Association of diabetes mellitus with early-onset colorectal cancer: A systematic review and meta-analysis of 19 studies including 10 million individuals and 30,000 events

Ta, Hoang Dang Khoa; Nguyen, Nam Nhat; Ho, Dang Khanh Ngan; Nguyen, Hieu D.; Ni, Yi-Chun; Yee, K.; Pan, Syu-Ruei; Nguyen, Hung Song; Thai, Trang Thi Bao; Chen, Ming‐Jenn

doi:10.1016/j.dsx.2023.102828

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…In a recently published systematic review and meta-analysis, Khoa Ta et al [ 37 ] analyzed 33359 early-CRC cases and 14259289 controls included in 12 studies. A significant positive correlation was found between diabetes mellitus and an increased risk of early-CRC which suggests that diabetes mellitus is a risk factor for the development of early-CRC.…”

Section: Etiopathogenetic Factorsmentioning

confidence: 99%

“…A significant positive correlation was found between diabetes mellitus and an increased risk of early-CRC which suggests that diabetes mellitus is a risk factor for the development of early-CRC. The higher prevalence of diabetes mellitus among younger adults observed may contribute to the increasing incidence of early-CRC[ 37 ]. It is therefore concluded that decisive interventions to reduce this two-way risk should be studied more extensively as this will contribute to the development of effective prevention and treatment strategies.…”

Section: Etiopathogenetic Factorsmentioning

confidence: 99%

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Early-onset gastrointestinal cancer: An epidemiological reality with great significance and implications

Triantafillidis,

Georgiou,

Konstadoulakis

et al. 2024

World J Gastrointest Oncol

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During the last few years, epidemiological data from many countries suggest that the incidence and prevalence of many cancers of the digestive system are shifting from the older to the younger ages, the so-called “early-onset cancer”. This is particularly evident in colorectal cancer and secondarily in other malignant digestive neoplasms, mainly stomach and in a lesser degree pancreas, and biliary tract. It should be emphasized that data concerning digestive neoplasms, except for those referring to the colon and stomach, could be characterized as rather insufficient. The exact magnitude of the shift in younger ages is expected to become clearer shortly, as long as relevant epidemiological data from many parts of the world would be available. The most important question concerns the etiology of this phenomenon, since its magnitude cannot be explained solely by the better diagnostic methodology and the preventive programs applied in many countries. The existing data support the assumption that a number of environmental factors may play a primary role in influencing carcinogenesis, sometimes from childhood. Changes that have appeared in the last decades related mainly to eating habits, consistency of gut microbiome and an increase of obese people interacting with genetic factors, ultimately favor the process of carcinogenesis. Even these factors however, are not entirely sufficient to explain the age-related changes in the frequency of digestive neoplasms. Studies of the individual effect of each of the already known factors or factors likely to be involved in the etiology of this phenomenon and studies using state-of-the-art technologies to accurately determine the degree of the population exposure to these factors are required. In this article, we attempt to describe the epidemiological data supporting the age-shifting of digestive malignancies and their possible pathogenesis. Finally, we propose some measures regarding the attitude of the scientific community to this alarming phenomenon.

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Section: Etiopathogenetic Factorsmentioning

confidence: 99%

Section: Etiopathogenetic Factorsmentioning

confidence: 99%

Early-onset gastrointestinal cancer: An epidemiological reality with great significance and implications

Triantafillidis,

Georgiou,

Konstadoulakis

et al. 2024

World J Gastrointest Oncol

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“…Identifying clinically significant subgroups is a cornerstone of personalized medicine, enabling the tailoring of treatments to patient characteristics that influence therapeutic outcomes. In clinical practice, a subset of patients are more likely to gain benefit from the current treatment, outweighing the harm [ 70 ], whereas some are at a greater probability of the opposing situation [ 71 ]. Identifying a subgroup of patients with a unique eigenvalue or effect emerges continuously across a broad range of medical fields [ 72 ], often with the goal of delineating patient risk stratification and facilitating optimal decision-making for varied patients.…”

Section: Aiming To Identify Clinically Significant Subgroupsmentioning

confidence: 99%

“…There are two ways in which one can use a variable to define a subgroup. The first is to directly use key baseline characteristics, including demographic variables such as age [ 76 ] and gender [ 77 , 78 ], as well as important clinical phenotypes [ 79 ], such as disease severity [ 71 ] and comorbidities [ 80 ], to define the subgroups in a separate or combined manner. By conducting subgroup analyses based on natural features, it is possible to uncover the heterogeneity of the intervention effects among target patients, thus enabling the selection of those who would most likely benefit from the intervention.…”

Section: Aiming To Identify Clinically Significant Subgroupsmentioning

confidence: 99%

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Qiao,

Chen,

Qian

et al. 2024

J Transl Med

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Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

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Risk factors for colorectal cancer in Morocco: A systematic review

Amsdar,

Arechkik,

Touaddi

et al. 2024

Clinical Epidemiology and Global Health

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Association of diabetes mellitus with early-onset colorectal cancer: A systematic review and meta-analysis of 19 studies including 10 million individuals and 30,000 events

Cited by 6 publications

References 20 publications

Early-onset gastrointestinal cancer: An epidemiological reality with great significance and implications

Early-onset gastrointestinal cancer: An epidemiological reality with great significance and implications

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Risk factors for colorectal cancer in Morocco: A systematic review

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