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

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. 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. 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. 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.JUS is funded by a National Institute of Health Research (NIHR) Clinica

Targeted depletion of pks+ bacteria from a fecal microbiota using specific antibodies

The pks island is one of the most prevalent pathogenicity islands among the Escherichia coli strains that colonize the colon of colorectal carcinoma (CRC) patients. This pathogenic island encodes the production of a nonribosomal polyketide-peptide named colibactin, which induces double-strand breaks in DNA molecules. Detection or even depletion of this pks-producing bacteria could help to understand the role of these strains in the context of CRC. In this work, we performed a large-scale in silico screening of the pks cluster in more than 6,000 isolates of E. coli. The results obtained reveal that not all the pks-detected strains could produce a functional genotoxin and, using antibodies against pks-specific peptides from surface cell proteins, a methodology for detection and depletion of pks+ bacteria in gut microbiotas was proposed. With our method, we were able to deplete a human gut microbiota of this pks+ strains, opening the door to strain-directed microbiota modification and intervention studies that allow us to understand the relation between these genotoxic strains and some gastrointestinal diseases. The human gut microbiome has also been hypothesized to play a crucial role in the development and progression of colorectal carcinoma (CRC). Between the microorganisms of this community, the Escherichia coli strains carrying the pks genomic island were shown to be capable of promoting colon tumorigenesis in a colorectal cancer mouse model, and their presence seems to be directly related to a distinct mutational signature in patients suffering CRC. This work proposes a novel method for the detection and depletion of pks-carrying bacteria in human gut microbiotas. In contrast to methods based on probes, this methodology allows the depletion of low-abundance bacterial strains maintaining the viability of both targeted and non-targeted fractions of the microbiota, allowing the study of the contribution of these pks-carrying strains to different diseases, such as CRC, and their role in other physiological, metabolic or immune processes.This work was supported by the Spanish “Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad” (Grant AGL2016-78311-R and contract BES-2017-080978, funded by AEI/FEDER, UEAGL2016-78311-R); the Asociación Española Contra el Cáncer (“Obtención de péptidos bioactivos contra el Cáncer Colo-Rectal a partir de secuencias genéticas de microbiomas intestinales”, Grant PS-2016 and by the Asturias Regional Plan I+D+i for research groups (FICYT-IDI/2018/000236, funded by PCTI Gobierno del Principado de Asturias/FEDER, UE). This study was also supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER006684). SING group thanks CITI (Centro de Investigación, Transferencia e Innovación) from the University of Vigo for hosting its IT infrastructure. A.B.M. was supported by a predoctoral contract from the AECC. Borja Sánchez and Abelardo Margolles are on the scientific board and are co-founders of Microviable Therapeutics SL. The other authors have no competing interests. Results presented in this paper are protected under European Patent EP19383077 (WO2021110833A1 and US20230029322A1; Tools and methods to detect and isolate colibactin producing bacteria).info:eu-repo/semantics/publishedVersio

Colorectal Cancer Survival in 50- to 69-Year-Olds after Introducing the Faecal Immunochemical Test

Population screening has improved early diagnosis of colorectal cancer (CRC). Nonetheless, most cases are diagnosed in symptomatic patients. Faecal immunochemical testing has been recommended for assessing patients with lower gastrointestinal symptoms, but whether it improves patient survival is unknown. Our objective was to compare CRC survival in 50- to 69-year-olds between asymptomatic screen-detected patients and symptomatic patients by route to diagnosis. Methods: We identified all cases of CRC diagnosed in 50-to 69-year-olds between 2009 and 2016, in Donostialdea (Gipuzkoa, Spain). Three groups were created: 1-screen-detected CRC; 2-CRC detected in symptomatic patients after a positive faecal immunochemical test(FIT); and 3-CRC detected in symptomatic patients without a FIT or after a negative result. We analysed survival using the Kaplan-Meier method and log-rank tests. Results: Of 930 patients diagnosed with CRC, 433 cases were detected through screening and 497 in symptomatic patients, 7.9% after a positive FIT and 45.5% by other means. The 3-year CRC survival was significantly lower in group 3 (69.5%) than groups 1 (93%; p = 0.007) or 2 (87.5%; p = 0.02). The risk of death was lower in groups 1 (HR 0.42, 95% CI 0.30–0.58) and 2 (HR 0.51; 95% CI 0.29–0.87). Conclusion: Half of CRC cases in 50- to 69-year-olds are diagnosed outside screening. Use of the FIT as a diagnostic strategy in symptomatic patients may improve survival

