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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">KJIM</journal-id>
<journal-title-group>
<journal-title>The Korean Journal of Internal Medicine</journal-title><abbrev-journal-title>Korean J Intern Med</abbrev-journal-title></journal-title-group>
<issn pub-type="ppub">1226-3303</issn>
<issn pub-type="epub">2005-6648</issn>
<publisher>
<publisher-name>The Korean Association of Internal Medicine</publisher-name></publisher></journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3904/kjim.2019.428</article-id>
<article-id pub-id-type="publisher-id">kjim-2019-428</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Article</subject>
<subj-group subj-group-type="heading">
<subject>Gastroenterology</subject>
</subj-group></subj-group></article-categories>
<title-group>
<article-title>Effect of <italic>Helicobacter pylori</italic> treatment on the long-term mortality in patients with type 2 diabetes</article-title></title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Young-Il</given-names></name><xref rid="af1-kjim-2019-428" ref-type="aff">1</xref></contrib>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Young Ae</given-names></name><xref rid="af2-kjim-2019-428" ref-type="aff">2</xref></contrib>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Hak Jin</given-names></name><xref rid="af3-kjim-2019-428" ref-type="aff">3</xref></contrib>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Su-Hyun</given-names></name><xref rid="af4-kjim-2019-428" ref-type="aff">4</xref></contrib>
<contrib contrib-type="author">
<name><surname>Hwangbo</surname><given-names>Yul</given-names></name><xref rid="af5-kjim-2019-428" ref-type="aff">5</xref></contrib>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Jae Gyu</given-names></name><xref rid="af6-kjim-2019-428" ref-type="aff">6</xref></contrib>
<contrib contrib-type="author">
<name><surname>Kim</surname><given-names>Jae J.</given-names></name><xref rid="af7-kjim-2019-428" ref-type="aff">7</xref></contrib>
<contrib contrib-type="author" corresp="yes">
<name><surname>Choi</surname><given-names>Il Ju</given-names></name><xref rid="af1-kjim-2019-428" ref-type="aff">1</xref></contrib></contrib-group>
<aff id="af1-kjim-2019-428">
<label>1</label>Center for Gastric Cancer, National Cancer Center, Goyang, 
<country>Korea</country></aff>
<aff id="af2-kjim-2019-428">
<label>2</label>National Cancer Control Institute, National Cancer Center, Goyang, 
<country>Korea</country></aff>
<aff id="af3-kjim-2019-428">
<label>3</label>Branch of Cardiology, Department of Internal Medicine, National Cancer Center, Goyang, 
<country>Korea</country></aff>
<aff id="af4-kjim-2019-428">
<label>4</label>Department of Neurology, Research Institute and Hospital, National Cancer Center, Goyang, 
<country>Korea</country></aff>
<aff id="af5-kjim-2019-428">
<label>5</label>Division of Endocrinology, Department of Internal Medicine, National Cancer Center, Goyang, 
<country>Korea</country></aff>
<aff id="af6-kjim-2019-428">
<label>6</label>Department of Internal Medicine, Chung-Ang University College of Medicine, Seoul, 
<country>Korea</country></aff>
<aff id="af7-kjim-2019-428">
<label>7</label>Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 
<country>Korea</country></aff>
<author-notes>
<corresp id="c1-kjim-2019-428">Correspondence to: <bold>Il Ju Choi, M.D</bold>., Center for Gastric Cancer, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang 10408, Korea, Tel: +82-31-920-2282, Fax: +82-31-920-2799, E-mail: <email>cij1224@ncc.re.kr</email>, <ext-link xlink:href="https://orcid.org/0000-0002-8339-9824" ext-link-type="uri">https://orcid.org/0000-0002-8339-9824</ext-link></corresp></author-notes>
<pub-date pub-type="ppub">
<month>5</month>
<year>2021</year></pub-date>
<pub-date pub-type="epub">
<day>1</day>
<month>12</month>
<year>2020</year></pub-date>
<volume>36</volume>
<issue>3</issue>
<fpage>584</fpage>
<lpage>595</lpage>
<history>
<date date-type="received">
<day>14</day>
<month>12</month>
<year>2019</year></date>
<date date-type="rev-recd">
<day>4</day>
<month>02</month>
<year>2020</year></date>
<date date-type="accepted">
<day>19</day>
<month>02</month>
<year>2020</year></date></history>
<permissions>
<copyright-statement>Copyright &#x000A9; 2021 The Korean Association of Internal Medicine</copyright-statement>
<copyright-year>2021</copyright-year>
<license>
<license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link xlink:href="http://creativecommons.org/licenses/by-nc/4.0/" ext-link-type="uri">http://creativecommons.org/licenses/by-nc/4.0/</ext-link>) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions>
<abstract>
<sec>
<title>Background/Aims</title>
<p>Meta-analyses of randomized trials reported a non-significant increase in overall mortality risk after <italic>Helicobacter pylori</italic> eradication. In this study, we investigated whether <italic>H. pylori</italic> treatment is associated with increased risk of overall mortality in patients with type 2 diabetes.</p></sec>
<sec>
<title>Methods</title>
<p>In this retrospective population-based cohort study, we identified 66,706 patients treated for type 2 diabetes between 2002 and 2010 from the Korean National Health Insurance Service-National Sample Cohort. Patients who received <italic>H. pylori</italic> treatment (Hp-treatment cohort, 1,727 patients) were matched to those who did not (non-treatment cohort, 3,454 patients) at a 1:2 ratio. The primary outcome was overall mortality. The secondary outcomes were mortalities due to cardiovascular disease, cerebrovascular disease, or cancers. To estimate hazard ratio (HR) with confidential interval (CI), we used the Cox proportional-hazard model.</p></sec>
<sec>
<title>Results</title>
<p>During a median follow-up of 4.7 years, the overall mortality was 5.9&#x00025; (101/1,727 patients) among patients in the Hp-treatment cohort and 7.6&#x00025; (364/3,454 patients) among patients in the non-treatment cohort. Adjusted HR (aHR) for overall mortality in the Hp-treatment cohort was 0.74 (95&#x00025; CI, 0.59 to 0.93; <italic>p</italic> = 0.011). The mortality risks due to cardiovascular disease (aHR, 1.34; 95&#x00025; CI, 0.54 to 3.30; <italic>p</italic> = 0.529), cerebrovascular disease (aHR, 0.97; 95&#x00025; CI, 0.37 to 2.55; <italic>p</italic> = 0.947), and cancer (aHR, 1.08; 95&#x00025; CI, 0.68 to 1.72; <italic>p</italic> = 0.742) were not significantly different between the groups.</p></sec>
<sec>
<title>Conclusions</title>
<p>In type 2 diabetes patients, overall mortality did not increase after <italic>H. pylori</italic> treatment.</p></sec></abstract>
<kwd-group>
<kwd>Helicobacter pylori</kwd>
<kwd>Mortality</kwd>
<kwd>Diabetes mellitus</kwd>
<kwd>type 2</kwd></kwd-group></article-meta></front>
<body>
<sec sec-type="intro">
<title>INTRODUCTION</title>
<p>A meta-analysis of randomized controlled trials (RCTs) conducted in asymptomatic general population reported 34&#x00025; reduction in gastric cancer incidence after <italic>Helicobacter pylori</italic> eradication &#x0005B;<xref ref-type="bibr" rid="b1-kjim-2019-428">1</xref>&#x0005D;. Gastric cancer mortality risk also decreased by 33&#x00025;, but a non-significant 9&#x00025; increase in the overall mortality risk was found after <italic>H. pylori</italic> eradication &#x0005B;<xref ref-type="bibr" rid="b1-kjim-2019-428">1</xref>&#x0005D;. A RCT in high-risk patients who underwent endoscopic resection for early gastric cancer reported a non-significant increased overall mortality risk among patients included in the <italic>H. pylori</italic> treatment group (hazard ratio &#x0005B;HR&#x0005D;, 1.95; <italic>p</italic> = 0.19) despite a significant reduction of metachronous gastric cancer risk &#x0005B;<xref ref-type="bibr" rid="b2-kjim-2019-428">2</xref>&#x0005D;. A more recent meta-analysis also demonstrated a non-significant risk increase in overall mortality with <italic>H. pylori</italic> treatment (risk ratio, 1.12; 95&#x00025; confidence interval &#x0005B;CI&#x0005D;, 0.93 to 1.34) &#x0005B;<xref ref-type="bibr" rid="b3-kjim-2019-428">3</xref>&#x0005D;. These data suggest a potential harmful effect of <italic>H. pylori</italic> treatment in terms of increased non-gastric cancer mortality. However, the true nature of this observation and the plausible underlying mechanisms remain unclear.</p>
