Evidence map›Paper›PMID 41103419›Full record

SynthesisFrontiers in immunology2025

Efficacy and safety of pembrolizumab for the treatment of advanced or recurrent ovarian cancer: a meta-analysis based on single-arm studies.

Xiaodong Mi, Liming Tan, Tong Lin, Yimin Yang, Hongmei Liu, Fei Tuo

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
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.

Xiaodong MiDepartment of Obstetrics and Gynecology, People's Hospital of Xiangxi Tujia and Miao Autonomous Prefecture, First Affiliated Hospital of Jishou University, Jishou, Hunan, China.
Liming TanDepartment of Nursing, Medical College of Jishou University, Jishou, Hunan, China.
Tong LinDepartment of Obstetrics and Gynecology, People's Hospital of Xiangxi Tujia and Miao Autonomous Prefecture, First Affiliated Hospital of Jishou University, Jishou, Hunan, China.
Yimin YangDepartment of Obstetrics and Gynecology, The Third Xiangya Hospital of Central South University, Changsha, Hunan, China.
Hongmei LiuDepartment of Obstetrics and Gynecology, Yongshun County People's Hospital, Yongshun, Hunan, China.
Fei TuoDepartment of Obstetrics and Gynecology, People's Hospital of Xiangxi Tujia and Miao Autonomous Prefecture, First Affiliated Hospital of Jishou University, Jishou, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Ovarian cancer is a common malignant tumor of the female reproductive system, and traditional treatments are unsatisfactory due to its intraperitoneal spreading mechanism and its biologic characteristic of being prone to drug resistance. Pembrolizumab has demonstrated high objective remission and overall survival rates in a variety of solid tumors, and clinical trials are now available to explore its efficacy in the treatment of ovarian cancer. The objective of this systematic review and meta-analysis was to synthesize the findings of multiple clinical studies in order to evaluate the effectiveness and safety of the immunotherapeutic agent Pembrolizumab in patients diagnosed with advanced or recurrent ovarian cancer. Methods: A comprehensive search of literature published up to 19 November 2024 was conducted in the following databases: PubMed, Embase, Cochrane Library, Web of Science, Ovid_medline, Scopus, and ProQuest. The outcomes related to the administration of pembrolizumab in patients with advanced or recurrent ovarian cancer were extracted, including objective remission rate (ORR), disease control rate (DCR), overall survival (OS), progression-free survival (PFS), and treatment-related adverse events (AEs). A further meta-analysis was then performed. Results: This meta-analysis comprised 625 patients across nine studies. A total of 617 patients were involved in the efficacy assessment, while 592 patients were included in the safety assessment. The pooled analysis indicated an ORR of 24% (95% confidence interval [CI], 0.13-0.35), a DCR of 63% (95% CI, 0.49-0.77), a median progression-free survival (mPFS) of 4.82 months (95% CI, 3.29-6.35), and a median overall survival (mOS) of 13.54 months (95% CI, 10.35-16.73). Subgroup analysis indicated that the ORR in the PD-L1-positive group was 24% (95% CI, 0.12-0.36), while the ORR in the PD-L1-negative group was 18% (95% CI, 0.09-0.27). No statistically significant difference was observed between the two groups. The ORR was 26% (95% CI, 0.13-0.33) for patients administered a 200 mg dose every three weeks (q3w), while it was 12% (95% CI, 0.02-0.30) for those receiving a 10 mg/kg dose every two weeks (q2w). The overall incidence of adverse reactions of any grade was 81% (95% CI, 0.71-0.91), whereas the incidence of grade 3 or higher adverse reactions was 32% (95% CI, 0.09-0.54). Conclusions: This meta-analysis indicates that pembrolizumab treatment for patients with advanced or recurrent ovarian cancer exhibits significant efficacy and an acceptable safety profile. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/ identifier CRD42024620116.

Indexed as

Antibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalImmune Checkpoint InhibitorsNeoplasm Recurrence, LocalOvarian NeoplasmsFemaleHumansTreatment OutcomeAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalImmune Checkpoint InhibitorspembrolizumabICISimmunotherapyovarian cancerPD-1pembrolizumab

Identifiers

PMID41103419
PMCPMC12521426

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.