A Novel Approach on the Use of Samples from Faecal Occult Blood Screening Kits for Metabolomics Analysis: Application in Colorectal Cancer Population

The incidence of colorectal cancer (CRC) is increasing, and currently it is the third most common cancer. Early CRC diagnosis is still difficult and relies on an invasive colonoscopy and tissue biopsy. The globally observed tendency demands non-invasive, specific, and accurate diagnostic tools for early diagnosis and prognosis. In this work, the main aim was to evaluate for the first time the feasibility of using extracts from the non-invasive sample collection from faecal occult blood (FOB) kits for its use in metabolomics studies taking advantage in this way of the high sensitivity of this technology. Then, a cohort of 131 samples from control individuals (CTL), adenoma (AD) and CRC patients were analysed using a semitargeted approach by ultra-high-performance liquid chromatography–time-of-flight–mass spectrometry (UHPLC-ToF-MS). Multivariate and univariate statistical analysis revealed that cholesteryl esters (ChoE) with polyunsaturated fatty acids (PUFAs) together with FOB were relevant metabolites that could clearly separate CRC patients from AD and CTL individuals, whereas the metabolic profiles of CTL and AD were very similar. These results are in agreement with previous findings and reveal the advantage of using the same FOBT samples for several analyses, which would facilitate sample collection and improve direct connection between FOB measurements and metabolomics analysis. Although the sample size and the number of metabolites should be enhanced to cover a wider range of metabolites, alterations in lipid metabolism clearly point out for future perspectives.This research was funded by Instituto de Salud Carlos III (DTS19/00160). M.E.B., B.L. and C.A. are employed by OWL Metabolomics (One-way Liver, S.L.)

Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias. A Randomized Trial.

Background: The role of computer-aided detection in identifying advanced colorectal neoplasia is unknown. Objective: To evaluate the contribution of computer-aided detection to colonoscopic detection of advanced colorectal neoplasias as well as adenomas, serrated polyps, and nonpolypoid and right-sided lesions. Design: Multicenter, parallel, randomized controlled trial. (ClinicalTrials.gov: NCT04673136) Setting: Spanish colorectal cancer screening program. Participants: 3213 persons with a positive fecal immunochemical test. Intervention: Enrollees were randomly assigned to colonoscopy with or without computer-aided detection. Measurements: Advanced colorectal neoplasia was defined as advanced adenoma and/or advanced serrated polyp. Results: The 2 comparison groups showed no significant difference in advanced colorectal neoplasia detection rate (34.8% with intervention vs. 34.6% for controls; adjusted risk ratio [aRR], 1.01 [95% CI, 0.92 to 1.10]) or the mean number of advanced colorectal neoplasias detected per colonoscopy (0.54 [SD, 0.95] with intervention vs. 0.52 [SD, 0.95] for controls; adjusted rate ratio, 1.04 [99.9% CI, 0.88 to 1.22]). Adenoma detection rate also did not differ (64.2% with intervention vs. 62.0% for controls; aRR, 1.06 [99.9% CI, 0.91 to 1.23]). Computer-aided detection increased the mean number of nonpolypoid lesions (0.56 [SD, 1.25] vs. 0.47 [SD, 1.18] for controls; adjusted rate ratio, 1.19 [99.9% CI, 1.01 to 1.41]), proximal adenomas (0.94 [SD, 1.62] vs. 0.81 [SD, 1.52] for controls; adjusted rate ratio, 1.17 [99.9% CI, 1.03 to 1.33]), and lesions of 5 mm or smaller (polyps in general and adenomas and serrated lesions in particular) detected per colonoscopy. Limitations: The high adenoma detection rate in the control group may limit the generalizability of the findings to endoscopists with low detection rates. Conclusion: Computer-aided detection did not improve colonoscopic identification of advanced colorectal neoplasias. Primary Funding Source: Medtronic

