Interleukin-10-819 promoter polymorphism in association with gastric cancer risk

Huiping Xue
Bing Lin
Jianfu An
†
Yuyuan Zhu
†
Gang Huang
Interleukin-10-819 promoter polymorphism in association with gastric cancer risk
R E S E A R C H A R T I C L E Open Access
Background: Potential functional allele T/C single nucleotide polymorphism (SNP) of Interleukin 10 (IL-10) promoter -819 (rs1800871) has been implicated in gastric cancer risk. We aimed to explore the role of T/C SNP of IL-10 -819 in the susceptibility to gastric cancer through a systematic review and meta-analysis.Methods: Each initially included article was scored for quality appraisal. Desirable data were extracted and registered into databases. 11 studies were ultimately eligible for the meta-analysis of IL-10 -819 T/C SNP. We adopted the most probably appropriate genetic model (recessive model). Potential sources of heterogeneity were sought out via subgroup and sensitivity analyses, and publication biases were estimated.Results: IL-10 -819 TT genotype is associated with the overall reduced gastric cancer risk among Asians and even apparently observed among high quality subgroup Asians. IL-10-819 TT genotype is not statistically associated with the overall reduced gastric cancer susceptibility in persons with H. pylori infection compared with controls without H. pylori infection. IL-10 -819 TT genotype is reversely associated with diffuse-subtype risk but not in intestinalsubtype risk. IL-10 -819 TT genotype is not reversely associated with non-cardia or cardia subtype gastric cancer susceptibility.Conclusions: IL-10 -819 TT genotype seems to be more protective from gastric cancer in Asians. Whether IL-10 -819 TT genotype may be protective from gastric cancer susceptibility in persons infected with H. pylori or in diffuse-subtype cancer needs further exploring in the future well-designed high quality studies among different ethnicity populations. Direct sequencing should be more used in the future.

Background

Nowadays, worldwide gastric cancer incidence has decreased but its mortality still ranks second [1][2][3]. In Asia [4], especially China [5], gastric cancer constitutes the top lethal malignancy. As is widely known, infectious, dietary, environmental, and genetic factors are implicated in gastric carcinogenesis, but only a minority of persons exposed to risk factors such as Helicobacter pylori (H. pylori) infection ultimately develop gastric cancer [6], which implies that host genetic susceptibility plays an important role in developing gastric cancer [7][8][9]. Such various susceptibilities could be explained, in part, by single nucleotide polymorphisms (SNPs) of susceptible genes [7][8][9]. During the long pathogenesis from chronic gastritis to gastric cancer spawned by H. pylori infection, host-activated neutrophils and mononuclear cells can produce not only proinflammatory cytokines such as interleukin (IL)-1β, IL-6, IL-8 and tumor necrosis factor (TNF)-α but also anti-inflammatory cytokines like IL-10. Rivetingly, the level of IL-10 besides those of IL-1 and TNF-α could also be elevated in gastric mucosa infected with H. pylori.

IL-10, a potent pleiotropic cytokine, has the dual ability to immunosuppress or immunostimulate anti-cancer properties [10]. Interleukin-10 inhibits the production of pro-inflammatory cytokines by inhibition of T-helper 1 (Th1) lymphocytes and stimulation of B lymphocytes and Th2 lymphocytes and thus downregulates the inflammatory response [10][11][12]. The human IL-10 gene, located on chromosome 1q31-32, consists of five exons and four introns and one of polymorphisms is reported in its promoter region at position -819 C/T SNP [13].

In 2003, Wu MS et al. [14] first published their study on IL-10-819 C/T SNP. Since then, researchers have consecutively reported associations of IL-10-819 C/T SNP with the susceptibility to gastric cancer, but with mixed or conflicting results [15][16][17][18][19][20][21][22][23][24][25]. Up to now, there has been only one published meta-analysis article focusing on IL-10-819 C/T SNP [26], but that meta-analysis failed to adopt the most likely appropriate genetic model, and thus the authentic values of statistical results could be compromised.

Accordingly, the aim of our meta-analysis was to shed more light, using the most appropriate genetic model, on the role of IL-10-819 C/T SNP in the risk of developing gastric cancer and to identify possible sources of heterogeneity among the eligible studies.

Methods

Search strategy

A systematic literature search was performed for articles regarding IL-10-819 C/T SNP associated with the risk of developing gastric cancer. The MEDLINE, EMBASE databases, Chinese National Knowledge Infrastructure (CNKI), Web of Science, and BIOSIS databases were used simultaneously with the combination of terms "Interleukin 10", "IL-10", "interleukin", or "cytokine"; "gene"; "polymorphism", "variant", or "SNP"; and "gastric cancer", "gastric carcinoma", "diffuse gastric cancer" or "stomach cancer" from January 2000 to September 2011. The search was performed without any restriction on language. The scope of computerized literature search was expanded according to the reference lists of retrieved articles. The relevant original articles were also sought manually.

Study selection

Studies concerning the association of IL-10-819 C/T SNP with the risk of developing gastric cancer were included if the following conditions were met: (i) any study described the association of IL-10-819 C/T SNP with gastric cancer; (ii) any study reported the numbers of both controls and gastric cancer cases; (iii) results were expressed as odds ratio (OR) with 95% confidence intervals (CI); and (iv) studies were case-control or nested case-control ones.

