Literature DB >> 26714746

Change in forced vital capacity and associated subsequent outcomes in patients with newly diagnosed idiopathic pulmonary fibrosis.

William M Reichmann1, Yanni F Yu2, Dendy Macaulay3, Eric Q Wu4, Steven D Nathan5.   

Abstract

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a rare and serious disease characterized by progressive lung-function loss. Limited evidence has been published on the impact of lung-function loss on subsequent patient outcomes. This study examined change in forced vital capacity (FVC) across IPF patients in the 6 months after diagnosis and its association with clinical and healthcare resource utilization (HRU) outcomes in a real-world setting in the U.S.
METHODS: A retrospective chart review was conducted of patients diagnosed with IPF by U.S. pulmonologists. Patient eligibility criteria included: 1) 40 years or older with a confirmed date of first IPF diagnosis with high-resolution computed tomography and/or lung biopsy between 01/2011 and 06/2013; 2) FVC results recorded at first diagnosis (±1 month) and at 6 months (±3 months) following diagnosis. Based on relative change in FVC percent predicted (FVC%), patients were categorized as stable (decline <5%), marginal decline (decline ≥5% and <10%), or significant decline (decline ≥10%). Physician-reported clinical and HRU outcomes were assessed from ~6 months post-diagnosis until the last contact date with the physician and compared between FVC% change groups. Multivariable Cox proportional-hazards models were constructed to assess risk of mortality, suspected acute exacerbation (AEx), and hospitalization post-FVC% change. Generalized estimating equations were used to account for multiple patients contributed by individual physicians.
RESULTS: The sample included 490 IPF patients contributed by 168 pulmonologists. The mean (SD) age was 61 (11) years, 68% were male, and the mean (SD) baseline FVC% was 60% (26%). 250 (51%) patients were categorized as stable, 98 (20%) as marginal decline, and 142 (29%) as significant decline. The mean (SD) observation time was 583 (287) days. In both unadjusted analysis and multivariable models, significantly worse clinical outcomes and increased HRU were observed with greater lung-function decline.
CONCLUSIONS: These findings suggest that nearly half of IPF patients experienced decline in FVC% within ~6 months following IPF diagnosis. Greater FVC% decline was associated with an increased risk of further IPF progression, suspected AEx, mortality, and higher rate of HRU. Management options that slow FVC decline may help improve future health outcomes in IPF.

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Year:  2015        PMID: 26714746      PMCID: PMC4696269          DOI: 10.1186/s12890-015-0161-5

Source DB:  PubMed          Journal:  BMC Pulm Med        ISSN: 1471-2466            Impact factor:   3.317


Background

Idiopathic pulmonary fibrosis (IPF) is a rare, chronic, and serious pulmonary disease of unknown etiology characterized by the progressive loss of lung function. The prevalence of IPF in the U.S. is estimated to be 14 to 43 per 100,000 person-years and increases with age [1]. More recent incidence and prevalence estimates among the elderly U.S. population are 91 and 495 cases per 100,000 person-years [2]. Following diagnosis, the prognosis is generally poor, with a median survival time of approximately 3–5 years [3, 4]. Patients with IPF may remain stable, progress steadily over time, progress rapidly, or experience episodes of acute deterioration, some of which can be acute exacerbations (AEx) [5]. Until recently, treatment options for IPF patients in the U.S. had been limited to oxygen therapy, pulmonary rehabilitation, and, in select cases, lung transplantation [5, 6]. In October 2014, the Food and Drug Administration approved two new pharmacologic agents for IPF, expanding treatment options [7, 8]. Both drugs have been recommended for use in the 2015 update to the 2011 ATS/ERS/JRS/ALAT IPF clinical practice guidelines [9]. The variable clinical course of IPF presents a challenge to predicting disease progression and managing care of patients [3]. Given the limited treatment options and the substantial impact of the disease on patients’ health outcomes [10, 11], increased evidence regarding the clinical progression of IPF are needed. Previous studies have shown that patients with IPF have significantly higher healthcare resource utilization (HRU) compared to matched controls [12, 13] as well as an increased risk of death [14]. Martinez et al. reported on the clinical course of IPF in a multicenter randomized controlled trial and observed frequent hospitalizations and rapid progression of lung disease in patients who died due to IPF [15]. Further, decline in FVC has been shown to be associated with an increased risk of progression and death [16-18]. However, studies have not examined the relationship between lung-function change and other clinical outcomes, such as AEx or HRU. The research gap arises in part due to difficulty in obtaining measures of lung function at time points throughout the course of disease in the real world. Such data could be useful for key stakeholders, especially with the recent availability of disease modulating therapies for IPF. This study aimed to address the evidence gap through the use of chart data extracted by treating pulmonologists from a nationwide panel in the U.S. The existing literature have been constrained to either post-hoc analyses of patients from randomized controlled trials or observational studies from single centers, neither of which may be representative of the broader IPF population. The approach used in this study allowed for a study population with a sufficient sample size that would be representative of a variety of treatment settings. The objective of this study was to assess the association of lung-function change with clinical outcomes and IPF-related HRU in patients with newly diagnosed IPF.

Methods

Data source

A retrospective chart review was conducted by pulmonologists from a nationally representative panel using an online case report form. The panel comprised over 1,000 pulmonologists working in both academic and non-academic institutions, and covered all regions in the U.S. The pulmonologist panel was demographically similar to those on the American Medical Association master list [19].

Sample selection

Pulmonologists on the panel were invited via e-mail to participate. Those who accepted the invitation completed a questionnaire to assess their eligibility. Pulmonologists were eligible to participate if they had complete access to their patients’ (inpatient and outpatient) IPF-related medical records. Eligible physicians were then requested to randomly select IPF patients who met the inclusion criteria for this study. IPF patients were eligible for chart abstraction if they met the following criteria: 1) 40 years or older with a confirmed date of first IPF diagnosis with HRCT and/or lung biopsy between January 1, 2011 and June 30, 2013; and 2) the patient’s pulmonary function tests measured using FVC were recorded at or around first IPF diagnosis (±1 month) and at or around 6 months (±3 months) following diagnosis. Pulmonologists were compensated for their participation and remained anonymous to the study sponsor and vice versa. The electronic case report form and study synopsis were reviewed by the New England Institutional Review Board, which granted exemption from a full review because this non-interventional study collected retrospective, de-identified data. Patient consent forms were not required, and the chart abstraction form did not request any information that could be linked to a patient’s identity, such as name, date of birth, date of death, or social security number.

Study period

Data were collected from the date of initial IPF diagnosis until last follow-up. The last follow-up date was defined as either: 1) the last contact the pulmonologist had with the patient for those who were alive as of chart abstraction; or 2) the date of death for the deceased. The study period was divided into two time periods, concurrent and subsequent. The “concurrent period” was defined as the time from initial IPF diagnosis date to the FVC measurement closest to 6 months post-IPF diagnosis. The “subsequent period” was defined as the time from the FVC measurement date closest to 6 months post-IPF diagnosis to the last follow-up date (i.e., end of the study period) with no requirement for minimum length of follow-up. The length of the concurrent and subsequent periods therefore varied for patients.