Risk of gastrointestinal cancer in a symptomatic cohort after a complete colonoscopy: Role of faecal immunochemical test

BACKGROUND: Faecal immunochemical test (FIT) has been recommended to assess symptomatic patients for colorectal cancer (CRC) detection. Nevertheless, some conditions could theoretically favour blood originating in proximal areas of the gastrointestinal tract passing through the colon unmetabolized. A positive FIT result could be related to other gastrointestinal cancers (GIC). AIM To assess the risk of GIC detection and related death in FIT-positive symptomatic patients (threshold 10 mu g Hb/g faeces) without CRC. METHODS: Post hoc cohort analysis performed within two prospective diagnostic test studies evaluating the diagnostic accuracy of different FIT analytical systems for CRC and significant colonic lesion detection. Ambulatory patients with gastrointestinal symptoms referred consecutively for colonoscopy from primary and secondary healthcare, underwent a quantitative FIT before undergoing a complete colonoscopy. Patients without CRC were divided into two groups (positive and negative FIT) using the threshold of 10 mu g Hb/g of faeces and data from follow-up were retrieved from electronic medical records of the public hospitals involved in the research. We determined the cumulative risk of GIC, CRC and upper GIC. Hazard rate (HR) was calculated adjusted by age, sex and presence of significant colonic lesion. RESULTS: We included 2709 patients without CRC and a complete baseline colonoscopy, 730 (26.9%) with FIT >= 10 mu gr Hb/gr. During a mean time of 45.5 +/- 20.0 mo, a GIC was detected in 57 (2.1%) patients: An upper GIC in 35 (1.3%) and a CRC in 14 (0.5%). Thirty-six patients (1.3%) died due to GIC: 22 (0.8%) due to an upper GIC and 9 (0.3%) due to CRC. FIT-positive subjects showed a higher CRC risk (HR 3.8, 95%CI: 1.2-11.9) with no differences in GIC (HR 1.5, 95%CI: 0.8-2.7) or upper GIC risk (HR 1.0, 95%CI: 0.5-2.2). Patients with a positive FIT had only an increased risk of CRC-related death (HR 10.8, 95%CI: 2.1-57.1) and GIC-related death (HR 2.2, 95%CI: 1.1-4.3), with no differences in upper GIC-related death (HR 1.4, 95%CI: 0.6-3.3). An upper GIC was detected in 22 (0.8%) patients during the first year. Two variables were independently associated: anaemia (OR 5.6, 95%CI: 2.2-13.9) and age >= 70 years (OR 2.7, 95%CI: 1.1-7.0). CONCLUSION Symptomatic patients without CRC have a moderate risk increase in upper GIC, regardless of the FIT result. Patients with a positive FIT have an increased risk of post-colonoscopy CRC

Development and external validation of a faecal immunochemical test-based prediction model for colorectal cancer detection in symptomatic patients

