Evidence map›Paper›PMID 37155023›Full record

ArticleJournal of clinical immunology2023

Nomogram for Predicting Early Mortality after Umbilical Cord Blood Transplantation in Children with Inborn Errors of Immunity.

Ping Wang, Chao Liu, Zhongling Wei, Wenjin Jiang, Hua Sun, Yuhuan Wang, Jia Hou, Jinqiao Sun, Ying Huang, Hongsheng Wang and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of clinical immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

15 authors.

Ping WangDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.ORCID 0000-0003-0286-4083
Chao LiuYidu Cloud Technology Inc, Beijing, 100083, China.ORCID 0000-0002-6708-4654
Zhongling WeiDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Wenjin JiangDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Hua SunDepartment of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Yuhuan WangDepartment of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Jia HouDepartment of Clinical Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Jinqiao SunDepartment of Clinical Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Ying HuangDepartment of Gastroenterology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Hongsheng WangDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Yao WangYidu Cloud Technology Inc, Beijing, 100083, China.
Xinjun HeYidu Cloud Technology Inc, Beijing, 100083, China.
Xiaochuan WangDepartment of Clinical Immunology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Xiaowen QianDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China.
Xiaowen ZhaiDepartment of Hematology/Oncology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, 201102, China. xwzhai@fudan.edu.cn.ORCID 0000-0002-3505-0302

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePediatric patients with inborn errors of immunity (IEI) undergoing umbilical cord blood transplantation (UCBT) are at risk of early mortality. Our aim was to develop and validate a prediction model for early mortality after UCBT in pediatric IEI patients based on pretransplant factors.

methodsData from 230 pediatric IEI patients who received their first UCBT between 2014 and 2021 at a single center were analyzed retrospectively. Data from 2014-2019 and 2020-2021 were used as training and validation sets, respectively. The primary outcome of interest was early mortality. Machine learning algorithms were used to identify risk factors associated with early mortality and to build predictive models. The model with the best performance was visualized using a nomogram. Discriminative ability was measured using the area under the curve (AUC) and decision curve analysis.

resultsFifty days was determined as the cutoff for distinguishing early mortality in pediatric IEI patients undergoing UCBT. Of the 230 patients, 43 (18.7%) suffered early mortality. Multivariate logistic regression with pretransplant albumin, CD4 (absolute count), elevated C-reactive protein, and medical history of sepsis showed good discriminant AUC values of 0.7385 (95% CI, 0.5824-0.8945) and 0.827 (95% CI, 0.7409-0.9132) in predicting early mortality in the validation and training sets, respectively. The sensitivity and specificity were 0.5385 and 0.8154 for validation and 0.7667 and 0.7705 for training, respectively. The final model yielded net benefits across a reasonable range of risk thresholds.

conclusionThe developed nomogram can predict early mortality in pediatric IEI patients undergoing UCBT.

Indexed as

Cord Blood Stem Cell TransplantationHematopoietic Stem Cell TransplantationSepsisChildHumansNomogramsRetrospective StudiesInborn errors of immunitynomogrampediatric patientsumbilical cord blood transplantation

Identifiers

PMID37155023
PMCPMC10354135

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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.