Evidence map›Paper›PMID 33563114›Full record

SynthesisTechnology in cancer research & treatment

Prognostic Value of Pretreatment D-Dimer Level in Small-Cell Lung Cancer: A Meta-Analysis.

Jialong Li, Yan Wang, Jue Li, Guowei Che

Abstract readMeta-Analysis
In one paragraph

Synthesis in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

4 authors.

Jialong LiDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Yan WangDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Jue LiDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Guowei CheDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, People's Republic of China.ORCID 0000-0003-0500-6180

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePretreatment plasma d-dimer has been reported to be a potential prognostic indicator of lung cancer. To determine the prognostic significance of pretreatment d-dimer level in predicting clinical outcomes, such as the overall survival (OS) and progression-free survival (PFS), of patients with small cell lung cancer (SCLC).

methodsA systematic search in PubMed, Web of Science, EMBASE, Cochrane Library, CNKI, SinoMed, Wanfang and VIP databases was performed to identify available studies. The pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were applied to assess the association of pretreatment d-dimer level with prognosis of SCLC patients. All statistical analyses were conducted via the STATA 12.0 version software.

resultsA total of 7 studies involving 964 patients were included in this meta-analysis and all patients were from China. The results showed that elevated pretreatment d-dimer level was significantly correlated with worse OS (HR = 1.90, 95% CI: 1.55-2.34,

conclusionsPretreatment blood concentration of d-dimer may deserve as a reliable factor to predict prognosis of Chinese patients with SCLC. More well-designed prospective studies with large samples are still needed to verify our findings.

Indexed as

BiomarkersFibrin Fibrinogen Degradation ProductsHumansLung NeoplasmsPrognosisProportional Hazards ModelsPublication BiasSmall Cell Lung CarcinomaBiomarkersFibrin Fibrinogen Degradation Productsfibrin fragment Dd-dimermeta-analysisprognosissmall cell lung cancer

Identifiers

PMID33563114
PMCPMC7879000

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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.