A Risk Prediction Index for Advanced Colorectal Neoplasia at Screening Colonoscopy

A novel colorectal cancer screening framework with feature interpretability to identify high-risk populations for colonoscopy

BACKGROUND AND AIM

Risk assessment is of paramount importance for the detection and treatment of colorectal cancer. We developed and validated a feature interpretability screening framework to identify high-risk populations and recommend colonoscopy for them.

METHODS

We utilized a training cohort consisting of 1 252 605 participants who underwent colonoscopies in Shanghai from 2013 to 2015 to develop the screening framework. We incorporated Shapley additive explanation values into feature selection to provide interpretability for the framework. Two sampling methods were separately employed to mitigate potential model bias caused by class imbalance. Furthermore, we employed various machine learning algorithms to construct risk assessment models and compared their performance. We tested the screening models on an external validation cohort of 359 462 samples and conducted comprehensive evaluation and statistical analysis of the validation results.

RESULTS

The external validation results demonstrated that the models in the proposed framework achieved sensitivity over 0.734, specificity over 0.790, and area under the receiver operating characteristic curve ranging from 0.808 to 0.859. In the predictions of the best-performing model, the prevalence rates of colorectal cancer were 0.059% and 1.056% in the low- and high-risk groups, respectively. If colonoscopies were performed only on the high-risk group predicted by the model, only 14.36% of total colonoscopies would be needed to detect 74.86% of colorectal cancer cases.

CONCLUSIONS

We developed and validated a novel framework to identify populations at high risk for colorectal cancer. Those classified as high risk should undergo colonoscopy for further diagnosis.

Establishment and validation of symptomatic patients colorectal screening score for predicting colorectal neoplasia risk

OBJECTIVES

Currently, most colorectal neoplasia (CRN) screening strategies target asymptomatic individuals. However, studies on patients with non-specific gastrointestinal symptoms (NSGS) are limited. We aimed to develop a CRN risk score specifically for patients with NSGS.

METHODS

We prospectively enrolled patients who underwent initial colonoscopy between June 2020 and June 2021. A new risk scoring system was constructed and its applicability was evaluated.

RESULTS

A total of 1522 consecutive patients were enrolled, among whom 1016 symptomatic patients were randomly divided into a training cohort and a validation cohort at a ratio of 7:3. The constructed Symptomatic Patients Colorectal Screening (SPCS) score showed higher diagnostic efficacy and sensitivity than several previous scoring systems. Using the SPCS score, the patients were divided into a low-risk group (-2 to 3 points) and a high-risk group (4-10 points) for CRN. Additionally, the detection rate of CRN in the training and validation cohorts of the high-risk group were 41.7% and 37.0%, respectively. The SPCS score detected 79.3% (188/237) of CRN and 87.5% (42/48) of advanced CRN in the high-risk group, which reduced the workload of colonoscopy to 45.9% (466/1016).

CONCLUSION

An effective CRN risk scoring system was established and validated for symptomatic patients, which accurately classified individuals into low-risk and high-risk groups for CRN and might be used to optimize colonoscopic resource allocation.

Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart?

Current colorectal cancer (CRC) screening recommendations take a "one-size-fits-all" approach using age as the major criterion to initiate screening. Precision screening that incorporates factors beyond age to risk stratify individuals could improve on current approaches and optimally use available resources with benefits for patients, providers, and health care systems. Prediction models could identify high-risk groups who would benefit from more intensive screening, while low-risk groups could be recommended less intensive screening incorporating noninvasive screening modalities. In addition to age, prediction models incorporate well-established risk factors such as genetics (eg, family CRC history, germline, and polygenic risk scores), lifestyle (eg, smoking, alcohol, diet, and physical inactivity), sex, and race and ethnicity among others. Although several risk prediction models have been validated, few have been systematically studied for risk-adapted population CRC screening. In order to envisage clinical implementation of precision screening in the future, it will be critical to develop reliable and accurate prediction models that apply to all individuals in a population; prospectively study risk-adapted CRC screening on the population level; garner acceptance from patients and providers; and assess feasibility, resources, cost, and cost-effectiveness of these new paradigms. This review evaluates the current state of risk prediction modeling and provides a roadmap for future implementation of precision CRC screening.

Non-invasive model for predicting esophageal varices based on liver and spleen volume

BACKGROUND

Upper endoscopy is the gold standard for predicting esophageal varices in China. Guidelines and consensus suggest that patients with liver cirrhosis should undergo periodic upper endoscopy, most patients undergo their first upper endoscopy when esophageal variceal bleeds. Therefore, it is important to develop a non-invasive model to early diagnose esophageal varices.

AIM

To develop a non-invasive predictive model for esophageal varices based on liver and spleen volume in viral cirrhosis patients.

METHODS

We conducted a cross-sectional study based on viral cirrhosis crowd in the Second Affiliated Hospital of Xi'an Jiaotong University. By collecting the basic information and clinical data of the participants, we derived the independent risk factors and established the prediction model of esophageal varices. The established model was compared with other models. Area under the receiver operating characteristic curve, calibration plot and decision curve analysis were used to test the discriminating ability, calibration ability and clinical practicability in both the internal and external validation.

RESULTS

The portal vein diameter, the liver and spleen volume, and volume change rate were the independent risk factors of esophageal varices. We successfully used the factors to establish the predictive model [area under the curve (AUC) 0.87, 95%CI: 0.80-0.95], which showed better predictive value than other models. The model showed good discriminating ability, calibration ability and the clinical practicability in both modelling group and external validation group.

CONCLUSION

The developed non-invasive predictive model can be used as an effective tool for predicting esophageal varices in viral cirrhosis patients.

Head-to-head comparison of a risk-adapted screening strategy using various risk prediction models in detecting colorectal neoplasm

BACKGROUND AND AIM

The risk-adapted screening strategy showed satisfying colorectal cancer (CRC) screening yield and efficiency. We therefore further explored the diagnostic performance variation of this strategy using different risk prediction models.

METHODS

A literature search was conducted to identify studies evaluating risk models for advanced colorectal neoplasm (ACN). The included models were retrospectively validated in a subset sample (N = 3219) from a population-based CRC screening trial in China. Diagnosis-related indictors were compared between the risk-adapted screening strategy using different models and the fecal immunochemical test (FIT)-only strategy. For simulated populations with ACN prevalence of 3% to 12%, the trade-off of additional false positives for each additional true positive were calculated.

RESULTS

We included 14 eligible risk models with the area under the curves ranging 0.570 to 0.652 in the validation set. The overall sensitivities of the risk-adapted screening strategy using different risk models for ACN varied from 46.0% to 69.8%, higher than FIT (21.9%), but at the expense of specificities (51.6% to 78.3% vs 97.1%). For population having ACN prevalence of 3%, risk-adapted screening strategies needed 20.5 to 31.1 additional false positives for each additional true positive compared with FIT, and respective number would substantially reduce (4.7 to 7.1) as the ACN prevalence increased to 12%.