<p>Globally, the leading causes of death include ischemic heart disease and stroke and cancer &#x0005B;<xref ref-type="bibr" rid="b4-kjim-2019-428">4</xref>&#x02013;<xref ref-type="bibr" rid="b6-kjim-2019-428">6</xref>&#x0005D;. A significant association between increased cardiovascular disease mortality and clarithromycin, which is a commonly used antibiotic for <italic>H. pylori</italic> eradication, has been suggested &#x0005B;<xref ref-type="bibr" rid="b7-kjim-2019-428">7</xref>&#x02013;<xref ref-type="bibr" rid="b9-kjim-2019-428">9</xref>&#x0005D;. Thus, we hypothesized that <italic>H. pylori</italic> treatment might be associated with increased risk of mortality due to these major causes of death which might over-compensate the decrease of gastric cancer mortality. Type 2 diabetes is an important risk factor for cardiovascular disease, cerebrovascular disease, and cancers &#x0005B;<xref ref-type="bibr" rid="b10-kjim-2019-428">10</xref>,<xref ref-type="bibr" rid="b11-kjim-2019-428">11</xref>&#x0005D;. In this retrospective cohort study, we investigated whether <italic>H. pylori</italic> treatment is associated with overall mortality increase or with mortality increase from the main causes in patients with type 2 diabetes.</p></sec>
<sec sec-type="methods">
<title>METHODS</title>
<sec>
<title>Data source</title>
<p>This study used the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) database from 2002 to 2013 &#x0005B;<xref ref-type="bibr" rid="b12-kjim-2019-428">12</xref>&#x0005D;. Using probability sampling, a representative sample cohort of approximately one million subjects (2.2&#x00025; of the total eligible population) was extracted from all beneficiaries of the National Health insurance and National Medical Aid in 2002 depending on the entire national cohort information. The cohort follow-up was for 11 years until 2013 &#x0005B;<xref ref-type="bibr" rid="b12-kjim-2019-428">12</xref>&#x0005D;. In this cohort, we used disease codes of the International Classification of Diseases, 10th Revision (ICD-10) to identify the disease diagnosis and the cause of death &#x0005B;<xref ref-type="bibr" rid="b13-kjim-2019-428">13</xref>&#x0005D;. The database has been validated in several studies performed in Korea &#x0005B;<xref ref-type="bibr" rid="b14-kjim-2019-428">14</xref>&#x02013;<xref ref-type="bibr" rid="b16-kjim-2019-428">16</xref>&#x0005D;.</p></sec>
<sec>
<title>Study design and population</title>
<p>Our study design is a population-based retrospective cohort study. The Institutional Review Board of the National Cancer Center approved this study (NCC2016-0043). Requirement for informed consent from each individual was waived.</p>
<p>Detailed patient selection methods have been described in our previous study evaluating the association between overall mortality and <italic>H. pylori</italic> treatment in hypertension patients &#x0005B;<xref ref-type="bibr" rid="b16-kjim-2019-428">16</xref>&#x0005D;. Using the disease codes for type 2 diabetes (ICD-10 code, E11 to E14), type 2 diabetes patients aged 20 years or older were selected between 2002 and 2010. Patients who had been prescribed one or more anti-diabetic drugs were finally included in the analyses.</p>
<p>Patients who received <italic>H. pylori</italic> eradication treatment after the diagnosis of type 2 diabetes until June 2013 were included in the <italic>H. pylori</italic> treatment cohort. The prescription of <italic>H. pylori</italic> eradication medication was examined using drug codes for standard triple therapy (proton-pump inhibitor &#x0005B;PPI&#x0005D;, amoxicillin, and clarithromycin for 7 to 14 days) or bismuth quadruple therapy (PPIs, bismuth, tetracycline, and metronidazole for 7 to 14 days), which were approved for the first-line and the second-line treatment in Korea &#x0005B;<xref ref-type="bibr" rid="b17-kjim-2019-428">17</xref>&#x0005D;. Each patient in the <italic>H. pylori</italic> treatment cohort was matched with those in the non-treatment cohort at an 1:2 ratio by using a simple random sampling method without replacement. Variables for matching included age group, sex, date of type 2 diabetes diagnosis, and Charlson comorbidity index (CCI) score &#x0005B;<xref ref-type="bibr" rid="b18-kjim-2019-428">18</xref>&#x0005D;.</p>
<p>The observation periods for study outcomes started on the prescription date for <italic>H. pylori</italic> therapy in the treatment cohort and the corresponding date in matched control patients in the non-treatment cohort. The observation periods ended on December 31st, 2013 (<xref rid="s2-kjim-2019-428" ref-type="supplementary-material">Supplementary Fig. 1</xref>). Patients who died due to any causes or those who were diagnosed with cancers, cardiovascular diseases, or cerebrovascular diseases before or within the 6 months after the initiation of the observation periods were excluded.</p></sec>
<sec>
<title>Study outcomes</title>
<p>The primary outcome was overall (all-cause) mortality, and the secondary outcomes included cardiovascular disease mortality, cerebrovascular mortality, and overall cancer mortality occurring at least 6 months after the start of the observation period. The specific ICD-10 code for cancers (C00 to 97), cardiovascular diseases (I20 to I25), and cerebrovascular diseases (I60 to I66) are provided in <xref rid="s1-kjim-2019-428" ref-type="supplementary-material">Supplementary Table 1</xref>.</p></sec>
<sec>
<title>Statistical analysis</title>
<p>Student <italic>t</italic> test and chi-square test were used for descriptive analyses to compare baseline characteristics between groups. Overall mortality was compared using the Kaplan-Meier curves with log-rank test. We used univariate and multivariate Cox proportional hazard regression models to estimate HR with 95&#x00025; CI for mortalities and incidences of cancers, cardiovascular, and cerebrovascular diseases according to the <italic>H. pylori</italic> treatment.</p>
<p>Age, sex, socioeconomic status, CCI scores, and the use of aspirin and metformin were included as the covariates for the multivariate analysis. Statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, NC, USA), and <italic>p</italic> values less than 0.05 were considered statistically significant.</p></sec></sec>
<sec sec-type="results">
<title>RESULTS</title>
<sec>
<title>Baseline characteristics of the study population</title>
<p>A total of 66,706 type 2 diabetes patients aged &#x02265; 20 years were prescribed at least one anti-diabetic medication between 2002 and 2010. A total of 3,059 patients received prescription for <italic>H. pylori</italic> treatment from the date of diagnosis for type 2 diabetes to June 30, 2013. Among them, 1,251 patients who died from any causes or were diagnosed with cancer, cardiovascular, or cerebrovascular diseases within 6 months before or after <italic>H. pylori</italic> treatment were excluded. Finally, a total of 1,727 patients in the <italic>H. pylori</italic> treatment cohort and 3,454 matched patients in the non-treatment cohort were selected for the analysis (<xref rid="f1-kjim-2019-428" ref-type="fig">Fig. 1</xref>).</p>
<p>Patients in the <italic>H. pylori</italic> treatment cohort had a higher proportion of patients with household income level &gt; 50&#x00025; (62.3&#x00025; vs. 57.3&#x00025;, <italic>p =</italic> 0.001) and metformin users (83.0&#x00025; vs. 80.1&#x00025;, <italic>p</italic> = 0.011) compared to the non-treatment cohort. Other baseline characteristics were not significantly different between the two cohorts. The standard triple therapy regimen was prescribed in 98.4&#x00025; of patients in the <italic>H. pylori</italic> treatment cohort (<xref rid="t1-kjim-2019-428" ref-type="table">Table 1</xref>).</p></sec>
