10-Year risk of colorectal cancer: development and validation of a prediction model in middle-aged Japanese men

Prognostic impact of subcutaneous fat quality and sarcopenia on the survival outcomes in patients with colorectal cancer

PURPOSE

This study aimed to evaluate the relationship between the quantity and quality of subcutaneous fat and prognosis following colorectal cancer resection.

METHOD

We conducted a retrospective analysis of the clinical data of 399 patients who underwent curative resection for stage 2 or 3 colorectal cancer between January 2013 and March 2019. This study examined the correlation between sarcopenia and various fat parameters, including fat area and density, and assessed their impact on the prognosis.

RESULTS

Sarcopenia was associated with a lower subcutaneous and visceral fat area, higher Hounsfield unit value in subcutaneous fat, and reduced modified intramuscular adipose tissue content in the multifidus, erector spinae, and psoas muscles. A low modified intramuscular adipose tissue content in the multifidus and erector spinae muscles was an independent prognostic factor for overall survival (hazard ratio, 2.28; p = 0.0329) and recurrence-free survival (hazard ratio: 2.32, p = 0.0233). Additionally, subcutaneous fat with a high Hounsfield unit was an independent predictor of a recurrence-free survival (hazard ratio, 2.68; p = 0.0142).

CONCLUSION

Subcutaneous fat quality is correlated with sarcopenia and it thus serves as a prognostic factor for recurrence after stage 2 or 3 colorectal cancer resection.

Association between metabolic syndrome and the risk of colorectal cancer: a prospective study in China

OBJECTIVE

To evaluate the correlation between metabolic syndrome (MetS) and its components on the incidence of colorectal cancer (CRC) based on data from Jinchang Cohort.

METHODS

This is a large prospective cohort study. Between 2011 and 2020, a total of 43 516 individuals from Jinchang Cohort were included for this study. Hazard ratios (HRs) with 95% confidence intervals (CIs) for CRC according to MetS were calculated with the Cox proportional hazard models. The restricted cubic spine models with four knots were conducted to fit the dose-response relationships.

RESULTS

MetS was associated with increased risk of CRC (n = 141; HR: 1.64, 95% CI: 1.15-2.33) after adjusting for confounding factors (age, sex, education level, family history of CRC, smoking index and alcohol index). Participants with hyperglycemia had a significantly higher risk of developing incident CRC (HR: 1.70; 95% CI: 1.19-2.43). The positive association between MetS and CRC was observed in males (HR: 1.76; 95% CI: 1.17-2.63), but not in females (HR: 1.24; 95% CI: 0.59-2.64). Furthermore, linear dose-response relationship was found between fasting plasma glucose (FPG) and CRC risk in males ( Poverall < 0.05, Pnon-linear = 0.35). When stratified by smoke and drink, MetS was found to increase the incidence of CRC only in the smoke (HR: 2.07, 95% CI: 1.35-3.18) and drink (HR: 2.93, 95% CI: 1.51-5.69) groups.

CONCLUSION

MetS was associated with a higher risk of CRC incidence. Hyperglycemia lended strong support to the role of MetS in new-onset CRC, especially in males. Other components of MetS were not found to be associated with increased risk of CRC.

Lifestyle predictors of colorectal cancer in European populations: a systematic review

Background

Colorectal cancer (CRC) is the second most prevalent cancer in Europe, with one-fifth of cases attributable to unhealthy lifestyles. Risk prediction models for quantifying CRC risk and identifying high-risk groups have been developed or validated across European populations, some considering lifestyle as a predictor.

Purpose

To identify lifestyle predictors considered in existing risk prediction models applicable for European populations and characterise their corresponding parameter values for an improved understanding of their relative contribution to prediction across different models.

Methods

A systematic review was conducted in PubMed and Web of Science from January 2000 to August 2021. Risk prediction models were included if (1) developed and/or validated in an adult asymptomatic European population, (2) based on non-invasively measured predictors and (3) reported mean estimates and uncertainty for predictors included. To facilitate comparison, model-specific lifestyle predictors were visualised using forest plots.

Results

A total of 21 risk prediction models for CRC (reported in 16 studies) were eligible, of which 11 were validated in a European adult population but developed elsewhere, mostly USA. All models but two reported at least one lifestyle factor as predictor. Of the lifestyle factors, the most common predictors were body mass index (BMI) and smoking (each present in 13 models), followed by alcohol (11), and physical activity (7), while diet-related factors were less considered with the most commonly present meat (9), vegetables (5) or dairy (2). The independent predictive contribution was generally greater when they were collected with greater detail, although a noticeable variation in effect size estimates for BMI, smoking and alcohol.

Conclusions

Early identification of high-risk groups based on lifestyle data offers the potential to encourage participation in lifestyle change and screening programmes, hence reduce CRC burden. We propose the commonly shared lifestyle predictors to be further used in public health prediction modelling for improved uptake of the model.

An adjusted Asia-Pacific colorectal screening score system to predict advanced colorectal neoplasia in asymptomatic Chinese patients

PURPOSE

The Asia-Pacific Colorectal Screening (APCS) score and its derivatives have been used to predict advanced colorectal neoplasia (ACN). However, it remains unknown whether they apply to the current Chinese population in general clinical practice. Therefore, we aimed to update the APCS score system by applying data from two independent asymptomatic populations to predict the risk of ACN in China.

METHODS

We developed an adjusted APCS (A-APCS) score by using the data of asymptomatic Chinese patients undergoing colonoscopies from January 2014 to December 2018. Furthermore, we validated this system in another cohort of 812 patients who underwent screening colonoscopy between January and December 2021. The discriminative calibration ability of the A-APCS and APCS scores was comparatively evaluated.

RESULTS

Univariate and multivariate logistic regression were applied to assess the risk factors for ACN, and an adjusted scoring system of 0 to 6.5 points was schemed according to the results. Utilizing the developed score, 20.2%, 41.2%, and 38.6% of patients in the validation cohort were classified as average, moderate, and high risk, respectively. The corresponding ACN incidence rates were 1.2%, 6.0%, and 11.1%, respectively. In addition, the A-APCS score (c-statistics: 0.68 for the derivation and 0.80 for the validation cohort) showed better discriminative power than using predictors of APCS alone.

CONCLUSIONS

The A-APCS score may be simple and useful in clinical applications for predicting ACN risk in China.

External validation of models for predicting risk of colorectal cancer using the China Kadoorie Biobank

BACKGROUND

In China, colorectal cancer (CRC) incidence and mortality have been steadily increasing over the last decades. Risk models to predict incident CRC have been developed in various populations, but they have not been systematically externally validated in a Chinese population.  This study aimed to assess the performance of risk scores in predicting CRC using the China Kadoorie Biobank (CKB), one of the largest and geographically diverse prospective cohort studies in China.

METHODS

Nine models were externally validated in 512,415 participants in CKB and included 2976 cases of CRC. Model discrimination was assessed, overall and by sex, age, site, and geographic location, using the area under the receiver operating characteristic curve (AUC). Model discrimination of these nine models was compared to a model using age alone. Calibration was assessed for five models, and they were re-calibrated in CKB.

