Development and external validation of a nomogram to predict the risk of Upper gastrointestinal precancerous lesions in a non-high-incidence area

Development and validation of a nomogram for obesity and related factors to detect gastric precancerous lesions in the Chinese population: a retrospective cohort study

Objectives

The purpose of this study was to construct a nomogram to identify patients at high risk of gastric precancerous lesions (GPLs). This identification will facilitate early diagnosis and treatment and ultimately reduce the incidence and mortality of gastric cancer.

Methods

In this single-center retrospective cohort study, 563 participants were divided into a gastric precancerous lesion (GPL) group (n=322) and a non-atrophic gastritis (NAG) group (n=241) based on gastroscopy and pathology results. Laboratory data and demographic data were collected. A derivation cohort (n=395) was used to identify the factors associated with GPLs to develop a predictive model. Then, internal validation was performed (n=168). We used the area under the receiver operating characteristic curve (AUC) to determine the discriminative ability of the predictive model; we constructed a calibration plot to evaluate the accuracy of the predictive model; and we performed decision curve analysis (DCA) to assess the clinical practicability predictive model.

Results

Four -predictors (i.e., age, body mass index, smoking status, and -triglycerides) were included in the predictive model. The AUC values of this predictive model were 0.715 (95% CI: 0.665-0.765) and 0.717 (95% CI: 0.640-0.795) in the derivation and internal validation cohorts, respectively. These values indicated that the predictive model had good discrimination ability. The calibration plots and DCA suggested that the predictive model had good accuracy and clinical net benefit. The Hosmer-Lemeshow test results in the derivation and validation cohorts for this predictive model were 0.774 and 0.468, respectively.

Conclusion

The nomogram constructed herein demonstrated good performance in terms of predicting the risk of GPLs. This nomogram can be beneficial for the early detection of patients at high risk of GPLs, thus facilitating early treatment and ultimately reducing the incidence and mortality of gastric cancer.

Prevalence of Gastric Precursor Lesions in Countries With Differential Gastric Cancer Burden: A Systematic Review and Meta-analysis

BACKGROUND & AIMS

The prevalence of precursor lesions for gastric cancer (GC) and the differential burden between countries of varying GC risk is not well-understood. We conducted a systematic review and meta-analysis to estimate the global prevalence of precursor lesions.

METHODS

We estimated the prevalence of atrophic gastritis (AG), gastric intestinal metaplasia (IM), and dysplasia in regions with low, medium, and high GC incidence. Because IM is an advanced manifestation of AG, we assessed the prevalence of less advanced precursors, regardless of the presence of more advanced lesions. Prevalence was sub-stratified by Helicobacter pylori infection, symptomatology, and period (<2000, 2000-2010, and >2010).

RESULTS

Among the 582 articles that underwent full-text review, 166 studies met inclusion criteria. The global prevalence estimates of AG, IM, and dysplasia were 25.4%, 16.2%, and 2.0%, respectively, on the basis of 126 studies that reported the prevalence of less advanced precursors, regardless of the presence of more advanced lesions. The prevalence of all precursor lesions was higher in high and medium compared with low GC incidence countries (P < .01). Prevalence of AG and IM was significantly higher among H pylori-infected individuals (P < .01) but not statistically different between symptomatic and asymptomatic individuals (P > .17). All precursors demonstrated a secular decrease in prevalence over time.

CONCLUSIONS

Gastric precursor lesions have differences in prevalence in regions with differential GC incidence and are associated with H pylori infection. Because of the substantial prevalence of precursor lesions in both symptomatic and asymptomatic individuals, symptomatic evaluation may not be sufficient to identify individuals at risk. These estimates provide important insights for tailoring GC prevention strategies.

One-off low-dose CT screening of positive nodules in lung cancer: A prospective community-based cohort study

BACKGROUND

To improve the early stage diagnosis and reduce the lung cancer (LC) mortality for positive nodule (PN) population, data on effectiveness of PN detection using one-off low-dose spiral computed tomography (LDCT) screening are needed to improve the PN management protocol. We evaluate the effectiveness of PN detection and developed a nomogram to predict LC risk for PNs.

METHODS

A prospective, community-based cohort study was conducted. We recruited 292,531 eligible candidates during 2012-2018. Individuals at high risk of LC based on risk assessment underwent LDCT screening and were divided into PN and non-PN groups. The effectiveness of PN detection was evaluated in LC incidence, mortality, and all-cause mortality. We performed subgroup analysis of characteristic variables for the association between PN and LC risk. A competing risk model was used to develop the nomogram.

RESULTS

Participants (n = 14901) underwent LDCT screening; PNs were detected in 1193 cases (8·0%). After a median follow-up of 6·1 years, 193 were diagnosed with LC (1·3%). Of these, 94 were in the PN group (8·0%). LC incidence, mortality, and all-cause mortality were significantly higher in the PN group (adjusted hazard ratios: 10.60 (7.91-14.20), 7.97 (5.20-12.20), and 1.94 (1.51-2.50), respectively). Additionally, various PN characteristics were associated with an increased probability of developing LC. The C-index value of the nomogram for predicting LC risk of PN individuals was 0·847.

CONCLUSIONS

The protocol of PNs management for improvement could focus on specific characteristic population and high-risk PN individuals by nomogram assessment.

Development and external validation of a nomogram to predict the risk of Upper gastrointestinal precancerous lesions in a non-high-incidence area

BACKGROUND

Upper gastrointestinal precancerous lesions (UGPL) is the major preventable disease in non-high-incidence area. A prognostic nomogram was constructed to predict and identity susceptible population of UGPL before endoscope screening.

METHODS

We recruited 300 ,016 eligible participants for upper gastrointestinal cancer (UGC) screening aged 40-74 years from two cities in Hunan province from 2012 to 2019. Individuals at high risk of UGC on basis of questionnaire estimation underwent endoscopic screening. Participants in two cities accepting endoscopy were used as training and external validation cohorts, respectively. A nomogram was developed based on independent prognostic factors of UGPL determined in multivariable logistic regression analysis.

RESULTS

Of 35, 621 with high risk for UGC, 10, 364 subjects undertook endoscopy (participation rate of 29.1%). The detection rate for UGPL was 4.55%. The nomogram showed that age, gender, mental trama, picked food, and atrophic gastritis history in a descending order were significant contributors to UGPL risk. The C-index value of internal and external validation of the model is 0.612 and 0.670, respectively. The calibration data for UGPL showed optimal agreement between the nomogram prediction and actual observation. Furthermore, high-risk and low-risk group divided based on score from the nomogram predicted a significantly distinct detection rate.

CONCLUSION

The nomogram provides screening workers a simple and accurate tool for identifying individuals at a higher risk of UGPL as primary screening before endoscopy among Chinese population in non-high-risk areas, thus reducing the incidence of UGC by improving the UGPL detection.