<sec>
<title>Risk factors for overall mortality after <italic>H. pylori</italic> treatment</title>
<p>During the observation periods until December 2013 (median, 4.7 years; interquartile range, 2.5 to 7.3), death occurred in 364 (7.0&#x00025;) patients; 101 (5.9&#x00025;) patients in the <italic>H. pylori</italic> treatment cohort and 263 (7.6&#x00025;) in the non-treatment cohort. The <italic>H. pylori</italic> treatment cohort had a significantly higher overall survival rate compared to the non-treatment cohort (5-year overall survival rates, 95.4&#x00025; vs. 92.6&#x00025;, respectively; <italic>p</italic> = 0.015 by the log-rank test) (<xref rid="f2-kjim-2019-428" ref-type="fig">Fig. 2</xref>). In a multivariate Cox-proportional hazard regression analysis, <italic>H. pylori</italic> treatment cohort had a significantly reduced risk for overall mortality with an adjusted HR (aHR) of 0.74 (95&#x00025; CI, 0.59 to 0.93; <italic>p</italic> = 0.011) (<xref rid="t2-kjim-2019-428" ref-type="table">Table 2</xref>). Other significant risk factors associated with increased overall mortality were age &#x02265; 60 years, male sex, household income level lower than 50&#x00025;, CCI score &#x02265; 2 (vs. CCI score 0). Aspirin use (aHR, 0.76; 95&#x00025; CI, 0.58 to 0.99; <italic>p</italic> = 0.039) and metformin use (aHR, 0.56; 95&#x00025; CI, 0.44 to 0.71; <italic>p</italic> &lt; 0.001) were associated with decreased overall mortality.</p></sec>
<sec>
<title>Risk of cardiovascular disease, cerebrovascular disease, and overall cancer incidence according to <italic>H. pylori</italic> treatment</title>
<p>No significant differences were found in cardiovascular and cerebrovascular disease incidences between <italic>H. pylori</italic> treatment cohort and non-treatment cohort. <italic>H. pylori</italic> treatment cohort had increased risk for overall cancer incidence (aHR, 1.28; 95&#x00025; CI, 1.03 to 1.58; <italic>p</italic> = 0.024) compared with the non-treatment cohort. According to cancer type, the <italic>H. pylori</italic> treatment cohort showed significant incidence increase in colorectal cancer (aHR, 2.25; 95&#x00025; CI, 1.25 to 4.04; <italic>p</italic> = 0.007) and thyroid cancer (aHR, 1.54; 95&#x00025; CI, 1.02 to 2.31; <italic>p</italic> = 0.039) (<xref rid="t3-kjim-2019-428" ref-type="table">Table 3</xref>).</p></sec>
<sec>
<title>Mortality risk due to cardiovascular disease, cerebrovascular disease, and overall cancers according to <italic>H. pylori</italic> treatment</title>
<p>Mortality risks due to common cause of death including cardiovascular disease, cerebrovascular disease and cancers are described in <xref rid="t4-kjim-2019-428" ref-type="table">Table 4</xref>. Mortality risks due to cardiovascular disease (aHR, 1.34; 95&#x00025; CI, 0.54 to 3.30; <italic>p</italic> = 0.529), cerebrovascular disease (aHR, 0.97; 95&#x00025; CI, 0.37 to 2.55; <italic>p</italic> = 0.947), and overall cancers (aHR, 1.08; 95&#x00025; CI, 0.68 to 1.72; <italic>p</italic> = 0.742) were not significantly different between the <italic>H. pylori</italic> treatment and non-treatment cohorts. No significant associations between <italic>H. pylori</italic> treatment and mortality risks for gastric cancer (aHR, 1.75; 95&#x00025; CI, 0.46 to 6.60; <italic>p</italic> = 0.411) as well as other cancer types were found (<xref rid="t4-kjim-2019-428" ref-type="table">Table 4</xref>).</p></sec></sec>
<sec sec-type="discussion">
<title>DISCUSSION</title>
<p>In this retrospective cohort study, we investigated overall mortality risk according to <italic>H. pylori</italic> treatment as the primary outcome, and evaluated cause-specific mortality risks due to major causes of death in patients with type 2 diabetes. <italic>H. pylori</italic> treatment was associated with a significant decrease in the risk of overall mortality. However, <italic>H. pylori</italic> treatment was not associated with mortality risks due to cardiovascular disease, cerebrovascular disease, and overall cancers.</p>
<p>In the report of global cancer statistics 2018 (GLOBOCAN 2018), gastric cancer was the fifth most common cancer, and the third leading cause of cancer death worldwide &#x0005B;<xref ref-type="bibr" rid="b19-kjim-2019-428">19</xref>&#x0005D;. <italic>H. pylori</italic> was classified as a group 1 carcinogen for gastric cancer by the International Agency for Research on Cancer &#x0005B;<xref ref-type="bibr" rid="b20-kjim-2019-428">20</xref>&#x0005D;. More than 50&#x00025; of the world&#x02019;s population (approximately 4.4 billion individuals) was infected with <italic>H. pylori</italic> in 2015 &#x0005B;<xref ref-type="bibr" rid="b21-kjim-2019-428">21</xref>&#x0005D;. In Korea, gastric cancer was the most commonly diagnosed cancer in 2015 &#x0005B;<xref ref-type="bibr" rid="b22-kjim-2019-428">22</xref>&#x0005D;, and the estimated prevalence of <italic>H. pylori</italic> infection is about 54&#x00025; &#x0005B;<xref ref-type="bibr" rid="b21-kjim-2019-428">21</xref>&#x0005D;. However, <italic>H. pylori</italic> treatment as a primary prevention strategy for gastric cancer has not yet been implemented. Meta-analysis of RCTs showed 9&#x00025; to 12&#x00025; non-significant increase of overall mortality &#x0005B;<xref ref-type="bibr" rid="b1-kjim-2019-428">1</xref>,<xref ref-type="bibr" rid="b3-kjim-2019-428">3</xref>&#x0005D;. Of the two largest RCTs included in those meta-analyses, Wong et al. &#x0005B;<xref ref-type="bibr" rid="b23-kjim-2019-428">23</xref>&#x0005D; reported no increase in overall mortality risk (relative risk, 0.95; 95&#x00025; CI, 0.53 to 1.69), whereas Ma et al. &#x0005B;<xref ref-type="bibr" rid="b24-kjim-2019-428">24</xref>&#x0005D; showed 10&#x00025; non-significant increase of overall mortality risk (relative risk, 1.10; 95&#x00025; CI 0.89 to 1.36). However, overall mortality was evaluated as a secondary outcome in the previous trials and no primary outcome study has been performed &#x0005B;<xref ref-type="bibr" rid="b1-kjim-2019-428">1</xref>,<xref ref-type="bibr" rid="b23-kjim-2019-428">23</xref>,<xref ref-type="bibr" rid="b24-kjim-2019-428">24</xref>&#x0005D;. Therefore, we evaluated the overall mortality after <italic>H. pylori</italic> treatment as the primary study outcome in type 2 diabetes patients selected from the national cohort database who had increased cardiovascular or cerebrovascular disease risks. This database provides reliable data for mortality including exact date and cause of death. Overall mortality risk did not increase after <italic>H. pylori</italic> treatment, and this result is similar to that of our previous study evaluating the association between overall mortality and <italic>H. pylori</italic> treatment in a hypertension patient cohort &#x0005B;<xref ref-type="bibr" rid="b16-kjim-2019-428">16</xref>&#x0005D;. These results might be an evidence for supporting the use of <italic>H. pylori</italic> treatment as a primary prevention strategy for gastric cancer.</p>
