Evidence map›Paper›PMID 39697226›Full record

ArticleFrontiers in oncology2024

High-intensity focused ultrasound (HIFU) assisted by a rectal Foley catheter for the treatment of recurrent mucinous ovarian cancer: a case report and literature review.

Xiaoyin Guo, Wei Liu, Kun Zhou, Hui Zhu, Lu Pan, Chunping Feng, Ling Liu

Abstract readCase Reports
In one paragraph

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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

7 authors.

Xiaoyin GuoClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Wei LiuClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Kun ZhouClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Hui ZhuClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Lu PanDepartment of Rehabilitation Medicine, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Chunping FengClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Ling LiuClinical Center for Tumor Therapy, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

​Mucinous ovarian cancer (MOC) is characterized by high malignancy, poor prognosis and a high recurrence rate. Surgical adjuvant chemotherapy is the main treatment for MOC. The recurrence rate of advanced mucinous ovarian cancer following surgery is significantly high, with limited efficacious treatment options available. Moreover, chemotherapy alone results in low sensitivity in this context. High-intensity focused ultrasound (HIFU) not only efficiently ablates targeted tumor lesions but also elicits an immune response within the body and increases tumor cell susceptibility to drugs, thus increasing therapeutic effectiveness. We report a case of recurrent mucinous ovarian cancer treated with HIFU combined with chemotherapy, which effectively controlled tumor growth and prolonged patient survival. High-intensity focused ultrasound in combination with chemotherapy for the treatment of recurrent and surgically difficult ovarian cancer could provide new treatment strategies.

Indexed as

chemotherapycombined therapyhigh-intensity focused ultrasoundmucinous ovarian cancertumor recurrence

Identifiers

PMID39697226
PMCPMC11652346

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.