Exfoliated colonocyte DNA levels and clinical features in the diagnosis of colorectal cancer: a cohort study in patients referred for investigation

The performance of FIT-based and other risk prediction models for colorectal neoplasia in symptomatic patients: a systematic review

Background

Colorectal cancer (CRC) incidence and mortality are increasing internationally. Endoscopy services are under significant pressure with many overwhelmed. Faecal immunochemical testing (FIT) has been advocated to identify a high-risk population of symptomatic patients requiring definitive investigation by colonoscopy. Combining FIT with other factors in a risk prediction model could further improve performance in identifying those requiring investigation most urgently. We systematically reviewed performance of models predicting risk of CRC and/or advanced colorectal polyps (ACP) in symptomatic patients, with a particular focus on those models including FIT.

Methods

The review protocol was published on PROSPERO (CRD42022314710). Searches were conducted from database inception to April 2023 in MEDLINE, EMBASE, Cochrane libraries, SCOPUS and CINAHL. Risk of bias of each study was assessed using The Prediction study Risk Of Bias Assessment Tool. A narrative synthesis based on the guidelines for Synthesis Without Meta-Analysis was performed due to study heterogeneity.

Findings

We included 62 studies; 23 included FIT (n = 22) or guaiac Faecal Occult Blood Testing (n = 1) combined with one or more other variables. Twenty-one studies were conducted solely in primary care. Generally, prediction models including FIT consistently had good discriminatory ability for CRC/ACP (i.e. AUC >0.8) and performed better than models without FIT although some models without FIT also performed well. However, many studies did not present calibration and internal and external validation were limited. Two studies were rated as low risk of bias; neither model included FIT.

Interpretation

Risk prediction models, including and not including FIT, show promise for identifying those most at risk of colorectal neoplasia. Substantial limitations in evidence remain, including heterogeneity, high risk of bias, and lack of external validation. Further evaluation in studies adhering to gold standard methodology, in appropriate populations, is required before widespread adoption in clinical practice.

Funding

National Institute for Health and Care Research (NIHR) [Health Technology Assessment Programme (HTA) Programme (Project number 133852).

Development and Validation of Risk Prediction Models for Colorectal Cancer in Patients with Symptoms

We aimed to develop and validate prediction models incorporating demographics, clinical features, and a weighted genetic risk score (wGRS) for individual prediction of colorectal cancer (CRC) risk in patients with gastroenterological symptoms. Prediction models were developed with internal validation [CRC Cases: n = 1686/Controls: n = 963]. Candidate predictors included age, sex, BMI, wGRS, family history, and symptoms (changes in bowel habits, rectal bleeding, weight loss, anaemia, abdominal pain). The baseline model included all the non-genetic predictors. Models A (baseline model + wGRS) and B (baseline model) were developed based on LASSO regression to select predictors. Models C (baseline model + wGRS) and D (baseline model) were built using all variables. Models' calibration and discrimination were evaluated through the Hosmer-Lemeshow test (calibration curves were plotted) and C-statistics (corrected based on 1000 bootstrapping). The models' prediction performance was: model A (corrected C-statistic = 0.765); model B (corrected C-statistic = 0.753); model C (corrected C-statistic = 0.764); and model D (corrected C-statistic = 0.752). Models A and C, that integrated wGRS with demographic and clinical predictors, had a statistically significant improved prediction performance. Our findings suggest that future application of genetic predictors holds significant promise, which could enhance CRC risk prediction. Therefore, further investigation through model external validation and clinical impact is merited.

Risk prediction models for colorectal cancer in people with symptoms: a systematic review

Background

Colorectal cancer (CRC) is the fourth leading cause of cancer-related death in Europe and the United States. Detecting the disease at an early stage improves outcomes. Risk prediction models which combine multiple risk factors and symptoms have the potential to improve timely diagnosis. The aim of this review is to systematically identify and compare the performance of models that predict the risk of primary CRC among symptomatic individuals.

Methods

We searched Medline and EMBASE to identify primary research studies reporting, validating or assessing the impact of models. For inclusion, models needed to assess a combination of risk factors that included symptoms, present data on model performance, and be applicable to the general population. Screening of studies for inclusion and data extraction were completed independently by at least two researchers.

Results

Twelve thousand eight hundred eight papers were identified from the literature search and three through citation searching. 18 papers describing 15 risk models were included. Nine were developed in primary care populations and six in secondary care. Four had good discrimination (AUROC > 0.8) in external validation studies, and sensitivity and specificity ranged from 0.25 and 0.99 to 0.99 and 0.46 depending on the cut-off chosen.

Conclusions

Models with good discrimination have been developed in both primary and secondary care populations. Most contain variables that are easily obtainable in a single consultation, but further research is needed to assess clinical utility before they are incorporated into practice.

Electronic supplementary material

The online version of this article (doi:10.1186/s12876-016-0475-7) contains supplementary material, which is available to authorized users.

DNA quantification of exfoliated colonocytes as a novel screening tool for colorectal cancer

AIMS

Colorectal cancer (CRC) sheds viable cells in the mucocelluar layer overlaying the colonic mucosa which travels distally alongside the faecal stream. These cells can be retrieved from the surface of the rectal mucosa. DNA quantification of these cells may be a marker of CRC, assessment of which was aim of this study.

METHODS

A prospective double-blinded study of 467 consecutive patients referred with symptoms suggestive of CRC. Cells were collected from the surface of the rectal mucosa and total DNA quantified. DNA scores were compared with outcome after subjects had completed bowel investigations. Analysis of receiver operating characteristic (ROC) curves was performed to determine the optimum cut-off point for a positive result.

RESULTS

107 of the 467 patients were excluded due to; excessive faecal contamination of samples (n = 84); declined investigations (n = 17); inappropriate referral (n = 5); unfit (n = 1). 263 patients had lower GI endoscopy; 89 CT colonography and 8 barium enema. The diagnosis were; CRC (n = 23), inflammatory bowel disease (IBD) (n = 7), adenomatous polyps (AP) (n = 20) and no significant abnormality detected (n = 310). ROC analysis revealed that sensitivities at a specificity of 60% for detecting CRC were 91.3%; for CRC and IBD 86.7%; and for CRC, IBD and AP 72.0%.

CONCLUSION

In symptomatic patients DNA quantification of cells retrieved from the surface of the rectal mucosa is sensitive for the detection of CRC. Although faecal contamination is a limitation of this technique, refinement and application of other molecular tests hold promise for a better non invasive method for the detection of CRC.