Literature DB >> 31686802

Does chronic obstructive pulmonary disease increase the risk of prostate cancer? A nationwide population-based study.

Wen-Lin Hsu1, Hung-Yi Chen2, Fung-Wei Chang3,4,5, Ren-Jun Hsu6,7.   

Abstract

Purpose: Chronic obstructive pulmonary disease (COPD) is a major pulmonary disease. However, few studies have investigated the relationship between COPD and prostate cancer (PCa). This study aimed to investigate the association between COPD severity and PCa risk. Patients and methods: We conducted a nationwide population-based cohort study utilizing data from 2001 to 2013 from the National Health Insurance Research Database of Taiwan. Cox proportional hazards models with 1:1 propensity score-matched analysis were used to investigate the association between COPD and PCa risk. We further divided the COPD group according to severe complications (including acute respiratory failure, cardiopulmonary arrest, pneumonia, and acute exacerbation) to test for the relationship between COPD severity and PCa risk.
Results: This study included 47,634 patients (23,817 COPD patients and 23,817 matched non-COPD controls). Among them, 756 (1.59%) were diagnosed with PCa during a mean follow-up period of 7.05±4.13 years; 387 (1.62%) were from the COPD group and 369 (1.55%) were from the control group. Compared with the patients without COPD, the adjusted hazard ratio (HR) for PCa in the COPD patients was 1.10 (95% confidence interval [CI] 0.95-1.27), while that in the COPD patients with complications was 2.46 (95% CI 1.96-3.61). Conclusions: An increased risk for PCa was found among the COPD patients with complications. COPD complications included acute respiratory failure, cardiopulmonary arrest, pneumonia, and acute exacerbation. These findings may help physicians in treating COPD with complications and in remaining alert to the potential development of PCa.
© 2019 Hsu et al.

Entities:  

Keywords:  National Health Insurance Research Database; chronic obstructive pulmonary disease; prostate cancer

Mesh:

Year:  2019        PMID: 31686802      PMCID: PMC6709785          DOI: 10.2147/COPD.S210975

Source DB:  PubMed          Journal:  Int J Chron Obstruct Pulmon Dis        ISSN: 1176-9106


Introduction

Prostate cancer (PCa) is the cancer most commonly diagnosed in men in the United States, with 161,360 new cases in 2017.1 Recently, the incidence of PCa has been increasing in Taiwan.2 At present, PCa is the fifth most common cancer among men in Taiwan, with 5,106 new cases in 2015.2 The etiological factors of PCa include age, family history, and race.3 Additionally, chronic inflammation has been identified as a precursor of prostate carcinogenesis,4 and proliferative inflammatory atrophy (PIA) has been reported to progress to PCa.5 Inflammation of the prostate may increase the production of inflammatory cytokines and reactive oxygen species (ROS), which increase cellular proliferation or carcinogenesis.4 Chronic obstructive pulmonary disease (COPD) is a major disease worldwide6 and has been predicted to be the third leading cause of death in 2020.7 A recent epidemiological survey found that the prevalence of COPD in Taiwan is 6.1%.8 Smoking, occupational pollution, and air pollution are major etiological factors for COPD.9 The condition is characterized by progressive persistent airflow limitation. Airflow limitation develops from chronic inflammation due to the presence of noxious particles or gases in the airways.10 The parthogeneses of both PCa and COPD include chronic inflammation. However, there have been only a limited number of studies discussing the association between PCa and COPD. We thus conducted a nationwide population-based cohort study in Taiwan using a nationwide database to investigate the association between COPD severity and the risk of PCa.

