ReviewAdvances in ophthalmology practice and research
Personalized treatment concepts in extraocular cancer.
Review in Advances in ophthalmology practice and research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Correlation between ocular tumor distribution and age based on analysis of pathological specimens.American journal of translational research · 2026Article
- Merkel Cell Carcinoma: Evolving Therapeutics, Continued Challenges.Head & neck · 2025Review
- Enhancing the potency of CAR-T cells against solid tumors through transcription factor engineering.JCI insight · 2025Review
- [New systemic treatment approaches for malignant eyelid tumors].Die Ophthalmologie · 2025Review
- Validation of a portable three-dimensional imaging system for volumetric measurement in the periorbital region.Frontiers in medicine · 2025Article
- Targeted Drug Delivery in Periorbital Non-Melanocytic Skin Malignancies.Bioengineering (Basel, Switzerland) · 2024Review
- Global research trends in the treatment of squamous cell carcinoma over the past decade: A bibliometric analysis.Advances in ophthalmology practice and researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The periocular skin is neoplasms-prone to various benign and malignant. Periocular malignancies are more aggressive and challenging to cure and repair than those in other skin areas. In recent decades, immunotherapy has significantly advanced oncology, allowing the autoimmune system to target and destroy malignant cells. Skin malignancies, especially periocular tumors, are particularly sensitive to immunotherapy. This technique has dramatically impacted the successful treatment of challenging tumors. Main text: Extraocular cancers, including eyelid (basal cell carcinoma, squamous cell carcinoma, melanoma, merkel cell carcinoma), conjunctival tumors (conjunctival melanoma, ocular surface squamous neoplasia) and other rare tumors, are unique and challenging clinical situations. Several genetic alterations associated with the pathogenesis of these diseases have been identified, and molecular mechanism are essential for the development of the immunotherapy agents, such as Hedgehog pathway inhibitors (vismodegib and sonidegib) for basal cell carcinoma, BRAF/MEK inhibitors (vemurafenib, dabrafenib, and encorafenib) for melanoma, and immune checkpoint inhibitors (Avelumab, pembrolizumab) for Merkel cell carcinoma. Conclusions: The optimal treatment for periocular skin cancer depends on the type and size of the tumor and whether it involves orbital and adnexal structures. Adjuvant and neoadjuvant therapy with chemotherapy-targeted therapies and immune checkpoint inhibitors should be considered based on tumor type, tumor molecular profile, expected response rate, and candidacy for systemic treatment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.