RESULTS

The three models with the highest discrimination (Ma (Cox model) AUC 0.70 [95% CI 0.69-0.71]; Aleksandrova 0.70 [0.69-0.71]; Hong 0.69 [0.67-0.71]) included the variables age, smoking, and alcohol. These models performed significantly better than using a model based on age alone (AUC of 0.65 [95% CI 0.64-0.66]). Model discrimination was generally higher in younger participants, males, urban environments, and for colon cancer. The two models (Guo and Chen) developed in Chinese populations did not perform better than the others. Among the 10% of participants with the highest risk, the three best performing models identified 24-26% of participants that went on to develop CRC.

CONCLUSIONS

Several risk models based on easily obtainable demographic and modifiable lifestyle factor have good discrimination in a Chinese population. The three best performing models have a higher discrimination than using a model based on age alone.

Five-year absolute risk estimates of colorectal cancer based on CCRAT model and polygenic risk scores: A validation study using the Quebec population-based cohort CARTaGENE

The objective was to evaluate the predictive performance of the Colorectal Cancer Risk Assessment Tool (CCRAT) and three polygenic risk scores (Hsu et al., 2015; Law et al., 2019, Archambault et al., 2020) to predict the occurrence of colorectal cancer at five years in a Quebec population-based cohort. By using the CARTaGENE cohort, we computed the absolute risk of colorectal cancer with the CCRAT model, the polygenic risk scores (PRS) and combined clinico-genetic models (CCRAT + PRS). We also tailored the CCRAT model by using the marginal age-specific colorectal incidence rates in Canada and the risk score distribution. We reported the calibration and the discrimination. Performances of the PRSs, combined and tailored CCRAT models were compared to the original CCRAT model. The expected-to-observed ratio of the original CCRAT model was 0.54 [0.43-0.68]. The c-index was 74.79 [68.3-80.5]. The tailored CCRAT model improved the expected-to-observed ratio (0.74 [0.59-0.94]) and c-index (76.39 [69.7-82.1]). All PRS improved the expected-to-observed ratios (around 0.83, confidence intervals including one). PRSs' c-indexes were not significantly different from CCRAT models. Results from the combined models were close to those from the PRS models, Archambault combined model's c-index being significantly higher than the original and tailored CCRAT models (78.67 [70.8-86.5]; p < 0.001 and p = 0.028, respectively). In this Quebec cohort, CCRAT model has a good discrimination with a poor calibration. While the tailored CCRAT provides some gain in calibration, clinico-genetic models improved both calibration and discrimination. However, better calibrations must be obtained before a practical use among the inhabitants of Quebec province.

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.

A user-friendly objective prediction model in predicting colorectal cancer based on 234 044 Asian adults in a prospective cohort

BACKGROUND

Prediction models of colorectal cancer (CRC) had limited application for not being user-friendly. Whether fecal immunochemical tests (FITs) can help predict CRC has been overlooked.

PATIENTS AND METHODS

With 1972 CRCs identified, 234 044 adults aged ≥40 years were successively enrolled between 1994 and 2008. Prediction models were developed by questionnaire/medical screening and quantitative FIT. NNS (number needed to scope to find one cancer) is time dependent, spanning entire study period. Significant 'risk factors' were family history, body mass index, smoking, drinking, inactivity, hypertension, diabetes, carcinoembryonic antigen, and C-reactive protein.

RESULTS

Positive FIT (≥20 μg/g hemoglobin/feces) had cancer risk 10-fold larger than negative FIT, and within each age group, another 10-fold difference. The C statistic of FIT (0.81) with age and sex alone was superior to the 'common risk-factors' model (0.73). NNS, stratified by age and by FIT values, demonstrated a scorecard of cancer risks, like 1/15 or 1/25, in 5 years. When FIT was negative, cancer risk was small (1/750-1/3000 annually). The larger the FIT, the sooner the appearance of CRC. For every 80-μg/g increase of FIT, there were 1.5-year earlier development of CRC incidence and 1-year earlier development of CRC mortality, respectively. Given the same FIT value, CRC events appeared in the proximal colon sooner than the distal colon.

CONCLUSIONS

A simple user-friendly model based on a single FIT value to predict CRC risk was developed. When positive, NNS offered a simple quantitative value, with a better precision than most risk factors, even combined. When FIT is negative, risk is very small, but requiring a repeat every other year to rule out false negative. FIT values correlated well with CRC prognosis, with worst for proximal CRC.

Untreated Hypertension and Subsequent Incidence of Colorectal Cancer: Analysis of a Nationwide Epidemiological Database

Background

Studies of the association of hypertension with incident colorectal cancer (CRC) may have been confounded by including individuals taking antihypertensive medication, at high risk for CRC (ie, colorectal polyps and inflammatory bowel disease), or with shared risk factors (eg, obesity and diabetes). We assessed whether adults with untreated hypertension are at higher risk for incident CRC compared with those with normal blood pressure (BP), and whether any association is evident among individuals without obesity or metabolic abnormalities.

Methods and Results

Analyses were conducted using a nationwide health claims database collected in the JMDC Claims Database between 2005 and 2018 (n=2 220 112; mean age, 44.1±11.0 years; 58.4% men). Participants who were taking antihypertensive medications or had a history of CRC, colorectal polyps, or inflammatory bowel disease were excluded. Each participant was categorized as having normal BP (systolic BP [SBP]<120 mm Hg and diastolic BP [DBP] <80 mm Hg, n=1 164 807), elevated BP (SBP 120–129 mm Hg and DBP <80 mm Hg, n=341 273), stage 1 hypertension (SBP 130–139 mm Hg or DBP 80–89 mm Hg, n=466 298), or stage 2 hypertension (SBP ≥140 mm Hg or DBP ≥90 mm Hg, n=247 734). Over a mean follow‐up of 1112±854 days, 6899 incident CRC diagnoses occurred. After multivariable adjustment, compared with normal BP, hazard ratios for incident CRC were 0.93 (95% CI, 0.85–1.01) for elevated BP, 1.07 (95% CI, 0.99–1.15) for stage 1 hypertension, and 1.17 (95% CI, 1.08–1.28) for stage 2 hypertension. The hazard ratios for incident CRC for each 10‐mm Hg‐higher SBP or DBP were 1.04 (95% CI, 1.02–1.06) and 1.06 (95% CI, 1.03–1.09), respectively. These associations were present among adults who did not have obesity, high waist circumference, diabetes, or dyslipidemia.

Conclusions

Higher SBP and DBP, and stage 2 hypertension are associated with a higher risk for incident CRC, even among those without shared risk factors for CRC. BP measurement could identify individuals at increased risk for subsequent CRC.

Fasting Plasma Glucose and Incident Colorectal Cancer: Analysis of a Nationwide Epidemiological Database

CONTEXT

Although diabetes mellitus (DM) was reported to be associated with incident colorectal cancer (CRC), the detailed association between fasting plasma glucose (FPG) and incident CRC has not been fully understood.