CONCLUSIONS

Risk-adapted screening strategy using the current risk models showed improved sensitivity for ACN compared with FIT, at the cost of increased colonoscopy workload. The optimal strategy for screening practice should be tailored considering the disease burden and availability of healthcare resources.

A scoping review of risk-stratified bowel screening: current evidence, future directions

PURPOSE

In this scoping review, we examined the international literature on risk-stratified bowel screening to develop recommendations for future research, practice and policy.

METHODS

Six electronic databases were searched from inception to 18 October 2021: Medline, Embase, PsycINFO, CINAHL, Cochrane Database of Systematic Reviews and Cochrane Central Register of Controlled Trials. Forward and backwards citation searches were also undertaken. All relevant literature were included.

RESULTS

After de-deduplication, 3,629 records remained. 3,416 were excluded at the title/abstract screening stage. A further 111 were excluded at full-text screening stage. In total, 102 unique studies were included. Results showed that risk-stratified bowel screening programmes can potentially improve diagnostic performance, but there is a lack of information on longer-term outcomes. Risk models do appear to show promise in refining existing risk stratification guidelines but most were not externally validated and less than half achieved good discriminatory power. Risk assessment tools in primary care have the potential for high levels of acceptability and uptake, and therefore, could form an important component of future risk-stratified bowel screening programmes, but sometimes the screening recommendations were not adhered to by the patient or healthcare provider. The review identified important knowledge gaps, most notably in the area of organisation of screening services due to few pilots, and what risk stratification might mean for inequalities.

CONCLUSION

We recommend that future research focuses on what organisational challenges risk-stratified bowel screening may face and a consideration of inequalities in any changes to organised bowel screening programmes.

Development of a Large Colonoscopy-Based Longitudinal Cohort for Integrated Research of Colorectal Cancer: Partners Colonoscopy Cohort

BACKGROUND AND AIMS

Conventional adenomas (CAs) and serrated polyps (SPs) are precursors to colorectal cancer (CRC). Understanding metachronous cancer risk is poor due to lack of accurate large-volume datasets. We outline the use of natural language processing (NLP) in forming the Partners Colonoscopy Cohort, an integrated longitudinal cohort of patients undergoing colonoscopies.

METHODS

We identified endoscopy quality data from endoscopy reports for colonoscopies performed from 2007 to 2018 in a large integrated healthcare system, Mass General Brigham). Through modification of an established NLP pipeline, we extracted histopathological data (polyp location, histology and dysplasia) from corresponding pathology reports. Pathology and endoscopy data were merged by polyp location using a four-stage algorithm. NLP and merging procedures were validated by manual review of 500 pathology reports.

RESULTS

305,656 colonoscopies in 213,924 patients were identified. After merging, 76,137 patients had matched polyp data for 334,750 polyps. CAs and SPs were present in 86,707 (28.5%) and 55,373 (18.2%) colonoscopies. Among patients with polyps at index screening colonoscopy, 14,931 (33.4%) had follow-up colonoscopy (median 46.4, interquartile range 33.8-62.4 months); 91 (0.2%) and 1127 (2.5%) patients developed metachronous CRC and high-risk polyps (polyps ≥ 10 mm or CAs having high-grade dysplasia/villous/tublovillous histology or SPs with dysplasia). Genetic data were available for 23,787 (31.7%) patients with polyps from the Partners Biobank. The validation study showed a positive predictive value of 100% for polyp histology and locations.

CONCLUSION

We created the Partners Colonoscopy Cohort providing essential infrastructure for future studies to better understand the natural history of CRC and improve screening and post-polypectomy strategies.

Prediction Model Using Readily Available Clinical Data for Colorectal Cancer in Chinese Population

BACKGROUND

In China, health screening has become common, although colonoscopy is not always available or acceptable. We sought to develop a prediction model of colorectal cancer (CRC) for health screening population based on readily available clinical data to reduce labor and economic costs.

METHODS

We conducted a cross-sectional study based on a health screening population in Karamay Central Hospital. By collecting clinical data and basic information from participants, we identified independent risk factors and established a prediction model of CRC. Internal and external validation, calibration plot, and decision curve analysis were employed to test discriminating ability, calibration ability, and clinical practicability.

RESULTS

Independent risk factors of CRC, which were readily available in basic public health institutions, included high-density lipoprotein cholesterol, male sex, total cholesterol, advanced age, and hemoglobin. These factors were successfully incorporated into the prediction model (AUC 0.740, 95% CI 0.713-0.767). The model demonstrated a high degree of discrimination and calibration, in addition to a high degree of clinical practicability in high-risk people.

CONCLUSIONS

The prediction model exhibits good discrimination and calibration and is pragmatic for CRC screening in rural areas and basic public health institutions.

OUP accepted manuscript

Background

The uptake of colonoscopy is low in individuals at risk of colorectal cancer (CRC). We constructed a risk-prediction score (RPS) in a large community-based sample at high risk of CRC to enable more accurate risk stratification and to motivate and increase the uptake rate of colonoscopy.

Methods

A total of 12,628 participants classified as high-risk according to positivity of immunochemical fecal occult blood tests or High-Risk Factor Questionnaire underwent colonoscopy. Logistic regression was used to derive a RPS and analysed the associations of the RPS with colorectal lesions, giving odds ratios (ORs) and 95% confidence intervals (CIs).

Results

Of the participants, men (OR = 1.73, 95% CI = 1.58–1.90), older age (≥65 years; 1.41, 1.31–1.53), higher body mass index (≥28 kg/m²; 1.22, 1.07–1.39), ever smoking (1.47, 1.31–1.65), and weekly alcohol use (1.28, 1.09–1.52) were associated with a higher risk of colorectal lesions. We assigned 1 point to each of the above five risk factors and derived a RPS ranging from 0 to 5, with a higher score indicating a higher risk. Compared with a RPS of 0, a RPS of 1, 2, 3, and 4–5 showed a higher risk of colorectal lesions, with the OR (95% CI) being 1.50 (1.37–1.63), 2.34 (2.12–2.59), 3.58 (3.13–4.10), and 3.91 (3.00–5.10), respectively. The area under the receiver-operating characteristic curve of RPS in predicting colorectal lesions was 0.62.

Conclusions

Participants with an increase in the RPS of ≥1 point had a significantly higher risk of colorectal lesions, suggesting the urgency for measuring colonoscopy in this very high-risk group. High-risk strategies incorporating RPS may be employed to achieve a higher colonoscopy-uptake rate.

Designing a Predictive Model for Colorectal Neoplasia Diagnosis Based on Clinical and Laboratory Findings in Colonoscopy Candidate Patients

BACKGROUND

Health authorities have expanded two strategies to diminish CRC-related influence: CR screening and improve diagnostic process in symptomatic patients. The aim of the current study is to design a predictive model to identify the most important risk factors that can efficiently predict patients who have high risk of colorectal neoplasia.

