Evidence map›Paper›PMID 41246111›Full record

ArticleAdvances in hematology2025

A Novel Strategy for Assessing Bone Marrow Plasma Cell Percentage: Development and Internal Validation of a Surrogate Calculation Approach.

Ethan James Gantana, Zivanai Cuthbert Chapanduka

Abstract read
In one paragraph

Article in Advances in hematology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Ethan James GantanaDepartment of Pathology, Stellenbosch University, Cape Town, South Africa, sun.ac.za.ORCID https://orcid.org/0000-0002-0523-8494
Zivanai Cuthbert ChapandukaDepartment of Pathology, Stellenbosch University, Cape Town, South Africa, sun.ac.za.ORCID https://orcid.org/0000-0002-5489-8392

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The differentiation and diagnosis of plasma cell (PC) neoplasms (PCNs) such as multiple myeloma (MM) rely on the quantification of clonal PCs in the bone marrow (BM). For monitoring, the International Myeloma Working Group (IMWG) defines stringent response criteria based on the percentage of BM PC. However, BM biopsies are invasive and painful, and often with sampling variability. This study investigates whether routine biomarkers can predict BM trephine (BMT) PC% using multivariate regression. Methods: A cross-sectional study was conducted at Tygerberg Hospital, South Africa. Data were extracted from the National Health Laboratory Service (NHLS) database. The final dataset included 112 newly diagnosed MM patients with complete biomarker data for training of the partial least squares regression (PLS-R) model. Variables analyzed included SFLC ratio, paraprotein, Hb, calcium, creatinine, and albumin. Statistical methods included correlation analysis, regression modeling, and internal validation. Results: The cohort had a median age of 61 years and a male-to-female ratio of 1:1.5. PLS-R analysis identified significant predictors of BMT PC%, including SFLC ratio, paraprotein, Hb, and serum albumin. The final model equation showed moderate predictive power ( Conclusion: This study provides proof of concept for the use of biochemical markers to predict BMT PC% and offers a less invasive alternative for PC quantification in PCN. Standardization of sampling and measurement of biomarkers is essential for the refinement of these predictive models. Future multicenter studies should include prospective data collection to improve model accuracy and clinical applicability.

Identifiers

PMID41246111
PMCPMC12616256

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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.