Evidence map›Paper›PMID 30834254›Full record

ArticleBioMed research international2019

Hematologic Markers as Prognostic Factors in Nonmetastatic Esophageal Cancer Patients under Concurrent Chemoradiotherapy.

Yi-Feng Wu, Sung-Chao Chu, Bee-Song Chang, Yi-Tso Cheng, Tso-Fu Wang

Abstract read
In one paragraph

Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Observational
  8. Observational
  9. Review
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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

5 authors.

Yi-Feng WuDepartment of Hematology and Oncology, Buddhist Tzu Chi General Hospital, Hualien, Taiwan.ORCID 0000-0003-1073-9194
Sung-Chao ChuDepartment of Hematology and Oncology, Buddhist Tzu Chi General Hospital, Hualien, Taiwan.
Bee-Song ChangDepartment of Cardiovascular Surgery, Buddhist Tzu Chi General Hospital, Hualien, Taiwan.
Yi-Tso ChengDepartment of Cardiovascular Surgery, Buddhist Tzu Chi General Hospital, Hualien, Taiwan.
Tso-Fu WangDepartment of Hematology and Oncology, Buddhist Tzu Chi General Hospital, Hualien, Taiwan.ORCID 0000-0002-2251-6900

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nonmetastatic esophageal cancer can demonstrate a high local recurrence rate even under the standard treatment. We evaluated platelet counts before and after concurrent chemoradiotherapy (CCRT), neutrophil-to-lymphocyte ratio, and platelet-to-lymphocyte ratio for predicting esophageal cancer prognosis under CCRT. Newly diagnosed patients with esophageal cancer (stages IA-IIIC) who underwent CCRT during January 2013-December 2017 were enrolled. The data were collected retrospectively. Overall survival (OS), time to progressive disease (TPD), and time to metastasis (TM) were recorded for indicating prognosis. Kaplan-Meier curves were plotted and univariate and multivariate analyses were performed. In total, 105 patients were enrolled. The stages of esophageal cancer and surgery were associated with prognosis (i.e., OS, TPD, and TM). Based on TPD and TM, women had better prognosis than men. In the univariate analysis, high pre- and post-CCRT platelet counts (>300,000/

Indexed as

ChemoradiotherapyAdultAgedAged, 80 and overBiomarkers, TumorBlood PlateletsEsophageal NeoplasmsFemaleHumansKaplan-Meier EstimateLymphocyte CountLymphocytesMaleMiddle AgedNeutrophilsPlatelet CountBiomarkers, Tumor

Identifiers

PMID30834254
PMCPMC6374875

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.