METHOD

A cross-sectional study was constructed to include all patients who had positive test for FIT or had one or more risk factors for colorectal cancer based on the guidelines of detecting high-risk groups for colorectal cancer in Iran. Multivariable binary logistic regression model was constructed for prediction of colorectal neoplasia. We used sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratio to check the accuracy. The Hosmer-Lemeshow test, chi-square test, and p value were used to determine the precision of model.

RESULT

Following an AIC stepwise selection model, only nine potential variables, namely gender, watery diarrhea, IBD, abdominal pain, melena, body mass index, depression drug, anti-inflammatory drug, and age, were found to be a predictor of colorectal neoplasia. The best cut-point probability in the final model was 0.27 and results of sensitivity and specificity, based on maximizing these two criteria, were 66% and 62%, respectively.

CONCLUSION

Overall, our model prediction was comparable with other risk prediction models for colorectal cancer. It had a modest discriminatory power to distinguish an individual's neoplasia colorectal risk.

Evaluation of a risk score based on dietary and lifestyle factors to target a population at risk in colorectal cancer screening

BACKGROUND

The aim of our study was to assess three risk scores to predict lesions, advanced neoplasia (high-risk adenomas and colorectal cancer (CRC)) and CRC in individuals who participate to colorectal cancer screening.

METHODS

The data of dietary and lifestyle risk factors were carried out during 2 mass screening campaigns in France (2013-2016) and the FOBT result was collected until December 2018. The colonoscopy result in positive FOBT was recovered. Three risk scores (Betés score, Kaminski score and adapted-HLI) were calculated to detect individuals at risk of lesions.

RESULTS

The Betés score had an AUROC of 0.63 (95% CI, [0.61-0.66]) for lesions, 0.65 (95% CI, [0.61-0.68]) for advanced neoplasia and 0.65 (95% CI, [0.58-0.72]) for predicting screen-detected CRC. The adapted HLI score had an AUROC of 0.61 (95% CI, [0.58-0.65]) for lesions, 0.61 (95% CI, [0.56-0.65]) for advanced neoplasia and 0.55 (95% CI, [0.45-0.65]) for predicting screen-detected CRC. The Kaminski score had an AUROC of 0.65 (95% CI, [0.63-0.68]) for lesions, 0.65 (95% CI, [0.61-0.68]) for advanced neoplasia and 0.69 (95% CI, [0.62-0.76]) for predicting screen-detected CRC.

CONCLUSION

A simple questionnaire based on CRC risk factors could help general practitioners to identify participants with higher risk of significant colorectal lesions and incite them to perform the fecal occult blood test.

Application of deep learning to predict advanced neoplasia using big clinical data in colorectal cancer screening of asymptomatic adults

BACKGROUND/AIMS

We aimed to develop a deep learning model for the prediction of the risk of advanced colorectal neoplasia (ACRN) in asymptomatic adults, based on which colorectal cancer screening could be customized.

METHODS

We collected data on 26 clinical and laboratory parameters, including age, sex, smoking status, body mass index, complete blood count, blood chemistry, and tumor marker, from 70,336 first-time colonoscopy screening recipients. For reference, we used a logistic regression (LR) model with nine variables manually selected from the 26 variables. A deep neural network (DNN) model was developed using all 26 variables. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of the models were compared in a randomly split validation group.

RESULTS

In comparison with the LR model (AUC, 0.724; 95% confidence interval [CI], 0.684 to 0.765), the DNN model (AUC, 0.760; 95% CI, 0.724 to 0.795) demonstrated significantly improved performance with respect to the prediction of ACRN (p < 0.001). At a sensitivity of 90%, the specificity significantly increased with the application of the DNN model (41.0%) in comparison with the LR model (26.5%) (p < 0.001), indicating that the colonoscopy workload required to detect the same number of ACRNs could be reduced by 20%.

CONCLUSION

The application of DNN to big clinical data could significantly improve the prediction of ACRNs in comparison with the LR model, potentially realizing further customization by utilizing large quantities and various types of biomedical information.

Comparison of multiple statistical models for the development of clinical prediction scores to detect advanced colorectal neoplasms in asymptomatic Thai patients

A good clinical prediction score can help in the risk stratification of patients with colorectal cancer (CRC) undergoing colonoscopy screening. The aim of our study was to compare model performance of binary logistic regression (BLR), polytomous logistic regression (PLR), and classification and regression tree (CART) between the clinical prediction scores of advanced colorectal neoplasia (ACN) in asymptomatic Thai patients.We conducted a cross-sectional study of 1311 asymptomatic Thai patients to develop a clinical prediction model. The possible predictive variables included sex, age, body mass index, family history of CRC in first-degree relatives, smoking, diabetes mellitus, and the fecal immunochemical test in the univariate analysis. Variables with a P value of .1 were included in the multivariable analysis, using the BLR, CART, and PLR models. Model performance, including the area under the receiver operator characteristic curve (AUROC), was compared between the model types.ACN was diagnosed in 53 patients (4.04%). The AUROCs were not significantly different between the BLR and CART models for ACN prediction with an AUROC of 0.774 (95% confidence interval [95% CI]: 0.706-0.842) and 0.765 (95% CI: 0.698-0.832), respectively (P = .712). A significant difference was observed between the PLR and CART models in predicting average to moderate ACN risk with an AUROC of 0.767 (95% CI: 0.695-0.839 vs AUROC 0.675 [95% CI: 0.599-0.751], respectively; P = .009).The BLR and CART models yielded similar accuracies for the prediction of ACN in Thai patients. The PLR model provided higher accuracy for ACN prediction than the CART model.

Deep Neural Network-Based Prediction of the Risk of Advanced Colorectal Neoplasia

Background/Aims

Risk prediction models using a deep neural network (DNN) have not been reported to predict the risk of advanced colorectal neoplasia (ACRN). The aim of this study was to compare DNN models with simple clinical score models to predict the risk of ACRN in colorectal cancer screening.

Methods

Databases of screening colonoscopy from Kangbuk Samsung Hospital (n=121,794) and Kyung Hee University Hospital at Gangdong (n=3,728) were used to develop DNN-based prediction models. Two DNN models, the Asian-Pacific Colorectal Screening (APCS) model and the Korean Colorectal Screening (KCS) model, were developed and compared with two simple score models using logistic regression methods to predict the risk of ACRN. The areas under the receiver operating characteristic curves (AUCs) of the models were compared in internal and external validation databases.

Results

In the internal validation set, the AUCs of DNN model 1 and the APCS score model were 0.713 and 0.662 (p<0.001), respectively, and the AUCs of DNN model 2 and the KCS score model were 0.730 and 0.667 (p<0.001), respectively. However, in the external validation set, the prediction performances were not significantly different between the two DNN models and the corresponding APCS and KCS score models (both p>0.1).

Conclusions

Simple score models for the risk prediction of ACRN are as useful as DNN-based models when input variables are limited. However, further studies on this issue are warranted to predict the risk of ACRN in colorectal cancer screening because DNN-based models are currently under improvement.

