0.35	1.21	0.78–1.90	0.39	1.22	0.78–1.92	0.37
Gastroesophageal reflux disease	0.72	0.53–0.98	0.04	0.70	0.52–0.96	0.02	0.71	0.52–0.96	0.03	0.69	0.50–0.93	0.02
Peptic ulcer disease	0.89	0.52–1.55	0.69	0.91	0.52–1.57	0.73	0.89	0.52–1.55	0.69	0.90	0.52–1.56	0.72
Liver disease	1.03	0.45–2.32	0.95	1.07	0.47–2.43	0.87	0.97	0.43–2.20	0.94	1.00	0.44–2.28	> 0.99
Diabetes mellitus (any) None or diet controlled (referent) Uncomplicated requiring medications With end organ damage	1.10 1 0.84 1.67	0.78–1.55 0.55–1.29 0.85–3.28	0.58 0.42 0.14	1.09 1 0.83 1.59	0.77–1.54 0.54–1.28 0.80–3.15	0.62 0.41 0.18	1.11 1 0.86 1.58	0.79–1.57 0.56–1.34 0.80–3.12	0.54 0.51 0.19	1.11 1 0.86 1.51	0.78–1.56 0.56–1.33 0.76-3.00	0.57 0.50 0.24
Chronic kidney disease (any) None or mild (referent) Moderate-severe	1.43 1 3.19	0.98–2.07 1.18–8.68	0.06 0.02	1.40 1 3.23	0.96–2.04 1.19–8.78	0.07 0.02	1.40 1 3.14	0.97–2.04 1.15–8.54	0.075 0.03	1.38 1 3.19	0.95–2.01 1.17–8.67	0.09 0.02
Malignancy** (any) No solid tumor (referent) Local solid tumor Metastatic solid tumor	1.01 1 0.98 1.89	0.68–1.51 0.63–1.51 0.70–5.14	0.95 0.92 0.21	1.00 1 0.97 1.86	0.67–1.49 0.62–1.50 0.68–5.06	> 0.99 0.88 0.22	1.04 1 0.995 1.88	0.70–1.54 0.64–1.54 0.69–5.12	0.86 0.98 0.21	1.02 1 0.99 1.87	0.69–1.53 0.63–1.53 0.69–5.07	0.91 0.95 0.22
Lymphoma	2.66	0.65–10.83	0.17	2.69	0.66–10.97	0.17	2.36	0.57–9.72	0.23	2.40	0.58–9.87	0.22
Fracture (hip/leg/spine)	2.00	1.22–3.26	0.01	1.95	1.19–3.19	0.01	2.05	1.25–3.35	0.004	2.00	1.22–3.28	0.01
Osteoporosis	1.15	0.75–1.77	0.53	1.14	0.74–1.76	0.54	1.09	0.71–1.69	0.69	1.09	0.70–1.69	0.70
Depression	1.21	0.85–1.71	0.28	1.21	0.85–1.71	0.28	1.20	0.85–1.70	0.29	1.20	0.85–1.70	0.29
Dementia	1.44	0.71–2.93	0.31	1.50	0.74–3.07	0.26	1.49	0.73–3.04	0.27	1.55	0.76–3.17	0.23
Hypothyroidism	1.24	0.80–1.92	0.34	1.24	0.80–1.92	0.34	1.29	0.83–2.02	0.26	1.29	0.83–2.01	0.26
CCI	1.11	1.04–1.19	0.001	1.11	1.04–1.19	0.002	1.11	1.03–1.18	0.003	1.10	1.03–1.18	0.01
RDCI	1.12	1.00-1.26	0.04	1.12	0.999–1.25	0.05	1.12	1.00-1.26	0.048	1.12	0.996–1.25	0.06
ILD-GAP	1.05	0.96–1.15	0.28	-	-	-	1.05	0.96–1.15	0.31	-	-	-
RDCI – rheumatic disease comorbidity index; CCI – Charlson Comorbidity Index, ILD-GAP – Gender, Age, Physiology Index for Interstitial Lung Disease; PFTs – pulmonary function tests; FVC – forced vital capacity; DLCO – diffusing capacity of lung for carbon monoxide; UIP – usual interstitial pneumonia; HRCT – high resolution computed tomography; HR – hazard ratio; CI – confidence interval.
*Including transient ischemic attack
**Including skin cancer and hematologic malignancy