Materials and methods

Data source and collection

This was a retrospective population-based study that used data from Taiwan’s National Health Insurance Research Database (NHIRD), a huge database containing data from the National Health Insurance (NHI) program. The NHI program is a unique health and medical insurance system in Taiwan that was started in 1995. As of the end of 2013, the NHI program covered 99.9% of Taiwan’s 23 million residents.11 The NHIRD contains demographic data, medical records, and data on clinical procedures administered to all inpatients, outpatients, and emergency room patients. We used a sub-dataset of the NHIRD called the Longitudinal Health Insurance Database 2000 (LHID2000), a database that contains the data of one million people randomly selected from the larger NHIRD in 2000. The LHID2000 and NHIRD are similar in terms of demographic data and origin population.12 The clinical diagnoses of patients in the database were made according to the International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM). This study was approved by the Institutional Review Board of the Tri-Service General Hospital (approval number: TSGHIRB NO B-104-21).

Study population

The study subjects were selected using LHID2000 data from January 2000 to December 2013. Patients who were newly diagnosed with COPD (ICD-9-CM: 491,492, and 496) between 2001 and 2013 were enrolled in this study (Figure 1). The COPD diagnoses were performed by licensed physicians. The exclusion criteria were as follows: (1) patients who were diagnosed with a malignancy before January 1, 2001 (n=7,234), (2) patients who were male and <40 years old (n=690,366), (3) patients with a history of COPD or any immune or inflammatory diseases (n=148,866), and (4) patients with incomplete medical records (n=284) (Figure 1). A total of 23,817 patients with COPD were ultimately enrolled in the study group.
Figure 1

Flowchart of study design.

Abbreviation: NHIRD, National Health Insurance Research Database.

The control group was determined through a 1:1 matching with the study group considering age and income. Thus, 23,817 subjects were enrolled in the control group. For the study group, each patient’s date of COPD diagnosis was assigned as the index date and considered the starting point for the investigation of that patient, whereas for the control group, the year of the index date was a matched year in which the control subjects had utilized a medical service. We also defined COPD severity according to any acute respiratory events subsequent to the COPD diagnosis. Subsequent acute respiratory events included acute exacerbation (ICD-9-CM: 491.21), pneumonia (ICD-9-CM: 480-486), acute respiratory failure (ICD-9-CM: 518.81), and cardiopulmonary arrest (ICD-9-CM: 799.1, 798, and 427.5).

Outcomes

There were 47,634 subjects in this study (23,817 COPD patients and 23,817 control group patients). Each subject was monitored until December 2013 to identify those who were newly diagnosed with PCa (ICD-9-CM: 185).13 All medical diagnoses of the patients and any procedures and drugs administered to them were recorded completely during the follow-up period. Each COPD diagnosis (ICD-9-CM: 491, 492, and 496) was made by chest physicians based on at least two outpatient department visits or at least one admission during the follow-up period. More specifically, each clinical diagnosis of COPD was made according to typical symptoms such as chronic cough, dyspnea, and sputum production; exposure to risk factors such as tobacco smoking, occupational pollution, and indoor air pollution; and spirometry test results. The acute respiratory events subsequent to COPD, including pneumonia, acute exacerbation, acute respiratory failure, and cardiopulmonary arrest, were also diagnosed by chest physicians, cardiologists, or emergency physicians based on emergency room and admission records during the follow-up period. We selected patients aged >40 years due to the extremely low prevalence of COPD in patients aged <40 years.14 The diagnosis of PCa was based on the ICD-9-CM coding system (ICD-9-CM: 185) and was included in the Registry for Catastrophic Illness Patient Database (RCIPD).15 Patients with PCa who were listed in the RCIPD were relieved of any medical payment obligations after receiving a catastrophic illness certification. After experts confirmed the accuracy of a PCa diagnosis by the NHI administration with pathological and cytological reports, patients with PCa were given catastrophic illness certifications.

Variables

Various comorbidities, including alcohol abuse, tobacco use disorder, obesity, diabetes mellitus, hypertension, hyperlipidemia, liver disease, cerebrovascular disease, coronary heart disease (CHD), and chronic kidney disease (CKD) (ICD-9-CM codes in Table S1), were regarded as variables.
Table S1

ICD-9 diagnostic codes of variables

CovariatesICD-9-CM codes
Alcohol abuse303, 305.0, V11.3
Tobacco use disorder305.1, 491.0, 491.2, 492.8, 496, 523.6, 649.0, 989.84, V15.82
Obesity278.0
Diabetes mellitus250
Hypertension401, 402, 403, 404, 405
Hyperlipidemia272
Coronary heart disease410, 411, 412, 413, 414
Chronic kidney disease585, 586, 588
Liver disease456, 571, 572
Cerebral vascular accident430, 431, 432, 433, 434, 435, 436, 437, 438

Abbreviation: ICD-9, International Classification of Diseases-9th revision.