Risk prediction rule for advanced neoplasia on screening colonoscopy for average-risk individuals

BACKGROUND

In resource-limited countries, risk stratification can be used to optimize colorectal cancer screening. Few prospective risk prediction models exist for advanced neoplasia (AN) in true average-risk individuals.

AIM

To create and internally validate a risk prediction model for detection of AN in average-risk individuals.

METHODS

Prospective study of asymptomatic individuals undergoing first screening colonoscopy. Detailed characteristics including diet, exercise and medications were collected. Multivariate logistic regression was used to elucidate risk factors for AN (adenoma ≥1 cm, villous histology, high-grade dysplasia or carcinoma). The model was validated through bootstrapping, and discrimination and calibration of the model were assessed.

RESULTS

980 consecutive individuals (51% F; 49% M) were enrolled. Adenoma and AN detection rates were 36.6% (F 29%: M 45%; P < 0.001) and 5.1% (F 3.8%; M 6.5%) respectively. On multivariate analysis, predictors of AN [OR (95%CI)] were age [1.036 (1.00-1.07); P = 0.048], BMI [overweight 2.21 (0.98-5.00); obese 3.54 (1.48-8.50); P = 0.018], smoking [< 40 pack-years 2.01 (1.01-4.01); ≥ 40 pack-years 3.96 (1.86-8.42); P = 0.002], and daily red meat consumption [2.02 (0.92-4.42) P = 0.079]. Nomograms of AN risk were developed in terms of risk factors and age separately for normal, overweight and obese individuals. The model had good discrimination and calibration.

CONCLUSION

The prevalence of adenoma and AN in average-risk Lebanese individuals is similar to the West. Age, smoking, and BMI are important predictors of AN, with obesity being particularly powerful. Though external validation is needed, this model provides an important platform for improved risk-stratification for screening programs in regions where universal screening is not currently employed.

Association of Cardiovascular Risk Assessment with Early Colorectal Neoplasia Detection in Asymptomatic Population: A Systematic Review and Meta-Analysis

Previous studies have shown a strong coexistence of colorectal neoplasia (CRN) and cardiovascular diseases (CVD). This study was aimed to summarize the available evidence on association of CVD risk with early CRN detection in asymptomatic populations. PubMed, Web of Science, and Embase were systematically searched for eligible studies published until Dec 20, 2019. Studies exploring the associations of recommended CVD risk assessment methods (e.g., risk scores, carotid artery plaque, and coronary artery calcium score [CACS]) with risk of CRN were included. Meta-analyses were conducted to determine the overall association of CVD risk with the CRN. A total of 12 studies were finally included. The association of carotid artery plaque with the risk of colorectal adenoma (AD) was weakest (pooled odds ratio [OR)] 1.27, 95% confidence interval [CI), 1.12, 1.45]. Participants with CACS>100 had about 2-fold increased risk of AD than those with CACS=0. The pooled ORs were 3.36 (95% CI, 2.15, 5.27) and 2.30 (95% CI, 1.69, 3.13) for the risk of advanced colorectal neoplasia (AN) and AD, respectively, in participants with Framingham risk score (FRS)>20%, when compared to participants at low risk (FRS<10%). FRS might help identify subgroups at increased risk for AN, but further studies are needed.

Performance of individual and joint risk stratification by an environmental risk score and a genetic risk score in a colorectal cancer screening setting

Early detection of colorectal neoplasms can reduce the disease burden of colorectal cancer by timely intervention of individuals at high risk. Our aim was to evaluate a joint environmental-genetic risk score as a risk stratification tool for early detection of advanced colorectal neoplasm (ACRN). Known environmental risk factors and high-risk genetic loci were summarized into risk scores for ACRN in 1014 eligible participants of a screening study. The performances of single and joint environmental-genetic scores were evaluated with estimates and 95% confidence intervals (CI) of the absolute risk, relative risk and predictive ability using the area under the curve (AUC). Individuals with higher environmental risk scores showed increasing ACRN risk, with 3.1-fold for intermediate risk and 4.8-fold for very high risk, compared to the very low environmental risk group. Similarly, individuals with higher genetic risk scores showed increasing ACRN risk, with 2.2-fold for intermediate risk and 3.5-fold for very high risk, compared to the lowest genetic risk group. Moreover, the joint environmental-genetic score improved the ACRN risk stratification and showed higher predictive values (AUC = 0.64; 95%CI = 0.60-0.67) with substantial difference (p = 0.0002) compared to the single environmental score (0.58; 0.55-0.62). The integration of environmental and genetic factors looks promising for improving targeting individuals at high-risk of colorectal neoplasm. Applications in practical screening programs require optimization with additional genetic and other biomarkers involved in colorectal carcinogenesis.

Head-to-Head Comparison of the Performance of 17 Risk Models for Predicting Presence of Advanced Neoplasms in Colorectal Cancer Screening

OBJECTIVES

Many risk scores have been proposed to predict presence of advanced colorectal neoplasms, but a comprehensive comparison conducted in the same population is sparse. The aim of this study was to evaluate and directly compare the diagnostic performance of published risk prediction models for advanced colorectal neoplasms.

METHODS

Data were drawn from 2 cohorts of subjects undergoing screening colonoscopy in Germany, i.e., KolosSal (n = 16,195) and BliTz (n = 7,444). Absolute risks and relative risks were generated for the presence of at least 1 advanced neoplasm, taking the lowest risk group as the reference group. Performance of risk models was assessed by the area under the receiver operating characteristic curve (AUC) and compared by the net reclassification improvement.

RESULTS

The 2 cohorts included 1,917 (11.8%) and 848 (11.4%) participants with advanced neoplasm, respectively. Absolute risks were mostly between 5% and 10% among participants in the lowest risk group and between 15% and 20% among participants in the highest risk group, and relative risks mostly ranged from 2.0 to 4.0 across the risk models in both cohorts. The AUCs ranged from 0.58 to 0.65 in KolosSal and from 0.57 to 0.61 in BliTz for all risk scores. Compared to models with lower AUC, classification was significantly improved in most models with higher AUC.

DISCUSSION

Risk models for advanced colorectal neoplasms generally yielded modest discriminatory power, despite some variation in performance between models. Future studies should evaluate the performance of these risk models in racially diverse populations and investigate possible extensions, such as combination with polygenic risk scores.

A healthy lifestyle pattern has a protective association with colorectal polyps

BACKGROUND

Colorectal cancer is associated with lifestyle characteristics such as diet, physical inactivity, obesity, and smoking, but these are not incorporated in screening recommendations. Moreover, the joint association of these factors with various colorectal polyps is not established.

METHODS

A case-control study, among consecutive subjects aged 40-70 years, undergoing colonoscopy. Cases with colorectal polyps were compared with controls. Detailed information was gathered regarding polyp histology and anatomic location, demographics, medical history, anthropometrics, and lifestyle. The healthy lifestyle index was estimated as the sum of: non-smoking, maintaining a healthy weight, healthy diet, and physical activity.

