Evidence mapPaperPMID 42558813Full record

ArticleFrontiers in oncology2026

Plasma HPV ctDNA as a dynamic biomarker for treatment response and prognosis in locally advanced cervical cancer: protocol for a prospective cohort study.

Hailing Hou, Li Zhang, Chen Li, Miao Liu

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

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Hailing HouDepartment of Radiation Oncology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Li ZhangGynecologic Oncology Department, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Chen LiDepartment of Radiation Oncology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Miao LiuDepartment of Radiation Oncology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute & Hospital, National Clinical Research Center for Cancer, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Locally advanced cervical cancer (LACC) remains a major global health burden, and current imaging-based assessment after standard concurrent chemoradiotherapy (CCRT) is limited by delayed detection of treatment failure and poor sensitivity for microscopic residual disease. Circulating human papillomavirus DNA (HPV ctDNA) represents a tumor-specific biomarker with potential for real-time treatment monitoring. This prospective cohort study aims to evaluate whether dynamic monitoring of plasma HPV ctDNA can predict treatment response and prognosis in patients with LACC receiving CCRT. Methods/design: This single-center, observational cohort study will enroll 57 patients with histologically confirmed LACC (FIGO 2018 stage IB2-IVA) and baseline high-risk HPV infection. All patients will receive standard CCRT including external beam radiotherapy (45-50.4 Gy), concurrent weekly cisplatin (40 mg/m²), and intracavitary brachytherapy. Peripheral blood samples (10 mL) will be collected at five predefined time points: baseline (T0), mid-treatment (T1), end of CCRT (T2), 3 months post-CCRT (T3), and every 6 months thereafter for 24 months. Plasma HPV ctDNA will be quantified using droplet digital PCR targeting HPV16/18 E6/E7 genes. The primary endpoint is progression-free survival (PFS), comparing patients with detectable versus undetectable ctDNA at 3 months post-CCRT. Conclusion: This study will provide prospective evidence for HPV ctDNA as a minimally invasive biomarker for treatment monitoring and prognostic stratification in LACC, potentially informing future risk-adapted therapeutic strategies.

Indexed as

biomarkercervical cancerchemoradiotherapycirculating tumor DNAhuman papillomavirusliquid biopsy

Identifiers

PMID42558813
PMCPMC13438198

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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 Socratic graph.