IGF-I and IGFBP-3 and the risk of lung cancer: A meta-analysis based on nested case-control studies
© Chen et al; licensee BioMed Central Ltd. 2009
Received: 14 May 2009
Accepted: 24 June 2009
Published: 24 June 2009
Lung cancer is the leading cause of death from cancer worldwide. Conventional studies mainly think that insulin-like growth factor-I (IGF-I) and IGF-binding protein-3 (IGFBP-3) may promote and inhibit tumor growth, respectively. However, there are many different results about their function in some recent epidemiological studies. To evaluate the relationship between circulating serum levels of IGF-I, IGFBP-3 and lung cancer, a systematic review and meta-analysis of the published data was performed.
Literatures searched on PubMed and Embase databases were enrolled in the Meta-analysis. The Meta-analysis of all eligible studies was applied with Stata 10.0 software, and the pooled odds ratio(OR) and weighted mean difference (WMD) value were obtained. The Q test, Egger's test and Begg's funnel plot were used to evaluate the heterogeneity and publication bias between the studies.
There are no statistically significant heterogeneity and publication bias between the studies. For IGF- I, the pooled OR and WMD were 0.87(95%CI: 0.60~1.13,) and -3.04(95%CI: -7.10~1.02, P = 0.14), respectively. For IGFBP-3, the pooled OR and WMD were 0.68(95%CI: 0.48~0.88,) and -112.28(95%CI: -165.88~-58.68, P < 0.0001), respectively.
The association between circulating IGF- I levels and the risk of lung cancer were not statistically significant; IGFBP-3, acts as a tumor suppressor and has a inverse correlation with the risk of lung cancer.
Lung cancer is the leading cause of death from cancer worldwide, and the care rate remains less than 15% despite improvements in surgery, radiotherapy and chemotherapy . Insulin-like growth factor-I (IGF-I) and IGF-binding protein-3 (IGFBP-3) have been widely accepted that they may have key role on the genesis and development of many types of tumor including lung cancer [2–7].
Growth hormone stimulates production of IGF-I in the liver and peripheral tissues. IGF-I is also released locally in response to damage, either directly or through the action of other factors associated with tissue responses to damage, including epidermal growth factor, fibroblast growth factor, and platelet-derived growth factor . IGFBP-3 is the dominant circulating binding partner for both IGFs, accounting for 70 to 80% of their blood levels [8, 9]. Multiple lines of evidence suggest involvement of the IGF pathway across a range of malignancies, including both non-small cell lung cancer (NSCLC) and small cell lung cancer [5, 10, 11]. Elevated plasma levels of IGF-I have been associated with an increased risk of lung cancer, and high plasma levels of IGFBP-3 associated with a reduced risk . Similarly, IGFBP-3 promoter methylation in tumor cells has been linked to decreased survival in stage I NSCLC patients. These suggest that IGF-I may promote tumor cell growth, while IGFBP-3 acts as a tumor suppressor gene [12, 13]. At the same time, different results were obtained from other studies. Recently, many large-scale clinical prospective case-control studies on association between circulating levels of IGF-I, IGFBP-3 and the risk of lung cancer were performed [14–19]. However, the results of these studies still remain inconclusive, partially because of the possible relatively small sample size in each of the published studies.
Here we performed a systematic meta-analysis of all studies published to date to determine and assess the strength of the association between circulating levels of IGF- I and IGFBP-3 and lung cancer. It may be helpful in the diagnosis and treatment of lung cancer.
Search strategy and study selection
PubMed and Embase were searched using the search terms: "insulin-like growth factor-I", "lung neoplasm", "case-control study", "cohort study" and "prospective study" (last search was updated on 1 March 2009). All eligible studies were retrieved, and their bibliographies were checked for other relevant publications. Review articles and bibliographies of other relevant studies identified were hand-searched to find additional eligible studies. These searches were restricted to studies in which IGF-I and IGFBP-3 concentration were measured. Two investigators independently reviewed all potentially relevant articles. Disagreement or uncertainty between 2 investigators was resolved by discussion. Inclusion was restricted to nested case-control studies and prospective cohort studies published in English.
Data were independently abstracted in duplicate by 2 investigators using a standard protocol and data-collection form. Characteristics abstracted from the studies included name of the first author, location of the study, year of publication, case definition, control definition, selection criteria, method of IGF-I and IGFBP-3 measurement, confounding factors that were controlled for by matching or adjustment and mean and standard deviation (SD) of IGF-I and IGFBP-3 in each group, odds ratio (OR) comparing the highest category to the lowest and its 95% confidence interval(CI). For data not provided in tabular form or the main text, the required information were obtained by contacting corresponding authors as possible as we can.
Most of studies provided crude and adjusted OR. We used the adjusted OR comparing the highest category with the lowest as the principal effect measure in our meta-analysis. The cutoff values for these categories were based on control groups, which better represented the distribution of IGF-I and IGFBP-3 in the general population. The adjusted ORs and their 95% confidence intervals were abstracted directly from the publications. We also used the weighted mean difference (WMD) to compare circulating levels of IGF-1 and IGFBP-3 of lung cancer cases with that of their controls.