The patients were classified into four age groups: 40–49, 50–59, 60–69, and ≥70 years. They were also categorized into four groups based on monthly income in New Taiwan Dollars (NTD):

Statistical analysis

Categorical variables were expressed as frequencies and percentages, and numerical variables were expressed as means and standard deviations. The Chi-square test was performed to examine differences in the categorical variables among the study groups, and an independent t-test was performed to examine differences in the numerical variables among the study groups. Moreover, we used Cox proportional hazards regression models to estimate the effects of risk factors on the hazard ratios (HRs) and 95% confidence intervals (CIs). The proportion of the study group with PCa was analyzed using Kaplan-Meier curves and the log-rank test. All multivariable Cox regression models were adjusted for variables including age, COPD, and comorbidities. A two-sided p-value of <0.05 was considered statistically significant. All statistical methods were performed using SAS for Windows, version 9.4 (SAS Institute Inc., Cary, NC).

Results

There were 47,634 patients (23,817 COPD patients and 23,817 control group patients) with a mean age of 63.72±12.29 years enrolled in this study. The demographic characteristics of the subjects are listed in Table 1. The COPD patients mostly belonged to the older-age group, and hypertension, CHD, and liver disease were the three most common comorbidities among them. Compared with the non-COPD patients, the COPD patients had higher Charlson comorbidity index scores; higher rates of CHD, CKD, liver disease, and cerebrovascular accident; and lower rates of hypertension and hyperlipidemia. Regarding complications, 126 (0.26%) of the COPD patients had pneumonia, acute exacerbation, and acute respiratory failure. Among all the patients, 756 (1.59%) were diagnosed with PCa during a mean follow-up period of 7.05±4.13 years; 387 (1.62%) of them were from the COPD group and 369 (1.55%) were from the control group.
Table 1

Characteristics of study population

Male subjectsTotalNon-COPDCOPDp-value
n=47,634n=23,817n=23,817
n%n%n%
Age (mean ± SD, years)63.72±12.2963.49±12.2263.95±12.340.858
 40–497,87116.523,93816.533,93316.51
 50–599,22719.374,62019.404,60719.34
 60–6912,20425.626,10325.626,10125.62
 >7018,33238.499,15638.449,17638.53
Insurance income (monthly)0.571
 06,28113.193,29413.843,36413.54
 0–16,50010,22421.464,86820.444,85620.48
 16,500–19,2003,5587.471,7757.451,7837.58
 19,200–33,30018,93039.749,12338.308,91839.18
 ≧33,3008,64118.144,75719.974,89619.22
Charlson comorbidity index (mean ± SD)1.38±1.601.23±1.551.53±1.64<0.0001**
 016,73235.139,99241.956,74028.30
 114,07729.556,34126.627,73632.48
 28,07016.943,56114.954,50918.93
 ≥38,75518.383,92316.474,83220.29
Comorbidity
 Alcohol abuse5251.102821.182431.020.095
 Tobacco use disorder1,3002.736592.776412.690.632
 Obesity1560.33720.30840.350.377
 Diabetes10,43421.95,22021.925,21421.890.955
 Hypertension24,34151.1012,32651.7512,01550.450.004*
 Hyperlipidemia10,29421.615,25022.045,04421.180.022*
 Liver disease8,28917.43,01312.655,27622.15<0.0001**
 Chronic kidney disease2,3724.981,1324.751,2405.210.024*
 Coronary heart disease12,90827.16,34726.656,56127.550.028*
 Cerebral vascular accident8,06716.943,88216.34,18517.570.0002**
COPD’s severity
 COPD only23,68999.46
 COPD with complications1260.26
 Acute exacerbation260.05
 Pneumonia1130.24
 Acute respiratory failure90.02
Prostate Cancer0.5331
 No46,87898.4123,43098.3823,44898.45
 Yes7561.593871.623691.55
Follow-up time (years)<0.0001**
 Mean ± SD7.05±4.137.46±4.026.64±4.19

Notes: *p<0.05 ; **p<0.01.