Independent variables and outcome measures

The main independent variable of interest was relative change in FVC percent predicted (FVC%) over 6 months. The stable group was defined as <5 % decrease in FVC%, the marginal decline group as ≥5 % and <10 % decrease in FVC%, and the significant decline group as ≥10 % decrease in FVC%. Other lung-function measures collected included forced expiratory volume after 1 min (FEV1), FEV1/FVC ratio, and the single breath diffusing capacity for the lung for carbon monoxide (DLCO). The GAP index was also calculated at the initial IPF diagnosis based on the patient’s gender, age, FVC%, and DLCO values [20]. In order to estimate the GAP index for all patients, missing DLCO values were imputed for 108 patients (22 %) using single imputation (see Appendix). Clinical and IPF-related HRU outcomes were collected during the subsequent period and were based on physician report. Clinical outcomes included all-cause mortality, mortality due to IPF, mortality due to a suspected AEx, suspected AEx, and IPF progression. Suspected AEx was defined by asking participating pulmonologists if a particular outpatient visit, emergency room (ER) visit, or hospitalization was related to an IPF AEx. IPF progression was based on physician assessment. Physicians were asked if the patient had experienced one of the following since the previous visit: progressive dyspnea, increased cough, sustained decrease from baseline in absolute FVC and DLCO, progression of fibrosis from baseline on HRCT, AEx, respiratory failure, or new need for supplemental oxygen or increase in oxygen requirements. IPF-related HRU outcomes were collected in the outpatient, ER, and hospital settings. Outcomes in the outpatient setting included the timing and number of outpatient visits, outpatient visits that were unscheduled and/or for urgent care, and outpatient visits that were for suspected AEx. Also documented were the timing and number of visits where prednisone, azathioprine, and/or N-acetylcysteine were prescribed and where arterial blood gas test, high-resolution computed tomography, chest x-ray, lung biopsy, and/or pulmonary rehabilitation were conducted for IPF. Similar outcomes were documented when patients presented to the ER and hospital settings. Information on the above clinical and HRU variables was also collected for the concurrent period to assess whether patients in different FVC% change groups had different characteristics in the concurrent period.

Statistical analysis

Summary statistics for characteristics of the treating physician and their practice were calculated. Patient characteristics at the time of diagnosis were compared between patients in different FVC% change groups. The incidence rate (IR) or risk of clinical and HRU outcomes was assessed using unadjusted regression analysis with FVC% change group as the only independent variable and was estimated at the per-patient-half-year level for the concurrent period and per-patient-year level for the subsequent period. Negative binomial regression was used to estimate the incidence rate ratio (IRR) and its 95 % confidence interval (CI) for count variables. Logistic regression was used to estimate the odds ratio (OR) and its 95 % CI for binary variables except for mortality. For both models, patient-specific offset terms were used to account for varying follow-up time. For mortality, Kaplan-Meier analysis was performed to obtain the risk of death by 12 months, and an unadjusted Cox proportional hazards regression was used to estimate the hazard ratio (HR) and its 95 % CI. As a sensitivity analysis, the stable and marginal decline groups were combined, and HRU outcomes were compared between this combined group and the significant decline group (See Appendix), i.e., FVC% decline <10 % vs. FVC% decline ≥10 %. Additionally, multivariable Cox proportional hazards regressions were constructed to assess factors associated with risk of mortality, hospitalization, and suspected AEx. For each model, the main independent variable of interest was the FVC% change group while the control variables consisted of physician’s main practice setting, patient characteristics and symptoms at IPF diagnosis, smoking status, GAP index, suspected AEx in the concurrent period, and use of prednisone and azathioprine in the concurrent period. The combination therapy of prednisone and azathioprine was included per the findings of the PANTHER-IPF clinical trial, which found the triple drug combination of prednisone, azathioprine, and n-acetylcysteine to significantly increase mortality risk relative to placebo [21]. In constructing the Cox regressions, the proportional hazards assumption was tested and found to be satisfied for the FVC% change group variables for all models. The HR and 95 % CI for each risk factor were estimated. All regression analyses used the generalized estimating equations (GEE) technique to account for correlation from the clustering of multiple patient charts contributed by the same pulmonologist. P-values for all pairwise comparisons of FVC% change groups were adjusted for multiple comparisons using a Bonferroni correction, and p-values that were less than 0.05 were considered to be statistically significant. All statistical analyses were performed using SAS version 9.3.

Results

Physician characteristics

A total of 168 pulmonologists participated in this study, of whom 69 (41.1 %) practiced in an academic setting. The practices were distributed across the Northeast (36.3 %), South (25.0 %), Midwest (20.8 %) and West (17.9 %) of the U.S. The mean (SD) number of years in practice for the pulmonologists was 15.0 (6.4), with each on average contributing data abstracted from 3 patient charts (Appendix: Table 9).

Patient characteristics

Four-hundred ninety IPF patients were included in this study, of which 250 (51.0 %) were classified as stable, 98 (20.0 %) were classified as having a marginal decline, and 142 (29.0 %) were classified as having a significant decline. The mean (SD) follow-up time for the entire sample was 583 (287) days with the average length of the concurrent and subsequent periods being 176 (56) and 407 (283) days, respectively. The majority of the IPF patients were male (68.4 %), and the average age was 61.1 (10.8) years. The majority of patients were of White race (75.3 %) and were enrolled in commercial/private insurance (48.6 %) or Medicare (43.7 %) (Table 1).
Table 1

Baseline characteristics by FVC% change group

By lung-function change category (based on relative change in FVC%)a
Stable [A]Marginal [B]Significant [C] P-value*
(N = 250)(N = 98)(N = 142)[C] vs. [A][C] vs. [B][B] vs. [A]
Male, N (%)167 (66.8 %)70 (71.4 %)98 (69.0 %)0.9990.9990.999
Age (years), mean (SD)60.8 (10.8)62.1 (9.6)60.9 (11.5)0.9990.9990.930
BMI, mean (SD)26.7 (4.9)26.5 (4.4)26.3 (4.6)0.9990.9990.999
Race, N (%)b
 White183 (73.2 %)82 (83.7 %)104 (73.2 %)0.9990.1930.098
 Black or African American34 (13.6 %)11 (11.2 %)24 (16.9 %)0.9990.6500.999
 Hispanic, Latino, or Spanish Origin26 (10.4 %)5 (5.1 %)13 (9.2 %)0.9990.6460.295
 Asian7 (2.8 %)1 (1.0 %)1 (0.7 %)0.4790.9990.952
 Other2 (0.8 %)0 (0.0 %)0 (0.0 %)
Insurance type, N (%)b
 Commercial/private insurance113 (45.2 %)45 (45.9 %)80 (56.3 %)0.1930.5020.999
 Medicare109 (43.6 %)44 (44.9 %)61 (43.0 %)0.9990.9990.999
 Medicaid26 (10.4 %)12 (12.2 %)17 (12.0 %)0.9990.9990.999
 Military insurance (VA or active military)9 (3.6 %)2 (2.0 %)3 (2.1 %)0.9990.9990.999
 Other0 (0.0 %)1 (1.0 %)0 (0.0 %)---
 No insurance8 (3.2 %)1 (1.0 %)1 (0.7 %)0.2280.9990.584
Smoking status at diagnosis, N (%)0.7890.9990.999
 Never smoked98 (39.2 %)44 (44.9 %)48 (33.8 %)
 Former smoker124 (49.6 %)42 (42.9 %)77 (54.2 %)
 Current smoker21 (8.4 %)11 (11.2 %)16 (11.3 %)
 Unknown/not sure7 (2.8 %)1 (1.0 %)1 (0.7 %)
Exposure to activities/ environmental agents, N (%)b
 Asbestos10 (4.0 %)3 (3.1 %)11 (7.7 %)0.3360.6500.999
 Farming/agriculture27 (10.8 %)9 (9.2 %)25 (17.6 %)0.2130.1310.999
 Hairdressing12 (4.8 %)4 (4.1 %)4 (2.8 %)0.9990.9990.999
 Metal dust18 (7.2 %)2 (2.0 %)10 (7.0 %)0.9990.1720.154
 Stone cutting/polishing7 (2.8 %)0 (0.0 %)6 (4.2 %)0.999<0.001*<0.001*
 Coal mining5 (2.0 %)1 (1.0 %)2 (1.4 %)0.9990.9990.999
 Other3 (1.2 %)3 (3.1 %)2 (1.4 %)0.9990.9990.669
 None182 (72.8 %)78 (79.6 %)92 (64.8 %)0.3400.037*0.598
Family history of pulmonary fibrosis, N (%)16 (6.4 %)6 (6.1 %)5 (3.5 %)0.5640.9230.999
Measurement period (days)
 Concurrent, mean (SD)172.8 (55.5)174.9 (53.7)181.6 (56.8)0.5750.9990.999
 Subsequent, mean (SD)438.3 (283.1)423.0 (280.0)340.1 (275.9)0.013*0.1180.999
 Total follow-up, mean (SD)611.1 (282.7)597.9 (285.8)521.7 (286.6)0.036*0.2250.999

