Evidence map›Paper›PMID 34531687›Full record

ArticleCancer management and research2021

A Preliminary Study of the Complement Component 1q Levels in Predicting the Efficacy of Combined Immunotherapy in Patients with Lung Cancer.

Daoming Zhang, Yuan Li, Haoyue Li, Tian Tang, Yongfa Zheng, Xufeng Guo, Ximing Xu

Open access · goldAbstract read
In one paragraph

Article in Cancer management and research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% of its field
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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Complement system in tumor growth and metastases.British journal of cancer · 2026
    Review
  2. Review
  3. Article
  4. Inside-Out of Complement in Cancer.Frontiers in immunology · 2022
    Review
  5. 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 at 2 institutions in 1 country.

Daoming ZhangCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Yuan LiCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Haoyue LiDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Tian TangCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Yongfa ZhengCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Xufeng GuoCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Ximing XuCancer Center, Renmin Hospital of Wuhan University, Wuhan, People's Republic of China.
Wuhan University · CNRenmin Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the value of serum complement component 1q (C1q) levels in predicting the efficacy of combined immunotherapy in patients with lung cancer.

methodsA total of 42 patients with lung cancer who received combined immunotherapy in the cancer center of Renmin Hospital of Wuhan University were included in this study. The clinical data of serum C1q and lactate dehydrogenase (LDH) levels before and three weeks after immunotherapy were collected.

resultsResponse evaluation showed that the number of patients with complete response (CR), partial response (PR), stable disease (SD), and progressive disease (PD) was 0 (0%), 26 (61.9%), 14 (33.3%), and 2 (4.8%), respectively. The CR/PR group (patients with CR or PR) showed higher

conclusionHigh C1q levels before immunotherapy and increased C1q levels and decreased LDH levels 3 weeks afterward suggest good therapeutic effects of combined immunotherapy in patients with lung cancer. Serum C1q levels have certain clinical significance in predicting the efficacy of combined immunotherapy.

Indexed as

complement component 1qefficacy predictionimmunotherapy

Identifiers

PMID34531687
PMCPMC8439965
OpenAlexW3199548858

What OpenQuestion holds

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LicenceCC BY-NC
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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.