Evidence map›Paper›PMID 39123101›Full record

ArticleBMC geriatrics2024

High cardiovascular mortality risk among older merkel cell carcinoma patients.

Jia-Nan Huang, Hai Yu, Xichun Xia, Wai-Kit Ming, Shuai Wu, Leong Nga Cheng, Lee ALice Yu Ying, Jinrong Zhang, Yuzhen Jiang, Wenhui Chen and 3 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

13 authors.

Jia-Nan Huang *Department of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Hai Yu *Department of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Xichun Xia *Institute of Biomedical Transformation, Jinan University, Guangzhou, China.
Wai-Kit MingDepartment of Infectious Diseases and Public Health, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China.
Shuai WuDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Leong Nga ChengDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Lee ALice Yu YingHong Kong Medical and Education Training Limited, Kowloon, Hong Kong SAR, China.
Jinrong ZhangDepartment of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China.
Yuzhen JiangRoyal Free Hospital & University College London, London, UK.
Wenhui ChenShanghai Aige Medical Beauty Clinic Co., Ltd.(Agge), Shanghai, China.
Qiqi Zhao *Department of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China. zqq19950330@163.com.
Jun Lyu *Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China. lyujun2020@jnu.edu.cn.
Liehua Deng *Department of Dermatology, The First Affiliated Hospital of Jinan University & Jinan University Institute of Dermatology, Guangzhou, China. Liehuadeng@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePrevious research has primarily focused on the incidence and mortality rates of Merkel cell carcinoma (MCC), neglecting the examination of cardiovascular mortality (CVM) risk among survivors, particularly older patients. This study aims to assess the risk of CVM in older individuals diagnosed with MCC.

methodsData pertaining to older MCC patients were obtained from the Surveillance, Epidemiology, and End Results database (SEER). CVM risk was measured using standardized mortality ratio (SMR) and cumulative mortality. Multivariate Fine-Gray's competing risk model was utilized to evaluate the risk factors contributing to CVM.

resultsAmong the study population of 2,899 MCC patients, 465 (16.0%) experienced CVM during the follow-up period. With the prolongation of the follow-up duration, the cumulative mortality rate for CVM reached 27.36%, indicating that cardiovascular disease (CVD) became the second most common cause of death. MCC patients exhibited a higher CVM risk compared to the general population (SMR: 1.69; 95% CI: 1.54-1.86, p < 0.05). Notably, the SMR for other diseases of arteries, arterioles, and capillaries displayed the most significant elevation (SMR: 2.69; 95% CI: 1.16-5.29, p < 0.05). Furthermore, age at diagnosis and disease stage were identified as primary risk factors for CVM, whereas undergoing chemotherapy or radiation demonstrated a protective effect.

conclusionThis study emphasizes the significance of CVM as a competing cause of death in older individuals with MCC. MCC patients face a heightened risk of CVM compared to the general population. It is crucial to prioritize cardiovascular health starting from the time of diagnosis and implement personalized CVD monitoring and supportive interventions for MCC patients at high risk. These measures are essential for enhancing survival outcomes.

Indexed as

Carcinoma, Merkel CellCardiovascular DiseasesSkin NeoplasmsAgedAged, 80 and overFemaleHumansMaleRisk AssessmentRisk FactorsSEER ProgramUnited StatesAnd End results database (SEER)Cardiovascular disease (CVD)Cardiovascular mortality (CVM)Competing risk modelCumulative mortalityEpidemiologyMerkel cell carcinoma (MCC)Risk factorStandardized mortality ratio (SMR)Surveillance

Identifiers

PMID39123101
PMCPMC11312700

What OpenQuestion holds

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Registered trials

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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.