RESULTS

A total of 788 participants were included (cases n = 403, controls n = 385). The healthy lifestyle index had a negative association with colorectal polyps (OR = 0.72, 95% CI 0.62-0.85, P < 0.001), both adenomas and serrated polyps (OR = 0.75, 0.64-0.89, and OR = 0.59, 0.44-0.79, respectively), and both proximal and distal adenomas (OR = 0.77, 0.62-0.95, and OR = 0.73, 0.59-0.90, respectively). Adherence to ≥ 2 healthy lifestyle components was strongly related with colorectal polyps (OR = 0.50, 0.34-0.75, P = 0.001). Abstinence from smoking, and a healthy diet were the factors most strongly associated with lower odds of colorectal polyps (OR = 0.58, 0.42-0.79, and OR = 0.61, 0.44-0.85, respectively).

CONCLUSIONS

Adherence to a healthy lifestyle (≥2 healthy lifestyle components) is inversely associated with colorectal polyps, especially serrated and distal polyps, with no dose-response association. Components most strongly associated with lower odds of colorectal polyps were maintaining a healthy diet and abstinence from smoking. Lifestyle-related characteristics may assist in risk stratification and are potential goals for colorectal neoplasia prevention.

Risk Scores for Predicting Advanced Colorectal Neoplasia in the Average-risk Population: A Systematic Review and Meta-analysis

OBJECTIVES

A systematic review and meta-analysis was performed to summarize the available evidence on risk scores for predicting advanced colorectal neoplasia (advanced adenomas and cancer) in average-risk and asymptomatic populations undergoing screening colonoscopy.

METHODS

PubMed, EMBASE, and Web of Science databases were searched up to 28 March 2018. Studies that developed or validated a risk score to predict the risk of advanced colorectal neoplasia were included. Two reviewers independently extracted study characteristics including diagnostic performance indicators and assessed risk of bias and applicability in the included studies. Meta-analyses were conducted to determine the overall discrimination of risk scores evaluated by more than 1 study.

RESULTS

A total of 22 studies including 17 original risk scores were identified. Risk scores included a median number of 5 risk factors. Factors most commonly included were age, sex, family history in first-degree relatives, body mass index and smoking. The area under the receiver operating characteristic curve of risk scores ranged from 0.62 to 0.77 in the individual studies and from 0.61 to 0.70 in the meta-analyses.

CONCLUSIONS

Although the majority of available risk scores had relatively weak discriminatory power, they may be of some use for risk stratification in CRC screening. Rather than developing more risk scores based on environmental risk factors, future research should focus on exploring possibilities of enhancing predictive power by combining risk factor data with novel laboratory matters, such as polygenetic risk scores.

Factors related to colorectal cancer in advanced adenomas and serrated polyps: a further step toward individualized surveillance

AIM

The risk of presenting synchronous or metachronous neoplasm, either adenoma or carcinoma, increases after an initial colonic lesion develops. It is known as tumor multicentricity and constitutes the rationale for surveillance programs. This study was designed to identify the clinical, pathologic, and molecular features related to previous or synchronous colorectal cancer (CRC) in patients with advanced adenomas (AA) or serrated polyps (SP).

PATIENTS AND METHODS

We carried out a prospective analysis of 4143 colonoscopies performed at our medical department between 1 September 2014 and 30 September 2015. Patients with AA/SP associated with previous or synchronous CRC are compared with patients with solitary AA/SP. We also performed immunohistochemical for the mismatch repair proteins in 120 AA or SP, 60 of them related to CRC.

RESULTS

Three-hundred and seventy-nine AA or SP were removed. Among these, 66 (17.3%) were associated with a previous (n=31) or synchronous CRC (n=35). Age older than or equal to 65 years (odds ratio: 1.15, 95% confidence interval: 1.05-1.26, P=0.002) and male sex (odds ratio: 2.13, 95% confidence interval: 1.3-3.49, P=0.003) were found to be independent predictive factors for CRC in patients with AA/SP by multivariate analysis. Only one of the 120 AA/SP available for immunohistochemical testing showed loss of staining and it was not related to CRC.

CONCLUSION

In patients with AA or SP, it is possible to identify a subgroup that is more likely to be associated with CRC and then prone to tumor multicentricity. These results have potential implications for establishing criteria for a more targeted surveillance.

Smoking Habits are Strongly Associated With Colorectal Polyps in a Population-based Case-control Study

GOALS

The goal of this study is to test the association between lifetime smoking habits and colorectal polyps of different classifications.

BACKGROUND

Smoking is an established risk factor for several cancers, including colorectal cancer. However, the association between lifetime smoking habits including intensity, duration, and cessation, and premalignant colorectal polyps is yet to be established.

STUDY

A case-control study among 828 consecutive subjects aged 40 to 70 years, undergoing screening or diagnostic colonoscopy. Exclusion criteria were: medically treated diabetes, colectomy, and belonging to colorectal cancer high risk group. Polyps were stratified according to histology (serrated or adenomatous polyp) and location. All participants underwent anthropometric measurements and a structured medical and lifestyle interview.

RESULTS

Current-smoking was more strongly associated with increased odds for distal rather than proximal polyps [odds ratio (OR), 4.00; 95% confidence interval (CI), 2.40-6.68 and OR, 2.52; 95% CI, 1.46-4.36, respectively], with serrated-polyps rather than adenomas (OR, 6.36; 95% CI, 2.77-14.57 and OR, 3.01; 1.90-4.74, respectively). All levels of smoking intensity (daily cigarettes) were associated with colorectal polyps. A dose-response association was seen between smoking duration and colorectal polyps. Smoking duration of ≥20 years was strongly associated with distal polyps (OR, 4.01; 95% CI, 1.62-9.84), independently of potential confounders, smoking intensity and years since smoking cessation. All associations were stronger for distal serrated polyps.

CONCLUSIONS

Smoking duration is associated with colorectal plyps, independently of other potential confounders, smoking intensity, and cessation. The association is stronger with distal rather than proximal polyps, and with serrated polyps rather than adenomas.

Predicting Likelihood of Surgery Before First Visit in Patients With Back and Lower Extremity Symptoms: A Simple Mathematical Model Based on More Than 8,000 Patients

STUDY DESIGN

Retrospective analysis of prospectively collected data.

OBJECTIVE

To create a data-driven triage system stratifying patients by likelihood of undergoing spinal surgery within 1 year of presentation.

SUMMARY OF BACKGROUND DATA

Low back pain (LBP) and radicular lower extremity (LE) symptoms are common musculoskeletal problems. There is currently no standard data-derived triage process based on information that can be obtained before the initial physician-patient encounter to direct patients to the optimal physician type.

METHODS

We analyzed patient-reported data from 8006 patients with a chief complaint of low back pain and/or LE radicular symptoms who presented to surgeons at a large multidisciplinary spine center between September 1, 2005 and June 30, 2016. Univariate and multivariate analysis identified independent risk factors for undergoing spinal surgery within 1 year of initial visit. A model incorporating these risk factors was created using a random sample of 80% of the total patients in our cohort, and validated on the remaining 20%.