<p>In the present study, most of the patients (98.4&#x00025;) in the <italic>H. pylori</italic> treatment cohort received clarithromycin-containing standard triple therapy. A clinical trial reported that clarithromycin use for 2 weeks in stable coronary artery disease increased cardiovascular mortality and overall mortality risk during 10-year follow-up period, although the exact underlying mechanism is unknown &#x0005B;<xref ref-type="bibr" rid="b7-kjim-2019-428">7</xref>,<xref ref-type="bibr" rid="b25-kjim-2019-428">25</xref>,<xref ref-type="bibr" rid="b26-kjim-2019-428">26</xref>&#x0005D;. In addition, clarithromycin use was associated with increased risk of cardiovascular mortality during short-term periods, especially because of arrhythmia-related cardiovascular events &#x0005B;<xref ref-type="bibr" rid="b9-kjim-2019-428">9</xref>,<xref ref-type="bibr" rid="b27-kjim-2019-428">27</xref>&#x0005D;. Meanwhile, retrospective studies evaluating the association between mortality and clarithromycin use for <italic>H. pylori</italic> treatment have reported inconsistent results &#x0005B;<xref ref-type="bibr" rid="b28-kjim-2019-428">28</xref>&#x02013;<xref ref-type="bibr" rid="b30-kjim-2019-428">30</xref>&#x0005D;. A retrospective study demonstrated that overall mortality risk after clarithromycin-containing <italic>H. pylori</italic> treatment significantly increased during a median follow-up of 3 years (aHR, 1.09; 95&#x00025; CI, 1.00 to 1.18) &#x0005B;<xref ref-type="bibr" rid="b28-kjim-2019-428">28</xref>&#x0005D;, whereas two studies did not show any increased risk in long-term overall mortality &#x0005B;<xref ref-type="bibr" rid="b29-kjim-2019-428">29</xref>,<xref ref-type="bibr" rid="b30-kjim-2019-428">30</xref>&#x0005D;. Previous studies included high-risk patients diagnosed with cardiovascular diseases (arrhythmia, ischemic heart disease, or heart failure) who might develop short-term adverse events or mortality associated with clarithromycin use &#x0005B;<xref ref-type="bibr" rid="b28-kjim-2019-428">28</xref>&#x02013;<xref ref-type="bibr" rid="b30-kjim-2019-428">30</xref>&#x0005D;. We excluded patients with cardiovascular or cerebrovascular diseases before or within 6 months after <italic>H. pylori</italic> treatment to avoid the short-term cardiovascular effects of clarithromycin use. In our study, the long-term cardiovascular mortality was not significantly associated with <italic>H. pylori</italic> treatment, although almost all patients (98.4&#x00025;) received a clarithromycin-containing standard triple regimen.</p>
<p>Our study showed that <italic>H. pylori</italic> treatment was associated with increased risk in overall cancer incidence but reduced risk in overall cancer mortality. Previous studies reported that antibiotics use was associated with increased overall cancer risks &#x0005B;<xref ref-type="bibr" rid="b31-kjim-2019-428">31</xref>&#x0005D;, and the risk of various cancers including lung, colon, prostate, and breast cancer &#x0005B;<xref ref-type="bibr" rid="b31-kjim-2019-428">31</xref>,<xref ref-type="bibr" rid="b32-kjim-2019-428">32</xref>&#x0005D;. One of the suggested mechanisms for increased cancer risks is disrupted gut microbiota (dysbiosis) by antibiotics use. Dysbiosis might have negative effects on the process of carcinogenesis including initiation, progression, and dissemination of cancer or cancer treatment efficacy &#x0005B;<xref ref-type="bibr" rid="b33-kjim-2019-428">33</xref>,<xref ref-type="bibr" rid="b34-kjim-2019-428">34</xref>&#x0005D;. However, in our study, significant increased risks were found only in colorectal cancer and thyroid cancer. In contrast, the colorectal cancer mortality risk did not increase, and no thyroid cancer mortality was observed. In Korea, colorectal cancer incidence also increased after the introduction of colorectal cancer screening program in 2004 with decreased trends of colorectal cancer mortality &#x0005B;<xref ref-type="bibr" rid="b22-kjim-2019-428">22</xref>,<xref ref-type="bibr" rid="b35-kjim-2019-428">35</xref>&#x0005D;. In addition, opportunistic thyroid cancer screening was associated with increased thyroid cancer incidence without a concomitant increase in thyroid cancer-related mortality &#x0005B;<xref ref-type="bibr" rid="b36-kjim-2019-428">36</xref>&#x0005D;. Thus, increased overall cancer incidence risk in the <italic>H. pylori</italic> treatment cohort seemed to be associated with increased cancer screening. Another explanation for the increased risk of overall cancer incidence in the treatment cohort might be associated with higher economic status. Because the treatment cohort had a higher proportion of patients with household income level of &gt; 50&#x00025; than the non-treatment cohort, patients in the treatment cohort might have accessed more health-care services, including opportunistic health screening programs. Further prospective studies are needed to investigate whether short duration of antibiotics use for <italic>H. pylori</italic> treatment (7 to 14 days) is associated with increased cancer risks due to dysbiosis.</p>
<p>Despite increased risks of cardiovascular disease and cancers in the <italic>H. pylori</italic> treatment cohort, no increase in overall mortality risk and cause-specific mortality risks due to cardiovascular disease and cancers were observed. In addition to the <italic>H. pylori</italic> treatment, the use of metformin (aHR, 0.56; <italic>p</italic> &lt; 0.001) and aspirin (aHR, 0.76; <italic>p</italic> = 0.039) were significant factors associated with reduced overall mortality risk. These results might be explained by the healthy user bias, that is, health-seeking patients tend to initiate preventive therapies and try to engage in healthy lifestyle behaviors, and metformin users are more likely to be engaged in healthy behaviors &#x0005B;<xref ref-type="bibr" rid="b37-kjim-2019-428">37</xref>&#x0005D;. In the present study, healthy user bias might be present, and the treatment cohort had higher proportions of better household income levels, and metformin users.</p>
<p>Our study findings should be interpreted in light of several limitations. First, our study population was type 2 diabetes patients, and the severity of diabetes might have been different between the <italic>H. pylori</italic> treatment cohort and non-treatment cohort. The severity of diabetes could not be assessed because the NHIS-NSC database did not provide any laboratory data such as glycated hemoglobin or blood glucose level. Second, the severity and treatment results of cardiovascular disease, cerebrovascular disease, or cancers might affect overall or disease-specific mortality. However, we could not assess the information due to the limitation of the NHIS-NSC database. Third, compliance for the <italic>H. pylori</italic> treatment and <italic>H. pylori</italic> eradication status after the treatment were not available from the database. Thus, we could not analyze whether <italic>H. pylori</italic> eradication status after treatment affected overall mortality or not. Third, in the non-treatment cohort, both <italic>H. pylori</italic> infected patients who were not treated and those who were not infected were included. Finally, although we included aspirin and metformin use as the covariate to evaluate risks of incidence and mortality from cardiovascular disease, cerebrovascular disease, and cancers, several factors were not considered in our analyses such as the type of intervention treatment or other drugs including anti-platelet agents or statins.</p>
<p>In conclusion, <italic>H. pylori</italic> treatment in patients with type 2 diabetes was not significantly associated with increased overall mortality. Among the major causes of death, no significant increase in the risk of mortality due to cardiovascular disease, cerebrovascular diseases, or overall cancers were observed. However, long-term prospective trials are necessary to confirm our findings and to apply <italic>H. pylori</italic> eradication as a primary gastric cancer prevention strategy in the general population without concern of overall mortality increase.</p>
<boxed-text>
<caption>
<title>KEY MESSAGE</title></caption>
<list list-type="order">
<list-item>
<p>In this population-based retrospective cohort study using the Korean National Health Insurance Service-National Sample Cohort database, long-term overall mortality risk was not increased after <italic>Helicobacter pylori</italic> treatment in patients with type 2 diabetes.</p></list-item>
<list-item>
<p>In addition, <italic>H. pylori</italic> treatment was not associated with mortality risk increase due to cardiovascular disease, cerebrovascular disease, and all cancers.</p></list-item>
<list-item>
<p>However, further long-term prospective trials are necessary to confirm our findings and to apply <italic>H. pylori</italic> eradication as a primary gastric cancer prevention strategy in the general population without concern of overall mortality increase.</p></list-item></list></boxed-text></sec>
</body>
<back>
<sec sec-type="supplementary-material"><title>Supplementary Materials</title>