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

bPhysicians were allowed to select multiple values for race, insurance type, and exposure to activities/environmental agents, so counts and percentages may not sum to the total N or 100 %

*All p-values were adjusted for multiple comparisons using the Bonferroni correction

Baseline characteristics by FVC% change group aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 % bPhysicians were allowed to select multiple values for race, insurance type, and exposure to activities/environmental agents, so counts and percentages may not sum to the total N or 100 % *All p-values were adjusted for multiple comparisons using the Bonferroni correction At the initial IPF diagnosis date, the mean (SD) FVC of the population was 2.5 (1.0) liters, and the mean (SD) FVC% was 60.4 % (26.1 %), while the mean (SD) DLCO percent predicted was 51.3 % (15.5 %). The mean GAP index was 3.3 (1.5) out of a maximum score of 8 (highest risk). The most common IPF symptoms at diagnosis were dyspnea or shortness of breath (87.6 %), cough (72.7 %), and fatigue or malaise (47.3 %). Gastroesophageal reflux disease was the most commonly reported comorbidity (31.2 %). Generally, patient characteristics were not significantly different among the three FVC% change groups. The significant decline group had lower DLCO and FEV1 values than the stable group (47.7 % vs. 53.4 % for DLCO, p = 0.033; 1.7 vs. 2.0 liters for FEV1, p = 0.021) (Table 2). The significant decline group also had higher rates of dyspnea and gradual, unintended weight loss than the stable group (93.0 % vs. 83.6 % for dyspnea, p = 0.030; 16.9 % vs. 6.8 % for unintended weight loss, p = 0.035).
Table 2

Clinical characteristics at initial IPF diagnosis by FVC% change group

By lung-function change category (based on relative change in FVC%)a
Stable [A]Marginal [B]Significant [C] P-value*
(N = 250)(N = 98)(N = 142)[C] vs. [A][C] vs. [A][C] vs. [A]
Comorbidities, N (%)b
 Gastroesophageal reflux disease82 (32.8 %)26 (26.5 %)45 (31.7 %)0.9990.9990.999
 Cardiac disorder43 (17.2 %)28 (28.6 %)34 (23.9 %)0.2600.9990.053
 Metabolic disorder38 (15.2 %)20 (20.4 %)29 (20.4 %)0.5000.9990.642
 Other vascular disorder32 (12.8 %)23 (23.5 %)27 (19.0 %)0.3000.9990.069
 Pulmonary hypertension31 (12.4 %)20 (20.4 %)16 (11.3 %)0.9990.0950.198
 Emphysema18 (7.2 %)8 (8.2 %)15 (10.6 %)0.7830.9990.999
 Other pulmonary disorder14 (5.6 %)7 (7.1 %)13 (9.2 %)0.4350.9990.999
Symptoms at IPF diagnosis, N (%)b
 Dyspnea/shortness of breath209 (83.6 %)88 (89.8 %)132 (93.0 %)0.030*0.9990.668
 Cough175 (70.0 %)71 (72.4 %)110 (77.5 %)0.4280.9990.999
 Fatigue or malaise107 (42.8 %)47 (48.0 %)78 (54.9 %)0.1450.9990.999
 Rapid, shallow breathing25 (10.0 %)11 (11.2 %)14 (9.9 %)0.9990.9990.999
 Gradual, unintended weight loss17 (6.8 %)9 (9.2 %)24 (16.9 %)0.035*0.3170.999
 Clubbing14 (5.6 %)11 (11.2 %)17 (12.0 %)0.3090.9990.321
 Other1 (0.4 %)0 (0.0 %)2 (1.4 %)---
GAP index, mean (SD)c 3.3 (1.5)3.5 (1.5)3.7 (1.4)0.1490.9990.774
Lung-function measures at IPF diagnosis, mean [median] (SD)
 FVC (liters)2.6 (1.1)2.4 (0.9)2.4 (1.0)0.8210.9990.796
 FVC%61.7 %(26.1 %)58.5 % (24.0 %)59.5 % (27.6 %)0.9990.9990.999
 FEV1 (liters)2.0 (0.9)1.8 (0.7)1.7 (0.6)0.021*0.9010.395
 FEV1/FVC79.6 % (12.6 %)79.9 % (11.8 %)80.7 % (12.5 %)0.9990.9990.999
 DLCO percent predicted53.4 % (14.4 %)51.2 % (16.1 %)47.7 % (16.5 %)0.033*0.5830.962

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

bPhysicians were allowed to select multiple values for comorbidities and symptoms, so counts and percentages may not sum to the total N or 100 %

cMissing values for DLCO were imputed using a single imputation method in which observed DLCO was regressed on patient's index FVC%, age, gender, BMI, smoking status at diagnosis, exposure to environmental agents, comorbidities (including cardiac disorder, pulmonary hypertension, emphysema, and gastroesophageal reflux disease), and symptoms at IPF diagnosis (including dyspnea/shortness of breath and gradual, unintended weight loss)

*All p-values were adjusted for multiple comparisons using the Bonferroni correction

Clinical characteristics at initial IPF diagnosis by FVC% change group aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 % bPhysicians were allowed to select multiple values for comorbidities and symptoms, so counts and percentages may not sum to the total N or 100 % cMissing values for DLCO were imputed using a single imputation method in which observed DLCO was regressed on patient's index FVC%, age, gender, BMI, smoking status at diagnosis, exposure to environmental agents, comorbidities (including cardiac disorder, pulmonary hypertension, emphysema, and gastroesophageal reflux disease), and symptoms at IPF diagnosis (including dyspnea/shortness of breath and gradual, unintended weight loss) *All p-values were adjusted for multiple comparisons using the Bonferroni correction

Unadjusted analysis of clinical characteristics and HRU in the concurrent period

No significant differences were observed between the FVC% change groups in the concurrent period with regards to rate or risk of suspected AEx and HRU. The exception to this was risk of progression, which was higher for the significant and marginal decline groups compared to the stable group (Table 3).
Table 3

Clinical characteristics and healthcare resource utilization in the concurrent period by FVC% change group

