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Record W4405039664 · doi:10.1182/blood-2024-207293

Characteristics of Myelodysplastic Syndromes with Idiopathic Pulmonary Fibrosis

2024· article· en· W4405039664 on OpenAlexaff
Inés Zugasti, Samuel Urrutia, Eduardo Edelman Saul, Georgina S. Daher-Reyes, Mohammad Asim Amjad, Jia Wu, Koji Sasaki, Ajay Sheshadri, Guillermo Garcia‐Manero

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineMyelodysplastic syndromesIdiopathic pulmonary fibrosisPulmonary fibrosisInternal medicineFibrosisGastroenterologyLungBone marrow

Abstract

fetched live from OpenAlex

Introduction The co-occurrence of myelodysplastic syndromes (MDS) and idiopathic pulmonary fibrosis (IPF) is highly specific of an underlying short telomere syndrome (STS), most of which harbor a TERT germline mutation. The understanding of germline MDS predisposition is increasing, however, the only evidence in this context is reported by Papiris et al., describing 5 patients co-affected with IPF and MDS. Most STS are diagnosed after the sixth decade, with IPF usually being the primary manifestation. This particular scenario is of relevance, as comorbidities like IPF alongside with other known predispositions may play a crucial role in hematologic malignancy management. The study aims to describe the molecular profile, clinical and pulmonary characteristics, and outcomes of a cohort of 141 patients with MDS and pulmonary fibrosis (PF) diagnosed in our center from November 2008 to February 2022. Methods This retrospective single-center study included patients diagnosed with MDS and PF from November 2008-February 2022. For mutational analysis, 28 or 81-gene NGS panel covering TERT and TERT but no other STS-related genes were used. Responses were assessed using the IWG2023 criteria. Chest CT images and functional respiratory tests at IPF diagnosis were individually reviewed by the Pulmonary Team of our center. Results Of the 141 patients identified with MDS and PF, 75 were diagnosed with IPF, and of those, 61 had available molecular data. The median age at MDS diagnosis was 71 years (52-91), and 75% were male. Fifty-one (84%) had MDS, 2 (4%) MDS/MPN, and 7 (12%) CMML. Based on IPSS-M, 19 (40%) were classified as very high-risk, 10 ( 21%) high-risk, 2 (4%) moderate-high, 4 (9%) moderate-low, 8 (17%) low and 4 (9%) as a very low. CPSS-Mol on the CMML patients stratified 3 (44%), 2 (28%), 2 (28%) to high, intermediate-2, and intermediate-1 risk categories, respectively. Twenty patients (33%) progressed to AML, and 13 (20%) underwent an HSCT. Results from the 81-gene panel, which includes TERT were available in 46 patients, 13 of whom harbored a TERT germinal mutation. This led to an incidence of suspected STS of 28.3% in individuals co-affected with IPF and MDS. Overall Response Rate (ORR) (IWG2023 criteria) was 62.9% (first line), 39.4% (second line), and 50% (third line). The median follow-up of the cohort was 39.01 months, and the median Overall Survival (OS) was 30.6 months (95% CI 22.4 - 48.4, n=61). TERT-mutated patients were diagnosed with MDS younger (median 69 vs. 73 years, p=0.033). Five (36%) of them had MDS-IB2, 3 (21%) MDS-biTP53, and 3 (21%) MDS-SF3B1 and MDS-LB, respectively (none CMML or MDS/MPS). Mutations in TERT were significantly associated with co-mutations in SRSF2 (p=0.043), without differences with other splicing genes. TERT-mutated patients also presented an earlier age of IPF diagnosis (p=0.039) and carried with more severe interstitial lung disease (ILD) (p=0.001). No differences were identified in smoke history, fibrogenic exposure, patterns on CT at IPF diagnosis, pulmonary function tests, or respiratory symptoms. Patients with wildtype TERT did not exhibit any cutaneous (p=0.000), hepatic involvement (p=0.024), nor premature aging signs (p=0.088). First-grade family history was significant for IPF (p=0.003). TERT and wildtype TERT mutated groups received equivalent MDS treatments; no differences were observed in responses. OS was not shorter for TERT-mutated patients (wildtype 29.2 months (95% CI 22.4 - 66.3) vs. TERT-mutated 19.7 months (95% CI 7.9 - NA); p=0.92). However, harboring a TERT mutation conferred a shorter OS only in very-high IPSS-M patients (median OS 20.3 months (95%CI 15.5-NA; n=9) vs. 8 months (95% CI 6.14 - NA, n=5); p=0.038). Patients with TERT mutation died significantly more of non-infectious respiratory causes (p=0.005). Univariate analysis for OS was significant for IPSS-M (p=0.000), 2022 WHO classification (p=0.001), and TP53 mutation (p=0.000). TERT mutations and pulmonary characteristics had no impact on survival. Conclusion The incidence of suspected STS in patients with concomitant MDS and IPF is 28.3%. MDS and IPF present at younger age in those with TERT mutation and may impact survival if they present with high-risk MDS. Larger cohorts are needed to validate these results. Nevertheless, this study has profound implications for clinical decisions, family counseling, and early advice on avoiding smoke and other potential fibrogenic exposures.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.008
GPT teacher head0.227
Teacher spread0.218 · 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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