<supplementary-material content-type="loca-data" id="s1-kjim-2019-428">
<label>Supplementary Table 1.</label><caption><p>Disease codes used for patient selection and outcome evaluation</p>
</caption><media mimetype="application" mime-subtype="pdf" xlink:href="kjim-2019-428-suppl1.pdf"/></supplementary-material>
<supplementary-material content-type="loca-data" id="s2-kjim-2019-428">
<label>Supplementary Figure 1</label><caption><p>The observation periods for study outcome evaluation. The initiation dates of observation period were <italic>Helicobacter pylori</italic> treatment prescription date in the treatment cohort and the corresponding date of <italic>H. pylori</italic> treatment prescription in matched patients of the non-treatment cohort. Outcome assessments were continued until December 2013.</p>
</caption><media mimetype="application" mime-subtype="pdf" xlink:href="kjim-2019-428-suppl2.pdf"/></supplementary-material>
</sec>
<ack>
<title>Acknowledgments</title>
<p>This study used the Korean National Health Insurance Service-National Sample Cohort database (NHIS-2016-2-191) provided by the National Health Insurance Service. This study was supported by a grant from the Korea Health Technology R&amp;D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (grant number HC15C1077) and partially supported by the grant from the National Cancer Center, Republic of Korea (grant number 1910370).</p></ack>
<fn-group><fn id="fn1-kjim-2019-428" fn-type="conflict">
<p><bold>Conflict of interest</bold></p>
<p>No potential conflict of interest relevant to this article was reported.</p></fn></fn-group>
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<sec sec-type="display-objects">
<title>Figures and Tables</title>
<fig id="f1-kjim-2019-428" position="float">
<label>Figure 1</label>
<caption>
<p>Study flow. A total of 1,727 patients in the <italic>Helicobacter pylori</italic> treatment cohort were matched with 3,454 patients in the non-treatment cohort at a 1:2 ratio by using simple random sampling without replacement.</p></caption>
<graphic xlink:href="kjim-2019-428f1.gif"/></fig>
<fig id="f2-kjim-2019-428" position="float">
<label>Figure 2</label>
<caption>
<p>Kaplan-Meier curves for overall survival according to the <italic>Helicobacter pylori</italic> treatment. During a median follow-up of 4.7 years, death of any cause was reported in 5.9&#x00025; of patients in the <italic>H. pylori</italic> treatment cohort and 7.6&#x00025; of patients in the non-treatment cohort. The <italic>H. pylori</italic> treatment cohort had a significantly higher overall survival rate as compared with the non-treatment cohort (<italic>p</italic> = 0.015 by the log-rank test).</p></caption>
<graphic xlink:href="kjim-2019-428f2.gif"/></fig>
<table-wrap id="t1-kjim-2019-428" position="float">
<label>Table 1</label>
<caption>
<p>Baseline characteristics of the study population</p></caption>
<table frame="hsides" rules="rows">
<thead>
<tr>
<th valign="middle" align="left">Characteristic</th>
<th valign="middle" align="center"><italic>H. pylori</italic> treatment cohort (n = 1,727)</th>
<th valign="middle" align="center">Non-treatment cohort (n = 3,454)</th>
<th valign="middle" align="center"><italic>p</italic> value</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Age, yr</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.000</td></tr>
<tr>
<td valign="top" align="left">&#x02003;20&#x02013;29</td>
<td valign="top" align="center">15 (0.9)</td>
<td valign="top" align="center">30 (0.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;30&#x02013;39</td>
<td valign="top" align="center">180 (10.4)</td>
<td valign="top" align="center">360 (10.4)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;40&#x02013;49</td>
<td valign="top" align="center">578 (33.5)</td>
<td valign="top" align="center">1,156 (33.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;50&#x02013;59</td>
<td valign="top" align="center">586 (33.9)</td>
<td valign="top" align="center">1,172 (33.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;60&#x02013;69</td>
<td valign="top" align="center">326 (18.9)</td>
<td valign="top" align="center">652 (18.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;70&#x02013;79</td>
<td valign="top" align="center">39 (2.3)</td>
<td valign="top" align="center">78 (2.3)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02265; 80</td>
<td valign="top" align="center">3 (0.2)</td>
<td valign="top" align="center">6 (0.2)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Sex</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.000</td></tr>
<tr>
<td valign="top" align="left">&#x02003;Male</td>
<td valign="top" align="center">1,090 (63.1)</td>
<td valign="top" align="center">2,180 (63.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Female</td>
<td valign="top" align="center">637 (36.9)</td>
<td valign="top" align="center">1,274 (36.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Residential area</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.090</td></tr>
<tr>
<td valign="top" align="left">&#x02003;Metropolitan</td>
<td valign="top" align="center">836 (48.4)</td>
<td valign="top" align="center">1,586 (45.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Small city or rural</td>
<td valign="top" align="center">891 (51.6)</td>
<td valign="top" align="center">1,868 (54.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Household income level</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.001</td></tr>
<tr>
<td valign="top" align="left">&#x02003;0&#x00025;&#x02013;50&#x00025;</td>
<td valign="top" align="center">651 (37.7)</td>
<td valign="top" align="center">1,475 (42.7)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;51&#x00025;&#x02013;100&#x00025;</td>
<td valign="top" align="center">1,076 (62.3)</td>
<td valign="top" align="center">1,979 (57.3)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Smoking</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.003</td></tr>
<tr>
<td valign="top" align="left">&#x02003;Never smoker</td>
<td valign="top" align="center">679 (39.3)</td>
<td valign="top" align="center">1,215 (35.2)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Ex-smoker</td>
<td valign="top" align="center">167 (9.7)</td>
<td valign="top" align="center">258 (7.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Current smoker</td>
<td valign="top" align="center">403 (23.3)</td>
<td valign="top" align="center">546 (15.8)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Missing</td>
<td valign="top" align="center">478 (27.7)</td>
<td valign="top" align="center">1,435 (41.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Alcohol drinking</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.425</td></tr>
<tr>
<td valign="top" align="left">&#x02003;Never drinking</td>
<td valign="top" align="center">707 (40.9)</td>
<td valign="top" align="center">1,181 (34.2)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;1&#x02013;2 time/wk</td>
<td valign="top" align="center">378 (21.9)</td>
<td valign="top" align="center">600 (17.4)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;3&#x02013;4 time/wk</td>
<td valign="top" align="center">129 (7.5)</td>
<td valign="top" align="center">212 (6.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;5&#x02013;7 time/wk</td>
<td valign="top" align="center">83 (4.8)</td>
<td valign="top" align="center">108 (3.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Missing</td>
<td valign="top" align="center">430 (24.9)</td>
<td valign="top" align="center">1,353 (39.2)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Body mass index, kg/m<sup>2</sup></td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.208</td></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02264; 18.5</td>
<td valign="top" align="center">11 (0.6)</td>
<td valign="top" align="center">31 (0.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;18.6&#x02013;2.9</td>
<td valign="top" align="center">338 (19.6)</td>
<td valign="top" align="center">522 (15.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;23.0&#x02013;24.9</td>
