Evidence map›Paper›PMID 38328606›Full record

ArticleCancer pathogenesis and therapy2023

Pre-mobilization platelet count predicts stem cell yield during mobilization in patients with multiple myeloma.

Yuan Chen, Shan Gao, Yutong Wang, Minqiu Lu, Bin Chu, Lei Shi, Qiuqing Xiang, Lijuan Fang, Yuehua Ding, Mengzhen Wang and 4 more

Abstract read
In one paragraph

Article in Cancer pathogenesis and therapy, 2023. 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
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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

14 authors.

Yuan ChenHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Shan GaoHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Yutong WangHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Minqiu LuHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Bin ChuHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Lei ShiHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Qiuqing XiangHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Lijuan FangHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Yuehua DingHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Mengzhen WangHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Xi LiuHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Xin ZhaoHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Kai SunHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.
Li BaoHematology Department, Beijing Jishuitan Hospital, Beijing 100035, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Autologous hematopoietic stem cell (HSC) transplantation remains the recommended treatment for eligible patients with multiple myeloma (MM). Increasing the number of transplanted CD34 Methods: We conducted a retrospective study of 110 patients who were newly diagnosed with MM and underwent autologous HSC collection at Beijing Jishuitan Hospital between March 2016 and July 2022. Multiple factors were analyzed using the Mann-Whitney Results: We found that patient age affected stem cell collection significantly; for patients younger than 55 years, the number of CD34+ cells harvested may be ​≥ ​2 ​× ​10 Conclusions: This finding could guide us to predict the approximate number of CD34

Indexed as

Hematopoietic stem cell collectionMultiple myelomaPlatelet count

Identifiers

PMID38328606
PMCPMC10846336

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.