Evidence map›Paper›PMID 30599001›Full record

ArticleBioMed research international2018

Peripheral Blood Lymphocyte-to-Monocyte Ratio as a Useful Prognostic Factor in Newly Diagnosed Multiple Myeloma.

Ying Tian, Yue Zhang, Wan-Qiu Zhu, Xiao-Lei Chen, He-Bing Zhou, Wen-Ming Chen

Abstract read
In one paragraph

Article in BioMed research international, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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

Ying TianDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-7682-6907
Yue ZhangDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-8017-6596
Wan-Qiu ZhuDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-9595-0425
Xiao-Lei ChenDepartment of Hematology, Beijing Lu-He Hospital, Capital Medical University, Beijing, China.
He-Bing ZhouDepartment of Hematology, Beijing Lu-He Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-7486-7585
Wen-Ming ChenDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-9070-9280

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The survival of individuals with tumors may be predicted by the peripheral blood lymphocyte-to-monocyte ratio (LMR) upon diagnosis in recent studies. For patients with multiple myeloma (MM) in the era of novel agents, the prognostic significance of LMR remains unclear. In this study, the prognostic impact of LMR is evaluated by 285 patients with MM who are treated with proteasome inhibitor and/or immunomodulatory drug. LMR is a proven predictor of survival using the receiver operating characteristic curve, with 4.2 as the cutoff point. Patients with LMR ≤ 4.2 at diagnosis had poorer overall survival (OS) and progression-free survival (PFS) than those with LMR > 4.2. In addition, multivariate analysis showed that LMR less than 4.2 is an independent predictor for the OS (hazard ratio [HR]: 1.703; 95% confidence interval [CI]: 1.020-2.842;

Indexed as

AgedDisease-Free SurvivalFemaleHumansLeukocytes, MononuclearLymphocyte CountLymphocytesMaleMonocytesMultiple MyelomaMultivariate AnalysisPrognosisProportional Hazards Models

Identifiers

PMID30599001
PMCPMC6287166

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.