Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model.
Chin J Cancer Res
; 32(5): 605-613, 2020 Oct 31.
Article
em En
| MEDLINE
| ID: mdl-33223755
ABSTRACT
OBJECTIVE:
This study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort.METHODS:
A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).RESULTS:
Totally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23-3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71-74.28) in a general population.CONCLUSIONS:
Our questionnaire-based model is effective at identifying high-risk individuals for gastric cancer.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Clinical_trials
/
Etiology_studies
/
Prognostic_studies
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Qualitative_research
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Risk_factors_studies
Idioma:
En
Revista:
Chin J Cancer Res
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
China