Methodological quality appraisal

To identify high-quality studies, we mainly adopted predefined criteria for Quality Appraisal initially proposed by Thakkinstian et al. [27], adapted by Camargo et al. [28], and refined by Xue et al. [7][8][9]. The criteria (seen in Additional file 1: Table S1) cover credibility of controls, representativeness of cases, consolidation of gastric cancer, genotyping examination, and association assessment [7][8][9]. Methodological quality was independently assessed by two investigators (B. Lin and J. An). Disagreements were resolved through discussion. Scores ranged from the lowest zero to the highest ten. Articles with the score lower than 6.5 were considered "low or moderate quality" ones, whereas those no lower than 6.5 were thought of as "high quality" ones.

Data extraction

The following data from each article were extracted: authors, year of publication, country, ethnicity of participants (categorized as Caucasians, Asians, Latinos, etc.), study design, source of controls, number of controls and of cases, genotyping method, distribution of age and gender, Lauren's classification (intestinal, diffuse, or mixed), and anatomical classification (cardia or non-cardia cancer).

The data were extracted and registered into two databases independently by two investigators (B.Lin and J An) who were blind to journal names, institutions or fund grants. Any discrepancy between these two investigators was resolved by the third investigator (H. Xue), who participated in the discussion with them and made an ultimate decision.

Statistical analysis

All statistical analyses were performed using STATA statistical software (Version 10.1, STATA Corp, College Station, TX). Two-sided Ps < 0.05 were considered statistically significant. HWE in controls was calculated again in our meta-analysis. The chi-square goodness of fit was used to test deviation from HWE (significant at the 0.05 level). Odds ratios (OR) and 95% confidence intervals (95% CI) were employed to assess the strength of associations between IL-10-819 T/C SNP with gastric cancer risk. OR 1 , OR 2 , and OR 3 regarding IL-10-819 T/ C SNP were calculated for genotypes TT versus CC, CT versus CC, and TT versus CT, respectively.

The above pairwise differences were used to determine the most appropriate genetic model. If OR 1 = OR 3 ≠ 1 and OR 2 = 1, then a recessive model is suggested. If OR 1 = OR 2 ≠ 1 and OR 3 = 1, then a dominant model is implied. If OR 2 = 1/OR 3 ≠ 1 and OR 1 = 1, then a complete overdominant model is suggested. If OR 1 > OR 2 > 1 and OR 1 > OR 3 > 1, or OR 1 < OR 2 < 1 and OR 1 < OR 3 < 1, then a codominant model is indicated [29]. If a dominant model was indicated, the original grouping was collapsed and the new group of T carriers (TT + CT) was compared with CC genotype; if a recessive model was suggested, TT was compared to the group of CC plus CT; if a complete overdominant model was implied, the group of TT plus CC was compared with CT; or if a codominant model was insinuated, TT was compared with CT and with CC, respectively.

The Q statistic was used to test for heterogeneity among the studies included in the meta-analysis. A fixed-effects model, using Mantel-Haenszel (M-H) method, was used to calculate the pooled ORs when homogeneity existed on the basis of Q-test p value no less than 0.1. By contrast, a random-effects model, using DerSimonian and Laird method (D + L), was utilized if there was heterogeneity based on Q-test p value less than 0.1. The significance of pooled ORs was tested by Z test (P < 0.05 was considered significant).

Sensitivity analysis was performed, in which the metaanalysis estimates were computed after every one study being omitted in each turn.

Finally, publication bias was assessed by performing funnel plots qualitatively, and estimated by Begg's and Egger's tests quantitatively.

Results

Literature search and study selection

After comprehensive searching, a total of 242 articles (236 in English and 6 in Chinese) were retrieved. 230 articles were initially excluded after being read by their respective title and abstract (203 not related gene polymorphism, 6 the same gene but not related locus polymorphisms, 7 related to other gastrointestinal diseases other than gastric cancer, 2 related to precancerous gastric lesions, 1 meta-analysis paper, 1 colorectal carcinoma, 7 related to the effects of bacterial or viral factors (2 Epstein-Barr virus, 5 Helicobacter pylori), 3 unrelated reviews). In our meta-analysis were initially included altogether 12 studies [14][15][16][17][18][19][20][21][22][23][24][25] which catered to the inclusion criteria, and these 12 full-text articles then were considered for further evaluation. 1 article was further excluded due to its lacking normal healthy controls [25]. Those 11 studies seemed appropriate to the meta-analysis of the associations with gastric cancer regarding IL-10-819 T/C SNP. Two studies [20,24] were deviated from HWE through our calculation. Generally speaking, any study that deviated from Hardy-Weinberg equilibrium should have been removed; however, considering that the numbers of participants in those two studies were large and given that sensitivity analyses would be conducted, we remained those two studies in our metaanalysis.

Thus, 11 studies [14][15][16][17][18][19][20][21][22][23][24] with a total of 4008 controls and 1490 cases were ultimately eligible for the meta-analysis of IL-10-819 T/C SNP. The corresponding characteristics were seen in Table 1. The flow chart of literature search and study selection was seen in Figure 1.