<td valign="top" align="center">362 (21.0)</td>
<td valign="top" align="center">565 (16.4)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02265; 25.0</td>
<td valign="top" align="center">600 (34.7)</td>
<td valign="top" align="center">1,031 (29.8)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Missing</td>
<td valign="top" align="center">416 (24.1)</td>
<td valign="top" align="center">1,305 (37.8)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">CCI score at the time of type 2 diabetes diagnosis</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1.000</td></tr>
<tr>
<td valign="top" align="left">&#x02003;0</td>
<td valign="top" align="center">665 (38.5)</td>
<td valign="top" align="center">1,330 (38.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;1</td>
<td valign="top" align="center">381 (22.1)</td>
<td valign="top" align="center">762 (22.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02265; 2</td>
<td valign="top" align="center">681 (39.4)</td>
<td valign="top" align="center">1,362 (39.4)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Aspirin use<xref rid="tfn3-kjim-2019-428" ref-type="table-fn">a</xref></td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.963</td></tr>
<tr>
<td valign="top" align="left">&#x02003;No</td>
<td valign="top" align="center">1,338 (77.5)</td>
<td valign="top" align="center">2,678 (77.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Yes</td>
<td valign="top" align="center">389 (22.5)</td>
<td valign="top" align="center">776 (22.5)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Metformin use<xref rid="tfn3-kjim-2019-428" ref-type="table-fn">a</xref></td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">0.011</td></tr>
<tr>
<td valign="top" align="left">&#x02003;No</td>
<td valign="top" align="center">294 (17.0)</td>
<td valign="top" align="center">689 (19.9)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Yes</td>
<td valign="top" align="center">1,433 (83.0)</td>
<td valign="top" align="center">2,765 (80.1)</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left"><italic>H. pylori</italic> treatment regimen</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">-</td></tr>
<tr>
<td valign="top" align="left">&#x02003;PPI-clarithromycin containing triple therapy</td>
<td valign="top" align="center">1,658 (96.0)</td>
<td valign="top" align="center">-</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Bismuth-containing quadruple therapy</td>
<td valign="top" align="center">27 (1.6)</td>
<td valign="top" align="center">-</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">&#x02003;Both</td>
<td valign="top" align="center">42 (2.4)</td>
<td valign="top" align="center">-</td>
<td valign="top" align="center"/></tr>
<tr>
<td valign="top" align="left">Follow-up period, yr</td>
<td valign="top" align="center">4.79 (2.61&#x02013;7.35)</td>
<td valign="top" align="center">4.71 (2.50&#x02013;7.26)</td>
<td valign="top" align="center">0.360</td></tr></tbody></table>
<table-wrap-foot><fn id="tfn1-kjim-2019-428">
<p>Values are presented as number (&#x00025;) or median (interquartile range).</p></fn><fn id="tfn2-kjim-2019-428">
<p><italic>H. pylori</italic>, <italic>Helicobacter pylori</italic>; CCI, Charlson comorbidity index; PPI, proton-pump inhibitor.</p></fn><fn id="tfn3-kjim-2019-428">
<label>a</label>
<p>Patients who used aspirin and metformin were defined as those who were prescribed the drugs for at least 30 days.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="t2-kjim-2019-428" position="float">
<label>Table 2</label>
<caption>
<p>Risk factors associated with overall mortality</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="middle" rowspan="3" align="left">Variable</th>
<th valign="middle" rowspan="3" align="center">No.</th>
<th colspan="2" valign="middle" align="center">Univariate analysis<xref rid="tfn5-kjim-2019-428" ref-type="table-fn">a</xref></th>
<th colspan="2" valign="middle" align="center">Multivariate analysis<xref rid="tfn5-kjim-2019-428" ref-type="table-fn">a</xref>,<xref rid="tfn6-kjim-2019-428" ref-type="table-fn">b</xref></th></tr>
<tr>
<th colspan="2" valign="middle" align="center">
<hr/></th>
<th colspan="2" valign="middle" align="center">
<hr/></th></tr>
<tr>
<th valign="middle" align="center">Unadjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th>
<th valign="middle" align="center">Adjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Age, yr</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;&lt; 60</td>
<td valign="top" align="center">4,077</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02265; 60</td>
<td valign="top" align="center">1,104</td>
<td valign="top" align="left">3.39 (2.75&#x02013;4.17)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">3.58 (2.90&#x02013;4.42)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Sex</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">0.005</td>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Female</td>
<td valign="top" align="center">3,270</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Male</td>
<td valign="top" align="center">1,911</td>
<td valign="top" align="left">1.38 (1.10&#x02013;1.73)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.64 (1.31&#x02013;2.05)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Household income level</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;0&#x00025;&#x02013;50&#x00025;</td>
<td valign="top" align="center">2,126</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;51&#x00025;&#x02013;100&#x00025;</td>
<td valign="top" align="center">3,055</td>
<td valign="top" align="left">0.68 (0.55&#x02013;0.83)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">0.68 (0.55&#x02013;0.84)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Residential area</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">0.446</td>
<td valign="top" align="left"/>
<td valign="top" align="right">0.986</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Metropolitan</td>
<td valign="top" align="center">2,422</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Small city or rural</td>
<td valign="top" align="center">2,759</td>
<td valign="top" align="left">1.08 (0.88&#x02013;1.33)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00 (0.81&#x02013;1.23)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">CCI score</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right"/>
<td valign="top" align="left"/>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;0</td>
<td valign="top" align="center">1,802</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;1</td>
<td valign="top" align="center">1,310</td>
<td valign="top" align="left">1.11 (0.83&#x02013;1.50)</td>
<td valign="top" align="right">0.486</td>
<td valign="top" align="left">1.18 (0.87&#x02013;1.58)</td>
<td valign="top" align="right">0.291</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;&#x02265; 2</td>
<td valign="top" align="center">2,069</td>
<td valign="top" align="left">1.68 (1.31&#x02013;2.14)</td>
<td valign="top" align="right">&lt; 0.001</td>
<td valign="top" align="left">1.73 (1.35&#x02013;2.22)</td>
<td valign="top" align="right">&lt; 0.001</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left"><italic>H. pylori</italic> treatment</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">0.016</td>
<td valign="top" align="left"/>
<td valign="top" align="right">0.011</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;No</td>
<td valign="top" align="center">3,454</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Yes</td>
<td valign="top" align="center">1,727</td>
<td valign="top" align="left">0.75 (0.60&#x02013;0.95)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">0.74 (0.59&#x02013;0.93)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Aspirin use</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">0.378</td>
<td valign="top" align="left"/>
<td valign="top" align="right">0.039</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;No</td>