RESULTS

The baseline 1-year surgery rate within our cohort was 39% for all patients and 42% for patients with LE symptoms. Those identified as high likelihood by the center's existing triage process had a surgery rate of 45%. The new triage scoring system proposed in this study was able to identify a high likelihood group in which 58% underwent surgery, which is a 46% higher surgery rate than in nontriaged patients and a 29% improvement from our institution's existing triage system.

CONCLUSION

The data-driven triage model and scoring system derived and validated in this study (Spine Surgery Likelihood-11), significantly improved existing processes in predicting the likelihood of undergoing spinal surgery within 1 year of initial presentation. This triage system will allow centers to more selectively screen for surgical candidates and more effectively direct patients to surgeons or nonoperative spine specialists.

LEVEL OF EVIDENCE

4.

Individualized colorectal cancer screening based on the clinical risk factors: beyond family history of colorectal cancer

BACKGROUND AND AIMS

Individuals without a family history of colorectal cancer (CRC) are screened uniformly despite interpersonal risk. To assess individual risk, we examined the age-specific prevalence of advanced colorectal neoplasia (ACRN) according to clinical risk factors and fecal immunochemical test (FIT) results.

METHODS

Participants without a family history of CRC who underwent screening colonoscopies and FITs were included. Clinical risk factors for ACRN were identified by using a logistic regression model. Point scores were assigned to each associated factor based on a regression coefficient.

RESULTS

A total of 34,658 participants were included. Age, male sex, smoking, and obesity were identified as risk factors. One-, 2-, and 1-point scores were assigned to male sex, smoking, and obesity, respectively. The prevalence of ACRN in individuals with 0, 1, and ≥2 risk score points was 1.4%, 1.6%, and 2.9% among those aged 50 to 51 years and 3.1%, 5.5%, and 7.5% among those aged ≥66 years, respectively. Among FIT-positive individuals, the prevalence of ACRN was 11.0% and 21.2% in those aged between 50 and 51 years and those aged ≥66 years, respectively. Among FIT-negative individuals with ≥2 risk score points, the prevalence of ACRN was 2.5% and 6.0% among those aged 50 to 51 years and those aged ≥66 years, respectively.

CONCLUSION

If the clinical risk score is ≥2 points (persons with smoking history or obese men), early colonoscopy may be recommended, even with no family history of CRC. Additionally, FIT may be an appropriate initial screening modality for average-risk individuals if the clinical risk score is 0 to 1.

Clinical risk stratification model for advanced colorectal neoplasia in persons with negative fecal immunochemical test results

OBJECTIVES

The fecal immunochemical test (FIT) has low sensitivity for detecting advanced colorectal neoplasia (ACRN); thus, a considerable portion of FIT-negative persons may have ACRN. We aimed to develop a risk-scoring model for predicting ACRN in FIT-negative persons.

MATERIALS AND METHODS

We reviewed the records of participants aged ≥40 years who underwent a colonoscopy and FIT during a health check-up. We developed a risk-scoring model for predicting ACRN in FIT-negative persons.

RESULTS

Of 11,873 FIT-negative participants, 255 (2.1%) had ACRN. On the basis of the multivariable logistic regression model, point scores were assigned as follows among FIT-negative persons: age (per year from 40 years old), 1 point; current smoker, 10 points; overweight, 5 points; obese, 7 points; hypertension, 6 points; old cerebrovascular attack (CVA), 15 points. Although the proportion of ACRN in FIT-negative persons increased as risk scores increased (from 0.6% in the group with 0-4 points to 8.1% in the group with 35-39 points), it was significantly lower than that in FIT-positive persons (14.9%). However, there was no statistical difference between the proportion of ACRN in FIT-negative persons with ≥40 points and in FIT-positive persons (10.5% vs. 14.9%, P = 0.321).

CONCLUSIONS

FIT-negative persons may need to undergo screening colonoscopy if they clinically have a high risk of ACRN. The scoring model based on age, smoking habits, overweight or obesity, hypertension, and old CVA may be useful in selecting and prioritizing FIT-negative persons for screening colonoscopy.

Comparison of Colonoscopy Surveillance Outcomes Between Young and Older Colorectal Cancer Patients

BACKGROUND

Young-onset colorectal cancer is uncommon, but the incidence is increasing. Despite several guidelines for colonoscopic surveillance following colorectal cancer resection, there is little consistency regarding the timing and age-adjusted strategies of surveillance colonoscopy after surgery of young-onset colorectal cancer. The aim of this study was to compare the outcomes of surveillance colonoscopy between sporadic colorectal cancer patients with young and older age after curative resection.

METHODS

We retrospectively reviewed 569 colorectal cancer patients who underwent curative resection between January 2006 and December 2010. The primary outcome was comparison of the development of metachronous advanced neoplasia during surveillance colonoscopy between young and older colorectal cancer patients.

RESULTS

There were 95 patients in the young age group and 474 patients in the older age group. The mean time interval from surgery to the development of metachronous advanced neoplasia was 99.2 ± 3.7 months in the young age group and 84.4 ± 2.5 months in the old age group (P = 0.03). In the multivariate analysis, age (OR, 3.56; P = 0.04) and family history of colorectal cancer (OR, 2.66; P = 0.008) were associated with the development of metachronous advanced neoplasia. None of the young patients without both family history of colorectal cancer and high-risk findings at index colonoscopy showed advanced neoplasia during the follow-up period.

CONCLUSIONS

Age and family history of colorectal cancer are independent risk factors for the occurrence of advanced neoplasia after curative colorectal cancer resection, suggesting age-adjusted strategies of surveillance colonoscopy.

Development and validation of a prediction model for adenoma detection during screening and surveillance colonoscopy with comparison to actual adenoma detection rates

OBJECTIVE

The adenoma detection rate (ADR) varies widely between physicians, possibly due to patient population differences, hampering direct ADR comparison. We developed and validated a prediction model for adenoma detection in an effort to determine if physicians' ADRs should be adjusted for patient-related factors.

MATERIALS AND METHODS

Screening and surveillance colonoscopy data from the cross-sectional multicenter cluster-randomized Endoscopic Quality Improvement Program-3 (EQUIP-3) study (NCT02325635) was used. The dataset was split into two cohorts based on center. A prediction model for detection of ≥1 adenoma was developed using multivariable logistic regression and subsequently internally (bootstrap resampling) and geographically validated. We compared predicted to observed ADRs.

