Meta-Analysis: Computed Tomographic Colonography

Colorectal cancer is the second most frequent cause of cancer-related death in the United States. Nearly 150000 new cases and 60000 deaths occur each year from this disease (1). Because colorectal cancer develops insidiously over time as genetic mutations accumulate in clinically silent adenomatous polyps, it is most commonly diagnosed at an advanced stage (2-4). If the condition is diagnosed at an early stage, the prognosis is favorable, with 5-year survival rates exceeding 90% (5, 6). Colorectal cancer, unlike many other types of cancer, can be prevented by removal of precancerous lesions. The long preclinical phase, early detectability, and improved prognosis of colorectal cancer have established the need for an accurate screening method. Various screening tests in current use reduce the incidence and rate of death from colorectal cancer (7, 8). Despite the proven efficacy of these tests, however, patient adherence to screening guidelines is low: Only 30% to 45% of persons eligible for screening undergo such tests. Low adherence rates are believed to be due to poor public awareness and poor public acceptance of current screening techniques (9-13). An increasingly popular screening test for colorectal cancer is computed tomographic (CT) colonography, also known as CT colography or virtual colonoscopy. Computed tomographic colonography was first described in 1994 as a radiographic technique in which thin-section images of pneumocolon could be reconstructed by sophisticated software into high-resolution 2- and 3-dimensional images (14). Over time, improvements in hardware and software have allowed faster scanning, reduced exposure to radiation, and better imaging. Newer modes of imaging (called fly-through) can produce results that resemble endoscopic images and permit sophisticated characterization of detected lesions (15-17). Early studies primarily used the spiral CT scanner, which has limitations in spatial resolution that can make small polyps more difficult to detect (17). The multidetector CT scanner has permitted rapid acquisition of finer images, obtained during a single breath-hold, that can greatly improve image quality and spatial resolution (17, 18). Many aspects of this technology are under study, including software that assists in detection of lesions, refinements in image reconstruction, and stool tagging (19-21). The latter development relies on ingestion of contrast material over several days or hours, after which software digitally subtracts residual solid and fluid fecal material from the acquired images, creating a virtually clean mucosal surface (22, 23). This technique may improve sensitivity and may someday obviate the need for bowel cleansing before examination. Although it is touted as a less invasive screening method than flexible sigmoidoscopy or colonoscopy, CT colonography typically requires full bowel cleansing and insufflation of air through the rectum (24). Studies have suggested that CT colonography may be similar, and in some cases preferable, to colonoscopy in terms of comfort and acceptability, but no convincing difference between these 2 approaches has been demonstrated (25-31). If virtual colonoscopy is found to have equivalent test characteristics, improve patient adherence, and be safer or less expensive than colonoscopy, it may be more cost-effective and become the screening method of choice (32, 33). Studies of the test characteristics of CT colonography have had mixed results. Pickhardt and colleagues used CT colonography in 1233 patients and found a sensitivity of 93.9% for adenomatous polyps larger than 8 mm (25). Other studies have had less favorable results, with sensitivities as low as 55% for polyps larger than 10 mm, raising concerns about the overall test performance of CT colonography when used in a broader range of settings (34). Various reasons for these discrepant results have been offered, but the source of this heterogeneity has not been fully explored (16, 35, 36). Such assessment is needed because patients and providers look to this technology in the hope of improving screening rates (29). We systematically reviewed the literature to assess the test performance of CT colonography compared with colonoscopy or surgery, to define characteristics of these studies, and to attempt to explain the sources of conflicting results. Methods Study Identification and Selection We searched the PubMed, EMBASE, and MEDLINE databases and the Cochrane Controlled Trials Register for all relevant articles published in the English language between 1975 and February 2005 by using the Medical Subject Headings or text words virtual colonoscopy, CT colonography, CT colography, or CT pneumocolon. The title and abstract of potentially relevant studies and review articles were screened for appropriateness before retrieval of the full articles. Two reviewers independently searched the literature. Inclusion criteria were a prospective, blinded design (in