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Record W3012669854 · doi:10.1093/jncics/pkz104

A Prospective Study of Circulating Chemokines and Angiogenesis Markers and Risk of Multiple Myeloma and Its Precursor

2019· article· en· W3012669854 on OpenAlexfundno aff
Jonathan N. Hofmann, Ola Landgren, Rebecca Landy, Troy J. Kemp, Loredana Santo, Charlene M. McShane, Joseph J. Shearer, Qing Lan, Nathaniel Rothman, Ligia A. Pinto, Ruth M. Pfeiffer, Allan Hildesheim, Hormuzd A. Katki, Mark P. Purdue

Bibliographic record

VenueJNCI Cancer Spectrum · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsnot available
FundersNational Cancer InstituteNational Institutes of HealthQueen's University BelfastQueen's UniversityCancer Research UK
KeywordsMedicineMonoclonal gammopathy of undetermined significanceInternal medicineProspective cohort studyOncologyMultiple myelomaOdds ratioAngiogenesisBiomarkerImmunologyGastroenterologyMonoclonalAntibodyMonoclonal antibody

Abstract

fetched live from OpenAlex

Abstract Background Experimental and clinical studies have implicated certain chemokines and angiogenic cytokines in multiple myeloma (MM) pathogenesis. To investigate whether systemic concentrations of these markers are associated with future MM risk and progression from its precursor, monoclonal gammopathy of undetermined significance (MGUS), we conducted a prospective study within the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Methods We measured concentrations of 45 immunologic and pro-angiogenic markers in sera from 241 MM case patients, 441 participants with nonprogressing MGUS, and 258 MGUS-free control participants using Luminex-based multiplex assays and enzyme-linked immunosorbent assays. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression. We also evaluated absolute risk of progression using weighted Kaplan-Meier estimates. All statistical tests were two-sided. Results Prediagnostic levels of six markers were statistically significantly elevated among MM case patients compared with MGUS-free control participants using a false discovery rate of 10% (EGF, HGF, Ang-2, CXCL12, CCL8, and BMP-9). Of these, three angiogenesis markers were associated with future progression from MGUS to MM: EGF (fourth vs first quartile: OR = 3.01, 95% CI = 1.61 to 5.63, Ptrend = .00028), HGF (OR = 2.59, 95% CI = 1.33 to 5.03, Ptrend = .015), and Ang-2 (OR = 2.14, 95% CI = 1.15 to 3.98, Ptrend = .07). A composite angiogenesis biomarker score substantially stratified risk of MGUS progression to MM beyond established risk factors for progression, particularly during the first 5 years of follow-up (areas under the curve of 0.71 and 0.64 with and without the angiogenesis marker score, respectively). Conclusions Our prospective findings provide new insights into mechanisms involved in MM development and suggest that systemic angiogenesis markers could potentially improve risk stratification models for MGUS patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.287
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2019
Admission routes1
Has abstractyes

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