RESULTS

The derivation (5 centers, 35 physicians, overall-ADR: 36%) and validation (4 centers, 31 physicians, overall-ADR: 40%) cohort included respectively 9934 and 10034 patients (both cohorts: 48% male, median age 60 years). Independent predictors for detection of ≥1 adenoma were: age (optimism-corrected odds ratio (OR): 1.02; 95%-confidence interval (CI): 1.02-1.03), male sex (OR: 1.73; 95%-CI: 1.60-1.88), body mass index (OR: 1.02; 95%-CI: 1.01-1.03), American Society of Anesthesiology physical status class (OR class II vs. I: 1.29; 95%-CI: 1.17-1.43, OR class ≥III vs. I: 1.57; 95%-CI: 1.32-1.86), surveillance versus screening (OR: 1.39; 95%-CI: 1.27-1.53), and Hispanic or Latino ethnicity (OR: 1.13; 95%-CI: 1.00-1.27). The model's discriminative ability was modest (C-statistic in the derivation: 0.63 and validation cohort: 0.60). The observed ADR was considerably lower than predicted for 12/66 (18.2%) physicians and 2/9 (22.2%) centers, and considerably higher than predicted for 18/66 (27.3%) physicians and 4/9 (44.4%) centers.

CONCLUSION

The substantial variation in ADRs could only partially be explained by patient-related factors. These data suggest that ADR variation could likely also be due to other factors, e.g. physician or technical issues.

Impact of Age on the Risk of Advanced Colorectal Neoplasia in a Young Population: An Analysis Using the Predicted Probability Model

BACKGROUND

The incidence of colorectal cancer is decreasing in adults aged ≥50 years and increasing in those aged <50 years.

AIMS

We aimed to establish risk stratification model for advanced colorectal neoplasia (ACRN) in persons aged <50 years.

METHODS

We reviewed the records of participants who had undergone a colonoscopy as part of a health examination at two large medical examination centers in Korea. By using logistic regression analysis, we developed predicted probability models for ACRN in a population aged 30-49 years.

RESULTS

Of 96,235 participants, 57,635 and 38,600 were included in the derivation and validation cohorts, respectively. The predicted probability model considered age, sex, body mass index, family history of colorectal cancer, and smoking habits, as follows: Y _ACRN = -8.755 + 0.080·X _age - 0.055·X _male + 0.041·X _BMI + 0.200·X _{family_history_of_CRC} + 0.218·X _{former_smoker} + 0.644·X _{current_smoker}. The optimal cutoff value for the predicted probability of ACRN by Youden index was 1.14%. The area under the receiver-operating characteristic curve (AUROC) values of our model for ACRN were higher than those of the previously established Asia-Pacific Colorectal Screening (APCS), Korean Colorectal Screening (KCS), and Kaminski's scoring models [AUROC (95% confidence interval): model in the current study, 0.673 (0.648-0.697); vs. APCS, 0.588 (0.564-0.611), P < 0.001; vs. KCS, 0.602 (0.576-0.627), P < 0.001; and vs. Kaminski's model, 0.586 (0.560-0.612), P < 0.001].

CONCLUSION

In a young population, a predicted probability model can assess the risk of ACRN more accurately than existing models, including the APCS, KCS, and Kaminski's scoring models.

A prediction model for advanced colorectal neoplasia in an asymptomatic screening population

Background

An electronic medical record (EMR) database of a large unselected population who received screening colonoscopies may minimize sampling error and represent real-world estimates of risk for screening target lesions of advanced colorectal neoplasia (CRN). Our aim was to develop and validate a prediction model for assessing the probability of advanced CRN using a clinical data warehouse.

Methods

A total of 49,450 screenees underwent their first colonoscopy as part of a health check-up from 2002 to 2012 at Samsung Medical Center, and the dataset was constructed by means of natural language processing from the computerized EMR system. The screenees were randomized into training and validation sets. The prediction model was developed using logistic regression. The model performance was validated and compared with existing models using area under receiver operating curve (AUC) analysis.

Results

In the training set, age, gender, smoking duration, drinking frequency, and aspirin use were identified as independent predictors for advanced CRN (adjusted P < .01). The developed model had good discrimination (AUC = 0.726) and was internally validated (AUC = 0.713). The high-risk group had a 3.7-fold increased risk of advanced CRN compared to the low-risk group (1.1% vs. 4.0%, P < .001). The discrimination performance of the present model for high-risk patients with advanced CRN was better than that of the Asia-Pacific Colorectal Screening score (AUC = 0.678, P < .001) and Schroy’s CAN index (AUC = 0.672, P < .001).

Conclusion

The present 5-item risk model can be calculated readily using a simple questionnaire and can identify the low- and high-risk groups of advanced CRN at the first screening colonoscopy. This model may increase colorectal cancer risk awareness and assist healthcare providers in encouraging the high-risk group to undergo a colonoscopy.

Obesity Increases Prevalence of Colonic Adenomas at Screening Colonoscopy: A Canadian Community-Based Study

BACKGROUND AND AIMS

Obesity is a risk factor for colorectal neoplasia. We examined the influence of obesity and metabolic syndrome (MetS) on prevalence of neoplasia at screening colonoscopy.

METHODS

We evaluated 2020 subjects undergoing first screening colonoscopy. Body mass index (BMI) was calculated at enrolment. Hyperlipidemia (HL), hypertension (HT), and diabetes mellitus (DM) were identified. Details of colonoscopy, polypectomy, and histology were recorded. Odds for adenomas (A) and advanced adenomas (ADV) in overweight (BMI 25.1-30) and obese (BMI > 30) subjects were assessed by multinomial regression, adjusted for covariates. Analyses included relationships between HL, HT, DM, age, tobacco usage, and neoplasia. Discriminatory power of HT, HL, DM, and BMI for neoplasia was assessed by binary logistic regression. Odds were calculated for neoplasia in each colonic segment related to BMI.

RESULTS

A and ADV were commoner in overweight and obese males, obese females, older subjects, and smokers. HL, HT, and DM were associated with increased odds for neoplasia, significantly for A with hypertension. BMI alone predicted neoplasia as well as HT, HL, DM, or combinations thereof. All segments of the colon were affected. Multiple polyps were particularly prevalent in the obese.

CONCLUSIONS

Obesity and MetS are risk factors for colonic neoplasia in a Canadian population.

A New Scoring System to Predict the Risk for High-risk Adenoma and Comparison of Existing Risk Calculators

BACKGROUND

Colorectal cancer (CRC) screening guidelines likely over-generalizes CRC risk, 35% of Americans are not up to date with screening, and there is growing incidence of CRC in younger patients.

GOALS

We developed a practical prediction model for high-risk colon adenomas in an average-risk population, including an expanded definition of high-risk polyps (≥3 nonadvanced adenomas), exposing higher than average-risk patients. We also compared results with previously created calculators.

STUDY

Patients aged 40 to 59 years, undergoing first-time average-risk screening or diagnostic colonoscopies were evaluated. Risk calculators for advanced adenomas and high-risk adenomas were created based on age, body mass index, sex, race, and smoking history. Previously established calculators with similar risk factors were selected for comparison of concordance statistic (c-statistic) and external validation.

RESULTS

A total of 5063 patients were included. Advanced adenomas, and high-risk adenomas were seen in 5.7% and 7.4% of the patient population, respectively. The c-statistic for our calculator was 0.639 for the prediction of advanced adenomas, and 0.650 for high-risk adenomas. When applied to our population, all previous models had lower c-statistic results although one performed similarly.