Background: Risk prediction models for colorectal cancer (CRC) detection in symptomatic patients based on available biomarkers may improve CRC diagnosis. Our aim was to develop, compare with the NICE referral criteria and externally validate a CRC prediction model, COLONPREDICT, based on clinical and laboratory variables. Methods: This prospective cross-sectional study included consecutive patients with gastrointestinal symptoms referred for colonoscopy between March 2012 and September 2013 in a derivation cohort and between March 2014 and March 2015 in a validation cohort. In the derivation cohort, we assessed symptoms and the NICE referral criteria, and determined levels of faecal haemoglobin and calprotectin, blood haemoglobin, and serum carcinoembryonic antigen before performing an anorectal examination and a colonoscopy. A multivariate logistic regression analysis was used to develop the model with diagnostic accuracy with CRC detection as the main outcome. Results: We included 1572 patients in the derivation cohort and 1481 in the validation cohorts, with a 13.6 % and 9. 1 % CRC prevalence respectively. The final prediction model included 11 variables: age (years) (odds ratio [OR] 1.04, 95 % confidence interval [CI] 1.02-1.06), male gender (OR 2.2, 95 % CI 1.5-3.4), faecal haemoglobin >= 20 mu g/g (OR 17.0, 95 % CI 10.0-28.6), blood haemoglobin = 3 ng/mL (OR 4.5, 95 % CI 3.0-6.8), acetylsalicylic acid treatment (OR 0.4, 95 % CI 0.2-0.7), previous colonoscopy (OR 0.1, 95 % CI 0.06-0.2), rectal mass (OR 14.8, 95 % CI 5.3-41.0), benign anorectal lesion (OR 0.3, 95 % CI 0.2-0.4), rectal bleeding (OR 2.2, 95 % CI 1.4-3.4) and change in bowel habit (OR 1.7, 95 % CI 1.1-2.5). The area under the curve (AUC) was 0.92 (95 % CI 0.91-0.94), higher than the NICE referral criteria (AUC 0.59, 95 % CI 0.55-0.63; p < 0.001). On the basis of the thresholds with 90 % (5.6) and 99 % (3.5) sensitivity, we divided the derivation cohort into three risk groups for CRC detection: high (30.9 % of the cohort, positive predictive value [PPV] 40.7 %, 95 % CI 36.7-45.9 %), intermediate (29.5 %, PPV 4.4 %, 95 % CI 2.8-6.8 %) and low (39.5 %, PPV 0.2 %, 95 % CI 0.0-1.1 %). The discriminatory ability was equivalent in the validation cohort (AUC 0.92, 95 % CI 0.90-0.94; p = 0.7). Conclusions: COLONPREDICT is a highly accurate prediction model for CRC detection.This study was funded by a grant from Instituto de Salud Carlos III (PI11/00094). JC and VH have received an intensification grant through the European Commission funded "BIOCAPS" project (FP-7-REGPOT 2012-2013-1, Grant agreement no. FP7-316265). The validation cohort recruitment was funded by a grant from Fundacio de la Marato TV3 2012 (785/U/2013). The funding institutions had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the article for publication

Predictive Value of Carcinoembryonic Antigen in Symptomatic Patients without Colorectal Cancer: A Post-Hoc Analysis within the COLONPREDICT Cohort

We aimed to assess the risk of cancer in patients with abdominal symptoms after a complete colonoscopy without colorectal cancer (CRC), according to the carcinoembryonic antigen (CEA) concentration, as well as its diagnostic accuracy. For this purpose, we performed a post-hoc analysis within a cohort of 1431 patients from the COLONPREDICT study, prospectively designed to assess the fecal immunochemical test accuracy in detecting CRC. Over 36.5 ± 8.4 months, cancer was detected in 115 (8%) patients. Patients with CEA values higher than 3 ng/mL revealed an increased risk of cancer (HR 2.0, 95% CI 1.3–3.1), CRC (HR 4.4, 95% CI 1.1–17.7) and non-gastrointestinal cancer (HR 1.7, 95% CI 1.0–2.8). A new malignancy was detected in 51 (3.6%) patients during the first year and three variables were independently associated: anemia (OR 2.8, 95% CI 1.3–5.8), rectal bleeding (OR 0.3, 95% CI 0.1–0.7) and CEA level >3 ng/mL (OR 3.4, 95% CI 1.7–7.1). However, CEA was increased only in 31.8% (95% CI, 16.4–52.7%) and 50% (95% CI, 25.4–74.6%) of patients with and without anemia, respectively, who would be diagnosed with cancer during the first year of follow-up. On the basis of this information, CEA should not be used to assist in the triage of patients presenting with lower bowel symptoms who have recently been ruled out a CRCThis work was supported by Spain’s Carlos III Healthcare Institute by means of project PI17/00837 (Co-funded by European Regional Development Fund/European Social Fund “A way to make Europe”/“Investing in your future

Development and external validation of a faecal immunochemical test-based prediction model for colorectal cancer detection in symptomatic patients