Heterogeneity assumption was checked by the chi-square-based Q test . A P value > 0.10 for the Q test indicates a lack of heterogeneity among studies, so the pooled OR estimate of the each study was calculated by the fixed-effects model (the Mantel-Haenszel method) . Otherwise, the random- effects model (the DerSimonian and Laird method) was used . An estimate of potential publication bias was carried out by the funnel plot, in which the standard error of log (OR) of each study was plotted against its log (OR). An asymmetric plot suggests a possible publication bias. Funnel plot asymmetry was assessed by the method of Egger's linear regression test, a linear regression approach to measure funnel plot asymmetry on the natural logarithm scale of the OR. The significance of the intercept was determined by the t test suggested by Egger (P < 0.05 was considered representative of statistically significant publication bias) . Stata statistical package version 10.0(Stata Corporation, College Station, TX) was used for the meta-analysis, using two-sided P-values.
Characteristics of studies included in the meta-analysis
Characteristics of case-control studies for lung cancer and IGF-I and IGFBP-3
OR(95%CI) for IGF-I
OR(95%CI) for IGFBP-3
Adjusted factors in the model in original report
Lukanova et al.
Age, date of recruitment in the study, menopausal status, current smoking, time since last meal, cotinine and BMI
London et al.
Spitz et al.
Age, sex, race, year of enrollment, and year of blood draw, BMI, smoking status, pack-years of smoking, exposure population
Waikai et al.
Age, area, gender, smoking habits, and BMI
Ahn et al.
Age, intervention arm, BMI, and years of smoking
Morris et al. 
After performing the tests for heterogeneity for IGF-I and IGFBP-3 separately, we decided to use a fixed-effect model to obtain a summary statistic as the tests were not statistically significant (Q-value of 5.86 with df = 5, P = 0.320 for IGF-I and Q-value of 6.66 with df = 5, P = 0.247 for IGFBP-3).
Studies reporting IGF-I and IGFBP-3 levels in lung cancer patients and their controls
Individual and combined WMD, ORs and 95% CIs by IGF-I and IGFBP-3
The individual and combined WMD of IGF-I and IGFBP-3 are shown in Table 3. We compared circulating levels of IGF-I and IGFBP-3 of lung cancer cases with that of controls, the results are the overall WMD = -3.04(95%CI: -7.10~1.02, P = 0.14) for IGF-I, and WMD = -112.28(95%CI: -165.88~-58.68, P < 0.0001) for IGFBP-3. The publication bias were also not statisitically significant and the funnel plot were not shown.
A single study involved in the meta-analysis was deleted each time to reflect the influence of the individual data-set to the pooled ORs, and the corresponding pooled ORs were not materially altered (data not shown).
Lung cancer is the leading cause of malignancy-related mortality. The mechanism of carcinogenesis is very complex, which involves many factors, such as IGF-I and IGFBP-3. Conventional studies coordinately think that IGF-I and IGFBP-3 may promote and inhibit tumor growth, respectively. In recent years, there are many epidemiological studies have different results. In this meta-analysis, our data suggests that IGF-I low in the lung cancer population, though we could not demonstrate statistical significance. With regard to the association between IGFBP-3 and lung caner, the data suggests IGFBP-3 acts as a tumor suppressor and has a inverse correlation with the risk of lung cancer, and it does have statistical significance.
The IGF family is supposed to play a pivotal role in regulating cell proliferation, apoptosis and transformation . Most circulating IGFs are produced by hepatocytes in response to growth hormone stimulation [25–27]. Circulating IGFBP-3 is produced by hepatic endothelium and Kupffer cells [26, 27]. A number of in vitro and in vivo studies have demonstrated that IGF-I is an effective mitogen in normal epithelial cells and has strong antiapoptotic effects on lung cancer cells [5, 10, 11]. However, the effect of IGF-I may be modulated by IGFBP-3 in circulation because most of the IGF-I is bound to IGFBP-3 and once bound it is not in its active form. The results of this meta-analiysis indicate that there are no statistically significant association between IGF-I and lung cancer, while the associaton between IGFBP-3 and lung cancer is very significant. High serum levels of IGFBP-3 associated with a reduced lung cancer risk.
Lung cancer is a multifactorial disease that results from complex interactions between many genetic and environmental factors. This means that there will not be single gene or single environmental factor that has large effects on lung cancer susceptibility. Due to limited studies and published data in original report, we could not make subgroup analysis by sex, smoking status, histological types and other variables. Possible limitations of our meta-analysis includes relatively small number of studies, different heterogeneous matching factors, different countries and ethnicities, possible publication bias, as well as possible interaction with other biologic and environmental factors. It is well documented that ethnic factor contributes to the lung cancer incidence. In our study, we included 2 U.S., 1 Chinese, 1 Japanese, 1 Finnish and 1 British studies. Therefore, heterogeneity by ethnicity needs to be taken into account when interpreting our data. Heterogeneous matching factors and differential adjustment for confounding factors are other sources of bias. The above limitations might have contributed to the low statistical power of our meta-analysis.
Despite some limitations, our results based on nested case-control studies which represent of best study design. In addition, we obtained the results from dichotomous and continuous variable respectively, which made the results more reliable. What's more, heterogeneity and publication bias of the studies were not significant. Thus, the data of our study are reliability.
In summary, we found that association between circulating levels of IGF-I, IGFBP-3 and the risk of lung cancer are marginally and statistically significant, respectively. So it may be helpful in the diagnosis and treatment of lung cancer. Since circulating IGF-I and IGFBP-3 remain important factors in lung cancer, more studies need to be conducted to discern this association. And uniform adjustment of confounding factors across the studies will help in terms of interpretability and comparability.
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