Overall meta-analysis among different ethnicity populations OR 1 (p value), OR 2 (p value), and OR 3 (p value) of IL-10-819 T/C SNP for overall ethnicities were 0.87 (p = 0.202), 0.86 (p = 0.083), and 0.88 (p = 0.095), respectively, hardly insinuating a probably suitable genetic model effect of putative protective T allele. Meanwhile, after ethnicity subgroup analysis, OR 1 (p value), OR 2 (p value), and OR 3 (p value) of IL-10-819 T/C SNP among Asians were 0.81 (p = 0.120), 0.95 (p = 0.734), and 0.83 (p = 0.027), respectively, suggesting a recessive genetic model effect of putative protective T allele (OR 1 = OR 3 < 1 and OR 2 = 1). Thus, the genotype TT was compared with the combined genotype CT-plus-CC. As in Figure  2, for overall gastric cancer a statistically significant finding could be noted among Asians (Figure 2A) but not among Caucasians ( Figure 2B) from the facts that the pooled ORs (95% CI, p value) were 0.82 (0.70-0.96, p = 0.015) for the former and 1.07 (0.50-2.26, p = 0.869) for the latter. Only one included study [16] dealt with latino population or mixed ethnicity, so pooled ORs could not be calculated among latino population in our meta-analysis.

Further subgroup analysis

Specific data for IL-10-819 T/C SNP were classified in accordance with the quality appraisal scores, into high quality (scores no less than 6.5) and median-and-low quality (scores less than 6.5) subgroups among different ethnicities. A statistically significant reverse association was only witnessed in Asians high quality subgroup but not in Asians median-and-low quality subgroup, on the grounds that the pooled ORs (95% CIs, p value) were 0.71 (0.58-0.87, p = 0.001) for the former and 1.05 (0.81-1.36, p = 0.719) for the latter. The pooled ORs (95% CIs, p value) among Caucasians median-and-low quality subgroup could not be calculated due to only 1 included study. The pooled ORs (95% CIs, p value) among Caucasians high quality subgroup were 0.71 (0.42-1.23, p = 0.225). If Asians high quality subgroup and Caucasians high quality subgroup were combined, and Asians median-and-low quality subgroup, Caucasians median-and-low quality subgroup, and Latinos median-and-low quality subgroup were also combined, the pooled ORs (95% CIs, p value) were 0.71 (0.59-0.86, p = 0.000) for the former (the combined high quality subgroup) and 1.15 (0.91-1.46, p = 0.240) for the latter (the combined median-and-low quality subgroup), based on the recessive genetic model in our initial option ( Figure  3). To further confirm the recessive genetic model, the above OR 1 (p value), OR 2 (p value), and OR 3 (p value) of IL-10-819 T/C SNP in the combined high quality subgroup for overall ethnicities were 0.64 (p = 0.002), #Data of cardia-subtype gastric cancer were accessible;^Data of noncardia-subtype gastric cancer were accessible; * Data of sporadic diffuse-subtype gastric cancer were accessible; ¶ Data of intestinal-subtype gastric cancer were accessible. +Data of the status of Helicobacter pylori of gastric cancer were accessible. RFLP: Restriction fragment length polymorphisms; TaqMan: 5'nuclease polymerase chain reaction assays; Pyrosequencing: a method of DNA sequencing (determining the order of nucleotides in DNA) based on the "sequencing by synthesis" principle. It differs from Sanger sequencing, in that it relies on the detection of pyrophosphate release on nucleotide incorporation, rather than chain termination with dideoxynucleotides; Direct sequencing: method of methylation analysis using bisulfite-treated DNA utilized PCR and standard dideoxynucleotide DNA sequencing to directly determine the nucleotides resistant to bisulfite conversion; ASP: the allele specific primer-polymerase chain reaction (ASP-PCR) method; SNaPshot: the SNaPshot assay which provides detection of certain SNPs 0.82 (p = 0.065), and 0.75 (p = 0.004), respectively, again indicating a recessive genetic model effect of putative protective T allele (OR 1 = OR 3 < 1 and OR 2 = 1).

When gastric cancer was classified into non-cardia (or distal) and cardia subtypes, no statistically significant findings were found among non-cardia subtype or among cardia subtype on the grounds that the pooled   In terms of H. pylori infection status, no statistically significant reverse association was noted among either H. pylori positive cancer patients compared with H. pylori negative controls or among H. pylori positive cancer patients compared with H. pylori positive controls, for pooled ORs (95% CIs, p value) were 0.64 (0.39-1.04, p = 0.072) in the former and 0.90 (0.63-1.29, p = 0.575) in the latter, but the p value was approximate to 0.05 in the former.

And when genotyping techniques were considered, a statistically significant finding was noted in direct sequencing subgroup but not in any other genotyping technique subgroup. In the direct sequencing, TaqMan, ABI Genetic Analyzer, Pyrosequencing, Snapshot, RFLP, ASP, and ABI real-time PCR genotyping technique subgroups, pooled ORs (95% CIs, p value) were 0.54 (0.