OBJECTIVE

We assessed whether hyperglycemia is associated with a higher risk for CRC.

DESIGN

Analyses were conducted using the JMDC Claims Database [n = 1 441 311; median age (interquartile range), 46 (40-54) years; 56.6% men). None of the participants were taking antidiabetic medication or had a history of CRC, colorectal polyps, or inflammatory bowel disease. Participants were categorized as normal FPG (FPG level < 100 mg/dL; 1 125 647 individuals), normal-high FPG (FPG level = 100-109 mg/dL; 210 365 individuals), impaired fasting glucose (IFG; FPG level = 110-125 mg/dL; 74 836 individuals), and DM (FPG level ≥ 126 mg/dL; 30 463 individuals).

RESULTS

Over a mean follow-up of 1137 ± 824 days, 5566 CRC events occurred. After multivariable adjustment, the hazard ratios for CRC events were 1.10 (95% CI 1.03-1.18) for normal-high FPG, 1.24 (95% CI 1.13-1.37) for IFG, and 1.36 (95% CI 1.19-1.55) for DM vs normal FPG. We confirmed this association in sensitivity analyses excluding those with a follow-up of< 365 days and obese participants.

CONCLUSION

The risk of CRC increased with elevated FPG category. FPG measurements would help to identify people at high-risk for future CRC.

Risk Factors for High-Risk Adenoma on the First Lifetime Colonoscopy Using Decision Tree Method: A Cross-Sectional Study in 6,047 Asymptomatic Koreans

Background/Aims: As risk of colorectal neoplasm is varied even in persons with “average-risk,” risk evaluation and tailored screening are needed. This study aimed to evaluate the risk factors of high-risk adenoma (HRA) in healthy individuals and determine the characteristics of advanced neoplasia (AN) among individual polyps.

Methods: Asymptomatic adults who underwent the first lifetime screening colonoscopy at the Seoul National University Hospital Healthcare System Gangnam Center (SNUH GC) were recruited from 2004 to 2007 as SNUH GC Cohort and were followed for 10 years. Demographic and clinical characteristics were compared between the subjects with and without AN (≥10 mm in size, villous component, and/or high-grade dysplasia and/or cancer) or HRA (AN and/or 3 or more adenomas). For individual polyps, correlations between clinical or endoscopic features and histologic grades were evaluated using a decision tree method.

Results: A total of 6,047 subjects were included and 5,621 polyps were found in 2,604 (43%) subjects. Advanced age, male sex, and current smoking status were statistically significant with regards to AN and HRA. A lower incidence of AN was observed in subjects taking aspirin. In the decision tree model, the location, shape, and size of the polyp, and sex of the subject were key predictors of the pathologic type. A weak but significant association was observed between the prediction of the final tree and the histological grouping (Kendall's tau-c = 0.142, p < 0001).

Conclusions: Advanced neoplasia and HRA can be predicted using several individual characteristics and decision tree models.

Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case-Control Study

Objective

To identify people with high-risk early colorectal neoplasm is highly desirable for pre-selection in colorectal cancer (CRC) screening in low-resource countries. We aim to build and validate a risk-based model so as to improve compliance and increase the benefits of screening.

Patients and Methods

Using data from the Shanghai CRC screening cohort, we conducted a population-based nested case–control study to build a risk-based model. Cases of early colorectal neoplasm were extracted as colorectal adenomas and stage 0-I CRC. Each case was matched with five individuals without neoplasm (controls) by the screening site and year of enrollment. Cases and controls were then randomly divided into two groups, with two thirds for building the risk prediction model and the other one third for model validation. Known risk factors were included for risk prediction models using logistic regressions. The area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow chi-square statistics were used to evaluate model discrimination and calibration. The predicted individual risk probability was calculated under the risk regression equation.

Results

The model incorporating age, sex, family history and lifestyle factors including body mass index (BMI), smoking status, alcohol, regular moderate-to-intensity physical activity showed good calibration and discrimination. When the risk cutoff threshold was defined as 17%, the sensitivity and specificity of the model were 63.99% and 53.82%, respectively. The validation data analysis also showed well discrimination.

Conclusion

A risk prediction model combining personal and lifestyle factors was developed and validated for high-risk early colorectal neoplasm among the Chinese population. This risk-based model could improve the pre-selection for screening and contribute a lot to efficient population-based screening in low-resource countries.

Inclusion of a gene-environment interaction between alcohol consumption and the aldehyde dehydrogenase 2 genotype in a risk prediction model for upper aerodigestive tract cancer in Japanese men

The well-known gene-environment interaction between alcohol consumption and aldehyde dehydrogenase 2 (ALDH2) genotype in upper aerodigestive tract cancer risk may improve our ability to identify high-risk subjects. Here, we developed and validated risk prediction models for this cancer in Japanese men and evaluated whether adding the gene-environment interaction to the model improved the predictive performance. We developed two case-cohort datasets in the Japan Public Health Center-based Prospective Study: one from subjects in the baseline survey for model development (108 cases and 4049 subcohort subjects) and the second from subjects in the 5-year follow-up survey for model validation (31 cases and 1527 subcohort subjects). We developed an environmental model including age, smoking status, and alcohol consumption, and a gene-environment interaction model including age, smoking status, and the combination of alcohol consumption and the ALDH2 genotype. We found a statistically significant gene-environment interaction for alcohol consumption and the ALDH2 genotype. The c-index for the gene-environment interaction model (0.71) was slightly higher than that for the environmental model (0.67). The values of integrated discrimination improvement and net reclassification improvement for the gene-environment interaction model were also slightly higher than those for the environmental model. Goodness-of-fit tests suggested that the models were well calibrated. Results from external model validation by the 5-year follow-up survey were consistent with those from the model development by the baseline survey. The addition of a gene-environment interaction to a lifestyle-based model might improve the performance to estimate the probability of developing upper aerodigestive tract cancer for Japanese men.

A Preoperative Risk Prediction Model for Lymph Node Examination of Stage I-III Colon Cancer Patients: A Population-Based Study

Background: Lymph node examination is a prognostic indicator for colon cancer (CC) patients. The aim of this study was to develop and validate a preoperative risk prediction model for inadequate lymph node examination. Methods: 24284 patients diagnosed as stage I-III CC between 2010-2014 were extracted from SEER database and randomly divided into development cohort (N=12142) and internal validation cohort (N=12142). 680 patients diagnosed as stage I-III CC between 2012-2014 were extracted from our hospital as external validation cohort. Logistic regression analysis was performed and risk score of each factor was calculated according to model formula. Model discrimination was assessed using C-statistics. Results: Preoperative risk factors were identified as gender, age, tumor site and tumor size. Patients with total risk score of 0-6 were considered as low risk group while patients scored ≥13 were considered as high risk group. The model had good discrimination and calibration in all cohorts and could apply to patients in the SEER database (American population) and patients in our hospital (Chinese population). Conclusions: The model could accurately predict the risk of inadequate lymph node examination before surgery and might provide useful reference for surgeons and pathologists.

