Evidence map›Paper›PMID 41764360›Full record

ArticleMedical science monitor : international medical journal of experimental and clinical research2026

Editorial: Recently Identified Global Trends in Cancer Incidence and Mortality and Modifiable Cancer Risk Factors.

Dinah V Parums

Abstract readEditorial
In one paragraph

Article in Medical science monitor : international medical journal of experimental and clinical research, 2026. 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

1 author.

Dinah V ParumsScience Editor, Medical Science Monitor, International Scientific Information, Inc., Melville, NY, USA.ORCID 0000-0003-0145-5464

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently analysed data from global population and epidemiological studies from 2022 and 2023 have shown that global incidence and mortality rates from cancer are escalating due to population growth and an increasingly aging population. There were up to 20 million new cancer diagnoses and 9.7 million deaths from cancer in 2022, with projections for cancer diagnoses to reach 35.3 million by 2050. However, recent analysis of the 2022 GLOBOCAN estimates of global and national cancer burden data by gender for 36 cancer sites in 185 countries showed that out of an estimated 18.7 million new cancer cases, 37.8% (7.1 million) were associated with 30 modifiable risk factors: 45.4% (4.3 million) in men and 29.7% (2.7 million) in women. Lung, stomach, and cervical cancer were the leading preventable cancers, and the main preventable risk factors for cancer included tobacco smoking (15.1%), infections with oncogenic viruses (10.2%), and alcohol consumption (3.2%). A third important recent finding is that while mortality rates from cancer have been falling in high-income countries such as the US, possibly due to better screening, diagnosis, and management, cancer incidence and mortality are increasing in low-income and middle-income countries. Finally, some recent lessons have been learned from the COVID-19 pandemic on cancer 'displacement' due to the disruption of cancer diagnostic and management services. This editorial presents four recently identified global trends in cancer incidence and mortality, including modifiable cancer risk factors that may affect individual lifestyle choices and inform global public health policy.

Indexed as

NeoplasmsCOVID-19FemaleGlobal HealthHumansIncidenceMaleRisk Factors

Identifiers

PMID41764360
PMCPMC12962391

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.