CONCLUSIONS

Our model compares favorably to previously established prediction models. Age and body mass index were used as continuous variables, likely improving the c-statistic. It also reports absolute predictive probabilities of advanced and high-risk polyps, allowing for more individualized risk assessment of CRC.

High-Density Lipoprotein Cholesterol, Blood Urea Nitrogen, and Serum Creatinine Can Predict Severe Acute Pancreatitis

BACKGROUND AND AIMS

Early prediction of disease severity of acute pancreatitis (AP) would be helpful for triaging patients to the appropriate level of care and intervention. The aim of the study was to develop a model able to predict Severe Acute Pancreatitis (SAP).

METHODS

A total of 647 patients with AP were enrolled. The demographic data, hematocrit, High-Density Lipoprotein Cholesterol (HDL-C) determinant at time of admission, Blood Urea Nitrogen (BUN), and serum creatinine (Scr) determinant at time of admission and 24 hrs after hospitalization were collected and analyzed statistically.

RESULTS

Multivariate logistic regression indicated that HDL-C at admission and BUN and Scr at 24 hours (hrs) were independently associated with SAP. A logistic regression function (LR model) was developed to predict SAP as follows: -2.25-0.06 HDL-C (mg/dl) at admission + 0.06 BUN (mg/dl) at 24 hours + 0.66 Scr (mg/dl) at 24 hours. The optimism-corrected c-index for LR model was 0.832 after bootstrap validation. The area under the receiver operating characteristic curve for LR model for the prediction of SAP was 0.84.

CONCLUSIONS

The LR model consists of HDL-C at admission and BUN and Scr at 24 hours, representing an additional tool to stratify patients at risk of SAP.

Serum Albumin Is Independently Associated with Persistent Organ Failure in Acute Pancreatitis

BACKGROUND AND AIMS

To investigate the association between serum albumin levels within 24 hrs of patient admission and the development of persistent organ failure in acute pancreatitis.

METHODS

A total of 700 patients with acute pancreatitis were enrolled. Multivariate logistic regression and subgroup analysis determined whether decreased albumin was independently associated with persistent organ failure and mortality. The diagnostic performance of serum albumin was evaluated by the area under Receiver Operating Characteristic (ROC) curves.

RESULTS

As levels of serum albumin decrease, the risk of persistent organ failure significantly increases (P_trend < 0.001). The incidence of organ failure was 3.5%, 10.6%, and 41.6% in patients with normal albumin and mild and severe hypoalbuminaemia, respectively. Decreased albumin levels were also proportionally associated with prolonged hospital stay (P_trend < 0.001) and the risk of death (P_trend < 0.001). Multivariate analysis suggested that biliary etiology, chronic concomitant diseases, hematocrit, blood urea nitrogen, and the serum albumin level were independently associated with persistent organ failure. Blood urea nitrogen and the serum albumin level were also independently associated with mortality. The area under ROC curves of albumin for predicting organ failure and mortality were 0.78 and 0.87, respectively.

CONCLUSION

A low serum albumin is independently associated with an increased risk of developing of persistent organ failure and death in acute pancreatitis. It may also be useful for the prediction of the severity of acute pancreatitis.

Prediction model and risk score for perforation in patients undergoing colorectal endoscopic submucosal dissection

BACKGROUND AND AIMS

Perforation is the adverse event of greatest concern during colorectal endoscopic submucosal dissection (ESD). Accurate risk prediction of perforation may enable prevention strategies and selection of the most efficient therapeutic option. This study aimed to develop and validate a risk prediction model for ESD-induced perforation.

METHODS

A multicenter cross-sectional study was performed on 2046 patients who underwent colorectal ESD at 9 Korean ESD Study Group-affiliated hospitals. The enrolled patients were randomly divided into either a derivation set or a validation set. In the derivation set, a prediction score was constructed to assess the risk of perforation using preoperative and procedural-related predictors selected via logistic regression. Discrimination and calibration of the prediction model was assessed using the validation set.

RESULTS

An ESD-induced perforation occurred in 135 patients (6.6%). In the derivation set, multivariate logistic regression identified endoscopist experience (≥50 ESDs: odds ratio [OR] = 0.59; 95% confidence interval [CI], 0.35-1.00), tumor size (+1-cm increments: OR = 1.39; 95% CI, 1.19-1.62), colonic location (OR = 2.20; 95% CI, 1.24-3.89), and submucosal fibrosis (OR = 2.00; 95% CI, 1.04-3.87) as predictive factors (C-statistic = 0.678; 95% CI, 0.617-0.739). In the validation set, the model showed good discrimination (C-statistic = 0.675; 95% CI, 0.615-0.735) and calibration (P = .635). When a simplified weighted scoring system based on the OR was used, risk of perforation ranged from 4.1% (95% CI, 2.8%-5.9%) in the low-risk group (score ≤4) to 11.6% (95% CI, 8.5%-15.6%) in the high-risk group (score >4).

CONCLUSIONS

This study developed and internally validated a score consisting of simple clinical factors to estimate the risk of colorectal ESD-induced perforation. This score can be used to identify patients at high risk before colorectal ESD.

Risk Stratification and Shared Decision Making for Colorectal Cancer Screening: A Randomized Controlled Trial

BACKGROUND

Eliciting patient preferences within the context of shared decision making has been advocated for colorectal cancer (CRC) screening, yet providers often fail to comply with patient preferences that differ from their own.

PURPOSE

To determine whether risk stratification for advanced colorectal neoplasia (ACN) influences provider willingness to comply with patient preferences when selecting a desired CRC screening option.

DESIGN

Randomized controlled trial.

SETTING/PARTICIPANTS

Asymptomatic, average-risk patients due for CRC screening in an urban safety net health care setting.

INTERVENTION

Patients were randomized 1:1 to a decision aid alone (n= 168) or decision aid plus risk assessment (n= 173) arm between September 2012 and September 2014.

OUTCOMES

The primary outcome was concordance between patient preference and test ordered; secondary outcomes included patient satisfaction with the decision-making process, screening intentions, test completion rates, and provider satisfaction.

RESULTS

Although providers perceived risk stratification to be useful in selecting an appropriate screening test for their average-risk patients, no significant differences in concordance were observed between the decision aid alone and decision aid plus risk assessment groups (88.1% v. 85.0%,P= 0.40) or high- and low-risk groups (84.5% v. 87.1%,P= 0.51). Concordance was highest for colonoscopy and relatively low for tests other than colonoscopy, regardless of study arm or risk group. Failure to comply with patient preferences was negatively associated with satisfaction with the decision-making process, screening intentions, and test completion rates.

LIMITATIONS

Single-institution setting; lack of provider education about the utility of risk stratification into their decision making.

CONCLUSIONS

Providers perceived risk stratification to be useful in their decision making but often failed to comply with patient preferences for tests other than colonoscopy, even among those deemed to be at low risk of ACN.