Evidence map›Paper›PMID 39600631›Full record

ArticleFrontiers in oncology2024

Causes of death after oral cancer diagnosis: a population based study.

Zhenyu Jiang, Li Shao, Jie Zhou, Xuwen Shao, Chao Shen

Abstract read
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Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

5 authors.

Zhenyu JiangDepartment of Nephrology, The First People's Hospital of Huzhou, The First Affiliated Hospital of Huzhou Teachers College, Huzhou, China.
Li ShaoDepartment of Stomatology, The First People's Hospital of Huzhou, The First Affiliated Hospital of Huzhou Teachers College, Huzhou, China.
Jie ZhouDepartment of Oncology, Huzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, China.
Xuwen ShaoDepartment of Physical Examination Center, Zhejiang Xinda Hospital, Huzhou, China.
Chao ShenDepartment of Nephrology, The First People's Hospital of Huzhou, The First Affiliated Hospital of Huzhou Teachers College, Huzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nowadays, the number of oral cancer survivors is increasing, emphasizing the importance of thoroughly understanding diverse causes of death in oral cancer survivors. Our study aimed to investigate the distribution of causes of death after oral cancer diagnosis. Methods: Eligible patients were identified between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. We calculated the number of deaths in different demographic and clinicopathological variables during each follow-up period. Standardized mortality ratios(SMRs) were generated for each cause of death after oral cancer diagnosis. Results: A total of 30538 patients diagnosed with oral cancer were included, and 17654 deaths were reported during follow-up period. 27.08% of deaths were caused by non-caner reasons. The proportion of non-cancer related deaths increased with the extension of survival time, and non-cancer death accounted for 57.93% of all deaths when followed up more than 10 years. The most common non-cancer cause of death was cardiovascular disease (SMR 4.68#; 95%CI 4.46-4.92). Conclusions: Non-cancer causes of death should not be ignored in oral cancer patients. For oral cancer survivors, multidisciplinary follow-up strategy should be recommended to achieve longer survival time.

Indexed as

cause of deathoral cancerSEERstandardized mortality ratios (SMRs)survival

Identifiers

PMID39600631
PMCPMC11588711

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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.