Data mining-based model and risk prediction of colorectal cancer by using secondary health data: A systematic review

OBJECTIVE

Prevention and early detection of colorectal cancer (CRC) can increase the chances of successful treatment and reduce burden. Various data mining technologies have been utilized to strengthen the early detection of CRC in primary care. Evidence synthesis on the model's effectiveness is scant. This systematic review synthesizes studies that examine the effect of data mining on improving risk prediction of CRC.

METHODS

The PRISMA framework guided the conduct of this study. We obtained papers via PubMed, Cochrane Library, EMBASE and Google Scholar. Quality appraisal was performed using Downs and Black's quality checklist. To evaluate the performance of included models, the values of specificity and sensitivity were comparted, the values of area under the curve (AUC) were plotted, and the median of overall AUC of included studies was computed.

RESULTS

A total of 316 studies were reviewed for full text. Seven articles were included. Included studies implement techniques including artificial neural networks, Bayesian networks and decision trees. Six articles reported the overall model accuracy. Overall, the median AUC is 0.8243 [interquartile range (IQR): 0.8050-0.8886]. In the two articles that reported comparison results with traditional models, the data mining method performed better than the traditional models, with the best AUC improvement of 10.7%.

CONCLUSIONS

The adoption of data mining technologies for CRC detection is at an early stage. Limited numbers of included articles and heterogeneity of those studies implied that more rigorous research is expected to further investigate the techniques' effects.

A New Comprehensive Colorectal Cancer Risk Prediction Model Incorporating Family History, Personal Characteristics, and Environmental Factors

PURPOSE

Reducing colorectal cancer incidence and mortality through early detection would improve efficacy if targeted. We developed a colorectal cancer risk prediction model incorporating personal, family, genetic, and environmental risk factors to enhance prevention.

METHODS

A familial risk profile (FRP) was calculated to summarize individuals' risk based on detailed cancer family history (FH), family structure, probabilities of mutation in major colorectal cancer susceptibility genes, and a polygenic component. We developed risk models, including individuals' FRP or binary colorectal cancer FH, and colorectal cancer risk factors collected at enrollment using population-based colorectal cancer cases (N = 4,445) and controls (N = 3,967) recruited by the Colon Cancer Family Registry Cohort (CCFRC). Model validation used CCFRC follow-up data for population-based (N = 12,052) and clinic-based (N = 5,584) relatives with no cancer history at recruitment to assess model calibration [expected/observed rate ratio (E/O)] and discrimination [area under the receiver-operating-characteristic curve (AUC)].

RESULTS

The E/O [95% confidence interval (CI)] for FRP models for population-based relatives were 1.04 (0.74-1.45) for men and 0.86 (0.64-1.20) for women, and for clinic-based relatives were 1.15 (0.87-1.58) for men and 1.04 (0.76-1.45) for women. The age-adjusted AUCs (95% CI) for FRP models for population-based relatives were 0.69 (0.60-0.78) for men and 0.70 (0.62-0.77) for women, and for clinic-based relatives were 0.77 (0.69-0.84) for men and 0.68 (0.60-0.76) for women. The incremental values of AUC for FRP over FH models for population-based relatives were 0.08 (0.01-0.15) for men and 0.10 (0.04-0.16) for women, and for clinic-based relatives were 0.11 (0.05-0.17) for men and 0.11 (0.06-0.17) for women.

CONCLUSIONS

Both models calibrated well. The FRP-based model provided better risk stratification and risk discrimination than the FH-based model.

IMPACT

Our findings suggest detailed FH may be useful for targeted risk-based screening and clinical management.

Study Profile of the Tohoku Medical Megabank Community-Based Cohort Study

Background

We established a community-based cohort study to assess the long-term impact of the Great East Japan Earthquake on disaster victims and gene-environment interactions on the incidence of major diseases, such as cancer and cardiovascular diseases.

Methods

We asked participants to join our cohort in the health check-up settings and assessment center based settings. Inclusion criteria were aged 20 years or over and living in Miyagi or Iwate Prefecture. We obtained information on lifestyle, effect of disaster, blood, and urine information (Type 1 survey), and some detailed measurements (Type 2 survey), such as carotid echography and calcaneal ultrasound bone mineral density. All participants agreed to measure genome information and to distribute their information widely.

Results

As a result, 87,865 gave their informed consent to join our study. Participation rate at health check-up site was about 70%. The participants in the Type 1 survey were more likely to have psychological distress than those in the Type 2 survey, and women were more likely to have psychological distress than men. Additionally, coastal residents were more likely to have higher degrees of psychological distress than inland residents, regardless of sex.

Conclusion

This cohort comprised a large sample size and it contains information on the natural disaster, genome information, and metabolome information. This cohort also had several detailed measurements. Using this cohort enabled us to clarify the long-term effect of the disaster and also to establish personalized prevention based on genome, metabolome, and other omics information.

Prevalence and risk factors of colorectal cancer in Asia

Globally, colorectal cancer (CRC) is a substantial public health burden, and it is increasingly affecting populations in Asian countries. The overall prevalence of CRC is reported to be low in Asia when compared with that in Western nations, yet it had the highest number of prevalent cases. This review described the prevalence of CRC in Asia according to the International Agency for Research on Cancer from World Health Organization (WHO) database and summarized its major risk factors. Non-modifiable factors include genetic factors, ethnicity, age, gender, family history and body height; smoking, alcohol drinking, weight, Westernized diet, physical inactivity, chronic diseases and microbiota were involved in environmental factors. These risk factors were separately discussed in this review according to published literature from Asian countries. CRC screening has been playing an important role in reducing its disease burden. Some recommendations on its screening practices have been formulated in guidelines for Asia Pacific countries.

Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies

OBJECTIVE

To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.

DESIGN

Models were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability).

RESULTS

The systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 0.74) in EPIC.

CONCLUSION

Several of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.

A scoring model for predicting advanced colorectal neoplasia in a screened population of asymptomatic Japanese individuals

BACKGROUND

Risk stratification of screened populations could help improve colorectal cancer (CRC) screening. Use of the modified Asia-Pacific Colorectal Screening (APCS) score has been proposed in the Asia-Pacific region. This study was performed to build a new useful scoring model for CRC screening.

METHODS

Data were reviewed from 5218 asymptomatic Japanese individuals who underwent their first screening colonoscopy. Multivariate logistic regression was used to investigate risk factors for advanced colorectal neoplasia (ACN), and a new scoring model for the prediction of ACN was developed based on the results. The discriminatory capability of the new model and the modified APCS score were assessed and compared. Internal validation was also performed.

