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Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model.
Cao, Maomao; Li, He; Sun, Dianqin; Lei, Lin; Ren, Jiansong; Shi, Jufang; Li, Ni; Peng, Ji; Chen, Wanqing.
Afiliação
  • Cao M; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Li H; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Sun D; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Lei L; Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China.
  • Ren J; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Shi J; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Li N; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
  • Peng J; Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China.
  • Chen W; Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Chin J Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Etiology_studies / Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Chin J Cancer Res Ano de publicação: 2020 Tipo de documento: Article País de afiliação: China