|Year : 2016 | Volume
| Issue : 5 | Page : 79-81
A meta-analysis of contrast-enhanced computer tomography in the diagnosis of colorectal cancer
Shuqian Man, Jianxun Zou, Mingjie Wang, Feng Liang, Shuyan Chen, Xueyong Zhang, Xudan Li
Department of Radiology, Lishui People's Hospital, The 6th Affiliated Hospital of Wenzhou Medical University, Zhejiang, Lishui 323000, PR China
|Date of Web Publication||7-Oct-2016|
Department of Radiology, Lishui People's Hospital, The 6th Affiliated Hospital of Wenzhou Medical University, Zhejiang, Lishui 323000
Source of Support: None, Conflict of Interest: None
Objective: To investigate the diagnostic value of contrast-enhanced computer tomography in diagnosis of colorectal cancer.
Methods: All the diagnostic studies about contrast-enhanced computer tomography in diagnosis of colorectal cancer were searched in the PubMed, Medline, EMBASE, CNKI, and Wanfang databases and included in this meta-analysis. The diagnostic sensitivity and specificity were pooled. The data were analyzed by statistic software Meta-DiSc1.4.
Results: After searching the databases, eight studies with 4764 cases were finally included in this meta-analysis. The combined results showed the pooled diagnostic sensitivity and specificity were 0.73 (95% confidence interval [CI] of 0.69–0.76) and 0.86 (95% CI of 0.85–0.87). Moreover, the area under the receiver operating characteristic was 0.896.
Conclusion: Contrast-enhanced computer tomography was a good method for detection colorectal cancer.
Keywords: Colorectal tumors, computer tomography, diagnosis, meta-analysis
|How to cite this article:|
Man S, Zou J, Wang M, Liang F, Chen S, Zhang X, Li X. A meta-analysis of contrast-enhanced computer tomography in the diagnosis of colorectal cancer. J Can Res Ther 2016;12:79-81
|How to cite this URL:|
Man S, Zou J, Wang M, Liang F, Chen S, Zhang X, Li X. A meta-analysis of contrast-enhanced computer tomography in the diagnosis of colorectal cancer. J Can Res Ther [serial online] 2016 [cited 2018 May 22];12:79-81. Available from: http://www.cancerjournal.net/text.asp?2016/12/5/79/191639
| > Introduction|| |
Colorectal carcinoma is one of the most diagnosed digestive tumors. It was reported that about 103,170 new cases of colon cancer and 40,290 new cases of rectal cancer were diagnosed in the US in the year of 2012. Moreover, it was estimated that about 51,690 cases were dead of colorectal cancer in the same year. Hence, colorectal cancer was one of the main causes of cancer-related death.
The main method for colorectal cancer diagnosis was colonoscopy with high specificity. However, for its mini-invasive and not convenient, it was not suitable for colorectal screening and low colorectal risk people. Contrast-enhanced computer tomography has been reported for colorectal diagnosis in the past few years with inconclusive conclusion.
| > Methods|| |
The electronic searching was performed by two reviewers Zou Jianxun and Wang Mingjie independently and cross-checked. All the diagnostic studies about contrast-enhanced computer tomography in diagnosis of colorectal cancer were searched in the PubMed, Medline, EMBASE, CNKI, and Wanfang databases. The searching words were as follows: computed tomography, colorectal tumors, diagnosis, sensitivity, and specificity. The references of these publications were also manually searched to retrieve additional studies.
Man Shuqian and Zou Jianxun independently extracted the general information and diagnostic data of the included publications. The extracted data included study design, publication year, journal of the paper published, diagnostic gold standard, true positive, false positive, false negative, and true negative, and the extracted data were checked by the third reviewer Li Xudan.
The statistical analysis was done by Meta-DiSc1.4 (http://www.biomedsearch.com/nih/Meta-DiSc-software-meta-analysis/16836745.html). Chi-square test was used to evaluate the statistical heterogeneity across the included studies. Fixed or random effect model was used to pooled the sensitivity and specificity according to the heterogeneity evaluation results.
| > Resluts|| |
Publications included in this meta-analysis
Eight diagnostic studies with 4764 cases were finally included in this meta-analysis. For the included 8 publications, four of them use intravenous contrast agent and other 4 use oral contrast agent. All of the included studies were published in English and indexed in the PubMed. The detailed characters of the included publications were shown in [Table 1].
Statistical heterogeneity for included studies
We use the Chi-square test and I2 to evaluate the statistical heterogeneity across the studies for the effect size of diagnostic sensitivity and specificity. We found that the I2were 92.8% and 84.6% for diagnostic sensitivity and specificity, respectively, which indicated significant statistical heterogeneity across the included studies. Thus, the pooled diagnostic sensitivity and specificity were calculated by random effect model.