RESULTS

ACN was detected in 225 participants. An 8-point scoring model for the prediction of ACN was developed using five independent risk factors for ACN (male sex, higher age, presence of two or more first-degree relatives with CRC, body mass index of > 22.5 kg/m², and smoking history of > 18.5 pack-years). The prevalence of ACN was 1.6% (34/2172), 5.3% (127/2419), and 10.2% (64/627) in participants with scores of < 3, ≥ 3 to < 5, and ≥ 5, respectively. The c-statistic of the scoring model was 0.70 (95% confidence interval, 0.67-0.73) in both the development and internal validation sets, and this value was higher than that of the modified APCS score [0.68 (95% confidence interval, 0.65-0.71), P = 0.03].

CONCLUSIONS

We built a new simple scoring model for prediction of ACN in a Japanese population that could stratify the screened population into low-, moderate-, and high-risk groups.

Development and validation of a risk assessment tool for gastric cancer in a general Japanese population

BACKGROUND

There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese.

METHODS

A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort.

RESULTS

During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort.

CONCLUSIONS

We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.

Predicting the risk for colorectal cancer with personal characteristics and fecal immunochemical test

We aimed to predict colorectal cancer (CRC) based on the demographic features and clinical correlates of personal symptoms and signs from Tianjin community-based CRC screening data.A total of 891,199 residents who were aged 60 to 74 and were screened in 2012 were enrolled. The Lasso logistic regression model was used to identify the predictors for CRC. Predictive validity was assessed by the receiver operating characteristic (ROC) curve. Bootstrapping method was also performed to validate this prediction model.CRC was best predicted by a model that included age, sex, education level, occupations, diarrhea, constipation, colon mucosa and bleeding, gallbladder disease, a stressful life event, family history of CRC, and a positive fecal immunochemical test (FIT). The area under curve (AUC) for the questionnaire with a FIT was 84% (95% CI: 82%-86%), followed by 76% (95% CI: 74%-79%) for a FIT alone, and 73% (95% CI: 71%-76%) for the questionnaire alone. With 500 bootstrap replications, the estimated optimism (<0.005) shows good discrimination in validation of prediction model.A risk prediction model for CRC based on a series of symptoms and signs related to enteric diseases in combination with a FIT was developed from first round of screening. The results of the current study are useful for increasing the awareness of high-risk subjects and for individual-risk-guided invitations or strategies to achieve mass screening for CRC.

External validation of risk prediction models for incident colorectal cancer using UK Biobank

BACKGROUND

This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire.

METHODS

External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries.

RESULTS

There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals.

CONCLUSIONS

Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.

Estimation of lifetime cumulative incidence and mortality risk of gastric cancer

Objective

To estimate cumulative incidence and mortality risk for gastric cancer by risk category.

Methods

Risk was classified into four types according to the presence/absence of Helicobacter pylori infection and chronic atrophic gastritis: in order of lowest to highest risk, Group A: H. pylori(−) and atrophic gastritis(−); Group B: H. pylori(+) and atrophic gastritis(−); Group C:H. pylori(+) and atrophic gastritis(+); and, Group D: H. pylori(−) and atrophic gastritis(+). We used vital statistics for the crude all-cause and crude gastric cancer mortality rates in 2011 and data from population-based cancer registries (the Monitoring of Cancer Incidence in Japan) for gastric cancer incidence in 2011. For relative risk and prevalence, we used the results of a meta-analysis integrating previous studies and data from the Japan Public Health Center-based Prospective Study for the Next Generation, respectively (baseline survey 2011–16). We calculated the crude incidence and mortality rates and estimated the cumulative risk using a life-table method.

Results

The estimated lifetime cumulative incidence risk was 11.4% for men and 5.7% for women. The estimated risk for Groups A, B, C and D was 2.4%, 10.8%, 26.7% and 35.5% for men, and 1.2%, 5.5%, 13.5% and 18.0% for women, respectively. Similarly, the estimated lifetime cumulative mortality risk was 3.9% for men and 1.8% for women. The estimated risk of mortality for Groups A, B, C and D was 0.8%, 3.6%, 9.0% and 12.0% for men, and 0.4%, 1.7%, 4.2% and 5.7% for women, respectively.

Conclusions

Our results may be useful for designing individually tailored prevention programs.

A modified colorectal screening score for prediction of advanced neoplasia: A prospective study of 5744 subjects

BACKGROUND AND AIM

We validated a modified risk algorithm based on the Asia-Pacific Colorectal Screening (APCS) score that included body mass index (BMI) for prediction of advanced neoplasia.

METHODS

Among 5744 Chinese asymptomatic screening participants undergoing a colonoscopy in Hong Kong from 2008 to 2012, a random sample of 3829 participants acted as the derivation cohort. The odds ratios for significant risk factors identified by binary logistic regression analysis were used to build a scoring system ranging from 0 to 6, divided into "average risk" (AR): 0; "moderate risk" (MR): 1-2; and "high risk" (HR): 3-6. The other 1915 subjects formed a validation cohort, and the performance of the score was assessed.

RESULTS

The prevalence of advanced neoplasia in the derivation and validation cohorts was 5.4% and 6.0%, respectively (P = 0.395). Old age, male gender, family history of colorectal cancer, smoking, and BMI were significant predictors in multivariate regression analysis. A BMI cut-off at > 23 kg/m² had better predictive capability and lower number needed to screen than that of > 25 kg/m² . Utilizing the score developed, 8.4%, 57.4%, and 34.2% in the validation cohort were categorized as AR, MR, and HR, respectively. The corresponding prevalence of advanced neoplasia was 3.8%, 4.3%, and 9.3%. Subjects in the HR group had 2.48-fold increased prevalence of advanced neoplasia than the AR group. The c-statistics of the modified score had better discriminatory capability than that using predictors of APCS alone (c-statistics = 0.65 vs 0.60).

CONCLUSIONS

Incorporating BMI into the predictors of APCS score was found to improve risk prediction of advanced neoplasia and reduce colonoscopy resources.

Inclusion of a Genetic Risk Score into a Validated Risk Prediction Model for Colorectal Cancer in Japanese Men Improves Performance

We previously developed and validated a risk prediction model for colorectal cancer in Japanese men using modifiable risk factors. To further improve risk prediction, we evaluated the degree of improvement obtained by adding a genetic risk score (GRS) using genome-wide association study (GWAS)-identified risk variants to our validated model. We examined the association between 36 risk variants identified by GWAS and colorectal cancer risk using a weighted Cox proportional hazards model in a nested case-control study within the Japan Public Health Center-based Prospective Study. GRS was constructed using six variants associated with risk in this study of the 36 tested. We assessed three models: a nongenetic model that included the same variables used in our previously validated model; a genetic model that used GRS; and an inclusive model, which included both. The c-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) were calculated by the 5-fold cross-validation method. We estimated 10-year absolute risks for developing colorectal cancer. A statistically significant association was observed between the weighted GRS and colorectal cancer risk. The mean c-statistic for the inclusive model (0.66) was slightly greater than that for the nongenetic model (0.60). Similarly, the mean IDI and NRI showed improvement when comparing the nongenetic and inclusive models. These models for colorectal cancer were well calibrated. The addition of GRS using GWAS-identified risk variants to our validated model for Japanese men improved the prediction of colorectal cancer risk. Cancer Prev Res; 10(9); 535-41. ©2017 AACR.

