Evidence map›Paper›PMID 35875418›Full record

ArticleClinical Medicine Insights. Oncology2022

Bone-Related Extramedullary Disease in Newly Diagnosed Myeloma Patients is an Independent Poor Prognostic Predictor.

Ying Wang, Aijun Liu, Tingting Xu, Jiahui Yin, Wenming Chen

Abstract read
In one paragraph

Article in Clinical Medicine Insights. Oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Article
  2. Article
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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.

Ying WangDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, P.R. China.ORCID https://orcid.org/0000-0003-4141-3859
Aijun LiuDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, P.R. China.
Tingting XuDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, P.R. China.
Jiahui YinDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, P.R. China.
Wenming ChenDepartment of Hematology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Bone-related extramedullary disease (EMD-B) is mass of clonal plasma cells derived from adjacent bone lesions and has obvious heterogeneities in clinical outcomes. This retrospective study aims to evaluate the treatment outcomes and long-term prognosis of newly diagnosed myeloma patients with EMD-B. Methods: This was a retrospective study conducted in Beijing Chaoyang Hospital from January 1, 2010 to December 31, 2019. Seventy-seven newly diagnosed multiple myeloma patients with EMD-B were selected. Propensity score matching (1:2) was used to match patients with and without EMD-B. After matching, 132 patients without extramedullary disease (non-EMD) were included in the study. All patients received bortezomib-based regimens as induction therapy. Results: After matching, baseline data of the 2 groups were comparable. The Cox regression analysis of patients with EMD-B showed that age, paravertebral lesions, and immunoglobulin D (IgD) type may have adverse effects on survival. Bone-related extramedullary disease at new diagnosis was a risk predictor of survival (hazard ration [HR] = 1.80, 95% confidence interval [CI]: 1.09-2.98, Conclusions: This study demonstrated that newly diagnosed myeloma patients with EMD-B had poor outcomes, which could be improved by ASCT.

Indexed as

autologous stem cell transplantationExtramedullary diseasemultiple myelomapropensity scoreproteasome inhibitor

Identifiers

PMID35875418
PMCPMC9301125

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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.