Table 3included on the bottom of the file

Secondary Outcome:

Two hundred patients (99.5%) in our cohort had ≥1 medical visit recorded in the EMR. One patient was lost to follow-up after one visit. Forty-eight (23.9%) patients died and 15 (7.5%) patients had lung transplant (Table 1). Older age, male sex, smoking history, lower FVC or DLCO, presence of UIP pattern, and history of CVA and/or CVD, DM (in particular with end-organ damage), and lymphoma were associated with significantly shorter time to lung transplant/death. After adjusting for ILD-GAP, age, UIP pattern on HRCT, DM, and lymphoma remained significantly associated with shorter time to lung transplant/death. After adjusting for the presence of UIP pattern, older age, male sex, smoking history, lower PFT parameters, congestive heart failure (CHF), DM, and lymphoma were significant factors associated with the outcome. Interestingly, only DM with end organ damage and lymphoma remained significantly associated with lung transplant/death after adjusting for both ILD-GAP and UIP (Table 4).

Table 4

Association of Baseline Characteristics with Time to Lung Transplant/Death
Baseline Characteristic	Univariable Analysis			Bivariable Analysis Model Adjusted for ILD-GAP			Bivariable Analysis Model Adjusted for UIP			Multivariable Analysis Model Adjusted for ILD-GAP and UIP
N = 200	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P	HR	95% CI	P
Age (years)	1.04	1.01–1.06	0.002	1.02	1.00-1.05	0.04	1.03	1.01–1.06	0.007	1.02	0.99–1.04	0.19
Male sex	2.49	1.49–4.15	< 0.001	1.55	0.89–2.72	0.12	2.32	1.38–3.91	0.002	1.42	0.81–2.48	0.22
Race White (referent) Black Asian Other	1 0.55 0.17 0.35	0.27–1.12 0.026–1.35 0.11–1.13	0.10 0.10 0.08	1 0.63 0.26 0.34	0.30–1.29 0.04–1.92 0.11–1.09	0.20 0.19 0.07	1 0.59 0.19 0.38	0.29–1.21 0.03–1.38 0.12–1.21	0.15 0.10 0.10	1 0.68 0.28 0.37	0.33–1.41 0.04–2.08 0.11–1.21	0.30 0.21 0.10
Hispanic ethnicity	1.43	0.79–2.60	0.24	1.18	0.64–2.17	0.60	1.40	0.77–2.53	0.27	1.19	0.65–2.19	0.57
Smoking history	1.97	1.19–3.24	0.01	1.42	0.84–2.42	0.19	1.84	1.11–3.06	0.02	1.32	0.77–2.24	0.31
Baseline FVC (%)	0.98	0.97 − 0.96	0.01	1.00	0.99–1.02	0.71	0.98	0.96–0.99	0.001	0.997	0.98–1.01	0.70
Baseline DLCO (%)	0.98	0.97–0.99	0.002	1.00	0.99–1.02	0.72	0.97	0.96–0.99	< 0.001	0.997	0.98–1.01	0.70
UIP pattern on HRCT	1.70	1.01–2.47	0.047	1.86	1.09–3.17	0.02	-	-	-	-	-	-
Unexplained air trapping on HRCT	1.19	0.73–1.93	0.50	1.42	0.86–2.35	0.17	1.41	0.84–2.37	0.20	1.62	0.97–2.72	0.07
Honeycombing on HRCT	1.12	0.65–1.93	0.69	1.14	0.66–1.97	0.64	1.18	0.68–2.04	0.56	1.25	0.72–2.18	0.43
Hypertension	1.33	0.77–2.29	0.31	1.18	0.68–2.05	0.56	1.39	0.80–2.42	0.24	1.19	0.68–2.07	0.54
Myocardial infarction	1.10	0.50–2.42	0.81	1.06	0.48–2.34	0.88	0.91	0.40–2.04	0.82	0.93	0.42–2.07	0.87
Congestive heart failure	1.83	0.97–3.45	0.06	1.34	0.70–2.55	0.37	2.00	1.05–3.81	0.03	1.47	0.77–2.82	0.24
Peripheral vascular disease	2.23	0.96–5.19	0.06	1.29	0.54–3.08	0.57	1.98	0.84–4.66	0.12	1.20	0.50–2.85	0.68