By lung-function change category (based on relative change in FVC%)a
Stable [A]Marginal [B]Significant [C]Relative effect measure (95 % CI)
(N = 250)(N = 98)(N = 142)[C] vs. [A][C] vs. [B][B] vs. [A]
6-Month IR per PatientIRR
Rate of suspected AEx0.210.250.251.20 (0.69–2.09)1.00 (0.55–1.82)1.20 (0.63–2.28)
6-Month RiskOR
Risk of suspected AEx14.1 %16.7 %20.4 %1.56 (0.78–3.15)1.27 (0.56–2.91)1.23 (0.56–2.70)
Risk of progression23.4 %38.7 %48.6 %3.09 (1.67–5.72)1.50 (0.75–3.00)2.07 (1.07–3.97)
6-Month IR per PatientIRR
Rate of IPF-related outpatient visits1.851.951.780.96 (0.82–1.12)0.91 (0.75–1.12)1.05 (0.87–1.27)
 Unscheduled and/or urgent care0.160.230.221.42 (0.64–3.15)0.97 (0.48–1.96)1.46 (0.76–2.80)
 For a suspected AEx0.170.190.191.16 (0.58–2.31)1.04 (0.52–2.09)1.11 (0.54–2.29)
Rate of IPF-related ER visits0.180.160.140.81 (0.31–2.11)0.87 (0.37–2.01)0.94 (0.40–2.17)
 For a suspected AEx0.040.020.051.15 (0.34–3.86)2.46 (0.41–14.72)0.47 (0.07–3.17)
Rate of IPF-related hospitalizations0.060.080.050.80 (0.20–3.12)0.59 (0.17–1.98)1.36 (0.35–5.20)
 For a suspected AEx0.040.060.040.96 (0.19–4.82)0.63 (0.17–2.32)1.52 (0.27–8.60)
 Rate of hospital days0.390.480.250.63 (0.10–3.82)0.52 (0.10–2.62)1.22 (0.28–5.26)
 Rate of ICU stays0.030.030.020.59 (0.07–4.97)0.47 (0.07–2.95)1.25 (0.21–7.58)
 Rate of ICU days0.080.180.070.79 (0.05–12.62)0.36 (0.03–4.05)2.16 (0.23–20.59)

AEx Acute exacerbation, IR incidence rate, IRR incidence rate ratio, OR odds ratio

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

Clinical characteristics and healthcare resource utilization in the concurrent period by FVC% change group AEx Acute exacerbation, IR incidence rate, IRR incidence rate ratio, OR odds ratio aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

Unadjusted analysis of clinical outcomes in the subsequent period

Significantly higher risk of worse clinical outcomes were observed in groups with greater FVC% decline, including risk of progression (significant vs. stable, >3-fold higher), risk of suspected AEx (significant vs. stable, >4-fold higher; marginal vs. stable, >2-fold higher), all-cause mortality (significant vs. stable, >5-fold higher; significant vs. marginal, 1.8-fold higher; marginal vs. stable, >2-fold higher), mortality due to IPF (significant vs. stable, >6-fold higher; significant vs. marginal, 1.9-fold higher; marginal vs. stable, >3-fold higher), and mortality due to a suspected AEx (significant vs. stable,>3-fold higher; marginal vs. stable, >3-fold higher) (Table 4). In the stable and marginal decline groups, mortality due to a suspected AEx was similar to all-cause and IPF-related mortality, indicating that suspected AEx was likely the main driver of mortality in these groups. However, in the significant decline group, mortality due to suspected AEx was approximately half that of all-cause and IPF-related mortality, indicating that progression of IPF might be the main driver of mortality in this group.
Table 4

Clinical outcomes in the subsequent period by FVC% change group

By lung-function change category (based on relative change in FVC%)a
Stable [A]Marginal [B]Significant [C]Relative effect measure (95 % CI)
(N = 250)(N = 98)(N = 142)[C] vs. [A][C] vs. [B][B] vs. [A]
12-Month IR per PatientIRR
Rate of suspected AEx0.260.470.742.87 (1.71–4.82)1.58 (0.95–2.64)1.82 (1.02–3.23)
12-Month RiskOR
Risk of suspected AEx19.2 %37.1 %50.9 %4.37 (2.09–9.16)1.76 (0.81–3.80)2.49 (1.28–4.82)
Risk of progression62.6 %76.2 %85.6 %3.56 (1.66–7.64)1.86 (0.81–4.26)1.92 (0.91–4.04)
Mortalityb Risk by 12 MonthsHR
 Death due to any cause6.4 %13.1 %28.0 %5.05 (2.75–9.27)1.85 (1.05–3.26)2.73 (1.51–4.94)
 Death due to IPF5.5 %10.3 %24.3 %6.23 (2.96–13.14)1.94 (1.01–3.70)3.22 (1.59–6.53)
 Death due to AEx5.0 %9.3 %13.1 %3.91 (1.56–9.84)1.22 (0.54–2.77)3.21 (1.41–7.30)

AEx acute exacerbation, IR incidence rate, IRR incidence rate ratio, OR odds ratio, HR hazard ratio

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

bKaplan-Meier survival analysis was used to estimate the risk of death by 12 months

Clinical outcomes in the subsequent period by FVC% change group AEx acute exacerbation, IR incidence rate, IRR incidence rate ratio, OR odds ratio, HR hazard ratio aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 % bKaplan-Meier survival analysis was used to estimate the risk of death by 12 months

Unadjusted analysis of HRU outcomes in the subsequent period

During the subsequent period, the overall IRs of outpatient visits, ER visits, and hospitalization were 2.39, 0.43, and 0.34 per patient-year, respectively. The corresponding overall 12-month risks of outpatient visits, ER visits, and hospitalization were 96.6 %, 21.5 % and 15.2 %, respectively. Significantly higher rates were observed in groups with greater FVC% decline for the following variables: outpatient visits for a suspected AEx, unscheduled and/or urgent care outpatient visits, hospitalization for a suspected AEx, treatments and medications prescribed at outpatient visits, arterial blood gas tests used in the ER setting, number of days in the hospital, ICU stays, and tests used in the hospital setting (Table 5). Similar results were found when the marginal and stable groups were combined and compared with the significant group (Appendix: Table 10).
Table 5

Healthcare resource utilization outcomes in the subsequent period by FVC% change group