Predicting advanced neoplasia at colonoscopy in a diverse population with the National Cancer Institute colorectal cancer risk-assessment tool

BACKGROUND

Tailoring screening to colorectal cancer (CRC) risk could improve screening effectiveness. Most CRCs arise from advanced neoplasia (AN) that dwells for years. To date, no available colorectal neoplasia risk score has been validated externally in a diverse population. The authors explored whether the National Cancer Institute (NCI) CRC risk-assessment tool, which was developed to predict future CRC risk, could predict current AN prevalence in a diverse population, thereby allowing its use in risk stratification for screening.

METHODS

This was a prospective examination of the relation between predicted 10-year CRC risk and the prevalence of AN, defined as advanced or multiple (≥3 adenomatous, ≥5 serrated) adenomatous or sessile serrated polyps, in individuals undergoing screening colonoscopy.

RESULTS

Among 509 screenees (50% women; median age, 58 years; 61% white, 5% black, 10% Hispanic, and 24% Asian), 58 (11%) had AN. The prevalence of AN increased progressively from 6% in the lowest risk-score quintile to 17% in the highest risk-score quintile (P = .002). Risk-score distributions in individuals with versus without AN differed significantly (median, 1.38 [0.90-1.87] vs 1.02 [0.62-1.57], respectively; P = .003), with substantial overlap. The discriminatory accuracy of the tool was modest, with areas under the curve of 0.61 (95% confidence interval [CI], 0.54-0.69) overall, 0.59 (95% CI, 0.49-0.70) for women, and 0.63 (95% CI, 0.53-0.73) for men. The results did not change substantively when the analysis was restricted to adenomatous lesions or to screening procedures without any additional incidental indication.

CONCLUSIONS

The NCI CRC risk-assessment tool displays modest discriminatory accuracy in predicting AN at screening colonoscopy in a diverse population. This tool may aid shared decision-making in clinical practice. Cancer 2016. © 2016 American Cancer Society. Cancer 2016;122:2663-2670. © 2016 American Cancer Society.

Evaluation of a risk index for advanced proximal neoplasia of the colon

BACKGROUND

A clinical risk index that uses distal colorectal findings at flexible sigmoidoscopy (FS) in conjunction with easily determined risk factors for advanced proximal neoplasia (APN) may be useful for tailoring or prioritizing screening with colonoscopy.

OBJECTIVE

To conduct an external evaluation of a previously published risk index in a large, well-characterized cohort.

DESIGN

Cross-sectional.

SETTING

Teaching hospital and colorectal cancer screening center.

PATIENTS

A total of 5139 asymptomatic persons aged 50 to 74 (54.9% women) with a mean age (±SD) of 58.3 (±6.2) years.

INTERVENTIONS

Between 2003 and 2011, all participants underwent a complete screening colonoscopy and removal of all polyps.

MAIN OUTCOME MEASUREMENTS

Participants were classified as low, intermediate, or high risk for APN, based on their composite risk index scores. The concordance or c-statistic was used to measure discriminating ability of the risk index.

RESULTS

A total of 167 persons (3.2%) had APN. The prevalence of those with APN among low-, intermediate-, and high-risk categories was 2.1%, 2.9%, and 6.5%, respectively. High-risk individuals were 3.2 times more likely to have APN compared with those in the low-risk category. The index did not discriminate well between those in the low- and intermediate-risk categories. The c-statistic for the overall index was 0.62 (95% confidence interval, 0.58-0.66).

LIMITATIONS

Distal colorectal findings were derived from colonoscopies and not FS itself.

CONCLUSION

The risk index discriminated between those at low risk and those at high risk, but it had limited ability to discriminate between low- and intermediate-risk categories for prevalent APN. Information on other risk factors may be needed to tailor, or prioritize, access to screening colonoscopy.

Effects of NSAIDs on the risk factors of colorectal cancer: a mini review

Evidence from epidemiological and experimental studies has shown that non-steroidal anti-inflammatory drugs (NSAIDs) reduce the risk of colorectal cancer (CRC). The function of NSAIDs and the molecular targets for chemopreventive effects on CRC have been extensively studied and their data were reported. However, the relation between NSAIDs and the risk factors of CRC have not been fully elucidated yet. Thus, relations between NSAIDs and the risk factors of CRC, such as overweight and obesity, alcohol, aging, hypertriglyceridemia and smoking, are summarized with our data and with recent reported data in this review.

The discriminatory capability of existing scores to predict advanced colorectal neoplasia: a prospective colonoscopy study of 5,899 screening participants

We evaluated the performance of seven existing risk scoring systems in predicting advanced colorectal neoplasia in an asymptomatic Chinese cohort. We prospectively recruited 5,899 Chinese subjects aged 50–70 years in a colonoscopy screening programme(2008–2014). Scoring systems under evaluation included two scoring tools from the US; one each from Spain, Germany, and Poland; the Korean Colorectal Screening(KCS) scores; and the modified Asia Pacific Colorectal Screening(APCS) scores. The c-statistics, sensitivity, specificity, positive predictive values(PPVs), and negative predictive values(NPVs) of these systems were evaluated. The resources required were estimated based on the Number Needed to Screen(NNS) and the Number Needed to Refer for colonoscopy(NNR). Advanced neoplasia was detected in 364 (6.2%) subjects. The German system referred the least proportion of subjects (11.2%) for colonoscopy, whilst the KCS scoring system referred the highest (27.4%). The c-statistics of all systems ranged from 0.56–0.65, with sensitivities ranging from 0.04–0.44 and specificities from 0.74–0.99. The modified APCS scoring system had the highest c-statistics (0.65, 95% C.I. 0.58–0.72). The NNS (12–19) and NNR (5-10) were similar among the scoring systems. The existing scoring systems have variable capability to predict advanced neoplasia among asymptomatic Chinese subjects, and further external validation should be performed.

Targeted screening for colorectal cancer in high-risk individuals

The idea of targeted screening for colorectal cancer based on risk profiles originates from its benefits to improve detection yield and optimize screening efficiency. Clinically, it allows individuals to be more aware of their own risk and make informed decisions on screening choice. From a public health perspective, the implementation of risk stratification strategies may better justify utilization of colonoscopic resources, and facilitate resource-planning in the formulation of population-based screening programmes. There are several at-risk groups who should receive earlier screening, and colonoscopy is more preferred. This review summarizes the currently recommended CRC screening strategies among subjects with different risk factors, and introduces existing risk scoring systems. Additional genetic, epidemiological, and clinical parameters may be needed to enhance their performance to risk-stratify screening participants. Future research studies should refine these scoring systems, and explore the adaptability, feasibility, acceptability, and user-friendliness of their use in clinical practice among different population groups.