Sensitivity analysis

Meta-analyses were conducted repeatedly when each particular study had been removed. The results indicated that fixed-effects estimates and/or random-effects estimates before and after the deletion of each study were similar at large, suggesting moderate to high stability of the meta-analysis results. The most influencing single study on the overall pooled estimates seemed to be the study conducted by Wu et al. [14], the sensitivity analysis, however, indicated moderate stability of the results from the facts that the ORs (95% CI, p value) for all ethnicity were 0.86 (0.74-0.99, p = 0.037) before the removal of that study and 0.94 (0.80-1.12, p = 0.488) after the removal of that study. In view of the study [20] conducted by Crusius JB et al. which is deviated from HWE, the ORs (95% CI, p value) were 0.86 (0.74-0.99, p = 0.037) before the removal of that study and 0.87 (0.75-1.01, p = 0.063) after the removal of that study for the all ethnicity, indicating moderate to high stability of the results. Similarly, after the removal of the study [24] conducted by Ko KP et al., also deviated from HWE, the OR (95% CI, p value) became 0.86 (0.74-1.00, p = 0.050), indicating high stability of the results (The illustrating figures were omitted due to the length of paper).

Cumulative meta-analysis

Cumulative meta-analyses of IL-10-819 T/C SNP association were also conducted among Asians ( Figure 4A) and among Caucasians ( Figure 4B) via the assortment of total number of sample size. As shown in Figure 4A, the inclination toward significant reverse associations with overall gastric cancer, though somewhat undulated, was obviously seen among Asians, whereas in Figure 4B, the seeming opposite tendency was observed among Caucasians.

Publication bias analysis

Publication bias was preliminarily examined by funnel plots qualitatively and estimated by Begg's and Egger's tests quantitatively. Its funnel plot ( Figure 5) showed that dots nearly symmetrically distributed, predominantly   Cumulative meta-analysis of associations between the IL-10-819 TT genotype, as compared with the combined CT-plus -CC genotype, and gastric cancer risk among different ethnicity populations sorted by publication year and the total sample size. Horizontal line, the accumulation of estimates as each study was added rather than the estimate of a single study. A) among Asians; B) among Caucasians. within pseudo 95% confidence limits. P values were 1.000 in Begg's test and 0.897 in Egger's test, separately, also suggesting no publication bias.

Discussion

In our meta-analysis, a statistically significant finding could be noted with the overall reduced risk of gastric cancer among Asians but not among Caucasians (TT vs CT-plus-CC); the opposite tendency toward the risk of gastric cancer could also be observed between Caucasians and Asians via cumulative meta-analysis sorted by publication time and total sample size. Thus, IL-10-819 TT genotype may seem to be more protective from overall gastric cancer susceptibility among Asians. To be sure, the different or even conflicting risk associations, if so, among different ethnicities should be further meticulously investigated and confirmed in the future.

Our further subgroup analyses also indicate that a statistically significant reverse association was witnessed in Asians high quality subgroup but not in Asians medianand-low quality subgroup; the reverse association tendency was also observed in Caucasians high quality subgroup, although the statistical significance could not be reached. The consistent reverse association trend between Asians high quality subgroup and Caucasians high quality subgroup could be apparently seen. The strong statistical significant reverse association could be found among the combined high quality subgroup regardless of ethnicities based on the recessive genetic model in our meta-analysis. Furthermore, the recessive genetic model was confirmed through the recalculation of OR 1 (p value), OR 2 (p value), and OR 3 (p value) in the combined high quality subgroup regardless of ethnicities. Therefore, it should be advocated that more rigorous high-quality studies should be designed in the future so as to accurately explore the real associations between IL-10-819 TT genotype and gastric cancer susceptibility among different ethnicities.

Additionally, 4 [17][18][19][20] out of 11 eligible studies were dealt with noncardia-subtype gastric cancer and 4 [15,[18][19][20] with cardia-subtype gastric cancer. No statistically significant findings could be noted with either subtype (TT vs CT-plus-CC). 2 studies [18,19] in our meta-analysis were dealt with pathologically intestinalsubtype gastric cancer and only 1 [19] out of 11 studies was dealt with pathologically diffuse-subtype gastric cancer. No statistically significant finding could be noted in intestinal-subtype but in diffuse-subtype cancer (TT vs CT-plus-CC). As is known, cardia-subtype gastric cancer differs from noncardia-subtype gastric cancer in etiology, pathology, carcinogenesis, and/or prognosis [30][31][32], so is intestinal-subtype cancer versus diffuse-subtype cancer. It could be said that the indiscriminate combination of cardia-subtype and noncardia-subtype cases or intestinal-subtype and diffuse-subtype cases in the majority of eligible studies may mask or at least underestimate the strength of the real associations [7][8][9].

Furthermore, it was reported that gastric cancer develops in those with H. pylori infection rather than in uninfected ones [33]. In our meta-analysis, no statistically significant reverse association with gastric cancer was found either among H. pylori positive cancer patients compared with H. pylori negative controls or among H. pylori positive cancer patients compared with H. pylori positive controls (TT vs CT-plus-CC), but the p value in the former was approximate to 0.05, insinuating that IL-10-819 TT genotype may seem to be more protective from overall gastric cancer susceptibility in persons infected with H. pylori. Certainly, the real association between H pylori infection and IL-10-819 TT genotype and gastric cancer susceptibility should be further meticulously investigated in the future.