Characteristics of study population Notes: *p<0.05 ; **p<0.01. The Cox regression analysis of risk factors of PCa is shown in Table 2. Compared to the control group, the adjusted HR for PCa in the COPD group was 1.10 (95% CI 0.95–1.27), while that in the COPD group with complications was 2.46 (95% CI 1.96–3.61). Elderly patients had a significantly higher risk of PCa (those aged ≥70 years had an adjusted HR [aHR] of 3.47 [95% CI 1.71–4.52] compared with those aged 40–49 years). Other significant risk factors of PCa were tobacco use disorder (aHR 2.30, 95% CI 1.61–3.27) and hypertension (aHR 1.19, 95% CI 1.02–1.39).
Table 2

Independent predictors of risk factors of PCa by Cox regression analysis

Crude HR95% CIp-valueAdjusted HR95% CIp-value
LowerUpperLowerUpper
Non-COPD1.1.
COPD1.0820.9381.2480.2791.1030.9551.2730.1817
COPD with complications3.373.2434.653<0.0001**2.4631.9603.615<0.0001**
Age group
40–4911.
50–591.0721.1602.133<0.0001**1.7611.0421.980<0.0001**
60–692.1951.2592.534<0.0001**2.0061.2853.271<0.0001**
>703.4131.8484.511<0.0001**3.4731.7174.522<0.0001**
Comorbidity
 Alcohol abuse0.1610.0231.1410.0680.2680.0381.9110.1890
 Tobacco use disorder1.9651.3862.786<0.0001**2.3001.6133.278<0.0001**
 Obesity1.3070.4214.0610.6432.0220.6486.3100.2254
 Diabetes1.1510.9651.3740.1170.9650.8021.1610.7068
 Hypertension1.5401.3341.779<0.0001**1.1951.0251.3930.023*
 Hyperlipidemia1.0800.9041.2890.3991.1980.9921.4480.0609
 Liver disease1.0370.8551.2590.7111.0470.8541.2840.6565
 Chronic kidney disease1.0910.7531.5830.6440.9520.6551.3830.7950
 Coronary heart disease1.2161.0381.4250.016*1.1420.9681.3470.1153
 Cerebral vascular accident1.0820.8791.3330.4570.8240.6661.0190.0734

Notes: *p<0.05 ; **p<0.01.

Abbreviation: PCa, prostate cancer.

Independent predictors of risk factors of PCa by Cox regression analysis Notes: *p<0.05 ; **p<0.01. Abbreviation: PCa, prostate cancer. As shown in the Kaplan-Meier curves in Figure 2, patients with severe COPD with complications had a higher cumulative incidence of PCa (log-rank test, p<0.001) by the end of the follow-up period than the non-COPD and COPD groups.
Figure 2

Kaplan-Meier analysis of developing prostate cancer in COPD, COPD with complication, and non-COPD groups.

