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First published online on March 30, 2007
Chest, doi:10.1378/chest.06-2784
doi:10.1378/chest.06-2784
(Chest. 2007; 131:1448-1453)
© 2007 American College of Chest Physicians
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Body Mass Index and Mortality in Patients With Idiopathic Pulmonary Fibrosis*

Mazen Alakhras, MD; Paul A. Decker, MS; Hassan F. Nadrous, MD, FCCP; Maria Collazo-Clavell, MD and Jay H. Ryu, MD, FCCP

* From the Divisions of Pulmonary and Critical Care Medicine (Drs. Alakhras, Nadrous, Ryu), Biostatistics (Mr. Decker), and Endocrinology, Diabetes, Metabolism, and Nutrition (Drs. Collazo-Clavell), Mayo Clinic, Rochester, MN.

Correspondence to: Jay H. Ryu, MD, FCCP, Division of Pulmonary and Critical Care Medicine, Desk East 18, Mayo Clinic, 200 First St SW, Rochester, MN 55905; e-mail: ryu.jay{at}mayo.edu

Abstract

Background: To examine the relationship between body mass index (BMI) and mortality in patients with idiopathic pulmonary fibrosis (IPF).

Methods: We studied a cohort of patients with IPF who were seen at the Mayo Clinic Rochester from 1994 through 1996. These patients met the current consensus definition of IPF. We excluded patients who had received prior treatment for IPF, had no follow-up data, or had no pulmonary function results available at the index visit.

Results: Of the 197 patients fulfilling the inclusion criteria, the mean (± SD) age was 71.4 ± 8.9 years, 137 patients (70%) were men, and the mean BMI was 28.2 ± 4.6. These patients were categorized by BMI into the following three groups: < 25; 25 to 30; and ≥ 30. There were 46 patients (23%) with a BMI of < 25 who had a median survival time of 3.6 years (1-year survival rate, 76% [95% confidence interval (CI), 65 to 90%]; 3-year survival rate, 54% [95% CI, 41 to 70%]). The second group consisted of 85 patients (43%) with a BMI between 25 and 30 who had a median survival time of 3.8 years (1-year survival rate, 84% [95% CI, 76 to 92%]; 3-year survival rate, 58% [95% CI, 48 to 70%]). The final group consisted of 66 patients (34%) with a BMI of ≥ 30 and who had a median survival time of 5.8 years (1-year survival rate, 91% [95% CI, 84 to 98%]; 3-year survival rate, 69% [95% CI, 58 to 81%]). Using a proportional hazards regression model, survival was significantly associated with BMI (hazard ratio, 0.93 for each 1-U increase in BMI; 95% CI, 0.89 to 0.97; p = 0.002) with increased BMI being associated with better survival.

Conclusion: Higher BMI was associated with better survival in patients with IPF.

Key Words: body mass index • interstitial lung disease • mortality • nutrition • prognosis • pulmonary fibrosis

Idiopathic pulmonary fibrosis (IPF) is the most common form of interstitial lung disease.123 IPF is defined as a specific form of chronic fibrosing interstitial pneumonia of unknown cause that is characterized by the histologic pattern of usual interstitial pneumonia (UIP).24 Although the precise incidence and prevalence of IPF are not known,5 a recent study6 from the United Kingdom reported a doubling of the estimated incidence of IPF between 1990 and 2003. This increase was not attributable to the aging of the population nor to the increased ascertainment of milder cases.

In most patients, IPF gradually worsens and is associated with a median survival time of approximately 2 to 3 years after diagnosis.123789 There currently is no effective therapy.101112 Several studies8913141516 have attempted to identify prognosticators for predicting survival in patients with IPF. In general, worse prognosis has been associated with older age, more severe physiologic impairment, greater radiologic extent of disease, and the presence of pulmonary hypertension at presentation.8917 In addition, evidence of disease progression, as documented by worsening pulmonary function parameters, has also been correlated with worse survival.13141516

Previous studies have shown that high body mass index (BMI) is a good prognostic sign in patients with COPD and chronic respiratory insufficiency.18192021222324 In the present study, we examined the relationship between BMI and survival in patients with IPF.

