Evidence map›Paper›PMID 38899940›Full record

ArticleCancer biology & medicine2024

Effectiveness of colorectal cancer screening integrating non-genetic and genetic risk: a prospective study based on UK Biobank data.

Yu Zhang, Chao Sheng, Zhangyan Lyu, Hongji Dai, Fangfang Song, Fengju Song, Yubei Huang, Kexin Chen

Abstract read
In one paragraph

Article in Cancer biology & medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yu ZhangDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Chao ShengDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Zhangyan LyuDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Hongji DaiDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Fangfang SongDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Fengju SongDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.
Yubei HuangDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.ORCID 0000-0002-6299-7112
Kexin ChenDepartment of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China.ORCID 0000-0003-4248-7681

Funding

National Key Research and Development Program of China 2021YFC2500400National Natural Science Foundation of China 82172894
6 · The paper itself

Abstract

objectiveFew studies have evaluated the benefits of colorectal cancer (CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model (QCancer-10) and a 139-variant polygenic risk score to evaluate the effectiveness of screening on CRC incidence and mortality.

methodsWe applied the integrated model to calculate 10-year CRC risk for 430,908 participants in the UK Biobank, and divided the participants into low-, intermediate-, and high-risk groups. We calculated the screening-associated hazard ratios (HRs) and absolute risk reductions (ARRs) for CRC incidence and mortality according to risk stratification.

resultsDuring a median follow-up of 11.03 years and 12.60 years, we observed 5,158 CRC cases and 1,487 CRC deaths, respectively. CRC incidence and mortality were significantly lower among screened than non-screened participants in both the intermediate- and high-risk groups [incidence: HR: 0.87, 95% confidence interval (CI): 0.81-0.94; 0.81, 0.73-0.90; mortality: 0.75, 0.64-0.87; 0.70, 0.58-0.85], which composed approximately 60% of the study population. The ARRs (95% CI) were 0.17 (0.11-0.24) and 0.43 (0.24-0.61), respectively, for CRC incidence, and 0.08 (0.05-0.11) and 0.24 (0.15-0.33), respectively, for mortality. Screening did not significantly reduce the relative or absolute risk of CRC incidence and mortality in the low-risk group. Further analysis revealed that screening was most effective for men and individuals with distal CRC among the intermediate to high-risk groups.

conclusionsAfter integrating both genetic and non-genetic factors, our findings provided priority evidence of risk-stratified CRC screening and valuable insights for the rational allocation of health resources.

Indexed as

Biological Specimen BanksColorectal NeoplasmsEarly Detection of CancerAdultAgedFemaleGenetic Predisposition to DiseaseHumansIncidenceMaleMiddle AgedProspective StudiesRisk AssessmentRisk FactorsUK BiobankUnited KingdomColorectal cancerincidencemortalitypolygenic risk scorescreening

Identifiers

PMID38899940
PMCPMC11359493

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.