Evidence map›Paper›PMID 38354707›Full record

ReviewRespiration; international review of thoracic diseases2024

Clinical Practice of Photodynamic Therapy for Non-Small Cell Lung Cancer in Different Scenarios: Who Is the Better Candidate?

Wen Sun, Qi Zhang, Xi Wang, Zhou Jin, Yuan Cheng, Guangfa Wang

Abstract readReview
In one paragraph

Review in Respiration; international review of thoracic diseases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
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  4. Article
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  6. Review
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  8. Review
  9. Self-illuminating liposome-derivedActa pharmaceutica Sinica. B · 2025
    Article
  10. Review
  11. 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

6 authors.

Wen SunDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China, Sun_Wenny@126.com.
Qi ZhangDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
Xi WangDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
Zhou JinDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
Yuan ChengDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.
Guangfa WangDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPhotodynamic therapy (PDT) is a relatively safe and highly selectivity antitumor treatment, which might be increasingly used as a supplement to conventional therapies. A clinical overview and detailed comparison of how to select patients and lesions for PDT in different scenarios are urgently needed to provide a basis for clinical treatment. SUMMARY: This review demonstrates the highlights and obstacles of applying PDT for lung cancer and underlines points worth considering when planning to initiate PDT. The aim was to make out the appropriate selection and help PDT develop efficacy and precision through a better understanding of its clinical use. KEY MESSAGES: Increasing evidence supports the feasibility and safety of PDT in the treatment of non-small cell lung cancer. It is important to recognize the factors that influence the efficacy of PDT to develop individualized management strategies and implement well-designed procedures. These important issues should be worth considering in the present and further research.

Indexed as

Carcinoma, Non-Small-Cell LungLung NeoplasmsPhotochemotherapyHumansCandidate selectionLung cancerPhotodynamic therapyTreatment efficacy

Identifiers

PMID38354707
PMCPMC10997268

What OpenQuestion holds

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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.