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Bone Marrow Fibrosis In Patients With Multiple Myeloma: A New Prognostic Factor For Survival?

2013· article· en· W2980094467 on OpenAlexaff
Tinna Hallgrimsdottir, Anna Porwit, Magnus Björkholm, Eva Rossmann, Hlíf Steingrímsdóttir, Sigrún H. Lund, Sigurður Y. Kristinsson

Bibliographic record

VenueBlood · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineBone marrowMultiple myelomaFibrosisProportional hazards modelIncidence (geometry)Internal medicineGastroenterologySurvival analysisPathologyStage (stratigraphy)SurgeryBiology

Abstract

fetched live from OpenAlex

Abstract Introduction Multiple myeloma (MM) is characterized by the proliferation of plasma cells in the bone marrow and a secretion of monoclonal immunoglobulins. Survival in MM is very variable and multiple factors are known to influence prognosis such as age, ISS stage, and genetic abnormalities. Fibrosis can be found in the bone marrow of MM patients but the literature reporting the incidence of fibrosis and its effect on prognosis is very limited. The purpose of this study was to estimate the incidence of bone marrow fibrosis in MM patients and its effect on survival. Materials and methods Data was collected at the Karolinska University Hospital in Solna, Sweden and information obtained from the hospital's records. We gathered information on all patients diagnosed with MM between 2003 and 2011. All bone marrow reports were reviewed and the presence of bone marrow fibrosis (evaluated using reticulin staining) at diagnosis was recorded. Fibrosis was graded as 1 (mild), 2 (significant) and 3 (advanced), in accordance with WHO 2008 criteria. Patients with fibrosis were paired with patients without fibrosis (matched by sex, birth year, and year of diagnosis). Survival comparing MM patients with and without fibrosis was evaluated using Kaplan-Meier estimate and Cox regression model. Results A total of 586 individuals, 327 males and 259 females, were diagnosed with MM at the Karolinska University Hospital, Solna during 2003 – 2011. Evidence of bone marrow fibrosis was noted in 223 (38%) patients at diagnosis, and 175 had fibrosis grade 1, 33 grade 2, and 15 grade 3. No significant difference was observed between males (N = 135) and females (N = 88) (p = 0.085). Mean age at diagnosis was significantly lower for patients with fibrosis (67.1 years) than in patients without fibrosis (69.7 years) (p = 0.013). Compared with paired patients without fibrosis (N = 217), patients with fibrosis had significantly worse survival (Figure), being 5.0 years vs. 4.4 years, respectively (relative risk (RR)=1.3, 95% confidence interval (CI) 1.00-1.70; p= 0.049). The difference was greatest in male patients and patients younger than 65 years at diagnosis. Survival was worse in patients with advanced fibrosis, 4.5 (95% CI 3.6-6.4) years for grade 1 fibrosis, and 3.0 (95% CI 1.6-NA) years for higher degree of fibrosis. Conclusion In this study, based on almost 600 patients with MM we show that bone marrow fibrosis is common at diagnosis (38%). Importantly, our findings show that the presence of fibrosis was associated with inferior survival. More studies are needed regarding the underlying causes for these findings, including treatment response, treatment-related complications and relation to other known prognostic factors. Disclosures: No relevant conflicts of interest to declare.

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)0.003
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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

Citations10
Published2013
Admission routes1
Has abstractyes

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