Evaluation of a clinical risk index for advanced colorectal neoplasia among a North American population of screening age

Background

A clinical risk index employing age, sex, family history of colorectal cancer (CRC), smoking history and body mass index (BMI) may be useful for prioritizing screening with colonoscopy. The aim of this study was to conduct an external evaluation of a previously published risk index for advanced neoplasia (AN) in a large, well-characterized cohort.

Methods

Five thousand one hundred thirty-seven asymptomatic persons aged 50 to 74 (54.9 % women) with a mean age (SD) of 58.3 (6.2) years were recruited for the study from a teaching hospital and colorectal cancer screening centre between 2003 and 2011. All participants underwent a complete screening colonoscopy and removal of all polyps. AN was defined as cancer or a tubular adenoma, traditional serrated adenoma (TSA), or sessile serrated adenoma (SSA) with villous characteristics (≥25% villous component), and/or high-grade dysplasia and/or diameter ≥10 mm. Risk scores for each participant were summed to derive an overall score (0–8). The c-statistic was used to measure discriminating ability of the risk index.

Results

The prevalence of AN in the study cohort was 6.8 %. The likelihood of detecting AN increased from 3.6 to 13.1 % for those with a risk score of 1 to 6 respectively. The c-statistic for the multivariable logistic model in our cohort was 0.64 (95 % CI = 0.61–067) indicating modest overlap between risk scores.

Conclusions

The risk index for AN using age, sex, family history, smoking history and BMI was found to be of limited discriminating ability upon external validation. The index requires further refinement to better predict AN in average risk persons of screening age.

Risk Prediction Models for Colorectal Cancer: A Systematic Review

Colorectal cancer is the second leading cause of cancer-related death in Europe and the United States. Survival is strongly related to stage at diagnosis and population-based screening reduces colorectal cancer incidence and mortality. Stratifying the population by risk offers the potential to improve the efficiency of screening. In this systematic review we searched Medline, EMBASE, and the Cochrane Library for primary research studies reporting or validating models to predict future risk of primary colorectal cancer for asymptomatic individuals. A total of 12,808 papers were identified from the literature search and nine through citation searching. Fifty-two risk models were included. Where reported (n = 37), half the models had acceptable-to-good discrimination (the area under the receiver operating characteristic curve, AUROC >0.7) in the derivation sample. Calibration was less commonly assessed (n = 21), but overall acceptable. In external validation studies, 10 models showed acceptable discrimination (AUROC 0.71-0.78). These include two with only three variables (age, gender, and BMI; age, gender, and family history of colorectal cancer). A small number of prediction models developed from case-control studies of genetic biomarkers also show some promise but require further external validation using population-based samples. Further research should focus on the feasibility and impact of incorporating such models into stratified screening programmes.

Do recent epidemiologic observations impact who and how we should screen for CRC?

Colorectal cancer (CRC) screening is recommended to begin at age 50 for those patients with no significant family history of CRC. However, even within this group of average-risk patients, there is data to suggest that there may be variation in CRC risk. These observations suggest that perhaps CRC screening should be tailored to target those patients at higher risk for earlier or more invasive screening as compared to those individuals at lower risk. The strategy of how to identify those higher-risk patients may not be straightforward. One method might be to use single risk factors such as smoking or elevated BMI as has been suggested in the recent American College of Gastroenterology CRC screening guidelines. Another paradigm involves the use of models which incorporate several risk factors to stratify patients by risk. This article will highlight recent large studies that examine recognized CRC risk factors as well as review recently developed CRC risk models. There will also be a discussion of the application of these factors and models in an effort to make CRC screening more efficient.

Personalizing colorectal cancer screening: a systematic review of models to predict risk of colorectal neoplasia

BACKGROUND & AIMS

A valid risk prediction model for colorectal neoplasia would allow patients to be screened for colorectal cancer (CRC) on the basis of risk. We performed a systematic review of studies reporting risk prediction models for colorectal neoplasia.

METHODS

We conducted a systematic search of MEDLINE, Scopus, and Cochrane Library databases from January 1990 through March 2013 and of references in identified studies. Case-control, cohort, and cross-sectional studies that developed or attempted to validate a model to predict risk of colorectal neoplasia were included. Two reviewers independently extracted data and assessed model quality. Model quality was considered to be good for studies that included external validation, fair for studies that included internal validation, and poor for studies with neither.

RESULTS

Nine studies developed a new prediction model, and 2 tested existing models. The models varied with regard to population, predictors, risk tiers, outcomes (CRC or advanced neoplasia), and range of predicted risk. Several included age, sex, smoking, a measure of obesity, and/or family history of CRC among the predictors. Quality was good for 6 models, fair for 2 models, and poor for 1 model. The tier with the largest population fraction (low, intermediate, or high risk) depended on the model. For most models that defined risk tiers, the risk difference between the highest and lowest tier ranged from 2-fold to 4-fold. Two models reached the 0.70 threshold for the C statistic, typically considered to indicate good discriminatory power.

CONCLUSIONS

Most current colorectal neoplasia risk prediction models have relatively weak discriminatory power and have not demonstrated generalizability. It remains to be determined how risk prediction models could inform CRC screening strategies.

Development and validation of a risk score predicting risk of colorectal cancer

BACKGROUND

Quantifying the risk of colorectal cancer for individuals is likely to be useful for health service provision. Our aim was to develop and externally validate a prediction model to predict 5-year colorectal cancer risk.

METHODS

We used proportional hazards regression to develop the model based on established personal and lifestyle colorectal cancer risk factors using data from 197,874 individuals from the 45 and Up Study, Australia. We subsequently validated the model using 24,233 participants from the Melbourne Collaborative Cohort Study (MCCS).

RESULTS

A total of 1,103 and 224 cases of colorectal cancer were diagnosed in the development and validation sample, respectively. Our model, which includes age, sex, BMI, prevalent diabetes, ever having undergone colorectal cancer screening, smoking, and alcohol intake, exhibited a discriminatory accuracy of 0.73 [95% confidence interval (CI), 0.72-0.75] and 0.70 (95% CI, 0.66-0.73) using the development and validation sample, respectively. Calibration was good for both study samples. Stratified models according to colorectal cancer screening history, that additionally included family history, showed discriminatory accuracies of 0.75 (0.73-0.76) and 0.70 (0.67-0.72) for unscreened and screened individuals of the development sample, respectively. In the validation sample, discrimination was 0.68 (0.64-0.73) and 0.72 (0.67-0.76), respectively.

CONCLUSION

Our model exhibited adequate predictive performance that was maintained in the external population.

IMPACT

The model may be useful to design more powerful cancer prevention trials. In the group of unscreened individuals, the model may be useful as a preselection tool for population-based screening programs.

Development and validation of a scoring system to identify individuals at high risk for advanced colorectal neoplasms who should undergo colonoscopy screening

BACKGROUND & AIMS

Screening the population for colorectal cancer (CRC) by colonoscopy could reduce the disease burden. However, targeted screening of individuals at high risk could increase its cost effectiveness.

