Evidence map›Paper›PMID 38571507›Full record

ArticleFrontiers in oncology2024

Assessing of case-cohort design: a case study for breast cancer patients in Xinjiang, China.

Mengjuan Wu, Tao Zhang, Chunjie Gao, Ting Zhao, Lei Wang, Gang Sun

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Mengjuan WuCountry College of Public Health, Xinjiang Medical University, Urumqi, China.
Tao ZhangCountry College of Public Health, Xinjiang Medical University, Urumqi, China.
Chunjie GaoCountry College of Public Health, Xinjiang Medical University, Urumqi, China.
Ting ZhaoDepartment of Medical Record Management, The Affiliated Cancer Hospital of Xinjiang Medical University, Urumqi Xinjiang, China.
Lei WangDepartment of Medical Engineering and Technology, Xinjiang Medical University, Urumqi Xinjiang, China.
Gang SunXinjiang Cancer Center/ Key Laboratory of Oncology of Xinjiang Uyghur Autonomous Region, Urumqi, Xinjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the effectiveness and clinical value of case-cohort design and determine prognostic factors of breast cancer patients in Xinjiang on the basis of case-cohort design. Methods: The survival data with different sample characteristics were simulated by using Cox proportional risk models. To evaluate the effectiveness for the case-cohort, entire cohort, and simple random sampling design by comparing the mean, coefficient of variation, etc., of covariate parameters. Furthermore, the prognostic factors of breast cancer patients in Xinjiang were determined based on case-cohort sampling designs. The models were comprehensively evaluated by likelihood ratio test, the area under the receiver operating characteristic curve (AUC), and Akaike Information Criterion (AIC). Results: In a simulations study, the case-cohort design shows better stability and improves the estimation efficiency when the censored rate is high. In the breast cancer data, molecular subtypes, T-stage, N-stage, M-stage, types of surgery, and postoperative chemotherapy were identified as the prognostic factors of patients in Xinjiang. These models based on the different sampling designs both passed the likelihood ratio test ( Conclusion: Simulations study confirmed the effectiveness of case-cohort design and further determined the prognostic factors of breast cancer patients in Xinjiang based on this design, which presented the practicality of case-cohort design in actual data.

Indexed as

breast cancercase-cohort designCox proportional hazards modelsimulations studysurvival prognosis

Identifiers

PMID38571507
PMCPMC10987809

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