<td valign="top" align="center">4,016</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Yes</td>
<td valign="top" align="center">1,165</td>
<td valign="top" align="left">0.89 (0.69&#x02013;1.15)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">0.76 (0.58&#x02013;0.99)</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Metformin use</td>
<td valign="top" align="center"/>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td>
<td valign="top" align="left"/>
<td valign="top" align="right">&lt; 0.001</td></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;No</td>
<td valign="top" align="center">983</td>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/>
<td valign="top" align="left">1.00</td>
<td valign="top" align="right"/></tr>
<tr>
<td colspan="6" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Yes</td>
<td valign="top" align="center">4,198</td>
<td valign="top" align="left">0.53 (0.42&#x02013;0.67)</td>
<td valign="top" align="right"/>
<td valign="top" align="left">0.56 (0.44&#x02013;0.71)</td>
<td valign="top" align="right"/></tr></tbody></table>
<table-wrap-foot><fn id="tfn4-kjim-2019-428">
<p>HR, hazard ratio; CI, confidence interval; CCI, Charlson comorbidity index; <italic>H. pylori</italic>, <italic>Helicobacter pylori</italic>.</p></fn><fn id="tfn5-kjim-2019-428">
<label>a</label>
<p>Analyses were performed using the Cox-proportional hazard model.</p></fn><fn id="tfn6-kjim-2019-428">
<label>b</label>
<p>Covariates for multivariate analysis included age, sex, economic status level, residential area, Charlson comorbidity index score, <italic>H. pylori</italic> treatment, and aspirin and metformin use.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="t3-kjim-2019-428" position="float">
<label>Table 3</label>
<caption>
<p>Risk of incidence of cardiovascular diseases, cerebrovascular diseases, and cancer according to <italic>H. pylori</italic> treatment</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="middle" rowspan="3" align="left">Variable</th>
<th colspan="2" valign="middle" align="center">No. of incidence (&#x00025;)</th>
<th colspan="4" valign="middle" align="center">Risk of incidence for <italic>H. pylori</italic> treatment cohort<xref rid="tfn8-kjim-2019-428" ref-type="table-fn">a</xref></th></tr>
<tr>
<th colspan="2" valign="middle" align="center">
<hr/></th>
<th colspan="4" valign="middle" align="center">
<hr/></th></tr>
<tr>
<th valign="middle" align="center"><italic>H. pylori</italic> treatment cohort (n = 1,727)</th>
<th valign="middle" align="center">Non-treatment cohort (n = 3,454)</th>
<th valign="middle" align="center">Unadjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th>
<th valign="middle" align="center">Adjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Cardiovascular disease</td>
<td valign="top" align="center">240 (13.90)</td>
<td valign="top" align="center">408 (11.81)</td>
<td valign="top" align="center">1.20 (1.02&#x02013;1.40)</td>
<td valign="top" align="left">0.028</td>
<td valign="top" align="center">1.16 (0.98&#x02013;1.36)</td>
<td valign="top" align="left">0.078</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Cerebrovascular disease</td>
<td valign="top" align="center">140 (8.11)</td>
<td valign="top" align="center">270 (7.82)</td>
<td valign="top" align="center">1.04 (0.85&#x02013;1.28)</td>
<td valign="top" align="left">0.692</td>
<td valign="top" align="center">1.02 (0.83&#x02013;1.25)</td>
<td valign="top" align="left">0.843</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Overall cancers</td>
<td valign="top" align="center">143 (8.28)</td>
<td valign="top" align="center">226 (6.54)</td>
<td valign="top" align="center">1.29 (1.04&#x02013;1.59)</td>
<td valign="top" align="left">0.019</td>
<td valign="top" align="center">1.28 (1.03&#x02013;1.58)</td>
<td valign="top" align="left">0.024</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Stomach cancer</td>
<td valign="top" align="center">21 (1.22)</td>
<td valign="top" align="center">31 (0.90)</td>
<td valign="top" align="center">1.36 (0.78&#x02013;2.36)</td>
<td valign="top" align="left">0.279</td>
<td valign="top" align="center">1.48 (0.85&#x02013;2.60)</td>
<td valign="top" align="left">0.169</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Oral cancer</td>
<td valign="top" align="center">8 (0.46)</td>
<td valign="top" align="center">7 (0.20)</td>
<td valign="top" align="center">2.29 (0.83&#x02013;6.31)</td>
<td valign="top" align="left">0.110</td>
<td valign="top" align="center">2.12 (0.77&#x02013;5.88)</td>
<td valign="top" align="left">0.148</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Esophageal cancer</td>
<td valign="top" align="center">1 (0.06)</td>
<td valign="top" align="center">1 (0.03)</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="left"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="left"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Colorectal cancer</td>
<td valign="top" align="center">24 (1.39)</td>
<td valign="top" align="center">22 (0.64)</td>
<td valign="top" align="center">2.20 (1.23&#x02013;3.92)</td>
<td valign="top" align="left">0.008</td>
<td valign="top" align="center">2.25 (1.25&#x02013;4.04)</td>
<td valign="top" align="left">0.007</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Liver cancer</td>
<td valign="top" align="center">20 (1.16)</td>
<td valign="top" align="center">39 (1.13)</td>
<td valign="top" align="center">1.03 (0.60&#x02013;1.76)</td>
<td valign="top" align="left">0.922</td>
<td valign="top" align="center">0.91 (0.53&#x02013;1.57)</td>
<td valign="top" align="left">0.739</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Biliary tract cancer</td>
<td valign="top" align="center">5 (0.29)</td>
<td valign="top" align="center">4 (0.12)</td>
<td valign="top" align="center">2.50 (0.67&#x02013;9.32)</td>
<td valign="top" align="left">0.172</td>
<td valign="top" align="center">2.50 (0.66&#x02013;9.44)</td>
<td valign="top" align="left">0.177</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Pancreatic cancer</td>
<td valign="top" align="center">8 (0.46)</td>
<td valign="top" align="center">11 (0.32)</td>
<td valign="top" align="center">1.46 (0.59&#x02013;3.62)</td>
<td valign="top" align="left">0.419</td>
<td valign="top" align="center">1.30 (0.52&#x02013;3.25)</td>
<td valign="top" align="left">0.575</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Lung cancer</td>
<td valign="top" align="center">9 (0.52)</td>
<td valign="top" align="center">25 (0.72)</td>
<td valign="top" align="center">0.72 (0.34&#x02013;1.54)</td>
<td valign="top" align="left">0.397</td>
<td valign="top" align="center">0.75 (0.35&#x02013;1.62)</td>
<td valign="top" align="left">0.470</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Breast cancer</td>
<td valign="top" align="center">3 (0.17)</td>
<td valign="top" align="center">7 (0.20)</td>
<td valign="top" align="center">0.86 (0.22&#x02013;3.31)</td>
<td valign="top" align="left">0.823</td>
<td valign="top" align="center">0.70 (0.18&#x02013;2.75)</td>
<td valign="top" align="left">0.614</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Prostate cancer</td>
<td valign="top" align="center">12 (0.69)</td>
<td valign="top" align="center">23 (0.67)</td>
<td valign="top" align="center">1.04 (0.52&#x02013;2.10)</td>
<td valign="top" align="left">0.906</td>
<td valign="top" align="center">1.04 (0.24&#x02013;4.43)</td>
<td valign="top" align="left">0.957</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Bladder cancer</td>
<td valign="top" align="center">3 (0.17)</td>
<td valign="top" align="center">5 (0.14)</td>
<td valign="top" align="center">1.20 (0.29&#x02013;5.02)</td>
<td valign="top" align="left">0.803</td>
<td valign="top" align="center">1.67 (0.64&#x02013;4.37)</td>
<td valign="top" align="left">0.296</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Thyroid cancer</td>
<td valign="top" align="center">8 (0.46)</td>
<td valign="top" align="center">9 (0.26)</td>
<td valign="top" align="center">1.78 (0.69&#x02013;4.61)</td>
<td valign="top" align="left">0.236</td>
