The use of electronic healthcare records for colorectal cancer screening referral decisions and risk prediction model development

Risk-stratified selection to colonoscopy in FIT colorectal cancer screening: development and temporal validation of a prediction model

BACKGROUND

Faecal immunochemical tests (FITs) yield many false positives and challenge colonoscopy capacity in colorectal cancer (CRC) screening programmes. We aimed to develop a risk-based selection of participants to undergo diagnostic colonoscopy.

METHODS

The study was observational and used registry data from the Danish CRC screening programme. We included all participants invited 2014-2016 with a positive FIT (≥ 20 μg fHb/g) who underwent colonoscopy (n = 56,459). We predicted the risk of CRC or advanced neoplasia (AN) from age, gender and FIT value using logistic regression. We evaluated calibration and discrimination and conducted temporal validation. We compared the number of CRCs and adenomas identified by risk cut-offs and by a corresponding FIT cut-off.

RESULTS

AUCs were 74.9% (95% CI: 73.6; 76.3) and 67.4% (95% CI: 66.8%; 68.0%) for the models predicting CRC and AN in the validation dataset. The cut-off of CRC risk calculated from age, gender and FIT value identified 1.03 times (95% CI: 1.02; 1.05) more CRCs and 1.01 times (95% CI: 1.01; 1.01) more medium/high-risk adenomas compared with the corresponding FIT cut-off.

CONCLUSIONS

With existing data, risk-stratified FIT screening using a risk cut-off instead of a FIT cut-off can slightly improve the selection to colonoscopy of those at highest risk of cancer and adenomas.

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.

Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review

Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool). Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome. Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice.

A diagnostic prediction model for colorectal cancer in elderlies via internet of medical things

Internet of Medical Things (IoMT) and embedded systems have improved the healthcare systems by enabling remote monitoring the patients’ health conditions anywhere and anytime especially during novel COVID-19 pandemic. In this paper, an IoT-based predicting model is proposed to predict colorectal cancer (CRC) in elderlies. It provides a CRC predicting model for the involved medical team to continuously trace an elderly’s biological indicators using smart wearable embedded systems and medical IoT devices. In this model, vital medical data is collected by IoMT devices and sensors, then analytical information is derived via machine learning (ML) methods for early CRC diagnosis and elderly’s health parameters changes. The experimental results confirm that the suggested model meets the proper accuracy of predicting the CRC in aged people.

Individualized faecal immunochemical test cut-off based on age and sex in colorectal cancer screening

The risk of having colorectal cancer (CRC) or its precursors vary with age and sex. Yet, most CRC screening programs using the quantitative faecal immunochemical test (FIT) use a uniform FIT cut-off. We aimed to calculate individualized FIT cut-offs based on age and sex. Data from a study of 1,112 asymptomatic average-risk screening participants undergoing colonoscopy without preselection were used to build a logistic regression model to calculate the risk of having advanced neoplasia (AN) at colonoscopy using age, sex, and FIT concentration as variables. We calculated age- and sex-adjusted FIT cut-off concentrations based on a uniform risk threshold. In a total of 101 of the 1,112 participants AN was detected at colonoscopy. We selected a risk threshold that would produce a specificity of 96.9% in the study group, matching the specificity of FIT at a cut-off of 20 µg Hb/g faeces. At this threshold, age- and sex-adjusted FIT cut-off concentrations ranged from 36.9 µg Hb/g faeces for 50-year-old women to 9.5 µg Hb/g faeces for 75-year old men. At this level of specificity, the risk-based model reached a sensitivity for AN of 28.7% (95%CI: 20.8 to 38.2) versus 27.7% (95%CI: 19.9 to 37.1) for FIT only. Using a risk threshold instead of a uniform FIT-based threshold for inviting screening participants to follow-up colonoscopy ensures that everyone has a comparable risk of AN prior to colonoscopy and may improve the detection of advanced neoplasia, although the absolute magnitude of the increase is likely to be limited.

Correlation between immunity from BCG and the morbidity and mortality of COVID-19

BACKGROUND

To investigate the association between parameters indicating immunity from BCG at country level (presence of BCG vaccination policy, BCG coverage, age-specific incidence of tuberculosis (TB)) and the morbidity and mortality of COVID-19.

METHODS

Country-specific data for COVID-19 cases and deaths, demographic details, BCG coverage and policy, age-specific TB incidence and income level were obtained. The crude COVID-19 cases and deaths per 100,000 population were calculated and assessed against the parameters indicating immunity from BCG using linear regression analysis.

RESULTS

Univariate analysis identified higher income level of a country to be significantly associated with COVID-19 cases (p < 0.0001) and deaths (p < 0.0001) but not with its case fatality rate. The association between COVID-19 and TB was strongest for TB incidence in patients > 65-years (Cases (rs = - 0.785,p = 0.0001)) and deaths (rs = - 0.647,p = 0.0001).Multivariate analysis identified the higher income level of a country and not having a universal BCG vaccination policy to affect the COVID-19 cases. The deaths were inversely affected by the presence of BCG vaccination policy and coverage; and positively by the TB incidence in patients > 65-years.

CONCLUSION

Significant inverse correlations observed between cases and deaths of COVID-19 and BCG related parameters highlights immunity from BCG as a likely explanation for the variation in COVID-19 across countries.