Cerebrovascular accident*	1.60	0.64–4.01	0.31	0.91	0.35–2.34	0.85	1.40	0.55–3.54	0.48	0.85	0.33–2.16	0.73
Cardiovascular disease of cerebrovascular accident*	1.87	1.07–3.27	0.03	1.36	0.76–2.43	0.29	1.72	0.97–3.04	0.06	1.27	0.71–2.25	0.42
Chronic obstructive pulmonary disease	0.86	0.48–1.51	0.59	1.08	0.61–1.92	0.79	0.87	0.49–1.53	0.62	1.06	0.60–1.88	0.83
Obstructive sleep apnea	1.24	0.59–2.61	0.57	1.59	0.75–3.38	0.23	1.23	0.59–2.59	0.58	1.61	0.75–3.44	0.22
Gastroesophageal reflux disease	0.78	0.46–1.31	0.34	0.76	0.45–1.28	0.30	0.73	0.43–1.24	0.24	0.69	0.40–1.17	0.17
Peptic ulcer disease	1.46	0.63–3.39	0.38	1.50	0.64–3.50	0.35	1.28	0.54-3.00	0.58	1.14	0.47–2.76	0.77
Liver disease	0.48	0.066–3.45	0.46	0.58	0.08–4.18	0.58	0.40	0.06–2.90	0.36	0.41	0.06–3.06	0.39
Diabetes mellitus (any) None or diet controlled (referent) Uncomplicated requiring medications With end organ damage	1.84 1 0.94 5.07	1.08–3.17 0.43–2.08 2.25–11.39	0.03 0.88 < 0.001	1.74 1 0.94 3.01	1.01–2.99 0.42–2.08 1.31–6.94	0.045 0.88 0.01	1.79 1 0.95 4.61	1.04–3.08 0.43–2.10 2.04–10.41	0.04 0.90 < 0.001	1.71 1 0.98 2.81	0.99–2.94 0.44–2.18 1.23–6.41	0.05 0.96 0.01
Chronic kidney disease (any) None or mild (referent) Moderate-severe	1.37 1 0.82	0.76–2.49 0.11–5.91	0.30 0.84	0.96 1 0.75	0.52–1.78 0.10–5.44	0.89 0.78	1.25 1 0.69	0.68–2.28 0.10-5.00	0.47 0.71	0.88 1 0.71	0.48–1.63 0.10–5.14	0.68 0.74
Malignancy** (any) No solid tumor (referent) Local solid tumor Metastatic solid tumor	1.44 1 1.43 0.82	0.77–2.71 0.72–2.81 0.11–5.93	0.26 0.31 0.84	1.18 1 1.11 1.22	0.63–2.24 0.56–2.22 0.17–8.90	0.60 0.76 0.85	1.42 1 1.46 0.62	0.75–2.66 0.74–2.88 0.08–4.60	0.28 0.27 0.64	1.20 1 1.14 1.07	0.64–2.27 0.57–2.26 0.15–7.91	0.57 0.71 0.95
Lymphoma	20.50	4.66–90.09	< 0.001	27.77	6.23-123.66	< 0.001	15.42	3.40-70.02	< 0.001	20.30	4.44–92.8	< 0.001
Fracture	1.57	0.67–3.65	0.30	1.47	0.63–3.42	0.37	1.44	0.62–3.36	0.4	1.44	0.62–3.36	0.4
Osteoporosis	1.02	0.47–2.25	0.95	0.92	0.42–2.03	0.84	0.92	0.42–2.04	0.84	0.79	0.35–1.76	0.56
Depression	1.42	0.78–2.58	0.25	1.41	0.78–2.57	0.26	1.41	0.78–2.57	0.26	1.38	0.76–2.51	0.29
Dementia	1.48	0.46–4.74	0.51	1.97	0.61–6.34	0.26	1.71	0.53–5.52	0.37	2.33	0.71–7.59	0.16
Hypothyroidism	1.53	0.75–3.12	0.25	1.91	0.92–2.96	0.08	1.67	0.81–3.43	0.16	2.02	0.97–4.17	0.06
CCI	1.18	1.07–1.30	0.001	1.13	1.02–1.26	0.02	1.16	1.04–1.29	0.01	1.10	0.99–1.23	0.08
RDCI	1.31	1.10–1.57	0.003	1.24	1.03–1.50	0.02	1.29	1.07–1.54	0.01	1.20	0.99–1.46	0.06
ILD-GAP	1.53	1.31–1.80	< 0.001	-	-	-	1.57	1.33–1.85	< 0.001	-	-	-
PFTs – pulmonary function tests; FVC – forced vital capacity; DLCO – diffusing capacity of lung for carbon monoxide; UIP – usual interstitial pneumonia; HRCT – high resolution computed tomography; HR – hazard ratio; CI – confidence interval; CCI – Charlson Comorbidity Index; RDCI – rheumatic disease comorbidity index; ILD-GAP – Gender, Age, Physiology Index for Interstitial Lung Disease.
*Including transient ischemic attack
**Including skin cancer and hematologic malignancy