Discussion

To our knowledge, no other cohort studies have investigated the association between COPD with complications and PCa in detail. In this large-scale cohort study, males with severe COPD complications including acute respiratory failure, cardiopulmonary arrest, pneumonia, and acute exacerbation were found to have a higher risk of PCa than males without COPD. The association between COPD and PCa can be attributed to several plausible mechanisms. First, COPD is a chronic inflammatory disease in both airways and outside the respiratory system.16,17 Meanwhile, chronic inflammation of the prostate is associated with PCa, and PIA has been reported to progress to PCa.5 Furthermore, severe COPD may have an acute exacerbated inflammatory process, and there is evidence of oxidative stress in COPD, particularly during acute exacerbations.18 Reactive oxygen species (ROS) levels are elevated in severe COPD. ROS cause tissue damage, resulting in carbonyl stress that further causes nonenzymatic posttranslational modifications of proteins. These protein carbonylation reactions may induce the pathophysiological mechanisms of many chronic diseases.19 COPD severity is correlated with carbonyl stress levels.20 Carbonyl stress further causes DNA damage, inducing the autoimmune response and pro-inflammatory signaling (nuclear factor [NF]-κB pathway).21,22 The mechanisms of exacerbations in COPD also include increased airway inflammation and elevated levels of pro-inflammatory cytokines.23 The exposure of airway epithelial cells to acute oxidative stress triggers increased glutathione synthesis, but COPD patients fail to show this phenomenon.24 Moreover, severe COPD has also been associated with glutathione S-transferase (GST) activity.25 The GST family of enzymes plays an important role in environmental carcinogens. Thakur et al revealed that GSTT1 null genotypes increase the risks of both COPD and PCa in the Indian population.26 Pro-inflammatory cytokines also play an important role in chronic inflammation in both COPD and PCa. Increased levels of interleukin (IL)‐1β, IL‐6, IL‐8, IL-17, and tumor necrosis factor (TNF)‐α have been observed in sputum and bronchoalveolar lavage fluid from COPD patients.27,28 Moreover, several inflammatory cytokines including IL-1, IL-6, and IL-17 have been reported to be induced by PCa.4 IL-6 is an activator of STAT3 and NF-κB complexes,29,30 and NF-κB activation has been reported in PCa development.31 Furthermore, higher IL-6 and IL-8 levels have been associated with more severe COPD,23 and increased IL-6 levels in patients with severe COPD may further affect PCa development. Studies have indicated that older men have an increased risk of COPD and PCa.32,33 Increasing age is a risk factor for severe COPD, especially in patients aged >80 years,34 and for PCa. Meanwhile, inhaled anticholinergic agents (ipratropium and tiotropium) are widely administered as maintenance treatment for COPD. However, such agents are linked to increased risk of acute urinary retention.35 Severe COPD is also treated with anticholinergic agents and systemic corticosteroids, and Foley insertion is performed to monitor daily urine output in ICU patients with severe COPD. In PCa, acute urinary retention and urine reflux are also well-known risk factors.36 This study has some limitations. First, all of the conditions were diagnosed using the ICD-9-CM coding system from the NHIRD, which is an administrative database; thus, detailed laboratory data or tumor marker results were not obtained. Although pulmonary function tests, FEV1/FVC ratios, prostate-specific antigen levels, computed tomography scans, and bone scans were not available, the diagnoses of PCa were ascertained by catastrophic illness certifications, which were reviewed by experts to confirm the given diagnosis. Second, instead of using the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification, we classified COPD by subsequent acute respiratory events, namely pneumonia, acute exacerbation, acute respiratory failure, and cardiopulmonary arrest. Third, some confounding factors such as cigarette smoking, obesity, and occupational exposure status might have been underestimated in the NHIRD database. Finally, this study has a retrospective nature; hence, more prospective studies are warranted to further investigate the association between COPD and PCa.

Conclusion

This study showed that COPD patients with complications have an increased risk of PCa. Thus, severe COPD may be a determining factor for PCa incidence. These findings may help physicians in treating COPD with complications and in remaining alert to the potential development of PCa. Relatedly, physicians may want to consider screening for PCa in those COPD patients with complications. Flowchart of study design. Abbreviation: NHIRD, National Health Insurance Research Database. Kaplan-Meier analysis of developing prostate cancer in COPD, COPD with complication, and non-COPD groups.

Supplementary material

ICD-9 diagnostic codes of variables Abbreviation: ICD-9, International Classification of Diseases-9th revision.
  32 in total

1.  Interleukin-6 induces prostate cancer cell growth accompanied by activation of stat3 signaling pathway .

Authors:  W Lou; Z Ni; K Dyer; D J Tweardy; A C Gao
Journal:  Prostate       Date:  2000-02-15       Impact factor: 4.104

Review 2.  Oxidative stress in COPD.