By lung-function decline category (based on relative change in FVC%)a
Stable [A]Marginal [B]Significant [C]Relative effect measure (95 % CI)
(N = 250)(N = 98)(N = 142)[C] vs. [A][C] vs. [B][B] vs. [A]
12-Month IR per PatientIRR
Rate of IPF-related outpatient visits2.242.572.551.14 (0.89–1.46)0.99 (0.76–1.30)1.15 (0.91–1.45)
 Unscheduled and/or urgent care0.180.380.543.01 (1.51–5.97)1.41 (0.78–2.55)2.13 (1.05–4.34)
 For a suspected AEx0.190.330.542.81 (1.47–5.40)1.64 (0.86–3.11)1.72 (0.80–3.69)
Rate of outpatient visits indicating that the following medications/treatments were prescribed for IPF
 Prednisone1.061.161.601.51 (1.08–2.10)1.38 (1.02–1.86)1.10 (0.79–1.52)
 Azathioprine0.360.310.541.51 (0.78–2.93)1.72 (0.84–3.53)0.88 (0.44–1.76)
 N-acetylcysteine0.650.700.791.22 (0.79–1.89)1.13 (0.67–1.90)1.08 (0.69–1.70)
Rate of outpatient visits that included the following tests/procedures
 Arterial blood gas test0.170.230.342.04 (0.77–5.38)1.46 (0.53–4.03)1.40 (0.55–3.56)
 HRCT0.230.350.351.55 (0.74–3.21)1.02 (0.45–2.31)1.51 (0.76–2.99)
 Chest X-ray0.480.660.601.23 (0.75–2.02)0.90 (0.55–1.48)1.36 (0.84–2.20)
 Lung biopsy0.030.040.010.44 (0.02–8.70)0.31 (0.02–4.91)1.42 (0.13–15.70)
 Pulmonary rehabilitation0.180.190.261.44 (0.79–2.63)1.35 (0.58–3.11)1.07 (0.52–2.23)
Rate of IFP-related ER visits0.350.540.531.53 (0.71–3.28)0.98 (0.51–1.87)1.56 (0.66–3.71)
 For a suspected AEx0.130.220.292.22 (0.95–5.21)1.32 (0.60–2.87)1.69 (0.67–4.27)
Rate of ER visits that included the following tests/procedures
 Arterial blood gas test0.150.350.332.24 (1.01–4.99)0.95 (0.45–2.00)2.36 (1.01–5.49)
 HRCT0.090.180.202.17 (0.85–5.58)1.09 (0.37–3.22)1.99 (0.60–6.67)
 Chest X-ray0.200.280.301.51 (0.69–3.32)1.10 (0.55–2.21)1.37 (0.61–3.09)
 Supplemental oxygen therapy0.170.230.291.74 (0.73–4.14)1.26 (0.52–3.04)1.39 (0.46–4.20)
Rate of IPF-related hospitalizations0.240.320.612.53 (0.70–9.10)1.89 (0.94–3.78)1.34 (0.34–5.29)
 For a suspected AEx0.090.210.434.69 (1.84–11.99)2.05 (1.03–4.08)2.29 (0.82–6.35)
 Rate of hospital days1.132.325.254.63 (1.31–16.42)2.27 (0.86–5.97)2.05 (0.66–6.33)
 Rate of ICU stays0.050.170.264.95 (1.20–20.41)1.53 (0.59–3.99)3.23 (0.72–14.53)
 Rate of ICU days0.300.691.224.05 (0.79–20.91)1.75 (0.58–5.35)2.31 (0.54–9.83)
Rate of hospitalizations that included the following tests/procedures
 Arterial blood gas test0.100.190.353.58 (1.33–9.64)1.87 (0.73–4.80)1.92 (0.61–6.00)
 Mechanical ventilation0.040.110.143.29 (0.63–17.23)1.33 (0.38–4.70)2.47 (0.57–10.73)
 Non-invasive ventilation0.020.080.2210.17 (3.25–31.86)2.80 (1.05–7.51)3.63 (0.90–14.70)
 Supplemental oxygen therapy0.070.130.283.95 (1.38–11.29)2.11 (0.93–4.82)1.87 (0.62–5.66)
12-Month RiskOR
Risk of having ≥1 outpatient visit97.5 %97.3 %95.0 %0.48 (0.14–1.62)0.52 (0.12–2.20)0.93 (0.23–3.76)
 Unscheduled or urgent care11.4 %26.9 %34.5 %4.10 (1.95–8.63)1.43 (0.69–2.98)2.87 (1.39–5.92)
 For a suspected AEx12.7 %21.9 %33.8 %3.52 (1.62–7.67)1.82 (0.82–4.05)1.93 (0.90–4.15)
Risk of having ≥1 ER visit14.4 %29.4 %32.4 %2.85 (1.36–5.98)1.15 (0.53–2.52)2.47 (1.22–5.03)
 For a suspected AEx7.8 %16.7 %22.1 %3.33 (1.40–7.94)1.42 (0.57–3.54)2.35 (0.98–5.65)
Risk of having ≥1 hospitalizations7.8 %19.1 %30.0 %5.04 (2.13–11.93)1.82 (0.71–4.66)2.76 (1.14–6.70)
 Intensive care unit (ICU) stay2.4 %8.4 %12.4 %5.86 (1.43–24.01)1.56 (0.41–5.90)3.77 (0.88–16.03)
 For a suspected AEx5.9 %15.1 %27.8 %6.08 (2.45–15.07)2.16 (0.84–5.54)2.81 (1.10–7.20)

IR incidence rate, IRR incidence rate ratio, OR odds ratio

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

Healthcare resource utilization outcomes in the subsequent period by FVC% change group IR incidence rate, IRR incidence rate ratio, OR odds ratio aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable" was defined as decline <5 %. "Marginal" was defined as decline ≥5 % and <10 %, while "Significant" was defined as decline ≥10 %

Multivariable analysis

Results of the Cox proportional hazards regressions showed that greater FVC% decline was associated with a higher risk of mortality, hospitalization, and suspected AEx in the subsequent period, adjusting for demographic and clinical characteristics. In addition, suspected AEx in the concurrent period was found to be associated with higher risk of mortality (HR = 2.59, p < 0.001), hospitalization (HR = 1.86, p = 0.030), and subsequent suspected AEx (HR = 2.98, p < 0.001) in the subsequent period (Tables 6, 7, and 8).
Table 6

Multivariable Cox proportional hazards regression on mortality in the subsequent period

Mortalitya
Hazard ratio (95 % CI) P-value*
Race
 White vs. non-white0.70 (0.39–1.26)0.231
Lung-function decline group
 Marginal decline vs. stable2.38 (1.04–5.45)0.036*
 Significant decline vs. stable4.42 (2.01–9.71)<0.001*
BMI
 25–30 vs. < 250.53 (0.29–0.97)0.038*
 ≥30 vs. < 250.38 (0.18–0.80)0.012*
Comorbidities
 Cardiac disorder vs. no cardiac disorder1.63 (0.94–2.82)0.080
 Pulmonary hypertension vs. no pulmonary hypertension2.53 (1.33–4.80)0.005*
 Emphysema vs. no emphysema1.49 (0.67–3.35)0.328
 Gastroesophageal reflux disease vs. no gastroesophageal reflux disease1.10 (0.64–1.92)0.725
Smoking status
 History of smoking vs. no history of smoking1.08 (0.64–1.83)0.773
Suspected AEx in the concurrent period
 Yes vs. no2.59 (1.49–4.53)<0.001*
Use of prednisone and azathioprine in the concurrent period
 Both vs. neither2.48 (1.19–5.19)0.016*
 Prednisone only vs. neither1.41 (0.66–3.01)0.376
 Azathioprine only vs. neither1.11 (0.18–7.01)0.909
Symptoms at initial IPF diagnosis
 Dyspnea vs. no dyspnea1.29 (0.48–3.48)0.609
 Weight loss vs. no weight loss1.95 (1.02–3.73)0.044*
Physician's main practice setting
 Academic vs. non-academic0.95 (0.51–1.77)0.876
GAP index (per unit increase)b 1.19 (0.98–1.44)0.080

aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations

bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index

*P-values less than 0.05 are indicated with an asterisk (*)

Table 7

Multivariable Cox proportional hazards regression on hospitalization in the subsequent period

Hospitalizationa
Hazard Ratio (95 % CI) P-value*
Race
 White vs. non-white0.50 (0.32–0.79)0.003*
Lung-function decline group
 Marginal decline vs. stable2.50 (1.06–5.91)0.033*
 Significant decline vs. stable3.37 (1.62–7.00)<0.001*
BMI
 25–30 vs. <250.59 (0.34–1.03)0.061
 ≥30 vs. <250.95 (0.51–1.74)0.861
Comorbidities
 Cardiac disorder vs. no cardiac disorder1.87 (1.06–3.32)0.032*
 Pulmonary hypertension vs. no pulmonary hypertension2.09 (1.15–3.83)0.017*
 Emphysema vs. no emphysema1.44 (0.62–3.36)0.399
 Gastroesophageal reflux disease vs. no gastroesophageal reflux disease1.08 (0.67–1.73)0.746
Smoking status
 History of smoking vs. no history of smoking1.02 (0.61–1.70)0.935
Suspected AEx in the concurrent period
 Yes vs. no1.86 (1.06–3.26)0.030*
Use of prednisone and azathioprine in the concurrent period
 Both vs. neither1.24 (0.59–2.62)0.575
 Prednisone only vs. neither1.25 (0.72–2.16)0.428
 Azathioprine only vs. neither0.74 (0.09–6.38)0.780
Symptoms at initial IPF diagnosis
 Dyspnea vs. no dyspnea1.43 (0.43–4.80)0.562
 Weight loss vs. no weight loss1.45 (0.77–2.76)0.250
Physician's main practice setting
 Academic vs. non-academic0.89 (0.51–1.55)0.680
GAP index (per unit increase)b 1.23 (1.04–1.46)0.018*

aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations

bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index

*P-values less than 0.05 are indicated with an asterisk (*)

