Evidence map›Paper›PMID 41703988›Full record

ArticleActa dermato-venereologica2026

Clinical and Pathological Characteristics of Skin Cancer Patients at Southern Medical University, Guangzhou, China.

Siqi Li, Jingwen Zou, Rongyi Chen, Lian Zhang

Abstract read
In one paragraph

Article in Acta dermato-venereologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Siqi LiDermatology Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
Jingwen ZouDermatology Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
Rongyi ChenDermatology Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.
Lian ZhangDermatology Hospital, Southern Medical University, Guangzhou, Guangdong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The incidence of skin cancer is increasing in China, yet large-scale clinical and pathological data from China remain scarce. A retrospective analysis was conducted of 648 histopathologically confirmed skin cancer cases diagnosed at the Dermatology Hospital, Southern Medical University from January 2020 to July 2023. Patient demographics, tumour distribution, histological subtypes, and treatment approaches were evaluated. Squamous cell carcinoma (31.9%) and basal cell carcinoma (31.2%) were the most prevalent, followed by cutaneous lymphomas (13.9%), dendritic cell and histiocytic neoplasms (13.3%), and melanoma (9.7%). Over half of the patients (53.5%) were aged ≥ 60 years. basal cell carcinoma and squamous cell carcinoma primarily involved the head and neck, while acral sites were dominant in melanoma (79.4%). Most cases of both basal cell carcinoma and squamous cell carcinoma were managed surgically, with surgical treatment performed in 95.5% of basal cell carcinomas and 94.2% of squamous cell carcinomas. Skin cancers in China predominantly affect older adults and commonly involve sun-exposed areas. Basal cell carcinoma is typically managed surgically due to its low-risk nature, while squamous cell carcinoma demonstrates clinical heterogeneity, warranting varied treatment strategies. The higher proportion of cutaneous lymphomas among younger patients highlights the need for age-specific diagnostic and therapeutic considerations.

Indexed as

Basal Cell CarcinomaMelanomaSkin NeoplasmsAdolescentAdultAgedAged, 80 and overAge DistributionChildChinaCutaneous Squamous Cell CarcinomaFemaleHumansIncidenceMaleMiddle Aged

Identifiers

PMID41703988
PMCPMC12924091

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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.