METHODS

We developed a scoring system to identify individuals with at least 1 advanced adenoma, based on easy-to-collect risk factors among 7891 participants of the German screening colonoscopy program. The system was validated in an independent sample of 3519 participants. Multiple logistic regression was used to develop the algorithm, and the regression coefficient-based scores were used to determine individual risks. Relative risk and numbers of colonoscopies needed for detecting one or more advanced neoplasm(s) were calculated for quintiles of the risk score. The predictive ability of the scoring system was quantified by the area under the curve.

RESULTS

We identified 9 risk factors (sex, age, first-degree relatives with a history of CRC, cigarette smoking, alcohol consumption, red meat consumption, ever regular use [at least 2 times/wk for at least 1 y] of nonsteroidal anti-inflammatory drugs, previous colonoscopy, and previous detection of polyps) that were associated significantly with risk of advanced neoplasms. The developed score was associated strongly with the presence of advanced neoplasms. In the validation sample, individuals in the highest quintile of scores had a relative risk for advanced neoplasm of 3.86 (95% confidence interval, 2.71-5.49), compared with individuals in the lowest quintile. The number needed to screen to detect 1 or more advanced neoplasm(s) varied from 20 to 5 between quintiles of the risk score. In the validation sample, the scoring system identified patients with CRC or any advanced neoplasm with area under the curve values of 0.68 and 0.66, respectively.

CONCLUSIONS

We developed a scoring system, based on easy-to-collect risk factors, to identify individuals most likely to have advanced neoplasms. This system might be used to stratify individuals for CRC screening.

Risk prediction model for colorectal cancer: National Health Insurance Corporation study, Korea

Purpose

Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection.

Methods

Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30–80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics.

Results

Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women.

Conclusions

Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.

Impact of five modifiable lifestyle habits on the probability of cancer occurrence in a Japanese population-based cohort: results from the JPHC study

OBJECTIVE

The present work aims to provide 10-year estimates of the probability of cancer occurrence in the Japanese population based on age, sex, and the pattern of adherence to five healthy lifestyle habits.

METHODS

The study population consisted of 74,935 participants in the Japan Public Health Center-Based Prospective Study (aged 45 to 74 years) who answered a 5-year follow-up questionnaire about various lifestyle habits between 1995 and 1999. The relationship between five previously identified healthy lifestyle habits (never smoking, moderate or no alcohol consumption, adequate physical activity, moderate salt intake, and appropriate body mass index) and cancer occurrence was assessed using a sex-specific parametric survival model.

RESULTS

Compared to individuals not adhering to any of the five habits, never-smoking men had a nearly 30% reduction in the 10-year probability of cancer occurrence (e.g., 20.5% vs. 28.7% at age 70), and never-smoking women had a 16% reduction (e.g., 10.5% vs. 12.5% at age 70). Adherence to all five habits was estimated to reduce the 10-year probability of cancer occurrence by 1/2 in men and 1/3 in women.

CONCLUSION

By quantifying the impact of lifestyle habits on the probability of cancer occurrence, this study emphasizes the importance of lifestyle improvement.

Risk for coronary heart disease increases risk for colorectal neoplasm

BACKGROUND & AIMS

Colorectal neoplasms and coronary artery disease have similar risk factors. Patients with established coronary artery disease have a high prevalence of colorectal neoplasms. However, little is known about the risk of colorectal neoplasms among individuals at risk for coronary artery disease.

METHODS

We performed a cross-sectional study of 3144 asymptomatic, average-risk individuals without history of coronary artery disease or other vascular disorders who received a screening colonoscopy examination from January to December 2010 at Konkuk University Medical Center in Seoul, Korea. Participants were classified as having low (<10%), intermediate (10%-20%), or high (≥20%) risk for developing coronary artery disease in the next 10 years, which was based on Framingham/Adult Treatment Panel III risk scores.

RESULTS

The prevalence of colorectal neoplasms in subjects with low, intermediate, and high risk for coronary artery disease was 25.6% (635/2485), 46.6% (252/541), and 53.4% (63/118), respectively (P < .001); the prevalence of advanced colorectal neoplasms was 4.9% (122/2485), 9.2% (50/541), and 17.8% (21/118), respectively, for these subjects (P < .001). In multivariate analyses, the high-risk group had a significantly increased risk of advanced colorectal neoplasm (odds ratio, 3.31; 95% confidence interval [CI], 1.94-5.65), compared with the low-risk group. The numbers of colonoscopies needed to identify individuals with advanced colorectal neoplasms in intermediate-risk and high-risk groups were 10.8 (95% CI, 8.6-14.7) and 5.6 (95% CI, 7.6-11.9), respectively, which were significantly lower than for the low-risk group (20.4; 95% CI, 17.4-24.6).

CONCLUSIONS

The prevalence and the risk of overall and advanced colorectal neoplasms increase with risk of coronary artery disease. Individuals with a 10-year risk of coronary artery disease ≥10% might benefit from colonoscopy screening, but further studies are needed to confirm and generalize these results.

Prediction of Colorectal Cancer Risk Using a Genetic Risk Score: The Korean Cancer Prevention Study-II (KCPS-II)

Colorectal cancer (CRC) is among the leading causes of cancer deaths and can be caused by environmental factors as well as genetic factors. Therefore, we developed a prediction model of CRC using genetic risk scores (GRS) and evaluated the effects of conventional risk factors, including family history of CRC, in combination with GRS on the risk of CRC in Koreans. This study included 187 cases (men, 133; women, 54) and 976 controls (men, 554; women, 422). GRS were calculated with most significantly associated single-nucleotide polymorphism with CRC through a genomewide association study. The area under the curve (AUC) increased by 0.5% to 5.2% when either counted or weighted GRS was added to a prediction model consisting of age alone (AUC 0.687 for men, 0.598 for women) or age and family history of CRC (AUC 0.692 for men, 0.603 for women) for both men and women. Furthermore, the risk of CRC significantly increased for individuals with a family history of CRC in the highest quartile of GRS when compared to subjects without a family history of CRC in the lowest quartile of GRS (counted GRS odds ratio [OR], 47.9; 95% confidence interval [CI], 4.9 to 471.8 for men; OR, 22.3; 95% CI, 1.4 to 344.2 for women) (weighted GRS OR, 35.9; 95% CI, 5.9 to 218.2 for men; OR, 18.1, 95% CI, 3.7 to 88.1 for women). Our findings suggest that in Koreans, especially in Korean men, GRS improve the prediction of CRC when considered in conjunction with age and family history of CRC.

Risk prediction models for colorectal cancer: a review

Risk prediction models are important to identify individuals at high risk of developing the disease who can then be offered individually tailored clinical management, targeted screening and interventions to reduce the burden of disease. They are also useful for research purposes when attempting to identify new risk factors for the disease. In this article, we review the risk prediction models that have been developed for colorectal cancer and appraise their applicability, strengths, and weaknesses. We also discuss the factors to be considered for future development and improvement of models for colorectal cancer risk prediction. We conclude that there is no model that sufficiently covers the known risk factors for colorectal cancer that is suitable for assessment of people from across the full range of risk and that a new comprehensive model is needed.