Table 8

Multivariable Cox proportional hazards regression on suspected acute exacerbation in the subsequent period

Suspected Acute Exacerbationa
Hazard Ratio (95 % CI) P-value*
Race
 White vs. non-white0.63 (0.45–0.88)0.007*
Lung-function decline group
 Marginal decline vs. stable2.02 (1.13–3.59)0.011*
 Significant decline vs. stable2.86 (1.69–4.85)<0.001*
BMI
 25–30 vs. <250.82 (0.53–1.26)0.362
 ≥30 vs. <250.75 (0.45–1.23)0.245
Comorbidities
 Cardiac disorder vs. no cardiac disorder1.57 (1.04–2.37)0.031*
 Pulmonary hypertension vs. no pulmonary hypertension1.65 (1.03–2.63)0.036*
 Emphysema vs. no emphysema1.89 (1.02–3.50)0.043*
 Gastroesophageal reflux disease vs. no gastroesophageal reflux disease1.07 (0.74–1.54)0.736
Smoking status
 History of smoking vs. no history of smoking0.91 (0.64–1.31)0.608
Suspected AEx in the concurrent period
 Yes vs. no2.98 (1.92–4.62)<0.001*
Use of prednisone and azathioprine in the concurrent period
 Both vs. neither1.40 (0.76–2.55)0.276
 Prednisone only vs. neither1.23 (0.81–1.87)0.335
 Azathioprine only vs. neither0.99 (0.32–3.05)0.980
Symptoms at initial IPF diagnosis
 Dyspnea vs. no dyspnea1.39 (0.68–2.83)0.368
 Weight loss vs. no weight loss1.16 (0.66–2.05)0.595
Physician's main practice setting
 Academic vs. non-academic1.02 (0.69–1.51)0.910
GAP index (per unit increase)b 1.07 (0.94–1.22)0.301

aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations

bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index

*P-values less than 0.05 are indicated with an asterisk (*)

Multivariable Cox proportional hazards regression on mortality in the subsequent period aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index *P-values less than 0.05 are indicated with an asterisk (*) Multivariable Cox proportional hazards regression on hospitalization in the subsequent period aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index *P-values less than 0.05 are indicated with an asterisk (*) Multivariable Cox proportional hazards regression on suspected acute exacerbation in the subsequent period aMultivariable Cox proportional hazard regression was used to estimate the hazard ratio, 95 % confidence interval and p-value, accounting for physician clustering using generalized estimating equations bThe hazard ratio for the GAP index was estimated for every one point increase in GAP index *P-values less than 0.05 are indicated with an asterisk (*)

Discussion

This study was a retrospective chart review of patients diagnosed with IPF designed to investigate the relationship of FVC% change with clinical and HRU outcomes. Overall, clinical characteristics and HRU were similar between FVC% change groups at initial IPF diagnosis and in the concurrent period. However, both unadjusted analysis and multivariable analysis showed that greater FVC% decline was associated with worse clinical outcomes and increased HRU during the subsequent period. In addition, experiencing a suspected AEx in the concurrent period was found to be a significant risk factor for mortality, hospitalization, and subsequent suspected AEx. To our knowledge, this is one of the largest chart review studies conducted for IPF patients in the U.S. and the only one that attempts to link FVC% change with HRU outcomes [16, 18, 22]. Results for clinical outcomes were similar to results from observational studies and randomized clinical trials [14, 16, 17, 23–26]. In particular, recent studies by Zappala et al. and Salisbury et al. have reported that patients with significant or marginal FVC declines were at higher risk of death compared to those with stable disease or not significant FVC decline [16, 26]. Results from the current study were reasonably concordant, especially for the comparison of the marginal FVC% decline and stable groups. Results for AEx were also in line with prior studies. For instance, Kondoh et al. found a higher risk of subsequent AEx for patients with a significant FVC decline (i.e., ≥10 %) at 6 months compared to those without a significant decline, reporting a HR of 2.6 (p = 0.049) [27]. The HR for our significant decline group relative to the stable group was similar at 2.86. Beyond comparable findings, our study adds to the IPF literature by assessing the association of FVC% change with HRU with a large cohort of IPF patients from a variety of practice settings. One recently published study reported that the proportion of hospitalization was 25 % among patients with IPF and that 37 % of hospitalizations resulted in an ICU stay [28]; our study reported 12-month risks of 15 % and 39 % for these outcomes, respectively, and additionally links them to FVC% decline. Comparison of our results to a claims study published in 2012 demonstrates that annual rates of outpatient visits and ER visits are similar, and the annual rate of hospitalization in our study is slightly lower (0.53 vs. 0.34) than the claims study [12]. Our lower rate of hospitalization is likely attributed to the fact that 1) the claims study reported all-cause hospitalizations, while our study focused on IPF-related hospitalizations; 2) we required patients to have a second FVC measurement approximately 6 months after diagnosis. Requiring a second FVC measurement may have excluded the most severe of patients who may have been hospitalized and died early in their disease course. In addition to evaluating the relationship between FVC% change and outcomes, our multivariable models provide information on patient characteristics associated with mortality, hospitalization, and AEx, adding to the literature on risk factors for these outcomes. AEx in the concurrent period was a consistent and strong risk factor across all these outcomes and was the strongest predictor of a subsequent AEx. Combination therapy with prednisone and azathioprine was associated with a significantly higher mortality risk relative to use of neither drug with an HR of 2.48 (p = 0.016), which is consistent with the findings of the PANTHER-IPF trial [21]. Select comorbidities were also significant predictors of worse outcomes as determined through our multivariable Cox regression models. In particular, pulmonary hypertension was a strong risk factor of all three adverse outcomes. While our result for mortality is concordant with the findings of numerous other studies, there is only a single prior report attesting to a relationship between pulmonary hypertension and AEx [29-32]. Furthermore, our finding of non-Caucasian patients being associated with worse outcomes adds to the literature on the disparities in health outcomes among IPF patients.

Strengths and limitations

Our study has several strengths. The study population came from different treating settings, including patients treated in the community, which is likely more reflective of real-world practice in IPF. A large number of patient charts were contributed by pulmonologists from a national physician panel, allowing for a broad sample of IPF patients across the U.S. Patient charts provided more comprehensive individual patient details and clinical granularity, which are not commonly collected in administrative claims data. Thus, our data source helps to better understand and capture underlying risk factors and allowed us to adjust for important observed confounders in the multivariable regression models. IPF diagnosis was confirmed by HRCT or biopsy as reported by the pulmonologist and is likely to be more accurate than a claims-based IPF patient identification algorithm. This study is subject to the limitations of retrospective studies. To account for temporal trends in IPF care and management, we sampled patients who were recently diagnosed with IPF. Consequently, the findings may not be applicable to patients diagnosed with IPF prior to 2011. Also, there is the potential for incomplete patient chart information and data entry errors from participating pulmonologists. To address these possible limitations, patient inclusion criteria required pulmonologist access to the patient’s complete inpatient and outpatient medical records related to IPF post-diagnosis. Real-time data checks for consistency and logic of responses were included in the online case report form to reduce the likelihood of data entry errors, such as ensuring that the dates of specific IPF-related events collected in the follow-up period were after the initial IPF diagnosis date. Our study did not further stratify patients who had smaller declines or improvement in FVC% within the stable group. Even though this group was classified as being stable, patients in this group had reasonably high risk of progression (62.6 %), suspected AEx (19.2 %), and all-cause mortality (6.4 %) over 12 months (Table 4). They also utilized a significant amount of resources in the subsequent period. Future studies teasing out the impact of smaller declines in FVC%, perhaps in conjunction with other measures of progression, may provide insight. The pulmonologist-reported suspected AEx in this study is another limitation, because the determination likely does not reflect the definition established by Collard et al. in 2007 [3]. More specifically, pulmonologists may use less stringent criteria in their practice settings when classifying AEx due to their patients’ inability to undergo certain procedures required by the definition. Consequently, the rate of suspected AEx observed in this study may be higher than the rate of AEx reported in clinical trials [5, 33]. We speculate that some cases of increased respiratory compromise for other reasons may have been erroneously labeled as a suspected AEx, a term that has indeed been recently defined in the literature [34]. On the other hand, our study provides insight into how AEx are perceived and defined in real-world clinical practice. As demonstrated in our study, these events still have profound implications on downstream HRU even if based on less strict criteria. Lastly, our study might not have included patients on both ends of the disease spectrum. Specifically, requiring that eligible patients have two FVC measures may have excluded patients with more severe disease who were unable to perform lung-function tests or those who did not survive long enough to receive the subsequent FVC assessment. On the other end of the spectrum, there might have been some milder, more stable patients who were not seen or did not have lung-function testing within the timeline specified in this study.