Table 4included on the bottom of the file

Effect of Baseline Comorbidity Indices on Outcomes:

In univariable analysis, both CCI and RDCI were significantly associated with lung disease progression (Table 3) and lung transplant/mortality outcomes (Table 4). ILD-GAP was significantly associated with lung transplant/mortality but not with lung disease progression (Tables 3 and 4).

The association of CCI with lung disease progression, but not that of RDCI, remained significant when adjusted for ILD-GAP and ILD-GAP and UIP. When adjusted for the presence or absence of UIP pattern alone, both CCI and RDCI remained significant predictors of the outcome (Table 3).

CCI and RDCI were significantly associated with shorter time to lung transplant/death even when adjusted for ILD-GAP or UIP. However, neither CCI nor RDCI were significantly associated with the lung transplant/mortality outcome after adjusting for both ILD-GAP and UIP pattern in multivariable analysis. Higher ILD-GAP was associated with significantly shorter time to lung transplant/death outcomes in univariable analysis and when adjusted for UIP (Table 4).

In this study we explored the prevalence and the effect of baseline comorbidities on lung disease progression and lung transplant/mortality in a cohort of patients with IPAF. We also assessed the performance of two well-established comorbidity indices, CCI and RDCI, in predicting outcomes in this population. We found that comorbidity indices provide comprehensive information regarding a patient’s prognosis, including lung disease progression.

Hypertension and GERD were the most prevalent comorbidities in our cohort. This was consistent with a study by Oldham, et al., where GERD was the most prevalent (52.8%) comorbidity in an IPAF cohort raising suspicion for a potential contribution of GERD to disease pathogenesis in IPAF (3). In addition, COPD, depression, and DM were found to be common comorbid conditions in our cohort, a finding which was not discussed in prior IPAF literature but has been demonstrated in other forms of ILD (12, 30, 31).

When evaluating the effect of comorbidities on lung disease progression, this study revealed that multiple comorbidities such as a history of CVA/CVD, moderate to severe CKD and fracture, specifically that of lower extremity or vertebrae, were associated with a faster onset of relative FVC decline of ≥ 10% or more from the time of cohort entry in patients with IPAF. Conversely, a history of GERD was associated with a longer time to lung disease progression.