With the coming of new genotyping technologies like seminested polymerase chain reaction, TaqMan allelic discrimination test, direct sequencing, the allele specific primer-polymerase chain reaction, pyrosequencing, or real-time PCR, we may witness an upsurge of genetic association studies in the future. In our meta-analysis, a statistically significant reverse association with gastric cancer susceptibility was only noted in direct sequencing technique subgroup but not in any other genotyping subgroup. The fact that the most significant result can be witnessed in direct sequencing technology in our meta-analysis is not necessarily a valid reason to demonstrate that other technologies cannot be used. Certainly, for a novel genotyping technique to be employed for the study of a particular genetic polymorphism, this technology should better be confirmed using direct sequencing. In that case, this new technology can be seen as valid as direct sequencing. Or the sensitivity and specificity of those genotyping techniques need to be explored so as to seek out optimal approaches which could minimize the genotyping errors [7][8][9]. Our opinion is that direct sequencing should be more used in future well-designed studies among different ethnicity populations.

And the mechanism of the influence of IL-10-819 SNP on carcinogenesis is still unknown, but it has been reported that IL-10 SNPs may influence immune function through modulating the activities of the NK cell, T cells, and macrophages and thus alter the disease progression [34]. Additionally, another investigated SNP at position -1082 (A/G) was reported to be significantly increased in prostate cancer patients and its action, together with VEGF and IL-8, was suspected to possibly influence cancer angiogenesis [35]. Whether IL-10-819 SNP may also influence cancer angiogenesis is worthy of further investigating in the future.

Finally, the strength of our meta-analysis could be summarized as follows. We sought to find as many publications as we could by means of various searching approaches. Any study that appeared to deviate from HWE was not excluded mechanically in our meta-analysis unless there are other convincing grounds for doubting the quality of the study [36]. We laid more emphasis on assessing biases across studies and pinpointing the potential sources of heterogeneity via subgroup and sensitivity analyses. More importantly, we have made great efforts to stratify ethnicity into Asians subgroup and Caucasian subgroup in accordance with accessible data. In particular, we have conducted overall meta-analysis among different ethnicity populations to carefully choose the most likely appropriate genetic model. We also have stratified the included studies through other subgroup analyses like anatomic classification, pathologically Lauren's classification, H. pylori infection status, sample size, and quality appraisal scores. We comprehensively assessed the publication biases using several means like Begg's and Egger's tests as well as funnel plot tests. In view of this, we convince that the results of our meta-analysis, in essence, are sound and reliable.

Certainly, there are some unavoidable limitations in our meta-analysis. Firstly, the information about overall gastric cancer susceptibility is predominantly provided, while other information about pathologic subtypes or anatomic subtypes of gastric cancer is less provided. Thus, the specific subtype results should be considered with caution. Secondly, with the merely published studies included in our meta-analysis, publication bias is very likely to occur, though no statistically significant publication bias is found in our meta-analysis. Thirdly, slight to moderate heterogeneity could be witnessed among the included studies. So as to minimize the potential bias, we designed a rigorous protocol before conducting our meta-analysis, and performed a scrupulous search for published studies using explicit methods for study selection, data extraction, statistical analysis, adoption of the most appropriate genetic model with extreme caution and sensitivity analysis.

Conclusions

In conclusion, IL-10-819 TT genotype may seem to be more protective from overall gastric cancer susceptibility among Asians and even more protective in high quality subgroup Asians. IL-10-819 TT genotype is not statistically associated with gastric cancer susceptibility in persons infected with H. pylori. IL-10-819 TT genotype is not associated with pathologic intestinal subtype but in diffuse subtype and not with anatomic subtypes (noncardia or cardia) of gastric cancer susceptibility in our meta-analysis. Direct sequencing should be more used in future well-designed high quality studies among different ethnicities or populations.

Additional material

Figure 1
1The flow chart of literature search and study selection.

Figure 2
2Odds ratios (ORs) for associations between IL-10-819 T/C SNP and gastric cancer risk (TT vs CT-plus-CC) among different ethnicity populations, in order of increasing publication year, 2003-2011. Studies were entered into the metaanalysis sequentially by year of publication. The sizes of the squares indicate the relative weight of each study. Bars, 95% confidence interval (CI). A) among Asians; B) among Caucasians.

Figure 3
3Odds ratios (ORs) for associations between IL-10-819 T/C SNP and gastric cancer risk (TT vs CT-plus-CC) among high quality subgroup participants regardless of ethnicities and among median-and-low quality subgroup participants regardless of ethnicities. The sizes of the squares indicate the relative weight of each study. Bars, 95% confidence interval (CI).

Figure 4
4Figure 4 Cumulative meta-analysis of associations between the IL-10-819 TT genotype, as compared with the combined CT-plus -CC genotype, and gastric cancer risk among different ethnicity populations sorted by publication year and the total sample size. Horizontal line, the accumulation of estimates as each study was added rather than the estimate of a single study. A) among Asians; B) among Caucasians.

Figure 5
5Funnel plot of publication bias for IL-10-819 SNP (TT vs CT-plus-CC). Note: Funnel plot with pseudo 95% confidence limits was used.