Materials and Methods

Study Population
Using a computer-assisted search, 487 patients with IPF who had been evaluated at Mayo Clinic Rochester during the period of January 1, 1994, to December 31, 1996, were identified, as previously described.25 The clinical, radiologic, and physiologic features for this population have been described previously.25 We excluded patients with previous treatment for IPF, no follow-up data, or no pulmonary function testing (PFT) results at the time of their initial visit to our medical center (the index visit). The diagnosis of IPF met the current American Thoracic Society/European Respiratory Society consensus definition,2 and the study group consisted of 197 patients with compatible clinical presentation plus either a histopathologic evidence of UIP on surgical lung biopsy specimens (n = 19) or characteristic findings on high-resolution CT (HRCT) scans. HRCT scans were read by an experienced pulmonary radiologist and interpreted as showing typical findings of UIP. This study was approved by the Mayo Foundation Institutional Review Board.

Clinical Data Collection
The clinical data, laboratory results, pulmonary function data, HRCT scan findings, and lung biopsy results from the initial evaluation at our medical center were extracted from the medical records. Treatments for IPF prior to and after the index visit date, including oxygen therapy, were also recorded. We determined the vital status of patients by reviewing medical records and death certificates as well as by phone interviews.

The baseline PFT was defined as the testing performed at the Mayo Clinic Rochester closest to the index visit, limited to testing within 90 days prior to the index visit date or 14 days following it. BMI (in kilograms per square meter) was calculated from the data obtained at the time of the baseline PFT.

PFT was performed using equipment (models 1070 and 1085; Medical Graphics; St. Paul, MN) that was calibrated daily to perform testing to American Thoracic Society specifications, as previously described.25 PFT included the measurement of lung volumes to total lung capacity determined by plethysmography, spirometry including FVC, FEV1, diffusing capacity of the lung for carbon monoxide (DLCO), and arterial oxygen saturation at rest and with exercise.

Statistical Analysis
Baseline characteristics were compared across the BMI groups using a Fisher exact test for categoric variables and analysis of variance (ANOVA) for continuous variables. For survival analysis, time zero was defined as the index visit, which was the date that the patient was first seen at the Mayo Clinic Rochester during the study period (ie, January 1, 1994, to December 31, 1996). Cumulative survival probabilities were estimated using the Kaplan-Meier method.26 Cox proportional hazards regression was used to examine the association of selected variables with survival.27 In all cases, p values < 0.05 were considered to be statistically significant.

Results

Patient Characteristics
Baseline characteristics of the study cohort of 197 patients are summarized in Table 1 . The mean ± SD age was 71.4 ± 8.9 years (median age, 72.9 years; age range, 42 to 93 years), and 137 patients (70%) were men. The mean BMI was 28.2 ± 4.6. These patients were categorized by BMI into the following three groups: < 25 or normal to underweight (n = 46; 23%); 25 to 30 or overweight (n = 85; 43%); and ≥ 30 or obese (n = 66; 34%). The group with a BMI of < 25 included four patients with a BMI of < 18.5 (underweight). The group with a BMI ≥ 30 included 12 patients with a BMI of 35 to 40 and 2 patients with a BMI of > 40. There was no statistically significant differences among the three groups regarding age, gender, smoking status, baseline pulmonary function results, or recommended treatment at the index visit (Tables 1, 2 ).


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Table 1. Patient Characteristics*

 

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Table 2. Baseline Pulmonary Function*

 
Survival
The patients with a BMI of < 25 had a median survival time of 3.6 years with a 1-year survival rate of 76% (95% confidence interval [CI], 65 to 90%) and a 3-year survival rate of 54% (95% CI, 41 to 70%). The second group with a BMI between 25 and 30 had a median survival time of 3.8 years, a 1-year survival rate of 84% (95% CI, 76 to 92%), and a 3-year survival rate of 58% (95% CI, 48 to 70%). The final group, with a BMI of ≥ 30, had a median survival time of 5.8 years, a 1-year survival rate of 91% (95% CI, 84 to 98%), and 3-year survival rate of 69% (95% CI, 58 to 81%) [Fig 1 ].


