Evidence map›Paper›PMID 31860991›Full record

ArticleMedicine2019

A simple screening score to predict diabetes in cancer patients: A Korean nationwide population-based cohort study.

Ji-Su Kim, Sun-Hye Ko, Myong Ki Baeg, Kyung-Do Han

Open access · goldAbstract read
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.3field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Cancer and the risk of perioperative arterial ischaemic events.European heart journal. Quality of care & clinical outcomes · 2024
    Article
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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

4 authors at 4 institutions in 1 country.

Ji-Su KimDepartment of Nursing, Chung-Ang University, Seoul.
Sun-Hye KoDepartment of Internal Medicine, Inje University Haeundae Paik Hospital, Inje University College of Medicine, Busan.
Myong Ki BaegMyong Ki Baeg, Department of Internal Medicine, International St. Mary's Hospital, College of Medicine, Catholic Kwandong University, Incheon.
Kyung-Do HanDepartment of Biostatistics, The Catholic University of Korea, Seoul, Republic of Korea.
Catholic Kwandong University · KRCatholic University of Korea · KRChung-Ang University · KRInje University Haeundae Paik Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many cancer patients develop diabetes, which may result in reduction of chemotherapy effectiveness and increased infection risk and cardiovascular mortality. Diabetes may also increase the risks of chemotherapy-related toxicity and post-operative mortality, or represent an obstacle to optimal cancer treatment. However, the clinical predictors of diabetes in cancer patients remain largely unknown. Therefore, the aim of our study was to evaluate the risk factors for developing diabetes and construct a nomogram to predict diabetes in cancer patients.We investigated patients from a national sample cohort obtained from the Korea National Health Insurance Service (KNHIS), which included 2% of the Korean population. Patients who had undergone routine medical evaluation by the KNHIS between 2004 and 2008 and been hospitalized due to cancer (ICD-10 codes C00-97) during the past 3 years were included. After excluding patients with type 2 diabetes and missing data, 10,899 patients were enrolled and followed-up until 2013. A total of 7630 (70%) patients were assigned as the training cohort and used to construct the nomogram which was based on a multivariable logistic regression model. The remaining patients (n = 3269) were used as the validation cohort.The incidence rate of diabetes was 12.1 per 1000 person-years over a mean follow-up of 6.6 ± 1.8 years. Significant risk factors for developing diabetes were age, sex, obesity, fasting plasma glucose, hypertension, and hypercholesterolmia. A nomogram was constructed using these variables and internally validated. The area under the curve was 0.70 (95% confidence interval, .666-.730, P < .0001) and the calibration plot showed agreement between the actual and nomogram-predicted diabetes probabilities.The nomogram developed in this study is easy to use and convenient for identifying cancer patients at high-risk for type 2 diabetes, enabling early type 2 diabetes screening and management.

Indexed as

Risk AssessmentAgedAge FactorsBlood GlucoseCohort StudiesDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansHypercholesterolemiaHypertensionIncidenceMaleNeoplasmsNomogramsObesityBlood Glucose

Identifiers

PMID31860991
PMCPMC6940131
OpenAlexW2996252973

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.