Table 1
1Study Characteristics of genotypes in gastric cancer cases and controls in the analysis of Interleukin-10-819 Promoter Genetic PolymorphismsFirst author Year of
publication

Quality assessment
scores

Genotyping
method

Total sample
size

Number of
controls

Number of
cases

Study
location

Ethnic
group

P values for
HWE

Controls,
genotypes(n)

All Cases,
genotypes(n)

CC CT TT CC CT TT

Wu MS
2003
7
Direct
sequencing

450
230
220
China
Asians
0.231397685 20 83 127 27 105 88

Savage SA # 2004
5
ABI Genetic
Analyzer

466
382
84
China
Asians
0.314869012 49 163 170 9 38 37

Alpízar-
Alpízar W

2005
6
Pyrosequencing
90
45
45
Costa Rica Latinos
0.08326454
18 24 3 25 16 4

Zambon CF^2005
5
TaqMan
773
644
129
Italy
Caucasians 0.696436614 353 245 46 70 42 17

Kamangar
F #^ ¶

2006
8
TaqMan
250
152
98
Finland
Caucasians 0.66272429
80 62 10 58 35 5

Sugimoto
M #^* ¶+

2007
6.5
ASP
273
168
105
Japan
Asians
0.194224595
9 73 86 6 57 42

Crusius JB #^2 008
8.5
ABI real-time
PCR

1323
1094
229
European
Caucasians 0.02386503 636 378 80 145 72 12

Xiao H
2009
6
RFLP
844
624
220
China
Asians
0.718880427 69 283 272 20 100 100

Ko KP
2009
7
SNaPshot
409
326
83
Korea
Asians
0.038333741 37 121 168 11 33 39
Su SP
2010
6.5
RFLP
143
100
43
China
Asians
0.433216715
6 43 51 4 21 18

Liu J +
2011
6.5
RFLP
477
243
234
China
Asians
0.772829993 28 106 109 39 96 99

AcknowledgementsThe National Natural Science Foundation of China (grants 30830038, 30970842, and 81071180); "973" Project (2012CB932604); the Key Project of Science and Technology Commission of Shanghai Municipality (grants 10JC1410000); and the Shanghai Leading Academic Discipline Project (grant S30203). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Authors' contributions Data were acquired by LB and AJ; Data were analyzed by XH, LB, AJ, ZY, and HG; This Manuscript was written by XH and revised by HG; and Statistical analysis was made by XH, AJ, LB and ZY. HG and XH designed, coordinated and supervised this whole work. All authors read and approved the final manuscript.Competing interestsThe authors declare that they have no competing interests.
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Internet-based Patient Self-care: The Next Generation of Health Care Delivery

PhD, RNJune Forkner-Dunn
Internet Services Group
Kaiser Foundation Health Plan, Inc
Oakland CaliforniaUSA

PhD, RNJune Forkner-Dunn
Internet Services Group Kaiser Foundation Health Plan, Inc
1800 Harrison Street, 18th Floor Oakland94612-3429CAUSA

Internet-based Patient Self-care: The Next Generation of Health Care Delivery
10.2196/jmir.5.2.e8Viewpoint Corresponding Author:Consumer participationInternetmedical informaticspatient educationphysician-patient relationsself caretechnologydisease managementcomputers
The United States health care system is an outdated model in need of fundamental change. As part of this change, the system must explore and take advantage of the potential benefits of the "e-revolution," a phenomenon that includes everyday use of the Internet by the general public. During 2002, an estimated 100 million Americans will have obtained information -including health information -from the Web as a basis for making decisions. The Internet is thus an influential force; and, as such, this medium could have a revolutionary role in retooling the trillion-dollar United States health care industry to improve patient self-management, patient satisfaction, and health outcomes. As a group, physicians use the Internet more than do many other sectors of the general adult population. However, physicians have not received sufficient information to convince them that they can provide higher-quality care by using the Internet; indeed, few studies have assessed the Internet's value for improving patients' medical self-management and health behavior, as well as their clinical outcomes and relationships with health care practitioners. New e-technology formats introduced to the growing consumer movement will drive the next generation of self-care by allowing patients to manage their own health conveniently and proficiently.(J Med Internet Res 2003;5(2):e8)

Introduction

The landmark Institute of Medicine report, "Crossing the quality chasm: a new health care system for the 21st century" [1], depicts an outdated model of health care that hosts worsening chronic medical conditions, skyrocketing health care expenditures, and failure to effectively transform technical innovation into improved health outcomes. The Internet may have a revolutionary role in retooling the trillion-dollar health care industry in the United States.

Indeed, by introducing new e-technology formats to the growing consumer movement, the online revolution may become the engine driving the next generation of self-care, thereby allowing patients to manage their own health conveniently and proficiently. Although the Internet's power to positively affect care management seems an intuitive concept, the Internet's value for improving health outcomes must be examined and documented to provide a basis for further advancement.