Conclusions

In summary, our study demonstrates that greater FVC% decline in the first 6 months after the initial IPF diagnosis is associated with worse clinical outcome and increased IPF-related HRU. The incremental burden of FVC% decline on patients and the healthcare system may underscore the importance of preservation of lung function in IPF patients. Future studies examining treatments that help slow lung function deterioration are warranted along with additional studies identifying predictors of patients at greatest risk of FVC% decline in the months following diagnosis and evaluating variation in effect of lung-function change across subgroups of patients. Our study further highlights the need for definitions and categorization of IPF worsening events that are more applicable to IPF physicians’ daily practice and capture less severe events than those defined by the Collard definition. Finally, management options that ameliorate declines in FVC may have an impact on and help to improve health outcomes in patients with IPF.
Table 9

Physician characteristics

Physicians (N = 168)
N (%) or Mean (SD)Median[Range]
Practice characteristics
 Main practice setting, N (%)
  Academic69 (41.1 %)
  Non-academic99 (58.9 %)
Practice location, N (%)
 Northeast61 (36.3 %)
 South42 (25.0 %)
 Midwest35 (20.8 %)
 West30 (17.9 %)
Physician characteristics
 Years in pulmonology practice, mean (SD) median [min, max]15.0 (6.4)14[3, 30]
 Percentage of time spent in inpatient vs. outpatient settings, mean (SD) median [min, max]
  Inpatient settings39.0 (17.2)40[5, 90]
  Outpatient settings61.0 (17.2)60[10, 95]
 Participation in IPF-related research during the past year, N (%)a,b
  IPF clinical trial involvement20 (11.9 %)
  Other IPF research involvement13 (7.7 %)
  None138 (82.1 %)
Physician-reported profile of treated patients (January 1, 2011 – June 20, 2013)
 Number of patients diagnosed with interstitial lung disease (ILD), mean (SD) median [min, max]132.7 (182.4)60[4, 1000]
  Number of ILD patients diagnosed with IPF76.2 (93.5)45[3, 600]
  Number of deaths within 6 months of IPF diagnosis10.0 (17.4)5[0, 150]
  Number of deaths within 12 months of IPF diagnosis20.6 (38.7)8[0, 350]
  Percent of ILD patients diagnosed with IPF68.4 (26.3)72[8, 100]
  Percent of IPF patients dying within 6 months of IPF diagnosis12.3 (11.4)10[0, 60]
  Percent of IPF patients dying within 12 months of IPF diagnosis26.0 (22.6)20[0, 94]
Number of charts abstractedc, mean (SD) median [min, max]2.9 (1.2)3[1, 4]

aResearch involvement includes IPF-related basic clinical research, epidemiology studies, outcomes studies, etc.

bPhysicians were allowed to select multiple values for type of research involvement, so counts and percentages may not sum to the total N or 100 %

cPhysicians have been permitted to abstract a maximum of 4 patient charts

Table 10

Healthcare resource utilization outcomes in the subsequent period

By lung-function change category (based on relative change in FVC%)a
All PatientsStable or Marginal (Δ < 10 %) [A]Significant (Δ ≥ 10 %) [B]Relative Effect Measure (95 % CI)
(N = 490)(N = 348)(N = 142)[B] vs. [A]
Subsequent Period
12-Month IR per PatientIRR
Rate of IPF-related outpatient visits2.392.342.561.09 (0.91–1.32)
 Unscheduled and/or urgent care0.300.240.552.25 (1.45–3.50)
 For a suspected AEx0.300.240.542.28 (1.47–3.51)
Rate of outpatient visits indicating that the following medications/treatments were prescribed for IPF
 Prednisone1.221.091.601.47 (1.16–1.85)
 Azathioprine0.390.340.541.57 (0.96–2.57)
 N-acetylcysteine0.700.670.791.19 (0.85–1.67)
Rate of outpatient visits that included the following tests/procedures
 Arterial blood gas test0.250.190.351.80 (0.90–3.60)
 High-resolution computed tomography0.290.270.361.32 (0.75–2.33)
 Chest X-ray0.550.540.601.11 (0.77–1.59)
 Lung biopsy0.030.030.010.39 (0.05–3.44)
 Pulmonary rehabilitation0.210.190.261.40 (0.86–2.27)
Rate of IPF-related ER visits0.430.410.531.30 (0.80–2.12)
 For a suspected AEx0.190.160.291.84 (1.04–3.27)
Rate of ER visits that included the following tests/procedures
 Arterial blood gas test0.240.210.341.63 (0.95–2.81)
 High-resolution computed tomography0.140.120.201.71 (0.88–3.30)
 Chest X-ray0.240.220.301.36 (0.79–2.32)
 Supplemental oxygen therapy0.210.180.291.58 (0.89–2.79)
Rate of IFP-related hospitalizations0.340.260.612.31 (1.10–4.85)
 For a suspected AEx0.200.130.433.46 (2.00–5.98)
 Rate of hospital days not for a suspected AEx0.530.440.811.84 (0.38–9.07)
 Rate of hospital days for a suspected AEx2.061.074.504.19 (1.69–10.41)
 Rate of ICU stays0.130.090.283.07 (1.38–6.83)
 Rate of ICU days0.620.421.222.92 (1.12–7.63)
Rate of hospitalizations that included the following tests/procedures
 Arterial blood gas test0.180.120.362.87 (1.48–5.54)
 Mechanical ventilation0.080.070.162.47 (0.85–7.12)
 Non-invasive ventilation0.080.040.205.50 (2.90–10.45)
 Supplemental oxygen therapy0.130.090.283.22 (1.69–6.17)

IR Incidence rate, IRR Incidence rate ratio

aLung-function change categories were defined as the relative change in FVC% from index to approximately 6 months following IPF diagnosis. "Stable or Marginal" was defined as decline less than 10 %, while "Significant" was defined as decline greater than or equal to 10 %

  28 in total

1.  Changes in clinical and physiologic variables predict survival in idiopathic pulmonary fibrosis.

Authors:  Harold R Collard; Talmadge E King; Becki Bucher Bartelson; Jason S Vourlekis; Marvin I Schwarz; Kevin K Brown
Journal:  Am J Respir Crit Care Med       Date:  2003-05-28       Impact factor: 21.405

2.  The clinical course of patients with idiopathic pulmonary fibrosis.

Authors:  Fernando J Martinez; Sharon Safrin; Derek Weycker; Karen M Starko; Williamson Z Bradford; Talmadge E King; Kevin R Flaherty; David A Schwartz; Paul W Noble; Ganesh Raghu; Kevin K Brown
Journal:  Ann Intern Med       Date:  2005-06-21       Impact factor: 25.391

3.  Prevalence and outcomes of pulmonary arterial hypertension in advanced idiopathic pulmonary fibrosis.

Authors:  Christopher J Lettieri; Steven D Nathan; Scott D Barnett; Shahzad Ahmad; Andrew F Shorr
Journal:  Chest       Date:  2006-03       Impact factor: 9.410

Review 4.  Health-related quality of life in patients with idiopathic pulmonary fibrosis: a systematic review.