which results of CT colonography were interpreted independently of findings on colonoscopy or during surgery); enrollment of adult patients who were to undergo CT colonography after a full bowel preparation, followed by complete colonoscopy or surgery; and use of at least a single-detector CT scanner, with colon insufflation by air or carbon dioxide, scan intervals no greater than 5 mm, and use of both 2-dimensional and 3-dimensional views during scan interpretation. Study Quality Two observers independently extracted data on test characteristics; study setting; patients; and components of methodologic quality that may be associated with bias in test accuracy studies, including disease severity, disease prevalence, prospective design, relevant clinical sample (as opposed to a diagnostic casecontrol study), enrollment of a series of consecutive patients, assurance that all patients underwent reference testing, performance and interpretation of the index test without knowledge of the results of the reference test, and performance and interpretation of the reference test without knowledge of the results of the index test (33). A piloted standardized data extraction sheet was used, and disagreements were resolved by consensus. Data Abstraction We abstracted characteristics of the study (design, country, year, reference standard, and type of contrast used), patients (demographic and risk for colorectal cancer), scanners (manufacturer, type of viewer, type of contrast, software, and hardware), and study quality. Sensitivity and specificity were calculated per patient, per polyp, and for polyps of 3 size categories: smaller than 6 mm, 6 to 9 mm, and larger than 9 mm. When data on test performance were reported for 2 or more separate CT colonography readers, we calculated an average value. When possible, we excluded data on double readings. If a study reported data related specifically to adenomas instead of polyps, in general, we abstracted only the data for adenomas. For studies that performed retrospective analysis (for example, fly-through imaging in the study by Cotton and associates [34]), we abstracted only data on CT colonography findings before colonoscopy. If data could not be extracted or calculated from the manuscript with confidence, none were entered. Two reviewers independently abstracted data, and disagreements were resolved by consensus. Statistical Analysis Pooled sensitivities and specificities on a per-patient basis were combined and weighted according to sample size. Confidence intervals for each study were calculated by using exact binomial methods in a random-effects model. We focused our analysis on per-patient data because this is the most important perspective for a screening test, whereas per-polyp data emphasize the ability of CT colonography to find colonic lesions. That is, the latter analysis assesses the performance of the technology rather than its utility as a screening tool. Heterogeneity was assessed by using the I2 statistic (37). The I2 statistic provides an estimate of the amount of variance due to heterogeneity rather than chance and is based on the traditional measure of variance, the Cochrane Q statistic. Potential threshold effects were assessed by using the Spearman statistic and by creating receiver-operating characteristic curves according to the method of Moses and coworkers (38). Heterogeneity was assessed by performing stratified analyses when the potential confounding variable was dichotomous or categorical, by plotting the weighted effect size against the potential confounding variable when that variable was continuous, and by applying meta-regression methods in either case (39). Subgroup analyses were done by year of publication, imaging technique (2-dimensional imaging with 3-dimensional confirmation only when a lesion was noted, 3-dimensional imaging with 2-dimensional confirmation, 2-dimensional imaging with concomitant 3-dimensional imaging, or fly-through technology), collimation width and reconstruction interval (in millimeters), type of scanner (single-detector, multidetector, or mixed), and use of a contrast agent (yes or no). When collimation or reconstruction thickness was given in half-millimeter increments, we rounded the values up to the next whole number. The meta-regression analysis used the restricted maximum likelihood method and was performed by using indicator variables to assess differences among the strata. All analyses were performed with Stata software, version 8.2 (Stata Corp., College Station, Texas). Data Synthesis Our final pool of eligible studies (Appendix Figure) included 33 prospective studies involving 6393 patients that compared CT colonography to the reference standard of colonoscopy or surgery (22, 25, 34, 40-69). Studies originated from 7 different countries, but most were done in the United States (64%). The average number of participants in a study was 248 (range, 20 to 1233). The mean age of participants was 61.9 years; 63.6% of participants were ma