The Online Revolution

Public use of the Internet as a health care tool has grown dramatically in the past few years, and this trend is expected to continue. During 2002, more than 100 million Americans will have searched online for information, including health information -an increase of 13 million from the previous year [2]. Obtaining information from the Web is often the basis for making health decisions and is thus an influential force. Of persons surveyed in 2000 by the Pew Internet & American Life Project, 41% said that the Internet affected their decisions about going to a doctor, treating an illness, or questioning their doctor [3]. This online phenomenon is occurring while a huge population segment, the postwar "baby boomers," is moving like a tsunami through the American health care system. Thanks to modern medicine, these adults will live longer than earlier generations ever could -and will flood the health care system with chronic ailments. Moreover, in addition to making health care decisions for themselves, this population is making such decisions for their elderly parents, many of whom have multiple chronic diseases. Baby boomers are demanding the same easy access to advanced health care technology as is currently available to them when they do their banking or plan a vacation. We have arrived at the era of the "impatient patient." Patients demand immediate, convenient access to a high level of personalized health care: they want it their way, and they want it now.

Effect of e-Technology on the Patient-Physician Relationship

Can the Internet empower patients? Can it enrich the patient-physician relationship? Breast cancer patients in an online education and support group had increased confidence in their physicians, as well as increased competence to deal with relevant, disease-related information. These patients were also more comfortable seeking information during a physician office visit and were more comfortable participating in their own care [4]. This study alone is minimal evidence to support changes in the patient-physician relationship and more research is needed.

A Harris Online poll found that patients who use the Internet to look for health information are more likely to ask more specific and informed questions of their doctors and to comply with prescribed treatment plans [5]. This was a survey and not a formal study. Further research is necessary to understand what effect the Internet age has on the patient-physician relationship. For example, are patients more compliant with prescribed therapy because they discussed it more with their physician or because they read it on the Web?

The "school of lay medicine" found on the Internet offers an important opportunity for patients to become actively engaged in their own care. During the pre-Internet era, medical information was published in medical textbooks and journals only, whereas patients can now gain access to citations of more than 12 million medical articles online [6]. Indeed, many patients are now helping to inform their physicians on the latest research and treatments.

Physicians Gerber and Eiser [7] postulate that the Internet age offers opportunities to improve the patient-physician relationship by sharing the burden of responsibility for knowledge. They also underline the necessity for research to identify the effects on the patient-physician relationship, as well as the effects on patient and physician satisfaction and on health outcomes.

The locus of power in health care also is shifting: instead of the doctor acting as sole manager of patient care (ie, "the captain of the ship"), a consumerist model has emerged in which patients and their doctors are partners in managing the patient's care [8].

On the other hand, there are many patients who do not wish to be the captain of the ship. Research needs to address how the Internet would affect these individuals.

Patient Self-management Using e-Monitoring

Several monitoring devices using the Internet have been developed to help patients manage their medical conditions at home. For example, diabetic patients can test their blood glucose level by using an e-device, which with the click of a computer mouse downloads the result to a health care practitioner. Patients with heart failure can step on an e-scale, which sends instantaneous alerts to health care professionals when the patient's weight exceeds the desired range. An e-shirt can be worn which transmits heart rate and respiratory rate over the Internet. A pill-sized camera can be swallowed which transmits pictures of the digestive tract over the Internet. Research is needed regarding health outcomes, cost effectiveness, as well as the long-term acceptance of these devices by patients.

The federal government has invested $28 million to evaluate home glucose monitoring via the Internet to homes of underserved rural and inner-city residents in New York State. The largest eHealth grant ever funded by the government, this study will serve as an important test case for the possibility of e-technology to improve health outcomes [9].

E-connecting to Others Who Have the Same Medical Condition

Online support groups exist for almost every disease and condition, and discussion topics within each disease category are limitless. For example, diabetic patients who enjoy scuba diving can learn from fellow diabetic scuba divers how to cope with diabetes 50 feet (15.2 meters) below the water's surface. But just as important as the information exchanged in these e-discussions is the emotional support they provide. For each e-patient seeking a listening "ear," dozens of other patients offer encouragement. In turn, these words of solace are read by hundreds (and sometimes thousands) of other patients who read Internet message boards. This support may be recorded for future reference of patients, clinicians, or health care planners.

Effect of e-Technology on Health Care Outcomes

Although online intervention may empower patients and may positively affect the patient-physician relationship, a realistic observation is that the Internet will be widely adopted as a part of usual care only if this venue improves patient self-management, betters patient satisfaction, and enhances health outcomes. To determine the success of Internet-based health care, rigorous outcome studies are needed.

A study by McKay et al [10] found that patients who participated in an online diabetes education and support group lowered their blood glucose levels more than controls did. Studies of online support groups for cystic fibrosis patients [11], amyotrophic lateral sclerosis (ALS) patients [12], and single mothers [13] also showed that participants in these online support groups gained satisfaction and confidence in managing their medical condition.

There are limitations to the few studies that have been done. For example, the above study by McKay et al used a small sample, only had short-term follow-up, and there were no solid clinical-outcomes measures. Further research is needed utilizing larger samples over longer periods, controlled and randomized, in tandem with significant outcomes to support policy changes and buy-in efforts for implementation.

The Achilles' Heel of the Online Revolution

Until recently, the powerful phenomenon of online health care has been largely overlooked by the health care system. Most institutions funding medical research, health policymakers, and health care professionals have ignored both the "e-revolution" and the fact that it is consumer driven. Although the Internet has intuitive potential for improving patient-physician relationships and communication, patient self-management, and health outcomes, outcome research exists for only a few studies and cannot be applied widely because of the studies' limitations.