Authors:  Paul A Kirkham; Peter J Barnes
Journal:  Chest       Date:  2013-07       Impact factor: 9.410

3.  Inhaled anticholinergic drugs and risk of acute urinary retention.

Authors:  Ana S M Afonso; Katia M C Verhamme; Bruno H C Stricker; Miriam C J M Sturkenboom; Guy G O Brusselle
Journal:  BJU Int       Date:  2010-09-29       Impact factor: 5.588

4.  Diminished immunoreactivity of gamma-glutamylcysteine synthetase in the airways of smokers' lung.

Authors:  Terttu Harju; Riitta Kaarteenaho-Wiik; Ylermi Soini; Raija Sormunen; Vuokko L Kinnula
Journal:  Am J Respir Crit Care Med       Date:  2002-09-01       Impact factor: 21.405

Review 5.  Chronic obstructive pulmonary disease in non-smokers.

Authors:  Sundeep S Salvi; Peter J Barnes
Journal:  Lancet       Date:  2009-08-29       Impact factor: 79.321

Review 6.  Autoimmunity and oxidatively modified autoantigens.

Authors:  Biji T Kurien; R Hal Scofield
Journal:  Autoimmun Rev       Date:  2008-05-27       Impact factor: 9.754

7.  Differences in interleukin-8 and tumor necrosis factor-alpha in induced sputum from patients with chronic obstructive pulmonary disease or asthma.

Authors:  V M Keatings; P D Collins; D M Scott; P J Barnes
Journal:  Am J Respir Crit Care Med       Date:  1996-02       Impact factor: 21.405

8.  4-Hydroxy-2-nonenal, a specific lipid peroxidation product, is elevated in lungs of patients with chronic obstructive pulmonary disease.

Authors:  Irfan Rahman; Annemarie A M van Schadewijk; Ann J L Crowther; Pieter S Hiemstra; Jan Stolk; William MacNee; Willem I De Boer
Journal:  Am J Respir Crit Care Med       Date:  2002-08-15       Impact factor: 21.405

9.  Comorbidities and risk of mortality in patients with chronic obstructive pulmonary disease.

Authors:  Miguel Divo; Claudia Cote; Juan P de Torres; Ciro Casanova; Jose M Marin; Victor Pinto-Plata; Javier Zulueta; Carlos Cabrera; Jorge Zagaceta; Gary Hunninghake; Bartolome Celli
Journal:  Am J Respir Crit Care Med       Date:  2012-05-03       Impact factor: 21.405

10.  Androgen deprivation therapy for prostate cancer and the risk of autoimmune diseases.

Authors:  Jui-Ming Liu; Cheng-Ping Yu; Heng-Chang Chuang; Chun-Te Wu; Ren-Jun Hsu
Journal:  Prostate Cancer Prostatic Dis       Date:  2019-01-28       Impact factor: 5.554

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Authors:  Avinoam Nevler; Samantha Z Brown; David Nauheim; Carla Portocarrero; Ulrich Rodeck; Jonathan Bassig; Christopher W Schultz; Grace A McCarthy; Harish Lavu; Theresa P Yeo; Charles J Yeo; Jonathan R Brody
Journal:  J Am Coll Surg       Date:  2020-02-11       Impact factor: 6.113

2.  Causes of Death after Prostate Cancer Diagnosis: A Population-Based Study.

Authors:  Yadong Guo; Xiaohui Dong; Shiyu Mao; Fuhan Yang; Ruiliang Wang; Wenchao Ma; Ji Liu; Cheng Li; Zongtai Zheng; Wentao Zhang; Aihong Zhang; Xudong Yao
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Review 3.  Clinical factors affecting prostate-specific antigen levels in prostate cancer patients undergoing radical prostatectomy: a retrospective study.

Authors:  Giovanni Tarantino; Felice Crocetto; Concetta Di Vito; Raffaele Martino; Savio Domenico Pandolfo; Massimiliano Creta; Achille Aveta; Carlo Buonerba; Ciro Imbimbo
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