Figure 1
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Figure 1. Survival analysis by BMI groups. Survival time was significantly associated with BMI (HR, 0.93 for each 1-U increase in BMI; 95% CI, 0.89 to 0.97; p = 0.002), with increased BMI being associated with better survival time.

 
Using a proportional hazards regression model, with survival as the dependent variable and BMI modeled as a continuous variable as the independent variable, survival was significantly associated with BMI (hazard ratio [HR], 0.93 for each 1-U increase in BMI; 95% CI, 0.89 to 0.97; p = 0.002), with increased BMI being associated with better survival time. We also investigated the univariable effect of known predictors of survival in IPF patients. The following variables were associated with survival: male gender (HR, 1.61; 95% CI, 1.05 to 2.48; p = 0.030), diagnosis by open lung biopsy (HR, 1.85; 95% CI, 1.04 to 3.31; p = 0.038), percent predicted FVC (HR, 0.99; 95% CI, 0.98 to 1.0; p = 0.023), percent predicted DLCO (HR, 0.97; 95% CI, 0.96 to 0.98; p < 0.001), and oxygen saturation with exercise (HR, 0.93; 95% CI, 0.89 to 0.96; p < 0.001). Age at the index visit (HR, 1.01; 95% CI, 0.99 to 1.03; p = 0.59), having ever smoked (HR, 0.99; 95% CI, 0.65 to 1.52; p = 0.98), recommended treatment (HR for prednisone therapy, 1.50 [95% CI, 0.81 to 2.78]; HR for colchicine therapy, 1.18 [95% CI, 0.79 to 1.78]; HR for both prednisone and colchicine therapy, 2.48 [95% CI, 0.88 to 6.95]; and HR other treatment, 1.08 [95% CI, 0.15 to 7.86]; p = 0.39), and oxygen saturation at rest (HR, 0.99; 95% CI, 0.90 to 1.08; p = 0.092) were not associated with survival. All of the known predictors listed above were included in a multivariable model with BMI, and BMI was still significantly associated with survival (HR, 0.86; 95% CI, 0.79 to 0.94; p < 0.001). Additionally, a multivariable model was fit with the predictors listed above excluding oxygen saturation at rest and exercise since these data were not captured for every subject and similar results were obtained for BMI (HR, 0.95; 95% CI, 0.90 to 0.99; p = 0.029).

Discussion

In this study, we found higher BMI to be associated with longer survival time in patients with IPF. To our knowledge, this is the first study examining the relationship between BMI and survival in patients with this disease. Most of the studies relating body composition abnormalities and chronic lung diseases have focused on individuals with COPD in whom underweight status is associated with increased mortality independent of the severity of airflow obstruction.182021 In patients with COPD, an index consisting of BMI, degree of airflow obstruction and dyspnea, and exercise capacity (ie, the BODE index)24 has been determined to be an important predictor of death from respiratory causes and all-cause mortality. Individuals with moderate-to-severe COPD are frequently underweight, which has been attributed, in part, to elevated activity-related energy expenditure and hypermetabolism as consequence of systemic inflammation associated with COPD.28 Undernutrition is also a major problem in patients with cystic fibrosis in whom poor nutritional status is associated with poor pulmonary function and decreased survival time.2930 The majority of our patients with IPF were not underweight.

Cano and colleagues23 found nutritional depletion, as assessed by BMI, to be one of the predictive factors of mortality in 446 subjects with chronic respiratory failure of various causes. This cohort included 162 subjects with restrictive disorders that consisted mainly of chest wall diseases and kyphoscoliosis; it was not stated how many of the patients had interstitial lung diseases or IPF. In a study of Dutch coal miners,31 the risk of mortality from COPD was increased in people who were underweight compared to those who were normal weight or overweight.

