Evidence map›Paper›PMID 37782372›Full record

ArticleAnnals of hematology2023

Validation of venous thromboembolism predictive model in hematologic malignancies.

Agnerys López Sacerio, Mara Caridad Tejeda Ramón, Aliuska Morales Helguera, Yunierkis Pérez Castillo, Javier Cruz Rodríguez, Jorge Felix Guerra Rodríguez, Anna Falanga

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In one paragraph

Article in Annals of hematology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 18% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Observational
  2. Review
  3. Review
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

7 authors at 3 institutions in 3 countries.

Agnerys López SacerioHematology Department, Arnaldo Milián University Hospital, Santa Clara, Cuba. alopezsacerio@gmail.com.ORCID http://orcid.org/0000-0001-8020-9186
Mara Caridad Tejeda RamónHematology Department, Arnaldo Milián University Hospital, Santa Clara, Cuba.ORCID http://orcid.org/0000-0003-0006-1527
Aliuska Morales HelgueraChemical Bioactive Center, Central University "Martha Abreu" de Las Villas, Santa Clara, Cuba.ORCID http://orcid.org/0000-0003-4781-547X
Yunierkis Pérez CastilloBio-Chemoinformatics Group and School of Physical and Mathematical Sciences, University of Las Américas, Quito, Ecuador.ORCID http://orcid.org/0000-0002-3710-0035
Javier Cruz RodríguezSurgical Department, Arnaldo Milián University Hospital, Santa Clara, Cuba.ORCID http://orcid.org/0000-0002-7849-4050
Jorge Felix Guerra RodríguezHematology Department, Arnaldo Milián University Hospital, Santa Clara, Cuba.ORCID http://orcid.org/0000-0002-9209-8863
Anna FalangaDepartment of Transfusion Medicine and Hematology, Hospital Papa Giovanni XXIII, Bergamo, Italy.ORCID http://orcid.org/0000-0002-5007-3457
Universidad Central "Marta Abreu" de las Villas (UCLV) · CUOspedale Papa Giovanni XXIII · ITUniversidad de Las Américas · EC

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although several scores stratify venous thromboembolism (VTE) risk in solid tumors, hematologic malignancies (HM) are underrepresented. To develop an internal and external validation of a logistic regression model to predict VTE risk in hospitalized HM patients. Validation of the existing VTE predictive model was performed through a prospective case-control study in 496 hospitalized HM patients between December 2010 and 2020 at the Arnaldo Milián University Hospital, Cuba. The predictive model designed with data from 285 patients includes 5 predictive factors: hypercholesterolemia, tumoral activity, use of thrombogenic drugs, diabetes mellitus, and immobilization. The model was internally validated using bootstrap analysis. External validation was realized in a prospective cohort of 211 HM patients. The predictive model had a 76.4% negative predictive value (NPV) and an 81.7% positive predictive value (PPV) in the bootstrapping validation. The area under curve (AUC) in the bootstrapping set was 0.838. Accuracy was 80.1% and 82.9% in the internal and external validation, respectively. In the external validation, the model produced 89.7% of NPV, 67.7% of PPV, 74.6% of sensitivity, and 86.2% of specificity. The AUC in the external validation was 0.900. VTE predictive model is a reproducible and simple tool with good accuracy and discrimination.

Indexed as

Hematologic NeoplasmsNeoplasmsVenous ThromboembolismCase-Control StudiesHumansRetrospective StudiesRisk AssessmentRisk FactorsHematologic malignancyPrimary preventionRisk assessment modelVenous thromboembolism

Identifiers

PMID37782372
OpenAlexW4387242155

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.