Although it is difficult to ascertain the association between the various comorbidities, prior studies have commented on the effects of these comorbidities on lung disease progression in patients with other forms of ILD. For example, CVD is a treatable comorbidity frequently observed in IPF and has been linked to worse outcomes, with proposed mechanisms including systemic inflammation, hypercoagulability, platelet activation, and oxidative stress (32–34). A complex relationship between CKD and lung disease progression, particularly through alterations of fluid homeostasis and acid-base balance, has also been demonstrated (35, 36). A potential explanation for the observed association of fracture and lung disease progression, in this study, is the increased prevalence of steroid use in patients with more severe disease which can thereby increase fracture risk. However, fracture was a baseline comorbidity in the cohort and thus steroid use would not be expected to contribute significantly to its prevalence at the time of baseline data collection. To evaluate this possibility, data regarding osteoporosis was also collected, but did not demonstrate a significant association with the studied outcomes. In other autoimmune diseases, such as rheumatoid arthritis, osteopenia and osteoporosis have correlated with higher mortality and fracture risk, when compared to the general population (18). Interestingly, GERD was found to be a protective factor for lung disease progression in our cohort, a finding which varies from prior studies that considered GERD to be a risk factor for ILD development (37). One consideration is the high prevalence of proton pump inhibitor use, an intervention hypothesized to slow lung disease progression in patients with IPF (38, 39). Based on our results, the association of CVD, CKD, fracture risk, and GERD with lung disease progression in patients with IPAF warrants further investigation.

Importantly, few prior studies have explored the prognostic impact of comorbid conditions in IPAF. Two studies suggested that hypothyroidism was associated with greater mortality (7, 8), but a diagnosis of obstructive sleep apnea (OSA) was correlated with better survival when compared to IPAF patients without these conditions (7). Malignancy was noted to be a serious comorbidity associated with faster progression of fibrotic lung disease in RD-ILD and IPAF (9). In our study, OSA and hypothyroidism were not significantly associated with outcomes, but lymphoma, as well as CKD and DM, were associated with shorter time to lung transplant/mortality. Similar to other studies, increasing age, male sex, and smoking history were also associated with shorter time to lung transplant/mortality in our cohort (40–44).

We evaluated the performance of the CCI and RDCI in patients with IPAF and found that both CCI and RDCI were helpful in predicting lung function and transplant/mortality outcomes, even after adjusting for UIP pattern. However, the performance of indices was variable for both outcomes when adjusted for both ILD-GAP and UIP pattern. Notably, CVA/CVD and fracture, which are components of RDCI, but not CCI, were important comorbidities associated with poor outcomes in our study. Additionally, depression was highly prevalent in our cohort but is only reflected within the RDCI score. These findings suggest that both CCI and RDCI may be useful tools for prognosticating outcomes in IPAF patients.

Our study has several strengths. We had a large, diverse IPAF cohort and the ability to explore numerous comorbidities. Sixteen percent of our cohort included Black patients, increasing the external validity of our findings. Comorbidities have been variably explored in cohorts of patients with IPAF, resulting in highly heterogeneous data of the prevalence of multiple comorbidities. In our study, we systematically and rigorously assessed the comorbidities used to calculate two commonly used comorbidity indices, particularly in autoimmune diseases, making our findings relevant to presumably autoimmune-related ILD such as IPAF. Our study was the first to use comorbidity indices CCI and RDCI to assess the comorbidity burden in this specific population and demonstrate their usefulness in assessing functional and survival outcomes. Specifically, this study supports the use of RDCI in this population, a possible advantage for rheumatologists seeing these patients. Our results also emphasize the need for comprehensive evaluation of IPAF patients and multiple tools for optimal management and monitoring, including HRCT imaging, PFT monitoring, and ILD-GAP and comorbidity assessments.

We acknowledge several limitations of our study. Given the retrospective nature of the study, the variables were collected by medical record review which can lead to misclassification bias, attrition bias, and the presence of missing data. We used precise and consistent definitions of the key comorbidities and variables to guide the data collection by two clinical researchers (with familiarity with both the medical record and management of these conditions and comorbidities) to mitigate the effects of misclassification bias and imaging data by an experienced ILD pulmonologist. However, loss to follow-up could have introduced selection bias. Patients who did not have repeat PFT data were excluded from the study, which could have been due to unknown death or a different cause that was not recorded in the medical record. Finally, while our study emphasizes the need for comorbidity screening for patients with IPAF, we were unable to evaluate whether controlling comorbidities would mitigate the often detrimental association with disease outcomes.