Because of significant statistical heterogeneity across the studies was found for effect size of sensitivity. The diagnostic sensitivity was calculated by random effect model. The combined results showed the pooled diagnostic sensitivity was 0.73 with its 95% CI of 0.69–0.76, [Figure 1].
For significant statistical heterogeneity, the specificity was pooled by random effect model. The pooled specificity was 0.86 with its 95% CI of 0.85–0.87, [Figure 2].
Area under the receiver operating characteristic
The diagnostic area under the receiver operating characteristic curve (AUC) was also calculated in this meta-analysis. The AUC was 0.896 [Figure 3].
| > Discussion|| |
In this meta-analysis, we finally included eight open published studies with 4764 cases. We found that the pooled diagnostic sensitivity was 0.73, which indicated the missed diagnosis rate was 17%. The pooled diagnostic specificity was 0.86, which indicated the misdiagnosis rate was 14%. It means that there were 14 noncolorectal cancer subjects diagnosed of this disease in 100 subjects who received contrast-enhanced computer tomography examination. Moreover, the pooled AUC was 0.896, which indicated contrast-enhanced computer tomography was a good method for detection of colorectal cancer with high sensitivity and specificity.
However, several limitations were found in our present meta-analysis: (1) the searching language was restricted to Chinese and English only. Hence, articles published in other language cannot be included in this meta-analysis. This drawback may lead to publication selection bias. (2) We found significant statistical heterogeneity across the included studies for the effect size of diagnostic sensitivity and specificity. (3) The cases included in each study were relatively small, which would decrease the statistical power. (4) No well-designed studies published in Chinese were found and included in this meta-analysis.
| > Conclusion|| |
According to the present evidence, contrast-enhanced computer tomography is a good method for the detection of colorectal cancer. However, for the above limitations, multicenter well-designed prospective diagnostic studies are needed for further evaluation, the clinical efficacy of contrast-enhanced computer tomography in diagnosis of colorectal cancer.,
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin 2012;62:10-29.
Chen M, Wang Y, Li Y, Zhao L, Ye S, Wang S, et al.
Association of plasma visfatin with risk of colorectal cancer: An observational study of Chinese patients. Asia Pac J Clin Oncol 2016;12:e65-74.
Fletcher JG, Johnson CD, Welch TJ, MacCarty RL, Ahlquist DA, Reed JE, et al.
Optimization of CT colonography technique: Prospective trial in 180 patients. Radiology 2000;216:704-11.
Wong BC, Wong WM, Chan JK, Lai KC, Hu WH, Chan CK, et al.
Virtual colonoscopy for the detection of colorectal polyps and cancers in a Chinese population. J Gastroenterol Hepatol 2002;17:1323-7.
Miao YM, Amin Z, Healy J, Burn P, Murugan N, Westaby D, et al.
A prospective single centre study comparing computed tomography pneumocolon against colonoscopy in the detection of colorectal neoplasms. Gut 2000;47:832-7.
Pickhardt PJ, Choi JR, Hwang I, Butler JA, Puckett ML, Hildebrandt HA, et al.
Computed tomographic virtual colonoscopy to screen for colorectal neoplasia in asymptomatic adults. N Engl J Med 2003;349:2191-200.
Pineau BC, Ott DJ. CT colonography to detect colorectal polyps: A virtual success? Am J Gastroenterol 2003;98:210-1.
Hoppe H, Quattropani C, Spreng A, Mattich J, Netzer P, Dinkel HP. Virtual colon dissection with CT colonography compared with axial interpretation and conventional colonoscopy: Preliminary results. AJR Am J Roentgenol 2004;182:1151-8.
Kim YS, Kim N, Kim SH, Park MJ, Lim SH, Yim JY, et al.
The efficacy of intravenous contrast-enhanced 16-raw multidetector CT colonography for detecting patients with colorectal polyps in an asymptomatic population in Korea. J Clin Gastroenterol 2008;42:791-8.
Johnson CD, Chen MH, Toledano AY, Heiken JP, Dachman A, Kuo MD, et al.
Accuracy of CT colonography for detection of large adenomas and cancers. N Engl J Med 2008;359:1207-17.
Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003;327:557-60.
Shafer SL, Dexter F. Publication bias, retrospective bias, and reproducibility of significant results in observational studies. Anesth Analg 2012;114:931-2.
Gandon Y. Screening for colorectal cancer: The role of CT colonography. Diagn Interv Imaging 2014;95:467-74.
Sali L, Falchini M, Taddei A, Mascalchi M. Role of preoperative CT colonography in patients with colorectal cancer. World J Gastroenterol 2014;20:3795-803.
[Figure 1], [Figure 2], [Figure 3]