The observation of improved survival in patients with IPF and higher BMI seems counterintuitive. Excess weight and obesity are well-recognized risk factors for increased morbidity and mortality.3233 To our knowledge, improved survival with increased BMI has not been described in patients with other interstitial lung diseases. However, this so called inverse epidemiology has been described in patients with other chronic conditions such as congestive heart failure and end-stage renal disease.34 BMI may influence the underlying disease process or clinical manifestations in an unexpected manner. It is also possible that BMI may influence the response to pharmacologic therapy or perhaps modify the risk of adverse effects from such treatments. For example, BMI has been shown to influence the response to inhaled corticosteroids in patients with asthma.35 It is interesting to note that a similar correlation has been noted in patients with COPD with a BMI of ≥ 30 in whom mortality was lower compared to those with a normal BMI; this effect of BMI was stronger on COPD mortality than that on all-cause mortality.21

Cytokines are recognized as playing an important role in the pathophysiology of IPF. There remains active debate as to the etiologic role of inflammation in the fibrosis that ensues.36 Obesity itself is associated with a state of chronic inflammation. Adipocytes, once thought to serve solely for energy storage, are active modulators of several physiologic processes through the secretion of various adipocytokines.3738394041 Adiponectin, which is inversely proportional to adiposity, has several antiinflammatory effects via interleukin (IL)-1 and IL-10 production.37383940 Leptin and resistin, both directly proportional to adiposity, promote inflammatory states by the induction of tumor necrosis factor-{alpha} and IL-6.37383940 High leptin levels, however, have a positive effect on adaptive immunity.37383940 In mice, leptin protects T lymphocytes from apoptosis; modulates T-cell proliferation and activation; and influences cytokine production, monocyte activation, and phagocytosis.373941 These changes can potentially offer protection against infection. It is important to remember that changes in cytokine production observed with excess weight are exerted by visceral fat. Visceral adiposity is not measured by BMI. Hence, what role these processes may play in patients with IPF remains a matter of speculation.

Finally, a potentially protective effect toward improved survival with higher BMI is inferred by improved nutrition. Malnutrition is associated with thymic atrophy, reduced T-cell function, and increased susceptibility to infection.41 Malnutrition also increases an individual’s susceptibility to the "ravages" of inflammation that potentially impact survival.37

There are several limitations to this study. This was a retrospective analysis, and the question addressed is exploratory in nature. Less than one half of the patients with IPF who were seen during the study period had the necessary data to allowing their inclusion for analysis. Our study assessed all-cause mortality since the cause of death was not available in many patients. We were also not able to assess the rate of decline in pulmonary function and the possible relationships to BMI since a substantial number of patients did not have sequential follow-up pulmonary function measurements performed. Additional investigations, including prospective studies, are necessary to confirm the association between BMI and survival in patients with IPF.

Nonetheless, the association of higher BMI and longer survival time in patients with IPF is intriguing. Further exploration of this issue may lead to additional insights into the pathogenesis of IPF as well as into the optimal management of patients afflicted with this disease.

Footnotes

Abbreviations: BMI = body mass index; CI = confidence interval; DLCO = diffusing capacity of the lung for carbon monoxide; HR = hazard ratio; HRCT = high-resolution CT; IL = interleukin; IPF = idiopathic pulmonary fibrosis; PFT = pulmonary function testing; UIP = usual interstitial pneumonia

This research was supported by the Mayo Institutional funds and the Robert N. Brewer Family Foundation.

The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Received for publication November 15, 2006. Accepted for publication January 11, 2007.