In summary, our study addresses a substantial healthcare gap for patients with IPAF, as few studies have examined comorbidities in this population. Multiple comorbidities are highly prevalent in IPAF and their burden, as assessed by comorbidity indices, influences functional and survival outcomes. Importantly, our study highlights the utility of two common comorbidity indices in assessing the outcomes of patients with IPAF. Particularly, the comorbidity burden in IPAF may be slightly better assessed by RDCI than CCI due to the inclusion of fracture and depression. Importantly, several of the comorbidities frequently seen in our cohort are modifiable and can be optimized, including DM, depression, COPD, GERD and others. Furthermore, potential mechanisms underlying CVA/CVD, CKD, and fracture with lung disease progression in IPAF need to be explored. Further prospective studies are needed to investigate whether aggressive treatment of comorbidities will mitigate poor outcomes. Clinicians taking care of patients with IPAF should be aware of common comorbid conditions, the potential prognostic implications of comorbidity indices, and the increased morbidity effect of specific comorbidities in this patient population.

IPAF: interstitial pneumonia with autoimmune features

ILD: interstitial lung disease

RD: rheumatic disease

CCI: Charlson Comorbidity Index

RDCI: rheumatic disease comorbidity index

GAP index: Gender-Age-Physiology index

FVC: forced vital capacity

DLCO: diffusing capacity for carbon monoxide

IPF: idiopathic pulmonary fibrosis

UTSW: University of Texas Southwestern

ERS: European Respiratory Society

ATS: American Thoracic Society

PFT: pulmonary function test

EMR: electronic medical record

HRCT: high-resolution computed tomography

UIP: usual interstitial pneumonia

FEV1: forced expiratory volume in one second

HR: hazard ratio

CI: confidence interval

GERD: gastroesophageal reflux disease

COPD: chronic obstructive pulmonary disease

DM: diabetes mellitus

CVA: cerebrovascular accident

CVD: cardiovascular disease

CKD: chronic kidney disease

CHF: congestive heart failure

Ethics Approval and Consent to Participate:

The University of Texas Southwestern Medical Center Institutional Review Board approved the study prior to the initiation of data extraction (IRB #STU-2019-0913). Waiver of informed consent from University of Texas Southwestern Medical Center Institutional Review Board (IRB #STU-2019-0913) was obtained for each subject for this medical record review retrospective study. All aspects of the study were performed in accordance with all relevant guidelines and regulations including Declaration of Helsinki.

Consent for Publication:

Not applicable.

Availability of Data and Materials:

The data sets generated during the current study are not publicly available due to protected

health information but are available from the corresponding author on reasonable request.

Competing Interests:

EJ reports salary support from Ruth L. Kirschstein Institutional National Research Service Award (T32).

MG reports no conflict of interest, financial or otherwise.

TA reports no conflict of interest, financial or otherwise.

UM reports no conflict of interest, financial or otherwise.

Funding:

The conduction of this study was supported by Ruth L. Kirschstein Institutional National Research Service Award (T32).

Authors’ Contributions:

EJ, MG, TA, and UM were involved in study design. EJ, MG and TA collected the data and EJ and MG analyzed the patient data. EJ, MG, TA, and UM have contributed to the writing of the manuscript and have read and approved the final manuscript.

Acknowledgments:

Not applicable

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Competing interest reported. EJ reports salary support from Ruth L. Kirschstein Institutional National Research Service Award (T32). MG reports no conflict of interest, financial or otherwise. TA reports no conflict of interest, financial or otherwise. UM reports no conflict of interest, financial or otherwise.

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Evaluation of Comorbidity Burden on Disease Progression and Mortality in Patients with Interstitial Pneumonia with Autoimmune Features: a Retrospective Cohort Study

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Abstract

Background

Methods

Results

Conclusions

BACKGROUND

METHODS

Cohort Assembly:

Inclusion/Exclusion Criteria:

Baseline characteristics:

Comorbidities:

Calculation of Comorbidity Indices and ILD Severity:

Pulmonary Function Tests:

Outcomes:

Statistical Analysis

RESULTS

Baseline Characteristics:

Prevalence of Comorbidities:

Primary Outcome:

Secondary Outcome:

Effect of Baseline Comorbidity Indices on Outcomes:

DISCUSSION

CONCLUSION

List Of Abbreviations

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References

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