Evidence map›Paper›PMID 38477498›Full record

ArticleCancer medicine2024

Global burden, risk factors, and trends of non-Hodgkin lymphoma: A worldwide analysis of cancer registries.

Junjie Huang, Sze Chai Chan, Veeleah Lok, Lin Zhang, Don Eliseo Lucero-Prisno, Wanghong Xu, Zhi-Jie Zheng, Edmar Elcarte, Mellissa Withers, Martin C S Wong

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
7.6field-weighted citation impact, top 2% 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

21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Understanding the factors influencing quality of life among survivors of Non-Hodgkin lymphoma after completing primary treatment: a systematic review.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  18. Neoplasia in the dromedary camel: a review (Frontiers in veterinary science · 2025
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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

10 authors at 8 institutions in 7 countries.

Junjie HuangThe Jockey Club School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0003-2382-4443
Sze Chai ChanThe Jockey Club School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong SAR, China.
Veeleah LokDepartment of Global Public Health, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden.
Lin ZhangSuzhou Industrial Park Monash Research Institute of Science and Technology, Suzhou, China.
Don Eliseo Lucero-PrisnoDepartment of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK.
Wanghong XuSchool of Public Health, Fudan University, Shanghai, China.ORCID 0000-0003-2045-2218
Zhi-Jie ZhengDepartment of Global Health, School of Public Health, Peking University, Beijing, China.
Edmar ElcarteUniversity of the Philippines, Manila, Philippines.
Mellissa WithersDepartment of Population and Health Sciences, Institute for Global Health, University of Southern California, Los Angeles, California, USA.
Martin C S WongThe Jockey Club School of Public Health and Primary Care, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong SAR, China.ORCID 0000-0001-7706-9370
Chinese University of Hong Kong · HKFudan University · CNKarolinska University Hospital · SELondon School of Hygiene & Tropical Medicine · GBPeking University · CNSuzhou Research Institute · CNUniversity of Southern California · USUniversity of the Philippines Manila · PH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-Hodgkin lymphoma (NHL) accounts for 90% of all malignant lymphomas. This study aimed to evaluate the global incidence, mortality, associated risk factors, and temporal trends of NHL by sex, age, and country.

methodsData from 185 countries globally were used for analysis. NHL incidence and mortality were collected via the GLOBOCAN (2020), CI5 series I-X, WHO mortality database, the Nordic Cancer Registries, and the SEER Program. The WHO Global Health Observatory provided country-level, age-standardized prevalence of lifestyle and metabolic risk factors. Trends were examined and reported based on average annual percentage change (AAPC) calculated using Joinpoint regression analysis. Incidence and AAPC are based on data for the last 10 years across countries.

resultsGlobally, age-standardized incidence and mortality rates for NHL were recorded at 5.8 and 2.6 per 100,000 individuals, respectively. At country-level, NHL incidence was significantly associated with various factors, including HDI (Human Development Index), GDP per capita, prevalence of tobacco and alcohol consumption, sedentary lifestyle, obesity, hypertension, diabetes and hypercholesterolaemia. Rising trend in NHL incidence was observed, with the highest increase recorded in Estonia (AAPC

conclusionsThis study indicates a rising trend of NHL incidence over the past decade- particularly in developed countries, older males, and younger populations. Further research should investigate deeper insights into specific etiology and prognosis of NHL across subtypes, and potential contributors towards these epidemiologic trends.

Indexed as

LymphomaLymphoma, Non-HodgkinFemaleGlobal HealthHumansIncidenceMaleRegistriesRisk Factorsincidencemortalitynon-Hodgkin lymphomarisk factorstemporal trends

Identifiers

PMID38477498
PMCPMC10935876
OpenAlexW4392750095

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.