Evidence map›Paper›PMID 34584376›Full record

ArticleChinese journal of cancer research = Chung-kuo yen cheng yen chiu2021

Comparative yield and efficiency of strategies based on risk assessment and fecal immunochemical test in colorectal cancer screening: A cross-sectional population-based analysis.

Hongda Chen, Le Wang, Ming Lu, Chen Zhu, Yunfeng Zhu, Weihua Ma, Xinmin Chen, Lingbin Du, Wanqing Chen

Open access · diamondAbstract read
In one paragraph

Article in Chinese journal of cancer research = Chung-kuo yen cheng yen chiu, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.0field-weighted citation impact, top 21% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Hongda ChenOffice of 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.
Le WangDepartment of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou 310005, China.
Ming LuOffice of 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.
Chen ZhuDepartment of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou 310005, China.
Yunfeng ZhuHaining Hospital of Traditional Chinese Medicine, Haining 314499, China.
Weihua MaHaining Hospital of Traditional Chinese Medicine, Haining 314499, China.
Xinmin ChenHaining Hospital of Traditional Chinese Medicine, Haining 314499, China.
Lingbin DuDepartment of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou 310005, China.
Wanqing ChenOffice of 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.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNJinzhou Kangning Hospital · CNZhejiang Cancer Hospital · CNCancer Hospital of Chinese Academy of Medical Sciences · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveIntegration of risk stratification into fecal immunochemical test (FIT) might aid in the suboptimal detection of advanced neoplasms by FIT in colorectal cancer (CRC) screening. A comparative study was conducted to evaluate the participation and diagnostic yield of the parallel combination of questionnaire-based risk assessment (QRA) and FIT, FIT-only and QRA-only strategies in a CRC screening program in China.

methodsThe study included 29,626 individuals aged 40-74 years and invited to participate in a CRC screening program in China. Participants were first invited to undertake QRA and one-time FIT (OC-sensor). Participants with positive QRA or FIT were deemed to be high-risk individuals who were recommended for subsequent colonoscopy. Participation, detection rate, and resource demand for colonoscopy were calculated and compared.

resultsOf the 29,626 invitees, 20,203 completed the parallel combination, 8,592 completed the QRA-only, and 11 completed the FIT-only strategy. For the parallel combination, FIT-only, and QRA-only strategies, the overall positivity rates were 10.2% (2,928/28,806), 5.4% (1,096/20,214), and 6.8% (1,944/28,795), respectively; the yield of advanced neoplasm per 10,000 invitees were 46.9 [95% confidence interval (95% CI): 39.8-55.4], 36.8 (95% CI: 30.5-44.4), and 12.2 (95% CI: 8.8-16.8), respectively; the positive predictive values for detecting advanced neoplasms among participants who completed colonoscopy were 4.7% (95% CI: 4.0%-5.6%), 9.9% (95% CI: 8.3%-11.9%), and 1.9% (95% CI: 1.3%-2.6%), respectively; the number of colonoscopies required to detect one advanced neoplasm was 11.4 (95% CI: 9.8-13.4), 5.7 (95% CI: 4.8-6.7), and 28.4 (95% CI: 20.7-39.2), respectively.

conclusionsThe parallel combination of QRA and FIT did not show superior efficacy for detecting advanced neoplasm compared with FIT alone in this CRC screening program.

Indexed as

Colorectal neoplasmfecal immunochemical testrisk stratificationscreening

Identifiers

PMID34584376
PMCPMC8435825
OpenAlexW3201348566

What OpenQuestion holds

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Registered trials

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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.