Is mailed outreach and patient navigation a perfect solution to improve HCC screening?

Hepatocellular carcinoma (HCC) is a significant global health problem, and its incidence is expected to exceed 1 million new HCC annually by 2025.1 The reported 3-year survival rate for advanced-stage HCC is less than 17%, while 70% of patients diagnosed with early-stage HCC can achieve 5-year survival.2 Despite well-established guidelines and the clear benefits of early detection, the meta-analysis results (29 papers, 1 18 799 patients) showed that only 24% of individuals at risk for developing HCC were screened.3 Efforts to surmount barriers at patient, provider and healthcare levels have shown a minimal screening rate increase over time.3 4 One of the reasons for the disappointing results might be the fact that authors focused on individual barriers, rather than considering the screening failure the result of the interplay of different factors. Additionally, the published studies have the following limitations, detailed reasons for…

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Novembre 2024

Where are we with gastric cancer screening in Europe in 2024?

The absolute number of annual cases of gastric cancer in Europe is rising. The Council of the European Union has recommended implementation of gastric cancer screening for countries or regions with a high gastric cancer incidence and death rates. However, as of 2024 no organised gastric cancer screening programme has been launched in Europe.
There are several ways to decrease gastric cancer burden, but the screen and treat strategy for Helicobacter pylori (H. pylori) seems to be the most appropriate for Europe. It has to be noted that increased use of antibiotics would be associated with this strategy.
Only organised population-based cancer screening is recommended in the European Union, therefore gastric cancer screening also is expected to fulfil the criteria of an organised screening programme. In this respect, several aspects of screening organisation need to be considered before full implementation of gastric cancer prevention in Europe; the age range of the target group, test types, H. pylori eradication regimens and surveillance strategies are among them. Currently, ongoing projects (GISTAR, EUROHELICAN, TOGAS and EUCanScreen) are expected to provide the missing evidence. Feedback from the decision-makers and the potential target groups, including vulnerable populations, will be important to planning the programme.
This paper provides an overview of the recent decisions of the European authorities, the progress towards gastric cancer implementation in Europe and expected challenges. Finally, a potential algorithm for gastric cancer screening in Europe is proposed.

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Novembre 2024

Effectiveness of mailed outreach and patient navigation to promote HCC screening process completion: a multicentre pragmatic randomised clinical trial

Background
Hepatocellular carcinoma (HCC) is plagued by failures across the cancer care continuum, leading to frequent late-stage diagnoses and high mortality. We evaluated the effectiveness of mailed outreach invitations plus patient navigation to promote HCC screening process completion in patients with cirrhosis.

Methods
Between April 2018 and September 2021, we conducted a multicentre pragmatic randomised clinical trial comparing mailed outreach plus patient navigation for HCC screening (n=1436) versus usual care with visit-based screening (n=1436) among patients with cirrhosis at three US health systems. Our primary outcome was screening process completion over a 36-month period, and our secondary outcome was the proportion of time covered (PTC) by screening. All patients were included in intention-to-screen analyses.

Results
All 2872 participants (median age 61.3 years; 32.3% women) were included in intention-to-screen analyses. Screening process completion was observed in 6.6% (95% CI: 5.3% to 7.9%) of patients randomised to outreach and 3.3% (95% CI: 2.4% to 4.3%) of those randomised to usual care (OR 2.05, 95% CI: 1.44 to 2.92). The intervention increased HCC screening process completion across most subgroups including age, sex, race and ethnicity, Child-Turcotte-Pugh class and health system. PTC was also significantly higher in the outreach arm than usual care (mean 37.5% vs 28.2%; RR 1.33, 95% CI: 1.31 to 1.35). Despite screening underuse, most HCC in both arms were detected at an early stage.

Conclusion
Mailed outreach plus navigation significantly increased HCC screening process completion versus usual care in patients with cirrhosis, with a consistent effect across most examined subgroups. However, screening completion remained suboptimal in both arms, underscoring a need for more intensive interventions.

Trial registration number
NCT02582918.

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Novembre 2024

Abstract 4139194: Predicting Cholesterol Screening Behavior After Age 50 Using Machine Learning: Insights from the Health and Retirement Study

Circulation, Volume 150, Issue Suppl_1, Page A4139194-A4139194, November 12, 2024. Background:In the U.S., about 8% of adults never received cholesterol screening. Although machine learning (ML) has been used to develop decision tools for Atherosclerotic Cardiovascular Disease (ASCVD) risk prediction, its application in behavioral forecasting has not yet been explored in the context of cholesterol screening behaviors. This study aimed to examine the performance and accuracy of ML algorithms in forecasting cholesterol screening behaviors in adults after age 50.Methods:This analysis used deidentified data from the Health and Retirement Study (HRS) 2004-2018. HRS is a longitudinal survey among 23,000 households in the U.S. Participants were excluded from the current analysis if they passed away by 2019, ever had ASCVD or stroke, were under age 50 at baseline, or had missing data in self-reported cholesterol screening. In total, 7176 participants (mean age [SD]=62 [8]) met the inclusion criteria; participants were randomly split into a training set (80%) and a testing set (20%). The synthetic minority oversampling technique was used to solve the imbalance distribution of the rare event. Five ML algorithms were used: random forest, gradient boosting machine (GBM), XGBoost, Support Vector Machine (SVM), and logistic regression. Accuracy, AUROC, and positive predictive value (PPV) were used to compare model performance. The average gain was evaluated for feature importance in the demographic and health domains.Results:In total, 232 (3.2%) respondents did not receive any cholesterol screening from 2008 to 2018. Experiments with five ML algorithms suggested that XGBoost with deeper trees and learning rate performed better in classifying those who did not screen for cholesterol levels over 10 years. Adding prior cholesterol screening history (2004-2006) into the model significantly improved model performance. Hypertension, self-rated health, and smoking were the major health features, while insurance, poverty, and work status were the major demographic features in the predictive model (accuracy=0.97; AUROC=0.88; PPV=0.42).Conclusion:Findings underscore the potential utility of ML models in predicting cholesterol screening behaviors after age 50. This could be the basis for developing decision tools for clinicians to identify those with a lower chance of cholesterol screening or make reminders accordingly. The low-cost predictive model might improve the uptake of preventive screening behaviors in middle-aged and older adults.

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Novembre 2024