As a group, physicians themselves have constituted a major source of resistance to online health care. An article, "Why doctors hate the Net" [14], identified 3 specific concerns of physicians:

• E-mail from patients further burdens overflowing physician schedules • During an already-crowded office visit schedule, e-savvy patients armed with printouts from the Internet waste precious time discussing information from unknown or otherwise-dubious sources • Much health-related information posted on the Internet is unreliable.

More than a century ago, a similar backlash in health care accompanied introduction of another technology: the telephone. Soon after invention of the telephone by Alexander Graham Bell, much cultural opposition to it was generated by physicians who doubted that the telephone could add value to medical practice. These physicians complained that answering calls would diminish the time available for in-person interaction with patients. Other physicians questioned whether patients would be willing to use the new technology. Some physicians worried that the telephone might destroy the patient-physician relationship [15].

As they did with the telephone, however, physicians are becoming less resistant to using the Internet for delivering patient care. Recent estimates of Internet-equipped physicians vary, but these reports agree that physician adoption of the Internet is increasing noticeably [16], and most agree that physicians (a group sometimes thought technophobic) use the Internet more than do many other sectors of the general adult population [17]. However, physicians have not received information sufficient to convince them that the Internet can help them provide higher-quality care: although 55% of physicians surveyed use e-mail to communicate with professional colleagues, only 13% stated a willingness to send e-mail to patients [18]. In contrast to this finding, 90% of patients surveyed wished to communicate with their physicians by e-mail [19].

In their article "We got mail," Moyer et al [20] highlight issues such as inequity of e-mail access, workload, medical-legal concerns, as well as privacy and confidentiality. Research is necessary to address these issues. Does e-mail from patients really burden a physician's schedule? If so, will triaging by others help? What effect does e-communication have on the patient-physician relationship? Can e-mail reminders from a "virtual case manager" improve health outcomes? Can providers be held liable if an unauthorized third party accesses confidential medical information sent by e-mail? Is e-mail cost-effective?

Access Gaps

Another obstacle to widely implementing online forms of health intervention is the assumption that lack of necessary technology by many senior, minority, and lower-income patients will exclude them from this intervention. While access to the Internet is less common in these groups, studies show that the "digital divide" is narrowing. indicating that more than half of that population is now online [22]. Like African Americans, however, Hispanics have less access to cyberspace than their Caucasian counterparts. In contrast, Asian Americans use the Internet more than other group: more than 75% of that population has access to the Internet [23].

Economics play a part in access. Studies show that lower-income people are less likely to be wired: 37% of those who are not wired have family incomes under $30000, whereas only 18% of those with Internet access have incomes under $30000 [24]. Poor reading skills add even more barriers to those economically disadvantaged for accessing the world of the Web.

The senior population has been slower than other age groups in embracing the Internet but this is changing. A Pew report [25] predicts that with many baby boomers approaching retirement age, seniors' use of the Internet will increase dramatically. The health care industry must be prepared to accommodate this growing segment of the population, many of whom will become homebound but will still need services, training, and reinforcement of medical self-management, as well as continued connection to clinicians and contact with other patients.

While eHealth technologies have the potential to reduce disparities in health care by promoting health and preventing disease, traditionally underserved groups who could benefit the most from eHealth initiatives, are the least likely to have access to such technologies. Although seniors and many minority groups are the fastest-growing segments of new Internet users [22,23,25], we need to better understand access barriers. Furthermore, Eng et al [26] raise important points regarding access issues for those who cannot read at all, those who cannot read English, and those with disabilities.

Time to " `Byte' the Bullet"

The eHealth care train has not only left the station but is rapidly moving down the track carrying tens of millions of e-patients and many possibilities for transforming patient self-management, improving health outcomes, and enhancing the patient-clinician relationship. Because of substantial opposition to the online revolution, however, the "e-train" has so far evaded the transcontinental health care network.

Fundamental change is needed in our outmoded, Internet-averse system of health care, which still prevails in the United States. The United States health care system must embrace the e-revolution by exploring and taking advantage of the potential benefits of this revolution for improving quality of care. To pursue this goal, rigorous research must explore ways to use e-technology for improving patients' medical self-management, health-related behavior, health outcomes, and relationships with health care practitioners.

From
August 2000 through July 2001, the number of African Americans using the Internet grew nearly 20% [21]. The proportion of wired African Americans (43%), nonetheless, remains low in comparison with the average of online Americans (58%) [21]. Internet access among Hispanics in the United States increased by 25% from March 2000 through February 2001,
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AcknowledgmentsAlan Eshleman, MD, and Beth Eshelman, LCSW, reviewed the manuscript.The Kaiser Permanente Medical Editing Department provided editorial assistance.Conflicts of InterestNone declared.
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Please cite as: Forkner-Dunn J Internet-based Patient Self-care: The Next Generation of Health Care Delivery. 10.2196/jmir.5.2.e812857664J Med Internet Res. 528Please cite as: Forkner-Dunn J Internet-based Patient Self-care: The Next Generation of Health Care Delivery J Med Internet Res 2003;5(2):e8 URL: http://www.jmir.org/2003/2/e8/ doi: 10.2196/jmir.5.2.e8 PMID: 12857664