Background: risk prediction models for colorectal cancer (CRC) detection in symptomatic patients based on available biomarkers may improve CRC diagnosis. Our aim was to develop, compare with the NICE referral criteria and externally validate a CRC prediction model, COLONPREDICT, based on clinical and laboratory variables. Methods: this prospective cross-sectional study included consecutive patients with gastrointestinal symptoms referred for colonoscopy between March 2012 and September 2013 in a derivation cohort and between March 2014 and March 2015 in a validation cohort. In the derivation cohort, we assessed symptoms and the NICE referral criteria, and determined levels of faecal haemoglobin and calprotectin, blood haemoglobin, and serum carcinoembryonic antigen before performing an anorectal examination and a colonoscopy. A multivariate logistic regression analysis was used to develop the model with diagnostic accuracy with CRC detection as the main outcome. Results: we included 1572 patients in the derivation cohort and 1481 in the validation cohorts, with a 13.6 % and 9.1 % CRC prevalence respectively. The final prediction model included 11 variables: age (years) (odds ratio [OR] 1.04, 95 % confidence interval [CI] 1.02-1.06), male gender (OR 2.2, 95 % CI 1.5-3.4), faecal haemoglobin ≥20 μg/g (OR 17.0, 95 % CI 10.0-28.6), blood haemoglobin <10 g/dL (OR 4.8, 95 % CI 2.2-10.3), blood haemoglobin 10-12 g/dL (OR 1.8, 95 % CI 1.1-3.0), carcinoembryonic antigen ≥3 ng/mL (OR 4.5, 95 % CI 3.0-6.8), acetylsalicylic acid treatment (OR 0.4, 95 % CI 0.2-0.7), previous colonoscopy (OR 0.1, 95 % CI 0.06-0.2), rectal mass (OR 14.8, 95 % CI 5.3-41.0), benign anorectal lesion (OR 0.3, 95 % CI 0.2-0.4), rectal bleeding (OR 2.2, 95 % CI 1.4-3.4) and change in bowel habit (OR 1.7, 95 % CI 1.1-2.5). The area under the curve (AUC) was 0.92 (95 % CI 0.91-0.94), higher than the NICE referral criteria (AUC 0.59, 95 % CI 0.55-0.63; p < 0.001). On the basis of the thresholds with 90 % (5.6) and 99 % (3.5) sensitivity, we divided the derivation cohort into three risk groups for CRC detection: high (30.9 % of the cohort, positive predictive value [PPV] 40.7 %, 95 % CI 36.7-45.9 %), intermediate (29.5 %, PPV 4.4 %, 95 % CI 2.8-6.8 %) and low (39.5 %, PPV 0.2 %, 95 % CI 0.0-1.1 %). The discriminatory ability was equivalent in the validation cohort (AUC 0.92, 95 % CI 0.90-0.94; p = 0.7). Conclusions: COLONPREDICT is a highly accurate prediction model for CRC detection

Increased Th17-Related Cytokine Serum Levels in Patients With Multiple Polyps of Unexplained Origin

OBJECTIVES: Most patientswith multiple colonic polyps do not have a known genetic or hereditary origin. Our aim was to analyze the presence of inflammatory cytokines and levels of glucose, insulin, and C-reactive protein (CRP) in patients with multiple colonic polyps. METHODS: Eighty-three patients with 10 or more adenomatous or serrated polyps and 53 control people with normal colonoscopy were included. Smoking habits were registered, and glucose, CRP, and basal insulin in the serum/blood weremeasured. Quantification of IL-2, IL-4, IL-6, IL-10, IL-11, IL-17A, and IL-23 cytokine levels in the serum was performed by a high-sensitivity enzyme-linked immunosorbent assay. RESULTS: Smoking and diabetesweremore prevalent in those with colonic polyps than in the control people (67% vs 16%, P = 0.001; 11% vs 2%, P = 0.048). In addition, the cytokine serum levels were higher, i.e., IL-2 (P = 0.001), IL-4 (P = 0.001), IL-6 (P = 0.001), IL-17A (P = 0.001), IL-23 (P = 0.014), and CRP (P = 0.003). Adjusting for sex, smoking, and diabetes in amultivariate analysis, IL-2, IL-4, IL-6, IL-17A, and IL-23 remained independently elevated in cases with multiple polyps. DISCUSSION: These results indicate that immune responses mediated by Th17 cells may be involved in the pathogenesis of multiple colonic polyps