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Record W3213661499 · doi:10.1182/blood-2021-149855

The Impact of Oral Hypoglycemics and Statins on Outcomes in Myelodysplastic Syndromes

2021· article· en· W3213661499 on OpenAlexaffabout
Eugène Brailovski, Qing Li, Ning Liu, Brian Leber, Dina Khalaf, Mitchell Sabloff, Grace Christou, Karen Yee, Lisa Chodirker, Anne Parmentier, Mohammed Siddiqui, Alexandre Mamedov, Liying Zhang, Ying Liu, Craig C. Earle, Matthew C. Cheung, Nicole Mittman, Rena Buckstein, Lee Mozessohn

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsHealth Sciences CentrePrincess Margaret Cancer CentreOttawa HospitalSunnybrook Health Science CentreJuravinski Cancer CentreInstitute for Clinical Evaluative SciencesUniversity of Toronto
Fundersnot available
KeywordsMedicineProportional hazards modelHazard ratioDisease registryInternal medicinePopulationObservational studyDiseaseConfidence intervalEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Background: Observational studies suggest an anti-neoplastic effect associated with statins, metformin, dipeptidyl peptidase-4 inhibitors (DPP4i), while sulfonylureas may have a neutral or detrimental effect. The aim of this study was to determine the impact of these medications in patients with myelodysplastic syndromes (MDS). Methods: A prospective Canadian national registry containing disease and patient-related characteristics enrolled patients with MDS between January 1, 2006 and December 31, 2019. The Ontario subset of the registry was linked to population-based health system administrative databases. The primary outcome was the impact of statin/oral hypoglycemic medication exposure on overall survival (OS). Cumulative medication exposure (in months) was evaluated from 1-year prior to registry enrollment to date of death or end of follow-up (March 31, 2020) as a time-varying covariate. Cox regression analysis controlling for comorbid disease burden (Aggregated Diagnosis Groups; ADG) and sociodemographic factors (age, sex, rurality, income quintile) examined the relationship between medication exposure and OS. Our secondary outcome was leukemia-free survival (LFS), in which cause-specific hazard model was used to evaluate the association between medication exposure and LFS, taking death as the competing event. Results: In total, 533 patients aged >66 years were included (395 lower-risk IPSS, 130 higher-risk IPSS). The median age was 76.0 years (IQR 72.0-81.0), 65.1% were male and 9% had secondary MDS. The mean follow-up was 2.6 years (SD+ 2.4). Starting one year prior to registry enrollment and until the end of follow-up, 49.3% used a statin, 18.9% used metformin, 9.0% used a sulfonylurea and 6.4% used a DPP4i. On univariate analysis, we identified an improved OS in the lower-risk IPSS group using DPP4i (HR 0.98, 95% CI 0.95-1.00, p=0.05), while there was no significant difference in the higher-risk IPSS group for users of DPP4i (HR 1.03, 95% CI 0.99-1.07, p=0.21). In both lower and higher-risk IPSS groups, there was no difference in mortality for statins (HR 1.00, CI 1.00-1.01, p=0.93), metformin (HR 1.00, CI 0.99-1.01, p=0.81) and sulfonylureas (HR 1.00, CI 0.99-1.02, p=0.43). Increased age (p<0.01), higher Charlson score (p<0.01), greater comorbid disease burden (p=0.04), higher-risk disease (IPSS p<0.01, IPSS-R p<0.01), history of heart failure (p<0.01) and hypertension (p=0.01) were predictive of inferior OS on univariate analysis. There was no association between exposure to the studied medications and LFS in the lower-risk group: metformin (HR 0.99, 95% CI 0.96-1.02, p=0.32), sulfonylureas (HR 0.99, 95% CI 0.94-1.04, p=0.57) and statins (HR 0.99, 95% CI 0.98-1.01, p=0.41). The impact of DPP4i exposure on LFS could not be assessed in lower risk disease due to infrequent events. There was also no association in the higher-risk IPSS group: DPP4i (HR 1.06, 95% CI 1.00-1.12, p=0.05), metformin (HR 1.02, CI 0.98-1.05, p=0.34), sulfonylureas (HR 1.04, 1.00-1.08, p=0.07) and statins (HR 1.02, 1.00-1.04, p=0.12). On multivariable analysis in the lower-risk IPSS group, no associations were identified between the use of medications of interest and all-cause mortality: DPP4i (HR 0.98, 95% CI 0.95-1.00, p=0.06), metformin (HR 1.00, 95% CI 0.99-1.01, p=0.99), sulfonylurea (HR 1.00, 95% CI 0.99-1.02, p=0.65) and statins (HR 1.00, 95% CI 0.99-1.00, p=0.56). In those with known cause of death, the main cause of death amongst DPP4i users was infection (35.7%) followed by acute myeloid leukemia (AML) (21.4%) and cardiac disease (14.3%), while the main cause of death in patients not on DPP4i was progressive MDS (23.2%) followed by AML (22.5%) and infections (22.1%). Conclusions: DPP4i may confer a survival benefit in lower-risk but not higher-risk MDS that cannot be explained by a reduction in cardiovascular deaths. Metformin, sulfonylureas and statins showed no impact on OS and LFS in lower and higher-risk groups. Improved bone marrow function through exosome inhibition and increased granulocyte-macrophage colony stimulating activity is the suggested mechanism for the potential survival benefit with DPP4i in lower-risk IPSS patients. This represents the first study evaluating the impact of oral hypoglycemic mediations and statins in a large cohort of patients with MDS. Further prospective studies are required to further evaluate the effects of DPP4i in MDS. Disclosures Leber: AMGEN: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Pfizer: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Abbvie: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; TaiHo: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Otsuka: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Astellas: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Jazz: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Khalaf: Pfizer: Honoraria; Novartis: Honoraria; Paladin: Honoraria. Sabloff: TaiHo: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; BMS: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Jaxx: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; ROCHE: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees. Yee: Astex: Membership on an entity's Board of Directors or advisory committees, Research Funding; Geron: Research Funding; Janssen: Research Funding; Jazz: Research Funding; MedImmune: Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Onconova: Research Funding; Tolero: Research Funding; AbbVie: Honoraria; Bristol-Myers Squibb/Celgene: Membership on an entity's Board of Directors or advisory committees; Otsuka: Membership on an entity's Board of Directors or advisory committees; Paladin: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Shattuck Labs: Membership on an entity's Board of Directors or advisory committees; TaiHo: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Genentech: Research Funding; F. Hoffmann La Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Forma Therapeutics: Research Funding. Buckstein: Celgene: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; TAIHO: Research Funding; Otsuka: Research Funding.

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 score0.044
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.362
Teacher spread0.324 · 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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Citations1
Published2021
Admission routes2
Has abstractyes

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