Authors:  J J Swigris; W G Kuschner; S S Jacobs; S R Wilson; M K Gould
Journal:  Thorax       Date:  2005-07       Impact factor: 9.139

5.  Analyses of efficacy end points in a controlled trial of interferon-gamma1b for idiopathic pulmonary fibrosis.

Authors:  Talmadge E King; Sharon Safrin; Karen M Starko; Kevin K Brown; Paul W Noble; Ganesh Raghu; David A Schwartz
Journal:  Chest       Date:  2005-01       Impact factor: 9.410

6.  Effect of preoperative pulmonary artery pressure on early survival after lung transplantation for idiopathic pulmonary fibrosis.

Authors:  T P M Whelan; J M Dunitz; R F Kelly; L B Edwards; C S Herrington; M I Hertz; P S Dahlberg
Journal:  J Heart Lung Transplant       Date:  2005-09       Impact factor: 10.247

7.  Quality of life of idiopathic pulmonary fibrosis patients.

Authors:  J De Vries; B L Kessels; M Drent
Journal:  Eur Respir J       Date:  2001-05       Impact factor: 16.671

8.  Pulmonary hypertension in patients with idiopathic pulmonary fibrosis.

Authors:  Hassan F Nadrous; Patricia A Pellikka; Michael J Krowka; Karen L Swanson; Nithima Chaowalit; Paul A Decker; Jay H Ryu
Journal:  Chest       Date:  2005-10       Impact factor: 9.410

9.  Physiology is a stronger predictor of survival than pathology in fibrotic interstitial pneumonia.

Authors:  Yangjin Jegal; Dong Soon Kim; Tae Sun Shim; Chae-Man Lim; Sang Do Lee; Younsuck Koh; Woo Sung Kim; Won Dong Kim; Jin Seong Lee; William D Travis; Masanori Kitaichi; Thomas V Colby
Journal:  Am J Respir Crit Care Med       Date:  2005-01-07       Impact factor: 21.405

10.  Prognostic implications of physiologic and radiographic changes in idiopathic interstitial pneumonia.

Authors:  Kevin R Flaherty; Jeanette A Mumford; Susan Murray; Ella A Kazerooni; Barry H Gross; Thomas V Colby; William D Travis; Andrew Flint; Galen B Toews; Joseph P Lynch; Fernando J Martinez
Journal:  Am J Respir Crit Care Med       Date:  2003-05-28       Impact factor: 21.405

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  12 in total

1.  Radiomics for the Prediction of Response to Antifibrotic Treatment in Patients with Idiopathic Pulmonary Fibrosis: A Pilot Study.

Authors:  Cheng-Chun Yang; Chin-Yu Chen; Yu-Ting Kuo; Ching-Chung Ko; Wen-Jui Wu; Chia-Hao Liang; Chun-Ho Yun; Wei-Ming Huang
Journal:  Diagnostics (Basel)       Date:  2022-04-15

Review 2.  Idiopathic Pulmonary Fibrosis: Best Practice in Monitoring and Managing a Relentless Fibrotic Disease.

Authors:  Wim A Wuyts; Marlies Wijsenbeek; Benjamin Bondue; Demosthenes Bouros; Paul Bresser; Carlos Robalo Cordeiro; Ole Hilberg; Jesper Magnusson; Effrosyni D Manali; António Morais; Spyridon Papiris; Saher Shaker; Marcel Veltkamp; Elisabeth Bendstrup
Journal:  Respiration       Date:  2019-12-12       Impact factor: 3.580

3.  Bronchoalveolar lavage cell profiles and proteins concentrations can be used to phenotype extrinsic allergic alveolitis patients.

Authors:  Martina Sterclova; Magdalena Smetakova; Ludek Stehlik; Jelena Skibova; Martina Vasakova
Journal:  Multidiscip Respir Med       Date:  2019-03-12

4.  Serum decorin is a potential prognostic biomarker in patients with acute exacerbation of idiopathic pulmonary fibrosis.

Authors:  Takefumi Nikaido; Yoshinori Tanino; Xintao Wang; Yuki Sato; Ryuichi Togawa; Masami Kikuchi; Kenichi Misa; Kazue Saito; Naoko Fukuhara; Takaya Kawamata; Mami Rikimaru; Takashi Umeda; Julia Morimoto; Tatsuhiko Koizumi; Yasuhito Suzuki; Kenichiro Hirai; Manabu Uematsu; Hiroyuki Minemura; Atsuro Fukuhara; Suguru Sato; Junpei Saito; Hiroshi Yokouchi; Kenya Kanazawa; Yoko Shibata
Journal:  J Thorac Dis       Date:  2018-09       Impact factor: 2.895

5.  Acute exacerbations of fibrosing interstitial lung disease associated with connective tissue diseases: a population-based study.

Authors:  Mengshu Cao; Jian Sheng; Xiaohua Qiu; Dandan Wang; Dongmei Wang; Yang Wang; Yonglong Xiao; Hourong Cai
Journal:  BMC Pulm Med       Date:  2019-11-14       Impact factor: 3.317

6.  First-in-human high-cumulative-dose stem cell therapy in idiopathic pulmonary fibrosis with rapid lung function decline.

Authors:  Alexander Averyanov; Irina Koroleva; Mikhail Konoplyannikov; Veronika Revkova; Victor Lesnyak; Vladimir Kalsin; Olesya Danilevskaya; Alexey Nikitin; Anna Sotnikova; Svetlana Kotova; Vladimir Baklaushev
Journal:  Stem Cells Transl Med       Date:  2019-10-15       Impact factor: 6.940

7.  Baseline High-Resolution CT Findings Predict Acute Exacerbation of Idiopathic Pulmonary Fibrosis: German and Japanese Cohort Study.

Authors:  Chihiro Hirano; Shinichiro Ohshimo; Yasushi Horimasu; Hiroshi Iwamoto; Kazunori Fujitaka; Hironobu Hamada; Nobuoki Kohno; Daisuke Komoto; Kazuo Awai; Nobuaki Shime; Francesco Bonella; Josune Guzman; Hilmar Kühl; Ulrich Costabel; Noboru Hattori
Journal:  J Clin Med       Date:  2019-11-24       Impact factor: 4.241

8.  Parametric Time-to-Event Model for Acute Exacerbations in Idiopathic Pulmonary Fibrosis.

Authors:  Fei Tang; Benjamin Weber; Susanne Stowasser; Julia Korell
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-01-25

Review 9.  Acute Exacerbation in Interstitial Lung Disease.

Authors:  Gabriela Leuschner; Jürgen Behr
Journal:  Front Med (Lausanne)       Date:  2017-10-23

Review 10.  Biomarkers in Progressive Fibrosing Interstitial Lung Disease: Optimizing Diagnosis, Prognosis, and Treatment Response.

Authors:  Willis S Bowman; Gabrielle A Echt; Justin M Oldham
Journal:  Front Med (Lausanne)       Date:  2021-05-10
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