References

  1. Ryu, JH, Colby, TV, Hartman, TE (1998) Idiopathic pulmonary fibrosis: current concepts. Mayo Clin Proc 73,1085-1101[ISI][Medline]
  2. American Thoracic Society/European Respiratory Society.. Idiopathic pulmonary fibrosis: diagnosis and treatment; international consensus statement. Am J Respir Crit Care Med 2000;161,646-664[Free Full Text]
  3. Gross, TJ, Hunninghake, GW Idiopathic pulmonary fibrosis. N Engl J Med 2001;345,517-525[Free Full Text]
  4. Visscher, DW, Myers, JL Histologic spectrum of idiopathic interstitial pneumonias. Proc Am Thorac Soc 2006;3,322-329[Abstract/Free Full Text]
  5. Raghu, G, Weycker, D, Edelsberg, J, et al Incidence and prevalence of idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2006;174,810-816[Abstract/Free Full Text]
  6. Gribbin, J, Hubbard, RB, Le Jeune, I, et al The incidence and mortality of idiopathic pulmonary fibrosis and sarcoidosis in the UK. Thorax 2006;61,980-985[Abstract/Free Full Text]
  7. Bjoraker, JA, Ryu, JH, Edwin, MK, et al Prognostic significance of histopathologic subsets in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 1998;157,199-203[ISI][Medline]
  8. King, TE JR, Tooze, JA, Schwarz, MI, et al Predicting survival in idiopathic pulmonary fibrosis: scoring system and survival model. Am J Respir Crit Care Med 2001;164,1171-1181[Abstract/Free Full Text]
  9. Wells, AU, Desai, SR, Rubens, MB, et al Idiopathic pulmonary fibrosis: a composite physiology index derived from disease extent observed by computed tomography. Am J Respir Crit Care Med 2003;167,962-969[Abstract/Free Full Text]
  10. Daniels, CE, Ryu, JH Treatment of idiopathic pulmonary fibrosis. Semin Respir Crit Care Med 2006;27,668-676[CrossRef][ISI][Medline]
  11. Walter, N, Collard, HR, King, TE, Jr Current perspectives on the treatment of idiopathic pulmonary fibrosis. Proc Am Thorac Soc 2006;3,330-338[Abstract/Free Full Text]
  12. Raghu, G Idiopathic pulmonary fibrosis: treatment options in pursuit of evidence-based approaches. Eur Respir J 2006;28,463-465[Free Full Text]
  13. Collard, HR, King, TE, Jr, Bartelson, BB, et al Changes in clinical and physiologic variables predict survival in idiopathic pulmonary fibrosis. Am J Respir Crit Care Med 2003;168,538-542[Abstract/Free Full Text]
  14. Flaherty, KR, Mumford, JA, Murray, S, et al Prognostic implications of physiologic and radiographic changes in idiopathic interstitial pneumonia. Am J Respir Crit Care Med 2003;168,543-548[Abstract/Free Full Text]
  15. Latsi, PI, du Bois, RM, Nicholson, AG, et al Fibrotic idiopathic interstitial pneumonia: the prognostic value of longitudinal functional trends. Am J Respir Crit Care Med 2003;168,531-537[Abstract/Free Full Text]
  16. Egan, JJ, Martinez, FJ, Wells, AU, et al Lung function estimates in idiopathic pulmonary fibrosis: the potential for a simple classification. Thorax 2005;60,270-273[Free Full Text]
  17. Nadrous, HF, Pellikka, PA, Krowka, MJ, et al Pulmonary hypertension complicating idiopathic pulmonary fibrosis. Chest 2005;128,2393-2399[Abstract/Free Full Text]
  18. Wilson, DO, Rogers, RM, Wright, EC, et al Body weight in chronic obstructive pulmonary disease: the National Institutes of Health Intermittent Positive-Pressure Breathing Trial. Am Rev Respir Dis 1989;139,1435-1438[ISI][Medline]
  19. Chailleux, E, Fauriux, B, Binet, F, et al Predictors of survival in patients receiving domiciliary oxygen therapy or mechanical ventilation: a 10-year analysis of ANTADIR Observatory. Chest 1996;109,741-749[Abstract/Free Full Text]