<td valign="top" align="center">1.54 (1.02&#x02013;2.31)</td>
<td valign="top" align="left">0.039</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Brain, CNS cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">2 (0.06)</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="left"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="left"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Non-Hodgkin lymphoma</td>
<td valign="top" align="center">2 (0.12)</td>
<td valign="top" align="center">1 (0.03)</td>
<td valign="top" align="center">4.00 (0.36&#x02013;44.12)</td>
<td valign="top" align="left">0.258</td>
<td valign="top" align="center">3.57 (0.32&#x02013;39.93)</td>
<td valign="top" align="left">0.302</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Leukemia</td>
<td valign="top" align="center">2 (0.12)</td>
<td valign="top" align="center">2 (0.06)</td>
<td valign="top" align="center">2.00 (0.28&#x02013;14.21)</td>
<td valign="top" align="left">0.488</td>
<td valign="top" align="center">2.34 (0.33&#x02013;16.75)</td>
<td valign="top" align="left">0.397</td></tr></tbody></table>
<table-wrap-foot><fn id="tfn7-kjim-2019-428">
<p><italic>H. pylori</italic>, <italic>Helicobacter pylori</italic>; HR, hazard ratio; CI, confidence interval; NA, not available; CNS, cerebral nervous system.</p></fn><fn id="tfn8-kjim-2019-428">
<label>a</label>
<p>The Cox-proportional hazard model was used for calculation of HR. In the multivariate analyses, covariates included were age, sex, economic status level, residential area, Charlson comorbidity index score, and aspirin and metformin use.</p></fn></table-wrap-foot></table-wrap>
<table-wrap id="t4-kjim-2019-428" position="float">
<label>Table 4</label>
<caption>
<p>Risk of cause-specific mortality according to <italic>H. pylori</italic> treatment</p></caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th valign="middle" rowspan="3" align="left">Variable</th>
<th colspan="2" valign="middle" align="center">No. of death (&#x00025;)</th>
<th colspan="4" valign="middle" align="center">Risk of mortality for <italic>H. pylori</italic> treatment cohort<xref rid="tfn10-kjim-2019-428" ref-type="table-fn">a</xref></th></tr>
<tr>
<th colspan="2" valign="middle" align="center">
<hr/></th>
<th colspan="4" valign="middle" align="center">
<hr/></th></tr>
<tr>
<th valign="middle" align="center"><italic>H. pylori</italic> treatment cohort (n = 1,727)</th>
<th valign="middle" align="center">Non-treatment cohort (n = 3,454)</th>
<th valign="middle" align="center">Unadjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th>
<th valign="middle" align="center">Adjusted HR (95&#x00025; CI)</th>
<th valign="middle" align="center"><italic>p</italic> value</th></tr></thead>
<tbody>
<tr>
<td valign="top" align="left">Overall</td>
<td valign="top" align="center">101 (5.85)</td>
<td valign="top" align="center">263 (7.61)</td>
<td valign="top" align="center">0.75 (0.60&#x02013;0.95)</td>
<td valign="top" align="center">0.016</td>
<td valign="top" align="center">0.74 (0.59&#x02013;0.93)</td>
<td valign="top" align="center">0.011</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Cardiovascular disease</td>
<td valign="top" align="center">8 (0.46)</td>
<td valign="top" align="center">12 (0.35)</td>
<td valign="top" align="center">1.33 (0.55&#x02013;3.26)</td>
<td valign="top" align="center">0.529</td>
<td valign="top" align="center">1.34 (0.54&#x02013;3.30)</td>
<td valign="top" align="center">0.529</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Cerebrovascular disease</td>
<td valign="top" align="center">6 (0.35)</td>
<td valign="top" align="center">14 (0.41)</td>
<td valign="top" align="center">0.86 (0.33&#x02013;2.23)</td>
<td valign="top" align="center">0.754</td>
<td valign="top" align="center">0.97 (0.37&#x02013;2.55)</td>
<td valign="top" align="center">0.947</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">Overall cancers</td>
<td valign="top" align="center">28 (1.62)</td>
<td valign="top" align="center">53 (1.53)</td>
<td valign="top" align="center">1.06 (0.67&#x02013;1.67)</td>
<td valign="top" align="center">0.811</td>
<td valign="top" align="center">1.08 (0.68&#x02013;1.72)</td>
<td valign="top" align="center">0.742</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Stomach cancer</td>
<td valign="top" align="center">4 (0.23)</td>
<td valign="top" align="center">5 (0.14)</td>
<td valign="top" align="center">1.60 (0.43&#x02013;5.96)</td>
<td valign="top" align="center">0.483</td>
<td valign="top" align="center">1.75 (0.46&#x02013;6.60)</td>
<td valign="top" align="center">0.411</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Oral cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Esophageal cancer</td>
<td valign="top" align="center">1 (0.06)</td>
<td valign="top" align="center">1 (0.03)</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Colorectal cancer</td>
<td valign="top" align="center">1 (0.06)</td>
<td valign="top" align="center">3 (0.09)</td>
<td valign="top" align="center">0.67 (0.07&#x02013;6.41)</td>
<td valign="top" align="center">0.726</td>
<td valign="top" align="center">0.87 (0.09&#x02013;8.58)</td>
<td valign="top" align="center">0.903</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Liver cancer</td>
<td valign="top" align="center">6 (0.35)</td>
<td valign="top" align="center">16 (0.46)</td>
<td valign="top" align="center">0.75 (0.29&#x02013;1.91)</td>
<td valign="top" align="center">0.545</td>
<td valign="top" align="center">0.65 (0.25&#x02013;1.69)</td>
<td valign="top" align="center">0.380</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Biliary tract cancer</td>
<td valign="top" align="center">4 (0.23)</td>
<td valign="top" align="center">3 (0.09)</td>
<td valign="top" align="center">2.67 (0.60&#x02013;11.93)</td>
<td valign="top" align="center">0.199</td>
<td valign="top" align="center">2.97 (0.65&#x02013;13.59)</td>
<td valign="top" align="center">0.162</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Pancreatic cancer</td>
<td valign="top" align="center">2 (0.12)</td>
<td valign="top" align="center">6 (0.17)</td>
<td valign="top" align="center">0.67 (0.14&#x02013;3.30)</td>
<td valign="top" align="center">0.619</td>
<td valign="top" align="center">0.64 (0.13&#x02013;3.22)</td>
<td valign="top" align="center">0.590</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Lung cancer</td>
<td valign="top" align="center">6 (0.35)</td>
<td valign="top" align="center">10 (0.29)</td>
<td valign="top" align="center">1.20 (0.44&#x02013;3.31)</td>
<td valign="top" align="center">0.721</td>
<td valign="top" align="center">1.47 (0.53&#x02013;4.10)</td>
<td valign="top" align="center">0.466</td></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Breast cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Prostate cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Bladder cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Thyroid cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Brain, CNS cancer</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">1 (0.03)</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Non-Hodgkin lymphoma</td>
<td valign="top" align="center">2 (0.12)</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr>
<tr>
<td colspan="7" valign="top" align="left">
<hr/></td></tr>
<tr>
<td valign="top" align="left">&#x02003;Leukemia</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/>
<td valign="top" align="center">NA</td>
<td valign="top" align="center"/></tr></tbody></table>
<table-wrap-foot><fn id="tfn9-kjim-2019-428">
<p><italic>H. pylori</italic>, <italic>Helicobacter pylori</italic>; HR, hazard ratio; CI, confidence interval; NA, not available; CNS, cerebral nervous system.</p></fn><fn id="tfn10-kjim-2019-428">
<label>a</label>
<p>The Cox-proportional hazard model was used for calculation of HR. In the multivariate analyses, covariates included were age, sex, economic status level, residential area, Charlson comorbidity index, and aspirin and metformin use.</p></fn></table-wrap-foot></table-wrap></sec></back></article>