  20. Schols, AMWJ, Slangen, J, Volovics, L, et al Weight loss is a reversible factor in the prognosis of chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1998;157,1791-1797[ISI][Medline]
  21. Landbo, C, Prescott, E, Lange, P, et al Prognostic value of nutritional status in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1999;160,1856-1861[Abstract/Free Full Text]
  22. Chailleux, E, Laaban, JP, Veale, D Prognostic value of nutritional depletion in patients with COPD treated by long-term oxygen therapy: data from the ANTADIR observatory. Chest 2003;23,1460-1466
  23. Cano, NJM, Pichard, C, Roth, H, et al C-reactive protein and body mass index predict outcome in end-stage respiratory failure. Chest 2004;126,540-546[Abstract/Free Full Text]
  24. Celli, BR, Cote, CG, Marin, JM, et al The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 2004;350,1005-1012[Abstract/Free Full Text]
  25. Douglas, WW, Ryu, JH, Schroeder, DR Idiopathic pulmonary fibrosis: impact of oxygen and colchicine, prednisone, or no therapy on survival. Am J Respir Crit Care Med 2000;161,1172-1178[Abstract/Free Full Text]
  26. Kaplan, ELP, Meier, P Non-parametric estimation from incomplete observations. J Am Stat Assoc 1958;53,457-481[CrossRef][ISI]
  27. Cox, DR Regression models and life-tables (with discussion). J R Stat Soc Ser B 1972;34,187-220
  28. Nici, L, Donner, C, Wouters, E, et al American Thoracic Society/European Respiratory Society statement on pulmonary rehabilitation. Am J Respir Crit Care Med 2006;173,1390-1413[Free Full Text]
  29. Stark, LJ, Powers, SW Behavioral aspects of nutrition in children with cystic fibrosis. Curr Opin Pulm Med 2005;11,539-542[CrossRef][ISI][Medline]
  30. Davis, PB Cystic fibrosis since 1938. Am J Respir Crit Care Med 2005;173,475-482[CrossRef][ISI][Medline]
  31. Meijers, JMM, Swaen, GMH, Slangen, JJM Mortality of Dutch coal miners in relation to pneumoconiosis, chronic obstructive pulmonary disease, and lung function. Occup Environ Med 1997;54,708-713[Abstract]
  32. Fontaine, KR, Redden, DT, Wang, C, et al Years of life lost due to obesity. JAMA 2003;289,187-193[Abstract/Free Full Text]
  33. Olshansky, SJ, Passaro, DJ, Hershow, RC, et al A potential decline in life expectancy in the United States in the 21st century. N Engl J Med 2005;352,1138-1145[Abstract/Free Full Text]
  34. Kalantar-Zadeh, K, Block, G, Horwich, T, et al Reverse epidemiology of conventional cardiovascular risk factors in patients with chronic heart failure. J Am Coll Cardiol 2004;43,1439-1444[Abstract/Free Full Text]
  35. Peters-Golden, M, Swern, A, Bird, SS, et al Influence of body mass index on the response to asthma controller agents. Eur Respir J 2006;27,495-503[Abstract/Free Full Text]
  36. Ask, K, Martin, GE, Kolb, M, et al Targeting genes for treatment in idiopathic pulmonary fibrosis. Proc Am Thorac Soc 2006;3,389-393[Abstract/Free Full Text]
  37. Tilg, H, Moschen, AR Adipocytokines: mediators linking adipose tissue, inflammation and immunity. Nat Rev Immunol 2006;6,772-783[CrossRef][ISI][Medline]
  38. Rondinone, CM Adipocyte-derived hormones, cytokines, and mediators. Endocrine 2006;29,81-90[CrossRef][ISI][Medline]
  39. Fantuzzi, G Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 2005;115,911-919[CrossRef][ISI][Medline]
  40. Juge-Aubry, CE, Henrichot, E, Meier, CA Adipose tissue: a regulator of inflammation. Best Pract Res Clin Endocrinol Metab 2005;19,547-566[CrossRef][Medline]
  41. Savino, W The thymus gland is a target in malnutrition. Eur J Clin Nutr 2002;56(suppl),S46-S49




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